﻿FN Clarivate Analytics Web of Science
VR 1.0
PT J
AU Imakumbili, MLE
   Semu, E
   Semoka, JMR
   Abass, A
   Mkamilo, G
AF Imakumbili, Matema L. E.
   Semu, Ernest
   Semoka, Johnson M. R.
   Abass, Adebayo
   Mkamilo, Geoffrey
TI Managing cassava growth on nutrient poor soils under different water
   stress conditions
SO HELIYON
LA English
DT Article
DE NPK fertilizers; Drought stress; New leaf formation; Crop water use;
   Plant growth; Leaf size; Nutrient supply; Climate change adaptation; Pot
   experiment; Three-way interactions
ID POTASSIUM FERTILIZER; YIELD; DROUGHT; PHYSIOLOGY; TILLAGE; DEFICIT;
   PLANT
AB Nitrogen (N), phosphorus (P) and potassium (K) fertiliser application, was able to counteract growth reductions, in cassava cultivated on nutrient poor soils, under one water stress condition. It however remains to be seen, whether N, P and K fertiliser application, would produce similar results, across different water stress conditions. A study was therefore conducted to determine how N, P and K fertiliser application, would influence cassava growth on nutrient poor soils, under various water stress conditions. Effects on new leaf formation and leaf size were also investigated. The study was a 2x3x4 factorial pot experiment, in a randomised complete block design. It included: two cassava varieties, three water stress levels and four fertiliser treatments. The water stress levels kept some plants watered at field capacities of 30% (severe water stress), 60% (mild water stress) and 100% (zero water stress). The fertiliser treatments consisted of a control (no fertiliser), a sole K fertiliser treatment (25 mg K/kg), a moderate N, P and K fertiliser treatment (25 mg N + 5 mg P + 25 mg K/kg) and a high N, P and K fertiliser treatment (50 mg N + 13 mg P + 50 mg K/kg). All data were analysed using the analysis of variance. Cassava growth was assessed by monitoring changes in the dry shoot mass of cassava plants. High and moderate N, P and K fertiliser application, produced cassava plants with higher and similar dry shoot masses, under mild water stress (10.5 g/plant, SE = 0.6 and 9.0 g/plant, SE = 0.6, respectively). High N, P and K fertiliser application, however gave cassava the highest dry shoot mass, under severe water stress (7.9 g/plant, SE = 0.4). Relatively high cassava growth was consistently achieved with high N, P and K fertiliser application, across all water stress conditions.
C1 [Imakumbili, Matema L. E.; Semu, Ernest; Semoka, Johnson M. R.] Sokoine Univ Agr, Dept Soils & Geol Sci, Morogoro, Tanzania.
   [Abass, Adebayo] Int Inst Trop Agr, Dar Es Salaam, Tanzania.
   [Mkamilo, Geoffrey] Naliendele Agr Res Inst, Roots & Tubers Dept, Mtwara, Tanzania.
C3 Sokoine University of Agriculture
RP Imakumbili, MLE (corresponding author), Sokoine Univ Agr, Dept Soils & Geol Sci, Morogoro, Tanzania.
EM imakumbili@gmail.com
RI Imakumbili, Matema/W-1755-2019
FU Alliance for a Green Revolution in Africa (AGRA) [2009 SHP 027]; Bill
   and Melinda Gates Foundation [OPP48790]
FX This work was supported by the Alliance for a Green Revolution in Africa
   (AGRA) (2009 SHP 027) and by the Bill and Melinda Gates Foundation
   (OPP48790) .
CR Adekayode FO, 2009, J FOOD AGRIC ENVIRON, V7, P279
   Alves AAC, 2004, ANN BOT-LONDON, V94, P605, DOI 10.1093/aob/mch179
   Alves AAC, 2000, CROP SCI, V40, P131, DOI 10.2135/cropsci2000.401131x
   Alves Alfredo Augusto Cunha, 2001, P67, DOI 10.1079/9780851995243.0067
   [Anonymous], 1997, SOILS OUR ENV
   [Anonymous], 1990, NIFTAL
   [Anonymous], 2005, CONTAINER GROWN EXPT
   [Anonymous], 2014, ROUTLEDGE
   [Anonymous], OFF J EUR UNION
   Bacon M., 2009, Water-use efficiency in plant biology
   Brouwer C, 1985, IRRIGATION WATER MAN
   Cadavid LF, 1998, FIELD CROP RES, V57, P45, DOI 10.1016/S0378-4290(97)00114-7
   Cakmak I, 2005, J PLANT NUTR SOIL SC, V168, P521, DOI 10.1002/jpln.200420485
   Chua MF, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10081103
   COCK JH, 1979, CROP SCI, V19, P271, DOI 10.2135/cropsci1979.0011183X001900020025x
   Cruz JL, 2016, SCI HORTIC-AMSTERDAM, V210, P122, DOI 10.1016/j.scienta.2016.07.012
   Daoud B, 2020, SCI HORTIC-AMSTERDAM, V272, DOI 10.1016/j.scienta.2020.109562
   De Pauw E., 1984, GCSURT047NET MIN AGR GCSURT047NET MIN AGR
   De Tafur SM, 1997, PHOTOSYNTHETICA, V34, P233, DOI 10.1023/A:1006892607834
   Díaz-Zorita M, 2000, SOIL TILL RES, V54, P11, DOI 10.1016/S0167-1987(99)00100-2
   Silva PPD, 2019, EUPHYTICA, V215, DOI 10.1007/s10681-019-2399-0
   El-Sharkawy Mabrouk A., 2007, Braz. J. Plant Physiol., V19, P257, DOI 10.1590/S1677-04202007000400003
   El-Sharkawy MA, 2006, PHOTOSYNTHETICA, V44, P481, DOI 10.1007/s11099-006-0063-0
   ELSHARKAWY MA, 1987, PLANT SOIL, V100, P345, DOI 10.1007/BF02370950
   Fernandes AM, 2017, J PLANT NUTR, V40, P2785, DOI 10.1080/01904167.2017.1382520
   Fukuda W.M.G., 2010, Selected Morphological and Agronomic Descriptors for the Characterization of Cassava
   Gomez K. A., 1984, Statistical procedures for agricultural research
   Gregory P.J., 2004, Water use efficiency in plant biology, P142
   Gregory PJ, 1997, PHILOS T ROY SOC B, V352, P987, DOI 10.1098/rstb.1997.0077
   Gutiérrez-Boem FH, 1999, PLANT SOIL, V207, P87
   Holmes E.B., 1979, P 5 S INT SOC TROP R P 5 S INT SOC TROP R, P487
   Howeler R., 2014, Sustainable Soil and Crop Management of Cassava in Asia
   Howeler R.H., 2011, CASSAVA HDB REFERENC
   Howeler Reinhardt H., 2001, P115, DOI 10.1079/9780851995243.0115
   Imakumbili M.L.E., 2019, MAKING WATER STRESS
   Imakumbili M.L.E, DATA CHANGES CASSAVA, P2021
   Imakumbili MLE, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0228641
   Jákli B, 2016, J PLANT NUTR SOIL SC, V179, P733, DOI 10.1002/jpln.201600340
   Moberg J.P., 2001, Soil Analysis Manual
   Motsara M., 2008, GUIDE LAB ESTABLISHM
   Ngugi K., 2013, J RENEW AGR, V1, P77
   Oroka F.O, 2016, J NAT SCI RES, V6, P86
   Ortiz-Bobea A, 2021, NAT CLIM CHANGE, V11, P306, DOI 10.1038/s41558-021-01000-1
   Otoo J.A, 1996, RAPID MULTIPLICATION RAPID MULTIPLICATION
   Payne WA, 1997, AGRON J, V89, P481, DOI 10.2134/agronj1997.00021962008900030019x
   Phocaides A., 2007, Handbook on Pressurized Irrigation Techniques, Food and Agricultural Organization of the United Nations
   Roberts M. J., 1993, PHOTOSYNTHESIS PRODU
   Samarah NH, 2005, AGRON SUSTAIN DEV, V25, P145, DOI 10.1051/agro:2004064
   Shan ZY, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-35711-x
   Shaxson F., 2003, FAO SOILS B, V79, P00100
   Soil Survey Division Staff, 2017, AGR HDB, V18
   Somasegaran P., 2012, Handbook for Rhizobia: Methods in Legume-Rhizobium Technology
   Srihawong W., 2015, Kasetsart Journal, Natural Science, V49, P844
   Temegne N. C., 2017, J EXP AGR INT, V16, P1
   Vandegeer R, 2013, FUNCT PLANT BIOL, V40, P195, DOI 10.1071/FP12179
   Veldkamp W.J, 2001, ZONATION INTEGRATED ZONATION INTEGRATED, VI
NR 56
TC 12
Z9 12
U1 1
U2 15
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
EI 2405-8440
J9 HELIYON
JI Heliyon
PD JUN
PY 2021
VL 7
IS 6
AR e07331
DI 10.1016/j.heliyon.2021.e07331
EA JUN 2021
PG 10
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA TK9NG
UT WOS:000674481000017
PM 34195433
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Klaus, VH
   Kiehl, K
AF Klaus, Valentin H.
   Kiehl, Kathrin
TI A conceptual framework for urban ecological restoration and
   rehabilitation
SO BASIC AND APPLIED ECOLOGY
LA English
DT Article
DE Urban ecosystem; Novel ecosystem; Hybrid ecosystem; Restoration target;
   Reference system; Urban grassland; Urban woodland; Urban greenspace;
   Native species; Biodiversity
ID PLANT-SPECIES RICHNESS; ECOSYSTEM SERVICES; GREEN SPACE; RIVER
   RESTORATION; BIODIVERSITY; CONSERVATION; MANAGEMENT; LAND; VEGETATION;
   ENVIRONMENTS
AB Urban greenspace has gained considerable attention during the last decades because of its relevance to wildlife conservation, human welfare, and climate change adaptation. Biodiversity loss and ecosystem degradation worldwide require the formation of new concepts of ecological restoration and rehabilitation aimed at improving ecosystem functions, services, and biodiversity conservation in cities. Although relict sites of natural and semi-natural ecosystems can be found in urban areas, environmental conditions and species composition of most urban ecosystems are highly modified, inducing the development of novel and hybrid ecosystems. A consequence of this ecological novelty is the lack of (semi-) natural reference systems available for defining restoration targets and assessing restoration success in urban areas. This hampers the implementation of ecological restoration in cities. In consideration of these challenges, we present a new conceptual framework that provides guidance and support for urban ecological restoration and rehabilitation by formulating restoration targets for different levels of ecological novelty (i. e., historic, hybrid, and novel ecosystems). To facilitate the restoration and rehabilitation of novel urban ecosystems, we recommend using established species-rich and well-functioning urban ecosystems as reference. Such urban reference systems are likely to be present in many cities. Highlighting their value in comparison to degraded ecosystems can stimulate and guide restoration initiatives. As urban restoration approaches must consider local history and site conditions, as well as citizens' needs, it may also be advisable to focus the restoration of strongly altered urban ecosystems on selected ecosystem functions, services and/or biodiversity values. Ecosystem restoration and rehabilitation in cities can be either relatively inexpensive or costly, but even expensive measures can pay off when they effectively improve ecosystem services such as climate change mitigation or recreation. Successful re-shaping and re-thinking of urban greenspace by involving citizens and other stakeholders will help to make our cities more sustainable in the future. (C) 2021 The Author(s). Published by Elsevier GmbH on behalf of Gesellschaft fur Okologie.
C1 [Klaus, Valentin H.] Swiss Fed Inst Technol, Inst Agr Sci, Univ Str 2, CH-8092 Zurich, Switzerland.
   [Kiehl, Kathrin] Osnabruck Univ Appl Sci, Oldenburger Landstr 24, D-49090 Osnabruck, Germany.
C3 Swiss Federal Institutes of Technology Domain; ETH Zurich
RP Klaus, VH (corresponding author), Swiss Fed Inst Technol, Inst Agr Sci, Univ Str 2, CH-8092 Zurich, Switzerland.
EM valentin.klaus@usys.ethz.ch
RI Klaus, Valentin H./JBJ-7038-2023
OI Klaus, Valentin H./0000-0002-7469-6800; Kiehl,
   Kathrin/0000-0003-3931-187X
CR Anderson EC, 2021, AMBIO, V50, P695, DOI 10.1007/s13280-020-01383-z
   [Anonymous], 2013, 312 SIA
   [Anonymous], 2004, The SER International Primer on Ecological Restoration
   Aronson MFJ, 2017, FRONT ECOL ENVIRON, V15, P189, DOI 10.1002/fee.1480
   Aronson MFJ, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.3330
   Baldwin Andrew H., 2004, Urban Ecosystems, V7, P125, DOI 10.1023/B:UECO.0000036265.86125.34
   Barnes MR, 2018, URBAN FOR URBAN GREE, V29, P284, DOI 10.1016/j.ufug.2017.12.008
   Bernhardt ES, 2007, FRESHWATER BIOL, V52, P738, DOI 10.1111/j.1365-2427.2006.01718.x
   Bonthoux S, 2014, LANDSCAPE URBAN PLAN, V132, P79, DOI 10.1016/j.landurbplan.2014.08.010
   Bretzel F, 2016, URBAN FOR URBAN GREE, V20, P428, DOI 10.1016/j.ufug.2016.10.008
   Bullock JM, 2011, TRENDS ECOL EVOL, V26, P541, DOI 10.1016/j.tree.2011.06.011
   Caspersen OH, 2010, URBAN FOR URBAN GREE, V9, P101, DOI 10.1016/j.ufug.2009.06.007
   Catalano C, 2018, ECOL ENG, V115, P15, DOI 10.1016/j.ecoleng.2018.01.006
   Chou RJ, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8111159
   Clarkson BD, 2016, ECOL MANAG RESTOR, V17, P180, DOI 10.1111/emr.12229
   De Valck J, 2019, ECOSYST SERV, V35, P139, DOI 10.1016/j.ecoser.2018.12.006
   Dearborn DC, 2010, CONSERV BIOL, V24, P432, DOI 10.1111/j.1523-1739.2009.01328.x
   Derkzen ML, 2017, CURR OPIN ENV SUST, V29, P32, DOI 10.1016/j.cosust.2017.10.001
   Dettmar J., 2005, PROJECT IND FORESTS, P276
   Durka W, 2017, J APPL ECOL, V54, P116, DOI 10.1111/1365-2664.12636
   EEA ~ European Environment Agency, 2016, 262016 EEA
   Elmqvist T, 2015, CURR OPIN ENV SUST, V14, P101, DOI 10.1016/j.cosust.2015.05.001
   F_ahser L., 2013, BFN-SKR, V334, P87
   Faeth SH, 2011, ANN NY ACAD SCI, V1223, P69, DOI 10.1111/j.1749-6632.2010.05925.x
   Fischer LK, 2020, CONSERV LETT, V13, DOI 10.1111/conl.12718
   Fischer LK, 2018, GLOBAL ENVIRON CHANG, V49, P35, DOI 10.1016/j.gloenvcha.2018.02.001
   Fischer LK, 2013, BIOL CONSERV, V159, P119, DOI 10.1016/j.biocon.2012.11.028
   FLL ~ Landscape Development and Landscaping Research Society e.V, 2018, GREEN ROOF GUID GUID, V6th ed.
   Francis RA, 2011, J ENVIRON MANAGE, V92, P1429, DOI 10.1016/j.jenvman.2011.01.012
   Gerner NV, 2018, ECOSYST SERV, V30, P327, DOI 10.1016/j.ecoser.2018.03.020
   Grote R, 2016, FRONT ECOL ENVIRON, V14, P543, DOI 10.1002/fee.1426
   Haase D, 2008, NAT CULT, V3, P1, DOI 10.3167/nc.2008.030101
   Hejkal J, 2017, URBAN ECOSYST, V20, P511, DOI 10.1007/s11252-016-0611-8
   Higgs E, 2017, RESTOR ECOL, V25, P8, DOI 10.1111/rec.12410
   Hobbs RJ, 2009, TRENDS ECOL EVOL, V24, P599, DOI 10.1016/j.tree.2009.05.012
   Hobbs RJ, 2006, GLOBAL ECOL BIOGEOGR, V15, P1, DOI 10.1111/j.1466-822x.2006.00212.x
   Jerome G, 2019, URBAN FOR URBAN GREE, V40, P174, DOI 10.1016/j.ufug.2019.04.001
   Jim CY, 2010, LAND USE POLICY, V27, P662, DOI 10.1016/j.landusepol.2009.08.027
   Johnson LR, 2019, URBAN FOR URBAN GREE, V41, P85, DOI 10.1016/j.ufug.2019.02.008
   Kausch E., 2012, European Journal of Turfgrass Science, V43, P43
   Keeler BL, 2019, NAT SUSTAIN, V2, P29, DOI 10.1038/s41893-018-0202-1
   Kenny J., 2019, ST LOUIS REV 0725
   Kiehl K., 2021, URBAN SERVICES ECOSY
   Kiehl K, 2019, RENATURIERUNGS OKOLO, P389
   Kiehl K, 2010, BASIC APPL ECOL, V11, P285, DOI 10.1016/j.baae.2009.12.004
   Klaus VH, 2013, RESTOR ECOL, V21, P665, DOI 10.1111/rec.12051
   Kollmann J., 2019, NEUARTIGE OKOSYSTEME, P435
   Kövendi-Jakó A, 2019, APPL VEG SCI, V22, P138, DOI 10.1111/avsc.12410
   Kowarik I, 2005, WILD URBAN WOODLANDS: NEW PERSPECTIVES FOR URBAN FORESTRY, P287, DOI 10.1007/3-540-26859-6_18
   Kowarik I, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11226318
   Kowarik I, 2011, ENVIRON POLLUT, V159, P1974, DOI 10.1016/j.envpol.2011.02.022
   Lampinen J, 2021, BASIC APPL ECOL, V50, P119, DOI 10.1016/j.baae.2020.10.006
   Landolt E, 2001, VIERTELJAHRESCHRIFT, V146, P41
   Latz Peter., 2017, RUST RED LANDSCAPE P
   Lin BB, 2015, BASIC APPL ECOL, V16, P189, DOI 10.1016/j.baae.2015.01.005
   Lindemann-Matthies P, 2018, WEB ECOL, V18, P121, DOI 10.5194/we-18-121-2018
   Liu H, 2017, ENVIRON EARTH SCI, V76, DOI 10.1007/s12665-017-6652-3
   Liu ZF, 2014, LANDSCAPE ECOL, V29, P763, DOI 10.1007/s10980-014-0034-y
   Lososová Z, 2012, GLOBAL ECOL BIOGEOGR, V21, P545, DOI 10.1111/j.1466-8238.2011.00704.x
   Lundholm J.T., 2006, URB HABITAT, V4, P87
   Macdonald E, 2018, LANDSCAPE URBAN PLAN, V177, P148, DOI 10.1016/j.landurbplan.2018.04.015
   Maimaitiyiming M, 2014, ISPRS J PHOTOGRAMM, V89, P59, DOI 10.1016/j.isprsjprs.2013.12.010
   Marzluff JM, 2001, RESTOR ECOL, V9, P280, DOI 10.1046/j.1526-100x.2001.009003280.x
   Matos D. M. Silva, 2002, Urban Ecosystems, V6, P151, DOI 10.1023/A:1026164427792
   Maurer U, 2000, LANDSCAPE URBAN PLAN, V46, P209, DOI 10.1016/S0169-2046(99)00066-3
   Mody K, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0234327
   Moorman C E., 2014, Urban wildlife conservation: Theory and practice, P303
   Oberndorfer E, 2007, BIOSCIENCE, V57, P823, DOI 10.1641/B571005
   odarczyk-Marciniak R., 2020, SUSTAINABLE CITIES A
   Otto-Zimmermann K., 2011, K OTTO ZIMMERMANN RE, P485
   Pardela L, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12114721
   Perini K., 2017, Urban Sustainability and River Restoration: Green and Blue Infrastructure
   Pierer C, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab2081
   Planchuelo G, 2019, LANDSCAPE URBAN PLAN, V189, P320, DOI 10.1016/j.landurbplan.2019.05.007
   Ravit B, 2017, AIMS ENVIRON SCI, V4, P458, DOI 10.3934/environsci.2017.3.458
   Rebele F, 2009, Renaturierung von Okosystemen in Mitteleuropa, P389
   Rudolph M, 2017, APPL VEG SCI, V20, P18, DOI 10.1111/avsc.12267
   Salas D. J., 2008, ECOL RESTOR, V26, P246, DOI [DOI 10.3368/ER.26.3.246, 10.3368/er.26.3.246]
   Schadek Ute, 2009, Urban Ecosystems, V12, P115, DOI 10.1007/s11252-008-0072-9
   Schröder R, 2020, ECOL ENG, V145, DOI 10.1016/j.ecoleng.2020.105728
   Schröder R, 2020, URBAN FOR URBAN GREE, V47, DOI 10.1016/j.ufug.2019.126509
   Schwarz N, 2017, ECOSYST SERV, V27, P161, DOI 10.1016/j.ecoser.2017.08.014
   Sehrt M, 2020, BASIC APPL ECOL, V42, P47, DOI 10.1016/j.baae.2019.10.008
   Seitz R., 2012, LWF WISSEN, V68, P46
   Sikorski P, 2018, URBAN FOR URBAN GREE, V35, P148, DOI 10.1016/j.ufug.2018.08.017
   Smith DA, 2010, RESTOR ECOL, V18, P914, DOI 10.1111/j.1526-100X.2009.00538.x
   Smith LS, 2014, URBAN FOR URBAN GREE, V13, P433, DOI 10.1016/j.ufug.2014.04.008
   Standish RJ, 2013, LANDSCAPE ECOL, V28, P1213, DOI 10.1007/s10980-012-9752-1
   Sukopp Herbert, 2002, Preslia (Prague), V74, P373
   Teixeira CP, 2020, LANDSCAPE ECOL, V35, P23, DOI 10.1007/s10980-019-00934-4
   van Andel J., 2012, RESTOR ECOL
   van den Bosch M, 2017, ENVIRON RES, V158, P373, DOI 10.1016/j.envres.2017.05.040
   Wastian L, 2016, J HYMENOPT RES, V49, P51, DOI 10.3897/JHR.49.7929
   Watson CJ, 2020, J APPL ECOL, V57, P436, DOI 10.1111/1365-2664.13542
   Weber A, 2012, ECOL ENG, V42, P160, DOI 10.1016/j.ecoleng.2012.01.007
   Weigelhofer G, 2011, ECOL ENG, V37, P1507, DOI 10.1016/j.ecoleng.2011.05.005
   Wild TC, 2011, WATER ENVIRON J, V25, P412, DOI 10.1111/j.1747-6593.2010.00236.x
   Zari MP., 2018, BIODIVERSITY INT J, V2, P357, DOI [10.15406/bij.2018.02.00087, DOI 10.15406/BIJ.2018.02.00087]
   Zhang Biao Zhang Biao, 2012, Journal of Resources and Ecology, V3, P243, DOI 10.5814/j.issn.1674-764x.2012.03.007
   Zingraff-Hamed A., 2018, THESIS TU MUNCHEN
   Zölch T, 2016, URBAN FOR URBAN GREE, V20, P305, DOI 10.1016/j.ufug.2016.09.011
NR 101
TC 75
Z9 84
U1 21
U2 168
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 1439-1791
EI 1618-0089
J9 BASIC APPL ECOL
JI Basic Appl. Ecol.
PD MAY
PY 2021
VL 52
BP 82
EP 94
DI 10.1016/j.baae.2021.02.010
EA MAR 2021
PG 13
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA RC2FR
UT WOS:000632620000008
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Bonekamp, PNJ
   Wanders, N
   van der Wiel, K
   Lutz, AF
   Immerzeel, WW
AF Bonekamp, P. N. J.
   Wanders, N.
   van Der Wiel, K.
   Lutz, A. F.
   Immerzeel, W. W.
TI Using large ensemble modelling to derive future changes in mountain
   specific climate indicators in a 2 and 3°C warmer world in High Mountain
   Asia
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE climate change; compound events; EC-Earth; High Mountain Asia; large
   ensemble modelling; mountain; return periods; weather extremes
ID GLACIER MASS BALANCES; PRECIPITATION; CMIP5; WINTER; VARIABILITY;
   ATTRIBUTION; IMPACT
AB Natural disasters in High Mountain Asia (HMA) are largely induced by precipitation and temperatures extremes. Precipitation extremes will change due to global warming, but these low frequency events are difficult to analyse using (short) observed time series. In this study, we analysed large 2000 year ensembles of present day climate and of a 2 and 3 degrees C warmer world produced with the EC-Earth model. We performed a regional assessment of climate indicators related to temperature and precipitation (positive degree days, accumulated precipitation, [pre- and post-] monsoon precipitation), their sensitivity to temperature change and the change in return periods of extreme temperature and precipitation in a 2 and 3 degrees C warmer climate. In general, the 2 degrees C warmer world shows a homogeneous response of changes in climate indicators and return periods, while distinct differences between regions are present in a 3 degrees C warmer world and changes no longer follow a general trend. This non-linear effect can indicate the presence of a tipping point in the climate system. The most affected regions are located in monsoon-dominated regions, where precipitation amounts, positive degree days, extreme temperature, extreme precipitation and compound events are projected to increase the most. Largest changes in climate indicators are found in East Himalaya, followed by the Hindu Kush and West and Central Himalaya regions. Western regions will experience drier summers and wetter winters, while monsoon dominated regions drier winters and wetter summers and northern regions a wetter climate year round. We also found that precipitation increases in HMA in a 3 degrees C warmer world are substantially larger (13%) compared to the global average (5.9%). Additionally, the increase in weather extremes will exacerbate natural hazards with large possible impacts for mountain communities. The results of this study could provide important guidance for formulating climate change adaptation strategies in HMA.
C1 [Bonekamp, P. N. J.; Wanders, N.; Lutz, A. F.; Immerzeel, W. W.] Univ Utrecht, Dept Phys Geog, Utrecht, Netherlands.
   [van Der Wiel, K.] Royal Netherlands Meteorol Inst, Res & Dev Weather & Climate Modelling, De Bilt, Netherlands.
C3 Utrecht University; Royal Netherlands Meteorological Institute
RP Bonekamp, PNJ (corresponding author), Univ Utrecht, Dept Phys Geog, Utrecht, Netherlands.
EM p.n.j.bonekamp@uu.nl
RI Immerzeel, Walter/E-2489-2012; van der Wiel, Karin/AAJ-8827-2021;
   Wanders, Niko/AAJ-2334-2021
OI Bonekamp, Pleun/0000-0002-7954-6510
FU ERC Horizon 2020 Framework Programme [676819]; Nederlandse Organisatie
   voor Wetenschappelijk Onderzoek [016.181.308, 016. Veni.181.049,
   ALWCL.2016.2]
FX ERC Horizon 2020 Framework Programme, Grant/Award Number: 676819;
   Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award
   Numbers: 016.181.308, 016. Veni.181.049, ALWCL.2016.2
CR Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   Aznar-Siguan G, 2019, GEOSCI MODEL DEV, V12, P3085, DOI 10.5194/gmd-12-3085-2019
   Biemans H, 2019, NAT SUSTAIN, V2, P594, DOI 10.1038/s41893-019-0305-3
   BOER GJ, 1993, CLIM DYNAM, V8, P225, DOI 10.1007/BF00198617
   Bonekamp PNJ, 2018, J HYDROMETEOROL, V19, P1565, DOI 10.1175/JHM-D-17-0212.1
   Brun F, 2017, NAT GEOSCI, V10, P668, DOI [10.1038/NGEO2999, 10.1038/ngeo2999]
   Brunello CF, 2019, EARTH PLANET SC LETT, V518, P148, DOI 10.1016/j.epsl.2019.04.030
   Buizza R, 1999, Q J ROY METEOR SOC, V125, P2887, DOI 10.1256/smsqj.56005
   Cannon F, 2017, J GEOPHYS RES-ATMOS, V122, P1456, DOI 10.1002/2016JD026038
   Copernicus Climate Change Service (C3S), 2017, Copernicus: Summer 2024 Hottest on Record Globally and for Europe, DOI DOI 10.24381/CDS.ADBB2D47
   Dai A, 2006, J CLIMATE, V19, P4605, DOI 10.1175/JCLI3884.1
   Farinotti D, 2020, NAT GEOSCI, V13, P8, DOI 10.1038/s41561-019-0513-5
   Gao YH, 2018, NPJ CLIM ATMOS SCI, V1, DOI 10.1038/s41612-018-0030-z
   Hall D.K., 2015, MODIS TERRA SNOW COV
   Hauser M, 2017, EARTHS FUTURE, V5, P1034, DOI 10.1002/2017EF000612
   Hazeleger W, 2015, NAT CLIM CHANGE, V5, P107, DOI 10.1038/NCLIMATE2450
   Hazeleger W, 2012, CLIM DYNAM, V39, P2611, DOI 10.1007/s00382-011-1228-5
   Held and Soden, 2006, J CLIMATOL, V19, P5686, DOI DOI 10.1175/JCLI3990.1
   Huffman GJ, 2007, J HYDROMETEOROL, V8, P38, DOI 10.1175/JHM560.1
   Huffman GJ, 2015, Algorithm Theor Basis Doc Version
   Immerzeel WW, 2020, NATURE, V577, P364, DOI 10.1038/s41586-019-1822-y
   Immerzeel WW, 2015, HYDROL EARTH SYST SC, V19, P4673, DOI 10.5194/hess-19-4673-2015
   James R, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.457
   Jury MW, 2020, INT J CLIMATOL, V40, P1738, DOI 10.1002/joc.6298
   Kirschbaum D, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2019GL085347
   Kraaijenbrink PDA, 2017, NATURE, V549, P257, DOI 10.1038/nature23878
   Kumar KK, 2011, CURR SCI INDIA, V101, P312
   LAMBERT SJ, 1995, J CLIMATE, V8, P1447, DOI 10.1175/1520-0442(1995)008<1447:TEOEGW>2.0.CO;2
   Li JP, 2010, J CLIMATE, V23, P6696, DOI 10.1175/2010JCLI3434.1
   Lutz AF, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0165630
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Lutz AF, 2013, HYDROL EARTH SYST SC, V17, P3661, DOI 10.5194/hess-17-3661-2013
   Lutz AF, 2019, REG ENVIRON CHANGE, V19, P833, DOI 10.1007/s10113-018-1433-4
   Nanditha JS, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab7555
   Palazzi E, 2013, J GEOPHYS RES-ATMOS, V118, P85, DOI 10.1029/2012JD018697
   Palazzi E, 2019, CLIM DYNAM, V52, P2685, DOI 10.1007/s00382-018-4287-z
   Papalexiou SM, 2019, WATER RESOUR RES, V55, P4901, DOI [10.1029/2018WR024067, 10.1029/2018wr024067]
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Pepin NC, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034026
   Rangwala I, 2016, CLIM DYNAM, V46, P2115, DOI 10.1007/s00382-015-2692-0
   RGI Consortium, 2017, Randolph Glacier Inventory-A Dataset of Global Glacier Outlines. (NSIDC-0770, Version 6), DOI [10.7265/N5-RGI-60, DOI 10.7265/N5-RGI-60]
   Sharmila S, 2015, GLOBAL PLANET CHANGE, V124, P62, DOI 10.1016/j.gloplacha.2014.11.004
   Stephens GL, 2008, J CLIMATE, V21, P6141, DOI 10.1175/2008JCLI2144.1
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Tariq S., 2014, Pak. J. Meteorol, V10, P39
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Trenberth KE, 2003, B AM METEOROL SOC, V84, P1205, DOI 10.1175/BAMS-84-9-1205
   Trenberth KE, 2015, NAT CLIM CHANGE, V5, P725, DOI 10.1038/NCLIMATE2657
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   van der Wiel K, 2019, GEOPHYS RES LETT, V46, P2093, DOI 10.1029/2019GL081967
   Vos F., 2010, ANN DISASTER STAT RE
   Wester P, 2019, HINDU KUSH HIMALAYA ASSESSMENT: MOUNTAINS, CLIMATE CHANGE, SUSTAINABILITY AND PEOPLE, P1, DOI 10.1007/978-3-319-92288-1
   Wijngaard RR, 2018, HYDROL EARTH SYST SC, V22, P6297, DOI 10.5194/hess-22-6297-2018
NR 53
TC 8
Z9 8
U1 1
U2 18
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD JAN
PY 2021
VL 41
SU 1
BP E964
EP E979
DI 10.1002/joc.6742
EA AUG 2020
PG 16
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA PT6DF
UT WOS:000560001100001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Apotsos, A
AF Apotsos, Alex
TI Mapping relative social vulnerability in six mostly urban municipalities
   in South Africa
SO APPLIED GEOGRAPHY
LA English
DT Article
DE Social vulnerability; South Africa; Urban municipalities; Mapping
ID CLIMATE-CHANGE ADAPTATION; ADAPTIVE CAPACITY; NATURAL HAZARDS;
   ASSESSMENTS; VARIABILITY; INDICATORS; CHALLENGES; HOUSEHOLDS; DYNAMICS;
   LEVEL
AB Urban decision-makers in South Africa face growing challenges related to rapidly expanding populations and a changing climate. To help target limited resources, municipalities have begun to conduct climate change vulnerability assessments. Many of these assessments take a holistic approach that combines both physical hazard exposure and the underlying socio-economic conditions that predispose populations to harm (i.e., social vulnerability). Given the increasing use of socio-economic conditions in climate change vulnerability analyses, this paper seeks to explore two key research questions: 1) can the spatial distribution of relative social vulnerability be estimated in six mostly urban South African municipalities, and if so, 2) how sensitive are the results to a range of subjective methodological choices often required when implementing this type of analysis. Here, social vulnerability is estimated using socio-economic and demographic data from the 2001 and 2011 South African censuses. In all six municipalities, social vulnerability varies spatially, driven primarily by differences in income, assets, wealth, employment and education, and secondarily by differences in access to services and demographics. Even though social vulnerability is estimated from a wide array of population characteristics, the spatial distribution is surprising similar to that of the percent of working-age individuals making less than 800 rand per month. Areas with high percentages of previously disadvantaged, extended family, and informal households tend to display relatively higher levels of social vulnerability. In fact, demographics (e.g., race, language, age) are often highly correlated with other characteristics that have direct ties to social vulnerability (e.g., income, employment, education). The spatial patterns of relative social vulnerability are similar in 2001 and 2011. However, there is some evidence social vulnerability is relatively lower in 2011. While the choice of input data and aggregation method can affect the spatial distribution of social vulnerability, the general spatial patterns appear to be fairly robust across a number of subjective choices related to methodological and aggregation approach, spatial resolution, and input data.
C1 [Apotsos, Alex] Williams Coll, Geosci Dept, Clark Hall,947 Main St, Williamstown, MA 01267 USA.
C3 Williams College
RP Apotsos, A (corresponding author), Williams Coll, Geosci Dept, Clark Hall,947 Main St, Williamstown, MA 01267 USA.
EM aa13@williams.edu
FU Fulbright Fellowship Grant from the United States Department of State;
   Climate System Analysis Group (CSAG) at the University of Cape Town
FX Funding for this research was graciously provided by a Fulbright
   Fellowship Grant from the United States Department of State. The author
   conducted this research while he was in residence with the Climate
   System Analysis Group (CSAG) at the University of Cape Town.
CR Adger WN, 2003, ECON GEOGR, V79, P387
   Alwang J., 2001, SOCIAL PROTECTION DI
   [Anonymous], CLIMATE RISK VULNERA
   [Anonymous], 2008, ENV ULNERABILITY ASS
   [Anonymous], 2015, CITY TSHWANE VULNERA
   [Anonymous], 2001, PNNLSA33642 US DEP E
   [Anonymous], 2009, Carbon & Climate Law Review
   Antwi-Agyei Philip, 2013, Environment Development and Sustainability, V15, P903, DOI 10.1007/s10668-012-9418-9
   Archer D, 2014, CLIM DEV, V6, P345, DOI 10.1080/17565529.2014.918868
   Batterbury SPJ, 2013, NATURAL DISASTERS AND ADAPTATION TO CLIMATE CHANGE, P149
   Birkmann J., 2006, Measuring Vulnerability to Natural Hazards-Towards Disaster Resilient Societies, V01, P9
   Brooks N, 2005, GLOBAL ENVIRON CHANG, V15, P151, DOI 10.1016/j.gloenvcha.2004.12.006
   Broto VC, 2015, CURR OPIN ENV SUST, V13, P11, DOI 10.1016/j.cosust.2014.12.005
   Burton C., 2008, Natural Hazards Review, V9, P136, DOI 10.1061/(ASCE)1527-6988(2008)9:3(136)
   Chu E, 2017, CITIES, V60, P378, DOI 10.1016/j.cities.2016.10.016
   Cutter S. L., 2013, MEASURING VULNERABIL, P304
   Cutter S.L., 2009, Final Report to Oxfam America, V5, P1
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Cutter SL, 1996, PROG HUM GEOG, V20, P529, DOI 10.1177/030913259602000407
   Cutter SL, 2014, GLOBAL ENVIRON CHANG, V29, P65, DOI 10.1016/j.gloenvcha.2014.08.005
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   de Sherbinin A., 2015, VIENNA YB POPULATION, V13, P131, DOI DOI 10.1553/POPULATIONYEARBOOK2015S131
   Dodman D, 2008, IDS BULL-I DEV STUD, V39, P67
   Downing T.E., 2006, 4 SEI
   Eriksen SH, 2005, GEOGR J, V171, P287, DOI 10.1111/j.1475-4959.2005.00174.x
   Fekete A, 2012, NAT HAZARDS, V61, P1161, DOI 10.1007/s11069-011-9973-7
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Finch C, 2010, POPUL ENVIRON, V31, P179, DOI 10.1007/s11111-009-0099-8
   Flato M, 2017, WORLD DEV, V90, P41, DOI 10.1016/j.worlddev.2016.08.015
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Gall M., 2007, INDICES SOCIAL VULNE
   Granderson AA, 2014, CLIM RISK MANAG, V3, P55, DOI 10.1016/j.crm.2014.05.003
   Gu HH, 2018, SUSTAIN CITIES SOC, V41, P170, DOI 10.1016/j.scs.2018.05.047
   Hinkel J, 2011, GLOBAL ENVIRON CHANG, V21, P198, DOI 10.1016/j.gloenvcha.2010.08.002
   Hung LS, 2016, APPL GEOGR, V76, P184, DOI 10.1016/j.apgeog.2016.09.021
   Lankao PR, 2011, CURR OPIN ENV SUST, V3, P142, DOI 10.1016/j.cosust.2010.12.016
   Le Roux A., 2010, S AFRICA RISK VULNER, P15
   le Roux A., 2018, S AFRICAN RISK VULNE, P26
   le Roux A, 2015, LECT NOTES GEOINF CA, P283, DOI 10.1007/978-3-319-17738-0_19
   Leck H., 2015, Current Opinion in Environmental Sustainability, V13, P61, DOI [10.1016/j.cosust.2015.02.004, DOI 10.1016/J.COSUST.2015.02.004]
   Lee YJ, 2014, ENVIRON IMPACT ASSES, V44, P31, DOI 10.1016/j.eiar.2013.08.002
   Leichenko R. M., 2002, Mitigation and Adaptation Strategies for Global Change, V7, P1, DOI 10.1023/A:1015860421954
   Letsie MM, 2015, MT RES DEV, V35, P115, DOI 10.1659/MRD-JOURNAL-D-14-00087.1
   Lujala P, 2014, NORSK GEOGR TIDSSKR, V68, P34, DOI 10.1080/00291951.2013.870600
   Mazumdar J., 2016, NAT HAZARDS, V82, P1, DOI [10.1007/811069-016-2261-9, DOI 10.1007/811069-016-2261-9]
   Nelson R, 2010, ENVIRON SCI POLICY, V13, P8, DOI 10.1016/j.envsci.2009.09.006
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Pelling Mark., 2009, DISASTER RISK REDUCT
   Preston BL, 2011, SUSTAIN SCI, V6, P177, DOI 10.1007/s11625-011-0129-1
   Reid P, 2006, GLOBAL ENVIRON CHANG, V16, P195, DOI 10.1016/j.gloenvcha.2006.01.003
   Roberts D, 2013, ENVIRON URBAN, V25, P299, DOI 10.1177/0956247813500904
   Rygel L., 2006, MITIG ADAPT STRAT GL, V11, P741, DOI [10.1007/s11027-006-0265-6, DOI 10.1007/S11027-006-0265-6]
   Soares MB, 2012, INT J CLIM CHANG STR, V4, P6, DOI 10.1108/17568691211200191
   Stats SA South African Census, 2015, 2011 10 SAMPL VERS 2
   Stats SA South African Census, 2001, VERS 1 1 PRET STAT S
   Tapia C, 2017, ECOL INDIC, V78, P142, DOI 10.1016/j.ecolind.2017.02.040
   Tate E, 2013, ANN ASSOC AM GEOGR, V103, P526, DOI 10.1080/00045608.2012.700616
   Tate E, 2012, NAT HAZARDS, V63, P325, DOI 10.1007/s11069-012-0152-2
   Tate E, 2010, ENVIRON PLANN B, V37, P646, DOI 10.1068/b35157
   Tompkins E, 2002, ENVIRON PLANN A, V34, P1095, DOI 10.1068/a34213
   van Huyssteen E, 2015, UPDATED CSIR SACN S
   Van Huyssteen E., 2009, Urban Forum, V20, P175, DOI DOI 10.1007/S12132-009-9058-9
   van Huyssteen E, 2013, JAMBA-J DISASTER RIS, V5, DOI 10.4102/jamba.v5i2.80
   Vincent K., 2004, Tyndall Center for Climate Change Research. Working Paper, V56, P41
   Wang CM, 2012, NAT HAZARDS, V63, P349, DOI 10.1007/s11069-012-0151-3
   Wisner B., 2004, At risk: natural hazards, people's vulnerability and disasters
   Wood NJ, 2010, NAT HAZARDS, V52, P369, DOI 10.1007/s11069-009-9376-1
   Ziervogel G, 2006, NAT RESOUR FORUM, V30, P294, DOI 10.1111/j.1477-8947.2006.00121.x
NR 69
TC 19
Z9 23
U1 2
U2 27
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0143-6228
EI 1873-7730
J9 APPL GEOGR
JI Appl. Geogr.
PD APR
PY 2019
VL 105
BP 86
EP 101
DI 10.1016/j.apgeog.2019.02.012
PG 16
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA HT3QV
UT WOS:000464479200008
DA 2025-01-10
ER

PT J
AU Meinel, U
   Schüle, R
AF Meinel, Ulrike
   Schuele, Ralf
TI The Difficulty of Climate Change Adaptation in Manufacturing Firms:
   Developing an Action-Theoretical Perspective on the Causality of
   Adaptive Inaction
SO SUSTAINABILITY
LA English
DT Article
DE climate change; adaptation; manufacturing firms; strategic management;
   action theory
ID DECISION-MAKING; SUPPLY CHAINS; BARRIERS; UNCERTAINTY; MANAGEMENT;
   DRIVERS; RISKS
AB Climate change induces various risks for supply chains of manufacturing firms. However, surveys have suggested that only a minority of firms conducts strategic adaptations, which we define as anticipatory and target-oriented action with the purpose of increasing resilience to climate change. While several barrier-centered studies have investigated the causality of non-adaptation in industry, the examined barriers are often not problem-specific. Furthermore, it has been shown that even in cases when managers perceive no barriers to adaptation at all, strategic adaptations may still not be conducted. On this background, the present analysis focuses on the logic of adaptive inaction, which we conceive, in particular, as inaction with regard to strategic adaptations. Adopting an action-theoretical perspective, the study examines (a) which aspects may shape the rationality of adaptive inaction among managers, (b) which more condensed challenges of conducting strategic adaptations emerge for managers, and (c) how the theoretical propositions can be tested. For this purpose, the study employs an exploratory approach. Thus, hypotheses on such aspects are explored, which may shape the rationality of adaptive inaction among managers. Subsequently, predictions are inferred from the theoretical propositions, which allow testing their empirical relevance. Methodologically, the hypotheses are explored by reexamining existing explanatory approaches from literature based on a set of pretheoretical assumptions, which include notions of bounded rationality. As a result, the study proposes 13 aspects which may constrain managers in conducting adaptations in such a way, which serves the economic utility of the firm. By condensing these aspects, 4 major challenges for managers are suggested: the challenges of (a) conducting long-term adaptations, of (b) conducting adaptations at an early point in time, of (c) conducting adaptations despite uncertain effects of the measures, and of (d) conducting adaptations despite cross-tier dependencies in supply chains. Finally, the study shows how the propositions can be tested and outlines a research agenda based on the developed theoretical suggestions.
C1 [Meinel, Ulrike] AlpS Ctr Climate Change Adaptat, Grabenweg 68, A-6020 Innsbruck, Austria.
   [Meinel, Ulrike] Univ Innsbruck, Inst Geog, Innrain 52f, A-6020 Innsbruck, Austria.
   [Meinel, Ulrike; Schuele, Ralf] Wuppertal Inst Climate Environm & Energy, Doppersberg 19, D-42103 Wuppertal, Germany.
C3 University of Innsbruck
RP Meinel, U (corresponding author), AlpS Ctr Climate Change Adaptat, Grabenweg 68, A-6020 Innsbruck, Austria.; Meinel, U (corresponding author), Univ Innsbruck, Inst Geog, Innrain 52f, A-6020 Innsbruck, Austria.; Meinel, U (corresponding author), Wuppertal Inst Climate Environm & Energy, Doppersberg 19, D-42103 Wuppertal, Germany.
EM ulrike.meinel@wupperinst.org; ralf.schuele@wupperinst.org
OI Schule, Ralf/0000-0002-4490-4648; Meinel, Ulrike/0000-0001-6869-2961
FU COMET funding program of the Austrian Ministry for Transport, Innovation
   and Technology [T2B-CCA]; Austrian Ministry of Science, Research and
   Economy; state of Tyrol; state Vorarlberg; University of Innsbruck
FX This work was conducted within the project T2B-CCA, which is supported
   by the COMET funding program of the Austrian Ministry for Transport,
   Innovation and Technology, the Austrian Ministry of Science, Research
   and Economy, the state of Tyrol, and the state Vorarlberg; the COMET
   program is processed by the Austrian Research Promotion Agency (FFG).
   Moreover, the work was promoted by the University of Innsbruck within
   the scope of a doctoral scholarship. The authors would particularly like
   to thank Holger Berg, Wuppertal Institute for Climate, Environment and
   Energy, for helpful comments and discussions.
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Agrawala S., 2011, PRIVATE SECTOR ENGAG
   Akamp M, 2013, J CLEAN PROD, V56, P54, DOI 10.1016/j.jclepro.2011.11.069
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Baum SD, 2009, ECOL ECON, V69, P197, DOI 10.1016/j.ecolecon.2009.08.024
   Berkhout F, 2012, WIRES CLIM CHANGE, V3, P91, DOI 10.1002/wcc.154
   Bertrand M, 2003, Q J ECON, V118, P1169, DOI 10.1162/003355303322552775
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Biesbroek GR, 2014, GLOBAL ENVIRON CHANG, V26, P108, DOI 10.1016/j.gloenvcha.2014.04.004
   BSR, 2011, AD CLIM CHANG GUID C
   Chambwera M, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P945
   Crawford Meg., 2013, Weathering the Storm: Building Business Resiliance to Climate Change
   Dilling L, 2015, WIRES CLIM CHANGE, V6, P413, DOI 10.1002/wcc.341
   EISENHARDT KM, 1989, ACAD MANAGE REV, V14, P57, DOI 10.2307/258191
   European Commission, 2017, CLIM SERV SERV SOC T
   Feng XL, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9040519
   Fichter K., 2013, 24 U OLD
   Fleming A, 2014, CLIM RISK MANAG, V1, P39, DOI 10.1016/j.crm.2013.12.003
   Ford JD, 2011, CLIMATIC CHANGE, V109, P399, DOI 10.1007/s10584-011-0029-5
   Gifford R, 2011, AM PSYCHOL, V66, P290, DOI 10.1037/a0023566
   Gifford R, 2011, WIRES CLIM CHANGE, V2, P801, DOI 10.1002/wcc.143
   Gottschick M, 2015, CLIMATIC CHANGE, V132, P445, DOI 10.1007/s10584-014-1203-3
   Gotze U., 2014, INVESTITIONSRECHNUNG
   Grüneis H, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-3542-1
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Hammoud MS, 2014, EUR J FUTURES RES, V2, DOI 10.1007/s40309-014-0042-9
   Hartmann J, 2014, J OPER MANAG, V32, P281, DOI 10.1016/j.jom.2014.01.005
   Heal G, 2014, REV ENV ECON POLICY, V8, P120, DOI 10.1093/reep/ret023
   Helfferich C., 2012, AGENCY ANAL HANDLUNS
   Heukelom Floris., 2014, BEHAV EC HIST
   Hopkins D, 2014, J SUSTAIN TOUR, V22, P107, DOI 10.1080/09669582.2013.804830
   Huq FA, 2016, J OPER MANAG, V46, P19, DOI 10.1016/j.jom.2016.07.005
   Jannek K., 2007, Corporate foresight in small and medium-sized enterprises
   Kaluza B., 2003, PRINCIPAL AGENT PROB
   Kash DE, 2002, TECHNOL FORECAST SOC, V69, P581, DOI 10.1016/S0040-1625(01)00171-8
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Kelly DL, 2005, J ENVIRON ECON MANAG, V50, P468, DOI 10.1016/j.jeem.2005.02.003
   Khurana M., 2011, International Journal of Manufacturing Systems, V1, P9
   Kovach JJ, 2015, J OPER MANAG, V37, P1, DOI 10.1016/j.jom.2015.04.002
   Lim-Camacho L, 2015, REG ENVIRON CHANGE, V15, P595, DOI 10.1007/s10113-014-0670-4
   Linnenluecke MK, 2012, BUS STRATEG ENVIRON, V21, P17, DOI 10.1002/bse.708
   Little D., 2009, SOCIAL AGENCY RATION
   Loechel B, 2013, CLIMATIC CHANGE, V119, P465, DOI 10.1007/s10584-013-0721-8
   Meinel U, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9071132
   Meinel U, 2017, GLOBAL ENVIRON CHANG, V44, P68, DOI 10.1016/j.gloenvcha.2017.03.006
   NORTH DC, 1991, J ECON PERSPECT, V5, P97, DOI 10.1257/jep.5.1.97
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   Pahl S, 2014, WIRES CLIM CHANGE, V5, P375, DOI 10.1002/wcc.272
   Paternoster R, 2015, J DEV LIFE-COURSE CR, V1, P209, DOI 10.1007/s40865-015-0013-2
   Poggensee K., 2011, INVESTITIONSRECHNUNG
   Popper K., 1959, LOGIC SCI DISCOVERY
   Ridoutt B, 2016, CLIMATE, V4, DOI 10.3390/cli4020026
   Roberge M W, 2014, LENGTHENING INVESTME
   Santarius T., 2012, Der Rebound-Effekt: uber die unerwunschten Folgen der erwunschten Energieeffizienz (No. 5)
   Simon HA, 1991, ORGAN SCI, V2, P125, DOI 10.1287/orsc.2.1.125
   Skokan K, 2013, J COMPETITIVENESS, V5, P57, DOI 10.7441/joc.2013.04.04
   Sridharan Ramaswami, 2013, International Journal of Value Chain Management, V7, P76
   Straub J., 2010, HDB QUALITATIVE FORS, P107
   The Global Compact; UNEP, 2012, BUS CLIM CHANG AD RE
   UK Environment Agency, 2013, ASS MAN CLIM CHANG R
   Vecchiato R, 2012, TECHNOL FORECAST SOC, V79, P436, DOI 10.1016/j.techfore.2011.07.010
   Vervoort JM, 2012, ECOL SOC, V17, DOI 10.5751/ES-05098-170424
   Weber M., 1972, Wirtschaft und Gesellschaft: Grundriss der Verstehenden Soziologie, V5th
   WWF; Germanwatch, 2015, KLIM FIN IHR BEARB
NR 64
TC 8
Z9 8
U1 2
U2 18
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD FEB
PY 2018
VL 10
IS 2
AR 569
DI 10.3390/su10020569
PG 16
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA FX3BB
UT WOS:000425943100292
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Sánchez-Bermejo, E
   Méndez-Vigo, B
   Picó, FX
   Martínez-Zapater, JM
   Alonso-Blanco, C
AF Sanchez-Bermejo, Eduardo
   Mendez-Vigo, Belen
   Xavier Pico, F.
   Martinez-Zapater, Jose M.
   Alonso-Blanco, Carlos
TI Novel natural alleles at FLC and LVR loci account for enhanced
   vernalization responses in Arabidopsis thaliana
SO PLANT CELL AND ENVIRONMENT
LA English
DT Article
DE climatic adaptation; flowering; FLOWERING LOCUS C (FLC); quantitative
   trait locus (QTL)
ID FLOWERING TIME; LANDSBERG ERECTA; EPIGENETIC MAINTENANCE; LINE
   POPULATION; COMPLEX TRAITS; FRIGIDA; ASSOCIATION; GENOME; GENE;
   POLYMORPHISM
AB Vernalization, the induction of flowering by low winter temperatures, is likely to be involved in plant climatic adaptation. However, the genetic, molecular and ecological bases underlying the quantitative variation that tunes vernalization sensitivity to natural environments are largely unknown. To address these questions, we have studied the enhanced vernalization response shown by the Ll-0 accession of Arabidopsis thaliana. Quantitative trait locus (QTL) mapping for several flowering initiation traits in relation to vernalization, in a new Ler x Ll-0 recombinant inbred line (RIL) population, identified large effect alleles at FRI, FLC and HUA2, together with two small effect loci named as Llagostera vernalization response (LVR) 1 and 2. Phenotypic analyses of near isogenic lines validated LVR1 effect on flowering vernalization responses. To further characterize the FLC allele from Ll-0, we carried out genetic association analyses using a regional collection of wild genotypes. FLC-Ll-0 appeared as a low-frequency allele that is distinguished by polymorphism Del(-57), a 50-bp-deletion in the 5'-UTR. Del(-57) was significantly associated with enhanced vernalization responses and FLC RNA expression, as well as with altitude and minimum temperatures. These results are consistent with Del(-57) acting as a novel cis-regulatory FLC polymorphism that may confer climatic adaptation by increasing vernalization sensitivity.
C1 [Sanchez-Bermejo, Eduardo; Mendez-Vigo, Belen; Martinez-Zapater, Jose M.; Alonso-Blanco, Carlos] CSIC, CNB, Dept Genet Mol Plantas, E-28049 Madrid, Spain.
   [Xavier Pico, F.] CSIC, EBD, Dept Ecol Integrat, Seville 41092, Spain.
   [Martinez-Zapater, Jose M.] Univ La Rioja, CSIC, ICVV, Gobierno De La Rioja 26006, Logrono, Spain.
C3 Consejo Superior de Investigaciones Cientificas (CSIC); CSIC - Centro
   Nacional de Biotecnologia (CNB); Consejo Superior de Investigaciones
   Cientificas (CSIC); CSIC - Estacion Biologica de Donana (EBD); Consejo
   Superior de Investigaciones Cientificas (CSIC); CSIC-CAR-UR - Instituto
   de Ciencias de la Vid y del Vino (ICVV); Universidad de La Rioja
RP Alonso-Blanco, C (corresponding author), CSIC, CNB, Dept Genet Mol Plantas, Plaza Murillo 2, E-28049 Madrid, Spain.
EM calonso@cnb.csic.es
RI Pico, Xavier/E-5697-2016; Martinez Zapater, Jose Miguel/I-4892-2012;
   Alonso-Blanco, Carlos/F-8864-2016
OI Martinez Zapater, Jose Miguel/0000-0001-7217-4454; Alonso-Blanco,
   Carlos/0000-0002-4738-5556; Pico, Xavier/0000-0003-2849-4922;
   Mendez-Vigo, Belen/0000-0002-9850-536X
FU Ministerio de Ciencia and Innovacion of Spain [BIO2010-15022,
   TRANSPLANTA CSD-2007-00057]
FX The authors thank Mercedes Ramiro and Jenifer Pozas for their excellent
   technical assistance. This work was funded by grants BIO2010-15022 and
   TRANSPLANTA CSD-2007-00057 from the Ministerio de Ciencia and Innovacion
   of Spain to C.A-B.
CR Alonso-Blanco C, 1998, GENETICS, V149, P749
   Alonso-Blanco Carlos, 2006, V323, P79
   Alonso-Blanco C, 2009, PLANT CELL, V21, P1877, DOI 10.1105/tpc.109.068114
   Atwell S, 2010, NATURE, V465, P627, DOI 10.1038/nature08800
   Ausín I, 2005, INT J DEV BIOL, V49, P689, DOI 10.1387/ijdb.052022ia
   BELL CJ, 1994, GENOMICS, V19, P137, DOI 10.1006/geno.1994.1023
   BERNATZKY R, 1986, THEOR APPL GENET, V72, P314, DOI 10.1007/BF00288567
   Brachi B, 2010, PLOS GENET, V6, DOI 10.1371/journal.pgen.1000940
   Bradbury PJ, 2007, BIOINFORMATICS, V23, P2633, DOI 10.1093/bioinformatics/btm308
   Caicedo AL, 2004, P NATL ACAD SCI USA, V101, P15670, DOI 10.1073/pnas.0406232101
   Chiang GCK, 2009, P NATL ACAD SCI USA, V106, P11661, DOI 10.1073/pnas.0901367106
   Choi K, 2011, PLANT CELL, V23, P289, DOI 10.1105/tpc.110.075911
   Clauss MJ, 2002, MOL ECOL, V11, P591, DOI 10.1046/j.0962-1083.2002.01465.x
   De Lucia F, 2011, CURR OPIN PLANT BIOL, V14, P168, DOI 10.1016/j.pbi.2010.11.006
   Doyle MR, 2005, PLANT J, V41, P376, DOI 10.1111/j.1365-313X.2004.02300.x
   Geraldo N, 2009, PLANT PHYSIOL, V150, P1611, DOI 10.1104/pp.109.137448
   Gomaa NH, 2011, MOL ECOL, V20, P3540, DOI 10.1111/j.1365-294X.2011.05193.x
   He YH, 2004, GENE DEV, V18, P2774, DOI 10.1101/gad.1244504
   Heo JB, 2011, SCIENCE, V331, P76, DOI 10.1126/science.1197349
   Jander G, 2002, PLANT PHYSIOL, V129, P440, DOI 10.1104/pp.003533
   Johanson U, 2000, SCIENCE, V290, P344, DOI 10.1126/science.290.5490.344
   Keurentjes JJB, 2007, GENETICS, V175, P891, DOI 10.1534/genetics.106.066423
   Kim DH, 2009, ANNU REV CELL DEV BI, V25, P277, DOI 10.1146/annurev.cellbio.042308.113411
   Kobayashi Y, 2007, GENE DEV, V21, P2371, DOI 10.1101/gad.1589007
   KONIECZNY A, 1993, PLANT J, V4, P403, DOI 10.1046/j.1365-313X.1993.04020403.x
   KOORNNEEF M, 1994, PLANT J, V6, P911, DOI 10.1046/j.1365-313X.1994.6060911.x
   Kranz A.R., 1987, GENETIC RESOURCES AR, V24
   Le Corre V, 2002, MOL BIOL EVOL, V19, P1261, DOI 10.1093/oxfordjournals.molbev.a004187
   LEE I, 1994, PLANT J, V6, P903, DOI 10.1046/j.1365-313X.1994.6060903.x
   Lempe J, 2005, PLOS GENET, V1, P109, DOI 10.1371/journal.pgen.0010006
   Li Y, 2010, P NATL ACAD SCI USA, V107, P21199, DOI 10.1073/pnas.1007431107
   Loudet O, 2002, THEOR APPL GENET, V104, P1173, DOI 10.1007/s00122-001-0825-9
   Martinez-Zapater J.M., 1994, COLD SPRING HARB SYM, P403
   Méndez-Vigo B, 2011, PLANT PHYSIOL, V157, P1942, DOI 10.1104/pp.111.183426
   Méndez-Vigo B, 2010, J EXP BOT, V61, P1611, DOI 10.1093/jxb/erq032
   Michaels SD, 1999, PLANT CELL, V11, P949, DOI 10.1105/tpc.11.5.949
   Michaels SD, 2003, P NATL ACAD SCI USA, V100, P10102, DOI 10.1073/pnas.1531467100
   Montesinos A, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0007213
   NAPPZINN K, 1969, INDUCTION FLOWERING, P291
   Nicholas KB, 1997, EMBNEW NEWS, V4
   Nordborg M, 2005, PLOS BIOL, V3, P1289, DOI 10.1371/journal.pbio.0030196
   Orr HA, 2005, NAT REV GENET, V6, P119, DOI 10.1038/nrg1523
   Poduska B, 2003, GENETICS, V163, P1457
   Redei G.P., 1970, BIBLIOGR GENET, V20, P1
   REDEI GP, 1962, Z VEREBUNGSL, V93, P164
   Roux F, 2006, TRENDS PLANT SCI, V11, P375, DOI 10.1016/j.tplants.2006.06.006
   Salomé PA, 2011, GENETICS, V188, P421, DOI 10.1534/genetics.111.126607
   Schläppi MR, 2006, PLANT PHYSIOL, V142, P1728, DOI 10.1104/pp.106.085571
   Schmid K, 2006, THEOR APPL GENET, V112, P1104, DOI 10.1007/s00122-006-0212-7
   Sheldon CC, 2002, PLANT CELL, V14, P2527, DOI 10.1105/tpc.004564
   Shindo C, 2005, PLANT PHYSIOL, V138, P1163, DOI 10.1104/pp.105.061309
   Shindo C, 2006, GENE DEV, V20, P3079, DOI 10.1101/gad.405306
   SNUSTAD DP, 1992, PLANT CELL, V4, P549, DOI 10.1105/tpc.4.5.549
   Stinchcombe JR, 2005, AM J BOT, V92, P1701, DOI 10.3732/ajb.92.10.1701
   Strange A, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019949
   Sung SB, 2006, NAT GENET, V38, P706, DOI 10.1038/ng1795
   Swiezewski S, 2009, NATURE, V462, P799, DOI 10.1038/nature08618
   Van Ooijen JW, 2000, MAPQTL VERSION 4 0 U
   Van Ooijen JW., 2001, Joinmap 3.0: software for the calculation of genetic 99 linkage maps
   Wang Q, 2007, CURR BIOL, V17, P1513, DOI 10.1016/j.cub.2007.07.059
   Warthmann N, 2007, BIOINFORMATICS, V23, P2784, DOI 10.1093/bioinformatics/btm428
   Weigel D, 2012, PLANT PHYSIOL, V158, P2, DOI 10.1104/pp.111.189845
   Werner JD, 2005, GENETICS, V170, P1197, DOI 10.1534/genetics.104.036533
   Wilczek AM, 2010, PHILOS T R SOC B, V365, P3129, DOI 10.1098/rstb.2010.0128
   Yu JM, 2006, NAT GENET, V38, P203, DOI 10.1038/ng1702
   Zhao KY, 2007, PLOS GENET, V3, DOI 10.1371/journal.pgen.0030004
NR 66
TC 26
Z9 31
U1 0
U2 37
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0140-7791
EI 1365-3040
J9 PLANT CELL ENVIRON
JI Plant Cell Environ.
PD SEP
PY 2012
VL 35
IS 9
BP 1672
EP 1684
DI 10.1111/j.1365-3040.2012.02518.x
PG 13
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 986ZS
UT WOS:000307386800011
PM 22494398
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Fedele, G
   Manco, I
   Barbato, G
   Verri, G
   Mercogliano, P
AF Fedele, Giusy
   Manco, Ilenia
   Barbato, Giuliana
   Verri, Giorgia
   Mercogliano, Paola
TI Evaluation of atmospheric indicators in the Adriatic coastal areas: a
   multi-hazards approach for a better awareness of the current and future
   climate
SO FRONTIERS IN CLIMATE
LA English
DT Article
DE climate change; atmospheric climate indicators; hazard assessment;
   high-resolution climate projections; AdriaClim Project
ID PRECIPITATION; SIMULATIONS; DROUGHT
AB Increasing climate resilience to global warming is one of the main challenges of the last few decades. Effective local measures have to be adopted to provide concrete solutions to the current and expected impacts of climate change. This is the goal of the AdriaClim Italia-Croatia Interreg Project (https://www.italy-croatia.eu/web/adriaclim), aimed at supporting the development of regional and local climate change adaptation plans for the Adriatic coastal regions. For this purpose, an exhaustive number of atmospheric climate indicators have been identified and evaluated across nine pilot areas to assess the current and expected main climate hazards affecting these regions, considering the worst-case emissions scenario (Representative Concentration Pathway RCP 8.5). The proposed analyses are provided by the results of the regional climate atmospheric model developed within the AdriaClim Project. The selected climate indicators are used to assess the possible evolution of the climate hazard across the pilot areas, covering different hazards, such as thermal discomfort, drought, and hydrological instability. A site-dependent investigation of the atmospheric climate indicators is proposed to emphasize which regions are more affected than others by the investigated climate hazards, thus warranting more attention in defining and proposing new adaptation strategies. The results highlight increasing temperatures (up to +3 degrees C) across the Adriatic coastal regions, with more emphasis on the Northern Adriatic, where the combined effect with the relevant decrease in precipitation (down to -2 mm/day) may lead to severe drought conditions in the coming decades. In contrast, precipitation-related diseases may hit more Central and South Italy than the Northern Adriatic, except for the Emilia-Romagna region, which is found to be highly sensitive to both hazard categories. Finally, it is relevant to emphasize that these analyses have to be carefully considered in supporting adaptation strategies due to the lack of uncertainty estimates representing a fundamental element for decision-makers.
C1 [Fedele, Giusy; Manco, Ilenia; Barbato, Giuliana; Verri, Giorgia; Mercogliano, Paola] CMCC Fdn, Euro Mediterranean Ctr Climate Change, Lecce, Italy.
   [Manco, Ilenia] Univ Bologna, Dept Phys & Astron, Bologna, Italy.
C3 Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC); University of
   Bologna
RP Fedele, G (corresponding author), CMCC Fdn, Euro Mediterranean Ctr Climate Change, Lecce, Italy.
EM giusy.fedele@cmcc.it
RI Fedele, Giusy/KMX-2602-2024; Verri, Giorgia/AAB-5811-2022
OI Barbato, Giuliana/0000-0001-5892-1062; Fedele, Giusy/0000-0003-2376-8015
FU AdriaClim project, Italy [10252001]
FX The authors acknowledge the AdriaClim Italia-Croatia Interreg Project
   (https://www.italy-croatia.eu/web/adriaclim) for providing funds that
   supported this research study.
CR Ahmed Z, 2022, SUSTAIN DEV, V30, P595, DOI 10.1002/sd.2251
   Appiotti F, 2014, REG ENVIRON CHANGE, V14, P2007, DOI 10.1007/s10113-013-0451-5
   Bala G, 2010, CLIM DYNAM, V35, P423, DOI 10.1007/s00382-009-0583-y
   Ballester J, 2023, NAT MED, V29, P1857, DOI 10.1038/s41591-023-02419-z
   Bucchignani E, 2016, INT J CLIMATOL, V36, P735, DOI 10.1002/joc.4379
   Casanueva A, 2020, ATMOS SCI LETT, V21, DOI 10.1002/asl.978
   Copernicus Climate Change Service, 2024, ECMWR
   Copernicus Climate Change Service, 2019, Complete UERRA regional reanalysis for Europe from 1961 to 2019, DOI [10.24381/cds.dd7c6d66, DOI 10.24381/CDS.DD7C6D66]
   Cos J, 2022, EARTH SYST DYNAM, V13, P321, DOI 10.5194/esd-13-321-2022
   Doughty CE, 2015, NATURE, V519, P78, DOI 10.1038/nature14213
   Drenkard EJ, 2021, ICES J MAR SCI, V78, P1969, DOI 10.1093/icesjms/fsab100
   Ek MB, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD003296
   Gordon LJ, 2005, P NATL ACAD SCI USA, V102, P7612, DOI 10.1073/pnas.0500208102
   Gudmundsson L, 2012, HYDROL EARTH SYST SC, V16, P3383, DOI 10.5194/hess-16-3383-2012
   Hermans K, 2021, CURR OPIN ENV SUST, V50, P236, DOI 10.1016/j.cosust.2021.04.013
   Hersbach H., ERA5 HOURLY DATA SIN, DOI [10.24381/cds.adbb2d47, 10.24381/cds. adbb2d47, 10.24381]
   L'Hévéder B, 2013, CLIM DYNAM, V41, P937, DOI 10.1007/s00382-012-1527-5
   Lafon T, 2013, INT J CLIMATOL, V33, P1367, DOI 10.1002/joc.3518
   Maraun D, 2016, CURR CLIM CHANGE REP, V2, P211, DOI 10.1007/s40641-016-0050-x
   Masson-Delmotte V., 2021, Climate Change 2021: The Physical Science Basis, P41
   Mentaschi L, 2024, FRONT CLIM, V6, DOI 10.3389/fclim.2024.1338374
   Pearson K., 1895, Philosophical Transanctions of the Royal Society A, V186, P343, DOI [10.1098/rsta.1895.0010, DOI 10.1098/RSTA.1895.0010]
   Pendergrass AG, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-17966-y
   Piani C, 2010, THEOR APPL CLIMATOL, V99, P187, DOI 10.1007/s00704-009-0134-9
   Raffa M, 2023, SCI DATA, V10, DOI 10.1038/s41597-023-02144-9
   Ruti PM, 2016, B AM METEOROL SOC, V97, P1187, DOI 10.1175/BAMS-D-14-00176.1
   Santos da Costa V., 2023, Front. Clim
   Skamarock W. C., 2008, A description of the advanced research WRF version 3, P125, DOI [DOI 10.5065/D68S4MVH, 10.5065/D68S4MVH, DOI 10.5065/1DFH-6P97]
   Straffelini E, 2023, AGR SYST, V208, DOI 10.1016/j.agsy.2023.103647
   Themessl MJ, 2012, CLIMATIC CHANGE, V112, P449, DOI 10.1007/s10584-011-0224-4
   Trisos CH, 2020, NATURE, V580, P496, DOI 10.1038/s41586-020-2189-9
   Verri G., 2023, Front. Clim
NR 32
TC 2
Z9 2
U1 0
U2 0
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-9553
J9 FRONT CLIM
JI Front. Clim.
PD FEB 28
PY 2024
VL 6
AR 1330299
DI 10.3389/fclim.2024.1330299
PG 16
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA LF2S1
UT WOS:001185307400001
OA gold
DA 2025-01-10
ER

PT J
AU Mastej, E
   Wright, S
   Braverman, M
   Devoie, É
   Egorov, I
   Quinton, W
AF Mastej, Ela
   Wright, Stephanie
   Braverman, Michael
   Devoie, Elise
   Egorov, Igor
   Quinton, William
TI An evaluation of ground-cooling systems in a saturated subarctic
   peatland
SO COLD REGIONS SCIENCE AND TECHNOLOGY
LA English
DT Article
DE Permafrost; Thermosiphon; Heat transfer; Snow reduction; Peatlands
ID 2-PHASE CLOSED THERMOSIPHON; DISCONTINUOUS PERMAFROST; CLIMATE-CHANGE;
   NORTHWEST-TERRITORIES; SCOTTY CREEK; COLD REGIONS; SNOW; THAW;
   PERFORMANCE; HYDROLOGY
AB The Canadian subarctic is one of the most rapidly warming regions on Earth. Permafrost thaw driven by climate change is linked to rapid landscape transition and is threatening northern infrastructure. Ground cooling systems are used in application-oriented projects largely pertaining to civil engineering operations and have been investigated in mineral-based soils with many successful outcomes. However, in near-saturated and peatdominated environments they remain largely unexplored. The increasing rates of climate change and concomitant landscape evolution coupled with increasing economic activity in the North affirm the growing need for the advancement of ground cooling technologies in saturated peat-based soils. This study compared the performance of three ground cooling systems in saturated peat overlying thawing permafrost at the Scotty Creek Research Station in the Northwest Territories, Canada. The systems included a single-phase active thermosiphon combined with a snow reduction cone (advanced thermosiphon; ATS), a single-phase passive thermosiphon (simple thermosiphon; STS), and two stand-alone snow reduction cones. Performance was assessed based on subsurface temperature profiles (ranging 2017-2022), physical frost table measurements, and estimates of net annual and seasonal heat transfer. Each system displayed distinct ground cooling capabilities, successfully creating, and maintaining frozen ground. The ATS stood out with the highest net annual heat transfer rate, though it requires energy sources for actively circulating the coolant. The STS exhibited slightly lower effectiveness but demonstrated greater resilience to component failure. The snow reduction cone confirmed the significance of snow in ground insulation and augmented the performance of the thermosiphon system, enhancing its overall efficiency. It is anticipated that this study will foster the development of liquid-filled thermosyphons in the domain of cooling technologies, with a particular focus on their application in saturated peat and other similar environments. Moreover, these findings hold significant promise in offering valuable support for climate change adaptation strategies for local communities.
C1 [Mastej, Ela; Wright, Stephanie; Quinton, William] Wilfrid Laurier Univ, Cold Reg Res Ctr, 75 Univ Ave W, Waterloo, ON N2L 3C5, Canada.
   [Mastej, Ela] Univ Guelph, Sch Environm Design & Rural Dev, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada.
   [Wright, Stephanie; Devoie, Elise] Queens Univ, Dept Civil Engn, 58 Univ Ave, Kingston, ON K7L 3N9, Canada.
   [Braverman, Michael] GHD, 40 Bathurst Dr, Waterloo, ON N2V 1V6, Canada.
   [Devoie, Elise] McGill Univ, Dept Earth & Planetary Sci, 845 Rue Sherbrooke O, Montreal, PQ H3A 0G4, Canada.
   [Egorov, Igor] Natl Res Council Canada, 1200 Montreal Rd,Bld M-20, Ottawa, ON K1A 0R6, Canada.
C3 Wilfrid Laurier University; University of Guelph; Queens University -
   Canada; McGill University; National Research Council Canada
RP Mastej, E (corresponding author), Wilfrid Laurier Univ, Cold Reg Res Ctr, 75 Univ Ave W, Waterloo, ON N2L 3C5, Canada.
EM emastej@uoguelph.ca; stephanie.wright@queensu.ca;
   Michael.Braverman@ghd.com; elise.devoie@queensu.ca;
   Igor.Egorov@nrc-cnrc.gc.ca; wquinton@wlu.ca
FU ArcticNet-Dehcho Collaborative on Permafrost [DCoP-P02]; NSERC
   [DF-568264- 2022, PDF-557503-2021]; GHD Consulting; National Research
   Council of Canada
FX We would like to acknowledge that the Scotty Creek Research station is
   located on treaty 11 land. We wish to thank the Dehcho First Nations and
   Liidlii Kue First Nation for their support and partnership in con-
   ducting this research on their traditional lands. We also would like to
   thank acknowledge the Scotty Creek Research Station for hosting this
   research project. Special thanks to Mason Dominico for all his unwa-
   vering technical assistance, Caren Ackley, Dr. Kristine Haynes and Dr.
   Goeff Kershaw for their guidance and support and Dr. Jon Warland for his
   unparalleled insight into the integral fabric of science and humanity. A
   special recognition for the late Dr. Matti Seppalafor his pioneering
   work on snow insulation and palsa formation and deep gratitude for his
   support of this project. This work was supported by ArcticNet-Dehcho
   Collaborative on Permafrost [DCoP-P02], NSERC Postdoctoral Fellowship
   [PDF-568264- 2022; PDF-557503-2021], GHD Consulting and the National
   Research Council of Canada.
CR Ahmed IS, 2021, HEAT TRANSF, V50, P1351, DOI 10.1002/htj.21933
   Azizi M, 2013, IND ENG CHEM RES, V52, P10015, DOI 10.1021/ie401543n
   Badache M, 2019, INVENTIONS-BASEL, V4, DOI 10.3390/inventions4010014
   Bo Z, 2011, COLD REG SCI TECHNOL, V65, P456, DOI 10.1016/j.coldregions.2010.10.012
   Bring A, 2017, EARTHS FUTURE, V5, P72, DOI 10.1002/2016EF000434
   Brown R.J.E., 1963, P 9 INT C PERMAFROST, P125
   Burgess M.M., 2000, Shallow Ground Temperatures, the Physical Environment of the Mackenzie Valley, Northwest Territories: A Base Line for the Assessment of Environmental Change
   Camill P, 1999, ECOSCIENCE, V6, P592, DOI 10.1080/11956860.1999.11682561
   Carpino O, 2021, HYDROL EARTH SYST SC, V25, P3301, DOI 10.5194/hess-25-3301-2021
   Carpino OA, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aad74e
   Carslaw H. S., 1959, Conduction of Heat in Solids, V2nd
   Chasmer L, 2017, GLOBAL CHANGE BIOL, V23, P2672, DOI 10.1111/gcb.13537
   Chen L, 2018, APPL THERM ENG, V128, P1624, DOI 10.1016/j.applthermaleng.2017.09.130
   Cheng GD, 2008, COLD REG SCI TECHNOL, V53, P241, DOI 10.1016/j.coldregions.2007.02.006
   Cline DW, 1997, J APPL METEOROL, V36, P32, DOI 10.1175/1520-0450(1997)036<0032:EOSOSA>2.0.CO;2
   Cohen J., 1994, Weather, V49, P150, DOI 10.1002/j.1477-8696.1994.tb05997.x
   Connon RF, 2015, HYDROL PROCESS, V29, P3831, DOI 10.1002/hyp.10604
   Connon R, 2018, J GEOPHYS RES-EARTH, V123, P281, DOI 10.1002/2017JF004469
   Connon RF, 2014, HYDROL PROCESS, V28, P4163, DOI 10.1002/hyp.10206
   Davidson DJ, 2003, CAN J FOREST RES, V33, P2252, DOI 10.1139/X03-138
   Derksen C., 2015, Bull. Amer. Meteor. Soc., V96, pS133, DOI [10.1175/2015BAMSStateoftheClimate.1, DOI 10.1175/2015BAMSSTATEOFTHECLIMATE.1]
   Devoie ÉG, 2021, J GEOPHYS RES-EARTH, V126, DOI 10.1029/2021JF006204
   Devoie ÉG, 2019, WATER RESOUR RES, V55, P9838, DOI 10.1029/2018WR024488
   Doré G, 2016, PERMAFROST PERIGLAC, V27, P352, DOI 10.1002/ppp.1919
   Edlund J., 1998, Unpublished report by Pacific Environment
   Environment and Climate Change Canada, 2021, Climate Change and Variations Bulletin
   Esch D C., 1988, Embankment Design and Construction in Cold Regions: an ASCE Monograph, P127
   Faria DA, 2000, HYDROL PROCESS, V14, P2683, DOI 10.1002/1099-1085(20001030)14:15<2683::AID-HYP86>3.0.CO;2-N
   Feng WJ, 2006, COLD REG SCI TECHNOL, V45, P51, DOI 10.1016/j.coldregions.2006.01.004
   Forsstrom A.M., 2002, P 11 INT C COLD REGI, P645
   Gagnon S, 2022, COLD REG SCI TECHNOL, V197, DOI 10.1016/j.coldregions.2022.103524
   Garon-Labrecque Marie-Eve, 2015, Canadian Field-Naturalist, V129, P349
   GNWT, 2018, Northern Voices, Northern Waters: NWT Water Stewardship Strategy
   Goetz P., 2010, Masters Thesis
   Hailong He, 2015, Geoderma Regional, V5, P198, DOI 10.1016/j.geodrs.2015.08.001
   Hayashi M, 2007, HYDROL PROCESS, V21, P2610, DOI 10.1002/hyp.6792
   Hayley D., 2004, 57 CANADIAN GEOTECHN
   Hayley D.W., 1983, P 4 INT C PERM FAIRB, VVolume 4, P468
   Haynes KM, 2019, GEOSCI DATA J, V6, P85, DOI 10.1002/gdj3.69
   Heuer C.E., 1979, The Application of Heat Pipes on the Trans-Alaska Pipeline
   Jafarov EE, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aadd30
   Kim M, 2021, CASE STUD THERM ENG, V27, DOI 10.1016/j.csite.2021.101358
   Kondratiev Valentin G., 2013, ISCORD 2013. Planning for Sustainable Cold Regions.10th International Symposium on Cold Regions Development, P191
   Larsen JN, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1567
   Lienhard IV, 2006, A Heat Transfer Textbook, V3rd
   Liston GE, 2011, J CLIMATE, V24, P5691, DOI 10.1175/JCLI-D-11-00081.1
   Liu JJ, 2012, HEALTH TECHNOL ASSES, V16, P1
   Long E.L., 2004, Passive Techniques for Ground Temperature Control, P77, DOI [10.1061/9780784407202.ch04, DOI 10.1061/9780784407202.CH04]
   M-Lepage J., 2012, Proceedings of the 15th International Specialty Conference on Cold Regions Engineering, P42, DOI 10.1061/9780784412473.005
   Malenfant-Lepage J., EXTENDED ABSTRACTS T, P261
   Marshall S, 2003, J CLIMATE, V16, P1062, DOI 10.1175/1520-0442(2003)016<1062:TPOWSC>2.0.CO;2
   McClymont AF, 2013, J GEOPHYS RES-EARTH, V118, P1826, DOI 10.1002/jgrf.20114
   McFadden T., 1985, Performance of the Thermotube Permafrost Stabilization System in the Airport Runway at Bethel, Alaska
   Mellander PE, 2007, CLIMATIC CHANGE, V85, P179, DOI 10.1007/s10584-007-9254-3
   [牛富俊 Niu Fujun], 2010, [冰川冻土, Journal of Glaciology and Geocryology], V32, P325
   Niu FJ, 2008, ACTA GEOL SIN-ENGL, V82, P949
   O'Neill HB, 2017, ARCT SCI, V3, P150, DOI 10.1139/as-2016-0036
   Pei WS, 2019, ENERGY, V179, P655, DOI 10.1016/j.energy.2019.04.156
   Pomeroy JW, 2007, HYDROL PROCESS, V21, P2650, DOI 10.1002/hyp.6787
   Quinton WL, 2013, HYDROGEOL J, V21, P201, DOI 10.1007/s10040-012-0935-2
   Quinton WL, 2011, HYDROL PROCESS, V25, P152, DOI 10.1002/hyp.7894
   Quinton WL, 2009, CAN WATER RESOUR J, V34, P311, DOI 10.4296/cwrj3404311
   Quinton W, 2019, HYDROL EARTH SYST SC, V23, P2015, DOI 10.5194/hess-23-2015-2019
   Quinton WL, 2008, HYDROL PROCESS, V22, P2829, DOI 10.1002/hyp.7027
   Rahman MA, 2014, INT J HEAT MASS TRAN, V73, P693, DOI 10.1016/j.ijheatmasstransfer.2014.02.057
   Raynolds MK, 2014, GLOBAL CHANGE BIOL, V20, P1211, DOI 10.1111/gcb.12500
   Richardson P., 1979, Alaska Constr. Oil, P20
   Richter-Menge J., 2017, The Arctic, V99, P143
   Smith SL, 2010, PERMAFROST PERIGLAC, V21, P117, DOI 10.1002/ppp.690
   Solomon AB, 2017, INT COMMUN HEAT MASS, V82, P9, DOI 10.1016/j.icheatmasstransfer.2017.02.001
   St Jacques JM, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2008GL035822
   Vincent LA, 2015, J CLIMATE, V28, P4545, DOI 10.1175/JCLI-D-14-00697.1
   Wagner A.M., 2014, ERDC/CRREL TR-14-1
   Wen Z, 2005, COLD REG SCI TECHNOL, V43, P150, DOI 10.1016/j.coldregions.2005.04.001
   Williams TJ, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/025006
   Wright SN, 2022, EARTH-SCI REV, V232, DOI 10.1016/j.earscirev.2022.104104
   Wu JJ, 2010, COLD REG SCI TECHNOL, V60, P234, DOI 10.1016/j.coldregions.2009.11.002
   Xu JF, 2008, COLD REG SCI TECHNOL, V53, P283, DOI 10.1016/j.coldregions.2007.09.002
   Zarling J., 1987, Thaw Stabilization of Roadway Embankments Constructed over Permafrost
   Zarling J.P., 1990, PERMAFROST CANADA P
   Zarling J.P., 1986, DRAFT FINAL REPORT (No. FHWA-AK-87-20
   Zhang F, 2015, HYDROL PROCESS, V29, P52, DOI 10.1002/hyp.10125
   Zhang MY, 2016, INT J HEAT MASS TRAN, V95, P1047, DOI 10.1016/j.ijheatmasstransfer.2015.12.067
   Zhang TJ, 2005, REV GEOPHYS, V43, DOI 10.1029/2004RG000157
   ZOLTAI SC, 1975, CAN J EARTH SCI, V12, P28, DOI 10.1139/e75-004
NR 85
TC 0
Z9 0
U1 2
U2 8
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0165-232X
EI 1872-7441
J9 COLD REG SCI TECHNOL
JI Cold Reg. Sci. Tech.
PD FEB
PY 2024
VL 218
AR 104095
DI 10.1016/j.coldregions.2023.104095
EA DEC 2023
PG 15
WC Engineering, Environmental; Engineering, Civil; Geosciences,
   Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology
GA EX5N4
UT WOS:001142245200001
DA 2025-01-10
ER

PT J
AU Sanogo, K
   Toure, I
   Arinloye, DDAA
   Dossou-Yovo, ER
   Bayala, J
AF Sanogo, Kapoury
   Toure, Ibrahim
   Arinloye, Djalalou-Dine A. A.
   Dossou-Yovo, Elliott Ronald
   Bayala, Jules
TI Factors affecting the adoption of climate-smart agriculture technologies
   in rice farming systems in Mali, West Africa
SO SMART AGRICULTURAL TECHNOLOGY
LA English
DT Article
DE Food security; Logistic regression model; Social factors; Technologies
   adoption
ID SUB-SAHARAN AFRICA; FOOD SECURITY; FARMERS; VARIABILITY; IMPACTS; YIELD;
   PERCEPTIONS; CHALLENGES; VARIETIES; TREES
AB Rice is a major staple crop in Mali, yet it is very vulnerable to climate change. Climate-Smart Agriculture (CSA) has been proposed as a solution to simultaneously address the challenges of climate change adaptation, mitigation, and food security. However, there is limited understanding of the factors that influence farmers' decisions to adopt CSA practices in Malian rice farming systems. This study aimed to identify CSA practices in rice farming systems and determine the factors that drive farmers' adoption. We conducted interviews with 440 rice producers, 70% of which were women, and organized 16 focus group discussions (FGDs), including nine exclusively for women, in the Sikasso region of Mali. Data was collected through interviews, surveys, and FGDs. We conducted surveys using a questionnaire and the FGDs and interviews followed a standardized guide. Descriptive statistics were used to explore the data, and we analyzed the factors influencing the adoption of CSA technologies using a logistic regression model. The findings showed that crop diversification, improved rice varieties, crop rotation, tree planting, micro-doses of organic manure, and micro-doses of mineral fertilizer were highly adopted CSA practices in the study area. Key barriers to the successful adoption of CSA practices included limited input availability, lack of control over technologies, insufficient labor availability, insufficient availability and high cost of seedlings for reforestation, lack of information on developed technologies, and limited land access for women and youth. The adoption of CSA technologies was significantly influenced by social factors such as respondents' age, education level, experience in rice production systems, gender, marital status, and membership in a rice producer cooperative. The results of this study are valuable for guiding extension services' approach and implementation to scaling up the adoption of CSA technologies. These findings also underscore the benefit of policies and programs focused on disseminating rice farming system CSA practices.
C1 [Sanogo, Kapoury] Ctr Reg Rech Agron Sotuba, ESPGRN BP, Inst Econ Rurale IER, Bamako, Mali.
   [Sanogo, Kapoury; Toure, Ibrahim] Ctr Int Forestry Res World Agroforestry CIFOR ICRA, Sahel Off, BP 5118, Bamako, Mali.
   [Arinloye, Djalalou-Dine A. A.] Ctr Int Forestry Res World Agroforestry CIFOR ICRA, Benin Off, 08 BP 0932, Tripostal Cotonou, Benin.
   [Dossou-Yovo, Elliott Ronald] Afr Rice Ctr AfricaRice, Dossou Yovo Elliott Ronald, Bouake, Cote Ivoire.
   [Bayala, Jules] Ivoire e Ctr Int Forestry Res World Agroforestry C, Sahel Off, 06 BP 9478, Ouagadougou, Burkina Faso.
C3 CGIAR; Africa Rice Center
RP Sanogo, K (corresponding author), Ctr Reg Rech Agron Sotuba, ESPGRN BP, Inst Econ Rurale IER, Bamako, Mali.
EM k.b.sanogo@cifor-icraf.org
OI SANOGO, Kapoury/0000-0001-6077-5316
FU International Development Association (IDA) of the World Bank [P173398]
FX This study received financial support from the International Development
   Association (IDA) of the World Bank under the project "Accelerating
   Impacts of CGIAR Climate Research for Africa (AICCRA) [P173398]". The
   authors would like to express their gratitude to all the farmers in the
   study area for their patience and cooperation during the survey.
CR Alhassan S. I., 2018, West African Journal of Applied Ecology, V26, P1
   [Anonymous], 2010, CLIM SMART AGR POL P
   Antwi-Agyei P, 2021, REG SUSTAIN, V2, P375, DOI 10.1016/j.regsus.2022.01.005
   Arouna A, 2017, GLOB FOOD SECUR-AGR, V14, P54, DOI 10.1016/j.gfs.2017.03.001
   Arouna Aminou., 2019, Sustainable Solutions for Food Security, P211, DOI 10.1007/978-3-319-77878-5_11
   Autio A, 2021, AGR SYST, V194, DOI 10.1016/j.agsy.2021.103284
   Balasubramanian V, 2007, ADV AGRON, V94, P55, DOI 10.1016/S0065-2113(06)94002-4
   Basak SR, 2015, WEATHER CLIM EXTREME, V7, P43, DOI 10.1016/j.wace.2014.12.002
   Bayala J, 2014, CURR OPIN ENV SUST, V6, P28, DOI 10.1016/j.cosust.2013.10.004
   Butt TA, 2005, CLIMATIC CHANGE, V68, P355, DOI 10.1007/s10584-005-6014-0
   Butt TA, 2006, CLIM POLICY, V5, P583, DOI 10.1080/14693062.2006.9685580
   Campbell BM, 2018, CURR OPIN ENV SUST, V34, P13, DOI 10.1016/j.cosust.2018.06.005
   Campbell BM, 2014, CURR OPIN ENV SUST, V8, P39, DOI 10.1016/j.cosust.2014.07.002
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Chidiebere-Mark N, 2019, OPEN AGRIC, V4, P237, DOI 10.1515/opag-2019-0022
   Defoer T., 2017, Rice based production systems for food security and poverty alleviation in sub Saharan Africa
   Diagne A, 2013, REALIZING AFRICA'S RICE PROMISE, P46, DOI 10.1079/9781845938123.0046
   Dossou-Yovo ER, 2022, FIELD CROP RES, V283, DOI 10.1016/j.fcr.2022.108548
   Dossou-Yovo ER, 2021, FIELD CROP RES, V270, DOI 10.1016/j.fcr.2021.108209
   Dossou-Yovo ER, 2020, FIELD CROP RES, V258, DOI 10.1016/j.fcr.2020.107963
   Dossou-Yovo ER, 2016, SOIL TILL RES, V156, P44, DOI 10.1016/j.still.2015.10.001
   Efisue A, 2008, J AGRON CROP SCI, V194, P393, DOI 10.1111/j.1439-037X.2008.00324.x
   FAO, 2021, FAOSTAT STAT DAT
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   Faye MD, 2010, DEV PRACT, V20, P428, DOI 10.1080/09614521003710013
   Fosu-Mensah B. Y., 2012, Environment Development and Sustainability, V14, P495, DOI 10.1007/s10668-012-9339-7
   Ibrahim A, 2022, ENVIRON SUSTAIN IND, V15, DOI 10.1016/j.indic.2022.100189
   Ibrahim A, 2021, FIELD CROP RES, V266, DOI 10.1016/j.fcr.2021.108149
   IMF, 2018, Poverty Reduction Strategy Paper Progress Report
   Mariano MJ, 2012, AGR SYST, V110, P41, DOI 10.1016/j.agsy.2012.03.010
   Kassa BA, 2022, SAGE OPEN, V12, DOI 10.1177/21582440221121604
   Kifle T, 2022, CLIM SERV, V26, DOI 10.1016/j.cliser.2022.100290
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Marapara TR, 2021, WATER ENVIRON J, V35, P514, DOI 10.1111/wej.12647
   Mutombo P., 2023, Eur. J. Develop. Stud, V1, P74, DOI [10.24018/ejdevelop.2023.3.1.198, DOI 10.24018/EJDEVELOP.2023.3.1.198]
   Nelson G., 2010, Food security, farming, and climate change to 2050: Scenarios, results, policy options
   Neway MM, 2022, COGENT SOC SCI, V8, DOI 10.1080/23311886.2022.2069209
   Niang A, 2017, FIELD CROP RES, V207, P1, DOI 10.1016/j.fcr.2017.02.014
   Onaga G., 2020, JUST ENOUGH NITROGEN, P221, DOI [10.1007/978-3-030-58065-0_15, DOI 10.1007/978-3-030-58065-0_15]
   Ouedraogo M., 2018, CCAFS Info Note
   Parolin P, 2010, AOB PLANTS, DOI 10.1093/aobpla/plq003
   Partey ST, 2020, CLIMATIC CHANGE, V158, P61, DOI 10.1007/s10584-018-2239-6
   Partey ST, 2018, J CLEAN PROD, V187, P285, DOI 10.1016/j.jclepro.2018.03.199
   Rodenburg J, 2022, FIELD CROP RES, V276, DOI 10.1016/j.fcr.2021.108397
   Salusu K, 2022, J. Agric. Agric. Technol., V8, P232
   Sanogo K, 2017, AGROFOREST SYST, V91, P345, DOI 10.1007/s10457-016-9933-z
   Serote B, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11121222
   Soullier G, 2020, GLOB FOOD SECUR-AGR, V25, DOI 10.1016/j.gfs.2020.100365
   Traore B, 2015, EXP AGR, V51, P615, DOI 10.1017/S0014479714000507
   Traore Kalifa, 2019, Journal of Environmental Protection, V10, P1333, DOI 10.4236/jep.2019.1010079
   Truong DD, 2022, FRONT SUSTAIN FOOD S, V6, DOI 10.3389/fsufs.2022.790089
   van Ittersum MK, 2016, P NATL ACAD SCI USA, V113, P14964, DOI 10.1073/pnas.1610359113
   van Oort AJ, 2017, GLOB FOOD SECUR-AGR, V12, P109, DOI 10.1016/j.gfs.2016.09.005
   van Oort PAJ, 2018, GLOBAL CHANGE BIOL, V24, P1029, DOI 10.1111/gcb.13967
   Vermeulen SJ, 2012, ANNU REV ENV RESOUR, V37, P195, DOI 10.1146/annurev-environ-020411-130608
   Zakaria A, 2020, EARTH SYST ENVIRON, V4, P257, DOI 10.1007/s41748-020-00146-w
   Zhang L, 2019, COMPUT ELECTRON AGR, V166, DOI 10.1016/j.compag.2019.105031
   Zossou E, 2020, J AGRIC EDUC EXT, V26, P291, DOI 10.1080/1389224X.2019.1702066
   Zougmoré RB, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13084305
NR 59
TC 16
Z9 16
U1 2
U2 6
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2772-3755
J9 SMART AGR TECHNOL
JI Smart Agric. Technol.
PD OCT
PY 2023
VL 5
AR 100283
DI 10.1016/j.atech.2023.100283
EA JUL 2023
PG 10
WC Agricultural Engineering; Agriculture, Multidisciplinary; Agronomy
WE Emerging Sources Citation Index (ESCI)
SC Agriculture
GA DR8P3
UT WOS:001133889900001
OA gold
DA 2025-01-10
ER

PT J
AU Gong, J
   Jin, TT
   Cao, EJ
   Wang, SM
   Yan, LL
AF Gong, Jie
   Jin, Tiantian
   Cao, Erjia
   Wang, Shimei
   Yan, Lingling
TI Is ecological vulnerability assessment based on the VSD model and
   AHP-Entropy method useful for loessial forest landscape protection and
   adaptative management? A case study of Ziwuling Mountain Region, China
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Spatiotemporal change; Exposure; Sensitivity; Adaptive Capacity;
   Ecological vulnerability index; Hot spot and cluster analysis; Adaptive
   ecological management
ID CLIMATE-CHANGE; SUSTAINABLE DEVELOPMENT; WATER-RESOURCES; GLOBAL CHANGE;
   PLATEAU; SYSTEM; RESTORATION; INDICATORS; VEGETATION; FRAMEWORK
AB Ecological vulnerability assessment is an effective tool to aid decision-makers in understanding the impact of natural and anthropogenic variables on ecosystems. Yet, we know little about incorporating ecological vulner-ability into accurate decision-making for climate change adaptation and human activities governance. This study proposes a comprehensive framework to link the Vulnerability Scoping Diagram (VSD) model, Analytic Hier-archy Process-Entropy method, hot spot and cluster analysis into ecological vulnerability assessment and man-agement in the Ziwuling Mountain Region (ZMR), a typical loessial forest landscape in arid China. There were significant spatial and temporal changes in the exposure, sensitivity, and adaptive capacity index in the ZMR from 1990 to 2017. The exposure and adaptive capacity index increased from 1990 to 2017. The subareas with a high exposure value were distributed in the north and south ZMR, and the subareas with a high adaptive capacity value were distributed in the east ZMR. The ecological vulnerability declined during the study period, with the smaller value subareas allocated in the middle and south ZMR and higher value in the north and southwest. Significant spatial clustering patterns on the hot and cold spots of ecological vulnerability existed in the ZMR. The clustering subareas of hot spots on ecological vulnerability were mainly characterized by dry steppe, less precipitation, and less vegetation coverage. The subareas of cold spots of ecological vulnerability were domi-nated by forestry and forestry-agricultural landscapes. Some suggestions and countermeasures were put forward for adaptive management and sustainability enhancement. Our results provide integrative methods linking the VSD model, AHP-entropy method, hot spot and cluster analysis to ecological vulnerability reduction and adaptive management for dryland sustainability, especially for the forest social-ecological systems in the Chinese Loess Plateau.
C1 [Gong, Jie; Jin, Tiantian; Cao, Erjia; Wang, Shimei; Yan, Lingling] Lanzhou Univ, Key Lab Western Chinas Environm Syst, Minist Educ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China.
C3 Lanzhou University
RP Gong, J (corresponding author), Lanzhou Univ, Key Lab Western Chinas Environm Syst, Minist Educ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China.
EM jgong@lzu.edu.cn
RI Gong, Jie/KMX-8624-2024
FU National Natural Science Foundation of China [4179420015]
FX This work was supported by the National Natural Science Foundation of
   China (Grant numbers 4179420015) . Many thanks to Grammarly Apps (a
   native English Grammar website, https://app.grammarly.com /) , Ginger
   Software (an English Grammar & Writing App, https://
   www.gingersoftware.com /) , as well as Dr. Vanessa Hull of University of
   Florida, USA, for improvement of scientific English writing. Special
   thanks are due to the anonymous reviewers and the editors for their
   helpful comments that improved the manuscript substantially.
CR Abson DJ, 2012, APPL GEOGR, V35, P515, DOI 10.1016/j.apgeog.2012.08.004
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   An S, 2008, CATENA, V75, P248, DOI 10.1016/j.catena.2008.07.003
   Beroya-Eitner MA, 2016, ECOL INDIC, V60, P329, DOI 10.1016/j.ecolind.2015.07.001
   Blanco V, 2017, J ENVIRON MANAGE, V196, P36, DOI 10.1016/j.jenvman.2017.02.066
   Buotte PC, 2016, J ENVIRON MANAGE, V169, P313, DOI 10.1016/j.jenvman.2015.12.017
   Cao E.J., 2020, SPATIOTEMPORAL CHANG, DOI [10.27204/d.cnki.glzhu.2020.000209, DOI 10.27204/D.CNKI.GLZHU.2020.000209]
   Chen C, 2019, NAT SUSTAIN, V2, P122, DOI 10.1038/s41893-019-0220-7
   Chen J, 2018, J GEOGR SCI, V28, P152, DOI 10.1007/s11442-018-1465-1
   [陈佳 Chen Jia], 2016, [地理学报, Acta Geographica Sinica], V71, P1172
   Chen YP, 2015, NAT GEOSCI, V8, P739, DOI 10.1038/ngeo2544
   Cinner JE, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0074321
   Colglazier W, 2015, SCIENCE, V349, P1048, DOI 10.1126/science.aad2333
   de Jong E, 2021, EARTH SYST GOV-NETH, V7, DOI 10.1016/j.esg.2020.100087
   De Lange HJ, 2010, SCI TOTAL ENVIRON, V408, P3871, DOI 10.1016/j.scitotenv.2009.11.009
   [杜婷 Du Ting], 2019, [兰州大学学报. 自然科学版, Journal of Lanzhou University. Natural Science], V55, P26
   Ellison JC, 2015, WETL ECOL MANAG, V23, P115, DOI 10.1007/s11273-014-9397-8
   Farley J, 2016, J ENVIRON MANAGE, V183, P389, DOI 10.1016/j.jenvman.2016.07.065
   Feng XM, 2016, NAT CLIM CHANGE, V6, P1019, DOI [10.1038/NCLIMATE3092, 10.1038/nclimate3092]
   Füssel HM, 2007, GLOBAL ENVIRON CHANG, V17, P155, DOI 10.1016/j.gloenvcha.2006.05.002
   Gabarrón M, 2018, J ENVIRON MANAGE, V206, P192, DOI 10.1016/j.jenvman.2017.10.034
   García-Sánchez IM, 2015, ECOL INDIC, V48, P171, DOI 10.1016/j.ecolind.2014.08.004
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Ghosh S, 2019, REMOTE SENS APPL, V13, P191, DOI 10.1016/j.rsase.2018.10.014
   Guerrero AM, 2018, ECOL SOC, V23, DOI 10.5751/ES-10232-230338
   Hambling T, 2011, INT J ENV RES PUB HE, V8, P2854, DOI 10.3390/ijerph8072854
   He L, 2018, J ENVIRON MANAGE, V206, P1115, DOI 10.1016/j.jenvman.2017.11.059
   Hong WY, 2016, ECOL INDIC, V69, P540, DOI 10.1016/j.ecolind.2016.05.028
   Hu XJ, 2021, ECOL INDIC, V125, DOI 10.1016/j.ecolind.2021.107464
   Jamei Y, 2019, SCI TOTAL ENVIRON, V659, P1335, DOI 10.1016/j.scitotenv.2018.12.308
   Jin TT, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.908057
   Jin Yi, 2011, Shengtaixue Zazhi, V30, P2646
   Kang D, 2014, SCI REP-UK, V4, DOI 10.1038/srep06873
   Kang H, 2018, J CLEAN PROD, V205, P619, DOI 10.1016/j.jclepro.2018.09.109
   Khashei-Siuki A, 2020, GROUNDWATER SUST DEV, V10, DOI 10.1016/j.gsd.2019.100328
   Kim BJ, 2021, INT J DISAST RISK RE, V56, DOI 10.1016/j.ijdrr.2021.102141
   Kou PL, 2021, SCI TOTAL ENVIRON, V778, DOI 10.1016/j.scitotenv.2021.146065
   Kumar M, 2021, ECOL INDIC, V125, DOI 10.1016/j.ecolind.2021.107568
   Lee YJ, 2014, ENVIRON IMPACT ASSES, V44, P31, DOI 10.1016/j.eiar.2013.08.002
   Lei B, 2013, ECO ENV VULNERABILIT
   [李德仁 Li Deren], 2012, [地球信息科学学报, Journal of Geo-Information Science], V14, P419
   [李连伟 Li Lianwei], 2018, [生态环境学报, Ecology and Environmental Sciences], V27, P297
   Li Q, 2021, SCI TOTAL ENVIRON, V761, DOI 10.1016/j.scitotenv.2020.143180
   Li XL, 2016, AMBIO, V45, P350, DOI 10.1007/s13280-015-0727-8
   Lü YH, 2021, CURR OPIN ENV SUST, V48, P1, DOI 10.1016/j.cosust.2020.08.001
   Lü YH, 2015, SCI REP-UK, V5, DOI 10.1038/srep08732
   [马骏 Ma Jun], 2015, [生态学报, Acta Ecologica Sinica], V35, P7117
   Mafi-Gholami D, 2021, J ENVIRON MANAGE, V299, DOI 10.1016/j.jenvman.2021.113573
   Berrouet LM, 2018, ECOL INDIC, V84, P632, DOI 10.1016/j.ecolind.2017.07.051
   Marshall N. A., 2010, A framework for social adaptation to climate change: sustaining tropical coastal communitites and industries
   Ostad-Ali-Askar K, 2018, J WATER CLIM CHANGE, V9, P239, DOI 10.2166/wcc.2018.999
   Ostad-Ali-Askari K, 2019, RIVER RES APPL, V35, P611, DOI 10.1002/rra.3463
   Polsky C, 2007, GLOBAL ENVIRON CHANG, V17, P472, DOI 10.1016/j.gloenvcha.2007.01.005
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Shindell D, 2017, SCIENCE, V356, P493, DOI 10.1126/science.aak9521
   Song GB, 2015, ECOL INDIC, V52, P57, DOI 10.1016/j.ecolind.2014.11.032
   Sun WY, 2015, AGR FOREST METEOROL, V209, P87, DOI 10.1016/j.agrformet.2015.05.002
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Weng HT, 2020, ENVIRON SCI POLLUT R, V27, P20025, DOI 10.1007/s11356-020-08517-6
   Wu CS, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15050855
   Wu XT, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abc0276
   Xia M, 2021, ECOL INDIC, V123, DOI 10.1016/j.ecolind.2020.107274
   [尤南山 You Nanshan], 2020, [地理科学, Scientia Geographica Sinica], V40, P315
   [修丽娜 Xiu Lina], 2019, [水土保持通报, Bulletin of Soil and Water Conservation], V39, P214
   Xu ZC, 2020, NATURE, V577, P74, DOI 10.1038/s41586-019-1846-3
   Zhang XY, 2022, ECOL INDIC, V135, DOI 10.1016/j.ecolind.2022.108586
   Zhao JC, 2018, ECOL INDIC, V91, P410, DOI 10.1016/j.ecolind.2018.04.016
   Zhou B, 2023, J ENVIRON SCI, V123, P3, DOI 10.1016/j.jes.2021.12.008
   Zou TH, 2021, ECOL INDIC, V133, DOI 10.1016/j.ecolind.2021.108429
   Zou TH, 2017, ECOL INDIC, V78, P405, DOI 10.1016/j.ecolind.2017.03.039
NR 70
TC 41
Z9 44
U1 28
U2 119
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD OCT
PY 2022
VL 143
AR 109379
DI 10.1016/j.ecolind.2022.109379
EA SEP 2022
PG 14
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 4Z5SD
UT WOS:000862267300004
OA gold
DA 2025-01-10
ER

PT J
AU Rodrigues, P
   Pedroso, V
   Reis, S
   Yang, CY
   Santos, JA
AF Rodrigues, Pedro
   Pedroso, Vanda
   Reis, Samuel
   Yang, Chenyao
   Santos, Joao A.
TI Climate change impacts on phenology and ripening of cv. Touriga Nacional
   in the Dao wine region, Portugal
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE climate change; Dao wine region; phenological development; Portugal;
   ripening models; Touriga Nacional
ID EUROPEAN GRAPEVINE MOTH; CHANGE PROJECTIONS; MODEL; TEMPERATURE;
   QUALITY; VITICULTURE; YIELD; CLASSIFICATION; REANALYSIS; SCENARIOS
AB The present study is devoted to climate change impact assessment on the phenological development and ripening of cv. Touriga Nacional in the Dao Wine Region, Portugal. For this purpose, the dates of the three main phenological stages (budbreak, flowering and veraison) and two maturity stages are projected for two future periods (2041-2070 and 2071-2100), under two anthropogenic radiative forcing scenarios (RCP4.5 and RCP8.5), and compared against a baseline period (1991-2020). The phenological and maturity stages are simulated using phenological development models (PDMs) and a temperature-based ripeness model (TRM), respectively. An overall advancement in both phenology and ripening stages are identified under future warmer climates, though site-dependent. Furthermore, the advancements in phenology are more pronounced (a) for stages between the beginning of veraison and end of ripening than for the earlier stages, (b) for the long-term future period (2071-2100) under RCP8.5 and (c) for the vineyard site "Viseu." These changes are due to the combination of budbreak advancement with a shortening of some phenophases. The strongest shortening is found in the ripening period, while no significant changes in flowering timings and duration of the berry development period are projected. The advancement and the shortening of the grapevine growing season will shift ripening to the warmest part of the year. This twofold climate change impact of the air temperature on ripening may affect the sugar and organic acid balance, as well as the colour of the must. The current findings can be used by the regional winemaking sector in planning and implementing suitable climate change adaptation to enhance its climate resiliency and sustainability. Subsequent studies for this wine region should be carried out to assess the climate change impacts on late frost risk, on climatic viticultural zoning, on yield and berry quality at harvest.
C1 [Rodrigues, Pedro] Polytech Inst Viseu, CERNAS IPV Res Ctr, Campus Politecn, P-3504510 Repeses, Viseu, Portugal.
   [Pedroso, Vanda] DRAPC Ctr Estudos Vitivinicolas do Dao, Nelas, Portugal.
   [Reis, Samuel] Assoc Desenvolvimento Viticultura Duriense ADVID, CoLAB VINES & WINES Natl Collaborat Lab Portugues, Edificio Ctr Excelencia Vinha E do Vinho, Vila Real, Portugal.
   [Yang, Chenyao; Santos, Joao A.] Univ Tras Os Montes & Alto Douro, Ctr Res & Technol Agroenvironm & Biol Sci CITAB, Vila Real, Portugal.
C3 University of Tras-os-Montes & Alto Douro
RP Rodrigues, P (corresponding author), Polytech Inst Viseu, CERNAS IPV Res Ctr, Campus Politecn, P-3504510 Repeses, Viseu, Portugal.
EM prodrigues@sc.ipv.pt
RI Santos, João/G-8805-2011; Reis, Samuel/AAC-4868-2022; Yang,
   Chenyao/ABA-5249-2021
OI Pedroso, Vanda/0000-0002-4903-1663; Rodrigues,
   Pedro/0000-0002-8309-2910; Santos, Joao Carlos Andrade
   dos/0000-0002-8135-5078; Yang, Chenyao/0000-0002-6079-8689; Reis,
   Samuel/0000-0003-0509-6999
FU European Union's Horizon 2020 Research and Innovation Programme
   [810176]; FCT (Foundation for Science and Technology, I.P)
   [UIDB/00681/2020, UIDB/04033/2020]; CENTRO2020
   [CENTRO-04-3928-FEDER-000001, CENTRO04-3928-FEDER-000028]
FX European Union's Horizon 2020 Research and Innovation Programme,
   Grant/Award Number: 810176; FCT (Foundation for Science and Technology,
   I.P), Grant/Award Numbers: UIDB/00681/2020, UIDB/04033/2020; CENTRO2020,
   Grant/Award Numbers: CENTRO-04-3928-FEDER-000001,
   CENTRO04-3928-FEDER-000028
CR Alikadic A, 2019, AGR FOREST METEOROL, V271, P73, DOI 10.1016/j.agrformet.2019.02.030
   Alves F., 2013, P 18 INT S GIESCO PO
   Blanco-Ward D, 2019, INT J CLIMATOL, V39, P5741, DOI 10.1002/joc.6185
   Caffarra A, 2011, AUST J GRAPE WINE R, V17, P52, DOI 10.1111/j.1755-0238.2010.00118.x
   Caffarra A, 2012, AGR ECOSYST ENVIRON, V148, P89, DOI 10.1016/j.agee.2011.11.017
   Caffarra A, 2010, INT J BIOMETEOROL, V54, P255, DOI 10.1007/s00484-009-0277-5
   Cameron W, 2021, AUST J GRAPE WINE R, V27, P334, DOI 10.1111/ajgw.12481
   Caubel J, 2015, AGR FOREST METEOROL, V207, P94, DOI 10.1016/j.agrformet.2015.02.005
   Coombe B. G., 1995, Australian Journal of Grape and Wine Research, V1, P104, DOI 10.1111/j.1755-0238.1995.tb00086.x
   Cornes RC, 2018, J GEOPHYS RES-ATMOS, V123, P9391, DOI 10.1029/2017JD028200
   Costa C, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10144943
   Costa R, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9040210
   Cuccia C, 2014, J INT SCI VIGNE VIN, V48, P169
   Dahlgren P, 2016, Q J ROY METEOR SOC, V142, P2119, DOI 10.1002/qj.2807
   de Cortázar-Atauri IG, 2017, OENO ONE, V51, P115, DOI 10.20870/oeno-one.2016.0.0.1622
   de Cortázar-Atauri IG, 2009, INT J BIOMETEOROL, V53, P317, DOI 10.1007/s00484-009-0217-4
   Droulia F, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12040495
   Duchêne E, 2005, AGRON SUSTAIN DEV, V25, P93, DOI 10.1051/agro:2004057
   Duchêne E, 2010, CLIM RES, V41, P193, DOI 10.3354/cr00850
   Fernández-González M, 2013, AEROBIOLOGIA, V29, P523, DOI 10.1007/s10453-013-9302-6
   Fraga H, 2016, J AGR SCI-CAMBRIDGE, V154, P795, DOI 10.1017/S0021859615000933
   Fraga H, 2014, REG ENVIRON CHANGE, V14, P295, DOI 10.1007/s10113-013-0490-y
   Fraga H, 2016, GLOBAL CHANGE BIOL, V22, P3774, DOI 10.1111/gcb.13382
   Fraga H, 2015, AM J ENOL VITICULT, V66, P482, DOI 10.5344/ajev.2015.15031
   Fraga H, 2012, CIENC TEC VITIVINIC, V27, P39
   Holzkamper A., 2010, P 10 EMS ANN M
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Jones GV, 2000, AM J ENOL VITICULT, V51, P249
   Jones GV, 2005, CLIMATIC CHANGE, V73, P319, DOI 10.1007/s10584-005-4704-2
   Kartschall T, 2015, METEOROL Z, V24, P189, DOI 10.1127/metz/2015/0534
   Koufos GC, 2018, INT J CLIMATOL, V38, P2097, DOI 10.1002/joc.5320
   Landelius T, 2016, Q J ROY METEOR SOC, V142, P2132, DOI 10.1002/qj.2813
   Leolini L, 2018, FIELD CROP RES, V222, P197, DOI 10.1016/j.fcr.2017.11.018
   Lopes J, 2008, CIENC TEC VITIVINIC, V23, P61
   Lucchetta V, 2019, BIO WEB CONF, V13, DOI 10.1051/bioconf/20191304016
   Magalhaes Nuno., 2008, Tratado de Viticultura - A videira, a vinha e o "terroir": 1A
   Malheiro AC, 2013, J INT SCI VIGNE VIN, V47, P287
   Malheiro AC, 2010, CLIM RES, V43, P163, DOI 10.3354/cr00918
   Mariani L, 2013, INT J BIOMETEOROL, V57, P881, DOI 10.1007/s00484-012-0615-x
   Martinez-Lüscher J, 2016, FRONT ENV SCI-SWITZ, V4, DOI 10.3389/fenvs.2016.00048
   Martins J, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11050990
   Michelini S, 2021, OENO ONE, V55, P159, DOI 10.20870/oeno-one.2021.55.2.4570
   Molitor D, 2014, AUST J GRAPE WINE R, V20, P160, DOI 10.1111/ajgw.12059
   Molitor D, 2019, OENO ONE, V53, P409, DOI 10.20870/oeno-one.2019.53.3.2329
   Molitor D, 2014, AM J ENOL VITICULT, V65, P72, DOI 10.5344/ajev.2013.13066
   Molitor D, 2011, CROP PROT, V30, P1649, DOI 10.1016/j.cropro.2011.07.020
   Morales-Castilla I, 2020, P NATL ACAD SCI USA, V117, P2864, DOI 10.1073/pnas.1906731117
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Ortega-Farias S. O., 2002, Agricultura Tecnica, V62, P27
   Parker AK, 2011, AUST J GRAPE WINE R, V17, P206, DOI 10.1111/j.1755-0238.2011.00140.x
   Parker A, 2013, AGR FOREST METEOROL, V180, P249, DOI 10.1016/j.agrformet.2013.06.005
   Parker AK, 2020, AGR FOREST METEOROL, V285, DOI 10.1016/j.agrformet.2020.107902
   Pereira SC, 2021, CLIMATE, V9, DOI 10.3390/cli9090139
   Piao SL, 2019, GLOBAL CHANGE BIOL, V25, P1922, DOI 10.1111/gcb.14619
   Ramos MC, 2020, VITIS, V59, P181, DOI 10.5073/vitis.2020.59.181-190
   Ramos MC, 2017, AGR FOREST METEOROL, V247, P104, DOI 10.1016/j.agrformet.2017.07.022
   Reis S, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12010098
   Reis S, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10113708
   Rodrigues P., 2016, 10 S VIT AL, V2, P127
   Rodrigues P, 2021, OENO ONE, V55, P337, DOI 10.20870/oeno-one.2021.55.3.4646
   Rodrigues P, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11091777
   Sadras VO, 2008, AUST J GRAPE WINE R, V14, P250, DOI 10.1111/j.1755-0238.2008.00025.x
   Santos JA, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10093092
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Suter B, 2021, FRONT PLANT SCI, V12, DOI 10.3389/fpls.2021.624867
   Tonietto J, 2004, AGR FOREST METEOROL, V124, P81, DOI 10.1016/j.agrformet.2003.06.001
   Van Leeuwen C., 2008, P 7 INT TERR C 19 23, P222
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Verdugo-Vásquez N, 2017, OENO ONE, V51, P277, DOI 10.20870/oeno-one.2017.51.2.1833
   Webb LB, 2007, AUST J GRAPE WINE R, V13, P165, DOI 10.1111/j.1755-0238.2007.tb00247.x
   Xu YW, 2012, CLIM DYNAM, V39, P1613, DOI 10.1007/s00382-011-1284-x
   Yan YF, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.01095
   Yang CY, 2019, CLIMATIC CHANGE, V154, P159, DOI 10.1007/s10584-019-02419-4
   Yang W, 2010, HYDROL RES, V41, P211, DOI 10.2166/nh.2010.004
   Zarrouk O, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01640
   Zheng W, 2017, VITIS, V56, P27, DOI 10.5073/vitis.2017.56.27-33
NR 76
TC 9
Z9 9
U1 2
U2 29
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD NOV 30
PY 2022
VL 42
IS 14
BP 7117
EP 7132
DI 10.1002/joc.7633
EA APR 2022
PG 16
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA 6C0AH
UT WOS:000781000000001
DA 2025-01-10
ER

PT J
AU Qi, L
   Liu, T
   Gao, Y
   Li, Q
   Tang, WG
   Tian, DC
   Su, K
   Xiong, Y
   Yang, J
   Feng, LZ
   Liu, QY
AF Qi, Li
   Liu, Tian
   Gao, Yuan
   Li, Qin
   Tang, Wenge
   Tian, Dechao
   Su, Kun
   Xiong, Yu
   Yang, Jun
   Feng, Luzhao
   Liu, Qiyong
TI Effect of absolute humidity on influenza activity across different
   climate regions in China
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE Influenza; Absolute humidity; Distributed lag nonlinear model
ID ILLNESS; TEMPERATURE; MORTALITY; SEASONALITY; EPIDEMICS; PATTERNS;
   DRIVERS; BURDEN
AB Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m(3) and 6.62 g/m(3). In Guangdong and Hainan, located in southernmost China, the risk of influenza activity increased with rising average AHmean with 16.74 g/m(3) and 20.18 g/m(3) as the break points. In Shanghai, Zhejiang, and Chongqing, the relationship between weekly average AHmean and influenza could be described as U-shaped curves, with the lowest RRs when weekly average AHmean was 11.95 g/m(3), 11.94 g/m(3), and 15.96 g/m(3), respectively. Meta-analysis results showed the cumulative RRs significantly increased as weekly average AHmean fell below 3.86 g/m(3) in the northern region, whereas significantly increased as weekly average AHmean rose above 18.46 g/m(3) and 15.22 g/m(3) in intermediate and southernmost regions, respectively. Both low and high AH might increase influenza risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.
C1 [Qi, Li; Li, Qin; Tang, Wenge; Su, Kun; Xiong, Yu] Chongqing Municipal Ctr Dis Control & Prevent, Chongqing 400042, Peoples R China.
   [Qi, Li; Liu, Qiyong] Chinese Ctr Dis Control & Prevent, State Key Lab Infect Dis Prevent & Control, Collaborat Innovat Ctr Diag & Treatment Infect Di, Natl Inst Communicable Dis Control & Prevent, Beijing 102206, Peoples R China.
   [Liu, Tian] Jingzhou Ctr Dis Control & Prevent, Jingzhou 434000, Hubei, Peoples R China.
   [Gao, Yuan] Monash Univ, Sch Publ Hlth & Prevent Med, Melbourne, Vic, Australia.
   [Tian, Dechao] Sun Yat Sen Univ, Sch Publ Hlth Shenzhen, Shenzhen 518107, Peoples R China.
   [Yang, Jun] Guangzhou Med Univ, Sch Publ Hlth, Guangzhou 511436, Peoples R China.
   [Feng, Luzhao] Chinese Acad Med Sci & Peking Union Med Coll, Sch Populat Med & Publ Hlth, Beijing 100730, Peoples R China.
C3 Chinese Center for Disease Control & Prevention; National Institute for
   Communicable Disease Control & Prevention, Chinese Center for Disease
   Control & Prevention; Collaborative Innovation Center for Diagnosis &
   Treatment of Infectious Diseases; Monash University; Sun Yat Sen
   University; Guangzhou Medical University; Chinese Academy of Medical
   Sciences - Peking Union Medical College; Peking Union Medical College
RP Liu, QY (corresponding author), Chinese Ctr Dis Control & Prevent, State Key Lab Infect Dis Prevent & Control, Collaborat Innovat Ctr Diag & Treatment Infect Di, Natl Inst Communicable Dis Control & Prevent, Beijing 102206, Peoples R China.; Yang, J (corresponding author), Guangzhou Med Univ, Sch Publ Hlth, Guangzhou 511436, Peoples R China.; Feng, LZ (corresponding author), Chinese Acad Med Sci & Peking Union Med Coll, Sch Populat Med & Publ Hlth, Beijing 100730, Peoples R China.
EM qili19812012@126.com; jzcdclt@163.com; gaoyuancdc@126.com;
   Qinlicdc@163.com; wengetang@163.com; tiandch@mail.sysu.edu.cn;
   260617392@qq.com; 29864800@qq.com; yangjun_eci@jnu.edu.cn;
   fengluzhao@cams.cn; liuqiyong@icdc.cn
RI Dechao, Tian/AAH-3719-2020; Li, Yong/AAA-1220-2022; Liu,
   TIAN/LSI-8155-2024
OI Liu, Qiyong/0000-0003-4066-7988
FU High-level Medical Reserved Personnel Training Project of Chongqing,
   Chongqing Health Commission Program [2019GDRC014]; Chongqing Science and
   Technology Bureau Program [CSTC2021 jscx-gksb-N0005]; China Postdoctoral
   Science Foundation [2019M660754]; National Natural Science Foundation of
   China [82003552]; Guangdong Basic and Applied Basic Research Foundation
   [2020A1515011161]; Ministry of Ecology and Environment of the People's
   Republic of China [202046]; China Prosperity Strategic Programme Fund
   (SPF) [15LCI1]; UK-China Cooperation on Climate Change Risk Assessment
   [PF3051_CH-WS3HBUE_YR1]; Academy of Finland (AKA) [202046] Funding
   Source: Academy of Finland (AKA)
FX Dr. Li Qi was supported by the High-level Medical Reserved Personnel
   Training Project of Chongqing, Chongqing Health Commission Program
   (grant number 2019GDRC014), Chongqing Science and Technology Bureau
   Program(grant number CSTC2021 jscx-gksb-N0005) and China Postdoctoral
   Science Foundation (grant number 2019M660754). Dr. Jun Yang was
   supported by the National Natural Science Foundation of China (No.
   82003552), and the Guangdong Basic and Applied Basic Research Foundation
   (No. 2020A1515011161). Dr. Qiyong Liu was supported by the Project
   commissioned by the Ministry of Ecology and Environment of the People's
   Republic of China (No. 202046), the China Prosperity Strategic Programme
   Fund (SPF) 2015-16 (Project Code: 15LCI1), and the UK-China Cooperation
   on Climate Change Risk Assessment (PF3051_CH-WS3HBUE_YR1).
CR Bai YL, 2019, PEERJ, V7, DOI 10.7717/peerj.6919
   Barreca AI, 2012, AM J EPIDEMIOL, V176, pS114, DOI 10.1093/aje/kws259
   Caini S, 2018, ENVIRON RES, V167, P307, DOI 10.1016/j.envres.2018.07.035
   Charland KML, 2009, EPIDEMIOL INFECT, V137, P1377, DOI 10.1017/S0950268809002283
   Chen RJ, 2018, BMJ-BRIT MED J, V363, DOI 10.1136/bmj.k4306
   Chong KC, 2020, SCI TOTAL ENVIRON, V703, DOI 10.1016/j.scitotenv.2019.134727
   Chong KC, 2020, J INFECTION, V80, P84, DOI 10.1016/j.jinf.2019.09.013
   Dai QG, 2018, SCI TOTAL ENVIRON, V645, P684, DOI 10.1016/j.scitotenv.2018.07.065
   Davis RE, 2016, INFLUENZA OTHER RESP, V10, P310, DOI 10.1111/irv.12369
   Descalzo MA, 2016, INFLUENZA OTHER RESP, V10, P340, DOI 10.1111/irv.12385
   Deyle ER, 2016, P NATL ACAD SCI USA, V113, P13081, DOI 10.1073/pnas.1607747113
   Emukule GO, 2016, INFLUENZA OTHER RESP, V10, P375, DOI 10.1111/irv.12393
   Feng LZ, 2020, INFLUENZA OTHER RESP, V14, P162, DOI 10.1111/irv.12711
   Fuhrmann C, 2010, GEOGR COMPASS, V4, DOI 10.1111/j.1749-8198.2010.00343.x
   Gasparrini A, 2012, STAT MED, V31, P3821, DOI 10.1002/sim.5471
   Gasparrini A, 2010, STAT MED, V29, P2224, DOI 10.1002/sim.3940
   Gasparrini A, 2013, BMC MED RES METHODOL, V13, DOI 10.1186/1471-2288-13-1
   Guo QZ, 2019, INFLUENZA OTHER RESP, V13, P166, DOI 10.1111/irv.12617
   Iuliano AD, 2018, LANCET, V391, P1285, DOI 10.1016/S0140-6736(17)33293-2
   Koep TH, 2013, BMC INFECT DIS, V13, DOI 10.1186/1471-2334-13-71
   Lowen AC, 2014, J VIROL, V88, P7692, DOI 10.1128/JVI.03544-13
   Mahamat A, 2013, J INFECTION, V67, P141, DOI 10.1016/j.jinf.2013.03.018
   Palekar RS, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0221479
   Peci A, 2019, APPL ENVIRON MICROB, V85, DOI 10.1128/AEM.02426-18
   Thai PQ, 2015, EPIDEMICS-NETH, V13, P65, DOI 10.1016/j.epidem.2015.06.002
   Qi L, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0246023
   Qi L, 2020, HUM VACC IMMUNOTHER, V16, P1668, DOI 10.1080/21645515.2019.1693721
   Qi L, 2020, SCI TOTAL ENVIRON, V716, DOI 10.1016/j.scitotenv.2020.136682
   Qi L, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0167866
   Shaman J, 2017, PLOS COMPUT BIOL, V13, DOI 10.1371/journal.pcbi.1005844
   Shaman J, 2010, PLOS BIOL, V8, DOI 10.1371/journal.pbio.1000316
   Shaman J, 2009, P NATL ACAD SCI USA, V106, P3243, DOI 10.1073/pnas.0806852106
   Shoji M, 2011, TOHOKU J EXP MED, V224, P251, DOI 10.1620/tjem.224.251
   Soebiyanto RP, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0134701
   Soebiyanto RP, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0100659
   Su W, 2020, PEERJ, V8, DOI 10.7717/peerj.8626
   Tamerius J, 2011, ENVIRON HEALTH PERSP, V119, P439, DOI 10.1289/ehp.1002383
   Tamerius JD, 2013, PLOS PATHOG, V9, DOI 10.1371/journal.ppat.1003194
   Xie X, 2007, INDOOR AIR, V17, P211, DOI 10.1111/j.1600-0668.2007.00469.x
   Yang J, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21305-1
   Yu HJ, 2013, PLOS MED, V10, DOI 10.1371/journal.pmed.1001552
   Zhang YZ, 2020, SCI TOTAL ENVIRON, V701, DOI 10.1016/j.scitotenv.2019.134607
NR 42
TC 6
Z9 7
U1 2
U2 14
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0944-1344
EI 1614-7499
J9 ENVIRON SCI POLLUT R
JI Environ. Sci. Pollut. Res.
PD JUL
PY 2022
VL 29
IS 32
BP 49373
EP 49384
DI 10.1007/s11356-022-19279-8
EA FEB 2022
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 2R0DZ
UT WOS:000761875000006
PM 35218485
DA 2025-01-10
ER

PT J
AU Chippagiri, R
   Gavali, HR
   Ralegaonkar, RV
   Riley, M
   Shaw, A
   Bras, A
AF Chippagiri, Ravijanya
   Gavali, Hindavi R.
   Ralegaonkar, Rahul V.
   Riley, Mike
   Shaw, Andy
   Bras, Ana
TI Application of Sustainable Prefabricated Wall Technology for Energy
   Efficient Social Housing
SO SUSTAINABILITY
LA English
DT Article
DE sustainable urban housing; bio-based construction products; prefab
   panels; cost comparison; peak cooling load
AB Under the India "Housing for all" scheme, 20 million urban houses have to be constructed by 2022, which requires the rate of construction to be around 8000 houses/day. Previous results by the team show that present design methods for affordable buildings and structures in India need improvement. The challenges are the disposal of solid waste generated from agro-industrial activities and the energy peak demand in extremely hot and cold seasons. The development of bio-based urban infrastructure which can adapt to the climatic conditions has been proposed. Inclusion of sustainable materials such as agro-industrial by-products and insulation materials has resulted in effective environmental sustainability and climate change adaptability. Precast components are highlighted as a suitable solution for this purpose as well as to fulfil the need of mass housing. India has a lesser record in implementing this prefab technology when compared to a global view. For the first time, a novel and sustainable prefab housing solution is tested for scale-up using industrial waste of co-fired blended ash (CBA) and the results are presented here. A model house of real scale measuring 3 x 3 x 3 m(3) was considered as a base case and is compared with 17 other combinations of model house with varying alignment of prefab panels. Comparison was made with commercially available fly ash brick and CBA brick with a conventional roof slab. A simulation study was conducted regarding cost and energy analysis for all the 18 cases. Various brick and panel compositions with CBA for housing were tried and the superior composition was selected. Similarly, 18 model houses of real scale were simulated, with different combinations of walls made of bricks or panels and different building orientations, to check the impact on energy peak cooling and cost. Results show that peak cooling load can be reduced by six times with bio-based prefab panels. Prefab construction can be considered for mass housing ranging above 100 housing units, each consisting of an area of 25 m(2).
C1 [Chippagiri, Ravijanya; Gavali, Hindavi R.; Ralegaonkar, Rahul V.] VNIT, Dept Civil Engn, Nagpur 440010, Maharashtra, India.
   [Riley, Mike; Shaw, Andy; Bras, Ana] Liverpool John Moores Univ, Built Environm & Sustainable Technol BEST Res Ins, Liverpool L3 3AF, Merseyside, England.
C3 National Institute of Technology (NIT System); Visvesvaraya National
   Institute of Technology, Nagpur; Liverpool John Moores University
RP Chippagiri, R (corresponding author), VNIT, Dept Civil Engn, Nagpur 440010, Maharashtra, India.
EM ravijanya991@gmail.com; gavali.hr@gmail.com; sanvan28@yahoo.com;
   m.l.riley@ljmu.ac.uk; A.Shaw@ljmu.ac.uk; a.m.armadabras@ljmu.ac.uk
RI Chippagiri, Ravijanya/ISV-4841-2023; Rals, Rahul/AAE-4417-2019; Gavali,
   Hindavi/AAE-4427-2019; Bras, Ana/JVO-1626-2024; Bras, Ana/E-7795-2015;
   ralegaonkar, rahul/O-5198-2015
OI Bras, Ana/0000-0002-6292-2073; GAVALI, HINDAVI/0000-0003-4022-4589;
   Shaw, Andy/0000-0001-5961-2464; ralegaonkar, rahul/0000-0002-3538-533X;
   Chippagiri, Ravijanya/0000-0002-1698-8282
FU LJMU Global Challenge Research Fund 2018-2020
FX This research was supported by funding under the grant LJMU Global
   Challenge Research Fund 2018-2020.
CR [Anonymous], 2017, GOV INDIA, V2017, P1
   [Anonymous], 2019, United Nations: Climate action and supported trend
   Bras A, 2020, ENERG BUILDINGS, V220, DOI 10.1016/j.enbuild.2020.110030
   Chirisa I, 2016, DEV SO AFR, V33, P113, DOI 10.1080/0376835X.2015.1113122
   Dave M, 2017, PROCEDIA ENGINEER, V180, P676, DOI 10.1016/j.proeng.2017.04.227
   Department of Economic and Social Affairs U.N., 2020, INDIA POPULATION
   Dineshkumar N., 2015, Int. J. Innov. Sci. Eng. Technol, V2, P527
   Einea A., 1991, PCI J, V36, P7892, DOI DOI 10.15554/PCIJ.11011991.78.98
   Ferdous W, 2019, ENG STRUCT, V183, P883, DOI 10.1016/j.engstruct.2019.01.061
   Gavali HR, 2020, J CLEAN PROD, V254, DOI 10.1016/j.jclepro.2020.120061
   Gavali HR, 2019, CONSTR BUILD MATER, V215, P180, DOI 10.1016/j.conbuildmat.2019.04.152
   GoI I, 2020, CEMENT IND INDIA, V25
   GoI I, 2019, INDIAN STEEL IND REP
   Ha S, 2017, J MANAGE ENG, V33, DOI 10.1061/(ASCE)ME.1943-5479.0000530
   Jaillon L, 2008, CONSTR MANAG ECON, V26, P953, DOI 10.1080/01446190802259043
   Khosravani MR, 2020, APPL MATER TODAY, V20, DOI 10.1016/j.apmt.2020.100689
   Khosravani MR, 2019, ENG STRUCT, V201, DOI 10.1016/j.engstruct.2019.109844
   Kim Y, 2019, EARTHS FUTURE, V7, P704, DOI 10.1029/2019EF001208
   Krishnanunny M., 2018, INT J PURE APPL MATH, V119, P1339
   Li ZD, 2014, HABITAT INT, V43, P240, DOI 10.1016/j.habitatint.2014.04.001
   Madurwar MV, 2015, J ENERG ENG, V141, DOI 10.1061/(ASCE)EY.1943-7897.0000200
   Malviya RK, 2020, MATER TODAY-PROC, V26, P3157, DOI 10.1016/j.matpr.2020.02.651
   Mao C, 2016, HABITAT INT, V57, P215, DOI 10.1016/j.habitatint.2016.08.002
   Naito C, 2012, J STRUCT ENG-ASCE, V138, P52, DOI 10.1061/(ASCE)ST.1943-541X.0000430
   O'Hegarty R, 2020, CONSTR BUILD MATER, V233, DOI 10.1016/j.conbuildmat.2019.117145
   Ram S, 2018, P I CIVIL ENG-ENG SU, V171, P425, DOI 10.1680/jensu.17.00008
   Riza F. V., 2010, CSSR 2010 2010 INT C, P999, DOI [10.1109/CSSR.2010.5773936, DOI 10.1109/CSSR.2010.5773936]
   Rodriguez RS, 2018, NAT CLIM CHANGE, V8, P181, DOI 10.1038/s41558-018-0098-9
   Sakhare VV, 2016, J CLEAN PROD, V112, P684, DOI 10.1016/j.jclepro.2015.07.088
   Steinhardt DA, 2016, SUSTAIN CITIES SOC, V22, P126, DOI 10.1016/j.scs.2016.02.008
   Tibrewal K., 2019, CLIM CHANG SIGNALS R, P211, DOI [10.1007/978-981-13-0280-0_13, DOI 10.1007/978-981-13-0280-0_13]
   Tiwari P, 2001, BUILD ENVIRON, V36, P1127, DOI 10.1016/S0360-1323(00)00056-1
   USAID, 2012, Sampling and household listing manual:demographic and health survey, P1
   van Ruijven BJ, 2016, RESOUR CONSERV RECY, V112, P15, DOI 10.1016/j.resconrec.2016.04.016
NR 34
TC 23
Z9 23
U1 4
U2 25
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD FEB
PY 2021
VL 13
IS 3
AR 1195
DI 10.3390/su13031195
PG 12
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA QD6IZ
UT WOS:000615620600001
OA Green Accepted, gold, Green Published
DA 2025-01-10
ER

PT J
AU Lee, YJ
   Lin, SY
AF Lee, Yung-Jaan
   Lin, Shih-Ying
TI Vulnerability and ecological footprint: a comparison between urban
   Taipei and rural Yunlin, Taiwan
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article; Proceedings Paper
CT 5th International Conference on Water Resource and Environment (WRE) /
   1st International Conference on Advances in Civil and Ecological
   Engineering Research (ACEER)
CY JUN 16-19, 2019
CL Macau Univ Sci & Technol, Macao, PEOPLES R CHINA
HO Macau Univ Sci & Technol
DE Climate change adaptation; Biophysical vulnerability; Social
   vulnerability; Integrated vulnerability; Ecological footprint
ID CLIMATE-CHANGE; SOCIAL VULNERABILITY; MEDITERRANEAN CITIES; LAND
   SUBSIDENCE; RESILIENCE; INDICATORS; HAZARDS; CITY; ADAPTATION; SCIENCE
AB Climate change issues and adaptation strategies have drawn much attention from many fields in recent years. Taiwan, an island state, is deeply threatened by the multiple threats posed by climate change. However, different urban and rural areas have numerous adaptation approaches due to their differences in vulnerability. In Taipei City (urban), its biophysical vulnerability is mainly affected by flooded areas and high flood depths caused by landslides and heavy rains. Its social vulnerability is affected by economic development, high household assets, and population concentration. In Yunlin County (rural), its biophysical vulnerability is also affected by flooded areas and high flood depths caused by heavy rains. Its social vulnerability is affected by the elderly living alone, low household assets, and low healthcare. In order to propose appropriate adaptation strategies of urban and rural areas under different vulnerabilities, this study uses an overlapping method to examine the relationship between the integrated vulnerability (biophysical and social) of Taipei and Yunlin along with the ecological footprint (EF), a measurement of human demands for resources and ecological services. This study reviews the literature and uses Taiwan's NCDR (National Science and Technology Center for Disaster Reduction) data to analyze the biophysical vulnerability and the social vulnerability and further calculate the integrated vulnerability. In this study, questionnaire surveys were conducted. In Taipei, 446 valid questionnaires were collected, while 393 were collected in Yunlin. The results show that personal EF in Taipei is higher than that in Yunlin. In the end, this study elucidates the relationship between integrated vulnerability and personal EF of Taipei and Yunlin. Four types of risk areas in urban Taipei and rural Yunlin are sorted out (high vulnerability/high EF, high vulnerability/low EF, low vulnerability/high EF, and low vulnerability/low EF). The empirical results can be adopted by local governments, communities, and NGOs to establish appropriate strategies for mitigation and adaptation in the different risk areas.
C1 [Lee, Yung-Jaan; Lin, Shih-Ying] Chung Hua Inst Econ Res, Taipei, Taiwan.
RP Lee, YJ (corresponding author), Chung Hua Inst Econ Res, Taipei, Taiwan.
EM yungjaanlee@gmail.com
CR Alam GMM, 2017, CLIM RISK MANAG, V17, P52, DOI 10.1016/j.crm.2017.06.006
   [Anonymous], 2004, TYNDALL CTR CLIMATE
   [Anonymous], 2015, WEO 2015 SPEC REP EN
   [Anonymous], J ENV PUBLIC HLTH
   [Anonymous], 2007, CLIMATE CHANGE 2007
   [Anonymous], 1994, Report by the GEF to the Intergovernmental Negotiating Committee for a Framework Convention on Climate Change on the Restructured Global Environment Facility A/AC.237/89, Annex I
   [Anonymous], 2012, NATL FOOTNAT FOOTPR
   Baabou W, 2017, ENVIRON SCI POLICY, V69, P94, DOI 10.1016/j.envsci.2016.12.013
   Bagliani M, 2003, ADV ECOL SCI, V18-19, P387
   Bagliani M, 2008, ECOL ECON, V65, P650, DOI 10.1016/j.ecolecon.2008.01.010
   Bevacqua A, 2018, ENVIRON SCI POLICY, V82, P19, DOI 10.1016/j.envsci.2018.01.006
   Chang HS, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-6294-x
   Nguyen CV, 2017, CLIMATIC CHANGE, V143, P355, DOI 10.1007/s10584-017-2012-2
   Cutter SL, 2003, ANN ASSOC AM GEOGR, V93, P1, DOI 10.1111/1467-8306.93101
   Cutter SL, 2014, GLOBAL ENVIRON CHANG, V29, P65, DOI 10.1016/j.gloenvcha.2014.08.005
   Fang K, 2014, ECOL INDIC, V36, P508, DOI 10.1016/j.ecolind.2013.08.017
   Fletcher TD, 2015, URBAN WATER J, V12, P525, DOI 10.1080/1573062X.2014.916314
   Galli A, 2015, ENVIRON SCI POLICY, V51, P125, DOI 10.1016/j.envsci.2015.04.002
   Garbutt K, 2015, ENVIRON HAZARDS-UK, V14, P156, DOI 10.1080/17477891.2015.1028018
   Garcia-Ayllon S, 2018, WATER-SUI, V10, DOI 10.3390/w10111642
   GFN, 2018, HAS HUM EC FOOTPR RE
   Gu HH, 2018, SUSTAIN CITIES SOC, V41, P170, DOI 10.1016/j.scs.2018.05.047
   Hsu WC, 2015, REMOTE SENS-BASEL, V7, P8202, DOI 10.3390/rs70608202
   Hung HC, 2016, LAND USE POLICY, V50, P48, DOI 10.1016/j.landusepol.2015.08.029
   IPCC, 2017, IPCC AGR OUTL 6 ASS
   Jabareen Y, 2015, LECT N ENERG, V29, P1, DOI 10.1007/978-94-017-9768-9
   Jabareen Y, 2013, CITIES, V31, P220, DOI 10.1016/j.cities.2012.05.004
   Jha A., 2015, DISASTER RISK REDUCT, P7
   Jha CK, 2018, INT J CLIM CHANG STR, V10, P121, DOI 10.1108/IJCCSM-03-2017-0059
   Jiang Y, 2018, ENVIRON SCI POLICY, V80, P132, DOI 10.1016/j.envsci.2017.11.016
   Joseph J, 2013, DISASTERS, V37, P185, DOI 10.1111/j.1467-7717.2012.01299.x
   Khailani DK, 2013, LAND USE POLICY, V30, P615, DOI 10.1016/j.landusepol.2012.05.003
   Lee YJ, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10082663
   Lee YJ, 2017, IOP C SER EARTH ENV, V94, DOI 10.1088/1755-1315/94/1/012161
   Lee YJ, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8010064
   Lee YJ, 2015, ENVIRON IMPACT ASSES, V54, P1, DOI 10.1016/j.eiar.2015.04.004
   Lee YJ, 2014, ENVIRON IMPACT ASSES, V44, P31, DOI 10.1016/j.eiar.2013.08.002
   Lin WY, 2016, GEOMAT NAT HAZ RISK, V7, P1659, DOI 10.1080/19475705.2015.1084542
   M aplecroft, 2011, WORLDS FAST GROW POP
   Marigi N.S., 2017, American Journal of Climate Change, V6, P52, DOI DOI 10.4236/AJCC.2017.61004
   Mavromatidi A, 2018, CITIES, V72, P189, DOI 10.1016/j.cities.2017.08.007
   McBain B, 2018, RESOURCES-BASEL, V7, DOI 10.3390/resources7020024
   McBain B, 2017, GLOBAL PLANET CHANGE, V155, P13, DOI 10.1016/j.gloplacha.2017.06.002
   McDonald GW, 2004, ECOL ECON, V50, P49, DOI 10.1016/j.ecolecon.2004.02.008
   Menoni S, 2012, NAT HAZARDS, V64, P2057, DOI 10.1007/s11069-012-0134-4
   NCDR, 2016, DIS POT MAP WEBS
   Niccolucci V, 2012, ECOL INDIC, V16, P23, DOI 10.1016/j.ecolind.2011.09.002
   Rajesh S, 2018, ECOL INDIC, V85, P93, DOI 10.1016/j.ecolind.2017.10.014
   Senapati S, 2017, MAR POLICY, V76, P90, DOI 10.1016/j.marpol.2016.11.023
   Spaans M, 2017, CITIES, V61, P109, DOI 10.1016/j.cities.2016.05.011
   Tung H, 2012, TECTONOPHYSICS, V578, P126, DOI 10.1016/j.tecto.2012.08.009
   Vogel C, 2007, GLOBAL ENVIRON CHANG, V17, P349, DOI 10.1016/j.gloenvcha.2007.05.002
   Wackernagel M, 2014, J IND ECOL, V18, P20, DOI 10.1111/jiec.12094
   Wang YT, 2017, RESOUR CONSERV RECY, V122, P11, DOI 10.1016/j.resconrec.2017.02.002
   Wei YG, 2015, SUSTAINABILITY-BASEL, V7, P3244, DOI 10.3390/su7033244
   Xia J, 2017, SCI CHINA EARTH SCI, V60, P652, DOI 10.1007/s11430-016-0111-8
   Zhang XL, 2018, CITIES, V72, P141, DOI 10.1016/j.cities.2017.08.009
NR 57
TC 7
Z9 7
U1 3
U2 66
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0944-1344
EI 1614-7499
J9 ENVIRON SCI POLLUT R
JI Environ. Sci. Pollut. Res.
PD OCT
PY 2020
VL 27
IS 28
SI SI
BP 34624
EP 34637
DI 10.1007/s11356-019-05251-6
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Environmental Sciences & Ecology
GA NH9ZY
UT WOS:000565020300006
DA 2025-01-10
ER

PT J
AU Zhao, YJ
   Sushama, L
AF Zhao, Yijie
   Sushama, Laxmi
TI Aircraft Takeoff Performance in a Changing Climate for Canadian Airports
SO ATMOSPHERE
LA English
DT Article
DE climate change; aviation; aircraft performance; maximum daily
   temperature; weight restriction day; crosswind; tailwind
ID MULTISCALE GEM MODEL; PROJECTED CHANGES; BOUNDARY-LAYER; WIND;
   PARAMETERIZATION; TEMPERATURES; TURBULENCE; IMPACT
AB Temperature and wind are major meteorological factors that affect the takeoff and landing performance of aircraft. Warmer temperatures and the associated decrease in air density in future climate, and changes to crosswind and tailwind, can potentially impact aircraft performance. This study evaluates projected changes to aircraft takeoff performance, in terms of weight restriction days and strong tailwind and crosswind occurrences, for 13 major airports across Canada, for three categories of aircraft used for long-, medium- and short-haul flights. To this end, two five-member ensembles of transient climate change simulations performed with a regional climate model, for Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, respectively, are analyzed. Results suggest that the projected increases in weight restriction days associated with the increases in daily maximum temperatures vary with aircraft category and airfield location, with larger increases noted for airfields in the south central regions of Canada. Although avoiding takeoff during the warmest period of the day could be a potential solution, analysis focused on the warmest and coolest periods of the day suggests more weight restriction hours even during the coolest period of the day, for these airfields. Though RCP8.5 in general suggests larger changes to weight restriction hours compared to RCP4.5, the differences between the two scenarios are more prominent for the coolest part of the day, as projected changes to daily minimum temperatures occur at a much faster rate for RCP8.5 compared to RCP4.5, and also due to the higher increases in daily minimum temperatures compared to maximum temperatures. Both increases and decreases to crosswind and tailwind are projected, which suggest the need for detailed case studies, especially for those airfields that suggest increases. This study provides useful preliminary insights related to aircraft performance in a warmer climate, which will be beneficial to the aviation sector in developing additional analysis and to support climate change adaptation-related decision-making.
C1 [Zhao, Yijie] McGill Univ, Dept Civil Engn & Appl Mech, Montreal, PQ H3A 0C3, Canada.
   McGill Univ, Trottier Inst Sustainabil Engn & Design, Montreal, PQ H3A 0C3, Canada.
C3 McGill University; McGill University
RP Zhao, YJ (corresponding author), McGill Univ, Dept Civil Engn & Appl Mech, Montreal, PQ H3A 0C3, Canada.
EM yijie.zhao@mail.mcgill.ca; laxmi.sushama@mcgill.ca
FU National Sciences and Engineering Research Council of Canada; Trottier
   Institute for Sustainability in Engineering and Design
FX This research was funded by the National Sciences and Engineering
   Research Council of Canada and the Trottier Institute for Sustainability
   in Engineering and Design.
CR [Anonymous], 2018, 787 Airplane Characteristics for Airport Planning. D6-58333, P180
   [Anonymous], 1981, National Safety and Operational Criteria for Runway Use Programs Document Information (8400.9), P8
   [Anonymous], 2018, Annex 14 to the Convention on International Civil Aviation, Aerodromes, P354
   [Anonymous], 2008, Pilot's handbook of aeronautical knowledge, P471
   Arora VK, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL046270
   Azorin-Molina C, 2018, ATMOS RES, V203, P175, DOI 10.1016/j.atmosres.2017.12.010
   Bélair S, 2005, MON WEATHER REV, V133, P1938, DOI 10.1175/MWR2958.1
   Bellasio R., 2014, J AIRL AIRPT MANAG, P4
   BENOIT R, 1989, MON WEATHER REV, V117, P1726, DOI 10.1175/1520-0493(1989)117<1726:IOATBL>2.0.CO;2
   Boeing, 2013, 737 AIRPL CHA AIRP P, P682
   Bureau of Transportation Statistics, 2019, WEATH SHAR DEL PERC
   BUSH E, 2019, CANADAS CHANGING CLI
   Coffel E, 2015, WEATHER CLIM SOC, V7, P94, DOI 10.1175/WCAS-D-14-00026.1
   Coffel ED, 2017, CLIMATIC CHANGE, V144, P381, DOI 10.1007/s10584-017-2018-9
   Cote J, 1998, MON WEATHER REV, V126, P1397, DOI 10.1175/1520-0493(1998)126<1397:TOCMGE>2.0.CO;2
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Delage Y, 1997, BOUND-LAY METEOROL, V82, P23, DOI 10.1023/A:1000132524077
   Diro GT, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10080430
   FAA, 2005, 15053254B FAA US DEP, P38
   Gratton G, 2020, CLIMATIC CHANGE, V160, P219, DOI 10.1007/s10584-019-02634-z
   Hersbach H., 2016, ECMWF NEWSL, V147, P5
   Irvine EA, 2016, TRANSPORT RES D-TR E, V47, P44, DOI 10.1016/j.trd.2016.04.014
   Jeong DI, 2018, SUSTAIN CITIES SOC, V36, P225, DOI 10.1016/j.scs.2017.10.004
   Jeong DI, 2016, CLIM DYNAM, V46, P3163, DOI 10.1007/s00382-015-2759-y
   KAIN JS, 1992, METEOROL ATMOS PHYS, V49, P93, DOI 10.1007/BF01025402
   Karwal A.K., 2001, P FLIGHT SAF FDN ANN
   LAPRISE R, 1992, MON WEATHER REV, V120, P197, DOI 10.1175/1520-0493(1992)120<0197:TEEOMW>2.0.CO;2
   Lee SH, 2019, NATURE, V572, P639, DOI 10.1038/s41586-019-1465-z
   Li J, 2005, J ATMOS SCI, V62, P286, DOI 10.1175/JAS-3396.1
   Martynov A, 2013, CLIM DYNAM, V41, P2973, DOI 10.1007/s00382-013-1778-9
   Mekis E, 2018, ATMOS OCEAN, V56, P71, DOI 10.1080/07055900.2018.1433627
   Oster C.V., 2010, P 51 ANN TRANSP RES
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Statistics Canada, 2020, TABL 23 10 0023 01 I
   SUNDQVIST H, 1989, MON WEATHER REV, V117, P1641, DOI 10.1175/1520-0493(1989)117<1641:CACPSW>2.0.CO;2
   Teufel B, 2019, CLIM DYNAM, V52, P4193, DOI 10.1007/s00382-018-4375-0
   Verseghy D., 2009, CLASS CANADIAN LAND, P180
   Wan H, 2010, J CLIMATE, V23, P1209, DOI 10.1175/2009JCLI3200.1
   WIERINGA J, 1980, B AM METEOROL SOC, V61, P962, DOI 10.1175/1520-0477(1980)061<0962:ROWOAA>2.0.CO;2
   Williams PD, 2017, ADV ATMOS SCI, V34, P576, DOI 10.1007/s00376-017-6268-2
   Williams PD, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/2/024008
   Williams PD, 2013, NAT CLIM CHANGE, V3, P644, DOI [10.1038/NCLIMATE1866, 10.1038/nclimate1866]
   Yeh KS, 2002, MON WEATHER REV, V130, P339, DOI 10.1175/1520-0493(2002)130<0339:TCMGEM>2.0.CO;2
   Zadra A., 2012, Recent changes to the orographic blocking parametrization
   Zhang XB, 2000, ATMOS OCEAN, V38, P395, DOI 10.1080/07055900.2000.9649654
   Zhou TJ, 2018, SCI BULL, V63, P700, DOI 10.1016/j.scib.2018.03.018
   Zhou YT, 2018, CLIMATIC CHANGE, V151, P463, DOI 10.1007/s10584-018-2335-7
NR 47
TC 5
Z9 7
U1 2
U2 16
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD APR
PY 2020
VL 11
IS 4
AR 418
DI 10.3390/atmos11040418
PG 21
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA LW9WE
UT WOS:000539492200105
OA gold
DA 2025-01-10
ER

PT J
AU Liu, Y
   Ruiz-Menjivar, J
   Zhang, L
   Zhang, JB
   Swisher, ME
AF Liu, Yong
   Ruiz-Menjivar, Jorge
   Zhang, Lu
   Zhang, Junbiao
   Swisher, Marilyn E.
TI Technical training and rice farmers' adoption of low-carbon management
   practices: The case of soil testing and formulated fertilization
   technologies in Hubei, China
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Technical training; Low-carbon technologies; Soil testing and formulated
   fertilization; Propensity score matching
ID CLIMATE-CHANGE ADAPTATION; GREENHOUSE-GAS EMISSIONS; ENVIRONMENTAL
   IMPACTS; NITROGEN MANAGEMENT; VEGETABLE FARMERS; PROPENSITY SCORE; MAIZE
   PRODUCTION; FOOD SECURITY; AGRICULTURE; HEALTH
AB More than a decade ago, the Chinese government created several agricultural programs with the objective to promote food security and to foster environmental sustainability via the adoption of more eco-conscious practices in agriculture. While the overall application rate of chemical fertilizer has significantly declined, the adoption of low-carbon technologies promoted through these initiatives remains relative low partly due to the lack of a wide-reaching systems to implement the recommended practices and farmers' lack of awareness and knowledge about the technologies. The purpose of this study is to examine the impact of technical training on low-carbon management practices, specifically on the adoption of soil testing and formulated fertilization technologies. We hypothesize that technical training and education facilitates the adoption of promoted technologies. Data for this research come from a random sample of 1115 rice farmers in Hubei, China. Using a logistic regression, we empirically examine the effect of having received formal technical training within the last 12 months on the likelihood of adopting low-carbon technologies. To account for potential heterogeneity and selection bias, we employ counterfactual framework and propensity score matching and estimate the average treatment effect for those who have received formal technical training. Our results revealed a positive and significant association between formal technical training and rice farmers' adoption of low-carbon technologies, with an average treatment effect of 0.2078. Males, younger farmers, and members of agricultural cooperatives were more likely to adopt soil testing and formulated fertilization technologies. Further, a gender analysis, conducted only with those who indicated having received technical training on low-carbon technologies, showed that trained females were more prone to adopt these technologies than trained males. Our findings provide and discuss meaningful implications for the development of future efforts to promote the adoption of low-carbon agricultural technologies in China. (C) 2019 Published by Elsevier Ltd.
C1 [Liu, Yong; Zhang, Lu; Zhang, Junbiao] Huazhong Agr Univ, Coll Econ & Management, Wuhan 430070, Peoples R China.
   [Ruiz-Menjivar, Jorge; Zhang, Lu; Swisher, Marilyn E.] Univ Florida, Dept Family Youth & Community Sci, Gainesville, FL 32607 USA.
   [Zhang, Lu] South China Agr Univ, Natl Sch Agr Inst & Dev, Guangzhou 510642, Guangdong, Peoples R China.
   [Ruiz-Menjivar, Jorge; Swisher, Marilyn E.] Univ Florida, Ctr Sustainable & Organ Food Syst, Gainesville, FL 32607 USA.
C3 Huazhong Agricultural University; State University System of Florida;
   University of Florida; South China Agricultural University; State
   University System of Florida; University of Florida
RP Zhang, L; Zhang, JB (corresponding author), Huazhong Agr Univ, Coll Econ & Management, Wuhan 430070, Peoples R China.
EM ly517@webmail.hzau.edu.cn; jorgerm@ufl.edu; luzhang@mail.hzau.edu.cn;
   zhangjunbiao@mail.hzau.edu.cn; mesw@ufl.edu
RI Liu, Yong/ABA-6780-2020
OI Liu, Yong/0000-0003-1939-2799; Ruiz-Menjivar, Jorge/0000-0003-1167-4839
FU Natural Sciences Foundation of China [41501213, 71333004, 71742003];
   Fundamental Research Funds for the Central Universities [2662017PY045];
   Key Project for Studies of Philosophy and Social Sciences by Ministry of
   Education [15JZD014]; University of Florida International Center's
   Global Fellowship Award
FX This work was supported by the Natural Sciences Foundation of China
   (41501213; 71333004; 71742003); the Fundamental Research Funds for the
   Central Universities (2662017PY045); the Key Project for Studies of
   Philosophy and Social Sciences by Ministry of Education (15JZD014); and
   the University of Florida International Center's Global Fellowship
   Award.
CR Ajayi OC, 2007, NAT RESOUR FORUM, V31, P306, DOI 10.1111/j.1477-8947.2007.00163.x
   Ajzen I., 1980, UNDERSTANDING ATTITU
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   [Anonymous], REV EC HOUSEH, DOI DOI 10.1023/A:1021847430758
   [Anonymous], 2010, SO AGR EC ASS ANN M
   [Anonymous], CHINA IS PROMOTING T
   [Anonymous], 2017, CHIN STAT YB 2017
   [Anonymous], 2013, EC APPROACH HUMAN BE
   [Anonymous], OXFORD HDB EC FOOD C
   [Anonymous], 2016, Chinas Carbon Emissions Report 2016
   [Anonymous], INT SOIL WATER CONSE
   [Anonymous], 1935, Supplement to the Journal of the Royal Statistical Society
   [Anonymous], 2011, 2011 INT C ELECT INF, DOI [10.1109/ICEICE.2011.5778158, DOI 10.1109/ICEICE.2011.5778158]
   [Anonymous], 1964, TRANSFORMATION TRADI
   Arunrat N, 2017, J CLEAN PROD, V143, P672, DOI 10.1016/j.jclepro.2016.12.058
   Austin PC, 2011, MULTIVAR BEHAV RES, V46, P119, DOI 10.1080/00273171.2011.540480
   Below TB, 2012, GLOBAL ENVIRON CHANG, V22, P223, DOI 10.1016/j.gloenvcha.2011.11.012
   Burton RJF, 2014, J ENVIRON MANAGE, V135, P19, DOI 10.1016/j.jenvman.2013.12.005
   Chen C, 2014, ENVIRON EARTH SCI, V71, P4073, DOI 10.1007/s12665-013-2792-2
   Defrancesco E, 2008, J AGR ECON, V59, P114, DOI 10.1111/j.1477-9552.2007.00134.x
   Fishbein M., 1975, Belief, attitudes, intention, DOI DOI 10.1080/00336297.1994.10484118.FAO/RAP/FIPL
   Gautam S, 2017, CROP PROT, V102, P161, DOI 10.1016/j.cropro.2017.08.022
   Ghimire R, 2016, J S ASIAN DEV, V11, P113, DOI 10.1177/0973174116629254
   Guo S., 2010, Propensity Score Analysis. Statistical Methods and Applications
   Heckman JJ, 1998, REV ECON STUD, V65, P261, DOI 10.1111/1467-937X.00044
   Hu RF, 2007, AGR SYST, V94, P331, DOI 10.1016/j.agsy.2006.10.002
   Huang J, 2012, J SOIL WATER CONSERV, V67, P321, DOI 10.2489/jswc.67.4.321
   Huang JK, 2008, J SOIL WATER CONSERV, V63, p165A, DOI 10.2489/jswc.63.5.165A
   Huang JK, 2015, AGR SYST, V135, P105, DOI 10.1016/j.agsy.2015.01.004
   Jia XP, 2013, J INTEGR AGR, V12, P364, DOI [10.1016/S2095-3119(13)60237-3, 10.1016/s2095-3119(13)60237-3]
   Jia XP, 2015, AGROECOL SUST FOOD, V39, P189, DOI 10.1080/21683565.2014.967436
   Jin JJ, 2015, SCI TOTAL ENVIRON, V538, P942, DOI 10.1016/j.scitotenv.2015.07.027
   Li YX, 2013, J ENVIRON QUAL, V42, P972, DOI 10.2134/jeq2012.0465
   [罗小娟 Luo Xiaojuan], 2013, [自然资源学报, Journal of Natural Resources], V28, P1891
   Magnan N, 2015, J DEV ECON, V116, P223, DOI 10.1016/j.jdeveco.2015.05.003
   Marino R, 2016, SMALL RUMINANT RES, V135, P50, DOI 10.1016/j.smallrumres.2015.12.012
   Marousek J, 2013, J AGR ENVIRON ETHIC, V26, P679, DOI 10.1007/s10806-012-9423-x
   Mponela P, 2016, LAND USE POLICY, V59, P38, DOI 10.1016/j.landusepol.2016.08.029
   Mu R, 2011, LABOUR ECON, V18, pS83, DOI 10.1016/j.labeco.2011.01.009
   Nkamleu GB, 2000, AGR SYST, V63, P111, DOI 10.1016/S0308-521X(99)00074-8
   Oluwole O, 2009, INT J AGR SUSTAIN, V7, P153, DOI 10.3763/ijas.2009.0431
   Oreskes N, 2004, SCIENCE, V306, P1686, DOI 10.1126/science.1103618
   Pan D, 2017, J ENVIRON MANAGE, V197, P130, DOI 10.1016/j.jenvman.2017.03.069
   Prochaska JO, 1997, AM J HEALTH PROMOT, V12, P38, DOI 10.4278/0890-1171-12.1.38
   Qi Y., 2013, Annual Review of Low-carbon Development in China: 2010
   Rahman S, 2003, J ENVIRON MANAGE, V68, P183, DOI 10.1016/S0301-4797(03)00066-5
   Ren C, 2017, APPL ENERG, V193, P414, DOI 10.1016/j.apenergy.2017.02.037
   Robertson GP, 2000, SCIENCE, V289, P1922, DOI 10.1126/science.289.5486.1922
   ROSENBAUM PR, 1983, BIOMETRIKA, V70, P41, DOI 10.1093/biomet/70.1.41
   RUBIN DB, 1974, J EDUC PSYCHOL, V66, P688, DOI 10.1037/h0037350
   RUBIN DB, 1980, J AM STAT ASSOC, V75, P591, DOI 10.2307/2287653
   Salemdeeb R, 2017, J CLEAN PROD, V140, P871, DOI 10.1016/j.jclepro.2016.05.049
   Shan YL, 2018, SCI DATA, V5, DOI 10.1038/sdata.2017.201
   Solazzo R, 2016, SCI TOTAL ENVIRON, V573, P1115, DOI 10.1016/j.scitotenv.2016.08.066
   Song Y, 2010, GEND TECHNOL DEV, V14, P25, DOI 10.1177/097185241001400102
   Suvedi M, 2017, J AGRIC EDUC EXT, V23, P351, DOI [10.1080/1389224x.2017.1323653, 10.1080/1389224X.2017.1323653]
   Tubiello FN, 2015, GLOBAL CHANGE BIOL, V21, P2655, DOI 10.1111/gcb.12865
   Vanlauwe B, 2010, OUTLOOK AGR, V39, P17, DOI 10.5367/000000010791169998
   Wang YH, 2005, TRENDS PLANT SCI, V10, P610, DOI 10.1016/j.tplants.2005.10.008
   Wei YP, 2009, LAND DEGRAD DEV, V20, P336, DOI 10.1002/ldr.922
   Wu HF, 2016, J AGRAR CHANGE, V16, P50, DOI 10.1111/joac.12089
   Yue Q, 2017, J CLEAN PROD, V149, P1011, DOI 10.1016/j.jclepro.2017.02.172
   Zhao L, 2018, FOOD CONTROL, V85, P308, DOI 10.1016/j.foodcont.2017.09.016
   Zheng JF, 2017, AGR ECOSYST ENVIRON, V241, P70, DOI 10.1016/j.agee.2017.02.034
   Zhong Z., 2014, FFTC AGR POLICY PLAT
NR 65
TC 138
Z9 149
U1 11
U2 184
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0959-6526
EI 1879-1786
J9 J CLEAN PROD
JI J. Clean Prod.
PD JUL 20
PY 2019
VL 226
BP 454
EP 462
DI 10.1016/j.jclepro.2019.04.026
PG 9
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology
GA IA9UA
UT WOS:000469901200040
DA 2025-01-10
ER

PT J
AU Alejo, LA
   Ella, VB
AF Alejo, Lanie A.
   Ella, Victor B.
TI Assessing the impacts of climate change on dependable flow and potential
   irrigable area using the SWAT model. The case of Maasin River watershed
   in Laguna, Philippines
SO JOURNAL OF AGRICULTURAL ENGINEERING
LA English
DT Article
DE Climate change; potential irrigable area; SWAT
ID IRRIGATION DISTRICT; RICE PRODUCTION; STREAMFLOW; COLORADO; SOIL
AB Seasonal changes in rainfall and temperature brought about by climate change affect water resources availability for rice production areas. There are currently no published applications of the soil and water assessment tool (SWAT) model on quantified effects of climate variability on irrigation service areas for rice production. The study assessed the impacts of climate change on dependable flow and potential irrigable areas of the Maasin River in Laguna, Philippines. Projected variations of rainfall and temperature in 2020 and 2050 developed using PRECIS model based on special report on emission scenarios were employed. The SWAT model was then used to simulate stream flow for each climate change scenario, from which dependable flows were quantified using flow duration analysis. Diversion water requirements for the rice areas in the watershed were determined using CROPWAT. Based on dependable flows and irrigation demand, the potential irrigable areas were estimated. Calibration and validation of the SWAT model showed satisfactory performance in stream flow simulations. The dependable flow in irrigation systems may decline by more than 50% in 2020 and by as much as 97% in 2050, because of seasonal changes in rainfall. In effect, the potential irrigable area may decrease to less than half of the current service area depending on the level of greenhouse gases emissions. SWAT water balance projections suggest surface runoff during wet seasons and increase annual groundwater recharge are possible sources of supplemental irrigation. Provisions of suitable storage reservoir facilities and groundwater development projects will alleviate water scarce conditions. The study demonstrated a technique that may be applied in other irrigation systems in the Philippines and in other countries to quantify the effects of climate change on dependable flows and potential irrigable areas. It can serve as an input to water resources planning and policy recommendations for climate change adaptation and risk reduction strategies. This technique can also be used to assess water resources in other perennial rivers and its viability for the development of new irrigation systems in the Philippines.
C1 [Alejo, Lanie A.] Isabela State Univ, Coll Engn, Echague 3309, Isabela, Philippines.
   [Ella, Victor B.] Univ Philippines, Los Banos, Laguna, Philippines.
C3 Isabela State University; University of the Philippines System;
   University of the Philippines Open University; University of the
   Philippines Los Banos
RP Alejo, LA (corresponding author), Isabela State Univ, Coll Engn, Echague 3309, Isabela, Philippines.
EM lhan_1023@yahoo.com
RI Ella, Victor/D-5099-2016; Alejo, Lanie/AAG-3756-2020
OI Ella, Victor/0000-0001-9993-1822; Alejo, Lanie/0000-0002-8058-483X
FU DOST - Engineering Research and Development for Technology; DOST -
   Science Education Institute; DOST - Philippine Council for Agriculture,
   Aquatic and Natural Resources Research and Development
FX the authors would like to thank the agencies and projects mentioned in
   this article, which generously shared their data. This work was
   supported by the DOST - Engineering Research and Development for
   Technology, DOST - Science Education Institute and the DOST - Philippine
   Council for Agriculture, Aquatic and Natural Resources Research and
   Development.
CR Akintug B, 2005, WATER RESOUR RES, V41, DOI 10.1029/2004WR003605
   Awan UK, 2014, J HYDROL, V519, P1368, DOI 10.1016/j.jhydrol.2014.08.049
   Bressiani DD, 2015, INT J AGR BIOL ENG, V8, P125, DOI 10.3965/j.ijabe.20150803.970
   Briones RU, 2016, J ENVIRON SCI MANAG, V19, P96
   Combalicer EA, 2012, J ENVIRON SCI MANAG, P1
   Ella V.B., 2011, SIMULATING HYDRAULIC
   Gassman PW, 2007, T ASABE, V50, P1211, DOI 10.13031/2013.23637
   Gianfagna CC, 2015, J HYDROL-REG STUD, V4, P583, DOI 10.1016/j.ejrh.2015.09.002
   Kopytkovskiy M, 2015, J HYDROL-REG STUD, V3, P473, DOI 10.1016/j.ejrh.2015.02.014
   Lansigan FP, 2000, AGR ECOSYST ENVIRON, V82, P129, DOI 10.1016/S0167-8809(00)00222-X
   Luo Y, 2008, J HYDROL, V352, P139, DOI 10.1016/j.jhydrol.2008.01.003
   Luo YX, 2011, PROCEDIA ENVIRON SCI, V10, P2050, DOI 10.1016/j.proenv.2011.09.321
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Neitsch SL., 2011, THEORETICAL DOCUMENT
   Palao L. K. M., 2013, Journal of Sustainable Development, V6, P73
   Peng SB, 2004, P NATL ACAD SCI USA, V101, P9971, DOI 10.1073/pnas.0403720101
   Reshmidevi TV, 2018, J HYDROL, V556, P1192, DOI 10.1016/j.jhydrol.2017.02.016
   Roberts MG, 2009, J APPL METEOROL CLIM, V48, P1718, DOI 10.1175/2008JAMC1628.1
   Sanborn SC, 2006, J HYDROL, V325, P241, DOI 10.1016/j.jhydrol.2005.10.018
   Srinivasan R, 1998, J AM WATER RESOUR AS, V34, P91, DOI 10.1111/j.1752-1688.1998.tb05962.x
   Tan ML, 2017, ATMOS RES, V189, P1, DOI 10.1016/j.atmosres.2017.01.008
   Tibebe M, 2016, SPRING GEOGR, P113, DOI 10.1007/978-3-319-18787-7_7
   Tolentino Arlene B., IAMURE INT J ECOL CO, V17, DOI [10.7718/ijec.v17i1.1067, DOI 10.7718/IJEC.V17I1.1067]
   Valencia JA., 2015, GLOB ADV RES J AGR S, V4, P2315
   Xie XH, 2011, J HYDROL, V396, P61, DOI 10.1016/j.jhydrol.2010.10.032
   Zheng J, 2010, MATH COMPUT MODEL, V51, P1312, DOI 10.1016/j.mcm.2009.10.036
NR 27
TC 6
Z9 6
U1 1
U2 10
PU PAGEPRESS PUBL
PI PAVIA
PA MEDITGROUP, VIA G BELLI, 4, PAVIA, 27100, ITALY
SN 1974-7071
EI 2239-6268
J9 J AGRIC ENG-ITALY
JI J. Agric. Eng.
PY 2019
VL 50
IS 2
BP 88
EP 98
AR 941
DI 10.4081/jae.2019.941
PG 11
WC Agricultural Engineering
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA IF0HA
UT WOS:000472755900004
DA 2025-01-10
ER

PT J
AU Rehfeldt, GE
   Leites, LP
   Joyce, DG
   Weiskittel, AR
AF Rehfeldt, Gerald E.
   Leites, Laura P.
   Joyce, Dennis G.
   Weiskittel, Aaron R.
TI Role of population genetics in guiding ecological responses to climate
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE climate change responses; ecological genetics; ecological optimum;
   genetic differentiation; genotype-environment interactions; growth
   potential-cold hardiness tradeoff; physiological optimum
ID PINUS-CONTORTA; DOUGLAS-FIR; MANAGEMENT STRATEGIES; LODGEPOLE PINE;
   ADAPTATION; GROWTH; RANGE; NICHE; NORTHERN; CLINES
AB Population responses to climate were assessed using 3-7 years height growth data gathered for 266 populations growing in 12 common gardens established in the 1980s as part of five disparate studies of Pinus contorta var. latifolia. Responses are interpreted according to three concepts: the ecological optimum, the climate where a population is competitively exclusive and in which, therefore, it occurs naturally; the physiological optimum, the climate where a population grows best but is most often competitively excluded; and growth potential, the innate capacity for growth at the physiological optimum. Statistical analyses identified winter cold, measured by the square root of negative degree-days calculated from the daily minimum temperature (MINDD0(1/2)), as the climatic effect most closely related to population growth potential; the colder the winter inhabited by a population, the lower its growth potential, a relationship presumably molded by natural selection. By splitting the data into groups based on population MINDD0(1/2) and using a function suited to skewed normal distributions, regressions were developed for predicting growth from the distance in climate space (MINDD0(1/2)) populations had been transferred from their native location to a planting site. The regressions were skewed, showing that the ecological optimum of most populations is colder than the physiological optimum and that the discrepancy between the two increases as the ecological optimum becomes colder. Response to climate change is dependent on innate growth potential and the discrepancy between the two optima and, therefore, is population-specific, developing out of genotype-environment interactions. Response to warming in the short-term can be either positive or negative, but long term responses will be negative for all populations, with the timing of the demise dependent on the amount of skew. The results pertain to physiological modeling, species distribution models, and climate-change adaptation strategies.
C1 [Leites, Laura P.] Penn State Univ, Dept Ecosyst Sci & Management, University Pk, PA 16802 USA.
   [Weiskittel, Aaron R.] Univ Maine, Sch Forest Resources, Orono, ME USA.
C3 Pennsylvania Commonwealth System of Higher Education (PCSHE);
   Pennsylvania State University; Pennsylvania State University -
   University Park; University of Maine System; University of Maine Orono
EM jrehfeldt@gmail.com
RI Weiskittel, Aaron/H-3688-2019
OI Weiskittel, Aaron/0000-0003-2534-4478
CR Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   [Anonymous], 1971, MISCELLANEOUS PUBLIC
   [Anonymous], 1969, P 10 SO FOR TREE IMP
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Bentz BJ, 2010, BIOSCIENCE, V60, P602, DOI 10.1525/bio.2010.60.8.6
   CAMPBELL RK, 1978, THEOR APPL GENET, V51, P233, DOI 10.1007/BF00273770
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   Gray LK, 2016, FOREST ECOL MANAG, V377, P128, DOI 10.1016/j.foreco.2016.06.041
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Huston M. A., 1994, BIOL DIVERSITY COEXI, P274
   Joyce DG, 2017, FORESTRY, V90, P594, DOI 10.1093/forestry/cpx018
   Joyce DG, 2013, FOREST ECOL MANAG, V295, P173, DOI 10.1016/j.foreco.2012.12.024
   Leites LP, 2012, NAT RESOUR MODEL, V25, P409, DOI 10.1111/j.1939-7445.2012.00129.x
   Leites LP, 2012, ECOL APPL, V22, P154, DOI 10.1890/11-0150.1
   Loehle C, 1998, J BIOGEOGR, V25, P735, DOI 10.1046/j.1365-2699.1998.2540735.x
   MATYAS C, 1994, TREE PHYSIOL, V14, P797, DOI 10.1093/treephys/14.7-8-9.797
   Millar CI, 2015, SCIENCE, V349, P823, DOI 10.1126/science.aaa9933
   MONSERUD RA, 1990, FOREST SCI, V36, P1
   Montwé D, 2016, GLOBAL CHANGE BIOL, V22, P806, DOI 10.1111/gcb.13123
   Morgenstern E.K., 1996, Geographic variation in forest trees: genetic basis and application of knowledge in silviculture
   Negron JF, 1998, FOREST ECOL MANAG, V107, P71, DOI 10.1016/S0378-1127(97)00319-8
   Putman R. J., 1984, PRINCIPLES ECOLOGY, P19
   Rehfeldt G. E., 2004, Recent Research Developments in Genetics & Breeding. Vol. 1, Part I, P113
   Rehfeldt G. E., 2003, Eurasian Journal of Forest Research, V6-2, P83
   Rehfeldt G. E., 1985, INT356 USDA FOR SERV
   Rehfeldt GE, 1999, ECOL MONOGR, V69, P375, DOI 10.1890/0012-9615(1999)069[0375:GRTCIP]2.0.CO;2
   Rehfeldt GE, 2001, CLIMATIC CHANGE, V50, P355, DOI 10.1023/A:1010614216256
   Rehfeldt GE, 2002, GLOBAL CHANGE BIOL, V8, P912, DOI 10.1046/j.1365-2486.2002.00516.x
   REHFELDT GE, 1985, CAN J FOREST RES, V15, P524, DOI 10.1139/x85-086
   REHFELDT GE, 1988, SILVAE GENET, V37, P131
   REHFELDT GE, 1983, CAN J FOREST RES, V13, P405, DOI 10.1139/x83-061
   REHFELDT GE, 1987, INT375 USDA FOR SERV
   REHFELDT GE, 1985, INT354 USDA FOR SERV
   Rehfeldt GE, 2008, ECOLOGY, V89, P2127, DOI 10.1890/06-2013.1
   Rehfeldt GE, 2014, FOREST ECOL MANAG, V324, P138, DOI 10.1016/j.foreco.2014.02.041
   Rehfeldt GE, 2014, FOREST ECOL MANAG, V324, P126, DOI 10.1016/j.foreco.2014.02.035
   Sáenz-Romero C, 2017, GLOBAL CHANGE BIOL, V23, P2831, DOI 10.1111/gcb.13576
   SAS Institute Inc, 2004, SAS STAT COMP SOFTW, V3rd Edition
   Sniezko RA, 2012, P 4 INT WORKSH GEN H
   Urban M. C., 2016, ECOLOGICAL GENETICS, P1
   *USDA FOR SERV, 2000, FOR INV AN NAT COR F, V1
   Walter H., 2012, VEGETATION EARTH ECO, P31
   Wang T, 2006, GLOBAL CHANGE BIOL, V12, P2404, DOI 10.1111/j.1365-2486.2006.01271.x
   Yanchuk A., 2009, UNASYLVA, V60, P231
NR 44
TC 34
Z9 34
U1 2
U2 72
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD FEB
PY 2018
VL 24
IS 2
BP 858
EP 868
DI 10.1111/gcb.13883
PG 11
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA FU6WX
UT WOS:000423994700054
PM 28862811
DA 2025-01-10
ER

PT J
AU Bastaminia, A
   Rezaei, MR
   Dastoorpoor, M
AF Bastaminia, Amir
   Rezaei, Mohammad Reza
   Dastoorpoor, Maryam
TI Identification and evaluation of the components and factors affecting
   social and economic resilience in city of Rudbar, Iran
SO INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
LA English
DT Article
DE Resilience; Social resilience; Economic residence; Earthquake; Rudbar;
   Iran
ID CLIMATE-CHANGE ADAPTATION; DISASTER RISK REDUCTION; COMMUNITY
   RESILIENCE; ECOLOGICAL RESILIENCE; LOCAL-LEVEL; VULNERABILITY;
   FRAMEWORK; HEALTH; RETHINKING; INDICATOR
AB The current study aims at identifying and measuring components and factors affecting social and economic resilience in Rudbar, Iran. This applied research is using descriptive and analytical methods. The sample size in the study was estimated as 345 households using the Cochran's formula. Using library resources and experts, the components and factors affecting social and economic resilience were identified. Afterwards, the required date and information were collected using field method and household questionnaire. To analyze the data, descriptive and analytical statistical methods, including one-sample t-test, univariate and multiple linear regressions, were used. Awareness, knowledge, skill, attitude and social capital indices were considered as components of social resilience and the amount and severity of damage, compensation, and the possibility of returning to occupational and financial conditions were considered as the economic resilience components. Results of descriptive statistics showed that, in terms of social resilience (216.3 +/- 33.4) and economic resilience (30.6 +/- 7.3) (Mean +/- SD), households in Rudbar were in a relatively appropriate and inappropriate conditions, respectively. With respect to the factors affecting social and economic resilience, the results of multiple linear regression model showed that social resilience increases with the length of stay in neighborhood, the number of educated family members, higher education level of the head of the household, the employed heads of household compared to unemployed ones, having physically-mentally disabled persons in the family, owning the house compared to renting it. Moreover, it seems that economic resilience might increase with having employed family members (other than the head of the household), medical and accident insurance, higher approximate value of dwelling, and lower monthly expenses. Based on the findings, the study proposes some social and economic resilience components which could be used to improve the flexibility and resilience level of the communities at neighborhood level.
C1 [Bastaminia, Amir; Rezaei, Mohammad Reza] Yazd Univ, Sch Humanities, Dept Geog, Yazd, Iran.
   [Dastoorpoor, Maryam] Ahvaz Jundishapur Univ Med Sci, Fac Publ Hlth, Dept Epidemiol & Biostat, Ahvaz, Iran.
C3 University of Yazd; Ahvaz Jundishapur University of Medical Sciences
   (AJUMS)
RP Dastoorpoor, M (corresponding author), Ahvaz Jundishapur Univ Med Sci, Fac Publ Hlth, Dept Epidemiol & Biostat, Ahvaz, Iran.
EM Abastami31@gmail.com; Rezaei58@gmail.com; mdastoorpour@yahoo.com
RI ; Dastoorpoor, Maryam/R-7335-2017
OI rezaei, mohammad reza/0000-0002-6721-3014; Dastoorpoor,
   Maryam/0000-0001-5268-334X
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Adger WN, 2000, PROG HUM GEOG, V24, P347, DOI 10.1191/030913200701540465
   Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Ainuddin S, 2012, INT J DISAST RISK RE, V2, P25, DOI 10.1016/j.ijdrr.2012.07.003
   Aldrich D.P., 2012, Building resilience: Social capital in Post-Disaster Recovery
   Alexander DE, 2013, NAT HAZARD EARTH SYS, V13, P2707, DOI 10.5194/nhess-13-2707-2013
   Anderies JM, 2004, ECOL SOC, V9
   [Anonymous], 2003, IHDP UPDATE NEWSLETT
   [Anonymous], 2007, Environ. Hazards, DOI [10.1016/j.envhaz.2007.10.001, DOI 10.1016/J.ENVHAZ.2007.10.001]
   [Anonymous], INT PERSPECTIVES NAT
   [Anonymous], BUILD RES NEP PUBL P
   [Anonymous], 2003, The Vulnerability of Cities: Natural Disasters and Social Resilience
   Basabe Pedro., 2013, Encyclopedia of Natural Hazards, P508, DOI [DOI 10.1007/978-1-4020-4399-4_180, DOI 10.1007/978-1-4020-4399-4180]
   Basher R., 2015, Disaster risks research and assessment to promote risk reduction and management
   Bastaminia A., 2016, INT J SOC SCI STUD, V4, P9, DOI [10.11114/ijsss.v4i11.1920, DOI 10.11114/IJSSS.V4I11.1920]
   Bene C., 2015, MONIT EVAL RESIL INT
   Berkes F, 2005, ECOSYSTEMS, V8, P967, DOI 10.1007/s10021-005-0140-4
   Berkes F., 2003, Navigating social and ecological systems: building resilience for complexity and change, DOI DOI 10.1017/CBO9780511541957
   Berkes F, 2007, NAT HAZARDS, V41, P283, DOI 10.1007/s11069-006-9036-7
   Birkmann J, 2013, NAT HAZARDS, V67, P193, DOI 10.1007/s11069-013-0558-5
   Birkmann J., 2006, Measuring Vulnerability to Natural Hazards-Towards Disaster Resilient Societies, V01, P9
   Bocchini P, 2014, J INFRASTRUCT SYST, V20, DOI 10.1061/(ASCE)IS.1943-555X.0000177
   Bodin R., 2004, ESS B, V2, P33
   Bonanno George A, 2010, Psychol Sci Public Interest, V11, P1, DOI 10.1177/1529100610387086
   Boon HJ, 2012, RECOVERY DISASTER RE, P467
   Brand F, 2009, ECOL ECON, V68, P605, DOI 10.1016/j.ecolecon.2008.09.013
   Brand FS, 2007, ECOL SOC, V12
   Briguglio L., 2006, Constr, V1, P265, DOI DOI 10.22459/PIRIG.11.2005.03
   Brock WilliamA., 2002, PANARCHY, P261
   Cannon T, 2010, NAT HAZARDS, V55, P621, DOI 10.1007/s11069-010-9499-4
   Carpenter A, 2015, INT J DISAST RISK RE, V14, P290, DOI 10.1016/j.ijdrr.2014.09.003
   Carpenter S, 2001, ECOSYSTEMS, V4, P765, DOI 10.1007/s10021-001-0045-9
   Castleden M, 2011, J PUBLIC HEALTH-UK, V33, P369, DOI 10.1093/pubmed/fdr027
   Center ADR, 2002, LIV RISK GLOB REV DI
   Chandra A., 2010, UNDERSTANDING COMMUN, DOI 10.7249/WR737
   Christopherson S, 2010, CAMB J REG ECON SOC, V3, P3, DOI 10.1093/cjres/rsq004
   Coghlan A., 2004, AUST J EMERG MANAG, V19, P3
   Cumming GS, 2006, ECOL SOC, V11
   Cumming GS, 2011, LANDSCAPE ECOL, V26, P899, DOI 10.1007/s10980-011-9623-1
   Cutter S.L., 2006, HAZARDS VULNERABILIT, P115
   Cutter SL, 2014, GLOBAL ENVIRON CHANG, V29, P65, DOI 10.1016/j.gloenvcha.2014.08.005
   Cutter SL, 2010, J HOMEL SECUR EMERG, V7
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Davis TA, 2004, WATER QUAL RES J CAN, V39, P183, DOI 10.2166/wqrj.2004.027
   Davoudi S, 2012, PLAN THEORY PRACT, V13, P299, DOI 10.1080/14649357.2012.677124
   Dawley S, 2010, LOCAL ECON, V25, P650, DOI 10.1080/02690942.2010.533424
   de Groot RS, 2010, ECOL COMPLEX, V7, P260, DOI 10.1016/j.ecocom.2009.10.006
   Dickson E., 2012, URBAN RISK ASSESSMEN
   Drobniak A., 2012, J EC MANAG U EC KATO, V10, P5
   Elliott JR, 2006, SOC SCI RES, V35, P295, DOI 10.1016/j.ssresearch.2006.02.003
   Emergency Management Australia, 2005, DIS DAT BAS
   EMG U., 2011, GLOBAL DRYLANDS UN S, P131
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   Eser U., 2002, Umwelt-Ethik-Recht, P160
   Ferris E, 2010, EARTHQUAKES FLOODS C
   Folke C., 2010, RESILIENCE THINKING
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   GARMEZY N, 1991, PEDIATR ANN, V20, P459, DOI 10.3928/0090-4481-19910901-05
   Gunderson Lance, 2010, Foundations of Ecological Resilience, P423, DOI 10.5822/978-1-59726-509-0_29
   Hall P.A., 2013, Social resilience in the neoliberal era, DOI DOI 10.1017/CBO9781139542425
   Hallegatte S., 2014, POLICY RES WORKING P
   Haynes K, 2015, CHILD GEOGR, V13, P357, DOI 10.1080/14733285.2013.848599
   Hill E., 2008, I URBAN REG DEV
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Hollnagel E., 2006, Epilogue: resilience engineering precepts. Resilience engineering: concepts and precepts, P347
   Hollnagel E., 2007, Resilience Engineering: Concepts and Precepts, DOI DOI 10.1201/9781315605685
   Inter-American Development Bank (IDB), 2010, IDB WORK PAP SER
   Islam R, 2014, INT J DISAST RISK RE, V10, P281, DOI 10.1016/j.ijdrr.2014.09.016
   Jabareen Y, 2013, CITIES, V31, P220, DOI 10.1016/j.cities.2012.05.004
   Janssen MA, 2006, GLOBAL ENVIRON CHANG, V16, P240, DOI 10.1016/j.gloenvcha.2006.04.001
   Joerin J, 2012, INT J DISAST RISK RE, V1, P44, DOI 10.1016/j.ijdrr.2012.05.006
   Keating A., 2014, ZH FLOOD RESIL ALLIA
   Keck M, 2013, ERDKUNDE, V67, P5, DOI 10.3112/erdkunde.2013.01.02
   Klein R.J.T., 2003, ENVIRON HAZARDS-UK, V5, P35, DOI DOI 10.1016/J.HAZARDS.2004.02.001
   Lei YD, 2014, NAT HAZARDS, V70, P609, DOI 10.1007/s11069-013-0831-7
   Levin S., 1998, Environment and Development Economics, V3, P221, DOI [10.1017/s1355770x98240125, DOI 10.1017/S1355770X98240125]
   Lorenz DF, 2013, NAT HAZARDS, V67, P7, DOI 10.1007/s11069-010-9654-y
   Navarro-Espigares JL, 2012, SERV IND J, V32, P571, DOI 10.1080/02642069.2011.596535
   Madni AM, 2009, IEEE SYST J, V3, P181, DOI 10.1109/JSYST.2009.2017397
   Magis K, 2010, SOC NATUR RESOUR, V23, P401, DOI 10.1080/08941920903305674
   Maguire B, 2007, AUST J EMERG MANAG, V22, P16
   Maharani YN, 2016, INT J DISAST RISK RE, V20, P63, DOI 10.1016/j.ijdrr.2016.10.012
   Marincioni F, 2013, INT J DISAST RISK RE, V4, P52, DOI 10.1016/j.ijdrr.2013.01.001
   Martin R., 2014, J ECON GEOGR
   Martin R, 2012, J ECON GEOGR, V12, P1, DOI 10.1093/jeg/lbr019
   Martin R, 2010, ECON GEOGR, V86, P1
   Martin SA, 2015, INT J DISAST RISK RE, V12, P53, DOI 10.1016/j.ijdrr.2014.12.001
   Mayunga J.S., 2007, SUMMER ACAD SOCIAL V, V1, P1, DOI DOI 10.1146/ANNUREV.ENERGY.32.051807.090348
   McEntire DA, 2002, PUBLIC ADMIN REV, V62, P267, DOI 10.1111/1540-6210.00178
   McGlade J, 2006, COMPLEXITY AND CO-EVOLUTION: CONTINUITY AND CHANGE IN SOCIO-ECONOMIC SYSTEMS, P147
   McPhearson T, 2015, ECOSYST SERV, V12, P152, DOI 10.1016/j.ecoser.2014.07.012
   Miles SB, 2011, CARTOGR GEOGR INF SC, V38, P36, DOI 10.1559/1523040638136
   Miller D.S., 2016, COMMUNITY DISASTER R
   Miller F, 2010, ECOL SOC, V15
   Mitchell T., 2012, Resilience: A risk management approach
   Modica M, 2015, NETW SPAT ECON, V15, P211, DOI 10.1007/s11067-014-9261-7
   Mumby PJ, 2014, CURR OPIN ENV SUST, V7, P22, DOI 10.1016/j.cosust.2013.11.021
   Nelson RR, 2015, RATE DIRECTION INVEN
   Nelson RR, 2009, EVOLUTIONARY THEORY
   Norris FH, 2008, AM J COMMUN PSYCHOL, V41, P127, DOI 10.1007/s10464-007-9156-6
   O'Sullivan TL, 2013, SOC SCI MED, V93, P238, DOI 10.1016/j.socscimed.2012.07.040
   Obrist B, 2010, PROG DEV STUD, V10, P283, DOI 10.1177/146499340901000402
   Olsson P, 2014, ECOL SOC, V19, DOI 10.5751/ES-06799-190401
   Orencio PM, 2013, INT J DISAST RISK RE, V3, P62, DOI 10.1016/j.ijdrr.2012.11.006
   Oxley MC, 2013, INT J DISAST RISK RE, V4, P1, DOI 10.1016/j.ijdrr.2013.03.004
   Palliyaguru R, 2014, DISASTERS, V38, P45, DOI 10.1111/disa.12031
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Pelling M., 2003, Natural Disasters and development in a globalizing world, DOI [DOI 10.4324/9780203402375, 10.4324/9780203402375]
   Perrings C, 1998, ENVIRON RESOUR ECON, V11, P503, DOI 10.1023/A:1008255614276
   Perrings C, 2000, ENVIRON RESOUR ECON, V16, P185, DOI 10.1023/A:1008374222463
   Phillips M.K., 2010, UNDERSTANDING RESILI
   Pickett STA, 2014, BUILD RES INF, V42, P143, DOI 10.1080/09613218.2014.850600
   Pike A, 2010, CAMB J REG ECON SOC, V3, P59, DOI 10.1093/cjres/rsq001
   Polit DF, 2007, RES NURS HEALTH, V30, P459, DOI 10.1002/nur.20199
   Poortinga W, 2012, HEALTH PLACE, V18, P286, DOI 10.1016/j.healthplace.2011.09.017
   Prasad N, 2009, CLIMATE RESILIENT CITIES: A PRIMER ON REDUCING VULNERABILITIES TO DISASTERS, P1, DOI 10.1596/978-0-8213-7766-6
   Reggiani A., 2002, Networks and Spatial Economics, V2, P211, DOI [DOI 10.1023/A:1015377515690, 10.1023/A:1015377515690]
   Rezaei M., 2016, J FUNDAM APPL SCI, V8, P1630, DOI [10.4314/jfas.v8i2s.103, DOI 10.4314/JFAS.V8I2S.103]
   Rose A, 2005, J REGIONAL SCI, V45, P75, DOI 10.1111/j.0022-4146.2005.00365.x
   Rose A., 2009, Published Articles Papers Paper 75
   Rose A, 2013, INT J DISAST RISK RE, V5, P73, DOI 10.1016/j.ijdrr.2013.08.003
   Rose Adam., 2004, Disaster Prevention and Management, V13, P307, DOI [10.1108/09653560410556528, DOI 10.1108/09653560410556528]
   Schmidtlein MC, 2008, RISK ANAL, V28, P1099, DOI 10.1111/j.1539-6924.2008.01072.x
   Shelton JE, 2009, SOC SCI QUART, V90, P480, DOI 10.1111/j.1540-6237.2009.00627.x
   Simmie J, 2010, CAMB J REG ECON SOC, V3, P27, DOI 10.1093/cjres/rsp029
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Timmermann P., 1981, ENV MONOGRAPH, V1, P1
   Tschakert P, 2010, ECOL SOC, V15
   Turner BL, 2010, GLOBAL ENVIRON CHANG, V20, P570, DOI 10.1016/j.gloenvcha.2010.07.003
   UNESCAP A. UNEP, 2012, GREEN GROWTH RES RES, P157
   UNISDR E OECD, 2013, UK PEER REV BUILD RE
   UNU EHS (United Nations University Institute for Environment and Human Security), 2013, WORLD RISK REP
   Usamah M, 2014, INT J DISAST RISK RE, V10, P178, DOI 10.1016/j.ijdrr.2014.08.007
   Vogel C, 2007, GLOBAL ENVIRON CHANG, V17, P349, DOI 10.1016/j.gloenvcha.2007.05.002
   Voss M., 2008, Behemoth: A Journal on Civilisation, V3, P39
   Walker B, 2006, ECOL SOC, V11
   Waller MA, 2001, AM J ORTHOPSYCHIAT, V71, P290, DOI 10.1037/0002-9432.71.3.290
   Walsh-Dilley M., 2013, Rights for Resilience: Bringing Power, Rights and Agency into the Resilience Framework
   Wilson GA, 2013, LAND USE POLICY, V31, P298, DOI 10.1016/j.landusepol.2012.07.011
   Wilson GA, 2012, GEOFORUM, V43, P1218, DOI 10.1016/j.geoforum.2012.03.008
   Wilson S, 2013, ECOL SOC, V18, DOI 10.5751/ES-05100-180122
   Wynd CA, 2003, WESTERN J NURS RES, V25, P508, DOI 10.1177/0193945903252998
   Zautra A, 2008, COMMUNITY DEV, V39, P130, DOI 10.1080/15575330809489673
   Zhou HJ, 2010, NAT HAZARDS, V53, P21, DOI 10.1007/s11069-009-9407-y
   Zoback ML, 2014, SCIENCE, V346, P283, DOI 10.1126/science.1261788
NR 146
TC 17
Z9 17
U1 2
U2 78
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-4209
J9 INT J DISAST RISK RE
JI Int. J. Disaster Risk Reduct.
PD JUN
PY 2017
VL 22
BP 269
EP 280
DI 10.1016/j.ijdrr.2017.01.020
PG 12
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA EX8XL
UT WOS:000403533400025
DA 2025-01-10
ER

PT J
AU Bonatti, M
   Lana, MA
   D'Agostini, LR
   de Vasconcelos, ACF
   Sieber, S
   Eufemia, L
   da Silva-Rosa, T
   Schlindwein, SL
AF Bonatti, Michelle
   Lana, Marcos A.
   D'Agostini, Luiz Renato
   de Vasconcelos, Ana Carolina F.
   Sieber, Stefan
   Eufemia, Luca
   da Silva-Rosa, Teresa
   Schlindwein, Sandro Luis
TI Social representations of climate change and climate adaptation plans in
   southern Brazil: Challenges of genuine participation
SO URBAN CLIMATE
LA English
DT Article
DE Climatic change; Perceptions; social learning; Land-use management;
   Tapera da Base; Southern Brazilian adaptation
ID VULNERABILITY; RESPONSES
AB Despite some honorable advances, a huge quantity of public, private, and civil climate adaptation initiatives have failed to work in the Santa Catarina State (SC), Southern Brazil. Consequently, the state continues to face climate impacts; sometimes resulting in human fatalities. The main objective of this paper is to present a case study (Tapera da Base) within the context of the project, "Climate Change and Vulnerable Populations in Brazil", which discusses the problems associated with climate adaptation and relates these to risk-reducing activities. The methodology adopted involved: identifying local development organizations, focus group, interviews, and survey among families in the most vulnerable areas. The main findings show that Tapera residents do not associate the possible increase in their vulnerability to climate dynamics. They point to areas such as education, sanitation, and social assistance, as their most important local problems; thus not including climate change. To generate genuine participation it is crucial to creating initiatives that promote a social learning space for residents to evaluate their self-state of vulnerability and possibilities of development. Therefore climate change can make sense and the responses at the community level will be created in the context that shape how climate risk is perceived, prioritized and managed.
C1 [Bonatti, Michelle; Lana, Marcos A.; Sieber, Stefan; Eufemia, Luca] Leibniz Ctr Agr Landscape Res, Muncheberg, Germany.
   [Lana, Marcos A.] Swedish Univ Agr Sci SLU, Dept Crop Prod Ecol, Uppsala, Sweden.
   [D'Agostini, Luiz Renato; Schlindwein, Sandro Luis] Univ Fed Santa Catarina, Florianopolis, SC, Brazil.
   [de Vasconcelos, Ana Carolina F.] Univ Fed Campina Grande, Agr Engn Dept, Campina Grande, Brazil.
   [da Silva-Rosa, Teresa] Vila Velha Univ Espirito Santo UVV ES, Ctr Socioenvironm & Urban Studies, Vila Velha, ES, Brazil.
   [Sieber, Stefan] Humboldt Univ, Dept Agr Econ, Berlin, Germany.
C3 Leibniz Association; Leibniz Zentrum fur Agrarlandschaftsforschung
   (ZALF); Swedish University of Agricultural Sciences; Universidade
   Federal de Santa Catarina (UFSC); Universidade Federal de Campina
   Grande; Humboldt University of Berlin
RP Bonatti, M (corresponding author), Leibniz Ctr Agr Landscape Res ZALF, Eberswalder Str 84, D-15374 Muncheberg, Germany.
EM Michelle.Bonatti@zalf.de
RI Chevelev-Bonatti, Michelle/JFJ-8529-2023; Lana, Marcos/R-2463-2018
OI Sieber, Stefan/0000-0002-4849-7277
FU Ministry of Science, Technology and Innovation (MCTI) through the
   National Council for Scientific and Technological Development (CNPq)
FX The development of this research was made possible thanks to funding by
   the Ministry of Science, Technology and Innovation (MCTI) through the
   National Council for Scientific and Technological Development (CNPq).
CR Adger W.Neil., 2010, Der Klimawandel
   [Anonymous], AN SIL CRIS
   [Anonymous], PEDAGOGY OPPRESSED
   [Anonymous], PROJETO MUDANCAS CLI
   [Anonymous], GEOSUL
   [Anonymous], POTSDAM HUMAN IMPACT
   [Anonymous], IMP DIS AGR ADDR INF
   [Anonymous], CAP BAS DEF CIV
   [Anonymous], HUMANIT SOC SCI REV
   [Anonymous], CAP DEV IND
   [Anonymous], INFLUENCIA CONDICOES
   [Anonymous], ENV POLLUT
   [Anonymous], CAMINHOS GEOGRAFIA
   [Anonymous], 2014, At Risk: Natural Hazards, People's Vulnerability and Disasters
   [Anonymous], J INT DEV
   [Anonymous], BRIT J SOCIOLOGY CEN
   [Anonymous], ENCONTRO NACL ASSOCI
   [Anonymous], 2011, GLOBAL ASSESSMENT RE
   [Anonymous], 2006, SAO PAULO PERSPECTIV
   [Anonymous], METODOLOGIA INVESTIG
   [Anonymous], CONDICOES HIDRICAS S
   Birkmann J, 2013, NAT HAZARDS, V67, P193, DOI 10.1007/s11069-013-0558-5
   Bonatti M, 2016, LAND USE POLICY, V58, P114, DOI 10.1016/j.landusepol.2016.06.033
   Camargo C.G.C., 2006, AGROPECUARIA CATARIN, V19, P31
   Cardona OmarD., 2013, Mapping Vulnerability: Disasters, Development and People
   Chardon A.-C., 1999, GEOJOURNAL, V49, P197, DOI [10.1023/A:1007184911934, DOI 10.1023/A:1007184911934]
   Camurça CED, 2016, AV PSICOL LATINOAM, V34, P117, DOI 10.12804/apl34.1.2016.08
   Debortoli NS, 2017, NAT HAZARDS, V86, P557, DOI 10.1007/s11069-016-2705-2
   Eakin H, 2006, ANNU REV ENV RESOUR, V31, P365, DOI 10.1146/annurev.energy.30.050504.144352
   Gifford R, 2011, AM PSYCHOL, V66, P290, DOI 10.1037/a0023566
   Gottschick M, 2008, SYST PRACT ACT RES, V21, P479, DOI 10.1007/s11213-008-9109-5
   Granderson AA, 2014, CLIM RISK MANAG, V3, P55, DOI 10.1016/j.crm.2014.05.003
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Haque MA, 2012, ENVIRON HEALTH-GLOB, V11, DOI 10.1186/1476-069X-11-1
   Herrmann M. L. P., 2001, LEVANTAMENTO DESASTR
   Hine DW, 1996, J APPL SOC PSYCHOL, V26, P993, DOI 10.1111/j.1559-1816.1996.tb01121.x
   Macchi M., 2008, INDIGENOUS TRADITION
   Maturana Humberto R., 1987, The Tree of Knowledge: The Biological Roots of Human Understanding
   Maxwell J.A, 2012, QUALITATIVE RES DESI, V41
   McKenzie M., 2007, Social learning toward a sustainable world: Principles, perspectives, and praxis, P331
   Mendizabal N., 2006, Estrategias de Investigacion Cualitativa
   O'Brien KL, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P164
   Otto H., 2009, Koers (Online), V74, P217
   Smith J. A., 2015, Qualitative psychology: A practical guide to research methods, V3rd
   Swim JK, 2011, AM PSYCHOL, V66, P241, DOI 10.1037/a0023220
NR 45
TC 6
Z9 6
U1 0
U2 18
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0955
J9 URBAN CLIM
JI Urban CLim.
PD SEP
PY 2019
VL 29
AR 100496
DI 10.1016/j.uclim.2019.100496
PG 12
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA JJ3CZ
UT WOS:000494040100020
DA 2025-01-10
ER

PT J
AU Kvande, T
   Liso, KR
AF Kvande, Tore
   Liso, Kim Robert
TI Climate adapted design of masonry structures
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Brickwork; Building defects; Building envelope; Building pathology;
   Building performance; Building stock; Climate adaptation; Climatic
   impact; Durability; Masonry; Moisture; Norway
ID EXPOSURE INDEX
AB This paper presents challenges concerning design of masonry structures in severe climates. Empirical data on the design and performance of masonry buildings in Norway are presented, based on a comprehensive analysis of 302 process induced masonry defect assignments over a 20-year period from 1983 to 2002. Analyses of building defects are necessary in order to further develop tools, solutions and preventive measures ensuring high-performance building envelopes. The results illuminate the vulnerability of masonry under varying climatic exposure. The amount of masonry defects in Norway illustrates that it is not only the extreme weather events that need to be studied as a foundation for geographically dependent design guidelines. Driving rain and frost action are the principal climatic challenges to be considered in the pursuit of high-performance masonry structures. Shrinkage and thermal movement, the most frequent defect category, dominate independent of the climatic impact. Merely small errors or mistakes can bring about major and often irreparable defects or damage to masonry structuresA large part of the cases could have been avoided through more detailed engineering and applied knowledge on existing design guidelines. Finally, performance requirements for better design guidelines are presented. The need for design guidelines to ensure local climate adaptation and improved design guidelines on movement joints is also revealed. (C) 2009 Elsevier Ltd. All rights reserved.
C1 [Liso, Kim Robert] SINTEF, Bldg & Infrastruct, NO-0314 Oslo, Norway.
   [Kvande, Tore] Norwegian Univ Sci & Technol, Dept Civil & Transport Engn, NO-7491 Trondheim, Norway.
C3 SINTEF; Norwegian University of Science & Technology (NTNU)
RP Kvande, T (corresponding author), SINTEF, Bldg & Infrastruct, POB 124, NO-0314 Oslo, Norway.
EM tore.kvande@halden.net; kim.robert.liso@sintef.no
OI Kvande, Tore/0000-0003-0522-9974
FU Research Council of Norway
FX This paper has in part been written within the SINTEF Research &
   Development Programme "Climate 2000 - Building Constructions in a More
   Severe Climate" (2000-2007). The authors gratefully acknowledge all
   construction industry partners and the Research Council of Norway, and
   the anonymous Building and Environment referees for valuable comments on
   the text.
CR ARTENS DRW, 2004, P 13 INT BRICK BLOCK
   *BS, 2001, 562832001 BS
   *BS, 1992, 8104192 BS
   BUHELT M, 1999, 990531 ERFA
   BUO FO, 1981, KULDEBROER ENERGISPA
   DEJONG P, 1992, CEMENT, V2, P26
   Edgell G., 2005, Building mortar for low rise housing: Recommendations, problems and solutions
   HANSEN P, 1991, MALING PUDSEDE FACAD
   HANSON B, 2006, SPECIFICATION HANSON
   Hens H., 2005, P 7 S BUILDING PHYS, P670
   HUMBLE E, 1990, ALDRE MURVERKSHUS RE
   JOHANSSON S, 2005, P 7 S BUILD PHYS NOR, P719
   JUSTNES H, 1999, DETERIORATION MECH L
   KVANDE T, 2003, 116 NBI
   Liso KR, 2006, PROC MONOGR ENG WATE, P425
   Liso K. R., 2006, THESIS NTNU
   Liso KR, 2007, BUILD ENVIRON, V42, P3547, DOI 10.1016/j.buildenv.2006.10.022
   Liso KR, 2005, BUILD RES INF, V33, P41, DOI 10.1080/0961321042000323798
   LNGVALDSEN T, 2001, 308 NBI
   MAAGE M, 1990, FROSTBESTSNDIGKEIT P
   MAAGE M, 1990, FROSTBESTINDIGKEIT P, P10
   MARCHAND J, 1998, P SEM SULPH ATT MECH
   MARTENS DRW, 2003, P 9 CAN MAS S NEW BR
   Neville A. M., 1995, PROPERTIES CONCRETE
   *NS, 2003, 7711 NSEN
   OSTERGAARD J, 1999, FORVITRINGAVMURVXRK
   OSTERGAARD J, 1998, 980525 ERFAR
   OSTERGAARD J, 2001, 011229 BYGERFA
   OSTERGAARD J, 1999, 991126 ERFA
   OSTERGAARD J, 2001, MISFARVEDE KALKUDFAL
   Rydock JP, 2005, BUILD ENVIRON, V40, P1450, DOI 10.1016/j.buildenv.2004.11.018
   STIRLING C, 2002, 262 BR
   THOMPSON G, 2002, P 6 INT MAS C STOK O
   Verbeck GJ, 1956, Highway research board bulletin, V150
   WAIDURN AM, 2001, 742864 BYGG
   WALDUM AM, 1998, 723235 NORW BUILD RE
NR 36
TC 25
Z9 27
U1 0
U2 12
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-1323
J9 BUILD ENVIRON
JI Build. Environ.
PD DEC
PY 2009
VL 44
IS 12
BP 2442
EP 2450
DI 10.1016/j.buildenv.2009.04.007
PG 9
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA 487LX
UT WOS:000269276900012
DA 2025-01-10
ER

PT S
AU Rao, CS
   Gopinath, KA
   Prasad, JVNS
   Prasannakumar
   Singh, AK
AF Rao, Ch. Srinivasa
   Gopinath, K. A.
   Prasad, J. V. N. S.
   Prasannakumar
   Singh, A. K.
BE Sparks, DL
TI Climate Resilient Villages for Sustainable Food Security in Tropical
   India: Concept, Process, Technologies, Institutions, and Impacts
SO ADVANCES IN AGRONOMY, VOL 140
SE Advances in Agronomy
LA English
DT Review; Book Chapter
ID SOIL CARBON SEQUESTRATION; SEMIARID TROPICS; ECONOMIC-IMPACT; SUMMER
   MONSOON; AGRICULTURE; MANAGEMENT; ADAPTATION; SYSTEM; PROJECTIONS;
   MITIGATION
AB The world population is expected to increase by a further three billion by 2050 and 90% of the three billion will be from developing countries that rely on existing land, water, and ecology for food and well-being of human kind. The Intergovernmental Panel on Climate Change (IPCC) in its fifth assessment report (AR5) stated that warming of the climate system is unequivocal and is more pronounced since the 1950s. The atmosphere and oceans have warmed, the amounts of snow and ice have diminished, and sea level has risen. Each of the last three decades has been successively warmer at the earth's surface than any preceding decade since 1850 and the globally averaged combined land and ocean surface temperature data as calculated by a linear trend show a warming of 0.85 degrees C (0.65-1.06 degrees C) over the period of 1880-2012. World Meteorological Organization (WMO) ranked 2015 as the hottest year on record.
   Climate change poses many challenges to growth and development in South Asia. The Indian agriculture production system faces the daunting task of feeding 17.5% of the global population with only 2.4% of land and 4% of water resources at its disposal. India is more vulnerable to climate change in view of the dependence of huge population on agriculture, excessive pressure on natural resources, and relatively weak coping mechanisms. The warming trend in India over the past 100 years has indicated an increase of 0.6 degrees C, which is likely to impact many crops, negatively impacting food and livelihood security of millions of farmers. There are already evidences of negative impacts on yield of wheat and paddy in some parts of India due to increased temperature, water stress, and reduction in number of rainy days. Significant negative impacts have been projected under medium-term (2020-39) climate change scenario, for example, yield reduction by 4.5-9%, depending on the magnitude and distribution of warming. Since agriculture currently contributes about 15% of India's gross domestic product (GDP), a negative impact on production implies cost of climate change to roughly range from 0.7% to 1.35% of GDP per year.
   Indian agriculture, with 80% of farmers being smallholders (<0.5 ha) having diverse socioeconomic backgrounds, is monsoon-dependent rainfed agriculture (58%), about 30% of population undernourished, migration from rural to urban regions, child malnutrition etc., has become more vulnerable with changed climate or variability situations. During the past decade, frequency of droughts, cyclone, and hailstorms increased, with 2002, 2004, 2009, 2012, and 2014 being severe droughts. Frequent cyclones and severe hailstorms in drought prone areas have become common. Eastern part of the country is affected by seawater intrusion. Reduced food grain productivity, loss to vegetable and fruit crops, fodder scarcity, shortage of drinking water to animals during summer, forced migration of animals, severe loss to poultry and fishery sectors were registered, threatening the livelihoods of rural poor.
   Enhancing agricultural productivity, therefore, is critical for ensuring food and nutritional security for all, particularly the resource-poor, small, and marginal farmers who would be the most affected. In the absence of planned adaptation, the consequences of long-term climate change on the livelihood security of the poor could be severe. In India, the estimated countrywide agricultural loss in 2030 is expected to be over $ 7 billion that will severely affect the income of at least 10% of the population.
   However, this could be reduced by 80%, if cost-effective climate resilient measures are implemented.
   Climate risks are best addressed through increasing adaptive capacity and building resilience which can bring immediate benefits and can also reduce the adverse impacts of climate change. Climate resilient agriculture (CRA) encompasses the incorporation of adaptation and resilient practices in agriculture which increases the capacity of the system to respond to various climate-related disturbances by resisting damage and ensures quick recovery. Such disturbances include events such as drought, flood, heat/cold wave, erratic rainfall pattern, pest outbreaks, and other threats caused by changing climate. Resilience is the ability of the system to bounce back and essentially involves judicious and improved management of natural resources, land, water, soil, and genetic resources through adoption of best bet practices.
   CRA is a way to achieve short-and long-term agricultural development priorities in the face of climate change and serves as a bridge to other development priorities. It seeks to support countries and other actors in securing the necessary policy, technical and financial conditions to enable them to: (1) sustainably increase agricultural productivity and incomes in order to meet national food security and development goals, (2) build resilience and the capacity of agricultural and food systems to adapt to climate change, and (3) seek opportunities to mitigate emissions of greenhouse gases (GHGs) and increase carbon sequestration. These three conditions (food security, adaptation, and mitigation) are referred to as the "triple win" of overall CRA.
   The concept of climate resilient village (CRV) has been taken up by Government of India, to provide stability to farm productivity and household incomes and resilience through livelihood diversification in the face of extreme climatic events like droughts, cyclones, floods, hailstorms, heat wave, frost, and seawater inundation. Development of CRVs warrants establishment of a host of enabling mechanisms to mobilize and empower communities in the decision-making process to manage and recover from climate risks.
   The overall program of establishing CRVs have structured village level institutions such as Village Climate Risk Management Committee (VCRMC), custom hiring center (CHC) for farm implements, community seed and fodder banks, commodity groups etc. The establishment of CRVs was based on bottom-up approach with village community taking a central role in decision making on institutional requirements, technological interventions and supporting systems with able support from experts. In our knowledge, the CRV network of National Initiative on Climate Resilient Agriculture (NICRA) is by far the largest outreach program involving farmer's participation ever undertaken in the field of climate change adaptation anywhere in the world.
   Planning, coordination, monitoring, and capacity building of the program at the country level is the responsibility of the research organization (ICAR-Central Research Institute for Dryland Agriculture). At the district level, Krishi Vigyan Kendra (KVK; Farm Science Centre) under the Division of Agricultural Extension under Indian Council of Agricultural Research (ICAR), All India Coordinated Research Project for Dryland Agriculture (AICRPDA) centers and Transfer of Technology divisions of various ICAR Institutions across the country are responsible in implementing the project at village level through farmers' participatory approach.
   To address the climate vulnerabilities of the selected villages, different interventions were planned under the four modules; however, the specific intervention under each module for a particular village was need based and decided based on climatic vulnerability and resource situation of the particular village. The four intervention modules being implemented are (1) Natural resource management (in situ moisture conservation, biomass mulching, residue recycling, manure management, soil health card-based nutrient application, water harvesting and recycling for supplementary or life saving irrigation, improved drainage in high rainfall/flood prone villages, conservation tillage, and water saving irrigation methods). (2) Crop production module consisting of introduction of short-duration and drought/flood-tolerant varieties, modifications in planting dates for postrainy (winter) season crops to cope with terminal heat stress, water saving paddy systems (System of Rice Intensification, aerobic, direct seeding), frost management in fruit/vegetables, community nursery in staggered dates to meet delay in onset of monsoon, energy-efficient farm machinery through village CHC with timely completion of farm operation in limited sowing window, location specific intercropping systems, and suitable agroforestry systems. (3) Module III covers livestock and fisheries interventions through augmentation of fodder production, fodder storage methods, prophylaxis, and improved shelters for reducing heat stress in livestock, management of fish ponds/tanks during water scarcity and excess water, and promotion of livestock as climate adaptation strategy. (4) Module IV consists of village level institutions, collective marketing groups, introduction of weather-based insurance, and climate literacy though establishment of automated weather stations.
   Impacts of these climate resilient interventions in the villages were assessed through various resilience indicators, importantly, improved farm productivity, farm income, livelihoods at household and village level. Environmental impacts were assessed on improved soil carbon sequestration, groundwater recharge, vegetation and forest cover, and measurements of GHG emissions which were correlated with ex ante assessment of village level carbon balance and overall contribution to global warming potential.
   These 151 CRVs are learning sites for further expanding resilient villages to adjoining clusters and districts so that large number of villages will become part of the overall adaptation-led climate change mitigation mission in the country.
C1 [Rao, Ch. Srinivasa; Gopinath, K. A.; Prasad, J. V. N. S.; Prasannakumar] ICAR Cent Res Inst Dryland Agr, Hyderabad, Telangana, India.
   [Singh, A. K.] Indian Council Agr Res, Agr Extens Div, New Delhi, India.
C3 Indian Council of Agricultural Research (ICAR); ICAR - Central Research
   Institute of Dryland Agriculture; Indian Council of Agricultural
   Research (ICAR)
RP Rao, CS (corresponding author), ICAR Cent Res Inst Dryland Agr, Hyderabad, Telangana, India.
EM cherukumalli2011@gmail.com
RI Prasad, Vipin/AAB-6441-2021; Singh, Arun/O-2869-2016
CR AFCL, 2011, REP IMP EV PIL WEATH
   Aggarwal PK, 2008, INDIAN J AGR SCI, V78, P911
   Amarasinghe U. A., 2009, STRATEGIC ANAL NATL, V1, P131
   Amarasinghe Upali A., 2007, INDIAS WATER SUPPLY
   [Anonymous], MAUSAM
   [Anonymous], MAUSAM
   [Anonymous], 2014, 21 ICRAF WORLD AGR C
   [Anonymous], INDIAN J DRYLAND AGR
   [Anonymous], 2003, CLIMATE CHANGE INDIA
   [Anonymous], 2008, 209 IND COUNC RES IN
   [Anonymous], 2015, REG OV FOOD INS AS P
   [Anonymous], FRAMEWORK GUIDELINES
   Ashrit RG., 2001, MAUSAM, V1, P229
   Bahinipati CS, 2014, CURR SCI INDIA, V107, P1997
   Bansil P. C., 1996, INDIAN FARMING   FEB, P30
   Beddington JR, 2012, SCIENCE, V335, P289, DOI 10.1126/science.1217941
   Bernoux M, 2010, EX ANTE CARBON BALAN, V101, P79
   Bhardwaj J., 2007, 4 EUR C SEV STORMS T
   BHASKARAN B, 1995, INT J CLIMATOL, V15, P873, DOI 10.1002/joc.3370150804
   Bhosale D. D., 2002, P INT C HYDR WAT MAN, VII, P390
   Birthal P. S., 2014, Agricultural Economics Research Review, V27, P145, DOI 10.5958/0974-0279.2014.00019.6
   BOWMAN DC, 1992, J AM SOC HORTIC SCI, V117, P75, DOI 10.21273/JASHS.117.1.75
   Campbell B. M., 2014, Ccafs-Cgiar
   Campbell BM, 2014, CURR OPIN ENV SUST, V8, P39, DOI 10.1016/j.cosust.2014.07.002
   Chaturvedi RK, 2012, CURR SCI INDIA, V103, P791
   DAC, 2015, AGR STAT GLANC 2014
   Dar MH, 2013, SCI REP-UK, V3, DOI 10.1038/srep03315
   Das A, 2014, INDIAN J AGR SCI, V84, P643
   De Boef WS, 2010, J SUSTAIN AGR, V34, P504, DOI 10.1080/10440046.2010.484689
   de Hann C., 1997, LIVE STOCK ENV FINDI
   De US, 2005, J INDIAN GEOPHYS UNI, V9, P173
   De U.S., 1999, DECCAN GEOGR, V37, P5
   Dhyani S. K., 2013, Indian Journal of Agroforestry, V15, P1
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   FAO and World Bank, 2001, FARM SYST POV IMPR F
   Fuhrer J, 2014, CABI CLIM CHANGE SER, V5, P1, DOI 10.1079/9781780642895.0000
   Garg Amit, 2015, 20151101 IND I MAN
   Ghosh PK, 2006, FIELD CROP RES, V96, P80, DOI 10.1016/j.fcr.2005.05.009
   Ghosh S, 2012, NAT CLIM CHANGE, V2, P86, DOI 10.1038/NCLIMATE1327
   GOI, 2014, AGR CESS 2010 11
   Gore P. G., 2010, 122010 IND MET DEP
   Goswami BN, 2006, SCIENCE, V314, P1442, DOI 10.1126/science.1132027
   Gregory PJ, 2005, PHILOS T R SOC B, V360, P2139, DOI 10.1098/rstb.2005.1745
   Gupta H, 2005, EPISODES, V28, P2
   Himanshu Sen A., 2013, EC POLIT WKLY, V16, P45
   Hobbs P. R., 2003, ASA special publications, V65, P149
   Hulme M., 1996, Climate Change and Southern Africa: An Exploration of Some Potential Impacts and Implications in the SADC Region: a Report Commissioned by WWF International and Co-ordinated by the Climatic Research Unit, UEA, Norwich
   Ionescu C, 2009, ENVIRON MODEL ASSESS, V14, P1, DOI 10.1007/s10666-008-9179-x
   Izaurralde RC, 2011, AGRON J, V103, P371, DOI 10.2134/agronj2010.0304
   Khadait V. N., 2011, RES J AGR SCI, V2, P110
   Kinyangi J., 2015, CCAFS Info note
   Kontar E. A., 2007, IAHS PUBLICATION, V312
   Kumar A, 2014, J EXP BOT, V65, P6265, DOI 10.1093/jxb/eru363
   Kumar K. K. S., 2007, Working paper 19/2007
   Kumar KK, 2011, CURR SCI INDIA, V101, P312
   Kumar KK, 2011, CLIM DYNAM, V36, P2159, DOI 10.1007/s00382-010-0974-0
   Kumar KN, 2013, WEATHER CLIM EXTREME, V1, P42, DOI 10.1016/j.wace.2013.07.006
   Kumar P., 1998, AGR EC POLICY SERIES, V98-01
   Kumar P., 2009, Agricultural economic Research Review, V22, P237, DOI [10.22004/ag.econ.57405, DOI 10.22004/AG.ECON.57405]
   LAL M, 1995, CURR SCI INDIA, V69, P752
   Lal M, 2001, CURR SCI INDIA, V81, P1196
   Lal Rattan, 2013, Ecohydrology & Hydrobiology, V13, P8, DOI 10.1016/j.ecohyd.2013.03.006
   Louwaars NP, 2012, J CROP IMPROV, V26, P39, DOI 10.1080/15427528.2011.611277
   Maharjan S. K., 2011, COMMUNITY SEED BANK, P54
   Maini P, 2016, MAUSAM, V67, P297
   Maini P, 2011, CURR SCI INDIA, V101, P1296
   Mall RK, 2007, CLIMATIC CHANGE, V82, P225, DOI 10.1007/s10584-006-9236-x
   Mall RK, 2006, CLIMATIC CHANGE, V78, P445, DOI 10.1007/s10584-005-9042-x
   Mehta CR, 2014, AMA-AGR MECH ASIA AF, V45, P43
   Milne E., 2012, 9 CCAFS CGIAR
   Mishra J.P., 2012, J FOOD LEGUMES, V25, P310
   Mishra P. K., 1995, EC POLIT WKLY, V30, P84
   Mittal S., 2007, EC POLIT WKLY    FEB, P444
   Mondal I., 2014, International Journal of Remote Sensing Applications, V4, P103, DOI [10.14355/ijrsa.2014.0402.04, DOI 10.14355/IJRSA.2014.0402.04]
   NAAS, 2013, 65 NAAS
   NRAA, 2013, Position paper No. 6
   Osman M., 2015, INDIAN J DRYLAND AGR, V30, P17
   Pai DS., 2004, Mausam, V55, P281, DOI DOI 10.54302/MAUSAM.V55I2.1083
   Pandey DN, 2003, CURR SCI INDIA, V85, P46
   Paroda R. S., 2000, Agricultural Economics Research Review, V13, P1
   Patel S. K., 2014, J POULT SCI TECHNOL, V2, P79
   Pathak P, 2005, NATURAL RESOURCES MANAGEMENT IN AGRICULTURE: METHODS FOR ASSESSING ECONOMIC AND ENVIRONMENTAL IMPACTS, P53, DOI 10.1079/9780851998282.0053
   Praduman Kumar Praduman Kumar, 2007, Economic and Political Weekly, V42, P3567
   Praharaj C.S., 2011, P 10 AGR SCI C SOIL, P410
   Prasad H.A.C., 2009, 22009DEA GOV IND
   Prasad Y.G., 2015, TECHNOLOGY DEMONSTRA
   Prasad YG., 2014, Smart practices and technologies for climate resilient agriculture
   Radhakrishna R., 2004, FOOD SECURITY NUTR V
   Raghavan K., 1967, Indian J. Met. Geophys, V18, P91
   Rajeevan M., 2013, CLIMATE CHANGE SUSTA, P1
   Ranuzzi A, 2012, ICRIER POLICY SERIES, V16
   Rao BB, 2015, AGR FOREST METEOROL, V200, P192, DOI 10.1016/j.agrformet.2014.09.023
   Rao CS, 2016, MAUSAM, V67, P169
   Rao CS, 2015, ADV AGRON, V133, P113, DOI 10.1016/bs.agron.2015.05.004
   Rao V.U.M, 2013, ANN AGR RES, V34, P15
   Rao VUM, 2014, Hailstorm threat to Indian agriculture: a historial perspective and future strategies
   Rathore L. S., 2013, J AGR PHYS, V13, P89
   Reddy B.S., 2015, INDIAN FARMING, V65, P45
   Reddy G.R., 2014, INDIAN J DRYLAND AGR, V29, P11
   Rosenstock T.S., 2015, WHAT IS SCI BASIS CL
   Samra J. S., 2006, Drought management strategies in India, P1
   Samra J.S, 2012, 3 INT AGR C NEW DELH
   Sapkota TB, 2015, J INTEGR ENVIRON SCI, V12, P31, DOI 10.1080/1943815X.2015.1110181
   Sarkar RK, 2009, INDIAN J AGR SCI, V79, P876
   Sati VP, 2010, J LIVEST SCI, V1, P9
   Scherr S.J., 2012, Agriculture Food Security, V1, P1
   Shanwad U.K., 2015, P 5 INT S FARM SYST
   Sharma KR., 2015, J SOIL WATER CONSERV, V14, P219
   Sikka AK, 2016, MAUSAM, V67, P155
   Sikka A.K., 2013, Atlas on the vulnerability of Indian agriculture to climate change
   Singh D.R., 2013, TRAINING MANUAL FORE, P236
   Singh H.B., 2009, BANKING INSURANCE, V4th
   Soora N.K., 2013, CLIMATIC CHANGE, V118, P669
   Srinivasarao C., 2011, SOIL CARBON SEQUESTR
   Srinivasarao C., 2013, INDIAN J DRYLAND AGR, V28, P1
   Srinivasarao C, 2016, AGR ECOSYST ENVIRON, V218, P73, DOI 10.1016/j.agee.2015.11.016
   Srinivasarao C, 2014, LAND DEGRAD DEV, V25, P173, DOI 10.1002/ldr.1158
   Srinivasarao C, 2014, SCI TOTAL ENVIRON, V487, P587, DOI 10.1016/j.scitotenv.2013.10.006
   Srinivasarao C, 2013, ADV AGRON, V121, P253, DOI 10.1016/B978-0-12-407685-3.00005-0
   Srinivasarao C, 2012, SOIL SCI SOC AM J, V76, P168, DOI 10.2136/sssaj2011.0184
   Srivastava A.K., 2000, MAUSAM, V51, P113, DOI [https://doi.org/10.54302/mausam.v51i2.1766, DOI 10.54302/MAUSAM.V51I2.1766]
   Stouffer R.J., 2011, CMIP5 Long-term experimental Design, V16, P5
   Subba Rao A. V. M., 2004, P NAT C CONS AGR CON, P9
   Swaminathan MS, 2001, CURR SCI INDIA, V81, P948
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Udmale P. D., 2014, The Open Agriculture Journal, V8, P41, DOI 10.2174/1874331501408010041
   Valdes A., 1986, CROP INSURANCE AGR D
   Venkatesh MS, 2013, CAN J SOIL SCI, V93, P127, DOI [10.4141/CJSS2012-072, 10.4141/cjss2012-072]
   Venkateswarlu B, 2012, CURR SCI INDIA, V102, P882
   Venkateswarlu B., 2009, Indian Journal of Agronomy, V54, P226
   Venkateswarlu B., 2012, DEMONSTRATION CLIMAT
   Werner AD, 2009, GROUND WATER, V47, P197, DOI 10.1111/j.1745-6584.2008.00535.x
   WMO, 2001, 920 WMO
NR 134
TC 77
Z9 78
U1 35
U2 423
PU ELSEVIER ACADEMIC PRESS INC
PI SAN DIEGO
PA 525 B STREET, SUITE 1900, SAN DIEGO, CA 92101-4495 USA
SN 0065-2113
EI 2213-6789
BN 978-0-12-804691-3; 978-0-12-804842-9
J9 ADV AGRON
JI Adv. Agron.
PY 2016
VL 140
BP 101
EP 214
DI 10.1016/bs.agron.2016.06.003
PG 114
WC Agronomy
WE Book Citation Index – Science (BKCI-S); Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA BH0CF
UT WOS:000394566200005
DA 2025-01-10
ER

PT J
AU Yue, XP
   Liu, W
   Wang, XW
   Yang, JT
   Lan, YX
   Zhu, ZP
   Yao, X
AF Yue, Xupan
   Liu, Wang
   Wang, Xiaowen
   Yang, Jintao
   Lan, Yuxiang
   Zhu, Zhipeng
   Yao, Xiong
TI Constructing an urban heat network to mitigate the urban heat island
   effect from a connectivity perspective
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Urban heat island network; Climate adaptation; Morphological spatial
   pattern analysis; Connectivity; Circuit theory
ID LAND-SURFACE TEMPERATURE; LANDSCAPE CONNECTIVITY; SPATIAL-PATTERN;
   CIRCUIT-THEORY; GREEN SPACES; CLIMATE; TECHNOLOGIES; IMPACT
AB Urban heat islands (UHIs) have been investigated from various perspectives. However, little is known about UHImitigation strategies in terms of UHI networks and the overall connectivity. Therefore, we developed a research framework to construct a UHI network from a connectivity perspective in a typical "furnace city"-Fuzhou city, China. Initially, morphological spatial patterns, mean standard deviations, and landscape connectivity were analyzed to identify UHI sources and assess their importance. Subsequently, six natural and socioeconomic factors were integrated into the model to create a combined resistance surface for thermal diffusion. Finally, circuit theory was applied to build a UHI network and pinpoint key nodes. Our results show that the combined resistance increased from the center of the study area to the periphery. In addition, 38 UHI sources, 84 thermal corridors, 30 heating nodes, and 21 cooling nodes were identified. The UHI sources and key nodes were primarily distributed in an uneven manner in the nuclear and northwestern regions of the research area. Furthermore, cooling measures were developed for UHI networks to reduce network connectivity. Our research framework offers a new perspective for promoting healthy urban development and climate-adaptation planning.
C1 [Yue, Xupan; Liu, Wang; Wang, Xiaowen; Yang, Jintao; Lan, Yuxiang; Zhu, Zhipeng; Yao, Xiong] Fujian Univ Technol, Coll Architecture & Urban Planning, Fuzhou 350118, Peoples R China.
   [Yao, Xiong] Minist Educ, Key Lab Ecol Energy Saving Study Dense Habitat, Shanghai 200092, Peoples R China.
C3 Fujian University of Technology
RP Yao, X (corresponding author), Fujian Univ Technol, Coll Architecture & Urban Planning, Fuzhou 350118, Peoples R China.
EM fjyx@fjut.edu.cn
RI Wang, Xiao-Wen/HTL-3465-2023
OI YAO, XIONG/0000-0002-3455-5798
FU National Natural Science Foundation of China [32301647, 32301648]; Key
   Labo-ratory of Ecology and Energy Saving Study of Dense Habitat,
   Ministry of Education, Tongji University [20220106]; Natural Science
   Foundation of Fujian Province, China [2021J05221]; Scientific Research
   Foundation of Fujian University of Technology [2022JG018, GY-Z20086]
FX This work was financially supported by the National Natural Science
   Foundation of China (Grant No. 32301647, 32301648) ; the Key Labo-ratory
   of Ecology and Energy Saving Study of Dense Habitat, Ministry of
   Education, Tongji University (Grant No. 20220106) ; the Natural Science
   Foundation of Fujian Province, China (Grant No. 2021J05221) ; and the
   Scientific Research Foundation of Fujian University of Technology (Grant
   No. 2022JG018, GY-Z20086) . We would like to thank Editage (
   www.editage.cn) for English language editing.
CR Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   Carlier J, 2019, SCI TOTAL ENVIRON, V651, P3241, DOI 10.1016/j.scitotenv.2018.10.077
   Chen LD, 2019, SCI CHINA EARTH SCI, V62, P2050, DOI 10.1007/s11430-019-9427-2
   Dai ZX, 2018, SCI TOTAL ENVIRON, V626, P1136, DOI 10.1016/j.scitotenv.2018.01.165
   Deilami K, 2018, INT J APPL EARTH OBS, V67, P30, DOI 10.1016/j.jag.2017.12.009
   Estoque RC, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15218-8
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Ezimand K, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103216
   Fu YJ, 2020, ECOL INDIC, V112, DOI 10.1016/j.ecolind.2019.106030
   Gao MW, 2022, ECOL INDIC, V139, DOI 10.1016/j.ecolind.2022.108867
   Gao Y, 2017, SCI REP-UK, V7, DOI 10.1038/srep46073
   Harmay NSM, 2021, SUSTAIN CITIES SOC, V69, DOI 10.1016/j.scs.2021.102861
   He BJ, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102028
   Herrera LP, 2017, BIODIVERS CONSERV, V26, P3465, DOI 10.1007/s10531-017-1416-7
   Huang LY, 2021, SUSTAIN CITIES SOC, V69, DOI 10.1016/j.scs.2021.102865
   Jang S, 2024, SUSTAIN CITIES SOC, V100, DOI 10.1016/j.scs.2023.105007
   Ke XL, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127159
   Kuang WH, 2015, LANDSCAPE ECOL, V30, P357, DOI 10.1007/s10980-014-0128-6
   Leonard PB, 2017, METHODS ECOL EVOL, V8, P519, DOI 10.1111/2041-210X.12689
   Liu F, 2024, SCI TOTAL ENVIRON, V915, DOI 10.1016/j.scitotenv.2024.169950
   Liu J, 2021, SUSTAIN CITIES SOC, V66, DOI 10.1016/j.scs.2020.102698
   [刘婷 Liu Ting], 2023, [生态学报, Acta Ecologica Sinica], V43, P615
   Lu YS, 2021, IEEE J-STARS, V14, P11386, DOI 10.1109/JSTARS.2021.3124558
   Luo JL, 2023, ECOL INDIC, V154, DOI 10.1016/j.ecolind.2023.110887
   Mabon L, 2021, GLOBAL ENVIRON CHANG, V68, DOI 10.1016/j.gloenvcha.2021.102248
   Maimaitiyiming M, 2014, ISPRS J PHOTOGRAMM, V89, P59, DOI 10.1016/j.isprsjprs.2013.12.010
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Marando F, 2022, SUSTAIN CITIES SOC, V77, DOI 10.1016/j.scs.2021.103564
   Masoudi M, 2019, ECOL INDIC, V98, P200, DOI 10.1016/j.ecolind.2018.09.058
   Masson V, 2020, ANNU REV ENV RESOUR, V45, P411, DOI 10.1146/annurev-environ-012320-083623
   Mokhtari Z, 2022, SUSTAIN CITIES SOC, V83, DOI 10.1016/j.scs.2022.103964
   Morabito M, 2021, SCI TOTAL ENVIRON, V751, DOI 10.1016/j.scitotenv.2020.142334
   Nie WB, 2023, SCI TOTAL ENVIRON, V859, DOI 10.1016/j.scitotenv.2022.160262
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   Peng J, 2022, LANDSCAPE ECOL, V37, P1707, DOI 10.1007/s10980-022-01439-3
   Peng J, 2020, LANDSCAPE URBAN PLAN, V202, DOI 10.1016/j.landurbplan.2020.103873
   Peng J, 2018, SCI TOTAL ENVIRON, V644, P781, DOI 10.1016/j.scitotenv.2018.06.292
   Qian WQ, 2023, SUSTAIN CITIES SOC, V94, DOI 10.1016/j.scs.2023.104525
   Santamouris M, 2018, J CIV ENG MANAG, V24, P638, DOI 10.3846/jcem.2018.6604
   Santos M, 2019, ECOLOGY, V100, DOI 10.1002/ecy.2883
   Shen ZJ, 2022, ECOL INDIC, V142, DOI 10.1016/j.ecolind.2022.109187
   Shiflett SA, 2017, SCI TOTAL ENVIRON, V579, P495, DOI 10.1016/j.scitotenv.2016.11.069
   Silveira C, 2024, SUSTAIN CITIES SOC, V112, DOI 10.1016/j.scs.2024.105589
   Soille P, 2009, PATTERN RECOGN LETT, V30, P456, DOI 10.1016/j.patrec.2008.10.015
   Spanowicz AG, 2019, LANDSCAPE ECOL, V34, P2261, DOI 10.1007/s10980-019-00881-0
   Steeneveld GJ, 2014, LANDSCAPE URBAN PLAN, V121, P92, DOI 10.1016/j.landurbplan.2013.09.001
   Tan XY, 2021, SUSTAIN CITIES SOC, V67, DOI 10.1016/j.scs.2021.102711
   Tian YH, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9091653
   Wang YJ, 2022, ECOL INDIC, V142, DOI 10.1016/j.ecolind.2022.109258
   Wang ZY, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13105732
   Wei JX, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10020327
   Wong PPY, 2016, BUILD ENVIRON, V95, P199, DOI 10.1016/j.buildenv.2015.09.024
   Xie P, 2020, SUSTAIN CITIES SOC, V59, DOI 10.1016/j.scs.2020.102162
   Yao X, 2022, SUSTAIN CITIES SOC, V82, DOI 10.1016/j.scs.2022.103902
   Yu SY, 2020, SCI TOTAL ENVIRON, V725, DOI 10.1016/j.scitotenv.2020.138229
   Yu ZW, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103135
   Yu ZW, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13061127
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Zhai TL, 2022, FRONT ECOL EVOL, V10, DOI 10.3389/fevo.2022.828979
   Zhang Q, 2022, BUILD ENVIRON, V222, DOI 10.1016/j.buildenv.2022.109375
   Zhang X, 2022, ECOL INDIC, V145, DOI 10.1016/j.ecolind.2022.109715
   Zhang YZ, 2017, INFRARED PHYS TECHN, V86, P35, DOI 10.1016/j.infrared.2017.08.008
   Zhao ZY, 2024, ECOL INDIC, V159, DOI 10.1016/j.ecolind.2024.111665
   Zhou DC, 2018, SCI TOTAL ENVIRON, V628-629, P415, DOI 10.1016/j.scitotenv.2018.02.074
   Zhou GJ, 2023, SCI TOTAL ENVIRON, V873, DOI 10.1016/j.scitotenv.2023.162261
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
NR 68
TC 1
Z9 1
U1 66
U2 66
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2210-6707
EI 2210-6715
J9 SUSTAIN CITIES SOC
JI Sust. Cities Soc.
PD NOV 1
PY 2024
VL 114
AR 105774
DI 10.1016/j.scs.2024.105774
EA AUG 2024
PG 14
WC Construction & Building Technology; Green & Sustainable Science &
   Technology; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Science & Technology - Other Topics;
   Energy & Fuels
GA F7A4C
UT WOS:001311301600001
DA 2025-01-10
ER

PT J
AU Peng, Y
   Mao, KK
   Li, HR
   Ping, JF
   Zhu, JY
   Liu, XY
   Zhang, ZT
   Jin, MH
   Wu, C
   Wang, N
   Yesaya, A
   Wilson, K
   Xiao, YT
AF Peng, Yan
   Mao, Kaikai
   Li, Hongran
   Ping, Junfen
   Zhu, Jingyun
   Liu, Xinye
   Zhang, Zhuting
   Jin, Minghui
   Wu, Chao
   Wang, Nan
   Yesaya, Alexander
   Wilson, Kenneth
   Xiao, Yutao
TI Extreme genetic signatures of local adaptation in a notorious rice pest,
   Chilo suppressalis
SO NATIONAL SCIENCE REVIEW
LA English
DT Article; Early Access
DE local adaptation; Chilo suppressalis; gene flow; cold tolerance
ID STEM BORER; POPULATION-STRUCTURE; POSITIVE SELECTION; GENOME; HISTORY;
   LEPIDOPTERA; DIFFERENTIATION; ASSOCIATION; TOLERANCE; INFERENCE
AB Climatic variation stands as a significant driving force behind genetic differentiation and the evolution of adaptive traits. Chilo (C.) suppressalis, commonly known as the rice stem borer, is a highly destructive pest that crucially harms rice production. The lack of natural population genomics data has hindered a more thorough understanding of its climate adaptation, particularly the genetic basis underlying adaptive traits. To overcome this obstacle, our study employed completely resequenced genomes of 384 individuals to explore the population structure, demographic history, and gene flow of C. suppressalis in China. This study observed that its gene flow occurred asymmetrically, moving from central populations to peripheral populations. Using genome-wide selection scans and genotype-environment association studies, we identified potential loci that may be associated with climatic adaptation. The most robust signal was found to be associated with cold tolerance, linked to a homeobox gene, goosecoid (GSC), whose expression level was significantly different in low and high latitudes. Moreover, downregulating the expression of this gene by RNAi enhances its cold tolerance phenotypes. Our findings have uncovered and delved into the genetic foundation of the ability of C. suppressalis to adapt to its environment. This is essential in ensuring the continued effectiveness and sustainability of novel control techniques.
C1 [Peng, Yan; Mao, Kaikai; Li, Hongran; Ping, Junfen; Zhu, Jingyun; Liu, Xinye; Zhang, Zhuting; Jin, Minghui; Wu, Chao; Wang, Nan; Yesaya, Alexander; Wilson, Kenneth; Xiao, Yutao] Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Minist Agr & Rural Affairs, Shenzhen Branch,Guangdong Lab Lingnan Modern Agr,K, Shenzhen 518120, Peoples R China.
   [Mao, Kaikai] Guangxi Univ, Coll Agr, Guangxi Key Lab Agroenvironm & Agr Prod Safety, Nanning 530004, Peoples R China.
   [Ping, Junfen] Henan Univ, Sch Life Sci, Kaifeng 475004, Peoples R China.
   [Ping, Junfen] Henan Univ, Shenzhen Res Inst, Shenzhen 518000, Peoples R China.
   [Wilson, Kenneth] Univ Lancaster, Lancaster Environm Ctr, Lancaster LA1 4YW, England.
C3 Ministry of Agriculture & Rural Affairs; Chinese Academy of Agricultural
   Sciences; Agriculture Genomes Institute at Shenzhen, CAAS; Guangdong
   Laboratory for Lingnan Modern Agriculture; Guangxi University; Henan
   University; Henan University; Lancaster University
RP Xiao, YT (corresponding author), Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Minist Agr & Rural Affairs, Shenzhen Branch,Guangdong Lab Lingnan Modern Agr,K, Shenzhen 518120, Peoples R China.
EM xiaoyutao@caas.cn
RI Zhang, Zhuting/HPG-8724-2023; liu, xy/JEP-3175-2023
FU Agricultural Science and Technology Innovation Program; Agricultural
   Genomics Institute at Shenzhen
FX We express our sincere appreciation to the three anonymous reviewers for
   their time and patience in reviewing the content and analysis of this
   manuscript. We thank Dr. Hongru Wang and Dr. Peng Wang of the
   Agricultural Genomics Institute at Shenzhen, Chinese Academy of
   Agricultural Sciences for the comments.
CR Alachiotis N, 2018, COMMUN BIOL, V1, DOI 10.1038/s42003-018-0085-8
   Andersen JL, 2015, FUNCT ECOL, V29, P55, DOI 10.1111/1365-2435.12310
   [Anonymous], 1957, Jpn J Appl Entomol Zool, DOI DOI 10.1303/JJAEZ.1957.100
   Basu A, 2016, P NATL ACAD SCI USA, V113, P1594, DOI 10.1073/pnas.1513197113
   Bay RA, 2017, AM NAT, V189, P463, DOI 10.1086/691233
   BLUM M, 1994, GENOMICS, V21, P388, DOI 10.1006/geno.1994.1281
   Browning BL, 2018, AM J HUM GENET, V103, P338, DOI 10.1016/j.ajhg.2018.07.015
   BULMER MG, 1972, GENET RES, V19, P17, DOI 10.1017/S0016672300014221
   Chen YX, 2017, GIGASCIENCE, V7, DOI 10.1093/gigascience/gix120
   Cheng XH, 2017, MOL ECOL, V26, P6871, DOI 10.1111/mec.14416
   Cingolani P, 2012, FLY, V6, P80, DOI 10.4161/fly.19695
   Danecek P, 2017, BIOINFORMATICS, V33, P2037, DOI 10.1093/bioinformatics/btx100
   Danecek P, 2011, BIOINFORMATICS, V27, P2156, DOI 10.1093/bioinformatics/btr330
   Denlinger D.L., 1991, P174
   Dhawan AK., 2013, Integrated Pest Management
   Excofffier L, 2021, BIOINFORMATICS, V37, P4882, DOI 10.1093/bioinformatics/btab468
   Excoffier L, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003905
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Forster J, 2012, P NATL ACAD SCI USA, V109, P19310, DOI 10.1073/pnas.1210460109
   Forster J, 2011, AM NAT, V178, P668, DOI 10.1086/662174
   Fu DM, 2016, J THERM BIOL, V61, P115, DOI 10.1016/j.jtherbio.2016.09.006
   Ge ZY, 2014, GENOME, V57, P79, DOI 10.1139/gen-2013-0188
   Günther T, 2013, GENETICS, V195, P205, DOI 10.1534/genetics.113.152462
   Hoban S, 2016, AM NAT, V188, P379, DOI 10.1086/688018
   Hoffmann AA, 2017, CURR OPIN INSECT SCI, V21, P7, DOI 10.1016/j.cois.2017.04.009
   Jin MH, 2023, INNOVATION-AMSTERDAM, V4, DOI 10.1016/j.xinn.2023.100454
   Kawecki TJ, 2021, MOL BIOL EVOL, V38, P2732, DOI 10.1093/molbev/msab061
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Khan Z., 1991, WORLD BIBLIO RICE ST
   Kim D, 2019, NAT BIOTECHNOL, V37, P907, DOI 10.1038/s41587-019-0201-4
   Kottler EJ, 2021, TRENDS ECOL EVOL, V36, P533, DOI 10.1016/j.tree.2021.02.004
   Kozak GM, 2019, CURR BIOL, V29, P3501, DOI 10.1016/j.cub.2019.08.053
   Li BY, 2024, NAT COMMUN, V15, DOI 10.1038/s41467-024-45631-2
   Li H., 2013, GENOMICS, DOI [10.48550/arXiv.1303.3997, DOI 10.48550/ARXIV.1303.3997]
   Li H, 2009, BIOINFORMATICS, V25, P2078, DOI 10.1093/bioinformatics/btp352
   Li XW, 2021, J PEST SCI, V94, P845, DOI 10.1007/s10340-020-01301-y
   Livak KJ, 2001, METHODS, V25, P402, DOI 10.1006/meth.2001.1262
   Lu MX, 2013, SCI REP-UK, V3, DOI 10.1038/srep03211
   Lu MX, 2012, ANN ENTOMOL SOC AM, V105, P479, DOI 10.1603/AN11171
   Ma WH, 2020, MOL ECOL RESOUR, V20, P268, DOI 10.1111/1755-0998.13078
   Mao KK, 2019, J ECON ENTOMOL, V112, P1866, DOI 10.1093/jee/toz109
   Meng XF, 2008, MOL ECOL, V17, P2880, DOI 10.1111/j.1365-294X.2008.03792.x
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Pavlidis P, 2013, MOL BIOL EVOL, V30, P2224, DOI 10.1093/molbev/mst112
   Peng Y, 2023, MOL BIOL EVOL, V40, DOI 10.1093/molbev/msad112
   Petkova D, 2016, NAT GENET, V48, P94, DOI 10.1038/ng.3464
   Polechová J, 2015, P NATL ACAD SCI USA, V112, P6401, DOI 10.1073/pnas.1421515112
   Pörtner HO, 2006, PHYSIOL BIOCHEM ZOOL, V79, P295, DOI 10.1086/499986
   Price MN, 2009, MOL BIOL EVOL, V26, P1641, DOI 10.1093/molbev/msp077
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Raj A, 2014, GENETICS, V197, P573, DOI 10.1534/genetics.114.164350
   Rausch T, 2012, BIOINFORMATICS, V28, pI333, DOI 10.1093/bioinformatics/bts378
   Rellstab C, 2015, MOL ECOL, V24, P4348, DOI 10.1111/mec.13322
   Rousset F, 1997, GENETICS, V145, P1219
   Sabeti PC, 2007, NATURE, V449, P913, DOI 10.1038/nature06250
   Sato A, 2014, P NATL ACAD SCI USA, V111, pE1249, DOI 10.1073/pnas.1322134111
   Savolainen O, 2013, NAT REV GENET, V14, P807, DOI 10.1038/nrg3522
   Secomandi S, 2023, CELL REP, V42, DOI 10.1016/j.celrep.2023.111992
   Sunday JM, 2011, P ROY SOC B-BIOL SCI, V278, P1823, DOI 10.1098/rspb.2010.1295
   Szpiech ZA, 2014, MOL BIOL EVOL, V31, P2824, DOI 10.1093/molbev/msu211
   Tang K, 2007, PLOS BIOL, V5, P1587, DOI 10.1371/journal.pbio.0050171
   Tang XT, 2016, MITOCHONDRIAL DNA A, V27, P1567, DOI 10.3109/19401736.2014.958670
   Terhorst J, 2017, NAT GENET, V49, P303, DOI 10.1038/ng.3748
   Tong DD, 2022, CELL REP, V41, DOI 10.1016/j.celrep.2022.111843
   Tong XL, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-33366-x
   Voight BF, 2006, PLOS BIOL, V4, P446, DOI 10.1371/journal.pbio.0040072
   Wallberg A, 2014, NAT GENET, V46, P1081, DOI 10.1038/ng.3077
   Wang ST, 2022, CELL, V185, P3138, DOI 10.1016/j.cell.2022.06.042
   Wright S, 1931, GENETICS, V16, P0097
   Xiao HJ, 2017, J PEST SCI, V90, P117, DOI 10.1007/s10340-016-0769-0
   Yadav S, 2019, MOL ECOL, V28, P3395, DOI 10.1111/mec.15146
   Zhan S, 2011, CELL, V147, P1171, DOI 10.1016/j.cell.2011.09.052
   Zhang Jun Zhang Jun, 2005, Scientia Agricultura Sinica, V38, P2451
   Zhou X, 2012, NAT GENET, V44, P821, DOI 10.1038/ng.2310
NR 74
TC 1
Z9 1
U1 34
U2 34
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 2095-5138
EI 2053-714X
J9 NATL SCI REV
JI Natl. Sci. Rev.
PD 2024 AUG 1
PY 2024
DI 10.1093/nsr/nwae221
EA AUG 2024
PG 15
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA A2T0J
UT WOS:001281093400001
OA gold
DA 2025-01-10
ER

PT J
AU McElwee, P
   Tuyen, NP
   Van Hue, L
   Huong, VTD
AF McElwee, Pamela
   Tuyen, Nghiem Phuong
   Van Hue, Le Thi
   Huong, Vu Thi Dieu
TI Climate precarity in rural livelihoods: Agrarian transformations and
   smallholder vulnerability in Vietnam
SO JOURNAL OF AGRARIAN CHANGE
LA English
DT Article
DE agrarian transformations; climate adaptation; climate precarity;
   intensification; swidden agriculture; vulnerability
ID ETHNIC-MINORITY LIVELIHOODS; MEKONG DELTA; SHIFTING CULTIVATION; CHANGE
   ADAPTATION; AGRICULTURAL TRANSFORMATION; SWIDDEN AGRICULTURE; CENTRAL
   HIGHLANDS; SOUTHEAST-ASIA; GIANG PROVINCE; FOOD SECURITY
AB In recent decades, agrarian transformations in Southeast Asia have resulted in significant environmental and social change, yet insufficient attention has focused on the particular pathways by which these changes have increased vulnerability to climate change. In particular, climate precarity, a situation in which class, social, labour and/or gender inequities amplify negative impacts from climate change, has been on the rise for many smallholders. Using case studies in Vietnam of changes to swidden agriculture in upland areas and the loss of deepwater rice systems in the Mekong Delta lowlands, the paper examines social differentiation and ecological outcomes of these processes and how they have increased climate precarity, particularly for poor households and women. Based on longitudinal fieldwork in affected regions, we identify key changes contributing to climate precarity as farming systems intensify. In particular, loss of flexibility in farmer decision-making, loss of voluntary engagement with markets, and declining access to social capital and entitlements have increased risks for households and reduced adaptation options. Suggestions are made to more directly address these elements in future agricultural and climate policies, rather than current approaches to climate adaptation that often promote even more intensification of agriculture, which runs the risk of exacerbating precarity.
C1 [McElwee, Pamela] Rutgers State Univ, New Brunswick, NJ 08854 USA.
   [Tuyen, Nghiem Phuong; Van Hue, Le Thi; Huong, Vu Thi Dieu] Cent Inst Nat Resources & Environm Studies, Hanoi, Vietnam.
C3 Rutgers University System; Rutgers University New Brunswick
RP McElwee, P (corresponding author), Rutgers State Univ, New Brunswick, NJ 08854 USA.
EM pamela.mcelwee@rutgers.edu
CR Adger WN, 2020, URBAN STUD, V57, P1588, DOI 10.1177/0042098020904594
   Adger WN, 2000, ANN ASSOC AM GEOGR, V90, P738, DOI 10.1111/0004-5608.00220
   Agrawal A, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P350
   Akram-Lodhi, 2007, J PEASANT STUD, V5, P73
   [Anonymous], 2010, Vietnam - Economics of adaptation to climate change
   Baird IG, 2022, J AGRAR CHANGE, V22, P278, DOI 10.1111/joac.12452
   Bales K, 2021, ENERGY RES SOC SCI, V77, DOI 10.1016/j.erss.2021.102096
   Barnett J, 2020, PROG HUM GEOG, V44, P1172, DOI 10.1177/0309132519898254
   Bayrak MM, 2022, CLIM DEV, V14, P935, DOI 10.1080/17565529.2022.2028596
   Berg H, 2001, CROP PROT, V20, P897, DOI 10.1016/S0261-2194(01)00039-4
   Bernstein H, 2006, CAN J DEV STUD, V27, P449, DOI 10.1080/02255189.2006.9669166
   BHARADWAJ K, 1985, J PEASANT STUD, V12, P7, DOI 10.1080/03066158508438273
   Biggs D., 2009, Contested waterscapes in the Mekong region: Hydropower, livelihoods and governance, P203
   Bonnin C, 2014, J PEASANT STUD, V41, P321, DOI 10.1080/03066150.2014.905471
   Bonnin C, 2012, GEOFORUM, V43, P95, DOI 10.1016/j.geoforum.2011.07.006
   Borras S.M., 2011, Political Dynamics of Land-grabbing in Southeast Asia: Understanding Europes Role
   Breman Jan., 1996, FOOTLOOSE LABOUR WOR, DOI [DOI 10.1017/CBO9781139171076, 10.1017/cbo9781139171076]
   Brown PR, 2019, CLIM DEV, V11, P383, DOI 10.1080/17565529.2018.1442798
   Brown PR, 2018, INT J AGR SUSTAIN, V16, P255, DOI 10.1080/14735903.2018.1472858
   Chapman A, 2016, SCI TOTAL ENVIRON, V559, P326, DOI 10.1016/j.scitotenv.2016.02.162
   Cochard R, 2017, ENVIRON REV, V25, P199, DOI 10.1139/er-2016-0050
   Cohn AS, 2017, ANNU REV ENV RESOUR, V42, P347, DOI 10.1146/annurev-environ-102016-060946
   Cole R, 2022, J AGRAR CHANGE, V22, P139, DOI 10.1111/joac.12460
   Cramb RA, 2009, HUM ECOL, V37, P323, DOI 10.1007/s10745-009-9241-6
   Cramb R, 2017, J PEASANT STUD, V44, P813, DOI 10.1080/03066150.2016.1242482
   Cruz-Del Rosario T, 2019, J CONTEMP ASIA, V49, P517, DOI 10.1080/00472336.2019.1581832
   CUMMINGS RC, 1978, HUM ORGAN, V37, P235, DOI 10.17730/humo.37.3.f36870xx34531480
   Dao N, 2015, J PEASANT STUD, V42, P347, DOI 10.1080/03066150.2014.990445
   De Koninck R., 2012, GAMBLING LAND CONT E, DOI [10.2307/j.ctv1ntgwj, DOI 10.2307/J.CTV1NTGWJ]
   De Koninck R., 2013, LESPACE G OGRAPHIQUE, V42, P143, DOI [10.3917/eg.422.0143, DOI 10.3917/EG.422.0143]
   Dove MR, 1997, HUM ORGAN, V56, P91, DOI 10.17730/humo.56.1.l784408q35174516
   Dressler WH, 2017, AMBIO, V46, P291, DOI 10.1007/s13280-016-0836-z
   Dumaresq D, 2020, GLOB FOOD SECUR-AGR, V26, DOI 10.1016/j.gfs.2020.100391
   Tran DD, 2021, AGR WATER MANAGE, V243, DOI 10.1016/j.agwat.2020.106495
   Tran DD, 2018, AGR WATER MANAGE, V206, P187, DOI 10.1016/j.agwat.2018.04.039
   Tran DD, 2018, J ENVIRON MANAGE, V217, P429, DOI 10.1016/j.jenvman.2018.03.116
   Duy V. T., 2021, International Journal of Sustainable Development Research, V7, P28, DOI [10.11648/j.ijsdr.20210702.11, DOI 10.11648/J.IJSDR.20210702.11, https://doi.org/10.11648/j.ijsdr.20210702.11]
   Dwyer MB, 2013, DEV CHANGE, V44, P309, DOI 10.1111/dech.12014
   Eakin HC, 2014, GLOBAL ENVIRON CHANG, V27, P1, DOI 10.1016/j.gloenvcha.2014.04.013
   Eakin H, 2018, ANTHROPOCENE, V23, P43, DOI 10.1016/j.ancene.2018.08.002
   Eastin J, 2018, WORLD DEV, V107, P289, DOI 10.1016/j.worlddev.2018.02.021
   FAO, 2011, CLIMATE CHANGE IMPAC
   Fortier F., 2013, FRONTIERS CLIMATE EN, P241, DOI [10.1007/978-3-642-35804-3_13, DOI 10.1007/978-3-642-35804-3_13]
   Fortier F, 2013, DEV CHANGE, V44, P81, DOI 10.1111/dech.12001
   Fox J, 2000, BIOSCIENCE, V50, P521, DOI 10.1641/0006-3568(2000)050[0521:SCANOP]2.0.CO;2
   Friederichsen R, 2010, EUR J DEV RES, V22, P564, DOI 10.1057/ejdr.2010.23
   Griffin PJ, 2020, MED ANTHROPOL, V39, P333, DOI 10.1080/01459740.2019.1643854
   Hall D., 2011, Powers of Exclusion: Land Dilemmas in Southeast Asia
   Hambloch C, 2022, J AGRAR CHANGE, V22, P58, DOI 10.1111/joac.12462
   Hellin J, 2020, CLIMATE, V8, DOI 10.3390/cli8020035
   Henin B, 2002, J CONTEMP ASIA, V32, P3, DOI 10.1080/00472330280000021
   Hoang T. M., 2000, IN SITU CONSERVATION, P58
   Hossain M., 1995, VIETNAM IRRI PARTNER, P263
   Hunsberger C, 2018, WORLD DEV, V108, P309, DOI 10.1016/j.worlddev.2018.02.008
   Huynh T. P. L., 2021, AFD RES PAPERS
   IMHEN UNDP, 2015, VIET NAM SPEC REP MA
   ISPONRE, 2010, VIET NAM ASS REP CLI
   Jakobsen J, 2007, AGR SYST, V94, P309, DOI 10.1016/j.agsy.2006.09.007
   Jiao X, 2017, WORLD DEV, V97, P266, DOI 10.1016/j.worlddev.2017.04.019
   Kelley LC, 2018, GEOFORUM, V97, P22, DOI 10.1016/j.geoforum.2018.10.006
   Kontgis C, 2019, APPL GEOGR, V102, P71, DOI 10.1016/j.apgeog.2018.12.004
   Kuchimanchi BR, 2019, CLIM DEV, V11, P918, DOI 10.1080/17565529.2019.1593815
   Kyeyune V, 2016, GEOFORUM, V71, P33, DOI 10.1016/j.geoforum.2016.03.001
   Le Coq Jean-Francois., 2005, Japanese Journal of Southeast Asian Studies, V42, P519
   Le H., 2021, COMPETING LAND MANGR
   Li TaniaMurray., 2014, Lands end: Capitalist relations on an indigenous frontier, DOI DOI 10.1215/9780822376460
   Lovell RJ, 2021, ENVIRON DEV SUSTAIN, V23, P7089, DOI 10.1007/s10668-020-00905-9
   Mahanty S, 2016, ASIA PAC VIEWP, V57, P180, DOI 10.1111/apv.12122
   Marks D, 2019, ADV GLOB CHANGE RES, V64, P253, DOI 10.1007/978-3-319-90400-9_15
   McElwee P, 2022, J SOUTHEAST ASIAN ST, V53, P153, DOI 10.1017/S0022463422000194
   Meyfroidt P, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/7/074012
   Meyfroidt P, 2013, GLOBAL ENVIRON CHANG, V23, P1187, DOI 10.1016/j.gloenvcha.2013.04.005
   Middleton C., 2018, Living with floods in a mobile Southeast Asia: a political ecology of vulnerability, migration and environmental change, P22, DOI [DOI 10.4324/9781315761435, 10.4324/9781315761435]
   Mikulewicz M, 2019, GEOFORUM, V104, P267, DOI 10.1016/j.geoforum.2019.05.010
   Mikulewicz M, 2018, CLIM DEV, V10, P18, DOI 10.1080/17565529.2017.1304887
   Misra M, 2017, CLIM DEV, V9, P337, DOI 10.1080/17565529.2016.1145101
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Nanhthavong V, 2022, WORLD DEV, V155, DOI 10.1016/j.worlddev.2022.105885
   Natarajan N, 2021, AREA, V53, P431, DOI 10.1111/area.12693
   Natarajan N, 2019, ENVIRON PLAN E-NAT, V2, P899, DOI 10.1177/2514848619858155
   Nghiem T, 2020, LAND-BASEL, V9, DOI 10.3390/land9020056
   Nguyen K.V., 2015, Asian Journal of Agriculture and Rural Development, V5, P202
   Ngoc NTH, 2019, TROPICS, V27, P81, DOI 10.3759/tropics.MS18-09
   Nguyen V. K., 2014, ADAPTATION CLIMATE C, P89
   Nguyen VK, 2019, REG ENVIRON CHANGE, V19, P2069, DOI 10.1007/s10113-019-01548-x
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Paprocki K, 2018, ANN AM ASSOC GEOGR, V108, P955, DOI 10.1080/24694452.2017.1406330
   Park CMY, 2017, J PEASANT STUD, V44, P1235, DOI 10.1080/03066150.2017.1384725
   Parsons L., 2021, CLIMATE CHANGE GLOBA, P15, DOI DOI 10.4324/9780367822903-3
   Pingali P. L., 1994, 2 EPTD INT FOOD RES
   Pingali PL, 1997, FOOD POLICY, V22, P345, DOI 10.1016/S0306-9192(97)00023-7
   Potter L., 2001, ASIA PAC VIEWP, V42, P305, DOI [10.1111/1467-8373.00151, DOI 10.1111/1467-8373.00151]
   Räsänen A, 2016, REG ENVIRON CHANGE, V16, P2291, DOI 10.1007/s10113-016-0974-7
   Ribot J, 2014, J PEASANT STUD, V41, P667, DOI 10.1080/03066150.2014.894911
   Rice JL, 2022, ENVIRON PLAN E-NAT, V5, P625, DOI 10.1177/2514848621999286
   Rigg J., 2020, Elements in Politics and Society in Southeast Asia, DOI [10.1017/9781108750622, DOI 10.1017/9781108750622]
   Rigg J, 2016, GEOFORUM, V76, P63, DOI 10.1016/j.geoforum.2016.08.014
   Rigg J, 2016, J RURAL STUD, V43, P118, DOI 10.1016/j.jrurstud.2015.11.003
   Rigg J, 2012, WORLD DEV, V40, P1469, DOI 10.1016/j.worlddev.2012.03.001
   Rothuis AJ, 1998, AQUAC RES, V29, P59, DOI 10.1111/j.1365-2109.1998.tb01100.x
   Schmidt-Vogt D, 2009, HUM ECOL, V37, P269, DOI 10.1007/s10745-009-9239-0
   Schoenberger L, 2017, J PEASANT STUD, V44, P933, DOI 10.1080/03066150.2017.1327850
   Scott J., 1999, SEEING STATE
   Shrestha BB, 2019, NAT HAZARDS, V97, P157, DOI 10.1007/s11069-019-03632-1
   Siddiqui T, 2021, GLOB POLICY, V12, P91, DOI 10.1111/1758-5899.12855
   Sikor T., 2005, Journal of Agrarian Change, V5, P405, DOI 10.1111/j.1471-0366.2005.00106.x
   Singh C, 2019, ENVIRON DEV, V30, P35, DOI 10.1016/j.envdev.2019.04.007
   Smith W, 2019, POLIT GEOGR, V72, P76, DOI 10.1016/j.polgeo.2019.04.004
   Standing G, 2011, BLOOMSB REVELAT, P1
   Sugden F, 2014, DEV CHANGE, V45, P656, DOI 10.1111/dech.12103
   Tanaka K., 1995, Southeast Asian Studies, V33, P81
   Taylor M, 2015, ROUT EXPLOR DEV STUD, P1
   Taylor M, 2018, J PEASANT STUD, V45, P89, DOI 10.1080/03066150.2017.1312355
   Taylor M, 2013, CLIM DEV, V5, P318, DOI 10.1080/17565529.2013.830954
   Taylor P, 2016, ASIA PAC VIEWP, V57, P145, DOI 10.1111/apv.12125
   Taylor P, 2013, MOD ASIAN STUD, V47, P500, DOI 10.1017/S0026749X12000406
   Taylor Philip., 2007, J VIETNAM STUD, V2, P3, DOI DOI 10.1525/VS.2007.2.2.3
   Thai T. M., 2010, JAPANESE J SE ASIAN, V48, P425
   Thanh BN, 2021, ENVIRON SCI POLICY, V122, P49, DOI 10.1016/j.envsci.2021.04.010
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   Tran TA, 2020, ASIA PAC VIEWP, V61, P162, DOI 10.1111/apv.12241
   Thu TP, 2020, LAND USE POLICY, V99, DOI 10.1016/j.landusepol.2017.10.057
   Toan L. T., 2021, CLIMATE CHANGE VIETN
   Tran D. V., 2006, SE ASIAN STUD, V41, P491
   Tran N. L. D., 2022, LAND USE POLICY, V119
   TRAN T., 2017, Water Resour. Rural. Dev, V9, P67, DOI [https://doi.org/10.1016/j.wrr.2017.04.002, DOI 10.1016/J.WRR.2017.04.002, 10.1016/j.wrr.2017.04.002]
   Truong HTT, 2020, J ASIAN AFR STUD, V55, P880, DOI 10.1177/0021909620935427
   Tschakert P, 2013, CLIM DEV, V5, P340, DOI 10.1080/17565529.2013.828583
   Nguyen TA, 2020, J RURAL STUD, V74, P86, DOI 10.1016/j.jrurstud.2019.12.008
   Turner S, 2019, J PEASANT STUD, V46, P276, DOI 10.1080/03066150.2017.1382477
   Turner S, 2012, PROF GEOGR, V64, P540, DOI 10.1080/00330124.2011.611438
   Turner Sarah., 2015, Frontier Livelihoods: Hmong in the Sino-Vietnamese Borderlands
   Turner Sarah., 2008, J VIETNAM STUD, V3, P158
   Nguyen VK, 2018, FOOD SECUR, V10, P1615, DOI 10.1007/s12571-018-0848-6
   van Staveren MF, 2018, J ENVIRON POL PLAN, V20, P267, DOI 10.1080/1523908X.2017.1348287
   Vandergeest P, 1999, RURAL SOCIOL, V64, P573, DOI 10.1111/j.1549-0831.1999.tb00379.x
   Venkatasubramanian K, 2018, DEV CHANGE, V49, P1580, DOI 10.1111/dech.12448
   Vicol M, 2022, J AGRAR CHANGE, V22, P3, DOI 10.1111/joac.12471
   Vien TD, 2006, MT RES DEV, V26, P192, DOI 10.1659/0276-4741(2006)26[192:UTSATE]2.0.CO;2
   Tu VH, 2019, ENVIRON DEV SUSTAIN, V21, P2401, DOI 10.1007/s10668-018-0140-0
   Vo T. X., 1995, VIETNAM IRRI PARTNER, P179
   Xuan V.T., 1975, JAPANESE J SE ASIAN, V13, P88
   Tong YD, 2017, ECOL ECON, V132, P205, DOI 10.1016/j.ecolecon.2016.10.013
   Ziegler AD, 2011, CONSERV BIOL, V25, P846, DOI 10.1111/j.1523-1739.2011.01664.x
   Zimmerer KS, 2018, ECOL SOC, V23, DOI 10.5751/ES-09935-230130
NR 146
TC 4
Z9 4
U1 5
U2 21
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1471-0358
EI 1471-0366
J9 J AGRAR CHANGE
JI J. Agrar. Chang.
PD OCT
PY 2023
VL 23
IS 4
BP 661
EP 686
DI 10.1111/joac.12555
EA JUN 2023
PG 26
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA U0VI8
UT WOS:001002655400001
OA hybrid
DA 2025-01-10
ER

PT J
AU de Moor, J
AF de Moor, Joost
TI Prioritizing adaptation and mitigation in the climate movement: evidence
   from a cross-national protest survey of the Global Climate Strike, 2019
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Climate mitigation; Climate adaptation; Transformation; Climate
   movement; Climate justice
ID TRANSFORMATIONAL ADAPTATION; PARTICIPATION; VULNERABILITY; POLITICS;
   ACTIVISM
AB Climate adaptation is seen by many as increasingly important and as deeply political, leading some to argue for its democratization. Social movements could play an important role in this. Meanwhile, we have recently witnessed a major swell in climate activism, as well as a growing realization among climate activists that it may be too late to prevent major climate disruptions. Yet to what extent this may lead to a focus on adaptation in the climate movement remains understudied. To address this gap in the literature, the current paper draws on survey data from 2,344 participants in Fridays For Future climate demonstrations in September 2019 in 13 cities in Europe, Australia and the USA. The analyses show that while one-half of the respondents still attributes greater weight to mitigation, the other half attributes equal weight to adaptation and mitigation, indicating a greater emphasis on adaptation than previously assumed. It is found that those supporting (equal focus on) adaptation experience less hope about the effectiveness of climate policies, and portray a reluctance to support far-reaching climate action. The latter indicates that support for adaptation in the climate movement is associated with conservative attitudes, indicating constraints for the emergence of a climate movement for transformational adaptation.
C1 [de Moor, Joost] Sci Po, Ctr European Studies & Comparat Polit CEE, Paris, France.
C3 Institut d'Etudes Politiques Paris (Sciences Po)
RP de Moor, J (corresponding author), Sci Po, Ctr European Studies & Comparat Polit CEE, Paris, France.
EM joost.demoor@sciencespo.fr
OI de Moor, Joost/0000-0002-0413-9590
FU FORMAS [2019-01961, 2019-00261]; Stockholm University's Human Sciences
   Area; Formas [2019-01961, 2019-00261] Funding Source: Formas; Swedish
   Research Council [2019-01961] Funding Source: Swedish Research Council
FX This study was funded by Stockholm University's Human Sciences Area and
   FORMAS (2019-01961 and 2019-00261).
CR Adger WN, 2016, GLOBAL ENVIRON CHANG, V38, pA1, DOI 10.1016/j.gloenvcha.2016.03.009
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Anguelovski I, 2016, J PLAN EDUC RES, V36, P333, DOI 10.1177/0739456X16645166
   [Anonymous], 2009, RACE PLACE ENV POSTK
   Bassett TJ, 2013, GEOFORUM, V48, P42, DOI 10.1016/j.geoforum.2013.04.010
   Bendell J., 2018, IFLAS OCCASIONAL PAP
   Boda CS, 2019, CLIMATIC CHANGE, V157, P631, DOI 10.1007/s10584-019-02611-6
   Brulle RJ, 2014, CLIMATIC CHANGE, V122, P681, DOI 10.1007/s10584-013-1018-7
   Burnell P, 2012, DEMOCRATIZATION, V19, P813, DOI 10.1080/13510347.2012.709684
   Buzogány A, 2022, FUTURES, V137, DOI 10.1016/j.futures.2022.102904
   Carmin JoAnn., 2015, Climate Change and Society: Sociological Perspectives, P164
   Cassegård C, 2018, ENVIRON PLAN E-NAT, V1, P561, DOI 10.1177/2514848618793331
   Dawson Ashley., 2019, Extreme Cities. The Peril and Promise of Urban Life in the Age of Climate Change
   de Moor J, 2022, ENVIRON POLIT, V31, P927, DOI 10.1080/09644016.2021.1959123
   de Moor J, 2021, SOC MOVEMENT STUD, V20, P619, DOI 10.1080/14742837.2020.1836617
   de Moor J, 2018, ENVIRON POLIT, V27, P1079, DOI 10.1080/09644016.2017.1410315
   De Moor Joost., 2020, Protest for a Future II: Composition, Mobilization and Motives of the Participants in Fridays For Future Climate Protests on 20-27 September, 2019, in 19 Cities around the World
   Dietz M, 2014, ROUT INT HANDB, P1
   Dillman D.A., 2009, Internet, Mail, and Mix-Mode Surveys: The Taylored Design Method
   Emilsson K, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12030882
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Felli R, 2012, ENVIRON PLANN A, V44, P1, DOI 10.1068/a44680
   Few R, 2007, CLIM POLICY, V7, P46, DOI 10.1080/14693062.2007.9685637
   Friberg A, 2022, TIME SOC, V31, P48, DOI 10.1177/0961463X21998845
   Garrelts H, 2014, ROUT INT HANDB, P1
   Gulev S. K., 2021, Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [DOI 10.1017/9781009157896.004, 10.1017/9781009157896, 10.1017/9781009157896.004]
   Hadden J, 2015, CAMB STUD CONTENT, P1
   Hodson M, 2017, LOCAL ENVIRON, V22, P8, DOI 10.1080/13549839.2017.1306498
   Hodson M, 2009, INT J URBAN REGIONAL, V33, P193, DOI 10.1111/j.1468-2427.2009.00832.x
   Intergovernmental Panel on Climate Change, 2018, SPEC REP GLOB WARM 1
   Jackson T., 2016, Prosperity without growth, DOI [10.4324/9781315677453, DOI 10.4324/9781315677453]
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Kenis A, 2014, ENVIRON POLIT, V23, P531, DOI 10.1080/09644016.2013.870067
   Kleres J, 2017, SOC MOVEMENT STUD, V16, P507, DOI 10.1080/14742837.2017.1344546
   Marquardt J, 2020, FRONT COMMUN, V5, DOI 10.3389/fcomm.2020.00048
   Meerow S, 2017, ENVIRON PLANN A, V49, P2619, DOI 10.1177/0308518X17735225
   Mikulewicz M, 2018, CLIM DEV, V10, P18, DOI 10.1080/17565529.2017.1304887
   Moser SC, 2014, WIRES CLIM CHANGE, V5, P337, DOI 10.1002/wcc.276
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   Pachauri RK., 2015, Climate Change 2014: Synthesis Report. Contribution of Working Groups I, P1
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Remling E, 2018, ENVIRON POLIT, V27, P477, DOI 10.1080/09644016.2018.1429207
   Ribot J, 2011, GLOBAL ENVIRON CHANG, V21, P1160, DOI 10.1016/j.gloenvcha.2011.07.008
   Roser-Renouf C, 2014, CLIMATIC CHANGE, V125, P163, DOI 10.1007/s10584-014-1173-5
   Rossi FedericoM., 2015, Movements in Times of Democratic Transition, P9
   Saunders C, 2012, ENVIRON POLIT, V21, P829, DOI 10.1080/09644016.2012.692937
   Schlosberg D, 2017, ENVIRON POLIT, V26, P413, DOI 10.1080/09644016.2017.1287628
   Schlosberg D, 2013, ENVIRON POLIT, V22, P37, DOI 10.1080/09644016.2013.755387
   Scoones I, 2020, CURR OPIN ENV SUST, V42, P65, DOI 10.1016/j.cosust.2019.12.004
   Simonet G, 2016, REG ENVIRON CHANGE, V16, P789, DOI 10.1007/s10113-015-0792-3
   Stuart D, 2020, J AGR ENVIRON ETHIC, V33, P487, DOI 10.1007/s10806-020-09835-y
   Tarrow S, 2012, STRANGERS AT THE GATES: MOVEMENTS AND STATES IN CONTENTIOUS POLITICS, P1, DOI 10.1017/CBO9780511920967
   Temper L, 2018, SUSTAIN SCI, V13, P747, DOI 10.1007/s11625-018-0543-8
   UCLA: Statistical Consulting Group, 2020, LOGISTIC REGRESSION
   Wahlstrom M, 2019, PROTEST FUTURE COMPO, DOI DOI 10.17605/OSF.IO/XCNZH
   Wahlström M, 2013, GLOBAL ENVIRON POLIT, V13, P101, DOI 10.1162/GLEP_a_00200
   Walgrave S, 2011, MOBILIZATION, V16, P203
   Whyte K, 2017, ENGL LANG NOTES, V55, P153, DOI 10.1215/00138282-55.1-2.153
   Zografos C, 2020, CITIES, V99, DOI 10.1016/j.cities.2020.102613
NR 60
TC 3
Z9 3
U1 0
U2 9
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1381-2386
EI 1573-1596
J9 MITIG ADAPT STRAT GL
JI Mitig. Adapt. Strateg. Glob. Chang.
PD AUG
PY 2022
VL 27
IS 6
AR 41
DI 10.1007/s11027-022-10003-y
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 3E4DY
UT WOS:000829935600001
PM 35909943
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Bolaños, TG
   Scheffran, J
   Costa, MM
AF Guillen Bolanos, Tania
   Scheffran, Juergen
   Manez Costa, Maria
TI Climate Adaptation and Successful Adaptation Definitions: Latin American
   Perspectives Using the Delphi Method
SO SUSTAINABILITY
LA English
DT Article
DE adaptation; successful adaptation; monitoring and evaluation; Latin
   America; Delphi method; knowledge co-production
ID EXPERT ELICITATION; GLOBAL STOCKTAKE; PUBLIC TRANSPORT; DEJA-VU; TRACK
AB Across the world, policies and measures are being developed and implemented to reduce the risks of climate change and adapt to its current and projected adverse effects. The Paris Agreement established the global stocktake to evaluate the collective progress made on adaptation. Nevertheless, various challenges still exist when evaluating adaptation progress, among which is the lack of standard definitions to support evaluation efforts. Therefore, we investigated the views of experts regarding the definitions of adaptation given by the Intergovernmental Panel on Climate Change (IPCC) and the definition of successful adaptation by Doria et al., with a focus on Latin America. Using the Delphi method, we obtained relevant knowledge and perspectives. As a result, we identified a high level of consensus (85%) among the experts regarding the IPCC's definition of climate adaptation. However, there was no consensus on the definition of successful adaptation. For both definitions, we present the elements on which the experts agreed and disagreed, as well as the proposed elements that could improve the definitions to support adaptation evaluation efforts. Additionally, we introduce a list of criteria and indicators that could improve the evaluation of adaptation at different management levels and facilitate the aggregation of information on adaptation progress.
C1 [Guillen Bolanos, Tania; Manez Costa, Maria] Helmholtz Zentrum Hereon, Climate Serv Ctr Germany GERICS, Fischertwiete 1, D-20095 Hamburg, Germany.
   [Guillen Bolanos, Tania; Scheffran, Juergen] Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur, D-20144 Hamburg, Germany.
C3 Helmholtz Association; Helmholtz-Zentrum Hereon; University of Hamburg
RP Bolaños, TG (corresponding author), Helmholtz Zentrum Hereon, Climate Serv Ctr Germany GERICS, Fischertwiete 1, D-20095 Hamburg, Germany.; Bolaños, TG (corresponding author), Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur, D-20144 Hamburg, Germany.
EM tania.guillen@hereon.de; juergen.scheffran@uni-hamburg.de;
   maria.manez@hereon.de
RI Scheffran, Jurgen/M-6876-2019; Guillen Bolanos, Tania/KYC-2240-2024;
   Manez Costa, Maria/P-1225-2017
OI Scheffran, Jurgen/0000-0002-7171-3062; Guillen Bolanos,
   Tania/0000-0003-4601-7783; Manez Costa, Maria/0000-0001-5415-0811
FU DFG
FX The authors are grateful to the Latin American experts who participated
   in the first and second round of the Delphi method exercise: A. Aguilar,
   X. Apestegui, F. Aragon-Durand, A.C. Borda, R. Borquez, M. Caffera, N.
   Canales, E. Castellanos, A. Cid Salinas, J. Cordano, I. Delgado-Pitti,
   P. Devis, L. Di Pietro, M. Florian, G. Fuentes Braeuner, H. Garate, A.
   Garcia Gonzalez, P.M. Garcia Meneses, M. Jadrijevic, C. Jones, O.
   Jordan, I. Lorenzo, A. Martin, F. Menna, G.J. Nagy, L.A. Ortega
   Fernandez, N.C. Paez Ortiz, A. Rodriguez Osuna, D. Ryan, J.O. Samayoa
   Juarez, R. Scribano, and A. Sobenes. We also would like to thank E.
   Gomez, S. Muwafu, and G. Langendijk for their valuable comments, which
   helped to improve the manuscript. This research contributes to the
   climate cluster of excellence CLICCS funded by DFG.
CR AC, 2014, REP WORKSH MON EV AD
   AC-UNFCCC, 2021, APPR REV OV PROGR MA
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P75, DOI 10.1016/j.gloenvcha.2005.03.001
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   [Anonymous], 2017, AD GAP REP GLOB ASS
   Atteridge A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.500
   Barnett Jon., 2013, SUCCESSFUL ADAPTATIO, P37
   Bassett TJ, 2013, GEOFORUM, V48, P42, DOI 10.1016/j.geoforum.2013.04.010
   Berrang-Ford L, 2019, NAT CLIM CHANGE, V9, P440, DOI 10.1038/s41558-019-0490-0
   Berrang-Ford L, 2015, REG ENVIRON CHANGE, V15, P755, DOI 10.1007/s10113-014-0708-7
   Beutel RG, 2014, INSECT MORPHOLOGY AND PHYLOGENY: A TEXTBOOK FOR STUDENTS OF ENTOMOLOGY, P117
   Brown C, 2018, ENVIRON DEV SUSTAIN, V20, P23, DOI 10.1007/s10668-016-9891-7
   Castellanos E, 2022, Climate Change 2022: Impacts, Adaptation and Vulnerability.
   Castellanos EJ., 2022, Climate Change 2022: Impacts, Adaptation, and Vulnerability
   Christiansen L., 2018, Adaptation metrics: Perspectives on measuring, aggregating and comparing adaptation results
   Craft B, 2018, CLIM POLICY, V18, P1203, DOI 10.1080/14693062.2018.1485546
   DECONINCK H, 2018, GLOBAL WARMING 1 5 C, DOI DOI 10.5281/ZENODO.1289889
   Dilling L, 2019, NAT CLIM CHANGE, V9, P572, DOI 10.1038/s41558-019-0539-0
   Dilling L, 2015, WIRES CLIM CHANGE, V6, P413, DOI 10.1002/wcc.341
   Doria MD, 2009, ENVIRON SCI POLICY, V12, P810, DOI 10.1016/j.envsci.2009.04.001
   Engle NL, 2014, MITIG ADAPT STRAT GL, V19, P1295, DOI 10.1007/s11027-013-9475-x
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Fiala N., 2019, BECOMING BIGGER BETT
   Ford JD, 2016, MITIG ADAPT STRAT GL, V21, P839, DOI 10.1007/s11027-014-9627-7
   Ford JD, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104005
   Ford JD, 2013, ECOL SOC, V18, DOI 10.5751/ES-05732-180340
   GEF-STAP, 2017, STRENGTH MON EV CLIM
   Hagen I, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac5271
   Hasson F, 2000, J ADV NURS, V32, P1008, DOI 10.1046/j.1365-2648.2000.01567.x
   Hirschhorn F, 2019, INT J SOC RES METHOD, V22, P309, DOI 10.1080/13645579.2018.1543841
   Hirschhorn F, 2018, RES TRANSP ECON, V69, P144, DOI 10.1016/j.retrec.2018.02.003
   Hoegh-Guldberg O, 2019, SCIENCE, V365, P1263, DOI 10.1126/science.aaw6974
   IPCC, 2022, Climate Change 2022: Impacts, Adaptation and Vulnerability, DOI DOI 10.1017/9781009325844
   Ishtiaque A, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01802-1
   Janetos AC, 2020, CLIMATIC CHANGE, V161, P171, DOI 10.1007/s10584-019-02651-y
   Kabir MH, 2021, J CLIM CHANG, V7, P25, DOI 10.3233/JCC210003
   Kato T., 2016, COMMUNICATING PROGR
   Keeney S, 2001, INT J NURS STUD, V38, P195, DOI 10.1016/S0020-7489(00)00044-4
   Klein R.J., 2017, ADV CLIMATE ADAPTATI
   Kuckartz U., 2019, Analyzing Qualitative Data with MAXQDA: Text, Audio, and Video
   Landeta J, 2006, TECHNOL FORECAST SOC, V73, P467, DOI 10.1016/j.techfore.2005.09.002
   Leiter T., 2017, Evaluating climate change action for sustainable development, P327, DOI DOI 10.1007/978-3-319-43702-6_4
   Leiter T., 2015, Monitoring and evaluation of climate change adaptation, P117, DOI [DOI 10.1002/EV.20135, 10.1002/ev.20135]
   Leiter T., 2019, Adaptation Metrics. Current Landscape and Evolving Practices
   Leiter T, 2021, ENVIRON SCI POLICY, V125, P179, DOI 10.1016/j.envsci.2021.08.017
   Lorenz S, 2014, GEOFORUM, V51, P252, DOI 10.1016/j.geoforum.2013.10.003
   Magnan A K., 2019, Towards a Global Adaptation Progress Tracker: first thoughts (01)
   Magnan AK, 2016, SCIENCE, V352, P1280, DOI 10.1126/science.aaf5002
   Magnan AK, 2016, NATURE, V530, P160, DOI 10.1038/530160d
   Montijo-Galindo A, 2020, COAST MANAGE, V48, P623, DOI 10.1080/08920753.2020.1803572
   Morgan MG, 2014, P NATL ACAD SCI USA, V111, P7176, DOI 10.1073/pnas.1319946111
   Moser S. C., 2013, SUCCESSFUL ADAPTATIO, P289
   Mousavi A, 2020, BMC PUBLIC HEALTH, V20, DOI 10.1186/s12889-020-09503-w
   Nalau J, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100290
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   New M., 2022, Climate Change 2022: Impacts, Adaptation
   Olazabal M, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab5532
   Owen G, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102071
   Persson Å, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.618
   Reguant Alvarez M., 2016, REIRE Revista d'Innovacio i Recerca en Educacio, V9, P87, DOI [DOI 10.1344/REIRE2016.9.1916, 10.1344/reire2016.9.1916]
   Ryan D, 2019, CLIM POLICY, V19, P1297, DOI 10.1080/14693062.2019.1661819
   Schalatek L., 2020, GLOBAL CLIMATE FINAN
   Schipper ELF, 2020, WORLD DEV PERSPECT, V18, DOI 10.1016/j.wdp.2020.100205
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   Sietsma AJ, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abf7f3
   Singh C, 2022, CLIM DEV, V14, P650, DOI 10.1080/17565529.2021.1964937
   Soleymani A, 2021, J CLEAN PROD, V290, DOI 10.1016/j.jclepro.2020.125186
   Tetzlaff JM, 2012, TRIALS, V13, DOI 10.1186/1745-6215-13-176
   Tompkins EL, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.545
   UNEP (United Nations Environment Programme), 2021, AD GAP REP 2020
   UNFCCC, 2018, PROGR EXP BEST PRACT
   UNFCCC, 2018, BIENN ASS OV CLIM FI, V121
   UNFCCC, 2015, DEC 1 CP 21 AD PAR A
   UNFCCC Monitoring and Assessing Progress, 2015, EFF GAPS PROC FORM I
   VANDIJK JAGM, 1990, TECHNOL FORECAST SOC, V37, P293, DOI 10.1016/0040-1625(90)90029-U
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Vogel B, 2015, GLOBAL ENVIRON CHANG, V31, P110, DOI 10.1016/j.gloenvcha.2015.01.001
NR 78
TC 3
Z9 3
U1 4
U2 14
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD MAY
PY 2022
VL 14
IS 9
AR 5350
DI 10.3390/su14095350
PG 21
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 1F8ZG
UT WOS:000795449300001
OA gold
DA 2025-01-10
ER

PT J
AU Maher, SP
   Morelli, TL
   Hershey, M
   Flint, AL
   Flint, LE
   Moritz, C
   Beissinger, SR
AF Maher, Sean P.
   Morelli, Toni Lyn
   Hershey, Michelle
   Flint, Alan L.
   Flint, Lorraine E.
   Moritz, Craig
   Beissinger, Steven R.
TI Erosion of refugia in the Sierra Nevada meadows network with climate
   change
SO ECOSPHERE
LA English
DT Article
DE Circuitscape; climate; connectivity; conservation; dispersal; meadows;
   refugia
ID DRIVE DOWNHILL SHIFTS; LANDSCAPE CONNECTIVITY; HABITAT FRAGMENTATION;
   MICROREFUGIA; RESPONSES; CALIFORNIA; LIZARD; GRAIN
AB Climate refugia management has been proposed as a climate adaptation strategy in the face of global change. Key to this strategy is identification of these areas as well as an understanding of how they are connected on the landscape. Focusing on meadows of the Sierra Nevada in California, we examined multiple factors affecting connectivity using circuit theory, and determined how patches have been and are expected to be affected by climate change. Connectivity surfaces varied depending upon the underlying hypothesis, although meadow area and elevation were important features for higher connectivity. Climate refugia that would promote population persistence were identified from downscaled climate layers, based on locations with minimal climatic change from historical conditions. This approach was agnostic to specific species, yielding a broad perspective about changes and localized habitats. Connectivity was not a consistent predictor of refugial status in the 20th century, but expected future climate refugia tended to have higher connectivity than those that recently deviated from historical conditions. Climate change is projected to reduce the number of refugial meadows on a variety of climate axes, resulting in a sparser network of potential refugia across elevations. Our approach provides a straightforward method that can be used as a tool to prioritize places for climate adaptation.
C1 [Maher, Sean P.; Morelli, Toni Lyn; Hershey, Michelle; Moritz, Craig; Beissinger, Steven R.] Univ Calif Berkeley, Museum Vertebrate Zool, Berkeley, CA 94720 USA.
   [Maher, Sean P.; Morelli, Toni Lyn; Beissinger, Steven R.] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA.
   [Maher, Sean P.] Missouri State Univ, Dept Biol, Springfield, MO 65897 USA.
   [Morelli, Toni Lyn] US Geol Survey, Dept Interior Northeast Climate Sci Ctr, Amherst, MA 01003 USA.
   [Flint, Alan L.; Flint, Lorraine E.] US Geol Survey, Calif Water Sci Ctr, Sacramento, CA 95819 USA.
   [Moritz, Craig] Australia Natl Univ, Res Sch Biol, Canberra, ACT 2601, Australia.
C3 University of California System; University of California Berkeley;
   University of California System; University of California Berkeley;
   Missouri State University; United States Department of the Interior;
   United States Geological Survey; United States Department of the
   Interior; United States Geological Survey; Australian National
   University
RP Maher, SP (corresponding author), Univ Calif Berkeley, Museum Vertebrate Zool, Berkeley, CA 94720 USA.; Maher, SP (corresponding author), Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA.; Maher, SP (corresponding author), Missouri State Univ, Dept Biol, Springfield, MO 65897 USA.
EM smaher02@gmail.com
RI Maher, Sean/V-7553-2017
OI Maher, Sean/0000-0002-3430-0410
FU California Landscape Conservation Cooperative [80250-BJ127]; U.C.
   Berkeley Initiative in Global Change Biology; NSF Bioinformatics
   Postdoctoral Research Fellowship
FX This work was primarily supported by a grant from the California
   Landscape Conservation Cooperative (80250-BJ127) to TLM, CM, and SRB,
   along with funding from the U.C. Berkeley Initiative in Global Change
   Biology to SRB and an NSF Bioinformatics Postdoctoral Research
   Fellowship to TLM. We thank Eric Berlow, Bob Westfall, Connie Millar,
   Sarah Stock, and David Wright for analytical input. We thank J.Z.
   Drexler and at least two anonymous reviewers for comments that improved
   earlier drafts.
CR [Anonymous], 2012, ARCGIS DESKT REL 10
   [Anonymous], 2012, TIGER LIN SHAP
   [Anonymous], ECOSPHERE
   Ashcroft MB, 2012, GLOBAL CHANGE BIOL, V18, P1866, DOI 10.1111/j.1365-2486.2012.02661.x
   Ashcroft MB, 2010, J BIOGEOGR, V37, P1407, DOI 10.1111/j.1365-2699.2010.02300.x
   Baguette M, 2007, LANDSCAPE ECOL, V22, P1117, DOI 10.1007/s10980-007-9108-4
   Berlow EL, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0072200
   Cayan DR, 2008, CLIMATIC CHANGE, V87, pS21, DOI 10.1007/s10584-007-9377-6
   Chisholm C, 2011, ECOGRAPHY, V34, P415, DOI 10.1111/j.1600-0587.2010.06588.x
   Crimmins SM, 2011, SCIENCE, V331, P324, DOI 10.1126/science.1199040
   Curtis JA, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0106984
   D'Odorico P, 2013, GLOBAL ECOL BIOGEOGR, V22, P364, DOI 10.1111/geb.12000
   Dalsgaard B, 2013, ECOGRAPHY, V36, P1331, DOI 10.1111/j.1600-0587.2013.00201.x
   Daly C, 2008, INT J CLIMATOL, V28, P2031, DOI 10.1002/joc.1688
   Damschen EI, 2006, SCIENCE, V313, P1284, DOI 10.1126/science.1130098
   DIFFENDORFER JE, 1995, ECOLOGY, V76, P827, DOI 10.2307/1939348
   Dobrowski SZ, 2011, GLOBAL CHANGE BIOL, V17, P1022, DOI 10.1111/j.1365-2486.2010.02263.x
   DUNNING JB, 1992, OIKOS, V65, P169, DOI 10.2307/3544901
   Epps CW, 2006, MOL ECOL, V15, P4295, DOI 10.1111/j.1365-294X.2006.03103.x
   Fites-Kaufman JA, 2007, TERRESTRIAL VEGETATION OF CALIFORNIA, 3RD EDITION, P456
   Flint L.E., 2012, ECOL PROCESS, V1, P1, DOI [DOI 10.1186/2192-1709-1-2, 10.1186/2192-1709-1-2]
   Flint L.E., 2013, ECOL PROCESS, V2, P1, DOI [DOI 10.1186/2192-1709-2-25, 10.1186/2192-1709-2-25]
   Fryjoff-Hung A., 2012, Sierra Nevada Multi-Source Meadow Polygons Compilation
   Gillingham PK, 2012, DIVERS DISTRIB, V18, P990, DOI 10.1111/j.1472-4642.2012.00933.x
   Gillson L, 2013, TRENDS ECOL EVOL, V28, P135, DOI 10.1016/j.tree.2012.10.008
   Hampe A, 2011, ANNU REV ECOL EVOL S, V42, P313, DOI 10.1146/annurev-ecolsys-102710-145015
   Hannah L, 2014, TRENDS ECOL EVOL, V29, P390, DOI 10.1016/j.tree.2014.04.006
   Hansen J, 2010, REV GEOPHYS, V48, DOI 10.1029/2010RG000345
   Hastings A, 2014, POPUL ECOL, V56, P21, DOI 10.1007/s10144-013-0416-z
   Hatfield RG, 2007, BIOL CONSERV, V139, P150, DOI 10.1016/j.biocon.2007.06.019
   Hijmans R.J., 2013, raster: Geographic data analysis and modeling
   Hijmans R.J., 2013, dismo: Species distribution modeling. R package version 0.8-17
   Hijmans RJ, 2011, SCIENCE, V334, DOI 10.1126/science.1203791
   Isaak DJ, 2015, GLOBAL CHANGE BIOL, V21, P2540, DOI 10.1111/gcb.12879
   Kearney M, 2004, ECOLOGY, V85, P3119, DOI 10.1890/03-0820
   Keppel G, 2015, FRONT ECOL ENVIRON, V13, P106, DOI 10.1890/140055
   Keppel G, 2012, GLOBAL ECOL BIOGEOGR, V21, P393, DOI 10.1111/j.1466-8238.2011.00686.x
   Koen EL, 2012, LANDSCAPE ECOL, V27, P29, DOI 10.1007/s10980-011-9675-2
   Lehner B., 2006, HYDROSHEDS TECHNICAL
   Lundquist JD, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2008JD009879
   Lutz JA, 2010, J BIOGEOGR, V37, P936, DOI 10.1111/j.1365-2699.2009.02268.x
   Maher SP, 2012, NAT COMMUN, V3, DOI 10.1038/ncomms2301
   Manel S, 2013, TRENDS ECOL EVOL, V28, P614, DOI 10.1016/j.tree.2013.05.012
   McCullough IM, 2016, LANDSCAPE ECOL, V31, P1063, DOI 10.1007/s10980-015-0318-x
   McIlroy SK, 2012, WETL ECOL MANAG, V20, P287, DOI 10.1007/s11273-012-9253-7
   McRae B. H., 2013, Circuitscape 4 User Guide
   Millar CI, 2004, ARCT ANTARCT ALP RES, V36, P181, DOI 10.1657/1523-0430(2004)036[0181:ROSCIT]2.0.CO;2
   Millar CI, 2015, QUATERN INT, V387, P106, DOI 10.1016/j.quaint.2013.11.003
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   Morelli TL, 2012, P ROY SOC B-BIOL SCI, V279, P4279, DOI 10.1098/rspb.2012.1301
   Moritz C, 2008, SCIENCE, V322, P261, DOI 10.1126/science.1163428
   Moritz MA, 2008, CLIMATIC CHANGE, V87, pS265, DOI 10.1007/s10584-007-9361-1
   Mosblech NAS, 2011, J BIOGEOGR, V38, P419, DOI 10.1111/j.1365-2699.2010.02436.x
   Neuwald JL, 2013, MOL ECOL, V22, P3666, DOI 10.1111/mec.12306
   Nuñez TA, 2013, CONSERV BIOL, V27, P407, DOI 10.1111/cobi.12014
   Opdam P, 2004, BIOL CONSERV, V117, P285, DOI 10.1016/j.biocon.2003.12.008
   Orrock JL, 2005, CONSERV GENET, V6, P623, DOI 10.1007/s10592-005-9016-6
   Ozgul A, 2010, NATURE, V466, P482, DOI 10.1038/nature09210
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rapacciuolo G, 2014, GLOBAL CHANGE BIOL, V20, P2841, DOI 10.1111/gcb.12638
   Roche LM, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0035734
   Rowe KC, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2014.1857
   Rubidge EM, 2012, NAT CLIM CHANGE, V2, P285, DOI 10.1038/NCLIMATE1415
   Rudnick D. A., 2012, Issues in Ecology, V16, P1, DOI [10.1095/biolreprod46.1.155, DOI 10.1095/BIOLREPROD46.1.155]
   Schreiber SJ, 2009, AM NAT, V174, P490, DOI 10.1086/605405
   Shah V.B., 2008, Circuitscape: a tool for landscape ecology, V7, P62
   Sinervo B, 2010, SCIENCE, V328, P894, DOI 10.1126/science.1184695
   Stephenson NL, 2011, SCIENCE, V334, DOI 10.1126/science.1205740
   STEPHENSON NL, 1990, AM NAT, V135, P649, DOI 10.1086/285067
   Tingley MW, 2012, GLOBAL CHANGE BIOL, V18, P3279, DOI 10.1111/j.1365-2486.2012.02784.x
   Urban NA, 2009, J MAMMAL, V90, P1431, DOI 10.1644/08-MAMM-A-393R.1
   Wilson JRU, 2009, TRENDS ECOL EVOL, V24, P136, DOI 10.1016/j.tree.2008.10.007
   With KA, 1997, OIKOS, V78, P151, DOI 10.2307/3545811
   Zeller KA, 2012, LANDSCAPE ECOL, V27, P777, DOI 10.1007/s10980-012-9737-0
NR 75
TC 19
Z9 23
U1 2
U2 100
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2150-8925
J9 ECOSPHERE
JI Ecosphere
PD APR
PY 2017
VL 8
IS 4
AR e01673
DI 10.1002/ecs2.1673
PG 17
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EU4FN
UT WOS:000400985300002
OA gold, Green Published
DA 2025-01-10
ER

PT C
AU Keller, B
   Yuan, T
   Magyari, E
AF Keller, Bruno
   Yuan, Tian
   Magyari, Eugen
BE Fazio, P
   Ge, H
   Rao, J
   Desmarais, G
TI The climate adapted design of buildings: An easy way for the
   optimization
SO Research in Building Physics and Building Engineering
SE Proceedings and Monographs in Engineering, Water and Earth Sciences
LA English
DT Proceedings Paper
CT 3rd International Building Physics Conference
CY AUG 27-31, 2006
CL Concordia Univ, Montreal, CANADA
HO Concordia Univ
AB As has been shown elsewhere [Burmeister 1996], the thermal dynamics of a room can be described in an excellent approximation by only three parameters: The generalized loss coefficient K, the time constant tau and the gain-to-loss factor gamma. As a first step of a successive optimization, in all climates the loss factors must be kept as low as possible, in a second step a best combination of time constant (storage capacity etc.) and gain-to-loss-coefficient (windows size etc.) must be found. For this a new method has been developed: The freerun-temperature (FRT) of a room in a given climate is its most important characteristic and is completely defined by these three parameters. The more time this FRT of a room remains in the comfort range of internal temperatures: zero energy hours (ZEH), the less thermal energy and power is needed to operate it and thus the better a design is adapted to the climate. With these fundamentals the optimization of the climate adapted design is transformed into a simple maximization of the ZEH depending only on tau and gamma: ZEH(tau,gamma). Also the effect of a variable sun-shading as well as of internal sources can easily be included. Some examples are given. As an illustration, in the appendix a first attempt for the classification of climates based on the principal parameters is presented.
C1 ETHZ, Swiss Fed Inst Technol, Chair Bldg Phys, Zurich, Switzerland.
C3 Swiss Federal Institutes of Technology Domain; ETH Zurich
RP Keller, B (corresponding author), ETHZ, Swiss Fed Inst Technol, Chair Bldg Phys, Zurich, Switzerland.
RI TIAN, Yuan/IXW-8665-2023
CR BURMEISTER H, 1996, 11586 ETH
   KELLER B, 2002, S BUILD PHYS DRESD 2, P113
NR 2
TC 0
Z9 0
U1 0
U2 0
PU TAYLOR & FRANCIS LTD
PI LONDON
PA 11 NEW FETTER LANE, LONDON EC4P 4EE, ENGLAND
BN 0-415-41675-2
J9 PROC MONOGR ENG WATE
PY 2006
BP 863
EP 869
PG 7
WC Construction & Building Technology
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Construction & Building Technology
GA BFL57
UT WOS:000242847800108
DA 2025-01-10
ER

PT C
AU Mahmoudabadi, V
   Ravichandran, N
AF Mahmoudabadi, Vahidreza
   Ravichandran, Nadarajah
BE Ching, J
   Najjar, S
   Wang, L
TI Uncertainty-Based Climate-Adaptive Design Optimization of Embedded
   Footing
SO GEO-RISK 2023: HAZARDS AND CLIMATE CHANGE
SE Geotechnical Special Publication
LA English
DT Proceedings Paper
CT Conference on Geo-Risk - Advances in Theory and Innovation in Practice
CY JUL 23-26, 2023
CL Arlington, VA
SP Amer Soc Civil Engineers, Geo Inst
DE Unsaturated soil; Climate events; Uncertainty-based design optimization;
   NSGA-II
AB This study aims to develop a quantitative framework to optimize embedded footing performance subjected to extreme historical climate events with respect to the uncertainties associated with site-specific soil and climatic parameters. The proposed method was applied to a semi-arid climate site in Riverside, California, as a case study. By performing the optimization procedure, it is found that the proposed climate-adaptive design method provides a better optimal design for the embedded footing in comparison with the conventional method. The optimization result indicates that the footing width significantly drops from 4.72 m to 3.79 m for the design at the Riverside site, compared to the conventional method. Regarding the total construction cost, the optimal design from the proposed method for the Riverside site shows 19% lower cost, compared to the one from the conventional method.
C1 [Mahmoudabadi, Vahidreza] Dataforensics LLC, Atlanta, GA 30345 USA.
   [Ravichandran, Nadarajah] Clemson Univ, Glenn Dept Civil Engn, Clemson, SC 29631 USA.
C3 Clemson University
RP Mahmoudabadi, V (corresponding author), Dataforensics LLC, Atlanta, GA 30345 USA.
RI Mahmoudabadi, Vahidreza/K-8781-2019
CR Al-Bittar T., 2012, THESIS U NANTES FRAN
   BOWLES JE, 1987, J GEOTECH ENG-ASCE, V113, P846, DOI 10.1061/(ASCE)0733-9410(1987)113:8(846)
   Briaud J.L., 2013, Geotechnical engineering: Unsaturated and saturated soils
   Converse Consultants, 2016, REV GEOT INV REP
   Deb K, 2002, IEEE T EVOLUT COMPUT, V6, P182, DOI 10.1109/4235.996017
   Ellithy G, 2017, TN17XX ERDCGSL USA E
   Fredlund DG, 2006, J GEOTECH GEOENVIRON, V132, P286, DOI 10.1061/(ASCE)1090-0241(2006)132:3(286)
   Juang C.H., 2013, SOUND GEOTECHNICAL R, P514
   Mahmoudabadi V., 2018, JOUR GEOENGINEERING, V13, P93
   Mahmoudabadi V, 2023, GEORISK, V17, P287, DOI 10.1080/17499518.2022.2088801
   Mahmoudabadi V, 2021, INT J NUMER ANAL MET, V45, P1437, DOI 10.1002/nag.3208
   Mahmoudabadi V, 2020, ENG GEOL, V264, DOI 10.1016/j.enggeo.2019.105317
   Mahmoudabadi V, 2019, INT J GEOMECH, V19, DOI 10.1061/(ASCE)GM.1943-5622.0001432
   Mahmoudabadi V, 2018, GEOTECH SP, P268
   Means, 1990, MEANS ESTIMATING HDB
   Oh WT, 2009, CAN GEOTECH J, V46, P903, DOI 10.1139/T09-030
   Richards LA, 1931, PHYSICS-J GEN APPL P, V1, P318, DOI 10.1063/1.1745010
   van Dam JC, 2000, J HYDROL, V233, P72, DOI 10.1016/S0022-1694(00)00227-4
   Vanapalli SK, 2007, SPRINGER PROC PHYS, V112, P483
   VANGENUCHTEN MT, 1980, SOIL SCI SOC AM J, V44, P892, DOI 10.2136/sssaj1980.03615995004400050002x
   Vardon PJ, 2015, ENVIRON GEOTECH, V2, P166, DOI 10.1680/envgeo.13.00055
NR 21
TC 0
Z9 0
U1 0
U2 0
PU AMER SOC CIVIL ENGINEERS
PI NEW YORK
PA UNITED ENGINEERING CENTER, 345 E 47TH ST, NEW YORK, NY 10017-2398 USA
SN 0895-0563
BN 978-0-7844-8496-8
J9 GEOTECH SP
PY 2023
VL 344
BP 20
EP 31
PG 12
WC Engineering, Geological
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Engineering
GA BV4XM
UT WOS:001043368200003
DA 2025-01-10
ER

PT J
AU Gottschick, M
AF Gottschick, Manuel
TI How stakeholders handle uncertainty in a local climate adaptation
   governance network
SO CLIMATIC CHANGE
LA English
DT Article
ID IGNORANCE; KNOWLEDGE; SCIENCE; LIMITS
AB Uncertainty is a debated issue in climate research, in research on the governance of climate adaptation, and in research on the social limits to adaptation. As a contribution to this debate, a constructivist discourse research approach is chosen to analyse and interpret how stakeholders handle uncertainty related to climate change knowledge. Four diverse conceptualisations of how uncertainty is handled serve as the discourse analysis framework: rational discourse, no-regret discourse, blissful discourse, and formative discourse. This framework is applied to analyse and interpret interviews of diverse stakeholder groups from a local governance adaptation network. In this network, conflicts between irrigation farmers, water authorities and nature conservation are negotiated. For most interviewees, uncertainty about climate change knowledge is not judged as problematic. This paper elaborates on why this is so and provides tentative assessments for each discourse type.
C1 Univ Hamburg, FSP BIOGUM, Hamburg, Germany.
C3 University of Hamburg
RP Gottschick, M (corresponding author), Univ Hamburg, FSP BIOGUM, Hamburg, Germany.
EM manuel.gottschick@uni-hamburg.de
RI Gottschick, Manuel/G-2069-2012
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   [Anonymous], 2011, Living in Denial: Climate change, emotions, and everyday life
   [Anonymous], 2010, GUIDANCE NOTE LEAD A
   [Anonymous], REPORT CLIMATE CHANG
   [Anonymous], 1981, Theorie des kommunikativen Handelns
   [Anonymous], 1995, Critical discourse analysis
   Aven T, 2010, RISK GOV SOC, V16, P1, DOI 10.1007/978-3-642-13926-0
   Berger Peter L., 2007, Die gesellschaftliche Konstruktion der Wirklichkeit. Eine Theorie der Wissenssoziologie, V25
   Bundschuh A, 2012, UMGANG UNSICHERHEIT
   Dessai S., 2007, UNCERTAINTY CLIMATE
   Douglas M., 1986, How Institutions Think
   Dow K, 2013, CURR OPIN ENV SUST, V5, P384, DOI 10.1016/j.cosust.2013.07.005
   Enserink B, 2013, FUTURES, V53, P1, DOI 10.1016/j.futures.2013.09.006
   Feindt P., 2011, RES SUSTAINABILITY, P159
   Feindt PH, 2008, NACHHALTIGE AGRAPOLI
   Foucault Michel, 1991, DISCIPLINE PUNISH BI
   Gottschick M, 2010, HOCHWASSERRISIKOMANA, V19
   Gottschick M, 2018, J ENVIRON POL PLAN, V20, P713, DOI [10.1080/1523908x.2013.842890, 10.1080/1523908X.2013.842890]
   Gross M, 2007, CURR SOCIOL, V55, P742, DOI 10.1177/0011392107079928
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   IRGC, 2009, AN ILL MOST COMM DEF
   Jacob D, 2012, REGIONALE KLIMAPROJE, V6
   Keller R, 2013, DOING DICOURSE RES I
   Keller R, 2011, HUM STUD, V34, P43, DOI 10.1007/s10746-011-9175-z
   Kitcher P, 2010, SCIENCE, V328, P1230, DOI 10.1126/science.1189312
   Oppermann E, 2011, CLIM DEV, V3, P71, DOI 10.3763/cdev.2010.0061
   Rayner S, 2012, ECON SOC, V41, P107, DOI 10.1080/03085147.2011.637335
   Rechid D, 2011, DATEN INFORM KLIMAWA
   Schaper J, 2011, GENESIS ISAIAH AND P, V20, P135
   SMITHSON M, 1993, KNOWLEDGE, V15, P133, DOI 10.1177/107554709301500202
   Swart R, 2009, CLIMATIC CHANGE, V92, P1, DOI 10.1007/s10584-008-9444-7
   Walker W.E, 2010, Integrated Assessment, V4, P5, DOI [10.1076/iaij.4.1.5.16466, DOI 10.1076/IAIJ.4.1.5.16466]
   Weingart P, 2000, PUBLIC UNDERST SCI, V9, P261, DOI 10.1088/0963-6625/9/3/304
   Yohe G, 2011, CLIMATIC CHANGE, V108, P629, DOI 10.1007/s10584-011-0176-8
NR 35
TC 10
Z9 11
U1 1
U2 28
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0165-0009
EI 1573-1480
J9 CLIMATIC CHANGE
JI Clim. Change
PD OCT
PY 2015
VL 132
IS 3
BP 445
EP 457
DI 10.1007/s10584-014-1203-3
PG 13
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA CR9YV
UT WOS:000361714300007
DA 2025-01-10
ER

PT C
AU Francis, WL
AF Francis, Wendy L.
BE Watson, A
   MurrietaSaldivar, J
   McBride, B
TI The Climate Adaptation Programs and Activities of the Yellowstone to
   Yukon Conservation Initiative
SO SCIENCE AND STEWARDSHIP TO PROTECT AND SUSTAIN WILDERNESS VALUES
SE USDA Forest Service Rocky Mountain Research Station Proceedings
LA English
DT Proceedings Paper
CT 9th World Wilderness Congress Symposium - Science and Stewardship to
   Protect and Sustain Wilderness Values
CY NOV 06-13, 2009
CL Merida, MEXICO
SP USDA, Forest Serv
AB The Yellowstone to Yukon Conservation Initiative (Y2Y) is an innovative transboundary effort to protect biodiversity and facilitate climate adaptation by linking large protected core areas through compatible land uses on matrix lands. The Y2Y organization acts as the keeper of the Y2Y vision and implements two interconnected programs Science and Action, and Vision and Awareness to promote the landscape, political, public, and financial conditions necessary for wildlife connectivity. The Y2Y vision has inspired many others who are also undertaking programs, projects, and actions contributing to its realization. This paper provides examples of projects being undertaken by the Y2Y organization as well as those being implemented by others and includes a brief summary of successes to date.
C1 [Francis, Wendy L.] Yellowstone Yukon Conservat Initiat, Conservat Sci & Act, POB 1477, Banff, AB T1L 1B4, Canada.
RP Francis, WL (corresponding author), Yellowstone Yukon Conservat Initiat, Conservat Sci & Act, POB 1477, Banff, AB T1L 1B4, Canada.
EM wendy@y2y.net
CR DEAN C, 2006, NY TIMES
   Environmental News Service, 2008, ANC PRONGH PATH BEC
   Franke O, 1981, CONSERVATION EVOLUTI
   Hummel M., 2008, Caribou and the north : a shared future
   Kramer B., 2009, SPOKESMAN REV   0611
   NEWMARK WD, 1995, CONSERV BIOL, V9, P512, DOI 10.1046/j.1523-1739.1995.09030512.x
   Ridler K., 2007, SEATTLE TIMES
   Western Governors' Association, 2009, WILDL COUNC
   Wilkinson T., 2005, AUDUBON MAGAZINE
   Y2Y Conservation Initiative, 2009, CAB PURC MOUNT UNPUB
   Yellowstone to Yukon Conservation Initiative, 2002, STRAT PLAN 200 UNPUB
NR 11
TC 0
Z9 0
U1 2
U2 16
PU US DEPT AGR, FOREST SERV ROCKY MT FOREST & RANGE EXPTL STN
PI FT COLLINS
PA FT COLLINS, CO 80526 USA
SN 1945-0672
J9 US FOR SERV RMRS-P
JI USDA For. Ser. Rocky Mt. Res. Stat. Proc.
PY 2011
VL 64
BP 57
EP 64
PG 8
WC Biodiversity Conservation; Environmental Studies
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA BH2IQ
UT WOS:000398977000009
DA 2025-01-10
ER

PT J
AU de Munnik, N
   Lenzholzer, S
AF de Munnik, Nina
   Lenzholzer, Sanda
TI Revealing urban climate through animated visualizations
SO JOURNAL OF LANDSCAPE ARCHITECTURE
LA English
DT Article
DE Visual communication; awareness; animations; urban climate; climate
   adaptation
ID CHANGE ADAPTATION; FLOOD RISK; PRIVATE RESPONSIBILITIES; CHANGE
   AWARENESS; HEAT-ISLAND; PERCEPTION; VULNERABILITY; MITIGATION; IMPACTS;
   MANAGEMENT
AB Climate change is intensifying urban climate problems and the design of public and private spaces should take this into account. However, the public often does not recognize these problems due to perceptual barriers. The hypothesis of this paper is that such perceptual barriers can be overcome through 'climate revelatory visualizations' that communicate the problems and solutions in an understandable way and can nudge parties into taking action. We created and tested several photorealistic animated visualization styles. The results indicate that urban climate problems and adaptation measures should be presented in photorealistic animations with graphic overlays to overcome perceptual barriers. The climate revelatory visualizations should frame climate adaptation positively, and feature the everyday environments of the target audience. Visualizations that reveal current situations, specifically the risks of particular climate problems, prove to have a warning function, whereas visualizations that reveal adaptation measures can motivate citizens and urban designers to take adaptation action.
C1 [de Munnik, Nina] Buro St & Co, Binckhorstlaan 36, NL-2516 BE The Hague, Netherlands.
   [Lenzholzer, Sanda] Wageningen Univ, Dept Environm Sci, Landscape Architecture & Spatial Planning Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
C3 Wageningen University & Research
RP de Munnik, N (corresponding author), Buro St & Co, Binckhorstlaan 36, NL-2516 BE The Hague, Netherlands.; Lenzholzer, S (corresponding author), Wageningen Univ, Dept Environm Sci, Landscape Architecture & Spatial Planning Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
EM ninademunnik@gmail.com; sanda.lenzholzer@wur.nl
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Ardaya AB, 2017, INT J DISAST RISK RE, V25, P227, DOI 10.1016/j.ijdrr.2017.09.006
   Backhaus A, 2012, URBAN WATER J, V9, P29, DOI 10.1080/1573062X.2011.633613
   Baldwin C, 2010, LOCAL ENVIRON, V15, P637, DOI 10.1080/13549839.2010.498810
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Bishop Ian D., 2005, VISUALIZATION LANDSC, P69
   Capstick S, 2015, WIRES CLIM CHANGE, V6, P35, DOI 10.1002/wcc.321
   Corburn J, 2009, URBAN STUD, V46, P413, DOI 10.1177/0042098008099361
   Cortesao J, 2020, J URBAN DES, V25, P293, DOI 10.1080/13574809.2019.1650638
   Daanen H.A., 2013, International Conference of Environmental Ergononomics, P16
   Demski C, 2017, CLIMATIC CHANGE, V140, P149, DOI 10.1007/s10584-016-1837-4
   Derkzen ML, 2017, LANDSCAPE URBAN PLAN, V157, P106, DOI 10.1016/j.landurbplan.2016.05.027
   Dockerty T., 2005, Computers, Environment and Urban Systems, V29, P297, DOI 10.1016/j.compenvurbsys.2004.05.004
   Falconer RH, 2009, J FLOOD RISK MANAG, V2, P198, DOI 10.1111/j.1753-318X.2009.01034.x
   Fatti CE, 2013, APPL GEOGR, V36, P13, DOI 10.1016/j.apgeog.2012.06.011
   Fratini CF, 2012, URBAN WATER J, V9, P317, DOI 10.1080/1573062X.2012.668913
   Glaas E, 2015, ENERGY RES SOC SCI, V10, P57, DOI 10.1016/j.erss.2015.06.012
   Haines A, 2006, PUBLIC HEALTH, V120, P585, DOI 10.1016/j.puhe.2006.01.002
   Jude S, 2006, J COASTAL RES, V22, P1527, DOI 10.2112/04-0294.1
   Kleerekoper L., 2016, THESIS DELFT U TECHN
   Kluck Jeroen, 2017, KLIMAATBESTENDIGE WI
   Laukkonen J, 2009, HABITAT INT, V33, P287, DOI 10.1016/j.habitatint.2008.10.003
   Lee T, 2017, MITIG ADAPT STRAT GL, V22, P761, DOI 10.1007/s11027-015-9697-1
   Lee TM, 2015, NAT CLIM CHANGE, V5, P1014, DOI 10.1038/NCLIMATE2728
   Leiserowitz A, 2006, CLIMATIC CHANGE, V77, P45, DOI 10.1007/s10584-006-9059-9
   Lemonsu A, 2015, URBAN CLIM, V14, P586, DOI 10.1016/j.uclim.2015.10.007
   Lenzholzer S, 2013, LANDSCAPE URBAN PLAN, V113, P120, DOI 10.1016/j.landurbplan.2013.02.003
   Lewis JL, 2012, J URBAN TECHNOL, V19, P85, DOI 10.1080/10630732.2012.673057
   Lorenz S, 2015, PHILOS T R SOC A, V373, DOI 10.1098/rsta.2014.0457
   Madsen HM, 2019, ENVIRON SCI POLICY, V98, P30, DOI 10.1016/j.envsci.2019.04.004
   Manzo K, 2010, AREA, V42, P96, DOI 10.1111/j.1475-4762.2009.00887.x
   McEwen L, 2012, HYDROL RES, V43, P675, DOI 10.2166/nh.2012.022
   McMahon R, 2016, CLIMATIC CHANGE, V138, P369, DOI 10.1007/s10584-016-1758-2
   Mees H, 2018, CLIM POLICY, V18, P1313, DOI 10.1080/14693062.2018.1434477
   Mees H, 2017, J ENVIRON POL PLAN, V19, P374, DOI 10.1080/1523908X.2016.1223540
   Mees HLP, 2013, J ENVIRON PLANN MAN, V56, P802, DOI 10.1080/09640568.2012.706600
   Mees HLP, 2012, J ENVIRON POL PLAN, V14, P305, DOI 10.1080/1523908X.2012.707407
   Moser SC, 2010, WIRES CLIM CHANGE, V1, P31, DOI 10.1002/wcc.11
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Nicholson-Cole S. A., 2005, Computers, Environment and Urban Systems, V29, P255, DOI 10.1016/j.compenvurbsys.2004.05.002
   Nijhuis Steffen., 2012, Journal of Design Research, V10, P239, DOI [DOI 10.1504/JDR.2012.051172, 10.1504/JDR.2012.051172]
   O'Neill SJ, 2016, GEO-GEOGR ENVIRON, V3, DOI 10.1002/geo2.v3.2
   O'Neill SJ, 2014, WIRES CLIM CHANGE, V5, P73, DOI 10.1002/wcc.249
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Martínez CIP, 2018, J CLEAN PROD, V178, P314, DOI 10.1016/j.jclepro.2017.12.246
   Rambonilaza T, 2016, J ENVIRON MANAGE, V180, P272, DOI 10.1016/j.jenvman.2016.05.037
   Runhaar H, 2012, REG ENVIRON CHANGE, V12, P777, DOI 10.1007/s10113-012-0292-7
   Schneider B, 2019, GEO-GEOGR ENVIRON, V6, DOI 10.1002/geo2.70
   Schroth O, 2015, LANDSCAPE URBAN PLAN, V142, P147, DOI 10.1016/j.landurbplan.2015.03.011
   Schroth O, 2014, ENVIRON COMMUN, V8, P413, DOI 10.1080/17524032.2014.906478
   Shaw A, 2009, GLOBAL ENVIRON CHANG, V19, P447, DOI 10.1016/j.gloenvcha.2009.04.002
   Sheppard S. R. J., 2012, Visualizing climate change: a guide to visual communication of climate change and developing local solutions
   Sheppard SRJ, 2005, ENVIRON SCI POLICY, V8, P637, DOI 10.1016/j.envsci.2005.08.002
   Sheppard SRJ, 2015, LANDSCAPE URBAN PLAN, V142, P95, DOI 10.1016/j.landurbplan.2015.07.006
   Smith NW, 2009, J RISK RES, V12, P647, DOI 10.1080/13669870802586512
   Tank Albert Klein, 2014, 6632014 KNMI
   Tiller TR, 2013, ASIA PAC J TOUR RES, V18, P21, DOI 10.1080/10941665.2012.697648
   Vachon Genevieve, 2013, ENQUIRY ARCC J ARCHI, V20, P14
   van den Brink Adri, 2017, RES LANDSCAPE ARCHIT, P45
   van der Linden S, 2015, PERSPECT PSYCHOL SCI, V10, P758, DOI 10.1177/1745691615598516
   Wardekker A, 2019, CLIMATIC CHANGE, V156, P273, DOI 10.1007/s10584-019-02522-6
   Webb B, 2017, INT PLAN STUD, V22, P68, DOI 10.1080/13563475.2016.1169916
NR 62
TC 5
Z9 5
U1 1
U2 12
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1862-6033
EI 2164-604X
J9 J LANDSC ARCHIT
JI J. Landsc. Archit.
PY 2020
VL 15
IS 2
BP 74
EP 85
DI 10.1080/18626033.2020.1852712
PG 12
WC Architecture
WE Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Architecture
GA QF9GY
UT WOS:000617197800007
DA 2025-01-10
ER

PT J
AU Crotteau, JS
   Sutherland, EK
   Jain, TB
   Wright, DK
   Jenkins, MM
   Keyes, CR
   Nagel, LM
AF Crotteau, Justin S.
   Sutherland, Elaine Kennedy
   Jain, Theresa B.
   Wright, David K.
   Jenkins, Melissa M.
   Keyes, Christopher R.
   Nagel, Linda M.
TI Initiating Climate Adaptation in a Western Larch Forest
SO FOREST SCIENCE
LA English
DT Article
DE Larix occidentalis; adaptive management; experimental silviculture;
   disturbance mitigation; Adaptive Silviculture for Climate Change
ID LARIX-OCCIDENTALIS; FIRE; TREE
AB Western larch forests are iconic in the interior northwest, and here we document the preemptive steps that scientists and managers are taking to steward these forests into the future. (hanging climate is forecast to have acute and chronic impacts on growth and disturbance in western larch forests. A group of scientists and managers in the northern Rocky Mountains have teamed up with the Adaptive Silviculture for Climate Change Network in an experiment to proactively manage forests for climate adaptation. The collaborative group developed a gradient of adaptation treatments (i.e., resistance, resilience, and transition) focused on climate change at Coram Experimental Forest and the Flathead National Forest. Treatments are scheduled, and monitoring will follow to fuel future research and to help guide regional managers who seek to learn from our treatments. We conclude with predictions of future dynamics in these stands and emphasize the value of landscape heterogeneity and the necessity of long-term monitoring for silvicultural experiments.
C1 [Crotteau, Justin S.] US Forest Serv, USDA, Pacific Northwest Res Stn, Juneau, AK 99801 USA.
   [Sutherland, Elaine Kennedy] US Forest Serv, Sutherland USDA, Rocky Mt Res Stn, Missoula, MT USA.
   [Jain, Theresa B.] US Forest Serv, USDA, Rocky Mt Res Stn, Moscow, ID USA.
   [Wright, David K.] US Forest Serv, USDA, Rocky Mt Res Stn, Missoula, MT USA.
   [Jenkins, Melissa M.] US Forest Serv, USDA, Flathead Natl Forest, Kalispell, MT USA.
   [Keyes, Christopher R.] Univ Montana, WA Franke Coll Forestry & Conservat, Missoula, MT 59812 USA.
   [Nagel, Linda M.] Colorado State Univ, Warner Coll Nat Resources, Ft Collins, CO 80523 USA.
C3 United States Department of Agriculture (USDA); United States Forest
   Service; United States Department of Agriculture (USDA); United States
   Forest Service; United States Department of Agriculture (USDA); United
   States Forest Service; United States Department of Agriculture (USDA);
   United States Forest Service; United States Department of Agriculture
   (USDA); United States Forest Service; University of Montana System;
   University of Montana; Colorado State University
RP Crotteau, JS (corresponding author), US Forest Serv, USDA, Pacific Northwest Res Stn, Juneau, AK 99801 USA.
EM justin.crotteau@usda.gov; elaine.sutherland@usda.gov;
   terrie.jain@usda.gov; david.wright2@usda.gov;
   melissa.m.jenkins@usda.gov; christopher.keyes@umontana.edu;
   linda.nagel@colostate.edu
RI Crotteau, Justin/AAT-6940-2020
OI Crotteau, Justin/0000-0001-8889-822X; Wright, David/0000-0002-0614-326X
FU USDA Forest Service Region One's Resource Inventory and Monitoring Board
FX We gratefully acknowledge those who made this study installation
   possible, including funding by USDA Forest Service Region One's Resource
   Inventory and Monitoring Board, Barry Bollenbacher, retired regional
   silviculturist who inspired the project, and Renate Bush (Region One
   Inventory and Analysis) who assisted in developing the monitoring
   design. The Northern Institute of Applied Climate Science is a key
   partner in the Adaptive Silviculture for Climate Change (ASCC) Network
   and helped facilitate the Kalispell, MT workshop. We thank Molly Roske
   (former ASCC Network Coordinator) for shepherding the project during the
   workshop and treatment developed phase. Employees of the Flathead
   National Forest have been critical to this effort, including Amanda
   Rollwage who found and laid out the study areas; Karl Anderson who led
   the stand exam crews that installed the plots and performed much of the
   pretreatment monitoring; Sarah Canepa, Eric Trimble, and Michele Draggoo
   who were instrumental in leading the NEPA process; and Hungry Horse
   District Ranger Rob Davies who has been in every way supportive of these
   efforts.
CR [Anonymous], CLIMATE CHANGE VUL 1
   [Anonymous], 1977, INTGTR34 USDA FOR SE
   [Anonymous], WO91 USDA FOR SERV W
   [Anonymous], 2002, ESSENTIAL FVS USERS
   [Anonymous], RMRSGTR341 USDA FOR
   Arno SF, 2000, US FOR SERV RMRS-P, P97
   ARNO SF, 1995, USDA INTERM, V319, P130
   BARRETT SW, 1991, CAN J FOREST RES, V21, P1711, DOI 10.1139/x91-237
   Bollenbacher BL, 2014, J FOREST, V112, P474, DOI 10.5849/jof.13-086
   Brown A.A., 1973, Forest fire: control and use
   CARLSON CE, 1995, USDA INTERM, V319, P123
   Cooper S.V., 1991, Forest habitat types of northern Idaho: a second approximation
   Dale VH, 2001, BIOSCIENCE, V51, P723, DOI 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
   Eyre F.H., 1980, Forest cover types of the United States and Canada
   FIEDLER CE, 1995, USDA INTERM, V319, P192
   Haffey C, 2018, FIRE ECOL, V14, DOI 10.4996/fireecology.140114316
   Halofsky JE, 2016, ATMOSPHERE-BASEL, V7, DOI 10.3390/atmos7030046
   Hood S, 2017, FIRE ECOL, V13, P66, DOI 10.4996/fireecology.130290243
   Jang W, 2016, BIOMASS BIOENERG, V92, P88, DOI 10.1016/j.biombioe.2016.06.009
   Janowiak MK, 2014, J FOREST, V112, P424, DOI 10.5849/jof.13-094
   JOYCE L. A., 2018, CLIMATE CHANGE VUL 1, P28
   Keane R.E., 2018, Climate Change Vulnerability and Adaptation in the Northern Rocky Mountains Part 1. Fort Collins, P128
   Kubiske ME, 2019, J FOREST, V117, P38, DOI 10.1093/jofore/fvy058
   Long JN, 2005, WEST J APPL FOR, V20, P205, DOI 10.1093/wjaf/20.4.205
   MENLOVE J., 2012, USDA FOREST SERVICE, V15
   Nagel LM, 2017, J FOREST, V115, P167, DOI 10.5849/jof.16-039
   Oliver W.W., 1990, SILVICS N AM, P413
   OSWALD BP, 1993, B TORREY BOT CLUB, V120, P148, DOI 10.2307/2996944
   Rehfeldt GE, 2010, MITIG ADAPT STRAT GL, V15, P283, DOI 10.1007/s11027-010-9217-2
   Reineke LH, 1933, J AGRIC RES, V46, P0627
   Sala A, 2001, OECOLOGIA, V126, P42, DOI 10.1007/s004420000503
   Schaedel MS, 2017, CAN J FOREST RES, V47, P861, DOI 10.1139/cjfr-2017-0074
   Schmidt W.C., 1990, AGR HDB, V654, P160
   SCHMIDT W. C., 1976, USDA FOREST SERVICE, V1520
   Smith J.K., 1997, FIRE ECOLOGY FOREST
   Smith KT, 2016, CAN J FOREST RES, V46, P535, DOI 10.1139/cjfr-2015-0377
   Swanston CW, 2016, NRSGTR872 USDA FOR S, DOI 10.2737/NRS-GTR-87-2
   USDA FOREST SERVICE, 2018, FS118 USDA FOR SERV
NR 38
TC 4
Z9 4
U1 0
U2 11
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0015-749X
EI 1938-3738
J9 FOREST SCI
JI For. Sci.
PD AUG
PY 2019
VL 65
IS 4
BP 528
EP 536
DI 10.1093/forsci/fxz024
PG 9
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA IT3SA
UT WOS:000482774200017
DA 2025-01-10
ER

PT J
AU Webler, T
   Tuler, S
   Dow, K
   Whitehead, J
   Kettle, N
AF Webler, T.
   Tuler, S.
   Dow, K.
   Whitehead, J.
   Kettle, N.
TI Design and evaluation of a local analytic-deliberative process for
   climate adaptation planning
SO LOCAL ENVIRONMENT
LA English
DT Article
DE climate change; adaptation; vulnerability; deliberative learning;
   decision support; analytic-deliberation
ID VULNERABILITY; RISK; PARTICIPATION; MANAGEMENT; PERSPECTIVES;
   RESILIENCE; ENGAGEMENT; STRATEGIES; FRAMEWORK; IMPACTS
AB In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.
C1 [Webler, T.; Tuler, S.] Social & Environm Res Inst, Amherst, MA USA.
   [Dow, K.; Kettle, N.] Univ S Carolina, Dept Geog, Columbia, SC 29208 USA.
   [Whitehead, J.] South Carolina Sea Grant Consortium, Charleston, SC USA.
C3 University of South Carolina System; University of South Carolina
   Columbia
RP Webler, T (corresponding author), Social & Environm Res Inst, Amherst, MA USA.
EM twebler@seri-us.org
RI Webler, Thomas/ABE-3201-2021; Tuler, Seth/KOC-8361-2024
OI Tuler, Seth/0009-0004-3930-1107
CR Abelson J, 2003, SOC SCI MED, V57, P239, DOI 10.1016/S0277-9536(02)00343-X
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   ADLER PA, 1995, CONTEMP SOCIOL, V24, P420, DOI 10.2307/2076552
   [Anonymous], 2008, PUBLIC PARTICIPATION
   [Anonymous], 1998, Mind as action
   [Anonymous], AM CLIM CHOIC AD IMP
   [Anonymous], 2008, Risk Governance. Coping with Uncertainty in a Complex World
   [Anonymous], 1996, Understanding Risk: Informing Decisions in a Democratic Society, DOI 10.5860/choice.34-5653
   [Anonymous], 2011, Learning Science through Computer Games and Simulations
   [Anonymous], 2002, Panarchy: Understanding Transformations in Human and Natural Systems
   [Anonymous], SCOPING STUDY REV CO
   Baxter J., 2006, Journal of Environmental Planning and Management, V49, P337, DOI DOI 10.1080/09640560600598361
   Blandford K., 2009, CLIMATE CHANGE PERCE
   Burton Ian., 1993, The Environment as Hazard
   Carpini MXD, 2004, ANNU REV POLIT SCI, V7, P315, DOI 10.1146/annurev.polisci.7.121003.091630
   Chilvers J, 2008, SCI TECHNOL HUM VAL, V33, P155, DOI 10.1177/0162243907307594
   Clark G.E., 1998, Mitigation and Adaptation Strategies for Global Change, V3, P59, DOI DOI 10.1023/A:1009609710795
   Climate Central, 2013, SURG SEAS
   Corburn J., 2005, STREET SCI
   Daniels StevenE., 2001, Working Through Environmental Conflict: The Collaborative Learning Appoach
   Delborne JA, 2011, PUBLIC UNDERST SCI, V20, P367, DOI 10.1177/0963662509347138
   Dietz T, 2005, ANNU REV ENV RESOUR, V30, P335, DOI 10.1146/annurev.energy.30.050504.144444
   Dietz T, 1998, BIOSCIENCE, V48, P441, DOI 10.2307/1313241
   Dietz T, 2013, P NATL ACAD SCI USA, V110, P14081, DOI 10.1073/pnas.1212740110
   DOW K, 1992, GEOFORUM, V23, P417, DOI 10.1016/0016-7185(92)90052-6
   Dow K, 2007, GEOGR COMPASS, V1, P302, DOI 10.1111/j.1749-8198.2007.00036.x
   Downing TE, 2012, WIRES CLIM CHANGE, V3, P161, DOI 10.1002/wcc.157
   Dryzek J.S., 2000, DELIBERATIVE DEMOCRA
   Eakin H, 2006, ANNU REV ENV RESOUR, V31, P365, DOI 10.1146/annurev.energy.30.050504.144352
   EPA, 2013, CLIM RES AW EV TOOL
   Feldman D L., 2008, Decision-support experiments and evaluations using seasonal-to-interannual forecasts and observational data: A focus on water resources, P101
   Ferber P., 2006, Bulletin of Science, Technology Society, V26, P388, DOI DOI 10.1177/0270467606292505
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fischer F, 2000, CITIZENS EXPERTS ENV
   Fishkin JS, 2005, ACTA POLIT, V40, P284, DOI 10.1057/palgrave.ap.5500121
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Folke C, 2010, ECOL SOC, V15
   Forester J, 1999, DELIBERATIVE PRACTIT, P81
   Frazier TG, 2010, APPL GEOGR, V30, P506, DOI 10.1016/j.apgeog.2010.05.007
   Frewer LJ, 2002, PUBLIC UNDERST SCI, V11, P363, DOI 10.1088/0963-6625/11/4/304
   Frohmberg E, 2000, RISK ANAL, V20, P101, DOI 10.1111/0272-4332.00010
   Füssel HM, 2007, GLOBAL ENVIRON CHANG, V17, P155, DOI 10.1016/j.gloenvcha.2006.05.002
   Gokhale A.A., 1995, Journal of Technology Education, V7
   Grimes M, 2006, EUR J POLIT RES, V45, P285, DOI 10.1111/j.1475-6765.2006.00299.x
   Hewes AK, 2008, REG STUD, V42, P1329, DOI 10.1080/00343400701654079
   Hohenemser C., 1985, Perilous progress: Managing the hazard of technology, P25
   Hufschmidt G, 2011, NAT HAZARDS, V58, P621, DOI 10.1007/s11069-011-9823-7
   Kasperson J.X., 2005, SOCIAL CONTOURS RISK, VII, P245
   KASPERSON RE, 1988, RISK ANAL, V8, P177, DOI 10.1111/j.1539-6924.1988.tb01168.x
   Kirshen P, 2008, CLIMATIC CHANGE, V86, P105, DOI 10.1007/s10584-007-9252-5
   Mastrandrea MD, 2010, CLIMATIC CHANGE, V100, P87, DOI 10.1007/s10584-010-9827-4
   McDevitt M, 2006, COMMUN EDUC, V55, P247, DOI 10.1080/03634520600748557
   McLain RJ, 1996, ENVIRON MANAGE, V20, P437, DOI 10.1007/BF01474647
   Merrill S., 2010, ARC USER         FAL, V2010, P28
   Mills D., 2011, NAT CLIM ASS VULN AS
   Moser SC, 2007, CREATING A CLIMATE FOR CHANGE: COMMUNICATING CLIMATE CHANGE AND FACILITATING SOCIAL CHANGE, P64, DOI 10.1017/CBO9780511535871.006
   National Climate Assessment, 2011, NCA REP SER
   NOAA, 2013, SEA LEV RIS COAST FL
   Pahl-Wostl C, 2009, GLOBAL ENVIRON CHANG, V19, P354, DOI 10.1016/j.gloenvcha.2009.06.001
   Pelling M., 1993, NATURAL DISASTER DEV
   Petts J, 2007, GEOGR J, V173, P300, DOI 10.1111/j.1475-4959.2007.00254.x
   Pidgeon N, 2011, NAT CLIM CHANGE, V1, P35, DOI [10.1038/NCLIMATE1080, 10.1038/nclimate1080]
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Rabinovich A, 2012, J ENVIRON PSYCHOL, V32, P11, DOI 10.1016/j.jenvp.2011.09.002
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Renn O, 2006, LAND USE POLICY, V23, P34, DOI 10.1016/j.landusepol.2004.08.005
   Renn O, 1999, ENVIRON SCI TECHNOL, V33, P3049, DOI 10.1021/es981283m
   Schon D.A.M. Rein., 1994, FRAME REFLECTION RES
   Senge P., 1990, 5 DISCIPLINE
   Sheppard S. R. J., 2012, Visualizing climate change: a guide to visual communication of climate change and developing local solutions
   SLOVIC P, 1987, SCIENCE, V236, P280, DOI 10.1126/science.3563507
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Spies S, 1998, RURAL SOCIOL, V63, P65
   Tate E, 2013, ANN ASSOC AM GEOGR, V103, P526, DOI 10.1080/00045608.2012.700616
   Tate E, 2012, NAT HAZARDS, V63, P325, DOI 10.1007/s11069-012-0152-2
   Thomalla F, 2006, DISASTERS, V30, P39, DOI 10.1111/j.1467-9523.2006.00305.x
   TNC, 2012, CLIM WIZ
   Tribbia J, 2008, ENVIRON SCI POLICY, V11, P315, DOI 10.1016/j.envsci.2008.01.003
   Tufts University, 2012, VIRT UND ENV
   Tuler S., 2002, 02005 SERI
   Tuler S., 1999, RISK HLTH SAFETY ENV, V10, P65
   Tuler S., 2000, J RISK RES, V5, P1, DOI DOI 10.1080/136698700376671
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Umoquit MJ, 2011, BMC MED RES METHODOL, V11, DOI 10.1186/1471-2288-11-11
   VCAPS, 2014, VCAPS PROC
   Webler T, 1999, POLICY STUD J, V27, P530, DOI 10.1111/j.1541-0072.1999.tb01984.x
   WEBLER T, 1995, RISK ANAL, V15, P421, DOI 10.1111/j.1539-6924.1995.tb00334.x
   Webler T., 1995, Fairness and Competence in Citizen Participation, P17
   Webler T, 2011, ENVIRON POLICY GOV, V21, P472, DOI 10.1002/eet.587
   Willows R.I., 2003, CLIMATE ADAPTATION R
   Wisner B., 2004, AT RISK, V2nd
   WYNNE B, 1991, SCI TECHNOL HUM VAL, V16, P111, DOI 10.1177/016224399101600108
   Yohe G, 2010, ANN NY ACAD SCI, V1196, P29, DOI 10.1111/j.1749-6632.2009.05310.x
NR 93
TC 21
Z9 24
U1 0
U2 19
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1354-9839
EI 1469-6711
J9 LOCAL ENVIRON
JI Local Environ.
PY 2016
VL 21
IS 2
BP 166
EP 188
DI 10.1080/13549839.2014.930425
PG 23
WC Green & Sustainable Science & Technology; Environmental Studies;
   Geography; Regional & Urban Planning; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Geography; Public Administration; Urban Studies
GA DP0GM
UT WOS:000378167300003
DA 2025-01-10
ER

PT J
AU Gober, P
   Larson, KL
   Quay, R
   Polsky, C
   Chang, H
   Shandas, V
AF Gober, Patricia
   Larson, Kelli L.
   Quay, Ray
   Polsky, Colin
   Chang, Heejun
   Shandas, Vivek
TI Why Land Planners and Water Managers Don't Talk to One Another and Why
   They Should!
SO SOCIETY & NATURAL RESOURCES
LA English
DT Article
DE climate adaptation; governance gap; land planning; suburban drought;
   sustainable resource use; urban growth; water management
ID CLIMATE; TEMPERATURE; CONSUMPTION; PHOENIX
AB Increasing evidence demonstrates that unsustainable land use practices result in human-induced drought conditions, and inadequate water supplies constrain land development in growing cities. Nonetheless, organizational barriers impair coordinated land and water management. Land planning is strongly influenced by political realities and interest groups, while water management is focused on the single-minded goal of providing reliable water for future development, often set apart from other priorities. Survey results from Portland, OR, and Phoenix, AZ, show that water managers and land planners are generally aware of the physical interconnections between land and water, but there is little cross-sector involvement in the two cities. Focusing on shared concerns about outdoor water use, climate variability, and water-sensitive urban design is a fruitful first step in integrating the practices of land planning and water management for climate adaptation and sustainable resource use.
C1 [Gober, Patricia] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85287 USA.
   [Gober, Patricia] Univ Saskatchewan, Johnson Shoyama Grad Sch Publ Policy, Saskatoon, SK, Canada.
   [Larson, Kelli L.] Arizona State Univ, Sch Geog Sci & Urban Planning, Sch Sustainabil, Tempe, AZ 85287 USA.
   [Quay, Ray] Arizona State Univ, Decis Ctr Desert City, Tempe, AZ 85287 USA.
   [Polsky, Colin] Clark Univ, Grad Sch Geog, Worcester, MA 01610 USA.
   [Chang, Heejun] Portland State Univ, Dept Geog, Portland, OR 97207 USA.
   [Shandas, Vivek] Portland State Univ, Nohad A Toulan Sch Urban Studies & Planning, Portland, OR 97207 USA.
C3 Arizona State University; Arizona State University-Tempe; University of
   Saskatchewan; Arizona State University; Arizona State University-Tempe;
   Arizona State University; Arizona State University-Tempe; Clark
   University; Portland State University; Portland State University
RP Gober, P (corresponding author), Arizona State Univ, Sch Geog Sci & Urban Planning, POB 875302, Tempe, AZ 85287 USA.
EM gober@asu.edu
RI Chang, Heejun/AGF-1404-2022
FU Direct For Social, Behav & Economic Scie; Divn Of Social and Economic
   Sciences [0951366] Funding Source: National Science Foundation; Direct
   For Social, Behav & Economic Scie; Divn Of Social and Economic Sciences
   [0849985] Funding Source: National Science Foundation; Division Of Ocean
   Sciences; Directorate For Geosciences [1058747] Funding Source: National
   Science Foundation; Division Of Ocean Sciences; Directorate For
   Geosciences [1238212] Funding Source: National Science Foundation
CR Barker I., 2011, I6 UK ENV AG
   Bates S., 2011, Bridging the governance gap: Strategies to integrate water and land use planning, VSecond
   Bormann FH., 2001, Redesigning the American lawn: a search for environmental harmony
   Carter JG, 2007, GEOGR J, V173, P330, DOI 10.1111/j.1475-4959.2007.00257.x
   Cruce T.L., 2009, Adaptation planning - What U.S. states and localities are doing
   Del Moral Ituarte L., 2000, J. Contingencies Cris. Manag, DOI [DOI 10.1111/1468-5973.00128, 10.1111/1468-5973.00128]
   Domene E, 2006, URBAN STUD, V43, P1605, DOI 10.1080/00420980600749969
   Fallah B, 2012, ANN REGIONAL SCI, V49, P589, DOI 10.1007/s00168-011-0466-0
   Fulton W., 2001, WHO SPRAWLS MOST GRO
   Gober P, 2012, URBAN GEOGR, V33, P1030, DOI 10.2747/0272-3638.33.7.1030
   Gober P, 2010, CURR OPIN ENV SUST, V2, P144, DOI 10.1016/j.cosust.2010.06.006
   Harlan SL, 2006, SOC SCI MED, V63, P2847, DOI 10.1016/j.socscimed.2006.07.030
   Hill T., 2007, GLOBAL ENV CHANGE PA, V7, P291
   Hind J. B., 2008, P WATER ENV FEDERATI, V20, P368
   Hirt P, 2008, ENVIRON HIST-US, V13, P482, DOI 10.1093/envhis/13.3.482
   House-Peters L, 2010, J AM WATER RESOUR AS, V46, P461, DOI 10.1111/j.1752-1688.2009.00415.x
   Jenerette GD, 2007, LANDSCAPE ECOL, V22, P353, DOI 10.1007/s10980-006-9032-z
   Jenkins VirginiaScott., 1994, The Lawn: A History of an American Obsession
   Kallis G, 2003, EUR PLAN STUD, V11, P245, DOI 10.1080/09654310303633
   Lach D, 2005, TEX LAW REV, V83, P2027
   Larson KL, 2009, ENVIRON SCI POLICY, V12, P1012, DOI 10.1016/j.envsci.2009.07.012
   Larson K. L., 2012, VULNERABILITY UNPUB
   Larson K. L., 2011, ANN C ASS AM GEOGR S
   Metropolitan Area Planning Council, 2008, WAT SUPPL COMP REG P
   Pendall Rolf., 2006, From Traditional to Reformed: A Review of the Land Use Regulations in the Nation's 50 Largest Metropolitan Areas
   Puget Sound Regional Council, 2008, PUG SOUND TRENDS T
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Rayner S., 2003, WEATHER FORECASTS AR
   Robbins Paul., 2007, Lawn People: How Grasses, Weeds, and Chemicals Make Us Who We Are
   Rosenzweig C, 2010, NATURE, V467, P909, DOI 10.1038/467909a
   Sandercock L., 1998, Towards Cosmopolis: Planning for Multicultural Cities
   Steinberg Ted., 2007, AM GREEN OBSESSIVE Q
   U.S. Environmental Protection Agency, 2008, OUTD WAT US US
   Wheater H, 2009, LAND USE POLICY, V26, pS251, DOI 10.1016/j.landusepol.2009.08.019
   White DD, 2008, SOC NATUR RESOUR, V21, P230, DOI 10.1080/08941920701329678
NR 35
TC 52
Z9 66
U1 1
U2 54
PU TAYLOR & FRANCIS INC
PI PHILADELPHIA
PA 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA
SN 0894-1920
EI 1521-0723
J9 SOC NATUR RESOUR
JI Soc. Nat. Resour.
PD MAR 1
PY 2013
VL 26
IS 3
BP 356
EP 364
DI 10.1080/08941920.2012.713448
PG 9
WC Development Studies; Environmental Studies; Regional & Urban Planning;
   Sociology
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology; Public
   Administration; Sociology
GA 100DP
UT WOS:000315676300008
DA 2025-01-10
ER

PT J
AU Roggero, M
   Bisaro, A
   Villamayor-Tomas, S
AF Roggero, Matteo
   Bisaro, Alexander
   Villamayor-Tomas, Sergio
TI Institutions in the climate adaptation literature: a systematic
   literature review through the lens of the Institutional Analysis and
   Development framework
SO JOURNAL OF INSTITUTIONAL ECONOMICS
LA English
DT Article
ID ADAPTIVE CAPACITY; ENVIRONMENTAL GOVERNANCE; COLLECTIVE ACTION;
   DECISION-MAKING; VULNERABILITY; BARRIERS; SUSTAINABILITY; ASSESSMENTS;
   MANAGEMENT
AB Analyses of climate adaptation seldom rely on the conceptual toolbox of institutional economics. Yet articles addressing institutions make up a large portion of the climate adaptation literature. With a wealth of institutionally relevant knowledge in the adaptation literature, organizing such knowledge in institutionally meaningful ways can advance the present understanding of the link between institutions and adaptation. Knowing which aspects of this link are well researched, and where in contrast research gaps lie, can provide guidance to institutional economists interested in adaptation. We contribute to this through a systematic review of the adaptation literature, assessing the consideration adaptation scholars give to different elements of the Institutional Analysis and Development framework. Results show a strong focus on collective choice and on adaptation by public actors, with an emphasis on rules in use, social interactions and, to a lesser extent, attributes of the community. Research gaps rather encompass operational and constitutional choice, private adaptation, physical interactions and biophysical conditions.
C1 [Roggero, Matteo] Humboldt Univ, Resource Econ Grp, Berlin, Germany.
   [Bisaro, Alexander] Global Climate Forum, Berlin, Germany.
   [Villamayor-Tomas, Sergio] Autonomous Univ Barcelona, ICTA, Barcelona, Spain.
C3 Humboldt University of Berlin; Autonomous University of Barcelona
RP Roggero, M (corresponding author), Humboldt Univ, Resource Econ Grp, Berlin, Germany.
EM matteo.mancini.roggero@gmail.com; sandy.bisaro@globalclimateforum.org;
   villamayortomas@gmail.com
OI Bisaro, Alexander/0000-0003-4281-0012
FU German Federal Ministry of Education and Research, BMBF [FKZ 03EK3523C];
   EU [642018]
FX We gratefully acknowledge funding by the German Federal Ministry of
   Education and Research, BMBF (grant agreement FKZ 03EK3523C) and by the
   EU (Green Win project, grant no. 642018). We also wish to thank Klaus
   Eisenack, the journal's editors and three anonymous reviewers for their
   precious comments on earlier versions of this paper.
CR Abel N, 2011, ENVIRON SCI POLICY, V14, P279, DOI 10.1016/j.envsci.2010.12.002
   Adger WN, 2003, ECON GEOGR, V79, P387
   [Anonymous], 2010, Ecology and Society
   [Anonymous], WILEY INTERDISCIPL R
   [Anonymous], 2005, Journal of Institutional Economics, DOI [DOI 10.1017/S1744137405000020, 10.1017/S1744137405000020]
   Armitage D, 2011, GLOBAL ENVIRON CHANG, V21, P995, DOI 10.1016/j.gloenvcha.2011.04.006
   Baird J, 2014, GLOBAL ENVIRON CHANG, V27, P51, DOI 10.1016/j.gloenvcha.2014.04.019
   Berrang-Ford L, 2015, REG ENVIRON CHANGE, V15, P755, DOI 10.1007/s10113-014-0708-7
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Bichard E, 2012, CLIMATIC CHANGE, V112, P633, DOI 10.1007/s10584-011-0257-8
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Biesbroek GR, 2014, GLOBAL ENVIRON CHANG, V26, P108, DOI 10.1016/j.gloenvcha.2014.04.004
   Biesbroek GR, 2010, GLOBAL ENVIRON CHANG, V20, P440, DOI 10.1016/j.gloenvcha.2010.03.005
   Cox M, 2012, ECOL SOC, V17, DOI 10.5751/ES-05173-170454
   Cuevas SC, 2016, CLIMATIC CHANGE, V136, P661, DOI 10.1007/s10584-016-1625-1
   DENZAU AT, 1994, KYKLOS, V47, P3, DOI 10.1111/j.1467-6435.1994.tb02246.x
   Eakin H, 2005, WORLD DEV, V33, P1923, DOI 10.1016/j.worlddev.2005.06.005
   Eisenack K, 2014, NAT CLIM CHANGE, V4, P867, DOI 10.1038/NCLIMATE2350
   Eisenack K, 2012, MITIG ADAPT STRAT GL, V17, P451, DOI 10.1007/s11027-011-9336-4
   Epstein G, 2015, CURR OPIN ENV SUST, V14, P34, DOI 10.1016/j.cosust.2015.03.005
   Ford JD, 2015, REG ENVIRON CHANGE, V15, P801, DOI 10.1007/s10113-014-0648-2
   Ford JD, 2011, CLIMATIC CHANGE, V106, P327, DOI 10.1007/s10584-011-0045-5
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Glaas E, 2010, LOCAL ENVIRON, V15, P525, DOI 10.1080/13549839.2010.487525
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Hagedorn K, 2008, EUR REV AGRIC ECON, V35, P357, DOI 10.1093/erae/jbn019
   Hall PA, 1996, POLIT STUD-LONDON, V44, P936, DOI 10.1111/j.1467-9248.1996.tb00343.x
   Harries T, 2011, GLOBAL ENVIRON CHANG, V21, P188, DOI 10.1016/j.gloenvcha.2010.09.002
   Hindriks F, 2015, J I ECON, V11, P515, DOI 10.1017/S1744137415000120
   Hinkel J, 2016, REG ENVIRON CHANGE, V16, P7, DOI 10.1007/s10113-014-0682-0
   Hodgson GM, 2015, J I ECON, V11, P497, DOI 10.1017/S1744137415000028
   Huntjens P, 2012, GLOBAL ENVIRON CHANG, V22, P67, DOI 10.1016/j.gloenvcha.2011.09.015
   IPCC, 2013, 37 SESS BAT 14 18 OC
   Janssen MA, 2006, GLOBAL ENVIRON CHANG, V16, P240, DOI 10.1016/j.gloenvcha.2006.04.001
   Jantarasami LC, 2010, ECOL SOC, V15
   Juhola S, 2011, ENVIRON SCI POLICY, V14, P239, DOI 10.1016/j.envsci.2010.12.006
   Kellens W, 2013, RISK ANAL, V33, P24, DOI 10.1111/j.1539-6924.2012.01844.x
   Knight J., 1997, Legal Theory, V3, P211, DOI [DOI 10.1017/S1352325200000768, 10.1017/S1352325200000768]
   Knight J., 1992, I SOCIAL CONFLICT
   McGinnis MD, 2011, POLICY STUD J, V39, P169, DOI 10.1111/j.1541-0072.2010.00401.x
   Nielsen JO, 2014, GLOBAL ENVIRON CHANG, V24, P402, DOI 10.1016/j.gloenvcha.2013.10.006
   NORTH DC, 1991, J ECON PERSPECT, V5, P97, DOI 10.1257/jep.5.1.97
   O'Brien K, 2007, CLIM POLICY, V7, P73, DOI 10.1080/14693062.2007.9685639
   Oberlack C, 2017, MITIG ADAPT STRAT GL, V22, P805, DOI 10.1007/s11027-015-9699-z
   Ostrom E, 2005, UNDERSTANDING INSTITUTIONAL DIVERSITY, P1
   Ostrom E., 2007, THEORIES POLICY PROC
   Ostrom E., 1990, GOVERNING COMMONS EV
   Ostrom E, 2011, POLICY STUD J, V39, P7, DOI 10.1111/j.1541-0072.2010.00394.x
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Paavola J, 2007, ECOL ECON, V63, P93, DOI 10.1016/j.ecolecon.2006.09.026
   Pahl-Wostl C., 2008, Ecology and Society, V13
   Pahl-Wostl C, 2007, WATER RESOUR MANAG, V21, P49, DOI 10.1007/s11269-006-9040-4
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Petticrew M, 2008, HEALTH ECON POLICY L, V3, P197, DOI 10.1017/S1744133108004453
   Plummer R, 2012, WATER RESOUR MANAG, V26, P4327, DOI 10.1007/s11269-012-0147-5
   Poteete AR, 2010, WORKING TOGETHER: COLLECTIVE ACTION, THE COMMONS, AND MULTIPLE METHODS IN PRACTICE, P1
   Poteete AR, 2008, WORLD DEV, V36, P176, DOI 10.1016/j.worlddev.2007.02.012
   Roggero M, 2015, ECOL ECON, V118, P114, DOI 10.1016/j.ecolecon.2015.07.022
   Seara T, 2016, GLOBAL ENVIRON CHANG, V38, P49, DOI 10.1016/j.gloenvcha.2016.01.006
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Thackeray SJ, 2010, GLOBAL CHANGE BIOL, V16, P3304, DOI 10.1111/j.1365-2486.2010.02165.x
   Nguyen TPL, 2016, AGR SYST, V143, P205, DOI 10.1016/j.agsy.2016.01.001
   Thiel A., 2012, ENV POLICY GOVERNANC
   Thiel A, 2016, ECOL ECON, V128, P159, DOI 10.1016/j.ecolecon.2016.04.018
   Vatn A., 2005, I ENV
   Villamayor-Tomas S., 2017, J I EC UNPUB
   Vogt JM, 2015, ECOL SOC, V20, DOI 10.5751/ES-07239-200155
   Williamson QE, 2000, J ECON LIT, V38, P595
   Young O.R., 2002, I DIMENSIONS ENV CHA, DOI DOI 10.7551/MITPRESS/3807.001.0001
   Zhang YQW, 2013, CLIMATIC CHANGE, V118, P183, DOI 10.1007/s10584-012-0642-y
NR 71
TC 28
Z9 31
U1 1
U2 30
PU CAMBRIDGE UNIV PRESS
PI CAMBRIDGE
PA EDINBURGH BLDG, SHAFTESBURY RD, CB2 8RU CAMBRIDGE, ENGLAND
SN 1744-1374
EI 1744-1382
J9 J I ECON
JI J. Inst. Econ.
PD JUN
PY 2018
VL 14
IS 3
SI SI
BP 423
EP 448
DI 10.1017/S1744137417000376
PG 26
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA GI3QQ
UT WOS:000434286600002
OA Bronze, Green Accepted
DA 2025-01-10
ER

PT J
AU Vantaggiato, FP
   Lubell, M
AF Vantaggiato, Francesca Pia
   Lubell, Mark
TI The benefits of specialized knowledge in polycentric
   governance(sic)(sic)(sic)Palabras clave
SO POLICY STUDIES JOURNAL
LA English
DT Article
DE climate adaptation; composition; policy forums; polycentric governance;
   specialization
ID SEA-LEVEL RISE; CLIMATE ADAPTATION; COLLABORATIVE GOVERNANCE; NETWORKS;
   INTERDEPENDENCE; PERFORMANCE; MANAGEMENT; GOVERNMENT; CONFLICT; LESSONS
AB Policy forums bring individual actors together to deliberate on specific policy issues. The literature found that actors' perceptions of forum performance depend on both their individual characteristics (goals, expertise, resources) and forum processes (trust, learning, beliefs). However, we do not know how different combinations of actors, embodying different types of knowledge or expertise, relate to forum performance. We distinguish between policy and institutional specialization. Forum participants can be policy specialists, who are experts on the policy issue, and/or institutional specialists, who are expert of the policy process in the governance system. The former excel at problem definition and facilitation; the latter enable inclusivity. We surmise that higher proportions of specialized actors positively affect the group's perceptions of forum performance in terms of both process and outcomes, particularly in high conflict forums. We test this claim using survey data on 55 policy forums working on adaptation to sea level rise in the San Francisco Bay Area, collected in summer 2018. The empirical findings lend support to our hypothesis as concerns policy specialists but not as concerns institutional specialists. Further research should devote more effort to study how actor composition affects forum performance.
C1 [Vantaggiato, Francesca Pia] Kings Coll London, Dept Polit Econ, Bush House North East Wing,40 Aldwych, London WC2B 4BG, England.
   [Lubell, Mark] Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA.
C3 University of London; King's College London; University of California
   System; University of California Davis
RP Vantaggiato, FP (corresponding author), Kings Coll London, Dept Polit Econ, Bush House North East Wing,40 Aldwych, London WC2B 4BG, England.
EM francesca.vantaggiato@kcl.ac.uk
RI Vantaggiato, Francesca/GPS-9047-2022; Lubell, Mark/H-5018-2012
OI Lubell, Mark/0000-0001-5757-7116
CR Agranoff R, 2006, PUBLIC ADMIN REV, V66, P56, DOI 10.1111/j.1540-6210.2006.00666.x
   Aligica PD, 2012, GOVERNANCE, V25, P237, DOI 10.1111/j.1468-0491.2011.01550.x
   Ansell C., 2012, Innovation Journal, V17
   Ansell C, 2008, J PUBL ADM RES THEOR, V18, P543, DOI 10.1093/jopart/mum032
   Ansell C, 2020, POLICY SOC, V39, P570, DOI 10.1080/14494035.2020.1785726
   Baruch Y, 2008, HUM RELAT, V61, P1139, DOI 10.1177/0018726708094863
   Berardo R, 2016, PUBLIC ADMIN REV, V76, P738, DOI 10.1111/puar.12532
   Berardo R, 2015, REV POLICY RES, V32, P443, DOI 10.1111/ropr.12128
   Calanni JC, 2015, J PUBL ADM RES THEOR, V25, P901, DOI 10.1093/jopart/mut080
   CALVERT RL, 1992, INT POLIT SCI REV, V13, P7, DOI 10.1177/019251219201300102
   Carlisle K, 2019, POLICY STUD J, V47, P921, DOI 10.1111/psj.12212
   Christensen Rune Haubo B., 2018, Cumulative link models for ordinal regression with the R package ordinal
   Christopoulos D, 2015, EUR POLIT SCI REV, V7, P475, DOI 10.1017/S1755773914000277
   Dobbin KB, 2021, POLICY STUD J, V49, P562, DOI 10.1111/psj.12375
   Edelenbos J, 2006, J PUBL ADM RES THEOR, V16, P417, DOI 10.1093/jopart/mui049
   Edelenbos J, 2013, PUBLIC MANAG REV, V15, P131, DOI 10.1080/14719037.2012.691009
   Ekstrom JA, 2014, URBAN CLIM, V9, P54, DOI 10.1016/j.uclim.2014.06.002
   Emerson K, 2015, PUBLIC PERFORM MANAG, V38, P717, DOI 10.1080/15309576.2015.1031016
   Emerson K, 2012, J PUBL ADM RES THEOR, V22, P1, DOI 10.1093/jopart/mur011
   Fischer M, 2019, POLICY STUD J, V47, P114, DOI 10.1111/psj.12310
   Fischer M, 2017, ENVIRON POLIT, V26, P870, DOI 10.1080/09644016.2017.1284981
   Gerlak A.K., 2012, OXFORD HDB US ENV PO, P413, DOI [DOI 10.1093/OXFORDHB/9780199744671.001.0001/OXFORDHB-9780199744671, 10.1093/oxfordhb/9780199744671.013.0019]
   Gerlak AK, 2011, J PUBL ADM RES THEOR, V21, P619, DOI 10.1093/jopart/muq089
   Hamilton M, 2018, ECOL SOC, V23, DOI 10.5751/ES-10179-230236
   Hamilton M, 2018, POLICY STUD J, V46, P222, DOI 10.1111/psj.12224
   Heikkila T, 2018, ENVIRON POLICY GOV, V28, P207, DOI 10.1002/eet.1809
   Heikkila T, 2013, POLICY STUD J, V41, P484, DOI 10.1111/psj.12026
   Hummel MA, 2018, REG ENVIRON CHANGE, V18, P1343, DOI 10.1007/s10113-017-1267-5
   Jasny L, 2015, SOC NETWORKS, V41, P36, DOI 10.1016/j.socnet.2014.11.005
   Javeline D, 2014, PERSPECT POLIT, V12, P420, DOI 10.1017/S1537592714000784
   Klijn EH, 2010, PUBLIC ADMIN, V88, P1063, DOI 10.1111/j.1467-9299.2010.01826.x
   Koebele EA, 2019, J ENVIRON POL PLAN, V21, P242, DOI 10.1080/1523908X.2019.1623661
   Leach WD, 2014, J PUBL ADM RES THEOR, V24, P591, DOI 10.1093/jopart/mut011
   Lubell M, 2021, NAT SUSTAIN, V4, P664, DOI 10.1038/s41893-021-00707-5
   Lubell M, 2022, POLICY STUD J, V50, P143, DOI 10.1111/psj.12430
   Lubell M, 2020, PUBLIC ADMIN REV, V80, P222, DOI 10.1111/puar.13159
   Lubell M, 2017, PUBLIC ADMIN REV, V77, P668, DOI 10.1111/puar.12622
   Lubell M, 2014, ECOL SOC, V19, DOI 10.5751/ES-06880-190423
   Lubell M, 2013, POLICY STUD J, V41, P537, DOI 10.1111/psj.12028
   Maag S, 2018, SOC NATUR RESOUR, V31, P1248, DOI 10.1080/08941920.2018.1484973
   McAllister RRJ, 2014, REG ENVIRON CHANGE, V14, P527, DOI 10.1007/s10113-013-0489-4
   McCauley D, 2018, ENERG POLICY, V119, P1, DOI 10.1016/j.enpol.2018.04.014
   McGinnis MD, 2012, PUBLIC ADMIN REV, V72, P15, DOI 10.1111/j.1540-6210.2011.02488.x
   Meier KJ, 2013, INT PUBLIC MANAG J, V16, P1, DOI 10.1080/10967494.2013.796253
   Mewhirter J, 2019, POLICY STUD J, V47, P996, DOI 10.1111/psj.12227
   Mewhirter J, 2019, SOC NATUR RESOUR, V32, P1239, DOI 10.1080/08941920.2019.1646366
   Mewhirter J, 2019, POLICY STUD J, V47, P159, DOI 10.1111/psj.12302
   Mildenberger M, 2019, GLOBAL ENVIRON CHANG, V55, P15, DOI 10.1016/j.gloenvcha.2019.01.002
   Morrison TH, 2019, GLOBAL ENVIRON CHANG, V57, DOI 10.1016/j.gloenvcha.2019.101934
   Morrison TH, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.479
   O'Toole LaurenceJ., 1999, J PUBL ADM RES THEOR, V9, P505
   OSTROM V, 1961, AM POLIT SCI REV, V55, P831, DOI 10.2307/1952530
   Preston BL, 2015, MITIG ADAPT STRAT GL, V20, P467, DOI 10.1007/s11027-013-9503-x
   RUBIN DB, 1976, BIOMETRIKA, V63, P581, DOI 10.2307/2335739
   Scott TA, 2017, J PUBL ADM RES THEOR, V27, P647, DOI 10.1093/jopart/mux009
   Scott TA, 2017, POLICY STUD J, V45, P191, DOI 10.1111/psj.12162
   Ulibarri N, 2015, POLICY STUD J, V43, P283, DOI 10.1111/psj.12096
   van Bueren EM, 2003, J PUBL ADM RES THEOR, V13, P193, DOI 10.1093/jopart/mug017
   Vogel David, 2018, CALIFORNIA GREENIN G
   Wang RQ, 2018, EARTHS FUTURE, V6, P677, DOI 10.1002/2017EF000742
   Weible CM, 2018, J PUBLIC POLICY, V38, P1, DOI 10.1017/S0143814X16000301
   Weible CM, 2017, POLICY SCI, V50, P23, DOI 10.1007/s11077-017-9280-6
NR 62
TC 6
Z9 6
U1 2
U2 11
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0190-292X
EI 1541-0072
J9 POLICY STUD J
JI Policy Stud. J.
PD NOV
PY 2022
VL 50
IS 4
BP 849
EP 876
DI 10.1111/psj.12464
EA APR 2022
PG 28
WC Political Science; Public Administration
WE Social Science Citation Index (SSCI)
SC Government & Law; Public Administration
GA 6W1TV
UT WOS:000780755800001
OA hybrid
DA 2025-01-10
ER

PT J
AU Landauer, M
   Goodsite, ME
   Juhola, S
AF Landauer, Mia
   Goodsite, Michael Evan
   Juhola, Sirkku
TI Nordic national climate adaptation and tourism strategies - (how) are
   they interlinked?
SO SCANDINAVIAN JOURNAL OF HOSPITALITY AND TOURISM
LA English
DT Article
DE Nordic countries; tourism management; public policy; climate change;
   national adaptation strategies
ID VULNERABILITY; DESTINATIONS; PERCEPTIONS; SCENARIOS; WEATHER; POLICY
AB The tourism sector is affected by climate change. Nordic tourism destinations have also experienced changes, such as changing precipitation patterns, lack of snow in winter and shifts in seasons. The sector has to implement adaptation strategies but it is unclear whether the current public climate policy is sufficient to support considering adaptation actions. We reviewed national climate strategies of the Nordic countries from the perspectives of tourism, but excluding the transport sector. We also reviewed Nordic national tourism strategies from the perspective of climate change, particularly the extent to which they address climate adaptation. We found out that the national climate strategies do not pay enough attention to tourism adaptation needs, nor do the national tourism strategies present adaptation actions that tourism actors could consider. To connect these national-level strategies, there is a need to review adaptation actions for tourism within the national adaptation framework supported by research based evidence. Next, by means of Nordic cooperation, guidance for both public and private tourism actors within and across Nordic countries can be provided. This can enhance the competitiveness and resilience of the Nordic tourism supply and contribute to the development of economically, environmentally and socially sustainable tourism in the region.
C1 [Landauer, Mia] Int Inst Appl Syst Anal, Risk & Resilience Program, Schlosspl 1, A-2381 Laxenburg, Austria.
   [Landauer, Mia] Int Inst Appl Syst Anal, Arctic Futures Initiat, Schlosspl 1, A-2381 Laxenburg, Austria.
   [Goodsite, Michael Evan] Univ Southern Denmark, Fac Engn, Odense, Denmark.
   [Juhola, Sirkku] Univ Helsinki, Dept Environm Sci, Helsinki, Finland.
   [Juhola, Sirkku] Aalto Univ, Dept Built Environm, Espoo, Finland.
   [Goodsite, Michael Evan] Univ Iceland, Environm & Nat Resources, Reykjavik, Iceland.
C3 International Institute for Applied Systems Analysis (IIASA);
   International Institute for Applied Systems Analysis (IIASA); University
   of Southern Denmark; University of Helsinki; Aalto University;
   University of Iceland
RP Landauer, M (corresponding author), Int Inst Appl Syst Anal, Risk & Resilience Program, Schlosspl 1, A-2381 Laxenburg, Austria.; Landauer, M (corresponding author), Int Inst Appl Syst Anal, Arctic Futures Initiat, Schlosspl 1, A-2381 Laxenburg, Austria.
EM landauem@iiasa.ac.at
RI Goodsite, Michael/X-9374-2019; Juhola, Sirkku/IXW-8093-2023; Landauer,
   Mia/KJM-4945-2024; Goodsite, Michael/B-7321-2012
OI Juhola, Sirkku/0000-0003-0095-2282; Landauer, Mia/0000-0002-7153-8495;
   Goodsite, Michael/0000-0002-4565-6607
FU Norden Top-level Research Initiative sub-programme "Effect Studies and
   Adaptation to Climate Change" through the Nordic Centre of Excellence
   for Strategic Adaptation Research (NORD-STAR)
FX The preparation of this publication has been supported by the Norden
   Top-level Research Initiative sub-programme "Effect Studies and
   Adaptation to Climate Change" through the Nordic Centre of Excellence
   for Strategic Adaptation Research (NORD-STAR).
CR Adger W. N., 2001, Journal of International Development, V13, P921, DOI 10.1002/jid.833
   Amelung B., 2007, Journal of Travel Research, V45, P285, DOI 10.1177/0047287506295937
   Amelung B, 2014, TOURISM MANAGE, V41, P228, DOI 10.1016/j.tourman.2013.10.002
   [Anonymous], 2015, Tourism highlights
   [Anonymous], 2008, DAN STRAT AD CHANG C
   [Anonymous], 2007, Swedish Government Official Reports, P60
   Arent DJ, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P659
   Becken S, 2013, TOUR MANAG PERSPECT, V6, P53, DOI 10.1016/j.tmp.2012.11.006
   Becken S, 2011, J POLICY RES TOUR LE, V3, P1, DOI 10.1080/19407963.2011.539378
   Biesbroek R., 2014, NATL ADAPTATION POLI, P136
   Danish Nature Agency, 2012, MAPP CLIM CHANG BARR
   Dawson J, 2013, TOURISM MANAGE, V35, P244, DOI 10.1016/j.tourman.2012.07.009
   Denstadli JM, 2011, ANN TOURISM RES, V38, P920, DOI 10.1016/j.annals.2011.01.005
   Dubois G., 2006, Journal of Sustainable Tourism, V14, P399, DOI 10.2167/jost539.0
   European Commission, 2015, TOUR IND SUBS EUR CO
   Forland EJ, 2013, TOURISM MANAGE, V36, P567, DOI 10.1016/j.tourman.2012.09.002
   Genc R., 2010, ACTA U DANUBIUS EC, V6, P54
   Gössling S, 2006, CLIMATIC CHANGE, V79, P163, DOI 10.1007/s10584-006-9081-y
   Gössling S, 2012, ANN TOURISM RES, V39, P36, DOI 10.1016/j.annals.2011.11.002
   Haanpää S, 2015, CURR ISSUES TOUR, V18, P966, DOI 10.1080/13683500.2014.892917
   Halkier H, 2010, SCAND J HOSP TOUR, V10, P89, DOI 10.1080/15022250.2010.484219
   Hall C.M., 2009, Nordic tourism: Issues and cases
   Hall CM, 2009, CONTEMP GEOGR LEIS T, P1
   Haukeland JV, 2010, SCAND J HOSP TOUR, V10, P248, DOI 10.1080/15022250.2010.502367
   Jopp R, 2010, CURR ISSUES TOUR, V13, P591, DOI 10.1080/13683501003653379
   Kaján E, 2013, CURR ISSUES TOUR, V16, P167, DOI 10.1080/13683500.2013.774323
   Konu H, 2011, TOURISM MANAGE, V32, P1096, DOI 10.1016/j.tourman.2010.09.010
   Landauer M, 2014, J TRAVEL RES, V53, P96, DOI 10.1177/0047287513481276
   Landauer M, 2012, TOURISM MANAGE, V33, P741, DOI 10.1016/j.tourman.2011.08.007
   Lesnikowski A, 2016, NAT CLIM CHANGE, V6, P261, DOI [10.1038/NCLIMATE2863, 10.1038/nclimate2863]
   Lundmark L., 2010, Tourism and change in polar regions: Climate, environments and experiences pp, P135
   Lundmark L, 2010, TOURISM, V58, P379
   Makkonen L, 2007, Geophysica, V43, P19
   Marttila Veikko., 2005, Finland's National Strategy for Adaptation to Climate Change
   Ministry of Agriculture and Forestry, 2014, FINL NAT CLIM CHANG
   Nicholls S, 2015, SCAND J HOSP TOUR, V15, P48, DOI 10.1080/15022250.2015.1010325
   Nordic Innovation Centre, 2008, WORKSH COP JUN 2008
   OECD/United Nations Environment Programme, 2011, OECD STUD TOUR, DOI [10. 1787/9789264119598-en, DOI 10.1787/9789264119598-EN]
   Perch-Nielsen SL, 2010, CLIMATIC CHANGE, V100, P579, DOI 10.1007/s10584-009-9692-1
   Pröbstl-Haider U, 2015, J OUTDOOR REC TOUR, V10, P1, DOI 10.1016/j.jort.2015.07.004
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Räisänen J, 2012, CLIM DYNAM, V38, P2575, DOI 10.1007/s00382-011-1076-3
   Saarinen J, 2014, SCAND J HOSP TOUR, V14, P1, DOI 10.1080/15022250.2014.886098
   Saarinen J, 2006, INT J INNOV SUSTAIN, V1, P214, DOI 10.1504/IJISD.2006.012423
   Scott D, 2010, PROCEDIA ENVIRON SCI, V1, P146, DOI 10.1016/j.proenv.2010.09.011
   SCOTT D., 2012, TOURISM CLIMATE CHAN
   Scott Daniel, 2009, V1, P171, DOI 10.1007/978-1-4020-8921-3_8
   Siegrist D, 2011, Z TOUR, V3, P179
   Tervo K, 2008, SCAND J HOSP TOUR, V8, P317, DOI 10.1080/15022250802553696
   Tervo-Kankare K, 2011, TOUR PLAN DEV, V8, P399, DOI 10.1080/21568316.2011.598180
   The Research Council of Norway, 2012, NORW CLIM RES EV
   Trawöger L, 2014, TOURISM MANAGE, V40, P338, DOI 10.1016/j.tourman.2013.07.010
NR 52
TC 11
Z9 12
U1 4
U2 28
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1502-2250
EI 1502-2269
J9 SCAND J HOSP TOUR
JI Scand. J. Hosp. Tour.
PY 2018
VL 18
SU 1
SI SI
BP S75
EP S86
DI 10.1080/15022250.2017.1340540
PG 12
WC Hospitality, Leisure, Sport & Tourism; Sociology
WE Social Science Citation Index (SSCI)
SC Social Sciences - Other Topics; Sociology
GA HC7WR
UT WOS:000452013200006
OA Green Submitted, Green Accepted
DA 2025-01-10
ER

PT J
AU McFadgen, B
   Huitema, D
AF McFadgen, Belinda
   Huitema, Dave
TI Stimulating Learning through Policy Experimentation: A Multi-Case
   Analysis of How Design Influences Policy Learning Outcomes in
   Experiments for Climate Adaptation
SO WATER
LA English
DT Article
DE policy learning; policy experiments; climate adaptation; science-policy
   interface
ID MANAGEMENT; PARTICIPATION; KNOWLEDGE; LESSONS
AB Learning from policy experimentation is a promising way to approach the "wicked problem" of climate adaptation, which is characterised by knowledge gaps and contested understandings of future risk. However, although the role of learning in shaping public policy is well understood, and experiments are expected to facilitate learning, little is known about how experiments produce learning, what types of learning, and how they can be designed to enhance learning effects. Using quantitative research methods, we explore how design choices influence the learning experiences of 173 participants in 18 policy experiments conducted in the Netherlands between 1997 and 2016. The experiments are divided into three "ideal types" that are expected to produce different levels and types of learning. The findings show that policy experiments produce cognitive and relational learning effects, but less normative learning, and experiment design influenced three of six measured dimensions of learning, especially the cognitive learning dimensions. This reveals a trade-off between designing for knowledge development and designing for normative or relational changes; choices that experiment designers should make in the context of their adaptation problem. Our findings also show the role leadership plays in building trust.
C1 [McFadgen, Belinda] Vrije Univ Amsterdam, Inst Environm Studies IVM, De Boelelaan 1085, NL-1081 HV Amsterdam, Netherlands.
   [Huitema, Dave] Vrije Univ Amsterdam, Deputy Dept, Inst Environm Studies IVM, Environm Policy Anal, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands.
   [Huitema, Dave] Netherlands Open Univ, Fac Management Sci & Technol, Dept Sci, Valkenburgerweg 177, NL-6419 AT Heerlen, Netherlands.
C3 Vrije Universiteit Amsterdam; Vrije Universiteit Amsterdam; Open
   University Netherlands
RP McFadgen, B (corresponding author), Vrije Univ Amsterdam, Inst Environm Studies IVM, De Boelelaan 1085, NL-1081 HV Amsterdam, Netherlands.
EM belinda.mcfadgen@vu.nl; dave.huitema@vu.nl
RI ; Huitema, Dave/L-1343-2013
OI Huitema, D./0000-0002-0139-3913; Huitema, Dave/0000-0001-8565-3200
FU Dutch government's Knowledge for Climate programme
FX The authors wish to thank the Dutch government's Knowledge for Climate
   programme, which funded this research.
CR [Anonymous], General Economic History
   [Anonymous], 1987, Rational ecology: Environmental and political economy
   [Anonymous], 2000, DEWEY ON DEMOCRACY
   [Anonymous], 2007, The Honest Broker: Making Sense of Science in Policy and Politics
   [Anonymous], 2010, ECOL SOC
   [Anonymous], 2011, Climate Governance at the Crossroads: Experimenting with a Global Response
   Ansell CK, 2016, ECOL ECON, V130, P64, DOI 10.1016/j.ecolecon.2016.05.016
   Armitage D, 2008, GLOBAL ENVIRON CHANG, V18, P86, DOI 10.1016/j.gloenvcha.2007.07.002
   Baird J, 2014, GLOBAL ENVIRON CHANG, V27, P51, DOI 10.1016/j.gloenvcha.2014.04.019
   BENNETT CJ, 1992, POLICY SCI, V25, P275, DOI 10.1007/BF00138786
   Berkhout F, 2010, ENVIRON SCI POLICY, V13, P261, DOI 10.1016/j.envsci.2010.03.010
   Bos JJ, 2012, TECHNOL FORECAST SOC, V79, P1340, DOI 10.1016/j.techfore.2012.04.006
   Broto VC, 2013, GLOBAL ENVIRON CHANG, V23, P92, DOI 10.1016/j.gloenvcha.2012.07.005
   CAMPBELL DT, 1969, AM PSYCHOL, V24, P409, DOI 10.1037/h0027982
   Checkel JT, 2001, INT ORGAN, V55, P553, DOI 10.1162/00208180152507551
   Dunn W.H., 1998, The Experimenting Society: Essays in Honor of Donald T
   Farrelly M, 2011, GLOBAL ENVIRON CHANG, V21, P721, DOI 10.1016/j.gloenvcha.2011.01.007
   Fischer F., 1995, EVALUATING PUBLIC PO
   Funtowicz S. O., 1990, Uncertainty and quality in science for policy, P115, DOI [DOI 10.1007/978-94-009-0621-110, DOI 10.1007/978-94-009-0621-1_3, 10.1007/978-94-009-0621-110]
   Gerlak AK, 2011, J PUBL ADM RES THEOR, V21, P619, DOI 10.1093/jopart/muq089
   Greenberg D., 2003, Social experimentation and public policymaking
   Haug C, 2011, TECHNOL FORECAST SOC, V78, P968, DOI 10.1016/j.techfore.2010.12.001
   Heikkila T, 2013, POLICY STUD J, V41, P484, DOI 10.1111/psj.12026
   Huitema D, 2016, ECOL SOC, V21, DOI 10.5751/ES-08797-210337
   Huitema D, 2014, POLITICS OF RIVER BASIN ORGANISATIONS: COALITIONS, INSTITUTIONAL DESIGN CHOICES AND CONSEQUENCES, P1
   Huitema D, 2009, ECOL SOC, V14
   Kemp R, 1998, TECHNOL ANAL STRATEG, V10, P175, DOI 10.1080/09537329808524310
   Leach WD, 2014, J PUBL ADM RES THEOR, V24, P591, DOI 10.1093/jopart/mut011
   Lee K.N., 1999, ECOL SOC, P3
   LINDBLOM CE, 1959, PUBLIC ADMIN REV, V19, P79, DOI 10.2307/973677
   Massey E., 2012, REG ENV CHANG
   McFadgen B., 2016, J ENV PLAN MANAG
   McFadgen B., 2017, POLICY SCI, P1
   Millo Y., 2006, SCI PUBL POLICY, V33, P179, DOI [10.3152/147154306781779046, DOI 10.3152/147154306781779046]
   Mintrom M, 2009, POLICY STUD J, V37, P649, DOI 10.1111/j.1541-0072.2009.00329.x
   Mostert E, 2007, ECOL SOC, V12
   Munaretto S, 2012, ECOL SOC, V17, DOI 10.5751/ES-04772-170219
   Muro M, 2012, ECOL SOC, V17, DOI 10.5751/ES-04476-170103
   Newig J, 2010, ECOL SOC, V15
   Ostrom E, 2005, UNDERSTANDING INSTITUTIONAL DIVERSITY, P1
   Owens S, 2004, ENVIRON PLANN A, V36, P1943, DOI 10.1068/a36281
   Pahl-Wostl C., 2008, Ecology and Society, V13
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Rodela R, 2012, ECOL ECON, V77, P16, DOI 10.1016/j.ecolecon.2012.02.032
   SABATIER PA, 1987, KNOWLEDGE, V8, P649, DOI 10.1177/0164025987008004005
   Sanderson I, 2002, PUBLIC ADMIN, V80, P1, DOI 10.1111/1467-9299.00292
   Schusler TM, 2003, SOC NATUR RESOUR, V16, P309, DOI [10.1080/08941920309158, 10.1080/08941920390178874]
   Thomas Webler., 1995, ENVIRON IMPACT ASSES, V15, P443, DOI DOI 10.1016/0195-9255(95)00043-E
   Van der Heijden J., 2014, J ENVIRON POL PLAN, P17
   Vedung E., 1997, PUBLIC POLICY PROGRA
   Voss JP, 2014, ENVIRON POLIT, V23, P735, DOI 10.1080/09644016.2014.923625
   WALTERS CJ, 1990, ECOLOGY, V71, P2060, DOI 10.2307/1938620
NR 52
TC 17
Z9 17
U1 3
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD SEP
PY 2017
VL 9
IS 9
AR 648
DI 10.3390/w9090648
PG 22
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Water Resources
GA FH9WM
UT WOS:000411567200022
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Westskog, H
   Hovelsrud, GK
   Sundqvist, G
AF Westskog, Hege
   Hovelsrud, Grete K.
   Sundqvist, Goran
TI How to Make Local Context Matter in National Advice: Towards Adaptive
   Comanagement in Norwegian Climate Adaptation
SO WEATHER CLIMATE AND SOCIETY
LA English
DT Article
ID VULNERABILITY ANALYSIS; GOVERNANCE; FRAMEWORK; CAPACITY; BARRIERS
AB Drawing on case studies in 12 Norwegian municipalities, this paper investigates how local context matters for developing national climate adaptation policies that are applicable at the municipal level. Moreover, it explicates which factors constitute this context and how these factors vary across the case municipalities. National climate adaptation policy in Norway can currently be characterized as top down, providing standardized requirements and advice to municipalities. However, Norwegian municipalities vary greatly with respect to physical conditions, organizational resources, and societal needs. They are autonomous to a great extent and are almost solely responsible for developing climate policy and planning within their own territories. Therefore, municipalities adapt national policies to their own context, reflecting local physiographic, organizational, and resource challenges, but these local translations are not fully recognized by national and sectoral actors. This paper underscores that the significant variation in contextual factors between municipalities is not sufficiently addressed and understood by national and sectoral governmental authorities. With the identified variation of the contextual factors across the case municipalities, an adaptive comanagement strategy within a multilevel governance system is suggested as a suitable framework to ensure a proactive approach to local adaptation, that is, mutual understanding and better cooperation between the national and local levels.
C1 [Westskog, Hege; Hovelsrud, Grete K.] Ctr Int Climate & Environm Res Oslo, Oslo, Norway.
   [Hovelsrud, Grete K.] Nord Univ, Fac Social Sci, Bodo, Norway.
   [Sundqvist, Goran] Univ Oslo, TIK Ctr Technol Innovat & Culture, Oslo, Norway.
C3 Nord University; University of Oslo
RP Westskog, H (corresponding author), Ctr Int Climate & Environm Res Oslo, Oslo, Norway.
EM hege.westskog@cicero.oslo.no
OI Westskog, Hege/0000-0003-4943-8874
FU Research Council of Norway [207622]; Academy of Finland (AKA) [207622]
   Funding Source: Academy of Finland (AKA)
FX We wish to thank Christian Bjornaes, communication director at Centre
   for International Climate and Environmental Research (CICERO) Oslo, for
   facilitating the process with the county governor of Vestfold and
   contributing with his skills to the interviews with the municipalities
   in Vestfold. Funding from the Research Council of Norway, Grant Number
   207622, is gratefully acknowledged.
CR Adger W. N., 1999, Mitig Adapt Strateg Glob Change, V4, P253, DOI [10.1023/A:1009601904210, DOI 10.1023/A:1009601904210]
   Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   Armitage D., 2007, Adaptive co-management: collaboration, learning and multi-level governance
   Armitage D., 2003, NAVIGATING SOCIAL EC
   Armitage D, 2011, GLOBAL ENVIRON CHANG, V21, P995, DOI 10.1016/j.gloenvcha.2011.04.006
   Armitage DR, 2009, FRONT ECOL ENVIRON, V7, P95, DOI 10.1890/070089
   Baird J, 2014, GLOBAL ENVIRON CHANG, V27, P51, DOI 10.1016/j.gloenvcha.2014.04.019
   Berkes F., 2010, Etudes/Inuit Studies, V34, P109, DOI DOI 10.7202/045407AR
   Bown N., 2013, Contested forms of governance in marine protected areas: A study of co-management and adaptive co-management
   Bulkeley H, 2005, POLIT GEOGR, V24, P875, DOI 10.1016/j.polgeo.2005.07.002
   Bulkeley H, 2005, ENVIRON POLIT, V14, P42, DOI 10.1080/0964401042000310178
   Dannevig H, 2013, ENVIRON PLANN C, V31, P490, DOI 10.1068/c1152
   Dannevig H, 2012, LOCAL ENVIRON, V17, P597, DOI 10.1080/13549839.2012.678317
   Dessai S, 2004, CLIM POLICY, V4, P107
   Elzinga A., 2008, Handbook of transdisciplinary research, P345, DOI [DOI 10.1007/978-1-4020-6699-322, DOI 10.1007/978-1-4020-6699-3_22]
   Fankhauser S, 1999, ECOL ECON, V30, P67, DOI 10.1016/S0921-8009(98)00117-7
   Fidel M, 2014, POLAR GEOGR, V37, P48, DOI 10.1080/1088937X.2013.879613
   Fitchett A., 2014, Urban Forum, DOI [DOI 10.1007/S12132-013-9215-Z, 10.1007/s12132-013-9215-z]
   Ford JD, 2004, ARCTIC, V57, P389, DOI 10.14430/arctic516
   Gunderson L. H., 2002, Panarchy: understanding transformations in human and natural systems
   Gustavsson E, 2009, ENVIRON PLANN C, V27, P59, DOI 10.1068/c07109j
   Heiberg E., 2012, ANSVARSFORDELING MEL
   Hovelsrud G. K, 2013, CLIMATIC CHANGE 2013
   Hovelsrud G. K, 2016, LOV SIKRING MOT ERST
   Hovelsrud GK, 2010, COMMUNITY ADAPTATION AND VULNERABILITY IN ARCTIC REGIONS, P1, DOI 10.1007/978-90-481-9174-1
   Hovelsrud GK, 2011, AMBIO, V40, P100, DOI 10.1007/s13280-011-0219-4
   Keskitalo ECH, 2011, REG ENVIRON CHANGE, V11, P579, DOI 10.1007/s10113-010-0182-9
   Kirchhoff Christine J., 2016, Water Resources Research, V52, P2951, DOI 10.1002/2015WR018431
   Kvalvik I, 2011, ACTA AGR SCAND B-S P, V61, P27, DOI 10.1080/09064710.2011.627376
   Lempert R, 2004, CLIMATIC CHANGE, V65, P1, DOI 10.1023/B:CLIM.0000037561.75281.b3
   Lynch AH, 2010, WEATHER CLIM SOC, V2, P311, DOI 10.1175/2010WCAS1049.1
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Norwegian Ministry of Environment, 2010, 201010 NOU MIN ENV
   NOU, 2010, 33 NOU
   Olsson P, 2004, ENVIRON MANAGE, V34, P75, DOI 10.1007/s00267-003-0101-7
   Plummer R, 2013, SUSTAINABILITY-BASEL, V5, P629, DOI 10.3390/su5020629
   Pohl C, 2011, FUTURES, V43, P618, DOI 10.1016/j.futures.2011.03.001
   Preston BL, 2015, MITIG ADAPT STRAT GL, V20, P467, DOI 10.1007/s11027-013-9503-x
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Schneider S.H., 2002, CLIMATE CHANGE POLIC
   Sellers JM, 2007, GOVERNANCE, V20, P609, DOI 10.1111/j.1468-0491.2007.00374.x
   Smit B, 2010, COMMUNITY ADAPTATION AND VULNERABILITY IN ARCTIC REGIONS, P1, DOI 10.1007/978-90-481-9174-1_1
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Tompkins EL, 2005, ENVIRON SCI POLICY, V8, P562, DOI 10.1016/j.envsci.2005.06.012
   Tornblad SH, 2014, J ENVIRON POL PLAN, V16, P37, DOI 10.1080/1523908X.2013.817946
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8080, DOI 10.1073/pnas.1231334100
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Vestfold Fylkeskommune, 2016, VESTF
   Watson A, 2013, ENVIRON MANAGE, V52, P1085, DOI 10.1007/s00267-013-0111-z
   West JJ, 2010, ARCTIC, V63, P338
NR 50
TC 25
Z9 26
U1 3
U2 13
PU AMER METEOROLOGICAL SOC
PI BOSTON
PA 45 BEACON ST, BOSTON, MA 02108-3693, UNITED STATES
SN 1948-8327
EI 1948-8335
J9 WEATHER CLIM SOC
JI Weather Clim. Soc.
PD APR
PY 2017
VL 9
IS 2
BP 267
EP 283
DI 10.1175/WCAS-D-16-0063.1
PG 17
WC Environmental Studies; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA ET4YM
UT WOS:000400291000012
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Aldous, A
   Fitzsimons, J
   Richter, B
   Bach, L
AF Aldous, Allison
   Fitzsimons, James
   Richter, Brian
   Bach, Leslie
TI Droughts, floods and freshwater ecosystems: evaluating climate change
   impacts and developing adaptation strategies
SO MARINE AND FRESHWATER RESEARCH
LA English
DT Article
DE climate adaptation strategies; coupled climate-hydrology models; dam
   reoperation; environmental flows; groundwater; groundwater-dependent
   ecosystems; land management; surface water
ID BIODIVERSITY; GROUNDWATER; STREAMFLOW; SENSITIVITY; MANAGEMENT;
   HYDROLOGY; SHIFTS; BASIN; DAMS
AB Climate change is expected to have significant impacts on hydrologic regimes and freshwater ecosystems, and yet few basins have adequate numerical models to guide the development of freshwater climate adaptation strategies. Such strategies can build on existing freshwater conservation activities, and incorporate predicted climate change impacts. We illustrate this concept with three case studies. In the Upper Klamath Basin of the western USA, a shift in land management practices would buffer this landscape from a declining snowpack. In the Murray-Darling Basin of south-eastern Australia, identifying the requirements of flood-dependent natural values would better inform the delivery of environmental water in response to reduced runoff and less water. In the Savannah Basin of the south-eastern USA, dam managers are considering technological and engineering upgrades in response to more severe floods and droughts, which would also improve the implementation of recommended environmental flows. Even though the three case studies are in different landscapes, they all contain significant freshwater biodiversity values. These values are threatened by water allocation problems that will be exacerbated by climate change, and yet all provide opportunities for the development of effective climate adaptation strategies.
C1 [Aldous, Allison; Bach, Leslie] Nature Conservancy, Portland, OR 97214 USA.
   [Fitzsimons, James] Nature Conservancy, Carlton, Vic 3053, Australia.
   [Fitzsimons, James] Deakin Univ, Sch Life & Environm Sci, Burwood, Vic 3125, Australia.
   [Richter, Brian] Nature Conservancy, Charlottesville, VA 22901 USA.
C3 Nature Conservancy; Nature Conservancy; Deakin University; Nature
   Conservancy
RP Aldous, A (corresponding author), Nature Conservancy, 821 SE 14th Ave, Portland, OR 97214 USA.
EM aaldous@tnc.org
RI Fitzsimons, James/W-2497-2019; Richter, Brian/IWK-6306-2023
OI Fitzsimons, James/0000-0003-4277-8040
CR Adam JC, 2009, HYDROL PROCESS, V23, P962, DOI 10.1002/hyp.7201
   [Anonymous], 2008, SRA Report 1: A Report on the Ecological Health of Rivers in the MurrayDarling Basin, 20042007
   [Anonymous], 2006, RIV RED GUM FOR INV, DOI DOI 10.1016/j.biocon.2005.12.032
   [Anonymous], ECOLOGICAL MANAGEMEN
   Ballinger A, 2006, ADV ECOL RES, V39, P85, DOI 10.1016/S0065-2504(06)39005-8
   Bates B.C., 2008, LINKING CLIMATE CHAN
   Brook BW, 2008, TRENDS ECOL EVOL, V23, P453, DOI 10.1016/j.tree.2008.03.011
   Brown J, 2011, FRONT ECOL ENVIRON, V9, P97, DOI 10.1890/090108
   CARLSON JR, 1993, ENV RES KLAMATH BASI, P197
   Chiew F.H., 2006, P 30 HYDR WAT RES S, P643
   Döll P, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/035006
   *DSE, 2008, NO REG SUST WAT STRA
   Fitzsimons James A., 2006, Proceedings of the Royal Society of Victoria, V118, P75
   Folke C, 2004, ANNU REV ECOL EVOL S, V35, P557, DOI 10.1146/annurev.ecolsys.35.021103.105711
   Gannett MW, 2007, 20075050 US GEOL SUR, DOI [10.3133/sir20075050, DOI 10.3133/SIR20075050]
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Jha M, 2006, J AM WATER RESOUR AS, V42, P997, DOI 10.1111/j.1752-1688.2006.tb04510.x
   Jones MJ, 2008, FISHERIES MANAG ECOL, V15, P71, DOI 10.1111/j.1365-2400.2007.00580.x
   Jones R.N., 2005, Estimating the Impacts of Climate Change on Victorias Runoff Using a Hydrological Sensitivity Model
   Kingsford RT, 2000, AUSTRAL ECOL, V25, P109, DOI 10.1046/j.1442-9993.2000.01036.x
   *MDBC, 2006, CHOW FLOODPL LINDS W
   Milly PCD, 2005, NATURE, V438, P347, DOI 10.1038/nature04312
   *NAT RES COUNC, 2008, HYDRL EFF CHANG FOR
   Neff R, 2000, CLIMATE RES, V14, P207, DOI 10.3354/cr014207
   Nolin AW, 2006, J HYDROMETEOROL, V7, P1164, DOI 10.1175/JHM543.1
   PALMER MA, 2008, PRELIMINARY REV ADAP, P1
   Pittock Jamie, 2008, Biodiversity (Ottawa), V9, P30
   Poff N.L., 2002, AQUATIC ECOSYSTEMS G
   Poff NL, 2007, P NATL ACAD SCI USA, V104, P5732, DOI 10.1073/pnas.0609812104
   Preston BL, 2008, ATMOS SCI LETT, V9, P202, DOI 10.1002/asl.188
   Richter BD, 2006, RIVER RES APPL, V22, P297, DOI 10.1002/rra.892
   Robertson Hugh A., 2005, Proceedings of the Royal Society of Victoria, V117, P139
   Rodell M, 2009, NATURE, V460, P999, DOI 10.1038/nature08238
   Scheffer M, 2001, NATURE, V413, P591, DOI 10.1038/35098000
   Schneeberger C, 2003, J HYDROL, V282, P145, DOI 10.1016/S0022-1694(03)00260-9
   Stewart G, 2002, WATER SCI TECHNOL, V45, P217, DOI 10.2166/wst.2002.0398
   Stewart IT, 2005, J CLIMATE, V18, P1136, DOI 10.1175/JCLI3321.1
   Tague C, 2008, CLIMATIC CHANGE, V86, P189, DOI 10.1007/s10584-007-9294-8
   US Geologic Survey, 2009, NAT WAT INF SYST NWI
   van Roosmalen L, 2007, VADOSE ZONE J, V6, P554, DOI 10.2136/vzj2006.0093
   VEAC, 2008, RIV RED GUM FOR INV
   *VEAC, 2008, ID FLOOD DEP NAT VAL
   *VEAC, 2007, RIV RED GUM IN PRESS
   Xu CY, 2005, ADV ATMOS SCI, V22, P789, DOI 10.1007/BF02918679
NR 44
TC 72
Z9 81
U1 0
U2 129
PU CSIRO PUBLISHING
PI CLAYTON
PA UNIPARK, BLDG 1, LEVEL 1, 195 WELLINGTON RD, LOCKED BAG 10, CLAYTON, VIC
   3168, AUSTRALIA
SN 1323-1650
EI 1448-6059
J9 MAR FRESHWATER RES
JI Mar. Freshw. Res.
PY 2011
VL 62
IS 3
SI SI
BP 223
EP 231
DI 10.1071/MF09285
PG 9
WC Fisheries; Limnology; Marine & Freshwater Biology; Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Fisheries; Marine & Freshwater Biology; Oceanography
GA 737KE
UT WOS:000288566900002
DA 2025-01-10
ER

PT J
AU Nikologianni, A
   Moore, K
   Larkham, PJ
AF Nikologianni, Anastasia
   Moore, Kathryn
   Larkham, Peter J.
TI Climate Emergency Adaptation and Sustainable Management Strategies in
   Rural and Agricultural Landscapes
SO INFRASTRUCTURES
LA English
DT Article
DE climate adaptation; rural infrastructure; policy; governance; water
   management; agriculture; landscape; climate emergency; crisis
AB This paper discusses the way in which climate emergency-related strategies and the concepts of climate adaptation, sustainability and governance are being introduced into rural and agricultural landscapes. To investigate environmental impacts on climate change, it uses examples from the `Landscape Observatory' (Catalonia) and the `Room for the River' (The Netherlands) landscape programmes. Noordwaard is the largest rural project of the Room for the River programme, dealing with agricultural land, farming and nature reserves at a strategic scale. It demonstrates the potential and significance of addressing the sea rising water levels by creating landscape climate adaptation projects by introducing the ideas of landscape, low carbon, ecosystem services and governance as vital aspects of rural infrastructure, which underpin the ways in which agricultural land and water are managed. The Landscape Observatory has had a significant impact on the development of landscape policies in Catalonia and has been influential in a global level. Focusing on Llucanes and the establishment of a Landscape Charter protecting the agricultural land and examining the natural area of La Cerdanya in Pyrenees, the research extracts best practices in policy and legislation as well as participatory methods on climate and landscape awareness. This research concludes that a communication strategy strongly supported by policies, legislation and governance structures, in conjunction with a wider understanding of the role of landscape, results in significantly improved responses to deal with the challenges of the climate crisis in rural and agricultural areas.
C1 [Nikologianni, Anastasia; Moore, Kathryn] Birmingham City Univ, Sch Architecture & Design, City Ctr Campus, Birmingham B4 7BD, W Midlands, England.
   [Larkham, Peter J.] Birmingham City Univ, Sch Engn & Built Environm, City Ctr Campus, Birmingham B4 7BD, W Midlands, England.
C3 Birmingham City University; Birmingham City University
RP Nikologianni, A (corresponding author), Birmingham City Univ, Sch Architecture & Design, City Ctr Campus, Birmingham B4 7BD, W Midlands, England.
EM anastasia.nikologianni@bcu.ac.uk; kathryn.moore@bcu.ac.uk;
   peter.larkham@bcu.ac.uk
OI Moore, Kathryn/0000-0002-0792-1537; Nikologianni, Dr
   Anastasia/0000-0002-2234-4707
FU EIT Climate-KIC
FX This research was partly funded by EIT Climate-KIC.
CR Altieri MA, 2017, CLIMATIC CHANGE, V140, P33, DOI 10.1007/s10584-013-0909-y
   [Anonymous], 2018, GLOBAL WARMING 15 C
   Cicala S., 2020, EXPECTED HLTH EFFECT
   Clapp J, 2015, SUSTAIN SCI, V10, P305, DOI 10.1007/s11625-014-0278-0
   Dutheil F, 2020, ENVIRON POLLUT, V263, DOI 10.1016/j.envpol.2020.114466
   Fairclough G, 2018, ROUTLEDGE HDB LANDSC
   Gossop C, 2011, CITIES, V28, P495, DOI 10.1016/j.cities.2011.09.003
   Hanna EG, 2011, ASIA-PAC J PUBLIC HE, V23, p105S, DOI 10.1177/1010539510391459
   Lawrence G., 2007, Supermarkets and agri-food supply chains: transformations in the production and consumption of foods, P1
   LILA, 2019, 2019 WINN INFR CAT N
   Nikologianni A., 2017, THESIS
   Nikologianni A, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11041024
   Nogue J., 2016, 03 LANDSC OBS CAT, V03, P142
   Sala P., 2017, MAPA PAISATGE TRANSF
   Torres M, 2011, CITIES, V28, P576, DOI 10.1016/j.cities.2011.06.005
   Van Alphen S., 2020, ADAPTIVE STRATEGIES, DOI 10.1007/978-3-030-00268-8
   van den Brink M. A., 2009, RIJKSWATERSTAAT HORN, DOI [10.1103/PhysRevLett.87.017901, DOI 10.1103/PHYSREVLETT.87.017901]
NR 17
TC 1
Z9 1
U1 0
U2 23
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2412-3811
J9 INFRASTRUCTURES-BASE
JI Infrastructures-Basel
PD NOV
PY 2020
VL 5
IS 11
AR 97
DI 10.3390/infrastructures5110097
PG 13
WC Construction & Building Technology; Engineering, Civil; Transportation
   Science & Technology
WE Emerging Sources Citation Index (ESCI)
SC Construction & Building Technology; Engineering; Transportation
GA QP2CH
UT WOS:000623643000009
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Braunschweiger, D
   Ohmura, T
   Schweier, J
   Olschewski, R
   Schulz, T
AF Braunschweiger, Dominik
   Ohmura, Tamaki
   Schweier, Janine
   Olschewski, Roland
   Schulz, Tobias
TI Preferences for proactive and reactive climate-adaptive forest
   management and the role of public financial support
SO FOREST POLICY AND ECONOMICS
LA English
DT Article
DE Choice experiment; Latent class analysis; Proactive interventions;
   Reactive interventions; Restoration; Transition
ID TO-NATURE SILVICULTURE; EUROPEAN FORESTS; ADAPTATION; RESILIENCE;
   DROUGHT; OWNERS; IMPACT
AB The impacts of climate change threaten forest ecosystems and the services they provide. Policies and measures to make forests more resilient to climate-change-induced disturbances are needed, but the success of such efforts depends on their acceptance among forest owners and managers. Based on a discrete choice experiment survey among Swiss forest owners and managers in the canton of Bern, we analysed whether respondents prefer (i) proactive over reactive interventions, (ii) advanced/natural regeneration over plantings, (iii) native over nonnative tree species, and (iv) the role governmental payment schemes play in these decisions. About one-third of the respondents belong to the class of forest managers and owners that are open to a transition strategy including proactive interventions and non-native tree species. Two-thirds of the forest owners and managers prefer a reactive restoration approach after disturbances and management that relies on native tree species. The amount of financial support plays a decisive role in the willingness of most respondents to accept adaptation measures. These results confirm the feasibility of diversifying the policy support toolbox to enable more proactive climate-adaptive forest management.
C1 [Braunschweiger, Dominik; Schweier, Janine; Olschewski, Roland; Schulz, Tobias] Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland.
   [Ohmura, Tamaki] Univ Zurich, Dept Evolutionary Biol & Environm Studies, Zurich, Switzerland.
C3 Swiss Federal Institutes of Technology Domain; Swiss Federal Institute
   for Forest, Snow & Landscape Research; University of Zurich
RP Braunschweiger, D (corresponding author), Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland.
EM dominik.braunschweiger@wsl.ch; tamaki.ohmura@uzh.ch;
   janine.schweier@wsl.ch; roland.olschewski@wsl.ch; tobias.schulz@wsl.ch
RI Schulz, Tobias/E-8129-2014
OI Schweier, Janine/0000-0003-4435-3089
FU Wald-und Holzforschungsforderung Schweiz (WHFF-CH)
   [01.0101.PZ/0F8511A1F/2021.13]; Canton of Aargau; Canton of Bern
FX We thank the Wald-und Holzforschungsforderung Schweiz (WHFF-CH, grant
   number 01.0101.PZ/0F8511A1F/2021.13) and the Cantons of Aargau and Bern
   for funding. We also acknowledge valuable input and feedback from the
   project's advisory board and the cantonal forest owner associations. Our
   special gratitude also goes to Nial Perry (WSL) for his methodological
   assistance in conducting the decision tree analysis.
CR Alberini A, 2007, ECON NON-MARK GOOD, V8, P203
   Albrich K, 2023, FORESTRY, V96, P399, DOI 10.1093/forestry/cpac022
   [Anonymous], 2020, State of Europes Forests 2020
   BAFU, 2008, Sturmschaden-Handbuch. Vollzugshilfe fur die Bewaltigung von Sturmschadenereignissen von nationaler Bedeutung Wald und Holz
   Bauhus J., 2013, Managing Forests as Complex Adaptive Systems: Building Resilience to the Challenge of Global Change, P187
   Bieling C, 2004, EUR J FOR RES, V123, P293, DOI 10.1007/s10342-004-0042-6
   Blattert C, 2022, FOREST POLICY ECON, V136, DOI 10.1016/j.forpol.2022.102689
   Blennow K, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abc2fa
   Blennow K, 2012, FOREST POLICY ECON, V24, P41, DOI 10.1016/j.forpol.2011.04.005
   Blewitt ME, 2008, NAT GENET, V40, P663, DOI 10.1038/ng.142
   Bone C, 2016, LAND USE POLICY, V52, P430, DOI 10.1016/j.landusepol.2016.01.003
   Brang P., 2016, Wald im Klimawandel: Grundlagen fur Adaptationsstrategien, P341
   Brang P., 2022, Wald und Holz, V9, P15
   Brang P, 2014, FORESTRY, V87, P492, DOI 10.1093/forestry/cpu018
   Büntgen U, 2021, NAT GEOSCI, V14, P190, DOI 10.1038/s41561-021-00698-0
   Canadian Forest Service, 2024, Forest glossary Online post
   Chrzan K., 2000, Sawtooth Research Paper Series
   Cienciala E, 2024, CARBON BAL MANAGE, V19, DOI 10.1186/s13021-023-00246-w
   Claas T., 2023, Forderprogramm Anreizschaffung
   D'Amato A. W., 2023, BOREAL FORESTS FACE, P359, DOI [DOI 10.1007/978-3-031-15988-6_13, 10.1007/978-3-031-15988-613, 10.1007/978-3-031-15988-6_13 10.1007/978-3-031-15988-6_13]
   de Cárcer PS, 2021, CURR FOR REP, V7, P167, DOI 10.1007/s40725-021-00144-9
   EC, 2021, EU Biodiversity Strategy for 2030-Bringing Nature Back into our Lives
   EC, 2021, New EU Forest Strategy for 2030
   Eriksson L, 2022, FOREST POLICY ECON, V140, DOI 10.1016/j.forpol.2022.102751
   Ficko A, 2019, FOREST POLICY ECON, V99, P21, DOI 10.1016/j.forpol.2017.09.010
   Glatthorn J., 2023, Schweizerische Zeitschrift Fur Forstwesen, V174, P64, DOI [10.3188/szf.2023.0064, DOI 10.3188/SZF.2023.0064]
   Hess S., 2024, Handbook of Choice Modelling, P372
   Holmes TP, 2017, ECON NON-MARK GOOD, V13, P133, DOI 10.1007/978-94-007-7104-8_5
   Jandl R, 2018, FORESTS, V9, DOI 10.3390/f9100592
   Johnston RJ, 2017, J ASSOC ENVIRON RESO, V4, P319, DOI 10.1086/691697
   Larsen J.B., 2022, Closer-to-nature forest management. From Science to Policy 12, V12, DOI [DOI 10.36333/FS12, 10.36333/fs12]
   Lindner M, 2014, J ENVIRON MANAGE, V146, P69, DOI 10.1016/j.jenvman.2014.07.030
   Louviere JJ, 2001, NEW HOR ENV ECO, P13
   Mason WL, 2022, FORESTRY, V95, P1, DOI 10.1093/forestry/cpab038
   Messier C, 2022, CONSERV LETT, V15, DOI 10.1111/conl.12829
   Mingers J., 1989, Machine Learning, V3, P319, DOI 10.1007/BF00116837
   Moser S, 2019, CLIMATIC CHANGE, V153, P21, DOI 10.1007/s10584-018-2358-0
   Mostegl NM, 2019, FOREST POLICY ECON, V99, P83, DOI 10.1016/j.forpol.2017.10.001
   Nikinmaa L, 2020, CURR FOR REP, V6, P61, DOI 10.1007/s40725-020-00110-x
   Owen G, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102071
   Palik BJ, 2022, ECOSPHERE, V13, DOI 10.1002/ecs2.4260
   Persson J, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12072659
   Pörtner HO, 2023, SCIENCE, V380, DOI 10.1126/science.abl4881
   Puettmann KJ, 2021, J FOREST, V119, P422, DOI 10.1093/jofore/fvab014
   Puettmann KJ, 2015, FOR ECOSYST, V2, DOI 10.1186/s40663-015-0031-x
   Raetz P., 2004, Erkenntnisse aus der Sturmschadenbewaltigung. Synthese des Lothar Grundlagenprogramms (367; Schriftenreihe Umwelt)
   Rathgeb Ursina, 2020, Schweizerische Zeitschrift fur Forstwesen, V171, P249, DOI 10.3188/szf.2020.0249
   Rigling Andreas, 2020, Schweizerische Zeitschrift fur Forstwesen, V171, P242, DOI 10.3188/szf.2020.0242
   Rissman AR, 2018, FRONT ECOL ENVIRON, V16, P454, DOI 10.1002/fee.1818
   Roitsch D, 2023, FOREST POLICY ECON, V154, DOI 10.1016/j.forpol.2023.103035
   Sandström C, 2020, FOREST POLICY ECON, V111, DOI 10.1016/j.forpol.2019.102051
   Santopuoli G, 2021, CAN J FOREST RES, V51, P1741, DOI 10.1139/cjfr-2020-0166
   Schuldt B, 2020, BASIC APPL ECOL, V45, P86, DOI 10.1016/j.baae.2020.04.003
   Schutz J.-P., 2022, Wald und Holz, V8, P25
   Schütz JP, 1999, FORESTRY, V72, P359, DOI 10.1093/forestry/72.4.359
   Schweizerischer Bundesrat, 2022, Anpassung des Waldes an den Klimawandel Bericht des Bundesrats in Erfullung der Motion 19.4177 Engler (Heche) vom 25.09.2019 und des Postulates 20.3750 Vara vom 18.06.2020
   Seidl R, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2202190119
   Seidl R, 2016, J APPL ECOL, V53, P120, DOI 10.1111/1365-2664.12511
   Seidl R, 2014, NAT CLIM CHANGE, V4, P806, DOI [10.1038/nclimate2318, 10.1038/NCLIMATE2318]
   Seidl R, 2013, J ENVIRON MANAGE, V114, P461, DOI 10.1016/j.jenvman.2012.09.028
   Senf C, 2021, NAT SUSTAIN, V4, P63, DOI 10.1038/s41893-020-00609-y
   Slavec A, 2023, FOREST POLICY ECON, V157, DOI 10.1016/j.forpol.2023.103074
   Sousa-Silva R, 2018, FOREST POLICY ECON, V90, P22, DOI 10.1016/j.forpol.2018.01.004
   Stadelmann G, 2013, FOREST ECOL MANAG, V305, P273, DOI 10.1016/j.foreco.2013.06.003
   Stein BA, 2013, FRONT ECOL ENVIRON, V11, P502, DOI 10.1890/120277
   Swait J, 2007, ECON NON-MARK GOOD, V8, P229
   Thom D, 2016, BIOL REV, V91, P760, DOI 10.1111/brv.12193
   Thomann E, 2018, J PUBL ADM RES THEOR, V28, P583, DOI 10.1093/jopart/muy024
   Train KE, 2009, DISCRETE CHOICE METHODS WITH SIMULATION, 2ND EDITION, P1, DOI 10.1017/CBO9780511805271
   Unterberger C, 2021, ECOL ECON, V180, DOI 10.1016/j.ecolecon.2020.106866
   Villamayor-Tomas S, 2019, LAND USE POLICY, V84, P200, DOI 10.1016/j.landusepol.2019.03.006
   Vinceti B, 2020, EUR J FOREST RES, V139, P1107, DOI 10.1007/s10342-020-01311-6
NR 72
TC 0
Z9 0
U1 4
U2 4
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1389-9341
EI 1872-7050
J9 FOREST POLICY ECON
JI Forest Policy Econ.
PD DEC
PY 2024
VL 169
AR 103348
DI 10.1016/j.forpol.2024.103348
EA OCT 2024
PG 12
WC Economics; Environmental Studies; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Business & Economics; Environmental Sciences & Ecology; Forestry
GA I5W1G
UT WOS:001330950600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Stache, E
   Hinterleitner, J
   Ottelé, M
   Jonkers, HM
AF Stache (Eva), E.
   Hinterleitner (Jutta), J.
   Ottele (Marc), M.
   Jonkers (Henk), H. M.
TI Implementation of a microclimate design model in the early design of new
   building projects - Case study Ecohof Noorderveer in the Netherlands
SO URBAN CLIMATE
LA English
DT Article
DE Microclimate design model; Ecosystem services; Ecosystem functions;
   Climate adaptation; Research by design; Implementation process;
   Stakeholder's participation
ID URBAN HEAT-ISLAND; ECOSYSTEM SERVICES; ENERGY-CONSUMPTION; PERFORMANCE
AB Given the ongoing global urbanization and the rise of heat, flooding, and drought in cities, the integration of climate adaptive measures based on "ecosystem functions and services" becomes imperative in design. This study details the implementation process of a microclimate design model in the design and retrofitting of the housing project Ecohof Noorderveer in Wormerveer, the Netherlands. The model, which quantifies local urban heat and mitigating measures through ecosystem functionalities, was incorporated into the program of requirements. The design process followed a research-by-design trajectory, involving iterative creative collaboration among all stakeholders, including future residents, the municipality, the water board, and the architect. The research employed the CFIR method to compare anticipated implementation outcomes with actual results. The findings suggest that introducing the microclimate design model into the program of requirements proved beneficial for the implementation process in the early design stage. The research-by-design approach was also deemed helpful, contingent on careful involvement of all participants in the knowledge-sharing process. This implementation method demonstrates significant potential for scaling up to standard urban development projects.
C1 [Stache (Eva), E.; Hinterleitner (Jutta), J.; Ottele (Marc), M.; Jonkers (Henk), H. M.] Delft Univ Technol TU Delft, Fac Civil Engn & Geosci, Dept 3MD, Stevinweg 1, NL-2628 CN Delft, Netherlands.
   [Hinterleitner (Jutta), J.] Fac Architecture & Built Environm, Management Built Environm, Julianalaan 134, NL-2628 BL Delft, Netherlands.
C3 Delft University of Technology; Delft University of Technology
RP Stache, E (corresponding author), Delft Univ Technol TU Delft, Fac Civil Engn & Geosci, Dept 3MD, Stevinweg 1, NL-2628 CN Delft, Netherlands.
EM postmaster@stache-architect.nl
RI Ottele, Marc/R-2488-2017
OI Jonkers, Henk/0000-0003-1156-7195
CR [Anonymous], 2013, ValuES: Methods for integrating ecosystem services into policy, planning, and practice
   [Anonymous], 2008, P 10 ANN C PART DES
   Bowen IS, 1926, PHYS REV, V27, P779, DOI 10.1103/PhysRev.27.779
   CBS, 2020, Tijdens hittegolf vooral meer sterfte in langdurige zorg online
   Costanza R, 1997, NATURE, V387, P253, DOI 10.1038/387253a0
   Costanza R, 2020, ECOSYST SERV, V43, DOI 10.1016/j.ecoser.2020.101096
   Cui H, 2022, J HYDROL-REG STUD, V42, DOI 10.1016/j.ejrh.2022.101147
   Dagnachew A., 2021, PBL publication, V4639
   Damschroder LJ, 2022, IMPLEMENT SCI, V17, DOI [10.1186/s13012-021-01181-5, 10.1186/s13012-022-01245-0]
   Damschroder LJ, 2009, IMPLEMENT SCI, V4, DOI 10.1186/1748-5908-4-50
   Fathi-Taperasht A, 2022, ECOL INDIC, V141, DOI 10.1016/j.ecolind.2022.109146
   Fini A, 2022, LANDSCAPE URBAN PLAN, V226, DOI 10.1016/j.landurbplan.2022.104501
   Gold HT, 2022, IMPLEMENT SCI, V17, DOI 10.1186/s13012-021-01172-6
   Grunewald K, 2021, ECOSYST SERV, V49, DOI 10.1016/j.ecoser.2021.101273
   Guattari C, 2018, ENERG BUILDINGS, V158, P605, DOI 10.1016/j.enbuild.2017.10.050
   Haase D, 2022, TREES FOREST PEOPLE, V8, DOI 10.1016/j.tfp.2022.100252
   Hinterleitner J., 2023, Ontwerpen in gebiedsontwikkeling
   Hinterleitner J, 2021, J URBAN DES, V26, P663, DOI 10.1080/13574809.2021.1917986
   Hirano Y, 2012, ENERGY, V37, P371, DOI 10.1016/j.energy.2011.11.018
   IPCC, 2023, Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [DOI 10.59327/IPCC/AR6-9789291691647, 10.59327/IPCC/AR6-9789291691647.001]
   Jha SK, 2022, CURR RES ENVIRON SUS, V4, DOI 10.1016/j.crsust.2021.100121
   Klaic M, 2022, IMPLEMENT SCI, V17, DOI 10.1186/s13012-021-01171-7
   Larsen L, 2004, J AM PLANN ASSOC, V70, P374
   Liu YZ, 2017, ENERG BUILDINGS, V152, P776, DOI 10.1016/j.enbuild.2016.11.019
   Lortie CJ, 2020, FACETS, V5, P642, DOI 10.1139/facets-2020-0021
   Lv PC, 2022, AGR FOREST METEOROL, V326, DOI 10.1016/j.agrformet.2022.109183
   Manso M, 2021, RENEW SUST ENERG REV, V135, DOI 10.1016/j.rser.2020.110111
   Mason SA, 2020, ECOSYST SERV, V46, DOI 10.1016/j.ecoser.2020.101203
   Mills G., 2021, The Urban Heat Island, DOI [10.1016/B978-0-12-815017-7.00001-1, DOI 10.1016/B978-0-12-815017-7.00001-1]
   Mirabi E, 2022, URBAN CLIM, V45, DOI 10.1016/j.uclim.2022.101261
   Moody R, 2021, URBAN FOR URBAN GREE, V66, DOI 10.1016/j.ufug.2021.127403
   Nijhuis S., 2020, RES URBANISM SERIES, V6, P55, DOI DOI 10.7480/RIUS.6.94
   Nur IJ, 2022, CURR RES ENVIRON SUS, V4, DOI 10.1016/j.crsust.2022.100166f
   Orlov A, 2020, GLOBAL ENVIRON CHANG, V63, DOI 10.1016/j.gloenvcha.2020.102087
   Ortiz L, 2022, URBAN CLIM, V41, DOI 10.1016/j.uclim.2021.101081
   Park CY, 2021, SUSTAIN CITIES SOC, V73, DOI 10.1016/j.scs.2021.103123
   Paulin MJ, 2020, ECOL MODEL, V438, DOI 10.1016/j.ecolmodel.2020.109331
   Pilcher JJ, 2002, ERGONOMICS, V45, P682, DOI 10.1080/00140130210158419
   Portman ME, 2013, APPL GEOGR, V45, P185, DOI 10.1016/j.apgeog.2013.09.011
   Qiu LR, 2022, LAND-BASEL, V11, DOI 10.3390/land11040545
   Robine J.-M., 2007, Report on Excess Mortality in Europe during Summer 2003, P28
   Rocha AD, 2022, SUSTAIN CITIES SOC, V85, DOI 10.1016/j.scs.2022.104051
   Serrano-Notivoli R, 2022, WEATHER CLIM EXTREME, V37, DOI 10.1016/j.wace.2022.100471
   Shi WZ, 2021, J HYDROL, V597, DOI 10.1016/j.jhydrol.2021.126179
   Song N, 2022, WATER RES, V225, DOI 10.1016/j.watres.2022.119136
   Stache E, 2022, BUILD ENVIRON, V213, DOI 10.1016/j.buildenv.2021.108489
   Veretennikov P., 2019, Report of the Ministry of Infrastructure and Water Management
   Wang J, 2021, WEATHER CLIM EXTREME, V34, DOI 10.1016/j.wace.2021.100379
   Ward PJ., 2020, Water Security, V11, P100070, DOI [10.1016/j.wasec.2020.100070, DOI 10.1016/J.WASEC.2020.100070]
   Xu ZH, 2022, ENVIRON SCI POLICY, V135, P6, DOI 10.1016/j.envsci.2022.04.010
   Yang XS, 2022, URBAN CLIM, V41, DOI 10.1016/j.uclim.2021.101074
   Yin C, 2022, CLIM RISK MANAG, V38, DOI 10.1016/j.crm.2022.100459
   Yu S, 2019, J CLEAN PROD, V208, P1219, DOI 10.1016/j.jclepro.2018.10.067
   Zeisel J., 2006, Inquiry by design: Environment/behavior/neuroscience in architecture, interiors, landscape, and planning
   Zimmerman R, 2020, URBAN CLIM, V34, DOI 10.1016/j.uclim.2020.100658
NR 55
TC 1
Z9 1
U1 5
U2 5
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0955
J9 URBAN CLIM
JI Urban CLim.
PD MAY
PY 2024
VL 55
AR 101956
DI 10.1016/j.uclim.2024.101956
EA MAY 2024
PG 15
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA TI7B6
UT WOS:001240690300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Barrett, S
   Chaitanya, RSK
AF Barrett, Sam
   Chaitanya, Raghav S. K.
TI Getting private investment in adaptation to work: Effective adaptation,
   value, and cash flows
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Private Investment; Adaptation; Asset Pricing
ID CLIMATE-CHANGE; ADAPTIVE CAPACITY; VALUE CREATION; MICROFINANCE; RISK;
   STRATEGIES; RESILIENCE; FINANCE; SECTOR
AB Private finance can contribute to the achievement of systemic climate adaptation. But the research community are yet to provide a framework for private investors and borrowers to assess the commercial viability of investments in adaptation. To date, investment cases have not been constructed with climate adaptation as the underlying investment logic -no framework explains how adaptation creates value and converts to cash flows. Instead cases are made as standard equity, debt or loan investments in climate vulnerable contexts, or as poorly specified climate resilience or adaptation solutions. Such specialisms and experiences are present within the public sector adaptation evaluation community, but they typically have few means to communicate with private investors and private adapting entities. This perspective sets out how private investments in adaptation generates value and cash flows that can be applied in investment cases to guide investors and those seeking to raise capital. First it sets out the conceptual and practical linkages between effective adaptation, value and cash flows. It then shows the importance of cash flows when formulating basic financial asset pricing methods, using examples of intangible assets for equity and fair value for debt-based instruments.
C1 [Barrett, Sam] Int Inst Environm & Dev, 235 High Holborn, London WC1V 7DN, England.
   [Chaitanya, Raghav S. K.] Univ Sussex, Sussex House, Brighton BN1 9RH, England.
C3 University of Sussex
RP Barrett, S (corresponding author), Int Inst Environm & Dev, 235 High Holborn, London WC1V 7DN, England.
CR Adger N., 2003, CLIMATE CHANGE ADAPT, P29, DOI DOI 10.1142/9781860945816_0003
   Amfo B., 2020, Forest Policy Econ., V119, P1
   [Anonymous], 2020, OECD Tourism Trends and Policies 2020, DOI DOI 10.1787/6B47B985-EN
   Anugwa IQ, 2022, CLIM POLICY, V22, P112, DOI 10.1080/14693062.2021.1953435
   Atteya A., 2018, The Adaptation Gap Report, P1
   Ayers JM, 2009, DEV POLICY REV, V27, P675, DOI 10.1111/j.1467-7679.2009.00465.x
   Barrett S., 2021, N. Dir. Eval., V167, P115
   Barrett S, 2021, CLIM DEV, V13, P173, DOI 10.1080/17565529.2020.1745739
   Barrett S, 2020, CLIM DEV, V12, P677, DOI 10.1080/17565529.2019.1676689
   Barrett S, 2015, GLOBAL ENVIRON POLIT, V15, P118, DOI 10.1162/GLEP_a_00314
   Barrett S, 2013, GLOBAL ENVIRON CHANG, V23, P1819, DOI 10.1016/j.gloenvcha.2013.07.015
   Barth E., 1995, Account. Horiz., V9, P1
   Berrang-Ford L, 2021, NAT CLIM CHANGE, V11, P989, DOI 10.1038/s41558-021-01170-y
   Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Biagini B, 2013, CLIM DEV, V5, P242, DOI 10.1080/17565529.2013.821053
   Cervigni R., 2017, Enhancing the climate resilience of Africa's infrastructure: the roads and bridges Sector, P1
   Chambwera M, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P945
   Chartered Financial Analyst Institute (CFA), 2020, Climate change analysis in the investment process, P1
   Chirambo D, 2017, J DEV SOC, V33, P150, DOI 10.1177/0169796X17692474
   Cissé JD, 2018, J DEV ECON, V135, P272, DOI 10.1016/j.jdeveco.2018.04.002
   Citi, 2020, Citi's TCFD Report, P1
   Clark R, 2018, LAND USE POLICY, V71, P335, DOI 10.1016/j.landusepol.2017.12.013
   Climate Resilience and Adaptation Finance and Technology Transfer Facility (CRAFT), 2017, Global Innovation Lab for Climate Finance Publication, P1
   Crichton D., 2018, Urban Flood Management, P83
   Crick F, 2018, WORLD DEV, V108, P157, DOI 10.1016/j.worlddev.2018.03.015
   Dardonville M, 2021, J CLEAN PROD, V286, DOI 10.1016/j.jclepro.2020.125456
   de Ruig LT, 2020, WATER RESOUR ECON, V32, DOI 10.1016/j.wre.2019.100147
   Devkota N., 2017, Asian J. Agric. Rural Dev, V7, P136, DOI DOI 10.18488/JOURNAL.1005/2017.7.7/1005.7.136.148
   DiBella J, 2020, BUS STRATEGY DEV, V3, P245, DOI 10.1002/bsd2.92
   Dowla A, 2018, BUS STRATEGY DEV, V1, P78, DOI 10.1002/bsd2.13
   Downing TE, 2012, WIRES CLIM CHANGE, V3, P161, DOI 10.1002/wcc.157
   Druce L., 2016, Demystifying Adaptation Finance for the Private Sector
   Dzebo A., 2019, Stockholm Environmental Institute (SEI) Publication, V1
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   European Union (EU) Task Force Rural Africa, 2019, An Africa Europe Agenda for Rural Transformation, P1
   Falconer A., 2016, Global Innovation Lab for Climate Finance Publication, P1
   Fankhauser S., 2016, The economics of climate-resilient development
   Fayolle V., 2019, Action on Climate Today Learning Paper 1-36
   Fenton A, 2017, WORLD DEV, V92, P192, DOI 10.1016/j.worlddev.2016.12.004
   Fleetwood S, 1997, CAMBRIDGE J ECON, V21, P729, DOI 10.1093/oxfordjournals.cje.a013695
   Forino G, 2021, ENVIRON DEV SUSTAIN, V23, P18540, DOI 10.1007/s10668-021-01468-z
   Ghanian M, 2020, LAND USE POLICY, V94, DOI 10.1016/j.landusepol.2020.104553
   GILfCF, 2021, Publication 1-32
   Goldstein A, 2019, NAT CLIM CHANGE, V9, P18, DOI 10.1038/s41558-018-0340-5
   Green Climate Fund (GCF), 2016, GCF Documentation 1-83
   Green Climate Fund (GCF), 2020, GCF Publication 1-252
   Green Climate Fund (GCF), 2018, GCF Documentation 1-105
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Gyrd-Hansen D, 2003, HEALTH ECON, V12, P1049, DOI 10.1002/hec.799
   Hammill A, 2008, IDS BULL-I DEV STUD, V39, P113, DOI 10.1111/j.1759-5436.2008.tb00484.x
   Hansen J, 2019, AGR SYST, V172, P28, DOI 10.1016/j.agsy.2018.01.019
   Hjelmbrekke H, 2017, INT J MANAG PROJ BUS, V10, P60, DOI 10.1108/IJMPB-12-2015-0116
   Hunt Alistair, 2017, Climate Services, V7, P78, DOI 10.1016/j.cliser.2016.10.004
   Jagnani M, 2021, ECON J, V131, P392, DOI 10.1093/ej/ueaa063
   Jordan JC, 2021, CLIM DEV, V13, P454, DOI 10.1080/17565529.2020.1799737
   Joshi M.Y., 2020, Int. J. Disaster Risk Reduct., V49, P1
   Karydas C., 2019, CER ETH Working Paper Series Working Paper, V19, P1
   Khan NA, 2021, LAND USE POLICY, V105, DOI 10.1016/j.landusepol.2021.105427
   Kim I, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031208
   Kling G, 2021, WORLD DEV, V137, DOI 10.1016/j.worlddev.2020.105131
   Kniveton D, 2015, DISASTERS, V39, pS35, DOI 10.1111/disa.12108
   Kundzewicz ZW, 2018, P NATL ACAD SCI USA, V115, P12321, DOI 10.1073/pnas.1818227115
   Kuruppu N, 2011, GLOBAL ENVIRON CHANG, V21, P657, DOI 10.1016/j.gloenvcha.2010.12.002
   Lepak DP, 2007, ACAD MANAGE REV, V32, P180, DOI 10.2307/20159287
   Lev Baruch., 2000, INTANGIBLES MANAGEME
   Little LR, 2015, CLIM RISK MANAG, V8, P9, DOI 10.1016/j.crm.2015.02.002
   Lu J., 2021, J. Environ. Manage., V279, P1
   Marter-Kenyon J, 2020, ANTHROPOCENE REV, V7, P159, DOI 10.1177/2053019620915633
   Meyer PB, 2019, FRONT ENG MANAG, V6, P117, DOI 10.1007/s42524-019-0009-4
   Montgomery M, 2018, RISK ANAL, V38, P2275, DOI 10.1111/risa.13127
   Nganga S., 2017, CIAT Publication 439, P1
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   OECD, 2018, Core Competencies Framework on financial literacy for MSMEs, P1
   OECD, 2021, OECD Development Coordination Directorate Publication 1-47
   Olson M., 1965, LOGIC COLLECTIVE ACT, V124
   Paseda O., 2020, Journal of Economics and Sustainable Development, V11, P29
   Pauw P, 2013, CLIM DEV, V5, P257, DOI 10.1080/17565529.2013.826130
   Pauw WP, 2022, CLIM DEV, V14, P91, DOI 10.1080/17565529.2021.1885337
   Pinto J.E., 2020, The Environmental Impacts of Plastics and Micro-Plastics Use, Waste and Pollution: EU and National Measures, P1
   Sandsmark M, 2007, ENVIRON RESOUR ECON, V37, P681, DOI 10.1007/s10640-006-9049-4
   Schartmüller C, 2018, 20TH INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION WITH MOBILE DEVICES AND SERVICES (MOBILEHCI 2018), DOI 10.1145/3229434.3229459
   Schramade W., 2019, Principles of Sustainable Finance
   Sealey K.S., 2018, Will Miami Survive?: The Dynamic Interplay Between Floods and Finance, P65
   Sharma A, 2017, CLIM POLICY, V17, P33, DOI 10.1080/14693062.2016.1213697
   Sims C, 2021, CLIM CHANG ECON, V12, DOI 10.1142/S2010007821500123
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Soanes M., 2021, IIED Issue Paper 1-48
   Surminski S, 2013, NAT CLIM CHANGE, V3, P943, DOI 10.1038/nclimate2040
   Tenzing JD, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.626
   Tervo-Kankare K, 2018, TOURISM GEOGR, V20, P202, DOI 10.1080/14616688.2017.1375973
   Tessema YA, 2019, CLIM RISK MANAG, V23, P136, DOI 10.1016/j.crm.2018.09.003
   UNEP, 2018, The Adaptation Gap Report
   UNEP, 2021, Adaptation Gap Report 2021: The Gathering Storm-Adapting to Climate Change in a Post-Pandemic World
   United Nations Environment Programme Finance Initiative (UNEP FI), 2019, Guidance on the Global Monitoring Plan for Persistent Organic Pollutants, P1
   van Bergeijk VM, 2020, J MAR SCI ENG, V8, DOI 10.3390/jmse8070489
   Wattel C., 2021, CCAFS Publication, P1
   White B., 2010, Mercy Corps Publication 1-27
   Williams PA, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100198
   World Bank, 2020, Poverty & Equity brief, P1
   World Bank, 2021, Energy Transitions Outlook: 1.5 C Pathway, P1
   World Bank, 2021, World Bank Group Publication 1-116
   Wreford A., 2020, Wiley Interdisciplinary Reviews. Climate Change, V11, P1
   Yaron G, 2020, J FLOOD RISK MANAG, V13, DOI 10.1111/jfr3.12662
NR 103
TC 1
Z9 1
U1 1
U2 7
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD DEC
PY 2023
VL 83
AR 102761
DI 10.1016/j.gloenvcha.2023.102761
EA SEP 2023
PG 8
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA X3AP1
UT WOS:001097217000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Solórzano, CR
AF Solorzano, Claudia Rodriguez
TI Connecting climate social adaptation and land use change in
   internationally adjoining protected areas
SO CONSERVATION & SOCIETY
LA English
DT Article
DE Americas; climate; conservation; land use change; protected areas;
   social adaptation
ID CALAKMUL-BIOSPHERE-RESERVE; ELITE CAPTURE; COVER CHANGE; DEFORESTATION;
   LIVELIHOODS; MIGRATION; TRAJECTORIES; CONSERVATION; CAMPECHE; PARKS
AB The development of climate adaptation strategies to address social problems derived from climate change is pressing. Yet, in addition to providing means to minimise the impact of climate variability and change on livelihoods, climate adaptation strategies might exacerbate environmental change and cause negative social impacts. Systematic research has not addressed the impacts of adaptation on environmental change. In this paper, I focus on land use change as a specific type of environmental change and on three adaptation strategies: diversification, pooling and out-migration. I analyse the influence of adaptation strategies on land use change by drawing on interviews with the managers of 56 internationally adjoining protected areas in 18 countries in the Americas. The findings indicate that the impact of adaptation depends on the adaptation strategy people choose. When people out-migrate, land use change increases. Community elite control for decision-making, shorter distances between communities and markets and more communities in and around the protected areas also increase land use change. These findings show that adaptation can be a driver of further environmental change, and thus further study is needed to understand the likely impacts of adaptation on conservation.
C1 [Solorzano, Claudia Rodriguez] Dartmouth Coll, Environm Studies Program, Hanover, NH 03755 USA.
   [Solorzano, Claudia Rodriguez] Texas A&M Univ, Ecosyst Sci & Management Dept, College Stn, TX 77843 USA.
   [Solorzano, Claudia Rodriguez] Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA.
   [Solorzano, Claudia Rodriguez] Indiana Univ, Workshop Polit Theory & Policy Anal, Bloomington, IN 47405 USA.
C3 Dartmouth College; Texas A&M University System; Texas A&M University
   College Station; University of Michigan System; University of Michigan;
   Indiana University System; Indiana University Bloomington
RP Solórzano, CR (corresponding author), Dartmouth Coll, Environm Studies Program, Hanover, NH 03755 USA.; Solórzano, CR (corresponding author), Texas A&M Univ, Ecosyst Sci & Management Dept, College Stn, TX 77843 USA.; Solórzano, CR (corresponding author), Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA.; Solórzano, CR (corresponding author), Indiana Univ, Workshop Polit Theory & Policy Anal, Bloomington, IN 47405 USA.
EM claudiars@dartmouth.edu
RI Solorzano, Claudia/G-8817-2011
OI Rodriguez Solorzano, Claudia/0000-0002-9470-6746
FU Mexican Council of Science and Technology, University of Michigan,
   Indiana University; Direct For Mathematical & Physical Scien; Division
   Of Chemistry [1313932] Funding Source: National Science Foundation
FX I am grateful for the support provided by the Mexican Council of Science
   and Technology, University of Michigan, Indiana University, Arun
   Agrawal, Maria Carmen Lemos, Ashwini Chhatre, Forrest Fleischman and
   Catherine Benson for the development of this manuscript.
CR Adger WN, 2002, AMBIO, V31, P358, DOI 10.1639/0044-7447(2002)031[0358:MRLTAS]2.0.CO;2
   Agarwal B, 2001, WORLD DEV, V29, P1623, DOI 10.1016/S0305-750X(01)00066-3
   Agrawal A, 1997, DEV CHANGE, V28, P435, DOI 10.1111/1467-7660.00050
   Agrawal A., 2000, 8 BIENN IASCP INT AS
   Agrawal Arun., 2005, ENVIRONMENTALITY TEC
   [Anonymous], 2008, ROLE LOCAL I ADAPTAT
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bray DB, 2008, ECOL SOC, V13
   Brockhaus M, 2013, ENVIRON SCI POLICY, V25, P94, DOI 10.1016/j.envsci.2012.08.008
   Bruner AG, 2001, SCIENCE, V291, P125, DOI 10.1126/science.291.5501.125
   Carr DL, 2008, HUM ECOL, V36, P231, DOI 10.1007/s10745-007-9154-1
   Carr DL, 2005, POPUL ENVIRON, V27, P89, DOI 10.1007/s11111-005-0014-x
   Carr DL, 2004, POPUL ENVIRON, V25, P585
   Chowdhury RR, 2006, APPL GEOGR, V26, P129, DOI 10.1016/j.apgeog.2005.11.004
   Cinner JE, 2011, GLOBAL ENVIRON CHANG, V21, P7, DOI 10.1016/j.gloenvcha.2010.09.001
   de Sherbinin A, 2008, GLOBAL ENVIRON CHANG, V18, P38, DOI 10.1016/j.gloenvcha.2007.05.005
   Dias B., 2003, INTERLINKAGES BIOL D
   Aguiar APD, 2007, ECOL MODEL, V209, P169, DOI 10.1016/j.ecolmodel.2007.06.019
   Eakin HC, 2014, GLOBAL ENVIRON CHANG, V27, P1, DOI 10.1016/j.gloenvcha.2014.04.013
   Erg B., 2010, GLOBAL OVERVIEW TRAN
   Ericson JA, 2006, LANDSCAPE URBAN PLAN, V74, P242, DOI 10.1016/j.landurbplan.2004.09.006
   Fazey I, 2011, GLOBAL ENVIRON CHANG, V21, P1275, DOI 10.1016/j.gloenvcha.2011.07.006
   Geist H.J., 2001, LUCC Report series, V4, P116
   Ghate Rucha., 2007, Conservation and Society, P331
   Gibson C.C., 2000, PEOPLE FORESTS COMMU
   Gray CL, 2014, LAND USE POLICY, V36, P182, DOI 10.1016/j.landusepol.2013.07.006
   Halstead Paul, 1989, BAD YEAR EC CULTURAL, DOI [DOI 10.1017/CBO9780511521218, 10.1017/CBO9780511521218]
   Hansen AJ, 2007, ECOL APPL, V17, P972, DOI 10.1890/05-1112
   Hecht SB, 2007, BIOSCIENCE, V57, P663, DOI 10.1641/B570806
   Lambin EF, 2001, GLOBAL ENVIRON CHANG, V11, P261, DOI [10.1016/S0959-3780(01)00007-3, 10.1146/annurev.energy.28.050302.105459]
   Lemos M.C., 2013, Climate Science for Serving Society: Research, Modeling and Prediction Priorities, P437, DOI DOI 10.1007/978-94-007-6692-1_16
   López E, 2006, AGR SYST, V90, P62, DOI 10.1016/j.agsy.2005.11.001
   Lund JF, 2013, WORLD DEV, V46, P104, DOI 10.1016/j.worlddev.2013.01.028
   Lysenko I., 2007, Unep-wcmc global list of transboundary protected areas, DOI DOI 10.1186/s13002-017-0148-9
   Nagendra H, 2006, APPL GEOGR, V26, P96, DOI 10.1016/j.apgeog.2005.11.002
   Seo SN, 2010, FOOD POLICY, V35, P32, DOI 10.1016/j.foodpol.2009.06.004
   Ostrom E, 2007, P NATL ACAD SCI USA, V104, P15181, DOI 10.1073/pnas.0702288104
   Persha L, 2011, SCIENCE, V331, P1606, DOI 10.1126/science.1199343
   Platteau JP, 2004, DEV CHANGE, V35, P223, DOI 10.1111/j.1467-7660.2004.00350.x
   Radel C, 2008, J LAT AM GEOGR, V7, P59, DOI 10.1353/lag.0.0001
   Rangarajan M, 2006, Conservation and Society, V4, P359
   Ribot JC, 2010, ENVIRON CONSERV, V37, P35, DOI 10.1017/S0376892910000329
   Rodriguez-Solorzano C, 2014, ECOL SOC, V19, DOI 10.5751/ES-06509-190253
   Sandwith Trevor., 2001, TRANSBOUNDARY PROTEC
   Serneels S, 2001, AGR ECOSYST ENVIRON, V85, P65, DOI 10.1016/S0167-8809(01)00188-8
   Sydenstricker-Neto J, 2012, POPUL ENVIRON, V34, P86, DOI 10.1007/s11111-012-0173-5
   Tucker CM, 2010, GLOBAL ENVIRON CHANG, V20, P23, DOI 10.1016/j.gloenvcha.2009.07.006
   van de Sand I, 2014, ECOL SOC, V19, DOI 10.5751/ES-06199-190147
   van der Linde H., 2001, Beyond Boundaries: Transboundary Natural Resource Management in Sub-Saharan Africa
   Zbicz D. C., 1999, THESIS
NR 50
TC 4
Z9 4
U1 0
U2 17
PU WOLTERS KLUWER MEDKNOW PUBLICATIONS
PI MUMBAI
PA WOLTERS KLUWER INDIA PVT LTD , A-202, 2ND FLR, QUBE, C T S  NO 1498A-2
   VILLAGE MAROL, ANDHERI EAST, MUMBAI, 400059, INDIA
SN 0972-4923
EI 0975-3133
J9 CONSERV SOC
JI Conserv. Soc.
PD APR-JUN
PY 2016
VL 14
IS 2
BP 125
EP 133
DI 10.4103/0972-4923.186334
PG 9
WC Biodiversity Conservation; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA DU7OU
UT WOS:000382405300005
OA hybrid
DA 2025-01-10
ER

PT J
AU Olazabal, M
   Broto, VC
AF Olazabal, Marta
   Broto, Vanesa Castan
TI Institutionalisation of urban climate adaptation: three municipal
   experiences in Spain
SO BUILDINGS & CITIES
LA English
DT Article
DE adaptation; cities; institutional change; institutions; learning;
   planning; transformation; urban governance; Spain
ID BARRIERS; GOVERNANCE; CITIES; PLANS
AB Comparative studies of urban adaptation have evaluated the progress, means and scope of adaptation planning. Practice on the ground shows that the local politics of climate adaptation advance through various strategies to align different interests and spheres of action or disrupt mainstream practices, which translates into a wide range of interventions. This paper focuses on understanding the dynamics and tools that enable the institutionalisation of adaptation practices in local governments, i.e. the means through which adaptation practices, beyond plans and policies, are embedded in the routines of urban governance. It presents a framework to analyse the institutionalisation of adaptation that maps stages and tools with the potential to deliver adaptation in urban areas. Adaptation is framed as a learning process involving overlapping phases of recognition (of needs, capacities and actors), groundwork (knowledge generation) and action on the ground (change). The framework compares three Spanish local government initiatives (Bilbao, Barcelona and Madrid). The analysis shows that adaptation can be effectively incorporated into standard rules, norms and practices using combinations of tools and spatial and temporal scales. The coupled stages of recognition, groundwork and action highlight the importance of long-term learning processes to engage with the temporal dimensions of adaptation governance.
C1 [Olazabal, Marta] Basque Ctr Climate Change, Leioa, Spain.
   [Olazabal, Marta] IKERBASQUE, Basque Fdn Sci, Bilbao, Spain.
   [Broto, Vanesa Castan] Univ Sheffield, Dept Geog, Sheffield, England.
C3 Basque Centre for Climate Change (BC3); Basque Foundation for Science;
   University of Sheffield
RP Olazabal, M (corresponding author), Basque Ctr Climate Change, Leioa, Spain.
EM marta.olazabal@bc3research.org
RI Olazabal, Marta/AFT-6957-2022; Broto, Vanesa/AAF-4485-2021; Olazabal,
   Marta/C-3027-2008
OI Castan Broto, Vanesa/0000-0002-3175-9859; Olazabal,
   Marta/0000-0002-3381-0654
FU European Research Council (ERC) under the European Union
   [804051-LO-ACT-ERC-2018-STG]; Maria de Maeztu's excellence accreditation
   [2018-22, MDM-2017-0714, MCIN/AEI/10.13039/501100011033]; Basque
   government through the BERC [2022-25]; GCRF [ES/T006358/1] Funding
   Source: UKRI
FX This article received <STRONG>FUNDING </STRONG>from the European
   Research Council (ERC) under the European Union's Horizon 2020 Research
   and Innovation Programme (grant agreement number
   804051-LO-ACT-ERC-2018-STG) . Marta Olazabal's research was also
   supported by Maria de Maeztu's excellence accreditation 2018-22
   (reference number MDM-2017-0714) , funded by
   MCIN/AEI/10.13039/501100011033/; and by the Basque government through
   the BERC 2022-25 programme.
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Aguiar FC, 2018, ENVIRON SCI POLICY, V86, P38, DOI 10.1016/j.envsci.2018.04.010
   Anguelovski I, 2011, CURR OPIN ENV SUST, V3, P169, DOI 10.1016/j.cosust.2010.12.017
   Araos M, 2016, ENVIRON SCI POLICY, V66, P375, DOI 10.1016/j.envsci.2016.06.009
   Arnott JC, 2016, ENVIRON SCI POLICY, V66, P383, DOI 10.1016/j.envsci.2016.06.017
   Avelino F, 2021, J POLITICAL POWER, V14, P425, DOI 10.1080/2158379X.2021.1875307
   Ayuntamiento de Madrid, 2015, Analisis de vulnerabilidad ante el cambio climatico en el municipio de Madrid
   Betsill MM, 2006, GLOBAL GOV, V12, P141, DOI 10.1163/19426720-01202004
   Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Broto VC, 2013, GLOBAL ENVIRON CHANG, V23, P92, DOI 10.1016/j.gloenvcha.2012.07.005
   Carmin J., 2012, Progress and challenges in urban climate adaptation planning: Results of a global survey, DOI [10.1177/0739456X11430951, DOI 10.1177/0739456X11430951]
   Carter JG, 2015, PROG PLANN, V95, P1, DOI 10.1016/j.progress.2013.08.001
   Davoudi S, 2012, PLAN THEORY PRACT, V13, P299, DOI 10.1080/14649357.2012.677124
   Dodman D., 2012, Adapting cities to climate change: Understanding and addressing the development challenges, DOI [10.4324/9781849770361, DOI 10.4324/9781849770361]
   Eisenack K, 2016, ECOL ECON, V124, P153, DOI 10.1016/j.ecolecon.2016.01.016
   Eisenack K, 2014, NAT CLIM CHANGE, V4, P867, DOI 10.1038/NCLIMATE2350
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   Fatoric S, 2020, CLIMATIC CHANGE, V162, P301, DOI 10.1007/s10584-020-02831-1
   Ford JD, 2015, MITIG ADAPT STRAT GL, V20, P505, DOI 10.1007/s11027-013-9505-8
   Sánchez FG, 2018, LAND USE POLICY, V79, P164, DOI 10.1016/j.landusepol.2018.08.010
   Garrido A., 2018, Cuadernos de Vivienda y Urbanismo, V11, P4, DOI [10.11144/Javeriana.cvu11-22.phce, DOI 10.11144/JAVERIANA.CVU11-22.PHCE]
   Garrido Martinez J. A., 2004, Revista Internacional de Los Estudios Vascos, V49, P23
   Gunderson L. H., 2002, Panarchy: understanding transformations in human and natural systems
   Guyadeen D, 2019, CLIMATIC CHANGE, V152, P121, DOI 10.1007/s10584-018-2312-1
   Heidrich O, 2013, CLIMATIC CHANGE, V120, P771, DOI 10.1007/s10584-013-0846-9
   Heikkinen M, 2020, J CLEAN PROD, V257, DOI 10.1016/j.jclepro.2020.120474
   Huitema D, 2016, ECOL SOC, V21, DOI 10.5751/ES-08797-210337
   Hunter NB, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab9d00
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2021The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel On Climate Change, DOI [10.1017/9781009325844.001, DOI 10.1017/9781009157940, 10.1017/9781009157896]
   Juhola S, 2016, INT J CLIM CHANG STR, V8, P338, DOI 10.1108/IJCCSM-03-2014-0030
   Klein J, 2018, GLOBAL ENVIRON CHANG, V53, P127, DOI 10.1016/j.gloenvcha.2018.09.012
   Kuhl L, 2020, WORLD DEV, V127, DOI 10.1016/j.worlddev.2019.104748
   Lesnikowski AC, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/4/044009
   Lesnikowski A, 2019, CLIMATIC CHANGE, V156, P447, DOI 10.1007/s10584-019-02533-3
   Lesnikowski AC, 2015, MITIG ADAPT STRAT GL, V20, P277, DOI 10.1007/s11027-013-9491-x
   Lourenço TC, 2019, REG ENVIRON CHANGE, V19, P629, DOI 10.1007/s10113-018-1362-2
   Martinez-Juarez P., 2020, EKONOMIAZ. Revista Vasca de Economia, V97, P191
   Meerow S, 2020, J AM PLANN ASSOC, V86, P39, DOI 10.1080/01944363.2019.1652108
   Moore ML, 2018, ECOL SOC, V23, DOI 10.5751/ES-10166-230238
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Neder EA, 2021, CLIMATIC CHANGE, V166, DOI 10.1007/s10584-021-03113-0
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   Olazabal M, 2021, ONE EARTH, V4, P828, DOI 10.1016/j.oneear.2021.05.006
   Olazabal M, 2021, LANDSCAPE URBAN PLAN, V206, DOI 10.1016/j.landurbplan.2020.103974
   Olazabal M, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab5532
   Olazabal M, 2019, INT J URBAN SUSTAIN, V11, P277, DOI 10.1080/19463138.2019.1583234
   Olazabal M, 2015, J CLEAN PROD, V109, P336, DOI 10.1016/j.jclepro.2015.08.047
   Oses N., 2012, Informe de Avance de Proyecto
   Patterson J.J., 2018, Adaptive Cities? Institutional Innovation Under Climate Change: A Global Survey of 96 Cities
   Patterson JJ, 2021, GLOBAL ENVIRON CHANG, V68, DOI 10.1016/j.gloenvcha.2021.102279
   Patterson JJ, 2019, J ENVIRON PLANN MAN, V62, P374, DOI 10.1080/09640568.2018.1510767
   Pelling M, 2011, ECOL SOC, V16
   Reckien D, 2018, J CLEAN PROD, V191, P207, DOI 10.1016/j.jclepro.2018.03.220
   Revi A, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P535
   Rodriguez Arantxa., 2003, GLOBALIZED CITY EC R, P181
   Satorras M, 2020, CITIES, V106, DOI 10.1016/j.cities.2020.102887
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   Shi LD, 2015, J AM PLANN ASSOC, V81, P191, DOI 10.1080/01944363.2015.1074526
   Sieber IM, 2018, REG ENVIRON CHANGE, V18, P2379, DOI 10.1007/s10113-018-1347-1
   Thaler T, 2019, SCI TOTAL ENVIRON, V650, P1073, DOI 10.1016/j.scitotenv.2018.08.306
   Tilleard S, 2016, CLIMATIC CHANGE, V137, P575, DOI 10.1007/s10584-016-1699-9
   Tompkins EL, 2010, GLOBAL ENVIRON CHANG, V20, P627, DOI 10.1016/j.gloenvcha.2010.05.001
   Le TDN, 2020, MITIG ADAPT STRAT GL, V25, P739, DOI 10.1007/s11027-019-09888-z
   UN-HABITAT, 2016, World Cities Report
   Wolfram M, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8020144
   Woodru SC, 2016, NAT CLIM CHANGE, V6, P796, DOI 10.1038/NCLIMATE3012
NR 67
TC 6
Z9 6
U1 4
U2 4
PU UBIQUITY PRESS LTD
PI LONDON
PA Unit 3N, 6 Osborn Street, LONDON, E1 6TD, ENGLAND
SN 2632-6655
J9 BUILD CITIES
JI Build. Cities
PY 2022
VL 3
IS 1
BP 570
EP 588
DI 10.5334/bc.208
PG 19
WC Construction & Building Technology
WE Emerging Sources Citation Index (ESCI)
SC Construction & Building Technology
GA OP1J2
UT WOS:001208385200008
OA gold, Green Accepted, Green Published
DA 2025-01-10
ER

PT J
AU Wei, J
   Zhang, YJ
AF Wei, Jin
   Zhang, Yue-Jun
TI Exploring a strategy for tall office buildings based on thermal energy
   consumption from industrialized perspective: An empirical study in China
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Climatic adaptation; Tall office buildings; Thermal energy consumption;
   Energy-efficient strategy; Building industrialization; National energy
   conservation policy
ID DECOMPOSITION; EMISSIONS; COMFORT; DESIGN; ENVIRONMENTS; PERFORMANCE;
   SIMULATION; SYSTEMS
AB Faced with urban high-density environment, current energy-saving measures are focused on climatic design and technical improvement, which might not align well with China's national policies on extending the longevity of high-rise buildings to realize life cycle sustainability. Therefore, this paper explores energy-efficient strategies for tall office buildings in response to the time-varying operational parameters to realize spatial malleability from industrialized perspective. The results from a case study show that, first, the model of office + multi-courtyards has positive impact on climatic adaptation, in terms of ventilation, air temperature, thermal radiation environment, and effectiveness of thermal energy conservation. Second, the average energy efficiency rate of the model of office + multi-courtyards is from 12.8% to 4.7% with the interior space coverage of 20%-80%. Third, when the interior space coverage ranges from 50% to 60%, the average energy efficiency rate appears substantial fluctuation from 10.3% to 6.5% and appears the change point when the interior space coverage is 58%. (C) 2020 Elsevier Ltd. All rights reserved.
C1 [Wei, Jin] South China Univ Technol, Sch Architecture, Guangzhou 510640, Peoples R China.
   [Zhang, Yue-Jun] Hunan Univ, Business Sch, Changsha 410082, Hunan, Peoples R China.
   [Zhang, Yue-Jun] Hunan Univ, Ctr Resource & Environm Management, Changsha 410082, Hunan, Peoples R China.
C3 South China University of Technology; Hunan University; Hunan University
RP Zhang, YJ (corresponding author), Hunan Univ, Business Sch, Changsha 410082, Hunan, Peoples R China.
EM zyjmis@126.com
RI Zhang, Yue-Jun/A-8850-2012
FU National Natural Science Foundation of China [71774051, 51678243];
   National Key Research and Development Program of China [2017YFC0702309];
   National Program for Support of Top-notch Young Professionals
   [W02070325]; Changjiang Scholars Program of the Ministry of Education of
   China [Q2016154]; Hunan Youth Talent Program
FX We gratefully acknowledge the financial support from the National
   Natural Science Foundation of China (nos. 71774051, 51678243), National
   Key Research and Development Program of China (nos. 2017YFC0702309),
   National Program for Support of Top-notch Young Professionals (no.
   W02070325), Changjiang Scholars Program of the Ministry of Education of
   China (no. Q2016154), and Hunan Youth Talent Program. Jin Wei also would
   like to thank Mr. Xiaojian Duan for his help in coupling of Energyplus
   and Matlab.
CR Aktacir MA, 2010, APPL ENERG, V87, P599, DOI 10.1016/j.apenergy.2009.05.008
   Buyle M, 2013, RENEW SUST ENERG REV, V26, P379, DOI 10.1016/j.rser.2013.05.001
   Chen HY, 2008, HABITAT INT, V32, P28, DOI 10.1016/j.habitatint.2007.06.005
   Gan VJL, 2019, J CLEAN PROD, V231, P1375, DOI 10.1016/j.jclepro.2019.05.324
   Habraken N.J., 2003, ISARC2003 FUTURE SIT, P21
   Henze GP, 2008, ENERG BUILDINGS, V40, P99, DOI 10.1016/j.enbuild.2007.01.014
   Hertzberger H., 2005, SPACE LEARNING LESSO
   Jaberansari M., 2016, INT C EN ENV EC ED U, P16
   Klemencic R., 2012, 9 CTBUH WORLD C SHAN, P19
   Korolija I, 2013, ENERG BUILDINGS, V60, P152, DOI 10.1016/j.enbuild.2012.12.032
   Kurokawa K., 2000, Architect and Associates: Selected and Current Works
   Li J, 2009, J ENVIRON MANAGE, V90, P2436, DOI 10.1016/j.jenvman.2008.12.015
   Li Z, 2015, APPL THERM ENG, V78, P9, DOI 10.1016/j.applthermaleng.2014.12.030
   Mi ZF, 2015, J CLEAN PROD, V103, P455, DOI 10.1016/j.jclepro.2014.06.011
   Mi ZF, 2018, EARTHS FUTURE, V6, P1007, DOI 10.1029/2018EF000840
   Perini K, 2017, ENERG BUILDINGS, V143, P35, DOI 10.1016/j.enbuild.2017.03.036
   Sayadi S, 2019, J CLEAN PROD, V241, DOI 10.1016/j.jclepro.2019.118277
   Susca T, 2011, ENVIRON POLLUT, V159, P2119, DOI 10.1016/j.envpol.2011.03.007
   Taleghani M, 2013, RENEW SUST ENERG REV, V26, P201, DOI 10.1016/j.rser.2013.05.050
   Tam WYV, 2018, J CLEAN PROD, V172, P4220, DOI 10.1016/j.jclepro.2017.11.130
   Tan YT, 2016, CITIES, V55, P82, DOI 10.1016/j.cities.2016.04.002
   Walikewitz N, 2015, BUILD ENVIRON, V84, P151, DOI 10.1016/j.buildenv.2014.11.004
   Wan KKW, 2012, APPL ENERG, V97, P274, DOI 10.1016/j.apenergy.2011.11.048
   Wan KSY, 2004, APPL ENERG, V78, P19, DOI 10.1016/S0306-2619(03)00103-X
   Wang K, 2016, ENERG ECON, V54, P50, DOI 10.1016/j.eneco.2015.11.013
   Wang QW, 2015, APPL ENERG, V151, P85, DOI 10.1016/j.apenergy.2015.04.034
   Xue F, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8111095
   Yang F, 2011, ARCHIT SCI REV, V54, P285, DOI 10.1080/00038628.2011.613646
   Yeang K., 2011, ECOSKYSCRAPERS, V2
   Yu SW, 2016, APPL ENERG, V165, P107, DOI 10.1016/j.apenergy.2015.12.064
   Zhang YJ, 2015, RENEW SUST ENERG REV, V41, P1255, DOI 10.1016/j.rser.2014.09.021
   Zhao J, 2014, ENERG BUILDINGS, V82, P341, DOI 10.1016/j.enbuild.2014.07.033
   Zheng ZJ, 2010, IEEE INT C BIOINFORM, P13, DOI 10.1109/BIBM.2010.5706527
NR 33
TC 5
Z9 5
U1 2
U2 24
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-6526
EI 1879-1786
J9 J CLEAN PROD
JI J. Clean Prod.
PD JUN 1
PY 2020
VL 257
AR 120497
DI 10.1016/j.jclepro.2020.120497
PG 11
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology
GA KY2EQ
UT WOS:000522383500073
DA 2025-01-10
ER

PT J
AU Page, R
   Dilling, L
AF Page, Rebecca
   Dilling, Lisa
TI How experiences of climate extremes motivate adaptation among water
   managers
SO CLIMATIC CHANGE
LA English
DT Article
DE Drought; Water; Climate adaptation; Organization policy
ID ADAPTIVE CAPACITY; RESOURCE MANAGEMENT; VULNERABILITY; COLORADO;
   RESPONSES; DROUGHT; LESSONS; WEATHER; SCIENCE
AB As water systems are likely to experience mounting challenges managing for climate variability and extremes as well as a changing climate, there is increasing interest in what motivates systems to implement adaptive measures. While extreme events have been hypothesized to stimulate organization change and act as "windows of opportunity" and "pacemakers" driving toward adaptation, they do not always seem to do so. We therefore sought to understand the responses and motivations for organizational behavior in the wake of two significant droughts across five smaller water systems in Western Colorado, USA. We conducted interviews and focus groups across these systems to understand whether and why significant droughts in 2002 and 2012 prompted adaptive change. Results indicate that systems did not uniformly decide to change their policies in the wake of drought, and even well-prepared systems were driven to change policies by other pressures, such as peer-system pressure and political pressure from residents. We find that organizational worldviews were important mediators of how the experience of drought manifest, or not, in organizational changes. These findings have implications for assumptions about what might drive organizational learning and change among water managers for climate adaptation in the future.
C1 [Page, Rebecca] Univ Colorado, Environm Studies Program & Western Water Assessme, Boulder, CO 80309 USA.
   [Dilling, Lisa] Univ Colorado, Cooperat Inst Res Environm Sci, Ctr Sci & Technol Policy Res, Environm Studies Program,Western Water Assessment, UCB 397, Boulder, CO 80309 USA.
C3 University of Colorado System; University of Colorado Boulder;
   University of Colorado System; University of Colorado Boulder
RP Dilling, L (corresponding author), Univ Colorado, Cooperat Inst Res Environm Sci, Ctr Sci & Technol Policy Res, Environm Studies Program,Western Water Assessment, UCB 397, Boulder, CO 80309 USA.
EM ldilling@colorado.edu
RI Dilling, Lisa/I-2889-2012
OI Dilling, Lisa/0000-0001-5061-0809
FU National Oceanic and Atmospheric Administration's Sectoral Applications
   Research Program [NA16OAR4310132]
FX We thank all of the Western Slope water managers who gave of their time
   to participate in this study. The authors gratefully acknowledge support
   from the National Oceanic and Atmospheric Administration's Sectoral
   Applications Research Program under Grant No. NA16OAR4310132, Ben
   Livneh, PI. We are also grateful to Eric Kuhn of the Colorado River
   District, Nolan Doesken of the Colorado Climate Center, and Jeff Lukas
   of the Western Water Assessment for providing valuable feedback and
   input into the design of this study. The authors are solely responsible
   for all content.
CR Argyris C., 1996, Organizational learning II: Theory, method, and practice, V2
   Bazeley P., 2013, Qualitative Data Analysis: Practical Strategies
   Berkhout F, 2012, WIRES CLIM CHANGE, V3, P91, DOI 10.1002/wcc.154
   Birkland T.A., 2006, Learning from Disaster: Policy Change after Catastrophic Events
   Birkmann J, 2010, NAT HAZARDS, V55, P637, DOI 10.1007/s11069-008-9319-2
   Burch S, 2007, CLIM POLICY, V7, P304, DOI 10.1080/14693062.2007.9685658
   Busenberg G.J., 2001, Journal of Public Policy, V21, P173, DOI DOI 10.1017/S0143814X0100109X
   Callihan LM, 2013, THESIS
   Carley KM, 1997, AM BEHAV SCI, V40, P310, DOI 10.1177/0002764297040003007
   Christoplos I, 2006, ELUSIVE WINDOW OPPOR, P1
   Diduck A, 2010, SPRINGER SER ENV MAN, P199, DOI 10.1007/978-3-642-12194-4_10
   Dilling L, 2019, CLIM RISK MANAG, V23, P32, DOI 10.1016/j.crm.2018.11.001
   Dilling L, 2015, WIRES CLIM CHANGE, V6, P413, DOI 10.1002/wcc.341
   FOLKES VS, 1988, J CONSUM RES, V15, P13, DOI 10.1086/209141
   Getches DavidH., 1990, WATER LAW NUTSHELL
   Gordon E., 2015, Colorado Climate Change Vulnerability Study. A report submitted to the Colorado Energy Office
   Granderson AA, 2014, CLIM RISK MANAG, V3, P55, DOI 10.1016/j.crm.2014.05.003
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   HASHIMOTO T, 1982, WATER RESOUR RES, V18, P14, DOI 10.1029/WR018i001p00014
   Hornberger GM, 2015, WATER RESOUR RES, V51, P4635, DOI 10.1002/2015WR016943
   Huitema D, 2010, ECOL SOC, V15
   Jacobs K, 2003, WATER RES M, V16, P177
   Kahan DM, 2012, NAT CLIM CHANGE, V2, P732, DOI 10.1038/NCLIMATE1547
   Kirchhoff Christine J., 2016, Water Resources Research, V52, P2951, DOI 10.1002/2015WR018431
   Klein R., 2006, Use of Climate Information in Municipal Drought Planning in Colorado
   Kuranz A, 2014, THESIS
   Lach D, 2005, TEX LAW REV, V83, P2027
   Linnenluecke MK, 2012, BUS STRATEG ENVIRON, V21, P17, DOI 10.1002/bse.708
   Livneh B, 2015, J HYDROL, V523, P196, DOI 10.1016/j.jhydrol.2015.01.039
   Livneh B, 2014, WATER RESOUR RES, V50, P8589, DOI 10.1002/2014WR015442
   Lowrey JL, 2009, CLIM RES, V40, P103, DOI 10.3354/cr00827
   Lukas J., 2014, CLIMATE CHANGE COLOR
   Maitlis S, 2005, ACAD MANAGE J, V48, P21, DOI 10.2307/20159639
   Maitlis S, 2014, ACAD MANAG ANN, V8, P57, DOI 10.1080/19416520.2014.873177
   McNeeley SM, 2016, WEATHER CLIM SOC, V8, DOI 10.1175/WCAS-D-15-0042.1
   McNeeley SM, 2014, REG ENVIRON CHANGE, V14, P1451, DOI 10.1007/s10113-014-0585-0
   Molotch NP, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004522
   Moynihan DP, 2008, PUBLIC ADMIN REV, V68, P350, DOI 10.1111/j.1540-6210.2007.00867.x
   Muro M, 2008, J ENVIRON PLANN MAN, V51, P325, DOI 10.1080/09640560801977190
   Page R, 2019, WEATHER CLIM SOC, V11, P851, DOI 10.1175/WCAS-D-18-0130.1
   Pelling M, 2008, ENVIRON PLANN A, V40, P867, DOI 10.1068/a39148
   Penning-Rowsell E, 2006, GLOBAL ENVIRON CHANG, V16, P323, DOI 10.1016/j.gloenvcha.2006.01.006
   Pielke RA, 2005, PURE APPL GEOPHYS, V162, P1455, DOI 10.1007/s00024-005-2679-6
   Pulwarty RS, 2001, J ENVIRON MANAGE, V63, P307, DOI 10.1006/jema.2001.0494
   Ray AJ, 2004, THESIS
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Slovic P, 2006, CURR DIR PSYCHOL SCI, V15, P322, DOI 10.1111/j.1467-8721.2006.00461.x
   Srdjevic B, 2004, WATER RESOUR MANAG, V18, P35, DOI 10.1023/B:WARM.0000015348.88832.52
   Travis WR, 2014, WEATHER CLIM EXTREME, V5-6, P29, DOI 10.1016/j.wace.2014.08.001
   Weick KE., 1995, Sensemaking in Organizations, DOI DOI 10.1016/S0956-5221(97)86666-3
   Yin R. K., 2013, Case study research: Design and methods, V5, DOI DOI 10.1097/FCH.0B013E31822DDA9E
NR 51
TC 21
Z9 23
U1 0
U2 13
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0165-0009
EI 1573-1480
J9 CLIMATIC CHANGE
JI Clim. Change
PD AUG
PY 2020
VL 161
IS 3
BP 499
EP 516
DI 10.1007/s10584-020-02712-7
EA APR 2020
PG 18
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA MZ7YA
UT WOS:000529122100001
DA 2025-01-10
ER

PT J
AU Zandvoort, M
   Kooijmans, N
   Kirshen, P
   van den Brink, A
AF Zandvoort, Mark
   Kooijmans, Nora
   Kirshen, Paul
   van den Brink, Adri
TI Designing with Pathways: A Spatial Design Approach for Adaptive and
   Sustainable Landscapes
SO SUSTAINABILITY
LA English
DT Article
DE adaptiveness; climate adaptation; decision pathways; flood risk
   management; landscape architecture; spatial design; uncertainty;
   visualization
ID SEA-LEVEL RISE; CLIMATE-CHANGE; ADAPTATION; FLEXIBILITY; FRAMEWORK;
   BOSTON; WATER; PART
AB Despite rising attention to pathways thinking in multiple domains such as climate adaptation, energy supply planning, and flood risk management, their spatial translation is so far understudied. We set out to study how spatial design based on pathways thinking can help develop more adaptive and sustainable landscapes. Using landscape analysis, field research, and research-through-designing in a case study on climate resilience in Boston (USA), we argue for better understanding of the spatial and design consequences of pathways in general. Our results indicate that pathways can be spatially translated, demanding landscape-informed choices when sequencing different policy actions. We found that spatial designing makes the landscape consequences of pathways transparent and enables policy-makers to replace the input of policy actions with spatial interventions, select pathways according to different underlying design strategies, use the mapped pathways to initiate an iterative research-through-designing process to test and inform different designs, and spatially visualize the pathways and possible sequences of actions. We conclude that policy-makers should be cognizant about the spatial implications of pathways and offer directions to enrich applications of pathways thinking for achieving adaptive and sustainable landscapes.
C1 [Zandvoort, Mark; Kooijmans, Nora; van den Brink, Adri] Wageningen Univ, Dept Environm Sci, Landscape Architecture Chair Grp, Droevendaalsesteeg 3, NL-6708 PB Wageningen, Netherlands.
   [Kirshen, Paul] Univ Massachusetts, Sch Environm, Sustainable Solut Lab, Boston, MA 02125 USA.
C3 Wageningen University & Research; University of Massachusetts System;
   University of Massachusetts Boston
RP Zandvoort, M (corresponding author), Wageningen Univ, Dept Environm Sci, Landscape Architecture Chair Grp, Droevendaalsesteeg 3, NL-6708 PB Wageningen, Netherlands.
EM mark.zandvoort@wur.nl; n.a.kooijmans@gmail.com; paul.kirshen@umb.edu;
   adri.vandenbrink@wur.nl
OI van den Brink, Adri/0000-0002-8403-7470; Zandvoort,
   Mark/0000-0001-6207-7562
CR Abbott M., 2018, LANDSC REV, V18, P89
   [Anonymous], THESIS
   [Anonymous], [No title captured]
   [Anonymous], 1990, Report of the IPCC coastal zone management subgroup: Intergovernmental Panel on Climate Change
   [Anonymous], THESIS
   [Anonymous], 2013, EEA Report No. 3/2013
   Batty M., 2012, Complexity Theories of Cities Have Come of Age
   Bell S., 2012, Landscape: Pattern
   BRAG, 2016, CLIM CHANG SEA LEV R
   Buurman J, 2016, POLICY SOC, V35, P137, DOI 10.1016/j.polsoc.2016.05.002
   Campos IS, 2016, ECOL SOC, V21, DOI 10.5751/ES-08059-210113
   City of Boston, 2016, CLIM READ BOST FIN R
   Deming E., 2011, Landscape architecture research inquiry, strategy, design
   Douglas EM, 2012, MITIG ADAPT STRAT GL, V17, P537, DOI 10.1007/s11027-011-9340-8
   Farthing Stuart., 2016, Research Design in Urban Planning
   Francis M., 2001, Landscape Journal, V20, P15, DOI [DOI 10.3368/LJ.20.1.15, 10.3368/lj.20.1, DOI 10.3368/LJ.20.1, 10.3368/lj.20.1.15]
   Gersonius B, 2013, CLIMATIC CHANGE, V116, P411, DOI 10.1007/s10584-012-0494-5
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Holmes R., 2010, MEASUREMENT BEDLOAD
   Howard Z, 2014, CODESIGN, V10, P46, DOI 10.1080/15710882.2014.881883
   Innes JudithEleanor., 2010, Planning with complexity: an introduction to collaborative rationality for public policy
   Karakaya E, 2018, J CLEAN PROD, V195, P651, DOI 10.1016/j.jclepro.2018.05.142
   Kirshen P., 2018, Journal of Extreme Events, 05, P1850013
   Kirshen P, 2008, CLIMATIC CHANGE, V90, P453, DOI 10.1007/s10584-008-9398-9
   Kuhl L, 2014, CLIMATIC CHANGE, V127, P493, DOI 10.1007/s10584-014-1273-2
   Kwadijk JCJ, 2010, WIRES CLIM CHANGE, V1, P729, DOI 10.1002/wcc.64
   Kwakkel Jan H., 2010, International Journal of Technology, Policy and Management, V10, P299, DOI 10.1504/IJTPM.2010.036918
   Lawrence J, 2017, ENVIRON SCI POLICY, V68, P47, DOI 10.1016/j.envsci.2016.12.003
   Lenzholzer S, 2013, LANDSCAPE URBAN PLAN, V113, P120, DOI 10.1016/j.landurbplan.2013.02.003
   Markard J, 2011, J INFRASTRUCT SYST, V17, P107, DOI 10.1061/(ASCE)IS.1943-555X.0000056
   Moroni S, 2015, PLAN THEOR, V14, P248, DOI 10.1177/1473095214521104
   Murphy DJ, 2017, LANDSCAPE URBAN PLAN, V167, P441, DOI 10.1016/j.landurbplan.2017.07.016
   Ramm TD, 2018, ENVIRON SCI POLICY, V87, P92, DOI 10.1016/j.envsci.2018.06.001
   Rauws W, 2016, ENVIRON PLANN B, V43, P1052, DOI 10.1177/0265813516658886
   Ray P. A., 2015, Confronting climate uncertainty in water resources planning and project design: The decision tree framework
   Reeder T., 2010, LESSONS THAMES ESTUA
   RIZA, 2003, VERK OPL VOLK ZOOMM
   Skrimizea E, 2019, PLAN THEOR, V18, P122, DOI 10.1177/1473095218780515
   Stremke S, 2012, EUR PLAN STUD, V20, P305, DOI 10.1080/09654313.2012.650909
   Thomas G, 2011, OXFORD REV EDUC, V37, P21, DOI 10.1080/03054985.2010.521622
   Van Assche K, 2011, J ENVIRON PLANN MAN, V54, P997, DOI 10.1080/09640568.2010.547687
   van den Brink A, 2014, LANDSCAPE RES, V39, P7, DOI 10.1080/01426397.2012.711129
   van den Brink Adri., 2017, Research in Landscape Architecture: methods and methodology
   van Dijk T, 2011, PLAN THEOR, V10, P124, DOI 10.1177/1473095210386656
   van Rhee G., 2012, Handreiking Adaptief Deltamanagement
   Wang T., 2004, P 8 REAL OPT ANN INT
   Weaver CP, 2013, WIRES CLIM CHANGE, V4, P39, DOI 10.1002/wcc.202
   Wilson PI, 2015, SOC NATUR RESOUR, V28, P109, DOI 10.1080/08941920.2014.948239
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
   Zandvoort M., 2017, THESIS
   Zandvoort M, 2019, J ENVIRON PLANN MAN, V62, P248, DOI 10.1080/09640568.2017.1409196
   Zandvoort M, 2017, ENVIRON SCI POLICY, V78, P18, DOI 10.1016/j.envsci.2017.08.017
NR 53
TC 7
Z9 7
U1 8
U2 44
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD FEB 1
PY 2019
VL 11
IS 3
AR 565
DI 10.3390/su11030565
PG 24
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA HL7NY
UT WOS:000458929500010
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Nguyen-Trung, K
   Saeri, AK
   Kaufman, S
AF Nguyen-Trung, Kien
   Saeri, Alexander K.
   Kaufman, Stefan
TI Incorporating pragmatism in a behaviour change-led climate adaptation
   project: a collaborative reflection
SO QUALITATIVE RESEARCH JOURNAL
LA English
DT Article; Early Access
DE Abductive reasoning; Behaviour change; Climate adaptation; Critical
   reflection; Knowledge co-production; Pragmatism; Qualitative research
ID REFLEXIVITY
AB PurposeThis article argues the value of integrating pragmatism in applying behavioural science to complex challenges. We describe a behaviour change-led knowledge co-production process in the specific context of climate change in Australia. This process was led by an interdisciplinary research team who struggled with the limitations of the prevailing deterministic behaviour change paradigms, such as the "test, learn, adapt" model, which often focuses narrowly on individual behaviours and fails to integrate multiple interpretations from diverse stakeholders into their knowledge co-production process.Design/methodology/approachThis article uses collaborative reflection as a method of inquiry. We document the team's experience of a recent challenge-led, programatic research initiative that applied behaviour change strategies to reduce climate vulnerabilities. We demonstrate the necessity of critical reflection and abductive reasoning in the face of the complexities inherent in knowledge co-production addressing complex problems. It underscores the importance of accommodating diverse perspectives and contextual nuances over a one-size-fits-all method.FindingsThe article shares lessons learnt about integrating collaborative and critical reflection throughout a project cycle and demonstrates the capacity of abductive reasoning to ease the challenges arising from the tension between behaviour change paradigms and knowledge co-production principles. This approach allows for a more adaptable and context-sensitive application, acknowledging the multiplicity of understandings and the dynamic nature of behavioural change in relation to climate adaptation.Originality/valueThis reflection contributes original insights into the fusion of pragmatism with behaviour change strategies, proposing a novel framework that prioritises flexibility, context-specificity and the recognition of various stakeholder perspectives in the co-production of knowledge.
C1 [Nguyen-Trung, Kien; Saeri, Alexander K.; Kaufman, Stefan] Monash Univ, Monash Sustainable Dev Inst, Behav Works Australia, Melbourne, Vic, Australia.
   [Nguyen-Trung, Kien] Monash Univ, Monash Sustainable Dev Inst, Water Sensit Cities Australia, Melbourne, Vic, Australia.
C3 Monash University; Monash University
RP Nguyen-Trung, K (corresponding author), Monash Univ, Monash Sustainable Dev Inst, Behav Works Australia, Melbourne, Vic, Australia.; Nguyen-Trung, K (corresponding author), Monash Univ, Monash Sustainable Dev Inst, Water Sensit Cities Australia, Melbourne, Vic, Australia.
EM kien.nguyen@monash.edu
RI Nguyen, Kien/AAE-8594-2021; Kaufman, Stefan/K-6786-2018
OI Nguyen, Kien/0000-0002-1782-7405; Kaufman, Stefan/0000-0001-7973-3845
FU Monash Sustainable Development Institute, Monash University
FX The authors would like to thank Monash Sustainable Development
   Institute, Monash University, for providing funding for this manuscript.
   The authors also would like to thank their colleagues at BehaviourWorks
   Australia for their support.
CR Adkins L, 2003, THEOR CULT SOC, V20, P21, DOI 10.1177/0263276403206002
   Boulet M, 2022, J ENVIRON MANAGE, V308, DOI 10.1016/j.jenvman.2022.114681
   Boulet M, 2021, APPETITE, V156, DOI 10.1016/j.appet.2020.104856
   Bourdieu P., 1997, Outline of a Theory of Practice, DOI DOI 10.1017/CBO9780511812507
   Bourdieu Pierre., 1977, CAMBRIDGE STUDIES SO, DOI [10.1017/CBO9780511812507, DOI 10.1017/CBO9780511812507]
   Braun V, 2022, QUAL PSYCHOL, V9, P3, DOI 10.1037/qup0000196
   Braun V, 2021, COUNS PSYCHOTHER RES, V21, P37, DOI 10.1002/capr.12360
   Braun V, 2021, QUAL RES SPORT EXERC, V13, P201, DOI 10.1080/2159676X.2019.1704846
   Braun V, 2019, QUAL RES SPORT EXERC, V11, P589, DOI 10.1080/2159676X.2019.1628806
   Braun V, 2021, QUAL RES PSYCHOL, V18, P328, DOI 10.1080/14780887.2020.1769238
   Brierley J.A., 2017, International Journal of Behavioural Accounting and Finance, V6, P140, DOI [10.1504/IJBAF.2017.10007499, DOI 10.1504/IJBAF.2017.086432]
   BRONFENBRENNER U, 1977, AM PSYCHOL, V32, P513, DOI 10.1037/0003-066x.32.7.513
   Bronfenbrenner U., 1979, ECOLOGY HUMAN DEV EX, P330
   Bryan CJ, 2021, NAT HUM BEHAV, V5, P980, DOI 10.1038/s41562-021-01143-3
   Cash PJ, 2017, DESIGN STUD, V48, P96, DOI 10.1016/j.destud.2016.10.001
   Chater N., 2022, Behav. Brain Sci., P1
   Ewert B, 2020, PUBLIC POLICY ADMIN, V35, P337, DOI 10.1177/0952076719889090
   Fook J., 2007, Practising Critical Reflection
   Fook J., 2012, Critical Reflection in Context
   Gaillard JC, 2022, DISASTER PREV MANAG, V31, P333, DOI 10.1108/DPM-08-2022-419
   Giddens A., 2013, CONSEQUENCES MODERNI
   Grundy E., 2021, report), DOI [10.26180/23951049.v3, DOI 10.26180/23951049.V3]
   Hallsworth M, 2023, NAT HUM BEHAV, V7, P310, DOI 10.1038/s41562-023-01555-3
   Hansen Pelle Guldborg., 2018, Behavioural Public Policy, V2, DOI DOI 10.1017/BPP.2018.13
   John P, 2019, POLICY POLIT, V47, P209, DOI 10.1332/030557319X15526371698257
   Kaufman S., 2021, Behaviour change in a changing climate: scoping paper in support of missions-based research and innovation for the BWA Consortium (report), DOI [10.26180/23961504.v1, DOI 10.26180/23961504.V1]
   Kaufman S, 2021, ENVIRON INNOV SOC TR, V40, P586, DOI 10.1016/j.eist.2021.10.010
   Kelly L.M., 2020, Methodological Innovations, V13, P1, DOI [10.1177/2059799120937242, DOI 10.1177/2059799120937242]
   Kerr ZY, 2014, BRAIN INJURY, V28, P1009, DOI 10.3109/02699052.2014.904049
   Lamaison P., 1986, Cultural Anthropology, V1, P110
   Lash S, 2003, THEOR CULT SOC, V20, P49, DOI 10.1177/0263276403020002003
   LASH S., 1994, Reflexive modernization, P198
   Leonard TC, 2008, CONST POLITICAL ECON, V19, P356, DOI 10.1007/s10602-008-9056-2
   Lupton D, 2021, QUAL RES, V21, P463, DOI 10.1177/1468794120939235
   Mazzucato M., 2018, European Commission, Research and Innovation, V36
   Michie S, 2011, IMPLEMENT SCI, V6, DOI 10.1186/1748-5908-6-42
   Miro, 2024, About Miro
   Morgan DL, 2007, J MIX METHOD RES, V1, P48, DOI 10.1177/2345678906292462
   Morgan DL, 2020, QUAL REP, V25, P64
   Morgan DL, 2014, QUAL INQ, V20, P1045, DOI 10.1177/1077800413513733
   Nguyen-Trung K., 2023, A brief introduction to a socio-ecological COM-B (SeCOM-B): a behaviour change framework response to wicked problems, DOI [10.31219/osf.io/4x6wa, DOI 10.31219/OSF.IO/4X6WA]
   Nguyen-Trung K, 2023, DISASTER PREV MANAG, V32, P298, DOI 10.1108/DPM-05-2022-0118
   Nguyen-Trung K, 2022, SOCIOL RES ONLINE, V27, P932, DOI 10.1177/13607804221133120
   Norris E, 2014, PSYCHOLOGIST, V27, P709
   Norstrom AV, 2020, NAT SUSTAIN, V3, P182, DOI 10.1038/s41893-019-0448-2
   Reynolds M, 1998, MANAGE LEARN, V29, P183, DOI 10.1177/1350507698292004
   RITTEL HWJ, 1973, POLICY SCI, V4, P155, DOI 10.1007/BF01405730
   Saeri A., 2023, Trial Report: DJAARA-Led Adaptation Forum for Local Governments
   Schimmelpfennig R, 2023, BEHAV PUBLIC POLICY, DOI 10.1017/bpp.2022.40
   Shove E, 2010, ENVIRON PLANN A, V42, P1273, DOI 10.1068/a42282
   Straβheim H., 2020, International Review of Public Policy, V2, P115
   Zoom Video Communications, 2024, About Zoom
NR 52
TC 2
Z9 2
U1 3
U2 3
PU EMERALD GROUP PUBLISHING LTD
PI Leeds
PA Floor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE,
   ENGLAND
SN 1443-9883
EI 1448-0980
J9 QUAL RES J
JI Qual. Res. J.
PD 2024 APR 23
PY 2024
DI 10.1108/QRJ-11-2023-0168
EA APR 2024
PG 14
WC Social Sciences, Interdisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Social Sciences - Other Topics
GA OF0R9
UT WOS:001205739000001
DA 2025-01-10
ER

PT J
AU Rosa, M
   Haines, K
   Cruz, T
   Forman, F
AF Rosa, Melissa
   Haines, Kyle
   Cruz, Teddy
   Forman, Fonna
TI A binational social vulnerability index (BSVI) for the San Diego-Tijuana
   region: mapping trans-boundary exposure to climate change for just and
   equitable adaptation planning
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Climate change; Social vulnerability; Climate adaptation; Urban
   planning; US-Mexico border
ID ENVIRONMENTAL JUSTICE; MEXICO BORDER; GLOBAL CHANGE; LAND-USE;
   COMMUNITY; RIVER; CALIFORNIA; RISK
AB To pursue just, inclusive, and participatory climate adaptation planning and policy, it is important to understand both regional climate trends and the ecological services that reduce vulnerability and exposure to climate risks at the community level. Rapidly growing cities like Tijuana and San Diego are doubly exposed to climate change because they have fewer resources to confront them and yet responsible for basic services that support everyday life of their residents, challenges that are complicated by the divided institutional and social context of an international border region. In the binational context, the regional community is fragmented by institutional, academic, and cultural factors, leading to adaptation planning that stops at the border despite the shared ecological setting of human settlements. This fragmentation is particularly dangerous for climate adaptation planning because it obscures inequalities as well as opportunities contained in the binational region. To address this deficit, we have synthesized information from a variety of regional spatial datasets to construct a continuous binational social vulnerability index (BSVI) at the census tract level across the San Diego-Tijuana border region. This paper details the datasets and methodology used to create the BSVI and explores some of the preliminary results of the analysis by juxtaposing this score with spatially explicit information on vegetation cover and climate projections of heat and rainfall extremes across the region. We close with a discussion on use of this research as a tool for local environmental justice and regional adaptation.
C1 [Rosa, Melissa; Haines, Kyle; Cruz, Teddy; Forman, Fonna] Univ Calif San Diego, UC San Diego Ctr Global Justice, 9500 Gilman Dr,MC 0523, La Jolla, CA 92093 USA.
C3 University of California System; University of California San Diego
RP Rosa, M (corresponding author), Univ Calif San Diego, UC San Diego Ctr Global Justice, 9500 Gilman Dr,MC 0523, La Jolla, CA 92093 USA.
EM mrosa@ucsd.edu; kyhaines@ucsd.edu; etcruz@ucsd.edu; fforman@ucsd.edu
OI Haines, Kyle/0000-0002-1750-9044; Rosa, Melissa/0000-0001-8474-7926
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Aguilera Fernandez A., 2017, FRONTERA NORTE, V30, P85
   Aguilera J, 2021, TIME
   Agyeman J, 2016, ANNU REV ENV RESOUR, V41, P321, DOI 10.1146/annurev-environ-110615-090052
   Alvarez R, 2012, J LAT AM CARIBB ANTH, V17, P24, DOI 10.1111/j.1935-4940.2012.01191.x
   Anderson JB, 2003, SOC SCI J, V40, P535, DOI 10.1016/S0362-3319(03)00067-3
   Anderson JB, 2023, J BORDERL STUD, V38, P1, DOI 10.1080/08865655.2020.1855229
   [Anonymous], 2010, Climate Action Plan Tax, City of Boulder, Colorado
   Avashia V, 2021, LANDSCAPE URBAN PLAN, V212, DOI 10.1016/j.landurbplan.2021.104107
   Bedsworth L., 2018, California's fourth climate change assessment: Statewide summary report
   Biggs TW, 2015, PROF GEOGR, V67, P166, DOI 10.1080/00330124.2014.905161
   Boulton C, 2018, LANDSCAPE URBAN PLAN, V178, P82, DOI 10.1016/j.landurbplan.2018.05.029
   Carruthers DV, 2008, SOC NATUR RESOUR, V21, P556, DOI 10.1080/08941920701648812
   Celermajer D, 2021, ENVIRON POLIT, V30, P119, DOI 10.1080/09644016.2020.1827608
   Clough-Riquelme J, 2006, EQUITY SUSTAINABLE D
   Coats S, 2015, J CLIMATE, V28, P2025, DOI 10.1175/JCLI-D-14-00634.1
   Costello A.B., 2005, PRACTICAL ASSESSMENT, DOI [10.7275/jyj1-4868, 10.7275/JYJ1-4868, DOI 10.7275/JYJ1-4868]
   Cruz T, 2023, TOP DOWNBOTTOM
   Cruz T, 2020, ARCHIT DESIGN, V90, P114, DOI 10.1002/ad.2534
   Cutter S.L., 2017, Social Vulnerability Index (SoVI): Methodology and Limitations
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Dalby S, 2014, GLOB POLICY, V5, P1, DOI 10.1111/1758-5899.12074
   Dawson B, 2022, THE INSIDER
   DeFries RS, 2012, BIOSCIENCE, V62, P603, DOI 10.1525/bio.2012.62.6.11
   Dimento J, 2017, UC OFFICE PRESIDENT
   Dominguez-Madrid AY, 2016, THESIS COLEGIO FRONT
   Eaton-Gonzalez R, 2015, LAND-BASEL, V4, P1138, DOI 10.3390/land4041138
   Mendoza JE, 2020, J BORDERL STUD, V35, P55, DOI 10.1080/08865655.2017.1367711
   Farley KA, 2012, LAND USE POLICY, V29, P187, DOI 10.1016/j.landusepol.2011.06.006
   Flanagan BE, 2011, J HOMEL SECUR EMERG, V8, DOI 10.2202/1547-7355.1792
   Forman F., 2016, Chapter 8. Bending the Curve and Closing the Gap: Climate Justice and Public Health, V2, P1, DOI DOI 10.1525/COLLABRA.67
   Ganster P, 2017, J BORDERL STUD, V32, P497, DOI 10.1080/08865655.2016.1198582
   Gardiner S.M., 2011, The perfect moral storm: The ethical tragedy of climate change, DOI 10.1093/acprof:oso/9780195379440.001.0001
   Gershunov A., 2011, GEOGRAPHY RES FORUM, V31, P6
   Goodrich KA, 2020, CURR OPIN ENV SUST, V42, P45, DOI 10.1016/j.cosust.2020.01.001
   Gordon DJ, 2017, ENVIRON POLIT, V26, P694, DOI 10.1080/09644016.2017.1320829
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Grineski SE, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/9/095012
   Grineski SE, 2012, APPL GEOGR, V33, P25, DOI 10.1016/j.apgeog.2011.05.013
   Gudino NE, 2021, PREPRINT
   Haines Kyle., 2015, Glocalism: Journal of Culture, Politics and Innovation
   Hansen J, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/034009
   Hartmann DL, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P159
   Hayward T, 2012, NAT CLIM CHANGE, V2, P843, DOI 10.1038/NCLIMATE1615
   INEGI, 2010, INEGI EC CENS 2009
   Lager F, 2021, ADAPTATION BORDERS P
   Lara-Valencia F, 2012, US MEXICAN BORDER EN, P267
   Liverman DM, 2006, ANNU REV ENV RESOUR, V31, P327, DOI 10.1146/annurev.energy.29.102403.140729
   Malloy JT, 2020, CLIMATIC CHANGE, V160, P1, DOI 10.1007/s10584-020-02705-6
   Martinez-Alier J, 2016, J PEASANT STUD, V43, P731, DOI 10.1080/03066150.2016.1141198
   McCarthy N., 2021, Forbes
   McLeman R, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-03056-6
   Moellendorf D., 2014, MORAL CHALLENGE DANG, DOI [10.1017/CBO9781139083652, DOI 10.1017/CBO9781139083652]
   National Environmental Justice Advisory Committee (NEJAC), 2002, NEJAC INT ROUNDTABLE
   Neri C, 2016, WEATHER CLIM SOC, V8, P95, DOI 10.1175/WCAS-D-15-0005.1
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Ojeda-Revah L, 2008, APPL VEG SCI, V11, P107, DOI 10.1111/j.1654-109X.2008.tb00209.x
   Ojeda-Revah L, 2008, ECON SOC TERRIT, V8, P517
   González AOO, 2012, ENG FAIL ANAL, V19, P51, DOI 10.1016/j.engfailanal.2011.09.005
   Pena S., 2015, Sociedad y Ambiente, V1, P47
   Pfahl S, 2017, NAT CLIM CHANGE, V7, P423, DOI [10.1038/NCLIMATE3287, 10.1038/nclimate3287]
   Pierce D.W., 2018, Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California's Fourth Climate Change Assessment
   Prado C, 2019, J ENVIRON POL PLAN, V21, P662, DOI 10.1080/1523908X.2019.1665991
   Quiñonez-Plaza A, 2017, J SOIL SEDIMENT, V17, P2873, DOI 10.1007/s11368-017-1778-1
   Quintana PJE, 2015, J BORDERL STUD, V30, P287, DOI 10.1080/08865655.2015.1066697
   Rivlin-Nadler M, 2021, INSIDE MIGRANT CAMP
   Rogers P, 2022, MERCURY NEWS
   Ruiz-Gibert JM, 2020, INT J RIVER BASIN MA, V18, P445, DOI 10.1080/15715124.2019.1597727
   San Diego Foundation, 2013, SAN DIEG CHANG CLIM
   Sánchez Rodríguez Roberto, 2014, Frontera norte, V26, P99
   Rodríguez RAS, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10072352
   Schlosberg D, 2017, ENVIRON POLIT, V26, P413, DOI 10.1080/09644016.2017.1287628
   Schlosberg D, 2010, GLOBAL ENVIRON POLIT, V10, P12, DOI 10.1162/GLEP_a_00029
   Schlosberg David., 2007, DEFINING ENV JUSTICE
   Secretaria de Proteccion al Ambiente & Baja California and Border Environment Cooperation Commission, 2014, FIN REP BAJ CAL PHAS
   Sen A., 1999, Development as freedom, V1st
   Shonkoff SB, 2011, CLIMATIC CHANGE, V109, P485, DOI 10.1007/s10584-011-0310-7
   Suarez-Orozco M.M., 2019, Humanitarianism and mass migration: Confronting the world crisis, V1st, P43
   United Nations Framework Convention on Climate Change, 2021, C PARTIES PARIS AGRE
   US Census Bureau, 2010, US CENS BUR 2010 CEN
   USGS, NDVI FDN REM SENS PH
   Warth G., 2022, SAN DIEGO UNION TRIB
   Wilder M, 2016, LOCAL ENVIRON, V21, P1332, DOI 10.1080/13549839.2015.1116063
   Wilder M, 2013, NCA REGION INPUT REP, P340, DOI 10.5822/978-1-61091-484-0_16
   Wilder M, 2010, ANN ASSOC AM GEOGR, V100, P917, DOI 10.1080/00045608.2010.500235
NR 85
TC 3
Z9 5
U1 5
U2 12
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1381-2386
EI 1573-1596
J9 MITIG ADAPT STRAT GL
JI Mitig. Adapt. Strateg. Glob. Chang.
PD FEB
PY 2023
VL 28
IS 2
AR 12
DI 10.1007/s11027-023-10045-w
PG 23
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 9R0VC
UT WOS:000945373300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Jim, CY
AF Jim, C. Y.
TI Assessing climate-adaptation effect of extensive tropical green roofs in
   cities
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Climate adaptation; Cooling load; Extensive green roof; Greenery
   infilling; Heat sink effect; Urban heat island
ID RESIDENTIAL BUILDINGS; COMPACT CITY; SKY GARDENS; HEAT-ISLAND;
   HONG-KONG; PERFORMANCE; MANAGEMENT; TRENDS; AREAS
AB Many cities have inadequate green infrastructures and cannot benefit from ecosystem services brought by greenspaces. Global warming and urban heat island (UHI) effect impose a dual warming impact on cities, especially compact ones. Green roofs offer a plausible solution for climate adaptation. In compact humid-tropical Hong Kong, two green-roof and a control bare-roof plots were installed on a high-rise building. Precision sensors were installed along a holistic vertical temperature profile extending from outdoor air to roof surface, green-roof material layers, and indoor ceiling and air. Three apartments under the plots were kept vacant to monitor air-conditioning energy consumption. The comprehensive-systematic data allowed in-depth analysis of thermal performance of vegetation (Sedum and Perennial Peanut) and weather (sunny, cloudy and rainy) in summer. Intense solar radiation at Control plot triggered significant material heating, which in turn warmed near-ground air to intensify UHI effect and indoor space to lift energy consumption. Sedum plot with incomplete plant cover, sluggish transpiration and limited substrate moisture storage had feeble evapotranspiration cooling. The warmed roof passed heat to near-ground air and subsurface layers to impose a small indoor cooling load. Peanut plot with high transpiration rate can significantly cool foliage surface and near-ground air to ameliorate UHI. Its high moisture-holding capacity, however, can generate an appreciable heat-sink to push heat downwards and increase indoor cooling load. Practical hints on green roof design and management were distilled from the findings for application in Hong Kong and beyond and to contribute to climate-resilient cities. (C) 2015 Elsevier B.V. All rights reserved.
C1 Univ Hong Kong, Dept Geog, Hong Kong, Hong Kong, Peoples R China.
C3 University of Hong Kong
RP Jim, CY (corresponding author), Univ Hong Kong, Dept Geog, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China.
EM hragjcy@hku.hk
RI Jim, CY/O-1025-2019
OI Jim, C.Y./0000-0003-4052-8363
FU Hong Kong Housing Authority
FX The research grant kindly awarded by the Hong Kong Housing Authority is
   gratefully acknowledged. The support and encouragement offered by Ms Ada
   Fung is warmly appreciated. Thanks are extended to Jeannette Liu, Wing
   Yiu Wong and Cyrus Lam for providing laborious field-work assistance,
   and Tina Tsang for cartographic support.
CR Akbari H, 2005, ENERG POLICY, V33, P721, DOI 10.1016/j.enpol.2003.10.001
   [Anonymous], 498 ENGL NAT
   [Anonymous], 2002, GROWING MEDIA ORNAME
   Australian Centre for International Agricultural Research, 2013, TROP FOR AR PINT
   Bass B., 2003, C GREEN ROOFT SUST C
   Berghage R.D, 2009, PUBLICATION NO600 R
   Blanusa T, 2013, BUILD ENVIRON, V59, P99, DOI 10.1016/j.buildenv.2012.08.011
   Bojic M, 2005, ENERG BUILDINGS, V37, P345, DOI 10.1016/j.enbuild.2004.07.003
   Bojic M, 2002, ENERG CONVERS MANAGE, V43, P165, DOI 10.1016/S0196-8904(01)00018-8
   Brenneisen Stephan, 2006, Urban Habitats, V4, P27
   Brown R., 2015, Landscape and Urban Planning, P1
   Byrne J. A., 2015, LANDSCAPE URBAN PLAN
   Carter T, 2007, LANDSCAPE URBAN PLAN, V80, P84, DOI 10.1016/j.landurbplan.2006.06.005
   Castleton HF, 2010, ENERG BUILDINGS, V42, P1582, DOI 10.1016/j.enbuild.2010.05.004
   Census and Statistics Department, 2013, POP OV
   Chan HS, 2012, CLIM RES, V55, P53, DOI 10.3354/cr01133
   Chen WY, 2011, J ENVIRON PLANN MAN, V54, P851, DOI 10.1080/09640568.2010.537552
   Cheng V, 2012, INT J BIOMETEOROL, V56, P43, DOI 10.1007/s00484-010-0396-z
   College of Tropical Agriculture and Human Resources, 2013, COV CROP LEG PER PEA
   Del Barrio EP, 1998, ENERG BUILDINGS, V27, P179
   Electrical & Mechanical Services Department, 2013, HONG KONG EN END US
   Emmanuel R., 2015, Landscape and Urban Planning
   Environmental Protection Department, 2013, CLIM CHANG EL CONS
   FLL, 2008, GUID PLANN EX UPK GR
   Getter KL, 2006, HORTSCIENCE, V41, P1276, DOI 10.21273/HORTSCI.41.5.1276
   Getter KL, 2011, ENERG BUILDINGS, V43, P3548, DOI 10.1016/j.enbuild.2011.09.018
   Givoni B, 2011, SOL ENERGY, V85, P1692, DOI 10.1016/j.solener.2009.10.003
   Hall JM, 2012, LANDSCAPE URBAN PLAN, V104, P410, DOI 10.1016/j.landurbplan.2011.11.015
   Hien WN, 2007, BUILD ENVIRON, V42, P25, DOI 10.1016/j.buildenv.2005.07.030
   Hong Kong Observatory, 2013, STAT SPEC WEATH EV
   Jim CY, 2015, ECOL ENG, V77, P348, DOI 10.1016/j.ecoleng.2015.01.021
   Jim CY, 2015, LANDSCAPE URBAN PLAN, V137, P107, DOI 10.1016/j.landurbplan.2015.01.001
   Jim CY, 2014, ECOL ENG, V62, P1, DOI 10.1016/j.ecoleng.2013.10.022
   Jim CY, 2012, LANDSC ECOL ENG, V8, P173, DOI 10.1007/s11355-011-0161-4
   Jim CY, 2012, URBAN FOR URBAN GREE, V11, P73, DOI 10.1016/j.ufug.2011.10.001
   Jim CY, 2011, ENERG BUILDINGS, V43, P2696, DOI 10.1016/j.enbuild.2011.06.018
   Jim CY, 2011, ENERG BUILDINGS, V43, P1341, DOI 10.1016/j.enbuild.2011.01.012
   Jim CY, 1996, COMMUN SOIL SCI PLAN, V27, P2049, DOI 10.1080/00103629609369687
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Klemm W., 2015, Landscape and Urban Planning, P1
   Koehler M, 2004, INT GREEN ROOF C 14, P72
   Lam TNT, 2010, APPL ENERG, V87, P2321, DOI 10.1016/j.apenergy.2009.11.003
   Lee TC, 2011, ADV ATMOS SCI, V28, P147, DOI 10.1007/s00376-010-9160-x
   Lee TC, 2010, 16 ANN INT SUST DEV
   Mathey J, 2011, LOCAL SUSTAIN, V1, P479, DOI 10.1007/978-94-007-0785-6_47
   Matthews T., 2015, LANDSCAPE URBAN PLAN
   Mazhar N., 2015, LANDSCAPE URBAN PLAN
   Milburn L. A. S., 2013, WASTED SPACE ALTERIN
   Niachou A, 2001, ENERG BUILDINGS, V33, P719, DOI 10.1016/S0378-7788(01)00062-7
   Parsons K., 2003, EFFECTS HOT MODERATE, V2nd
   Snodgrass E.C. Snodgrass., 2006, GREEN ROOF PLANTS RE, V3rd
   Stephenson R., 1994, Sedum: Cultivated Stonecrops
   Susca T, 2011, ENVIRON POLLUT, V159, P2119, DOI 10.1016/j.envpol.2011.03.007
   Svendsen E., 2012, Cities Environ, V5, P1, DOI [DOI 10.15365/CATE.5132012, 10.15365/cate.5132012]
   Tan P. Y., 2008, SELECTION PLANTS GRE
   Tan P. Y., 2003, C GREEN ROOFT SUST C
   Teemusk A, 2009, BUILD ENVIRON, V44, P643, DOI 10.1016/j.buildenv.2008.05.011
   Theodosiou T., 2013, INT J SUSTAINABLE EN
   Tian YH, 2012, URBAN FOR URBAN GREE, V11, P223, DOI 10.1016/j.ufug.2012.03.003
   Tian YH, 2011, LANDSCAPE URBAN PLAN, V101, P299, DOI 10.1016/j.landurbplan.2011.02.035
   Tso GKF, 2003, ENERGY, V28, P1671, DOI 10.1016/S0360-5442(03)00153-1
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   US Environmental Protection Agency (EPA), 2009, RED URB HEAT ISL COM
   Voyde E, 2010, J HYDROL ENG, V15, P395, DOI 10.1061/(ASCE)HE.1943-5584.0000141
NR 64
TC 84
Z9 89
U1 9
U2 209
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0169-2046
EI 1872-6062
J9 LANDSCAPE URBAN PLAN
JI Landsc. Urban Plan.
PD JUN
PY 2015
VL 138
SI SI
BP 54
EP 70
DI 10.1016/j.landurbplan.2015.02.014
PG 17
WC Ecology; Environmental Studies; Geography; Geography, Physical; Regional
   & Urban Planning; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography; Physical Geography; Public
   Administration; Urban Studies
GA CI8LE
UT WOS:000355023000007
DA 2025-01-10
ER

PT J
AU Gamalei, YV
AF Gamalei, Yu V.
TI The origin and evolution of higher plants
SO HERALD OF THE RUSSIAN ACADEMY OF SCIENCES
LA English
DT Article
AB This article, based on a paper presented at a RAS Presidium meeting, considers modern ideas on the origin and the main milestones in the evolution of higher plants. The history of their rise, water and air migrations, and participation in pedogenic processes is reconstructed proceeding from the structure of transport communications that were formed in the course of algal-mycobacterial symbiogenesis as buffer zones of exchange between the participants. Proceeding from further transformations of transport networks, regularities of the climatic adaptogenesis of higher plant forms in the Cenozoic are discussed.
C1 RAS, Komarov Bot Inst, Environm Physiol Lab, Moscow, Russia.
C3 Russian Academy of Sciences; Komarov Botanical Institute, Russian
   Academy of Sciences
RP Gamalei, YV (corresponding author), RAS, Komarov Bot Inst, Environm Physiol Lab, Moscow, Russia.
FU RAS Presidium; Russian Foundation for Basic Research [07-04-00834,
   10-04-01165]
FX This paper was supported by the RAS Presidium program Problems of the
   Origin of Life and the Development of the Biosphere and by grants of the
   Russian Foundation for Basic Research (project nos. 07-04-00834 and
   10-04-01165).
NR 0
TC 1
Z9 1
U1 2
U2 9
PU MAIK NAUKA/INTERPERIODICA/SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013-1578 USA
SN 1019-3316
J9 HER RUSS ACAD SCI+
JI Her. Russ. Acad. Sci.
PD JUL
PY 2012
VL 82
IS 4
BP 246
EP 254
DI 10.1134/S1019331612040028
PG 9
WC History & Philosophy Of Science; Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC History & Philosophy of Science; Science & Technology - Other Topics
GA 995VD
UT WOS:000308041000003
DA 2025-01-10
ER

PT J
AU Wang, SM
   Ma, YT
   Gong, J
   Jin, TT
AF Wang, Shimei
   Ma, Yutao
   Gong, Jie
   Jin, Tiantian
TI Dynamic Variation of Vegetation NPP and Its Driving Forces in the Yellow
   River Basin, China
SO CHINESE GEOGRAPHICAL SCIENCE
LA English
DT Article; Early Access
DE Net Primary Productivity (NPP); vegetation greening;
   Carnegie-Ames-Stanford Approach (CASA); Lund-Potsdam-Jena General
   Ecosystem Simulator (LPJ_GUESS); Yellow River Basin (YRB), China
ID NET PRIMARY PRODUCTIVITY; CLIMATE-CHANGE; QUANTITATIVE ASSESSMENT;
   SPATIAL-PATTERN; CARBON STOCK; TERRESTRIAL; VARIABILITY; GRASSLAND;
   ECOSYSTEMS; DEGRADATION
AB The productivity of vegetation is influenced by both climate change and human activities. Understanding the specific contributions of these influencing factors is crucial for ecological conservation and regional sustainability. This study utilized a combination of multi-source data to examine the spatiotemporal patterns of Net Primary Productivity (NPP) in the Yellow River Basin (YRB), China from 1982 to 2020. Additionally, a scenario-based approach was employed to compare Potential NPP (PNPP) with Actual NPP (ANPP) to determine the relative roles of climatic and human factors in NPP changes. The PNPP was estimated using the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) model, while ANPP was evaluated by the Carnegie-Ames-Stanford Approach (CASA) model using different NDVI data sources. Both model simulations revealed that significant greening occurring in the YRB, with a gradual decrease observed from southeast to northwest. According to the LPJ_GUESS model simulations, areas experiencing an increasing trend in NPP accounted for 86.82% of the YRB. When using GIMMS and MODIS NDVI data with CASA model simulations, areas showing an increasing trend in NPP accounted for 71.42% and 97.02%, respectively. Furthermore, both climatic conditions and human factors had positive effects on vegetation restoration; approximated 41.15% of restored vegetation areas were influenced by both climate variation and human activities, while around 31.93% were solely affected by climate variation. However, it was found that human activities served as the principal driving force of vegetation degradation within the YRB, impacting 26.35% of degraded areas solely due to human activities. Therefore, effective management strategies encompassing both human activities and climate change adaptation are imperative for facilitating vegetation restoration within this region. These findings will valuable for enhancing our understanding in NPP changes and its underlying factors, thereby contributing to improved ecological management and the pursuit of regional carbon neutrality in China.
C1 [Wang, Shimei; Ma, Yutao; Gong, Jie; Jin, Tiantian] Lanzhou Univ, Coll Earth & Environm Sci, Key Lab Western Chinas Environm Syst, Minist Educ, Lanzhou 730000, Peoples R China.
   [Ma, Yutao; Gong, Jie; Jin, Tiantian] Lanzhou Univ, Ctr Remote Sensing Ecol Environm Cold & Arid Reg, Lanzhou 730000, Peoples R China.
C3 Lanzhou University; Lanzhou University
RP Gong, J (corresponding author), Lanzhou Univ, Coll Earth & Environm Sci, Key Lab Western Chinas Environm Syst, Minist Educ, Lanzhou 730000, Peoples R China.; Gong, J (corresponding author), Lanzhou Univ, Ctr Remote Sensing Ecol Environm Cold & Arid Reg, Lanzhou 730000, Peoples R China.
EM jgong@lzu.edu.cn
RI Wang, Shimei/AAP-6273-2020; Gong, Jie/KMX-8624-2024
FU Centre for Scientific and Technical Information of the Slovak Republic
   [41991231, U21A2011]
FX Under the auspices of National Natural Science Foundation of China (No.
   41991231, U21A2011)
CR Ahlström A, 2015, SCIENCE, V348, P895, DOI 10.1126/science.aaa1668
   Bejagam V, 2022, ECOL INFORM, V70, DOI 10.1016/j.ecoinf.2022.101732
   Cao MK, 2004, ECOSYSTEMS, V7, P233, DOI 10.1007/s10021-003-0189-x
   Chen BX, 2014, AGR FOREST METEOROL, V189, P11, DOI 10.1016/j.agrformet.2014.01.002
   陈珊珊, 2022, [生态学报, Acta Ecologica Sinica], V42, P6439
   Chen T, 2020, SCI TOTAL ENVIRON, V743, DOI 10.1016/j.scitotenv.2020.140649
   Chen T, 2019, SCI TOTAL ENVIRON, V653, P1311, DOI 10.1016/j.scitotenv.2018.11.058
   Cramer W, 2001, GLOBAL CHANGE BIOL, V7, P357, DOI 10.1046/j.1365-2486.2001.00383.x
   Du XD, 2014, INT J ENV RES PUB HE, V11, P3215, DOI 10.3390/ijerph110303215
   Field CB, 1998, SCIENCE, V281, P237, DOI 10.1126/science.281.5374.237
   Foley JA, 2000, ECOL APPL, V10, P1620, DOI 10.1890/1051-0761(2000)010[1620:IDVCWG]2.0.CO;2
   Friedlingstein P., 2020, EARTH SYST SCI DATA, V12, P3269, DOI [10.5194/essd-12-3269-2020, DOI 10.5194/ESSD-12-3269-2020]
   Gao QZ, 2016, SCI REP-UK, V6, DOI 10.1038/srep26958
   Haberl H, 2007, P NATL ACAD SCI USA, V104, P12942, DOI 10.1073/pnas.0704243104
   He JJ, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103646
   Herrmann SM, 2005, GLOBAL ENVIRON CHANG, V15, P394, DOI 10.1016/j.gloenvcha.2005.08.004
   HOLBEN BN, 1986, INT J REMOTE SENS, V7, P1417, DOI 10.1080/01431168608948945
   Islam MR, 2024, AGR FOREST METEOROL, V349, DOI 10.1016/j.agrformet.2024.109959
   Ji YH, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-020-08593-8
   Jiang C, 2017, LAND USE POLICY, V69, P134, DOI 10.1016/j.landusepol.2017.08.019
   Jiang MC, 2021, SCI TOTAL ENVIRON, V786, DOI 10.1016/j.scitotenv.2021.147574
   Jiang WG, 2015, ECOL INDIC, V51, P117, DOI 10.1016/j.ecolind.2014.07.031
   Jiang YL, 2020, INT J BIOMETEOROL, V64, P765, DOI 10.1007/s00484-020-01866-4
   Joos F, 2001, GLOBAL BIOGEOCHEM CY, V15, P891, DOI 10.1029/2000GB001375
   Keenan TF, 2012, GLOBAL CHANGE BIOL, V18, P1971, DOI 10.1111/j.1365-2486.2012.02678.x
   Li CF, 2015, GLOBAL CHANGE BIOL, V21, P1951, DOI 10.1111/gcb.12846
   Li DJ, 2018, ECOL INDIC, V88, P351, DOI 10.1016/j.ecolind.2018.01.018
   Li H, 2019, GLOBAL PLANET CHANGE, V180, P51, DOI 10.1016/j.gloplacha.2019.05.009
   Lioubimtseva E, 2004, PROG PHYS GEOG, V28, P502, DOI 10.1191/0309133304pp422oa
   Liu HY, 2020, ECOL INDIC, V111, DOI 10.1016/j.ecolind.2019.106009
   Liu HY, 2018, AGR FOREST METEOROL, V256, P10, DOI 10.1016/j.agrformet.2018.02.015
   Lü YH, 2015, SCI REP-UK, V5, DOI 10.1038/srep08732
   Newman ME, 2014, AGR ECOSYST ENVIRON, V186, P185, DOI 10.1016/j.agee.2014.01.030
   Peng SZ, 2019, AGR FOREST METEOROL, V269, P270, DOI 10.1016/j.agrformet.2019.02.023
   Piao SL, 2015, GLOBAL CHANGE BIOL, V21, P1601, DOI 10.1111/gcb.12795
   Potter CS, 1998, GLOBAL CHANGE BIOL, V4, P315, DOI 10.1046/j.1365-2486.1998.00154.x
   Qi XZ, 2019, CATENA, V180, P224, DOI 10.1016/j.catena.2019.04.027
   Qian C, 2019, CATENA, V183, DOI 10.1016/j.catena.2019.104182
   Ren ZG, 2022, ECOL INDIC, V138, DOI 10.1016/j.ecolind.2022.108832
   Sitch S, 2003, GLOBAL CHANGE BIOL, V9, P161, DOI 10.1046/j.1365-2486.2003.00569.x
   Smith B, 2014, BIOGEOSCIENCES, V11, P2027, DOI 10.5194/bg-11-2027-2014
   Smith B, 2001, GLOBAL ECOL BIOGEOGR, V10, P621, DOI 10.1046/j.1466-822X.2001.00256.x
   Smith B, 2008, FOREST ECOL MANAG, V255, P3985, DOI 10.1016/j.foreco.2008.03.056
   Sun G, 2011, NONLINEAR PROC GEOPH, V18, P883, DOI 10.5194/npg-18-883-2011
   Sun WY, 2015, AGR FOREST METEOROL, V209, P87, DOI 10.1016/j.agrformet.2015.05.002
   Teng MJ, 2020, SCI TOTAL ENVIRON, V714, DOI 10.1016/j.scitotenv.2020.136691
   Tian F, 2021, ECOL INDIC, V125, DOI 10.1016/j.ecolind.2021.107479
   Tian HW, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.949564
   Tong XW, 2018, NAT SUSTAIN, V1, P44, DOI 10.1038/s41893-017-0004-x
   Wang B, 2022, POL J ENVIRON STUD, V31, DOI 10.15244/pjoes/148062
   [王菲 Wang Fei], 2023, [生态学报, Acta Ecologica Sinica], V43, P2501
   Wessels KJ, 2007, J ARID ENVIRON, V68, P271, DOI 10.1016/j.jaridenv.2006.05.015
   Xiao FJ, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14127399
   Xuan WX, 2023, FRONT PLANT SCI, V14, DOI 10.3389/fpls.2023.1043807
   Yan YC, 2019, ECOL INDIC, V103, P542, DOI 10.1016/j.ecolind.2019.04.020
   Yang Y, 2016, J ARID ENVIRON, V135, P164, DOI 10.1016/j.jaridenv.2016.09.004
   Yin L, 2020, ECOL INDIC, V112, DOI 10.1016/j.ecolind.2019.106013
   Zhan C, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.892747
   Zhang W, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105892
   Zhang Y, 2016, SCI TOTAL ENVIRON, V563, P210, DOI 10.1016/j.scitotenv.2016.03.223
   Zhao GJ, 2014, J HYDROL, V519, P387, DOI 10.1016/j.jhydrol.2014.07.014
   [赵军 ZHAO Jun], 2008, [干旱区研究, Arid Zone Research], V25, P53, DOI 10.3724/SP.J.1148.2008.00053
   Zhao XH, 2021, TERR ATMOS OCEAN SCI, V32, P53, DOI 10.3319/TAO.2020.08.25.01
   Zhou W, 2015, ECOL INDIC, V48, P560, DOI 10.1016/j.ecolind.2014.08.043
   Zhou W, 2014, ACTA OECOL, V55, P86, DOI 10.1016/j.actao.2013.12.006
   Zhu Wen-Quan, 2007, Zhiwu Shengtai Xuebao, V31, P413
NR 66
TC 0
Z9 0
U1 4
U2 4
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1002-0063
EI 1993-064X
J9 CHINESE GEOGR SCI
JI Chin. Geogr. Sci.
PD 2024 DEC 13
PY 2024
DI 10.1007/s11769-024-1477-y
EA DEC 2024
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA P4H3F
UT WOS:001377534400001
DA 2025-01-10
ER

PT J
AU Rodríguez-Barillas, M
   Poortvliet, PM
   Klerkx, L
AF Rodriguez-Barillas, Maria
   Poortvliet, P. Marijn
   Klerkx, Laurens
TI Unraveling farmers' interrelated adaptation and mitigation adoption
   decisions under perceived climate change risks
SO JOURNAL OF RURAL STUDIES
LA English
DT Article
DE Technology adoption; Sustainable practices; Risk management; Adoption
   risk; Farmer perception; Pro -environmental behavior; Climate -smart
   agriculture; Climate change adaptation; Climate change mitigation;
   Bundled innovations
ID PRO-ENVIRONMENTAL BEHAVIOR; SUSTAINABLE AGRICULTURAL PRACTICES;
   PROTECTION MOTIVATION THEORY; SMART-AGRICULTURE; SMALLHOLDER FARMERS;
   WATER CONSERVATION; PLANNED BEHAVIOR; COFFEE FARMERS; CHANGE BELIEFS;
   INNOVATIONS
AB Climate change poses a risk to agricultural activity. Understanding farmers' behaviors is increasingly important for managing climate risks and improving their adaptive capacity. This study aims to identify the key risk-related drivers influencing several adaptation and mitigation strategies by adopting various Climate-Smart Agriculture (CSA) technologies to reduce climate change vulnerability. We investigate the interrelated nature of the adoption of CSA technologies related to soil fertility, soil conservation, agroforestry, agro-advisory apps, and alternative coffee farming practices. To explore the role of the perceived risks related to CSA technology adoption, we constructed an extended model that combines protection motivation theory, perceived farmers' adoption risks and social and demographic determinants. We collected empirical data from 519 coffee farmers in Costa Rica and analyzed the data through a multivariate probit technique. The analysis reveals how the influence of perceived climate risks severity, perceived vulnerability, response efficacy, self-efficacy, and perceived cost changes according to the CSA technology. As for the perceived adoption risks, we show that the adoption likelihood of CSA technologies focused on mitigation decreases with increasing perceived adoption risk. Other determinants, such as the number of coffee buyers and the farmers' membership in an organization, steer the adoption of soil fertility practices, agroforestry, and agro-advisory mobile apps. Main theoretical implications include the integration of the CSA adoption risk-related perceptions to the protection motivation theory, since it reflects on farmers' fear of potential losses or additional costs associated with implementing these practices. The finding gives a nuanced explanation of farmers' decisions under pressing climate change threats. Practical implications for increasing CSA adoption are that CSA promotion programs must consider that farmers see CSA technologies as interrelated in their adoption decisions, meaning that more fruitful synergies could be promoted by acknowledging the bundled adoption of multiple CSA technologies. Thus, promoting a mix of CSA technologies and practices is essential for achieving resilience while increasing productivity.
C1 [Rodriguez-Barillas, Maria; Klerkx, Laurens] Wageningen Univ, Knowledge Technol & Innovat Grp, POB 8130, NL-6700 EW Wageningen, Netherlands.
   [Rodriguez-Barillas, Maria] Univ Costa Rica, Dept Econ Agr & Agronegocios, POB 11501-2060, San Pedro De Montes De Oc 115012060, Costa Rica.
   [Poortvliet, P. Marijn] Wageningen Univ, Strateg Commun Grp, POB 8130, NL-6700 EW Wageningen, Netherlands.
   [Klerkx, Laurens] Univ Talca, Fac Ciencias Agr, Dept Econ Agraria, Campus Lircay, Talca, Chile.
C3 Wageningen University & Research; Universidad Costa Rica; Wageningen
   University & Research; Universidad de Talca
RP Klerkx, L (corresponding author), Wageningen Univ, Knowledge Technol & Innovat Grp, POB 8130, NL-6700 EW Wageningen, Netherlands.
EM maria.rodriguezbarillas@wur.nl; laurens.klerkx@wur.nl
RI Klerkx, Laurens/ABD-4957-2021
OI Rodriguez-Barillas, Maria Fernanda/0000-0001-6064-608X
FU Universidad de Costa Rica
FX This work was supported by the Universidad de Costa Rica, San Jose ,
   Costa Rica.
CR Aggarwal PK, 2018, ECOL SOC, V23, DOI 10.5751/ES-09844-230114
   Ahmed Z, 2022, J RURAL STUD, V94, P274, DOI 10.1016/j.jrurstud.2022.06.008
   Akter A, 2023, CLIM RISK MANAG, V40, DOI 10.1016/j.crm.2023.100491
   Alpizar F, 2011, ECOL ECON, V70, P2317, DOI 10.1016/j.ecolecon.2011.07.004
   Amadu FO, 2020, WORLD DEV, V126, DOI 10.1016/j.worlddev.2019.104692
   Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   [Anonymous], 2018, Transforming Food and Agriculture To Achieve the SDGs
   [Anonymous], 2014, Climate-Smart Agriculture in Colombia
   [Anonymous], 2010, CLIM SMART AGR POL P
   Antwi-Agyei P, 2018, CLIM RISK MANAG, V19, P83, DOI 10.1016/j.crm.2017.11.003
   Arbuckle JG Jr, 2015, ENVIRON BEHAV, V47, P205, DOI 10.1177/0013916513503832
   Aryal JP, 2020, ENVIRON MANAGE, V66, P105, DOI 10.1007/s00267-020-01291-8
   Aryal JP, 2018, INT J CLIM CHANG STR, V10, P407, DOI [10.1108/IJCCSM-02-2017-0025, 10.1108/ijccsm-02-2017-0025]
   Asare-Nuamah P, 2021, ENVIRON DEV, V40, DOI 10.1016/j.envdev.2021.100680
   Ataei P, 2021, J RURAL STUD, V81, P374, DOI 10.1016/j.jrurstud.2020.11.003
   Avelino J, 2006, ECOL MODEL, V197, P431, DOI 10.1016/j.ecolmodel.2006.03.013
   Avelino J, 2015, FOOD SECUR, V7, P303, DOI 10.1007/s12571-015-0446-9
   Badsar M, 2023, ENVIRON DEV SUSTAIN, V25, P9903, DOI 10.1007/s10668-022-02468-3
   Barham BL, 2015, AGR ECON-BLACKWELL, V46, P11, DOI 10.1111/agec.12123
   Barrett CB, 2020, NAT SUSTAIN, V3, P974, DOI 10.1038/s41893-020-00661-8
   BCCR, 2023, Producto Interno Bruto por Actividad Economica volumen an precios del ano anterior encadenado, referencia 2017
   Beedell JDC, 1999, J ENVIRON MANAGE, V57, P165, DOI 10.1006/jema.1999.0296
   Beza E, 2018, COMPUT ELECTRON AGR, V151, P295, DOI 10.1016/j.compag.2018.06.015
   Bhattacharyya SS, 2022, SCI TOTAL ENVIRON, V815, DOI 10.1016/j.scitotenv.2022.152928
   Bockarjova M, 2014, GLOBAL ENVIRON CHANG, V28, P276, DOI 10.1016/j.gloenvcha.2014.06.010
   Bopp C, 2019, J ENVIRON MANAGE, V244, P320, DOI 10.1016/j.jenvman.2019.04.107
   Botzen WJW, 2019, RISK ANAL, V39, P2143, DOI 10.1111/risa.13318
   Bro AS, 2019, ENVIRON DEV SUSTAIN, V21, P895, DOI 10.1007/s10668-017-0066-y
   Bubeck P, 2012, RISK ANAL, V32, P1481, DOI 10.1111/j.1539-6924.2011.01783.x
   Bubeck P, 2018, RISK ANAL, V38, P1239, DOI 10.1111/risa.12938
   Bunn C, 2015, CLIMATIC CHANGE, V129, P89, DOI 10.1007/s10584-014-1306-x
   Campbell BM, 2014, CURR OPIN ENV SUST, V8, P39, DOI 10.1016/j.cosust.2014.07.002
   Cavanagh CJ, 2017, J RURAL STUD, V56, P114, DOI 10.1016/j.jrurstud.2017.09.010
   Chain-Guadarrama A, 2019, AGRON MESOAM, V30, P1, DOI 10.15517/am.v30i1.32615
   Chandra A, 2017, J POLIT ECOL, V24, P821, DOI 10.2458/v24i1.20969
   Chandran K. M., 2009, Journal of Rural Development (Hyderabad), V28, P369
   CICAFE, 2019, Sistema de alerta y recomendacion temprana para el combate de la roya, V1, P1
   Clarke M, 2021, J ENVIRON MANAGE, V286, DOI 10.1016/j.jenvman.2021.112161
   Cummings CL, 2021, RISK ANAL, V41, P204, DOI 10.1111/risa.13573
   Darnhofer I, 2020, SOCIOL RURALIS, V60, P505, DOI 10.1111/soru.12294
   de Sousa K, 2018, J RURAL STUD, V64, P11, DOI 10.1016/j.jrurstud.2018.09.018
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Djido A, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100309
   Emileva B, 2023, CLIM RISK MANAG, V41, DOI 10.1016/j.crm.2023.100537
   Engler A, 2019, J SOIL WATER CONSERV, V74, p74A, DOI 10.2489/jswc.74.4.74A
   Etumnu C, 2023, CLIM RISK MANAG, V40, DOI 10.1016/j.crm.2023.100494
   FAO, 2019, Agriculture and climate change - Challenges and opportunities at the global and local Level
   Faridi AA, 2020, LAND USE POLICY, V99, DOI 10.1016/j.landusepol.2020.104885
   Farstad M, 2022, J RURAL STUD, V96, P259, DOI 10.1016/j.jrurstud.2022.11.003
   FEDER G, 1993, TECHNOL FORECAST SOC, V43, P215, DOI 10.1016/0040-1625(93)90053-A
   FEDER G, 1985, ECON DEV CULT CHANGE, V33, P255, DOI 10.1086/451461
   Floyd DL, 2000, J APPL SOC PSYCHOL, V30, P407, DOI 10.1111/j.1559-1816.2000.tb02323.x
   Gao SJ, 2022, J RURAL STUD, V94, P111, DOI 10.1016/j.jrurstud.2022.05.018
   Gebrehiwot T, 2013, ENVIRON MANAGE, V52, P29, DOI 10.1007/s00267-013-0039-3
   Ghanian M, 2020, LAND USE POLICY, V94, DOI 10.1016/j.landusepol.2020.104553
   Greene W.H., 2009, MODELING ORDERED CHO
   Greene W.H., 1996, MARGINAL EFFECTS BIV
   Greene W. H., 2003, Econometric Analysis
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Haggar J, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.645958
   Hair J. F., 2010, Multivariate data analysis
   Harvey C. A., 2018, Agriculture & Food Security, V7, P57, DOI 10.1186/s40066-018-0209-x
   Harvey CA, 2021, AGRON SUSTAIN DEV, V41, DOI 10.1007/s13593-021-00712-0
   Harvey CA, 2017, AGR ECOSYST ENVIRON, V246, P279, DOI 10.1016/j.agee.2017.04.018
   Harvey CA, 2014, CONSERV LETT, V7, P77, DOI 10.1111/conl.12066
   Hellin J, 2019, NAT CLIM CHANGE, V9, P493, DOI 10.1038/s41558-019-0515-8
   Hochman Z, 2017, AGR SYST, V151, P61, DOI 10.1016/j.agsy.2016.11.007
   Huenchuleo C, 2012, LAND DEGRAD DEV, V23, P483, DOI 10.1002/ldr.1093
   ICAFE, 2022, Estadisticas de la caficultura de Costa Rica
   IMN MINAE., 2021, Costa Rica 2021: Inventario Nacional de gases de efecto invernadero y absorcion de carbono 1990-2017
   INEC, 2021, Coeficiente de Gini por hogar y per capita 2010-2021 WWW Document
   Jaleta M, 2013, AGR SYST, V121, P96, DOI 10.1016/j.agsy.2013.05.006
   Jara-Rojas R, 2013, LAND USE POLICY, V32, P292, DOI 10.1016/j.landusepol.2012.11.001
   Jara-Rojas R, 2012, AGR SYST, V110, P54, DOI 10.1016/j.agsy.2012.03.008
   Joffre OM, 2018, AQUACULTURE, V495, P528, DOI 10.1016/j.aquaculture.2018.06.012
   Kahsay G. A., 2023, WORLD DEV SUSTAINABI, V2, DOI DOI 10.1016/J.WDS.2023.100046
   KAISER HF, 1958, PSYCHOMETRIKA, V23, P187, DOI 10.1007/BF02289233
   Kangogo D, 2021, LAND USE POLICY, V109, DOI 10.1016/j.landusepol.2021.105666
   Kassie M, 2013, TECHNOL FORECAST SOC, V80, P525, DOI 10.1016/j.techfore.2012.08.007
   Kellstedt PM, 2008, RISK ANAL, V28, P113, DOI 10.1111/j.1539-6924.2008.01010.x
   Keshavarz M, 2016, J ARID ENVIRON, V127, P128, DOI 10.1016/j.jaridenv.2015.11.010
   Khoza S, 2019, DISASTER PREV MANAG, V28, P530, DOI 10.1108/DPM-10-2018-0347
   Klöckner CA, 2013, GLOBAL ENVIRON CHANG, V23, P1028, DOI 10.1016/j.gloenvcha.2013.05.014
   Kothe EJ, 2019, AUST J PSYCHOL, V71, P411, DOI 10.1111/ajpy.12271
   Kpadonou RAB, 2017, LAND USE POLICY, V61, P196, DOI 10.1016/j.landusepol.2016.10.050
   Kuehne G, 2017, AGR SYST, V156, P115, DOI 10.1016/j.agsy.2017.06.007
   Läderach P, 2017, CLIMATIC CHANGE, V141, P47, DOI 10.1007/s10584-016-1788-9
   Lee M, 2022, J RURAL STUD, V92, P214, DOI 10.1016/j.jrurstud.2022.03.031
   Leeuwis C., 2021, The Innovation Revolution in Agriculture. A Roadmap to Value Creation, P95, DOI [10.1007/978-3-030-50991-0, DOI 10.1007/978-3-030-50991-0_3]
   Li WJ, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100283
   Liang ZH, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100314
   Lipper L., 2018, Climate smart agriculture: building resilience to climate change, P13
   Long TB, 2017, INT FOOD AGRIBUS MAN, V20, P5, DOI [10.22434/IFAMR2016.0081, 10.22434/ifamr2016.0081]
   Long TB, 2016, J CLEAN PROD, V112, P9, DOI 10.1016/j.jclepro.2015.06.044
   Luís S, 2018, ENVIRON SCI POLICY, V80, P74, DOI 10.1016/j.envsci.2017.11.015
   Lyngbæk AE, 2001, AGROFOREST SYST, V53, P205, DOI 10.1023/A:1013332722014
   Makate C, 2019, ENVIRON SCI POLICY, V96, P37, DOI 10.1016/j.envsci.2019.01.014
   Makate C, 2019, J ENVIRON MANAGE, V231, P858, DOI 10.1016/j.jenvman.2018.10.069
   Markanday A, 2021, CLIM RISK MANAG, V34, DOI 10.1016/j.crm.2021.100359
   Mase AS, 2017, CLIM RISK MANAG, V15, P8, DOI 10.1016/j.crm.2016.11.004
   McCarthy N., 2018, Economics of Climate Smart Agriculture: An Overview, P31, DOI [10.1007/978-3-319-61194-53, DOI 10.1007/978-3-319-61194-53]
   Meierova T, 2022, J RURAL STUD, V92, P354, DOI 10.1016/j.jrurstud.2022.04.013
   Mercer DE, 2004, AGROFOREST SYST, V61-2, P311, DOI 10.1023/B:AGFO.0000029007.85754.70
   Mojo D, 2017, J RURAL STUD, V50, P84, DOI 10.1016/j.jrurstud.2016.12.010
   Moser CM, 2006, AGR ECON-BLACKWELL, V35, P373, DOI 10.1111/j.1574-0862.2006.00169.x
   Munguia OMD, 2021, AGR SYST, V191, DOI 10.1016/j.agsy.2021.103173
   Naranjo MA, 2019, J ECON BEHAV ORGAN, V166, P12, DOI 10.1016/j.jebo.2019.09.004
   Neset TS, 2019, CLIMATIC CHANGE, V153, P107, DOI 10.1007/s10584-019-02391-z
   Neufeldt H., 2013, AGR FOOD SECURITY, V2, P12, DOI DOI 10.1186/2048-7010-2-12
   Newell P, 2018, J PEASANT STUD, V45, P108, DOI 10.1080/03066150.2017.1324426
   Niles MT, 2016, CLIMATIC CHANGE, V135, P277, DOI 10.1007/s10584-015-1558-0
   Niles MT, 2015, AGR ECOSYST ENVIRON, V200, P178, DOI 10.1016/j.agee.2014.11.010
   Niles MT, 2013, GLOBAL ENVIRON CHANG, V23, P1752, DOI 10.1016/j.gloenvcha.2013.08.005
   O'Brien K, 2023, AMBIO, V52, P1448, DOI 10.1007/s13280-023-01873-w
   Ordaz J.L., 2010, Costa Rica: Efectos del cambio climatico sobre la agricultura, DF
   Ovalle-Rivera O, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0124155
   Pannell DJ, 2006, AUST J EXP AGR, V46, P1407, DOI 10.1071/EA05037
   Pannell DJ, 2020, APPL ECON PERSPECT P, V42, P31, DOI 10.1002/aepp.13009
   Payán F, 2009, AGROFOREST SYST, V76, P81, DOI 10.1007/s10457-008-9201-y
   Pomareda C, 2020, Evaluacion de la NAMA-Cafe de Costa Rica. Informe de Consultor 'ia BID-MAG. Evaluacion y Prospectiva
   Poortvliet PM, 2018, WATER RES, V131, P90, DOI 10.1016/j.watres.2017.12.032
   Prokopy LS, 2019, J SOIL WATER CONSERV, V74, P520, DOI 10.2489/jswc.74.5.520
   Rapidel B., 2012, Ecosystem Services from Agriculture and Agroforestry: Measurement and Payment, P1, DOI [10.4324/9781849775656, DOI 10.4324/9781849775656]
   Ratnadass A, 2021, CROP PROT, V146, DOI 10.1016/j.cropro.2021.105658
   Rhiney K, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2023212118
   Ricart S, 2023, REG ENVIRON CHANGE, V23, DOI 10.1007/s10113-023-02078-3
   Rodríguez-Barillas M, 2024, ENVIRON INNOV SOC TR, V50, DOI 10.1016/j.eist.2023.100791
   Rodríguez-Barillas M, 2024, AGR SYST, V213, DOI 10.1016/j.agsy.2023.103803
   Rogers R. W., 1983, Social psychophysiology: A source book, P153
   ROGERS RW, 1975, J PSYCHOL, V91, P93, DOI 10.1080/00223980.1975.9915803
   Sargani GR, 2023, J RURAL STUD, V100, DOI 10.1016/j.jrurstud.2023.103035
   Scherer L, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-017-0475-1
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   SEPSA, 2023, Informe Comercio Exterior del Sector Agropecuario 2021-2022
   Smit B., 2002, Migration and Adaption Strategies for Global Change, V7, P84
   Snider A, 2017, FOOD POLICY, V69, P231, DOI 10.1016/j.foodpol.2017.04.009
   Staub CG, 2021, J RURAL STUD, V81, P235, DOI 10.1016/j.jrurstud.2020.10.029
   Steenwerth KL., 2014, AGR FOOD SECURITY, V3, P1, DOI [10.1186/2048-7010-3-11, DOI 10.1186/2048-7010-3-11]
   Steg L, 2009, J ENVIRON PSYCHOL, V29, P309, DOI 10.1016/j.jenvp.2008.10.004
   Streletskaya NA, 2020, APPL ECON PERSPECT P, V42, P54, DOI 10.1002/aepp.13006
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Sutherland LA, 2012, J ENVIRON MANAGE, V104, P142, DOI 10.1016/j.jenvman.2012.03.013
   Tabe-Ojong MP, 2020, J ENVIRON MANAGE, V270, DOI 10.1016/j.jenvman.2020.110809
   Taylor M, 2018, J PEASANT STUD, V45, P89, DOI 10.1080/03066150.2017.1312355
   Teklewold H, 2019, CLIM DEV, V11, P180, DOI 10.1080/17565529.2018.1442801
   Teklewold H, 2013, J AGR ECON, V64, P597, DOI 10.1111/1477-9552.12011
   Teklu A, 2023, CLIM RISK MANAG, V39, DOI 10.1016/j.crm.2023.100477
   Trejo-Pech CO, 2023, AGR FOOD ECON, V11, DOI 10.1186/s40100-023-00256-9
   Vaast P., 2016, Climate Change: Observed Impacts on Planet Earth, Vsecond, P465, DOI [10.1016/B978-0-444-, DOI 10.1016/B978-0-444]
   Valkama E, 2020, GEODERMA, V369, DOI 10.1016/j.geoderma.2020.114298
   van der Linden S, 2015, J ENVIRON PSYCHOL, V41, P112, DOI 10.1016/j.jenvp.2014.11.012
   Verburg R, 2019, ENVIRON SCI POLICY, V97, P16, DOI 10.1016/j.envsci.2019.03.017
   Wallbott L, 2019, ECOL SOC, V24, DOI 10.5751/ES-10476-240124
   Wang J, 2023, CLIM RISK MANAG, V39, DOI 10.1016/j.crm.2023.100484
   Wang YD, 2019, J ENVIRON MANAGE, V237, P15, DOI 10.1016/j.jenvman.2019.02.070
   Wauters E., 2006, Psychology, P1
   Westermann O., 2015, CCAFS Research Program on Climate Change and. Food Security, V135, P1
   Wojtynia N, 2023, ENVIRON INNOV SOC TR, V49, DOI 10.1016/j.eist.2023.100776
   Wollni M, 2007, AGR ECON-BLACKWELL, V37, P243, DOI 10.1111/j.1574-0862.2007.00270.x
   World Bank CIAT CATIE, 2014, CSA Country Profiles for Latin America Series
   WorldBank CIAT CATIE, 2014, Climate-Smart Agriculture in Costa Rica
   Yazdanpanah M, 2014, J ENVIRON MANAGE, V135, P63, DOI 10.1016/j.jenvman.2014.01.016
   Zhang D.E., 2011, Impact of Soil Conservation Measures on Erosion Control and Soil Quality, P207
   Zhou ZF, 2020, J ENVIRON MANAGE, V270, DOI 10.1016/j.jenvman.2020.110806
   Zilberman D., 2018, Climate smart agriculture: building resilience to climate change, P49
NR 165
TC 2
Z9 2
U1 22
U2 22
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0743-0167
EI 1873-1392
J9 J RURAL STUD
JI J. Rural Stud.
PD JUL
PY 2024
VL 109
AR 103329
DI 10.1016/j.jrurstud.2024.103329
EA JUN 2024
PG 17
WC Geography; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Geography; Public Administration
GA XI1V1
UT WOS:001260970100001
OA hybrid
DA 2025-01-10
ER

PT J
AU Zhao, YR
   O'Neill, GA
   Coops, NC
   Wang, TL
AF Zhao, Yueru
   O'Neill, Gregory A.
   Coops, Nicholas C.
   Wang, Tongli
TI Predicting the site productivity of forest tree species using climate
   niche models
SO FOREST ECOLOGY AND MANAGEMENT
LA English
DT Article
DE Ecological niche models; Forest productivity; Random forest; Maxent;
   Assisted migration
ID DOUGLAS-FIR; LODGEPOLE PINE; POPULATIONS; IMPACTS; PERFORMANCE;
   STRATEGIES; ABUNDANCE; ABSENCES; GROWTH; INDEX
AB Species occurrence-based climate niche models (CNMs) serve as valuable tools for predicting the future ranges of species' suitable habitats, aiding the development of climate change adaptation strategies. However, these models do not address an essential aspect - productivity, which holds economic significance for timber production and ecological importance for carbon sequestration and ecosystem services. In this study, we investigated the potential to extend the CNMs to predict species productivity under various climate conditions. Lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.) were selected as our model species due to their comprehensive range-wide occurrence data and measurement of site productivity. To achieve this, we compared and optimized the performance of four individual modeling algorithms (Random Forest (RF), Maxent, Generalized Boosted Models (GBM), and Generalized Additive Model (GAM)) in reflecting site productivity by evaluating the effect of spatial filtering, and the ratio of presence to absence (p/a ratio) observations. Additionally, we applied a binning process to capture the overarching trend of climatic effects while minimizing the impact of other factors. We observed consistency in optimal performance across both species when using the unfiltered data and a 1:1.5 p/a ratio, which could potentially be extended to other species. Among the modeling algorithms explored, we selected the ensemble model combining RF and Maxent as the final model to predict the range-wide site productivity for both species. The predicted range-wide site productivity was validated with an independent dataset for each species and yielded promising results (R2 above 0.7), affirming our model's credibility. Our model introduced an innovative approach for predicting species productivity with high accuracy using only species occurrence data, and significantly advanced the application of CNMs. It provided crucial tools and insights for evaluating climate change's impact on productivity and holds a better potential for informed forest management and conservation decisions.
C1 [Zhao, Yueru; Wang, Tongli] Univ British Columbia, Dept Forest & Conservat Sci, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada.
   [O'Neill, Gregory A.] British Columbia Minist Forests, Kalamalka Forestry Ctr, 3401 Reservoir Rd, Vernon, BC V1B 2C7, Canada.
   [Coops, Nicholas C.] Univ British Columbia, Dept Forest Resource Management, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada.
C3 University of British Columbia; University of British Columbia
RP Wang, TL (corresponding author), Univ British Columbia, Dept Forest & Conservat Sci, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada.
EM tongli.wang@ubc.ca
RI Coops, Nicholas/J-1543-2012
OI Coops, Nicholas/0000-0002-0151-9037; Zhao, Yueru/0000-0001-6532-1794
FU Natural Sciences and Engineering Research Council of Canada
   [RGPIN-2018-04643]
FX We would like to express our sincere gratitude to Yong Luo of the BC
   Ministry of Forests and Kate Peterson from Tongli Wang's lab for their
   invaluable reviews. Their expertise and thoughtful insights have offered
   a distinct perspective and significantly enriched our manuscript. We
   also extend our thanks to the two anonymous reviewers for their
   constructive and insightful comments. Furthermore, we appreciate the
   funding pro- vided by the Natural Sciences and Engineering Research
   Council of Canada for supporting this study under the grant awarded to
   Tongli Wang (RGPIN-2018-04643) .
CR Alasadi S.A., 2017, J Eng Appl Sci, V12, P4102, DOI DOI 10.3923/JEASCI.2017.4102.4107
   Araújo MB, 2007, TRENDS ECOL EVOL, V22, P42, DOI 10.1016/j.tree.2006.09.010
   Araújo MB, 2006, J BIOGEOGR, V33, P1677, DOI 10.1111/j.1365-2699.2006.01584.x
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Boisvenue C, 2006, GLOBAL CHANGE BIOL, V12, P862, DOI 10.1111/j.1365-2486.2006.01134.x
   Boria RA, 2014, ECOL MODEL, V275, P73, DOI 10.1016/j.ecolmodel.2013.12.012
   Bracken JT, 2022, ECOSPHERE, V13, DOI 10.1002/ecs2.3951
   Brecka AFJ, 2020, FOREST ECOL MANAG, V474, DOI 10.1016/j.foreco.2020.118352
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Breiner FT, 2015, METHODS ECOL EVOL, V6, P1210, DOI 10.1111/2041-210X.12403
   Byeon DH, 2018, J ASIA-PAC BIODIVERS, V11, P325, DOI 10.1016/j.japb.2018.06.002
   Chhin S, 2008, FOREST ECOL MANAG, V256, P1692, DOI 10.1016/j.foreco.2008.02.046
   Coops NC, 2010, CAN J FOREST RES, V40, P511, DOI 10.1139/X09-201
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Fox EW, 2017, ENVIRON MONIT ASSESS, V189, DOI 10.1007/s10661-017-6025-0
   Friedman JH, 2001, ANN STAT, V29, P1189, DOI 10.1214/aos/1013203451
   GBIF.org, 2021, GBIF OCC DOWNL, DOI [10.15468/dl.8g335v, DOI 10.15468/DL.8G335V]
   Gu WD, 2004, BIOL CONSERV, V116, P195, DOI 10.1016/S0006-3207(03)00190-3
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Hällfors MH, 2016, BIOL CONSERV, V196, P60, DOI 10.1016/j.biocon.2016.01.031
   Hampe A, 2005, ECOL LETT, V8, P461, DOI 10.1111/j.1461-0248.2005.00739.x
   Hao TX, 2019, DIVERS DISTRIB, V25, P839, DOI 10.1111/ddi.12892
   He FL, 2000, AM NAT, V156, P553, DOI 10.1086/303403
   Hijmans Robert J, 2023, CRAN
   Iturbide M, 2015, ECOL MODEL, V312, P166, DOI 10.1016/j.ecolmodel.2015.05.018
   JAYNES ET, 1957, PHYS REV, V106, P620, DOI 10.1103/PhysRev.106.620
   Joyce LA, 1995, J BIOGEOGR, V22, P703, DOI 10.2307/2845973
   Kramer-Schadt S, 2013, DIVERS DISTRIB, V19, P1366, DOI 10.1111/ddi.12096
   Leites LP, 2012, ECOL APPL, V22, P154, DOI 10.1890/11-0150.1
   Liaw Andy, 2022, CRAN
   Littke KM, 2018, CAN J FOREST RES, V48, P421, DOI 10.1139/cjfr-2017-0385
   Littke KM, 2016, FOREST SCI, V62, P503, DOI 10.5849/forsci.15-191
   Lobo JM, 2010, ECOGRAPHY, V33, P103, DOI 10.1111/j.1600-0587.2009.06039.x
   Mahony C.R., 2021, A CMIP6 ensemble for downscaled monthly climate normals over North America
   Monserud RA, 2006, FOREST CHRON, V82, P562, DOI 10.5558/tfc82562-4
   Nigh G., 2015, Technical Report 085.
   Pecchi M, 2019, ECOL MODEL, V411, DOI 10.1016/j.ecolmodel.2019.108817
   Pedlar JH, 2012, BIOSCIENCE, V62, P835, DOI 10.1525/bio.2012.62.9.10
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2009, ECOL APPL, V19, P181, DOI 10.1890/07-2153.1
   Porfirio LL, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0113749
   R Core Team R, 2013, R: A language and environment for statistical computing
   Rehfeldt GE, 2006, INT J PLANT SCI, V167, P1123, DOI 10.1086/507711
   Ridgeway G, 2020, Generalized Boosted Models: A guide to the gbm package, DOI DOI 10.1016/J.DSR2.2019.104659
   Roberts DR, 2017, ECOGRAPHY, V40, P913, DOI 10.1111/ecog.02881
   Sheppard CS, 2014, GLOBAL CHANGE BIOL, V20, P2800, DOI 10.1111/gcb.12531
   Sun JJ, 2021, FOREST ECOL MANAG, V496, DOI 10.1016/j.foreco.2021.119474
   Svenning JC, 2011, QUATERNARY SCI REV, V30, P2930, DOI 10.1016/j.quascirev.2011.06.012
   Thuiller W, 2008, PERSPECT PLANT ECOL, V9, P137, DOI 10.1016/j.ppees.2007.09.004
   Thurm EA, 2018, FOREST ECOL MANAG, V430, P485, DOI 10.1016/j.foreco.2018.08.028
   van der Maaten E, 2017, ECOL EVOL, V7, P2585, DOI 10.1002/ece3.2696
   VanDerWal J, 2009, AM NAT, V174, P282, DOI 10.1086/600087
   Wang T, 2006, GLOBAL CHANGE BIOL, V12, P2404, DOI 10.1111/j.1365-2486.2006.01271.x
   Wang TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0156720
   Wang TL, 2010, ECOL APPL, V20, P153, DOI 10.1890/08-2257.1
   Weber MM, 2017, ECOGRAPHY, V40, P817, DOI 10.1111/ecog.02125
   Weiskittel A. R., 2012, Schweizerische Zeitschrift fur Forstwesen, V163, P70, DOI 10.3188/szf.2012.0070
   Wisz Mary S., 2009, BMC Ecology, V9, P8, DOI 10.1186/1472-6785-9-8
   Wood Simon, 2023, CRAN
   Zhao YR, 2023, ECOL INDIC, V148, DOI 10.1016/j.ecolind.2023.110072
   Zhao YR, 2023, FRONT FOR GLOB CHANG, V6, DOI 10.3389/ffgc.2023.1084797
NR 61
TC 1
Z9 1
U1 9
U2 19
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0378-1127
EI 1872-7042
J9 FOREST ECOL MANAG
JI For. Ecol. Manage.
PD JUN 15
PY 2024
VL 562
AR 121936
DI 10.1016/j.foreco.2024.121936
EA MAY 2024
PG 12
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA SV9D1
UT WOS:001237333200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Kuempel, CD
   Froehlich, HE
   Halpern, BS
AF Kuempel, Caitlin D.
   Froehlich, Halley E.
   Halpern, Benjamin S.
TI An informed thought experiment exploring the potential for a paradigm
   shift in aquatic food production
SO OCEAN & COASTAL MANAGEMENT
LA English
DT Article
DE Aquaculture; Blue revolution; Ecosystem-based fisheries management;
   Neolithic revolution; Seafood
ID CLIMATE-CHANGE ADAPTATION; ENVIRONMENTAL IMPACTS; OFFSHORE AQUACULTURE;
   MARINE FISHERIES; DOMESTICATION; CONSERVATION; SCENARIOS; KNOWLEDGE;
   SCIENCE; SECTOR
AB The Neolithic Revolution began approximately 10,000 years ago and is characterized by the ultimate, nearly complete transition from hunting and gathering to agricultural food production on land. The Neolithic Revolution is thought to have been catalyzed by a combination of local population pressure, cultural diffusion, property rights and climate change. We undertake a thought experiment that examines trends in these key hypothesized catalysts of the Neolithic Revolution and patterns of today to explore whether society could be on a path towards another paradigm shift in food production: away from hunting of wild fish towards a transition to mostly fish farming. We find similar environmental and cultural pressures have driven the rapid rise of aquaculture, during a period that has now been coined the Blue Revolution, providing impetus for such a transition in coming decades to centuries (as opposed to millennia). However, we also highlight the interacting and often mutually reinforcing impacts of 1) technological and scientific advancements, 2) environmental awareness and collective action and 3) globalization and trade influencing the trajectory and momentum of the Blue Revolution from patterns and processes of the Neolithic Revolution. We present two qualitative narratives that broadly fall within two future trajectories of seafood production: 1) a ubiquitous aquaculture transition and 2) commercial aquaculture and fisheries coexistence. Each narrative contains two sub-narratives based on differing management and regulatory strategies for aquaculture and fisheries. This scenarios approach aims to encourage logical, forward thinking, and innovative solutions to complex systems? dynamics. Scenario-based thought experiments are useful to explore large scale questions, increase the accessibility to a wider readership, and ideally catalyze discussion around proactive governance mechanisms. We argue the future is not fixed and society now has greater foresight and capacity to choose the workable balance between fisheries and aquaculture that supports economic, environmental, cultural and social objectives through combined planning, policies, and management.
C1 [Kuempel, Caitlin D.; Froehlich, Halley E.; Halpern, Benjamin S.] Univ Calif Santa Barbara, Natl Ctr Ecol Anal & Synth, 735 State St,Suite 300, Santa Barbara, CA 93101 USA.
   [Kuempel, Caitlin D.] Univ Queensland, Sch Biol Sci, St Lucia, Qld 4072, Australia.
   [Kuempel, Caitlin D.] Univ Queensland, Australian Res Council, Ctr Excellence Coral Reef Studies, St Lucia, Qld 4072, Australia.
   [Kuempel, Caitlin D.] Univ Queensland, Ctr Biodivers & Conservat Sci, St Lucia, Qld 4072, Australia.
   [Froehlich, Halley E.] Univ Calif Santa Barbara, Environm Studies, Santa Barbara, CA 93106 USA.
   [Froehlich, Halley E.] Univ Calif Santa Barbara, Ecol Evolut & Marine Biol, Santa Barbara, CA 93106 USA.
   [Halpern, Benjamin S.] Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA.
C3 National Center for Ecological Analysis & Synthesis; University of
   California System; University of California Santa Barbara; University of
   Queensland; University of Queensland; University of Queensland;
   University of California System; University of California Santa Barbara;
   University of California System; University of California Santa Barbara;
   University of California System; University of California Santa Barbara
RP Kuempel, CD (corresponding author), Univ Queensland, Sch Biol Sci, St Lucia, Qld 4072, Australia.
EM c.kuempel@uq.edu.au
RI Halpern, Benjamin/J-6141-2014; Kuempel, Caitlin/AAV-8807-2020
OI Froehlich, Halley/0000-0001-7322-1523; Kuempel,
   Caitlin/0000-0003-1609-9706
FU Zegar Family Foundation
FX The National Center for Ecological Analysis and Synthesis at UC Santa
   Barbara provided invaluable infrastructural support for this work. CDK,
   HEF and BSH acknowledge funding from the Zegar Family Foundation. We
   thank Allison Horst for her collaboration and artistic contribution on
   Table 1 and Fig. 1.
CR Aligica PD, 2005, TECHNOL FORECAST SOC, V72, P815, DOI 10.1016/j.techfore.2005.01.001
   Alvheim AR, 2020, FOODS, V9, DOI 10.3390/foods9030344
   American commercial fishers, 2018, OPP MAR FINFISH AQ U
   Anderson J. L., 2002, Marine Resource Economics, V17, P133
   Anderson JL, 2019, ANNU REV RESOUR ECON, V11, P101, DOI 10.1146/annurev-resource-100518-093750
   [Anonymous], 2013, FAOSTAT DAT COLL
   [Anonymous], 2017, US AQ
   [Anonymous], 2018, Impacts, risks, and adaptation in the united states: Fourth national climate assessment, VII, P1515, DOI DOI 10.7930/NCA4.2018
   [Anonymous], 2005, First farmers: the origins of agricultural societies, by peter bellwood
   Arlinghaus R, 2019, P NATL ACAD SCI USA, V116, P5209, DOI 10.1073/pnas.1902796116
   Arnason R, 2012, REV ENV ECON POLICY, V6, P217, DOI 10.1093/reep/res011
   Arquitt S, 2005, SYST DYNAM REV, V21, P305, DOI 10.1002/sdr.313
   Asche F, 2016, MAR POLICY, V69, P194, DOI 10.1016/j.marpol.2015.06.021
   Ashraf Q.H., 2011, SSRN, DOI DOI 10.2139/SSRN.903847
   Atkinson S., 2013, 126 MRDC
   Bacher K, 2015, GLOBEFISH RES PROGRA, V120, P35, DOI [DOI 10.13140/RG.2.1.1399.3840, 10.13140/RG.2.1.1399.3840]
   Barange M., 2018, FAO FISH AQUAC TECH
   Bene C, 2015, FOOD SECUR, V7, P261, DOI 10.1007/s12571-015-0427-z
   Bestor TC, 2001, AM ANTHROPOL, V103, P76, DOI 10.1525/aa.2001.103.1.76
   Bidgood J., 2017, NEW YORK TIMES
   Bjorndal T., 1999, Aquaculture Economics Management, V3, P238, DOI DOI 10.1080/13657309909380251
   Bowles S, 2013, P NATL ACAD SCI USA, V110, P8830, DOI 10.1073/pnas.1212149110
   Cao L, 2017, P NATL ACAD SCI USA, V114, P435, DOI 10.1073/pnas.1616583114
   Cheung WWL, 2013, NATURE, V497, P365, DOI 10.1038/nature12156
   Childe V.G., 1928, MOST ANCIENT E, DOI DOI 10.2307/593050
   Christiansen JS, 2014, GLOBAL CHANGE BIOL, V20, P352, DOI 10.1111/gcb.12395
   Clavelle T, 2019, FISH FISH, V20, P368, DOI 10.1111/faf.12351
   Cohen M. N., 1977, after six years of crisis. Food and Agriculture
   Costa-Pierce B.A., 2002, ECOLOGICAL AQUACULTU, DOI 10.1002/9780470995051
   Costello C, 2021, SUSTAIN SCI, V16, P1391, DOI 10.1007/s11625-020-00865-z
   Costello C, 2020, NATURE, V588, P95, DOI 10.1038/s41586-020-2616-y
   Costello C, 2016, P NATL ACAD SCI USA, V113, P5125, DOI 10.1073/pnas.1520420113
   Cottrell RS, 2021, REV AQUACULT, V13, P1583, DOI 10.1111/raq.12535
   Cottrell RS, 2018, GLOBAL CHANGE BIOL, V24, P580, DOI 10.1111/gcb.13873
   Davies IP, 2019, MAR POLICY, V104, P29, DOI 10.1016/j.marpol.2019.02.054
   Dey MM, 2016, MAR POLICY, V67, P171, DOI 10.1016/j.marpol.2016.01.004
   Downs JS, 2014, P NATL ACAD SCI USA, V111, P13627, DOI 10.1073/pnas.1317502111
   Duggan T, 2018, CALIFORNIA ABALONE S
   Evans LS, 2013, HUM ECOL, V41, P841, DOI 10.1007/s10745-013-9601-0
   FAO, 2018, STAT WORLD FISH AQ
   FAO, 2014, PROPERTY RIGHTS NATU, DOI DOI 10.5040/9781472564733.CH-008
   Free CM, 2019, SCIENCE, V363, P979, DOI 10.1126/science.aau1758
   Froehlich HE, 2018, NAT ECOL EVOL, V2, P1745, DOI 10.1038/s41559-018-0669-1
   Froehlich HE, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0169281
   Gaines SD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao1378
   Gentry RR, 2019, NAT SUSTAIN, V2, P949, DOI 10.1038/s41893-019-0395-y
   Gentry RR, 2017, NAT ECOL EVOL, V1, P1317, DOI 10.1038/s41559-017-0257-9
   Gentry RR, 2017, ECOL EVOL, V7, P733, DOI 10.1002/ece3.2637
   Gephart JA, 2020, REV FISH SCI AQUAC, V29, P122, DOI 10.1080/23308249.2020.1782342
   Goldstein M, 2008, J POLIT ECON, V116, P981, DOI 10.1086/595561
   Halpern BS, 2010, P NATL ACAD SCI USA, V107, P18312, DOI 10.1073/pnas.0908503107
   Hasan M. R., 2017, FAO NONSERIAL PUBLIC, V33
   Hibbs DA, 2004, P NATL ACAD SCI USA, V101, P3715, DOI 10.1073/pnas.0305531101
   Hidalgo M, 2019, ICES J MAR SCI, V76, P609, DOI 10.1093/icesjms/fsz067
   Hishamunda N, 2009, FOOD POLICY, V34, P102, DOI 10.1016/j.foodpol.2008.06.006
   Hoegh-Guldberg O, 2010, SCIENCE, V328, P1523, DOI 10.1126/science.1189930
   Hua K, 2019, ONE EARTH, V1, P316, DOI 10.1016/j.oneear.2019.10.018
   Karl TR, 2003, SCIENCE, V302, P1719, DOI 10.1126/science.1090228
   Klinger D, 2012, ANNU REV ENV RESOUR, V37, P247, DOI 10.1146/annurev-environ-021111-161531
   Klinger DH, 2018, MAR POLICY, V87, P356, DOI 10.1016/j.marpol.2017.09.025
   Knowler D, 2007, FOOD POLICY, V32, P25, DOI 10.1016/j.foodpol.2006.01.003
   Lafferty KD, 2015, ANNU REV MAR SCI, V7, P471, DOI 10.1146/annurev-marine-010814-015646
   Larson G, 2007, P NATL ACAD SCI USA, V104, P15276, DOI 10.1073/pnas.0703411104
   Lester SE, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03249-1
   Lester SE, 2018, P NATL ACAD SCI USA, V115, P7162, DOI 10.1073/pnas.1808737115
   Lewison RL, 2019, CONSERV LETT, V12, DOI 10.1111/conl.12628
   Longo SB, 2019, CONSERV BIOL, V33, P832, DOI 10.1111/cobi.13295
   Louder E, 2020, ENVIRON CONSERV, V47, P251, DOI 10.1017/S0376892920000387
   Maher LA, 2011, CAMB ARCHAEOL J, V21, P1, DOI 10.1017/S0959774311000011
   Maxwell S, 2016, NATURE, V536, P143, DOI 10.1038/536143a
   McCauley DJ, 2015, SCIENCE, V347, DOI 10.1126/science.1255641
   McLeod S, 2018, SEAWESTNEWS
   Merrie A, 2018, FUTURES, V95, P22, DOI 10.1016/j.futures.2017.09.005
   Nahuelhual L, 2019, FISH FISH, V20, P584, DOI 10.1111/faf.12354
   Nakajima T, 2019, NAT ECOL EVOL, V3, P1415, DOI 10.1038/s41559-019-0974-3
   Nations United., 2015, The United Nations Transforming Our World: The 2030 Agenda for Sustainable Development, V16301, P1
   Naylor RL, 2001, SCIENCE, V294, P1655, DOI 10.1126/science.1064875
   Naylor RL, 2000, NATURE, V405, P1017, DOI 10.1038/35016500
   Noakes DJ, 2003, FISHERIES MANAG ECOL, V10, P123, DOI 10.1046/j.1365-2400.2003.00336.x
   NORTH DC, 1977, ECON HIST REV, V30, P229
   Nwosu FM, 2016, INT J ECOSYST ECOL S, V6, P139
   Ogilvy J., 2014, World Futures, V70, P5, DOI DOI 10.1080/02604027.2014.875718
   Ottinger M, 2016, OCEAN COAST MANAGE, V119, P244, DOI 10.1016/j.ocecoaman.2015.10.015
   Peterson GD, 2003, CONSERV BIOL, V17, P358, DOI 10.1046/j.1523-1739.2003.01491.x
   Pingali P, 2007, FOOD POLICY, V32, P281, DOI 10.1016/j.foodpol.2006.08.001
   Poore J, 2018, SCIENCE, V360, P987, DOI 10.1126/science.aaq0216
   Reilly M, 2010, PHILOS T R SOC B, V365, P3049, DOI 10.1098/rstb.2010.0141
   Ricel JC, 2011, ICES J MAR SCI, V68, P1343, DOI 10.1093/icesjms/fsr041
   Richards MP, 2003, NATURE, V425, P366, DOI 10.1038/425366a
   Richerson PJ, 2001, AM ANTIQUITY, V66, P387, DOI 10.2307/2694241
   Sala E, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aat2504
   SAPEA (Science Advice for Policy by European Academies), 2017, FOOD OC CAN MOR FOOD, DOI [10.26356/foodfromtheoceans, DOI 10.26356/FOODFROMTHEOCEANS]
   Shukla PR, 2019, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems
   Spijkers J, 2019, GLOBAL ENVIRON CHANG, V57, DOI 10.1016/j.gloenvcha.2019.05.005
   Springmann M, 2018, NATURE, V562, P519, DOI 10.1038/s41586-018-0594-0
   Subasinghe R. P., 2003, FAO Fisheries Circular, P59
   Sumaila UR, 2019, MAR POLICY, V109, DOI 10.1016/j.marpol.2019.103695
   Swart RJ, 2004, GLOBAL ENVIRON CHANG, V14, P137, DOI 10.1016/j.gloenvcha.2003.10.002
   Szuwalski C, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0227106
   Tacon AGJ, 2020, REV FISH SCI AQUAC, V28, P43, DOI 10.1080/23308249.2019.1649634
   Teletchea F., 2016, Natural Resources, V7, P399, DOI DOI 10.4236/NR.2016.76034
   Teletchea F, 2015, J MAR SCI ENG, V3, P1227, DOI 10.3390/jmse3041227
   The Marine Ingredients Organization, 2017, FISH FISH OUT FIFO R
   Tilman D, 1999, P NATL ACAD SCI USA, V96, P5995, DOI 10.1073/pnas.96.11.5995
   Tilman D, 2014, NATURE, V515, P518, DOI 10.1038/nature13959
   Troell M, 2014, P NATL ACAD SCI USA, V111, P13257, DOI 10.1073/pnas.1404067111
   UN DESA, 2017, WORLD POP PRESP KEY
   Venter O, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12558
   Verdegem MCJ, 2013, REV AQUACULT, V5, P158, DOI 10.1111/raq.12011
   Voyer M., 2018, SOCIAL LICENSE OPERA
   Wang Y, 2017, PROPERTY RIGHTS LAND, V24099
   Weisdorf JL, 2005, J ECON SURV, V19, P561, DOI 10.1111/j.0950-0804.2005.00259.x
   Weitzel EM, 2016, ROY SOC OPEN SCI, V3, DOI 10.1098/rsos.160319
   Willett W, 2019, LANCET, V393, P447, DOI 10.1016/S0140-6736(18)31788-4
   Yu JK, 2020, MAR POLICY, V115, DOI 10.1016/j.marpol.2020.103892
   Zou LL, 2015, AQUACULT REP, V2, P46, DOI 10.1016/j.aqrep.2015.07.001
NR 116
TC 8
Z9 9
U1 1
U2 12
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0964-5691
EI 1873-524X
J9 OCEAN COAST MANAGE
JI Ocean Coastal Manage.
PD JUN 1
PY 2021
VL 206
AR 105574
DI 10.1016/j.ocecoaman.2021.105574
EA MAR 2021
PG 11
WC Oceanography; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Oceanography; Water Resources
GA RW2BZ
UT WOS:000646328900007
OA Green Submitted, Green Published
DA 2025-01-10
ER

PT J
AU Osawa, T
   Nishida, T
   Oka, T
AF Osawa, Takeshi
   Nishida, Takaaki
   Oka, Takashi
TI High tolerance land use against flood disasters: How paddy fields as
   previously natural wetland inhibit the occurrence of floods
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Eco-DRR; Ecosystem service; Green infrastructure; Paddy field; Wetlands
ID CLIMATE-CHANGE ADAPTATION; ECOSYSTEM SERVICES; RISK REDUCTION; GREEN
   INFRASTRUCTURE; ROOT REINFORCEMENT; BIODIVERSITY; TREE
AB Although natural disturbances are inherent in any ecosystem, they can be hazardous to the local residents, indicating that it is necessary to mitigate these disturbances as much as possible appropriately. There has been an increased interest in taking advantage of ecosystem functions for disaster risk reduction (Eco-DRR) as future infrastructure because of the lower introduction, maintenance costs, and the additional ecosystem services. Previous studies have suggested that intact ecosystems have a higher tolerance and/or resilience to natural disturbances. However, fully intact ecosystems have been decreasing rapidly worldwide. This study evaluates the functions of semi-natural land, namely, paddy fields, which is one of the typical agricultural land uses of monsoon Asia to reduce the societal damages of natural disasters. As semi-natural land is sometimes located close to or is similar to the original intact habitat, it could play a role in reducing flood disasters. In particular, paddy fields could be seen to be similar to intact wetland habitats, most of which have disappeared in recent decades due to development. To test this idea, the relationships between flood disasters and paddy fields with location condition in inland regions of central Japan were evaluated. We used flow accumulation value (FAV) as an index of intact wetland habitat; particularly, we considered that high FAV area might be previously natural wetland. Thus, paddy field located at high FAV values are considered similar to intact wetland habitats. Results showed that paddy fields located in high FAV areas were able to significantly reduce flood frequencies, occurrences of landslides, and debris floods. These results suggested that semi-natural land close to or on their natural habitats could function as intact ecosystems and provide Eco-DRR function as ecosystem services. These types of semi-natural land could be employed as green infrastructure to provide several extensive ecosystem services.
C1 [Osawa, Takeshi] Tokyo Metropolitan Univ, Grad Sch Urban Environm Sci, Minami Osawa 1-1, Hachioji, Tokyo 1920397, Japan.
   [Nishida, Takaaki; Oka, Takashi] Mitsubishi UFJ Res & Consulting Co Ltd, Kita Ku, 2-5-25 Umeda, Osaka 5308213, Japan.
   [Nishida, Takaaki] Res Inst Humanity & Nat, Kita Ku, 457-4 Motoyama, Kyoto 6038047, Japan.
   [Nishida, Takaaki] Kyoto Sangyo Univ, Fac Life Sci, Kita Ku, 457-4 Motoyama, Kyoto 6030855, Japan.
C3 Tokyo Metropolitan University; Research Institute for Humanity & Nature
   (RIHN); Kyoto Sangyo University
RP Osawa, T (corresponding author), Tokyo Metropolitan Univ, Grad Sch Urban Environm Sci, Minami Osawa 1-1, Hachioji, Tokyo 1920397, Japan.
EM arosawa@gmail.com
OI Osawa, Takeshi/0000-0002-2098-0902
FU Environment Research and Technology Development Fund [4-1805]; Ministry
   of the Environment, Japan
FX Three anonymous reviewers provided us useful suggestions. This study was
   supported by the Environment Research and Technology Development Fund
   (4-1805) of the Ministry of the Environment, Japan.
CR Alexander DE, 2013, NAT HAZARD EARTH SYS, V13, P2707, DOI 10.5194/nhess-13-2707-2013
   [Anonymous], 2016, SCI TOTAL ENV, DOI DOI 10.1016/J.SCITOTENV.2015.10.067
   Benedict M.A., 2006, GREEN INFRASTRUCTURE
   Bradshaw CJA, 2007, GLOBAL CHANGE BIOL, V13, P2379, DOI 10.1111/j.1365-2486.2007.01446.x
   Calder C, 2003, ECOLOGY, V84, P1395, DOI 10.1890/0012-9658(2003)084[1395:IMSOSI]2.0.CO;2
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Dudley N., 2015, HDB PRACTITIONERS, DOI [10.1038/ncomms4794, DOI 10.1038/NCOMMS4794]
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Ellison AM, 2004, ECOL LETT, V7, P509, DOI 10.1111/j.1461-0248.2004.00603.x
   Ferrario F, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4794
   Furuta N., 2017, INT J DISASTER RISK, DOI [0-1, 10.1016/j.ijdrr.2017.12.003, DOI 10.1016/J.IJDRR.2017.12.003]
   Gelman A., 2013, Bayesian Data Analysis
   HEY DL, 1995, RESTOR ECOL, V3, P4, DOI 10.1111/j.1526-100X.1995.tb00070.x
   Hobbs N.T., 2015, BAYESIAN MODELS STAT
   Iijima H, 2017, J FOREST RES-JPN, V22, P199, DOI 10.1080/13416979.2017.1305262
   JENSON SK, 1988, PHOTOGRAMM ENG REM S, V54, P1593
   Katayama N, 2015, AGR SYST, V132, P73, DOI 10.1016/j.agsy.2014.09.001
   Kobayashi Y, 2017, ENVIRON MANAGE, V59, P807, DOI 10.1007/s00267-017-0820-9
   Koyanagi T, 2009, BIOL CONSERV, V142, P1674, DOI 10.1016/j.biocon.2009.03.002
   Li YP, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-00924-z
   López-Vicente M, 2014, ENVIRON MODELL SOFTW, V62, P11, DOI 10.1016/j.envsoft.2014.08.025
   Lytle DA, 2004, TRENDS ECOL EVOL, V19, P94, DOI 10.1016/j.tree.2003.10.002
   Martin TG, 2016, NAT CLIM CHANGE, V6, P122, DOI 10.1038/nclimate2918
   Matsuno Y, 2006, PADDY WATER ENVIRON, V4, P189, DOI 10.1007/s10333-006-0048-4
   Mercer J, 2010, J INT DEV, V22, P247, DOI 10.1002/jid.1677
   Middleton B., 1999, WETLAND RESTORATION
   Moos C, 2016, EARTH SURF PROC LAND, V41, P951, DOI 10.1002/esp.3887
   Munang R, 2013, CURR OPIN ENV SUST, V5, P47, DOI 10.1016/j.cosust.2013.02.002
   Nakamura F, 2020, RIVER RES APPL, V36, P921, DOI 10.1002/rra.3576
   Natuhara Y, 2013, ECOL ENG, V56, P97, DOI 10.1016/j.ecoleng.2012.04.026
   Nicholls RJ, 1999, GLOBAL ENVIRON CHANG, V9, pS69, DOI 10.1016/S0959-3780(99)00019-9
   Nishihiro J., 2006, LANDSC ECOL ENG, V2, P171
   Onuma A, 2018, INT J DISAST RISK RE, V32, P22, DOI 10.1016/j.ijdrr.2018.01.025
   Osawa T, 2019, BIOL INVASIONS, V21, P2067, DOI 10.1007/s10530-019-01958-2
   Osawa T, 2016, LAND USE POLICY, V54, P78, DOI 10.1016/j.landusepol.2016.02.001
   Osawa T, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0079978
   Reice S.R., 2003, SILVER LINING BENEFI
   Renaud FG, 2016, ADV NAT TECH HAZ RES, V42, P1, DOI 10.1007/978-3-319-43633-3
   Rey Benayas J. M., 2007, CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, V2, DOI 10.1079/PAVSNNR20072057
   Reyers B, 2015, P NATL ACAD SCI USA, V112, P7362, DOI 10.1073/pnas.1414374112
   Roering JJ, 2003, CAN GEOTECH J, V40, P237, DOI 10.1139/T02-113
   Scarano FR, 2017, PERSPECT ECOL CONSER, V15, P65, DOI 10.1016/j.pecon.2017.05.003
   Smajgl A, 2013, FUTURES, V52, P52, DOI 10.1016/j.futures.2013.07.002
   Sudmeier-rieux K., 2013, ENV GUIDANCE NOTE DI
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   Washitani I., 2007, GLOB ENV RES, V11, P135
   Watson JEM, 2016, CURR BIOL, V26, P2929, DOI 10.1016/j.cub.2016.08.049
   Wikle CK, 2003, ECOLOGY, V84, P1382, DOI 10.1890/0012-9658(2003)084[1382:HBMFPT]2.0.CO;2
   Yoon CG, 2009, PADDY WATER ENVIRON, V7, P357, DOI 10.1007/s10333-009-0178-6
NR 49
TC 15
Z9 15
U1 0
U2 36
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD JUL
PY 2020
VL 114
AR 106306
DI 10.1016/j.ecolind.2020.106306
PG 7
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA NA6ZG
UT WOS:000559966500005
OA hybrid
DA 2025-01-10
ER

PT J
AU Hou, W
   Hou, XY
AF Hou, Wan
   Hou, Xiyong
TI Spatial-temporal changes in vegetation coverage in the global coastal
   zone based on GIMMS NDVI3g data
SO INTERNATIONAL JOURNAL OF REMOTE SENSING
LA English
DT Article
ID MANN-KENDALL; TREND TEST; SATELLITE; GROWTH; PLATEAU; DIFFERENCE;
   RESPONSES; DYNAMICS; DRIVERS; DECADES
AB In this paper, we used the Global Inventory Modelling and Mapping Studies (GIMMS) third-generation Normalized Difference Vegetation Index (NDVI) (GIMMS NDVI3g) dataset. Based on GIMMS NDVI3g data over the global coastal zone from 1982 to 2014, the spatial-temporal characteristics of vegetation coverage were analysed by plotting the spatial pattern and monthly calendar of NDVI; furthermore, historical trends and future evolutions of vegetation coverage change at the pixel scale were studied by performing the Mann-Kendall trend test and calculating the trend slope (beta) and Hurst index (H) of NDVI. The main findings are as follows: 1) Vegetation density exhibits dramatic differences in the global coastal zone. Specifically, desert belts mostly have perennial non-vegetation or low vegetation coverage, and tundra belts principally have moderate or high vegetation coverage; additionally, forest belts mainly have dense vegetation coverage. 2) In the global coastal zone, intra-annual variations in vegetation coverage show a 'boolean AND'-shaped curve with an obvious peak from June to September (maximum in July or August), while inter-annual variations show a fluctuating but generally slowly increasing trend over the entire study period; accordingly, variations in different subregions show significant differences. 3) At monthly, seasonal and annual scales, the overall vegetation coverage increases in the global coastal zone, while there are relatively few areas with decreasing vegetation coverage; furthermore, change trends of vegetation coverage in most areas will demonstrate relatively strong positive persistence in the future. 4) The increasing trend in high-latitude coastal tundra is extremely significant in the growing season because vegetation in the tundra belts is highly sensitive to climate change. 5) Areas with a decreasing trend of vegetation coverage exhibit spatial patterns of aggregation in the 'circum urban agglomeration' and 'nearby desert belt' regions, that is, the decreasing trend of vegetation coverage is relatively high in coastal urban agglomeration areas and desert belt peripheries. This paper is expected to provide knowledge to support vegetation conservation, ecosystem management, integrated coastal zone management and climate change adaptation in coastal areas.
C1 [Hou, Wan; Hou, Xiyong] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China.
   [Hou, Wan] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China.
   [Hou, Wan; Hou, Xiyong] Chinese Acad Sci, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai, Peoples R China.
C3 Chinese Academy of Sciences; Yantai Institute of Coastal Zone Research,
   CAS; Chinese Academy of Sciences; University of Chinese Academy of
   Sciences, CAS; Chinese Academy of Sciences
RP Hou, XY (corresponding author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China.
EM xyhou@yic.ac.cn
FU Strategic Priority Research Program of the Chinese Academy of Sciences
   [XDA19060205]; National Natural Science Foundation of China
   [31461143032]
FX This work was supported by the Strategic Priority Research Program of
   the Chinese Academy of Sciences (No. XDA19060205) and the National
   Natural Science Foundation of China (No. 31461143032).
CR Chen BZ, 2014, REMOTE SENS ENVIRON, V144, P28, DOI 10.1016/j.rse.2013.12.018
   De Keersmaecker W, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9010034
   de la Barrera F, 2017, ECOL INDIC, V81, P265, DOI 10.1016/j.ecolind.2017.05.067
   Dobbs C, 2017, SCI TOTAL ENVIRON, V592, P171, DOI 10.1016/j.scitotenv.2017.03.058
   [杜加强 Du Jiaqiang], 2016, [生态学报, Acta Ecologica Sinica], V36, P6738
   Du JQ, 2015, INT J APPL EARTH OBS, V38, P216, DOI 10.1016/j.jag.2015.01.006
   Fan XW, 2016, ISPRS J PHOTOGRAMM, V121, P177, DOI 10.1016/j.isprsjprs.2016.09.008
   Faour G, 2018, APPL GEOGR, V97, P184, DOI 10.1016/j.apgeog.2018.05.020
   Feng HH, 2017, J HYDROL, V550, P220, DOI 10.1016/j.jhydrol.2017.04.056
   Granero MAS, 2008, PHYSICA A, V387, P5543, DOI 10.1016/j.physa.2008.05.053
   Guo M, 2018, CHINESE GEOGR SCI, V28, P907, DOI 10.1007/s11769-018-1002-2
   Halkos G, 2018, ECON ANAL POLICY, V58, P153, DOI 10.1016/j.eap.2017.10.002
   Hamed KH, 2009, J HYDROL, V365, P86, DOI 10.1016/j.jhydrol.2008.11.024
   HOLBEN BN, 1986, INT J REMOTE SENS, V7, P1417, DOI 10.1080/01431168608948945
   Hou X., 2012, ACTA ECOL SIN, V32, P297, DOI [10.1016/J.CHNAES.2012.08.001, DOI 10.1016/J.CHNAES.2012.08.001, 10.1016/j.chnaes.2012.08.001]
   Ju JC, 2016, REMOTE SENS ENVIRON, V176, P1, DOI 10.1016/j.rse.2016.01.001
   Kim D, 2017, ATMOS ENVIRON, V148, P282, DOI 10.1016/j.atmosenv.2016.10.051
   Kong DD, 2017, GLOBAL PLANET CHANGE, V148, P1, DOI 10.1016/j.gloplacha.2016.10.020
   Lamchin M, 2018, SCI TOTAL ENVIRON, V618, P1089, DOI 10.1016/j.scitotenv.2017.09.145
   Lanfredi M, 2004, REMOTE SENS ENVIRON, V93, P565, DOI 10.1016/j.rse.2004.08.012
   Latifovic R, 2012, REMOTE SENS ENVIRON, V127, P84, DOI 10.1016/j.rse.2012.08.032
   Rêgo JCL, 2018, LAND USE POLICY, V71, P593, DOI 10.1016/j.landusepol.2017.10.055
   Liu Y, 2016, JNPS, V36, P19
   Masria A, 2014, PROCEDIA ENGINEER, V70, P1102, DOI 10.1016/j.proeng.2014.02.122
   Miao LJ, 2015, PHYS CHEM EARTH, V87-88, P50, DOI 10.1016/j.pce.2015.07.010
   Mohammat A, 2013, AGR FOREST METEOROL, V178, P21, DOI 10.1016/j.agrformet.2012.09.014
   Pang GJ, 2017, QUATERN INT, V444, P87, DOI 10.1016/j.quaint.2016.08.038
   Peng J, 2012, ECOL INDIC, V14, P28, DOI 10.1016/j.ecolind.2011.08.011
   Pereira P, 2013, PROCEDIA ENVIRON SCI, V19, P856, DOI 10.1016/j.proenv.2013.06.095
   Pinzon JE, 2014, REMOTE SENS-BASEL, V6, P6929, DOI 10.3390/rs6086929
   Shi H, 2003, AMBIO, V32, P145, DOI 10.1639/0044-7447(2003)032[0145:SAIOSE]2.0.CO;2
   Tehrany MS, 2017, J NAT CONSERV, V40, P12, DOI 10.1016/j.jnc.2017.08.004
   Tian YC, 2017, CHINESE GEOGR SCI, V27, P25, DOI 10.1007/s11769-017-0844-3
   Vicente-Serrano SM, 2016, REMOTE SENS ENVIRON, V187, P14, DOI 10.1016/j.rse.2016.10.001
   Vrieling A, 2014, INT J APPL EARTH OBS, V28, P238, DOI 10.1016/j.jag.2013.12.010
   [王恒 Wang Heng], 2018, [遥感技术与应用, Remote Sensing Technology and Application], V33, P703
   Wu SY, 2019, URBAN FOR URBAN GREE, V38, P215, DOI 10.1016/j.ufug.2018.12.010
   Xu HJ, 2017, SCI TOTAL ENVIRON, V579, P1658, DOI 10.1016/j.scitotenv.2016.11.182
   Yang XM, 2016, J ARID LAND, V8, P556, DOI 10.1007/s40333-016-0046-3
   Yue S, 2002, J HYDROL, V259, P254, DOI 10.1016/S0022-1694(01)00594-7
   Zhang Y, 2016, AGR FOREST METEOROL, V224, P1, DOI 10.1016/j.agrformet.2016.04.009
   Zhao L, 2018, AGR FOREST METEOROL, V249, P198, DOI 10.1016/j.agrformet.2017.11.013
NR 42
TC 13
Z9 16
U1 16
U2 97
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 0143-1161
EI 1366-5901
J9 INT J REMOTE SENS
JI Int. J. Remote Sens.
PD FEB 1
PY 2020
VL 41
IS 3
BP 1118
EP 1138
DI 10.1080/01431161.2019.1657603
EA AUG 2019
PG 21
WC Remote Sensing; Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Remote Sensing; Imaging Science & Photographic Technology
GA JF2QV
UT WOS:000483750300001
OA Green Published
DA 2025-01-10
ER

PT S
AU Kumar, RS
   Nishant, N
   Jha, K
   Binu, NK
   Thampi, B
AF Kumar, Rajesh S.
   Nishant, Nity
   Jha, Keshav
   Binu, N. K.
   Thampi, Balachandran
BE Filho, WL
TI Integrating Technologies, Measures and Policies for Climate Resilient
   Economy: A Case Analysis from Emerging Countries in the Asia-Pacific
   Region
SO CLIMATE CHANGE IN THE ASIA-PACIFIC REGION
SE Climate Change Management
LA English
DT Article; Book Chapter
AB The Asia-Pacific region accounts for significant level of greenhouse gas emissions globally. The recent abrupt drastic changes in the general climate are highly relevant for the Asia-Pacific than other regions owing to its highly vulnerable societies. However, the region has significant potential to contribute to both mitigation and adaptation efforts in the context of climate change. The regional scenario which is already experiencing multiple socio-economic problems is further worsened due to climate change. Nevertheless, it is pertinent to note that several countries in the region have initiated and implemented large-scale mitigation and adaptation programs. However, there is an urgent need to augment regional capacity, strengthen institutional coordination and knowledge sharing on mitigation and adaptation policies, strategies as well as programs. These interventions can potentially influence the extent to which countries integrate climate change policies within their broader development frameworks. In the current review we describe the climate change related threats and associated developmental risks in the Asia-Pacific region as well as analyze the sensitivity, potential resilience strategies, various adaptation and mitigation initiatives in the region in the broad context of the role to be played by the region to deal with climate change. In specifics, we attempt to develop a general typology for adaptation strategies framed upon emissions reduction technologies, practices, measures, national policies adopted in the countries in the region. The key economic sectors such as energy, buildings, and water supply systems are covered as part of this assessment through a comprehensive methodology to position the climate change threats in the backdrop of resilient economy. This framework makes use of nested flowcharts to demonstrate how, social and environmental forces interact to create situations vulnerable to sudden changes. Our work is expected to contribute the initiatives in developing climate change adaptation toolkit for Asia-Pacific countries which will be crucial in undertaking vulnerability assessments as well as in identification and prioritization of appropriate actions required to build resilience in the context of changing climate in the region.
C1 [Kumar, Rajesh S.] Indian Forest Serv, 103 MS Flats, New Delhi 110021, India.
   [Nishant, Nity] Univ Delhi, New Delhi 110021, India.
   [Jha, Keshav] ICLEI Local Govt Sustainabil, New Delhi 110020, India.
   [Binu, N. K.] Kerala Agr Univ, Coll Forestry, Trichur, Kerala, India.
   [Thampi, Balachandran] Govt India, Natl Rainfed Author, Planning Commiss India, New Delhi 110012, India.
C3 University of Delhi
RP Kumar, RS (corresponding author), Indian Forest Serv, 103 MS Flats, New Delhi 110021, India.
EM rskumarifs@gmail.com; ms.nity@gmail.com; keshavjha@live.in;
   nk_binu1@yahoo.com; kbthampi@gmail.com
CR [Anonymous], IND 2 NAT COMM UN FR
   [Anonymous], PROM CLIM RES DEV
   [Anonymous], ADAPT AS PAC NAD
   [Anonymous], SUMM AS PAC REG EV R
   [Anonymous], SCI UND URG ACT CARB
   [Anonymous], CLIM CHANG IMP AS PA
   [Anonymous], EXP M CLIM CHANG ED
   [Anonymous], VIETN 2 NAT COMM UN
   [Anonymous], GHG EM MARK DAT
   [Anonymous], BUILDING CLIMATE CHA
   [Anonymous], ENG AS PAC CLIM CHAN
   [Anonymous], PHIL IN NAT COMM CLI
   [Anonymous], MAL 2 NAT COMM NC2 U
   [Anonymous], NON 1 NAT COMM ACT C
   [Anonymous], AS PAC CLIM CHANG AD
   [Anonymous], 2012, IND 2 NAT COMM UN FR
   [Anonymous], 2012, 2 NAT COMM CLIM CHAN
   Ford JD, 2013, ECOL SOC, V18, DOI 10.5751/ES-05732-180340
   World Bank, 2014, Global financial development report 2014: FI
NR 19
TC 0
Z9 0
U1 0
U2 1
PU SPRINGER-VERLAG BERLIN
PI BERLIN
PA HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
SN 1610-2010
BN 978-3-319-14938-7; 978-3-319-14937-0
J9 CLIM CHANG MANAG
PY 2015
BP 375
EP 390
DI 10.1007/978-3-319-14938-7_22
D2 10.1007/978-3-319-14938-7
PG 16
WC Environmental Studies
WE Book Citation Index – Social Sciences & Humanities (BKCI-SSH)
SC Environmental Sciences & Ecology
GA BF6IL
UT WOS:000383133200023
DA 2025-01-10
ER

PT J
AU Feola, G
   Nunes, R
AF Feola, Giuseppe
   Nunes, Richard
TI Success and failure of grassroots innovations for addressing climate
   change: The case of the Transition Movement
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Grassroots innovations; Transition Movement; Sustainability; Resilience
ID SOCIAL INNOVATION; COMMUNITY; GOVERNANCE; SPACES
AB Grassroots innovations emerge as networks generating innovative solutions for climate change adaptation and mitigation. However, it is unclear if grassroots innovations can be successful in responding to climate change. Little evidence exists on replication, international comparisons are rare, and research tends to overlook discontinued responses in favour of successful ones. We take the Transition Movement as a case study of a rapidly spreading transnational grassroots network, and include both active and non-active local transition initiatives. We investigate the replication of grassroots innovations in different contexts with the aim to uncover general patterns of success and failure, and identify questions for future research. An online survey was carried out in 23 countries (N = 276). The data analysis entailed testing the effect of internal and contextual factors of success as drawn from the existing literature, and the identification of clusters of transition initiatives with similar internal and contextual factor configurations. Most transition initiatives consider themselves successful. Success is defined along the lines of social connectivity and empowerment, and external environmental impact. We find that less successful transition initiatives might underestimate the importance of contextual factors and material resources in influencing success. We also find that their diffusion is linked to the combination of local-global learning processes, and that there is an incubation period during which a transition initiative is consolidated. Transition initiatives seem capable of generalising organisational principles derived from unique local experiences that seem to be effective in other local contexts. However, the geographical locations matter with regard to where transition initiatives take root and the extent of their success, and 'place attachment' may have a role in the diffusion of successful initiatives. We suggest that longitudinal comparative studies can advance our understanding in this regard, as well as inform the changing nature of the definition of success at different stages of grassroots innovation development, and the dynamic nature of local and global linkages. (C) 2013 Elsevier Ltd. All rights reserved.
C1 [Feola, Giuseppe] Univ Reading, Dept Geog & Environm Sci, Reading RG66AB, Berks, England.
   [Nunes, Richard] Univ Reading, Sch Real Estate & Planning, Reading RG66AB, Berks, England.
C3 University of Reading; University of Reading
RP Feola, G (corresponding author), Univ Reading, Dept Geog & Environm Sci, Reading RG66AB, Berks, England.
EM g.feola@reading.ac.uk
OI Nunes, Richard J./0000-0003-0829-4130; Feola,
   Giuseppe/0000-0003-1069-503X
FU School of Human and Environmental Sciences; School of Real Estate and
   Planning at the University of Reading
FX The authors are grateful to all members of the transition initiatives
   who took their time to participate in this study, and to those who did
   not but who sent constructive critiques and comments that helped the
   authors improve the research. Celeste Salter, Michelle Bastian, Marco
   Mauri, Isabela Maria Gomez de Menezes, Holly Salvidge, Jesus
   Cordero-Salvado, Janine Baudach, Sophie Raynaud and Rogerio Henrique de
   Abreu provided invaluable help at different stages of the survey design,
   translation and dissemination. The authors also thank Amy Burnett, Peter
   McManners and Gill Seyfang for their comments on an earlier version of
   this manuscript, and Joan Allibone for proofreading. The project was
   co-funded by the School of Human and Environmental Sciences and the
   School of Real Estate and Planning at the University of Reading.
CR Aiken G, 2012, GEOGR COMPASS, V6, P89, DOI 10.1111/j.1749-8198.2011.00475.x
   [Anonymous], 2007, SYNTHESIS REPORT CON
   [Anonymous], 1983, RISK CULTURE ESSAY S
   Antonsich M, 2010, GEOJOURNAL, V75, P119, DOI 10.1007/s10708-009-9290-9
   Barthelmie RJ, 2008, SUSTAIN SCI, V3, P267, DOI 10.1007/s11625-008-0059-8
   Bergman N., 2010, C EN TRANS INT WORLD, P1
   Biggs R, 2010, ECOL SOC, V15, DOI 10.5751/ES-03411-150209
   Brangwyn B., 2008, Transition Initiatives Primer: Becoming a Transition Town, City, District, Village, Community or even Island, Version 26
   Broto VC, 2013, GLOBAL ENVIRON CHANG, V23, P92, DOI 10.1016/j.gloenvcha.2012.07.005
   Brown G, 2012, ENVIRON PLANN A, V44, P1607, DOI 10.1068/a44608
   Bulkeley H, 2005, POLIT GEOGR, V24, P875, DOI 10.1016/j.polgeo.2005.07.002
   Bulkeley H, 2006, URBAN STUD, V43, P2237, DOI 10.1080/00420980600936491
   Burch S, 2010, GLOBAL ENVIRON CHANG, V20, P287, DOI 10.1016/j.gloenvcha.2009.11.009
   Chiu T., 2001, KDD-2001. Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, P263, DOI 10.1145/502512.502549
   Church C., 2002, Thinking locally, acting nationally. Lessons for national policy from work on local sustainability
   Coenen L, 2012, RES POLICY, V41, P968, DOI 10.1016/j.respol.2012.02.014
   Connors P, 2011, COMMUNITY DEV J, V46, P558, DOI 10.1093/cdj/bsq014
   Devine-Wright P, 2013, LOCAL ENVIRON, V18, P1099, DOI 10.1080/13549839.2012.754742
   Devine-Wright P, 2013, GLOBAL ENVIRON CHANG, V23, P61, DOI 10.1016/j.gloenvcha.2012.08.003
   FEITELSON E, 1991, GLOBAL ENVIRON CHANG, V1, P396, DOI 10.1016/0959-3780(91)90005-E
   Feola G., 2012, 18 ANN INT SUST DEV
   Geels FW, 2007, RES POLICY, V36, P399, DOI 10.1016/j.respol.2007.01.003
   Glasbergen P, 2010, GLOBAL ENVIRON CHANG, V20, P130, DOI 10.1016/j.gloenvcha.2009.09.002
   Grin J., 2010, Routledge studies in sustainability transitions
   Haxeltine A., 2009, 134 TYND CTR CLIM CH
   Hodson M, 2010, RES POLICY, V39, P477, DOI 10.1016/j.respol.2010.01.020
   Hoffman SM, 2010, ENERG POLICY, V38, P7567, DOI 10.1016/j.enpol.2009.06.054
   Holloway J., 2010, CRACK CAPITALISM
   Holmgren David., 2004, PERMACULTURE PRINCIP
   Hopkins Rob., 2008, TRANSITION HDB
   Hopkins Rob., 2011, TRANSITION COMPANION
   Howaldt J., 2010, Social Innovation: Concepts, Research Fields and International Trends, International Monitoring (IMO)
   Kirwan J., 2013, GLOBAL ENVIRON CHANG, DOI DOI 10.1016/J.GL0EMRCHA.2012.12.004
   Leach M, 2012, ECOL SOC, V17, DOI 10.5751/ES-04933-170211
   Lewicka M, 2011, J ENVIRON PSYCHOL, V31, P207, DOI 10.1016/j.jenvp.2010.10.001
   Mason K, 2012, ANTIPODE, V44, P493, DOI 10.1111/j.1467-8330.2010.00868.x
   Mayer H, 2010, EUR PLAN STUD, V18, P1545, DOI 10.1080/09654313.2010.504336
   Merritt Amy., 2012, Development, V55, P96, DOI [10.1057/dev.2011.113, DOI 10.1057/DEV.2011.113]
   Middlemiss L, 2010, ENERG POLICY, V38, P7559, DOI 10.1016/j.enpol.2009.07.003
   Moloney S, 2010, ENERG POLICY, V38, P7614, DOI 10.1016/j.enpol.2009.06.058
   Moulaert F, 2005, URBAN STUD, V42, P1969, DOI 10.1080/00420980500279893
   Mulgan G., 2006, INNOVATIONS TECHNOLO, V1, P145, DOI [DOI 10.1162/ITGG.2006.1.2.145, 10.1162/itgg.2006.1.2.145]
   Mulugetta Y, 2010, ENERG POLICY, V38, P7541, DOI 10.1016/j.enpol.2010.05.050
   Neumeier S, 2012, SOCIOL RURALIS, V52, P48, DOI 10.1111/j.1467-9523.2011.00553.x
   North P, 2010, GEOFORUM, V41, P585, DOI 10.1016/j.geoforum.2009.04.013
   Norusis M.J., 2012, IBM SPSS Statistics 19 Statistical Procedures Companion
   Nunes R.J., 2013, AAG ASS AM GEOGR ANN
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   Ornetzelder M., 2013, GLOBAL ENVIRON CHANG, DOI DOI 10.1016/J.GL0ENV-CHA.2012.12.007
   Peters M.D., 2012, LOW CARBON COMMUNITI
   Pickerill J, 2009, GEOGR COMPASS, V3, P1515, DOI 10.1111/j.1749-8198.2009.00237.x
   Quilley S., 2012, 20121 U ESS
   Scannell L, 2010, J ENVIRON PSYCHOL, V30, P1, DOI 10.1016/j.jenvp.2009.09.006
   Scott-Cato M, 2010, ENVIRON POLIT, V19, P869, DOI 10.1080/09644016.2010.518677
   Seyfang G, 2007, ENVIRON POLIT, V16, P584, DOI 10.1080/09644010701419121
   Seyfang G, 2013, GLOBAL ENVIRON CHANG, V23, P881, DOI 10.1016/j.gloenvcha.2013.02.007
   Seyfang G, 2012, ENVIRON PLANN C, V30, P381, DOI 10.1068/c10222
   Seyfang Gill., 2011, The New Economics of Sustainable Consumption: Seeds of Change
   Smith A, 2005, RES POLICY, V34, P1491, DOI 10.1016/j.respol.2005.07.005
   Smith A., 2005, ENVIRON PLANN C, V24, P439
   Smith A, 2012, RES POLICY, V41, P1025, DOI 10.1016/j.respol.2011.12.012
   Smith Amanda., 2011, SOC MOVEMENT STUD, V10, P99, DOI DOI 10.1080/14742837.2011.545229
   Späth P, 2012, EUR PLAN STUD, V20, P461, DOI 10.1080/09654313.2012.651800
   TRAPESE, 2008, ROCK ROAD TRANS TRAN
   Truffer B, 2012, REG STUD, V46, P1, DOI 10.1080/00343404.2012.646164
   Veenhoven R, 2002, SOC INDIC RES, V58, P33, DOI 10.1023/A:1015723614574
   Walker G, 2011, WIRES CLIM CHANGE, V2, P777, DOI 10.1002/wcc.137
   Wells P., 2011, Interdiscip. Environ. Rev., V12, P372
   Westley F., 2006, Getting to maybe: How the world is changed
   Wilson GA, 2012, GEOFORUM, V43, P1218, DOI 10.1016/j.geoforum.2012.03.008
   Young OR, 2011, P NATL ACAD SCI USA, V108, P19853, DOI 10.1073/pnas.1111690108
NR 71
TC 187
Z9 206
U1 8
U2 157
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD JAN
PY 2014
VL 24
BP 232
EP 250
DI 10.1016/j.gloenvcha.2013.11.011
PG 19
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA AD8HC
UT WOS:000333506100023
OA Green Accepted
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Hedelin, B
   Alkan-Olsson, J
   Greenberg, L
AF Hedelin, Beatrice
   Alkan-Olsson, Johanna
   Greenberg, Larry
TI Collaboration Adrift: Factors for Anchoring into Governance Systems,
   Distilled from a Study of Three Regulated Rivers
SO SUSTAINABILITY
LA English
DT Article
DE collaborative capacity; floods directive; hydropower; sustainable
   development; Sweden; water framework directive
ID SUSTAINABLE WATER MANAGEMENT; FRAMEWORK; IMPLEMENTATION; RESOURCES;
   PARTICIPATION; COMPLEXITY; POLITICS
AB Collaboration has the potential to aid the balancing of values and goals that belong to different, sometimes competing, policy fields, such as energy, climate adaptation and nature conservation-a key component of sustainable governance. However, we need to know more of how collaboration can function as integrating (and integrated) components of governance systems. Three regulated Swedish rivers are used here as examples to explore factors that influence this function. The following factors are identified: transparency of value trade-offs, understanding of collaboration and governance, interplay between public sectors, integrating funding mechanisms, clarity of mandate, strategic use of networks and consistency of the governance system. As a consequence of the poor management of these factors in our case, water quality and ecology values are not integrated in strategic decision making, e.g., regarding hydropower, urban development or climate adaptation. Instead, they are considered add-ons, or "decorations". The Swedish case illustrates the meaning of the factors and their great importance for achieving sustainable governance.
C1 [Hedelin, Beatrice] Karlstad Univ, Ctr Soc Risk Res, Dept Polit Hist Relig & Cultural Studies, S-65188 Karlstad, Sweden.
   [Alkan-Olsson, Johanna] Lund Univ, Ctr Environm & Climate Sci, S-22100 Lund, Sweden.
   [Greenberg, Larry] Karlstad Univ, River Ecol & Management Res Grp, Dept Environm & Life Sci, S-65188 Karlstad, Sweden.
C3 Karlstad University; Lund University; Karlstad University
RP Hedelin, B (corresponding author), Karlstad Univ, Ctr Soc Risk Res, Dept Polit Hist Relig & Cultural Studies, S-65188 Karlstad, Sweden.
EM beatrice.hedelin@kau.se
RI Hedelin, Beatrice/H-2667-2012
FU Swedish research council for sustainable development, FORMAS - Swedish
   Civil Contingencies Agency [2016-01432]; Swedish Civil Contingencies
   Agency (Societal Resilience project); Swedish Research Council for
   Environment Agricultural Sciences and Spatial Planning [2016-01432];
   Formas [2016-01432] Funding Source: Formas
FX This research was funded by Swedish Research Council for Environment
   Agricultural Sciences and Spatial Planning (grant number 2016-01432) and
   the Swedish Civil Contingencies Agency (Societal Resilience project).
CR Allen J, 2007, REG STUD, V41, P1161, DOI 10.1080/00343400701543348
   Amsler LB, 2016, PUBLIC ADMIN REV, V76, P700, DOI 10.1111/puar.12605
   Ananda J, 2013, ECOL ECON, V86, P97, DOI 10.1016/j.ecolecon.2012.10.018
   [Anonymous], 2007, O.J. (L 288), P27
   [Anonymous], 2015, OFF J EUR UNION
   [Anonymous], 2000, The European Commission survey on electronic instructions for use (eIFUs) for medical devices
   [Anonymous], 2009, ENVIRON POLICY GOV, DOI DOI 10.1002/EET.509
   Ansell C, 2008, J PUBL ADM RES THEOR, V18, P543, DOI 10.1093/jopart/mum032
   Ardesjo Lunden K., 201966  SOU
   Arheimer B, 2015, HYDROL EARTH SYST SC, V19, P771, DOI 10.5194/hess-19-771-2015
   Armitage D., 2008, INT J COMMONS, V2, P7
   Bendz A, 2020, LOCAL GOV STUD, V46, P800, DOI 10.1080/03003930.2019.1682557
   Biswas AK, 2008, INT J WATER RESOUR D, V24, P5, DOI 10.1080/07900620701871718
   Bjärstig T, 2018, EUR PLAN STUD, V26, P35, DOI 10.1080/09654313.2017.1365819
   Brockwell E, 2020, J ENVIRON PLANN MAN, V63, P1001, DOI 10.1080/09640568.2019.1627187
   Brondizio ES, 2009, ANNU REV ENV RESOUR, V34, P253, DOI 10.1146/annurev.environ.020708.100707
   Bryan TA, 2004, SOC NATUR RESOUR, V17, P881, DOI 10.1080/08941920490505284
   Bryman A., 2016, Social Research Methods, V5th
   Calles O, 2009, RIVER RES APPL, V25, P1268, DOI 10.1002/rra.1228
   Carlander A, 2016, WATER POLICY, V18, P1267, DOI 10.2166/wp.2016.225
   Carlsson B., 2006, FRAMTIDENS OVERSVAMN
   Conley A, 2003, SOC NATUR RESOUR, V16, P371, DOI 10.1080/08941920309181
   Davies JS, 2015, ENVIRON PLANN C, V33, P223, DOI 10.1068/c11292
   DeFries R, 2017, SCIENCE, V356, P265, DOI 10.1126/science.aal1950
   Dietz T, 2003, SCIENCE, V302, P1907, DOI 10.1126/science.1091015
   Earle JR, 2011, WATER SCI TECHNOL, V64, P2044, DOI 10.2166/wst.2011.669
   Emerson K, 2012, J PUBL ADM RES THEOR, V22, P1, DOI 10.1093/jopart/mur011
   Falkenstrom V., 2020, USE EXCEPTIONS WATER
   Feist A, 2020, ENVIRON MANAGE, V66, P801, DOI 10.1007/s00267-020-01337-x
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Foster-Fishman PG, 2001, AM J COMMUN PSYCHOL, V29, P241, DOI 10.1023/A:1010378613583
   Frame T. M., 2004, Journal of Environmental Planning and Management, V47, P59, DOI 10.1080/0964056042000189808
   Fred M, 2020, LOCAL GOV STUD, V46, P351, DOI 10.1080/03003930.2019.1606799
   Granberg M, 2021, REGULATORY STATE NET, DOI [10.31219/osf.io/a2stn, DOI 10.31219/OSF.IO/A2STN]
   Graversgaard M, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10051634
   Hammer M, 2011, AMBIO, V40, P210, DOI 10.1007/s13280-010-0132-2
   Hannaford J, 2013, HYDROL EARTH SYST SC, V17, P2717, DOI 10.5194/hess-17-2717-2013
   Healey P., 2003, Planning Theory, V2, P101, DOI [10.1177/14730952030022002, DOI 10.1177/14730952030022002]
   Hedelin Beatrice, 2008, European Environment, V18, P327, DOI 10.1002/eet.489
   Hedelin B, 2017, J FLOOD RISK MANAG, V10, P226, DOI 10.1111/jfr3.12162
   Hedelin B., 2005, EUR J SPAT DEV, V3, P1
   Hedelin B., 2015, J NAT RESOUR POLICY, V7, P247
   Hedelin B, 2007, ENVIRON MANAGE, V39, P151, DOI 10.1007/s00267-004-0387-0
   Hedelin B, 2019, SUSTAIN SCI, V14, P733, DOI 10.1007/s11625-018-0635-5
   Hedelin B, 2017, WATER POLICY, V19, P286, DOI 10.2166/wp.2016.092
   Hovik S, 2016, J ENVIRON POL PLAN, V18, P535, DOI 10.1080/1523908X.2016.1149049
   Jager NW, 2016, WATER-SUI, V8, DOI 10.3390/w8040156
   James Meadowcroft., 2007, Journal of Environmental Policy and Planning, V9, P193, DOI [10.1080/15239080701631544, DOI 10.1080/15239080701631544]
   Jonsson AC, 2011, J ENVIRON PLANN MAN, V54, P909, DOI 10.1080/09640568.2010.541738
   Jordan A, 2008, ENVIRON PLANN C, V26, P17, DOI 10.1068/cav6
   Jordan A, 2010, ENVIRON POLICY GOV, V20, P147, DOI 10.1002/eet.539
   Jüpner R, 2010, WASSERWIRTSCHAFT, V100, P47
   Karpouzoglou T, 2016, ENVIRON SCI POLICY, V57, P1, DOI 10.1016/j.envsci.2015.11.011
   Knape A., 2020, DEBATE EUS WATER DIR
   Knape A., 2021, WATER AUTHORITIES SH
   Koglin T, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9101836
   Koontz TM, 2014, LAND USE POLICY, V38, P594, DOI 10.1016/j.landusepol.2014.01.005
   Kristianssen AC, 2021, CLIMATE, V9, DOI 10.3390/cli9040052
   Lindholm K., VATTENKRAFTSPRODUKTI
   Liu S, 2013, J ENVIRON MANAGE, V129, P92, DOI 10.1016/j.jenvman.2013.06.047
   Lundqvist L. J., 2004, Local Environment, V9, P413, DOI 10.1080/1354983042000255324
   Lundqvist LJ, 2008, URBAN AFF REV, V43, P299, DOI 10.1177/1078087407304689
   Margerum R.D., CONSENSUS IMPROVING, P1
   Matti S, 2017, WATER POLICY, V19, P99, DOI 10.2166/wp.2016.023
   Miller TR, 2013, SUSTAIN SCI, V8, P279, DOI 10.1007/s11625-012-0180-6
   Ostrom E., 1990, GOVERNING COMMONS EV
   Pahl-Wostl C, 2009, GLOBAL ENVIRON CHANG, V19, P354, DOI 10.1016/j.gloenvcha.2009.06.001
   Prager K, 2010, ENVIRON MANAGE, V46, P711, DOI 10.1007/s00267-010-9560-9
   Prutzer M., 2016, SAMVERKAN DELTAGANDE, P54
   Puja Sawhney Puja Sawhney, 2007, International Review for Environmental Strategies, V7, P117
   Robinson J, 2004, ECOL ECON, V48, P369, DOI 10.1016/j.ecolecon.2003.10.017
   Rutberg B., 2005, ARE MUNICIPALITIES A
   Schoon M, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10030679
   Sevä M, 2017, ENVIRON POLICY GOV, V27, P74, DOI 10.1002/eet.1734
   Smajgl A, 2015, ECOL SOC, V20, DOI 10.5751/ES-07421-200215
   Smith JL, 2008, LOCAL ENVIRON, V13, P353, DOI 10.1080/13549830701803323
   Soderasp J., 2018, LAW INTEGRATED ADAPT
   Soderasp J., 2015, EUR TIDSKR, V18, P508
   Söderasp J, 2019, J ENVIRON LAW, V31, P265, DOI 10.1093/jel/eqz003
   Solve T.W., 199540 SOU, P40
   Waylen KA, 2019, SCI TOTAL ENVIRON, V662, P373, DOI 10.1016/j.scitotenv.2018.12.462
   Westberg L, 2010, ENVIRON COMMUN, V4, P225, DOI 10.1080/17524031003755309
   Williams P, 2002, PUBLIC ADMIN, V80, P103, DOI 10.1111/1467-9299.00296
NR 83
TC 1
Z9 1
U1 1
U2 14
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD MAR
PY 2023
VL 15
IS 6
AR 4980
DI 10.3390/su15064980
PG 22
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA D4DX0
UT WOS:000968262400001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Chen, S
   Gong, BL
AF Chen, Shuai
   Gong, Binlei
TI Response and adaptation of agriculture to climate change: Evidence from
   China
SO JOURNAL OF DEVELOPMENT ECONOMICS
LA English
DT Article
DE Total factor productivity; Stochastic frontier analysis; Climate change;
   Response and adaptation; Agriculture in China
ID PRODUCTIVITY GROWTH; HIGH-TEMPERATURES; ECONOMIC-IMPACTS; FLUCTUATIONS;
   MINIMUM; WEATHER; MAXIMUM; REFORMS; YIELDS; LEARN
AB This article aims to identify the mechanism of how climate change affects agriculture through various channels and the mechanism of longer-run adaptation. Using a county-panel dataset spanning the past 35 years, we evaluate the impact of global warming on agricultural total factor productivity (TFP) as well as the impacts on agricultural inputs and outputs in China. Results show that, in the short run, extreme heat has negative effects on China's agricultural TFP and input utilization, which results in a more negative effect on agricultural output measured by yield. However, longer-run adaptation has offset 37.9% of the short-run effects of extreme heat exposure on TFP, while climate adaptation mitigates agricultural output loss to a greater extent due to more flexible adjustment in labor, fertilizer, and machines in the long run. Despite the detected climate adaptation, projections of impacts under future climate change scenarios still imply a substantial loss in China's agriculture.
C1 [Chen, Shuai; Gong, Binlei] Zhejiang Univ, China Acad Rural Dev CARD, Hangzhou, Peoples R China.
   [Chen, Shuai; Gong, Binlei] Zhejiang Univ, Sch Publ Affairs, Hangzhou, Peoples R China.
C3 Zhejiang University; Zhejiang University
RP Gong, BL (corresponding author), Zhejiang Univ, China Acad Rural Dev CARD, Hangzhou, Peoples R China.
EM gongbinlei@zju.edu.cn
RI chen, shuai/GXG-9235-2022
OI Gong, Binlei/0000-0002-0615-9341
FU National Natural Science Foundation of China [71903172, 71703149];
   Research Program for Humanities and Social Science by Chinese Ministry
   of Education [18YJC790034]; Soft Science Research Program of the
   Ministry of Agriculture and Rural Affairs [RKX202001A]; Soft Science
   Research Program of Zhejiang Province [2020C25020]; Qianjiang Talent
   Program [QJC1902008]; National Social Science Foundation of China
   [19ZDA106]; EfD Initiative of the University of Gothenburg through Sida;
   Fundamental Research Funds for the Central Universities; Academy of
   Social Governance at Zhejiang University
FX We are grateful to Jikun Huang, Eldon Ball, Frank Scrimgeour, Carlos San
   Juan Mesonada, Nillabja Ghosh, Songqing Jin, Shiji Zhao, Paul McNamara,
   Huanguang Qiu, Jinxia Wang, Yu Sheng, Shingo Kimura, Wei Si, Junfei Bai,
   Jian Zhang and the participants at the Second CCAP's Workshop on
   Measuring China's Agricultural Total Factor Productivity and Its
   International Comparison. We would like to express the deepest
   appreciation to Huanzhang Gu, Xigang Zhu, Zhaohui Wu, Weidong Luo,
   Funing Zhong, Zuhui Huang, Jinchuan Shi, Xiaobo Wu, Xianhai Huang, Jiang
   Wei, Wenrong Qian, Kevin Chen, Holly Wang, Biliang Luo, Xiurong He,
   Xinkai Zhu, Jing Zhu, Hengyun Ma, Ruifa Hu, Minjuan Zhao, Chengfang Liu,
   and Xiaohua Yu for their help and comments. We acknowledge the financial
   support of the National Natural Science Foundation of China (71903172
   and 71703149), the Research Program for Humanities and Social Science
   Granted by Chinese Ministry of Education (18YJC790034), Soft Science
   Research Program of the Ministry of Agriculture and Rural Affairs
   (RKX202001A), Soft Science Research Program of Zhejiang Province
   (2020C25020), Qianjiang Talent Program (QJC1902008), the National Social
   Science Foundation of China (19ZDA106), the EfD Initiative of the
   University of Gothenburg through Sida, the Fundamental Research Funds
   for the Central Universities, and Academy of Social Governance at
   Zhejiang University.
CR Acevedo S, 2020, J MACROECON, V65, DOI 10.1016/j.jmacro.2020.103207
   ALLEN JC, 1976, ENVIRON ENTOMOL, V5, P388, DOI 10.1093/ee/5.3.388
   [Anonymous], 1971, AGR DEV INT PERSPECT
   [Anonymous], 2002, J DEV ECON
   Aragon Fernando m, 2020, IN PRESS
   BASKERVILLE GL, 1969, ECOLOGY, V50, P514, DOI 10.2307/1933912
   Battese GE., 1992, J PROD ANAL, V3, P153, DOI [DOI 10.1007/BF00158774, 10.1007/BF00158774]
   Bos JWB, 2010, J DEV ECON, V91, P113, DOI 10.1016/j.jdeveco.2009.07.006
   Burke M, 2016, AM ECON J-ECON POLIC, V8, P106, DOI 10.1257/pol.20130025
   Campbell HF, 1998, J DEV ECON, V57, P421, DOI 10.1016/S0304-3878(98)00095-9
   Chen SA, 2016, J ENVIRON ECON MANAG, V76, P105, DOI 10.1016/j.jeem.2015.01.005
   Chen XG, 2018, AUST J AGR RESOUR EC, V62, P576, DOI 10.1111/1467-8489.12267
   CHRISTENSEN LR, 1973, REV ECON STAT, V55, P28, DOI 10.2307/1927992
   CROCKER TD, 1981, REV ECON STAT, V63, P361, DOI 10.2307/1924353
   Currie J, 2005, Q J ECON, V120, P1003, DOI 10.1162/003355305774268219
   [戴声佩 Dai Shengpei], 2014, [地理学报, Acta Geographica Sinica], V69, P650
   Dekle R, 2010, REV DEV ECON, V14, P487, DOI 10.1111/j.1467-9361.2010.00566.x
   Dell M, 2014, J ECON LIT, V52, P740, DOI 10.1257/jel.52.3.740
   Dell M, 2012, AM ECON J-MACROECON, V4, P66, DOI 10.1257/mac.4.3.66
   Deschênes O, 2007, AM ECON REV, V97, P354, DOI 10.1257/aer.97.1.354
   Deschênes O, 2011, AM ECON J-APPL ECON, V3, P152, DOI 10.1257/app.3.4.152
   Fishman R, 2019, J ENVIRON ECON MANAG, V93, P221, DOI 10.1016/j.jeem.2018.10.001
   Gong BL, 2020, AM J AGR ECON, V102, P641, DOI 10.1002/ajae.12009
   Gong BL, 2020, CHINA ECON REV, V60, DOI 10.1016/j.chieco.2020.101423
   Gong BL, 2020, J CHIN GOV, V5, P249, DOI 10.1080/23812346.2020.1741940
   Gong BL, 2020, J PROD ANAL, V53, P243, DOI 10.1007/s11123-019-00571-8
   Gong BL, 2018, EMERG MARK FINANC TR, V54, P3438, DOI 10.1080/1540496X.2018.1437542
   Gong BL, 2018, J DEV ECON, V132, P18, DOI 10.1016/j.jdeveco.2017.12.005
   Jin SQ, 2010, J PROD ANAL, V33, P191, DOI 10.1007/s11123-009-0145-7
   Kilby C, 2015, J DEV ECON, V115, P111, DOI 10.1016/j.jdeveco.2015.02.005
   Kjellstrom T, 2019, AM J IND MED, V62, P1076, DOI 10.1002/ajim.23051
   LIN JYF, 1992, AM ECON REV, V82, P34
   Liu H, 2004, CLIMATIC CHANGE, V65, P125, DOI 10.1023/B:CLIM.0000037490.17099.97
   Liu MS, 2021, J CHIN GOV, V6, P417, DOI 10.1080/23812346.2020.1721230
   Lobell DB, 2011, NAT CLIM CHANGE, V1, P42, DOI [10.1038/NCLIMATE1043, 10.1038/nclimate1043]
   MENDELSOHN R, 1994, AM ECON REV, V84, P753
   Mondiale B., 2008, World Development report: agriculture for development
   Pittelkow CM, 2015, NATURE, V517, P365, DOI 10.1038/nature13809
   Pratt AN, 2009, CHINA AGRIC ECON REV, V1, P9, DOI 10.1108/17561370910915339
   Roltsch WJ, 1999, INT J BIOMETEOROL, V42, P169, DOI 10.1007/s004840050101
   Ruttan VW, 2002, J ECON PERSPECT, V16, P161, DOI 10.1257/089533002320951028
   Schlenker W, 2006, REV ECON STAT, V88, P113, DOI 10.1162/rest.2006.88.1.113
   Schlenker W, 2016, REV ECON STUD, V83, P768, DOI 10.1093/restud/rdv043
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Sheng Y, 2020, AUST J AGR RESOUR EC, V64, P82, DOI 10.1111/1467-8489.12327
   Sheng Y, 2019, AM J AGR ECON, V101, P790, DOI 10.1093/ajae/aay104
   Thirtle C, 2003, WORLD DEV, V31, P1959, DOI 10.1016/j.worlddev.2003.07.001
   Wang JX, 2009, AGR ECON-BLACKWELL, V40, P323, DOI 10.1111/j.1574-0862.2009.00379.x
   Wang SL, 2013, AGR ECON-BLACKWELL, V44, P241, DOI 10.1111/agec.12008
   Wang XB, 2016, AGR ECON-BLACKWELL, V47, P309, DOI 10.1111/agec.12231
   Warszawski L, 2014, P NATL ACAD SCI USA, V111, P3228, DOI 10.1073/pnas.1312330110
   Welch JR, 2010, P NATL ACAD SCI USA, V107, P14562, DOI 10.1073/pnas.1001222107
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Zhang P, 2018, J ENVIRON ECON MANAG, V88, P1, DOI 10.1016/j.jeem.2017.11.001
   Zhang P, 2017, J ENVIRON ECON MANAG, V83, P8, DOI 10.1016/j.jeem.2016.12.001
   Zhang SR, 2020, CHINA AGR ECON REV, V12, P409, DOI 10.1108/CAER-04-2020-0055
   Zivin JG, 2014, J LABOR ECON, V32, P1, DOI 10.1086/671766
NR 57
TC 184
Z9 189
U1 129
U2 784
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0304-3878
EI 1872-6089
J9 J DEV ECON
JI J. Dev. Econ.
PD JAN
PY 2021
VL 148
AR 102557
DI 10.1016/j.jdeveco.2020.102557
PG 17
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA PE2CJ
UT WOS:000598176900007
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Jones, L
   Harvey, B
   Cochrane, L
   Cantin, B
   Conway, D
   Cornforth, RJ
   De Souza, K
   Kirbyshire, A
AF Jones, Lindsey
   Harvey, Blane
   Cochrane, Logan
   Cantin, Bernard
   Conway, Declan
   Cornforth, Rosalind J.
   De Souza, Ken
   Kirbyshire, Amy
TI Designing the next generation of climate adaptation research for
   development
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Adaptation; Research; Funding; Development
ID SCIENCE; AFRICA; RESILIENCE; RELEVANT; POLICY; ASIA
AB Adaptation research has changed significantly in recent years as funders and researchers seek to encourage greater impact, ensure value for money and promote interdisciplinarity across the natural and social sciences. While these developments are inherently positive, they also bring fresh challenges. With this in mind, this paper presents an agenda for the next generation of climate adaptation research for development. The agenda is based on insights from a dialogue session held at the 2016 Adaptation Futures conference as well as drawing on the collective experience of the authors. We propose five key areas that need to be changed in order to meet the needs of future adaptation research, namely: increasing transparency and consultation in research design; encouraging innovation in the design and delivery of adaptation research programmes; demonstrating impact on the ground; addressing incentive structures; and promoting more effective brokering, knowledge management and learning. As new international funding initiatives start to take shape, we underscore the importance of learning from past experiences and scaling-up of successful innovations in research funding models.
C1 [Jones, Lindsey; Conway, Declan] London Sch Econ, Grantham Inst Climate Change & Environm, Houghton St, London WC2A 2AE, England.
   [Jones, Lindsey; Harvey, Blane] Overseas Dev Inst, Risk & Resilience Programme, 203 Blackfriars Rd, London SE1 8NJ, England.
   [Harvey, Blane] McGill Univ, Dept Integrated Studies Educ, 3700 McTavish St, Montreal, PQ H3A 1Y2, Canada.
   [Cochrane, Logan] Int Dev Res Ctr, 150 Kent St, Ottawa, ON K1P 0B2, Canada.
   [Cochrane, Logan] Carleton Univ, Global & Int Studies, 1125 Colonel By Dr, Ottawa, ON, Canada.
   [Cantin, Bernard] Agr & Agri Food Canada, 1341 Baseline Rd, Ottawa, ON K1A 0C5, Canada.
   [Cornforth, Rosalind J.] Univ Reading, Walker Inst, Reading RG6 7BE, Berks, England.
   [De Souza, Ken] Dept Int Dev, Res & Evidence Div, 22 Whitehall, London SW1A 2EG, England.
   [Kirbyshire, Amy] Climate & Dev Knowledge Network, 203 Blackfriars Rd, London SE1 8NJ, England.
C3 University of London; London School Economics & Political Science;
   McGill University; Carleton University; Agriculture & Agri Food Canada;
   University of Reading
RP Jones, L (corresponding author), London Sch Econ, Grantham Inst Climate Change & Environm, Houghton St, London WC2A 2AE, England.; Jones, L (corresponding author), Overseas Dev Inst, Risk & Resilience Programme, 203 Blackfriars Rd, London SE1 8NJ, England.
EM l.jones3@lse.ac.uk; b.harvey@odi.org.uk; logan.cochrane@carleton.ca;
   bernard.Cantin@agr.gc.ca; d.conway@lse.ac.uk;
   r.j.cornforth@reading.ac.uk; k-desouza@dfid.gov.ac.uk;
   a.kirbyshire@cdkn.org.uk
RI Conway, Declan/HCH-7778-2022; Cochrane, Logan/X-7882-2019; Cornforth,
   Rosalind/D-2263-2019
OI Cochrane, Logan/0000-0001-7321-8295; Conway, Declan/0000-0002-4590-6733;
   Harvey, Blane/0000-0002-6626-4290; Cornforth,
   Rosalind/0000-0003-4379-9556
FU NERC [NE/M020371/1, NE/M008983/1] Funding Source: UKRI
CR [Anonymous], 2007, A stitch in time: lessons for climate change adaptation from the AIACC project
   Berthélemy JC, 2006, REV DEV ECON, V10, P179, DOI 10.1111/j.1467-9361.2006.00311.x
   Blicharska M, 2017, NAT CLIM CHANGE, V7, P21, DOI 10.1038/NCLIMATE3163
   Boyd E, 2013, NAT CLIM CHANGE, V3, P631, DOI 10.1038/NCLIMATE1856
   Buffardi A, 2015, METHODS LAB PUBLICAT
   Cochrane L, 2017, REG ENVIRON CHANGE, V17, P1553, DOI 10.1007/s10113-017-1140-6
   Conway D, 2014, NAT CLIM CHANGE, V4, P339, DOI 10.1038/NCLIMATE2199
   De Souza K, 2015, REG ENVIRON CHANGE, V15, P747, DOI 10.1007/s10113-015-0755-8
   Dodson J., 2017, BUILDING PARTNERSHIP
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Eyben R, 2015, UNCOVERING POLITICS
   Forch W., 2014, Agric Food Secur, V31, P1, DOI DOI 10.1186/2048-7010-3-13
   Green D., 2016, HOW CHANGE HAPPENS
   Harvey B, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9020315
   Hewitson B, 2015, NAT GEOSCI, V8, P497, DOI 10.1038/ngeo2465
   James R, 2014, NAT CLIM CHANGE, V4, P938, DOI 10.1038/nclimate2411
   Jones L., 2016, CHANGING ROLE NGOS S
   Klein R, 2017, ADVANCING CLIMATE AD
   Kuhlmann Stefan., 2014, The Challenge of Addressing Grand Challenges. A Think Piece on How Innovation Can be Driven Towards the Grand Challenges as Defined Under the Prospective European Union Framework Programme Horizon 2020. Report to ERIAB.
   Lang DJ, 2012, SUSTAIN SCI, V7, P25, DOI 10.1007/s11625-011-0149-x
   Leemans R, 2016, CURR OPIN ENV SUST, V19, P103, DOI 10.1016/j.cosust.2016.01.001
   Michaels S, 2009, ENVIRON SCI POLICY, V12, P994, DOI 10.1016/j.envsci.2009.05.002
   Moss C., 2016, NEXT GENERATION IDEA
   Mustelin J, 2013, CLIM DEV, V5, P189, DOI 10.1080/17565529.2013.812953
   OECD, 2014, RES CO OP DEV DEV CO
   Reid WV, 2010, SCIENCE, V330, P916, DOI 10.1126/science.1196263
   RITTEL HWJ, 1973, POLICY SCI, V4, P155, DOI 10.1007/BF01405730
   SARUA, 2014, STRENGTH U CONTR CLI
   Stern Nicholas., 2016, Building on success and learning from experience: An independent review of the research excellence framework
   Steynor A, 2016, CLIM RISK MANAG, V13, P95, DOI 10.1016/j.crm.2016.03.001
   Swart R, 2009, CLIMATIC CHANGE, V92, P1, DOI 10.1007/s10584-008-9444-7
   Tschakert P, 2016, GLOBAL ENVIRON CHANG, V40, P182, DOI 10.1016/j.gloenvcha.2016.07.004
   Turnhout E, 2013, SCI PUBL POLICY, V40, P354, DOI 10.1093/scipol/scs114
   Turnpenny J, 2009, ENVIRON SCI POLICY, V12, P347, DOI 10.1016/j.envsci.2009.01.004
   Vallejo B, 2016, WORLD DEV, V79, P1, DOI 10.1016/j.worlddev.2015.10.044
NR 35
TC 25
Z9 26
U1 0
U2 10
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD JAN
PY 2018
VL 18
IS 1
SI SI
BP 297
EP 304
DI 10.1007/s10113-017-1254-x
PG 8
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA FR6EE
UT WOS:000419157400023
OA hybrid
DA 2025-01-10
ER

PT J
AU Pirasteh, S
   Fang, YM
   Mafi-Gholami, D
   Abulibdeh, A
   Nouri-Kamari, A
   Khonsari, N
AF Pirasteh, Saied
   Fang, Yiming
   Mafi-Gholami, Davood
   Abulibdeh, Ammar
   Nouri-Kamari, Akram
   Khonsari, Nasim
TI Enhancing vulnerability assessment through spatially explicit modeling
   of mountain social-ecological systems exposed to multiple environmental
   hazards
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Google Earth Engine; Fuzzy Analytic Hierarchy Process; Machine learning;
   Resilience enhancement
ID CLIMATE-CHANGE; FOREST VEGETATION; ZAGROS FORESTS; ECOSYSTEM; REGION;
   ASSOCIATION; RESILIENCE; FRAMEWORK; DROUGHT; IMPACTS
AB The evaluation of the vulnerability of coupled socio-ecological systems is critical for addressing and preventing the adverse impacts of various environmental hazards and devising strategies for climate change adaptation. The initial step in vulnerability assessment involves exposure assessment, which entails quantifying and mapping the risks posed by multiple environmental hazards, thereby offering valuable insights for the implementation of vulnerability assessment methodologies. Consequently, this study sought to model the exposure of coupled social -ecological systems in mountainous regions to various environmental hazards. By a set of socio-economic, climatic, geospatial, hydrological, and demographic data, as well as satellite imagery, and examining 11 hazards, including droughts, pests, dust storms, winds, extreme temperatures, evapotranspiration, landslides, floods, wildfires, and social vulnerability, this research employed machine learning (ML) techniques and the fuzzy analytical hierarchy process (FAHP). Expert opinions were utilized to guide hazard weighting and calculate the exposure index (EI). Through the precise spatial mapping of EI variations across the socio-ecological systems in mountainous areas, this investigation provides insights into vulnerability to multiple environmental hazards, thereby laying the groundwork for future endeavors in supporting national -level vulnerability assessments aimed at fostering sustainable environments. The findings reveal that social vulnerability and pests receive the highest weighting, while floods and landslides are ranked lower. All hazards demonstrate significant correlations with the EI, with droughts exhibiting the strongest correlation (r > 0.81). Spatial analysis indicates a north -south gradient in forest exposure, with southern regions showing higher exposure hotspots (EI 29.08) compared to northern areas (EI 10.60). Validation based on Area Under Curve (AUC) and Consistency Rate (CR) in FAHP demonstrates robustness, with AUC values exceeding 0.78 and CR values below 0.1. Considering the anticipated intensification of hazards, management strategies should prioritize reducing social vulnerability, restore degraded areas using drought -resistant species, combat pests, and mitigate desertification. By integrating multidisciplinary data and expert opinions, this research contributes to informed decision -making regarding sustainable forest management and climate resilience in mountain ecosystems.
C1 [Pirasteh, Saied; Mafi-Gholami, Davood; Nouri-Kamari, Akram] Shaoxing Univ, Inst Artificial Intelligence, 508 West Huancheng Rd, Shaoxing 312000, Zhejiang, Peoples R China.
   [Pirasteh, Saied] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Geotech & Geomat, Chennai, Tamil Nadu, India.
   [Fang, Yiming] Shaoxing Univ, Sch Mech & Elect Engn, Shaoxing 312000, Peoples R China.
   [Mafi-Gholami, Davood] Shahrekord Univ, Fac Nat Resources & Earth Sci, Dept Forest Sci, Shahrekord 8818634141, Iran.
   [Abulibdeh, Ammar] Qatar Univ, Coll Arts & Sci, Dept Humanities, Appl Geog & GIS Program, POB 2713, Doha, Qatar.
   [Nouri-Kamari, Akram] Univ Tehran, Fac Nat Resources, Dept Environm, Tehran, Iran.
   [Khonsari, Nasim] Westcliff Univ, Coll Business, 17877 Von Karman Ave, Irvine, CA 92614 USA.
C3 Shaoxing University; Saveetha Institute of Medical & Technical Science;
   Saveetha School of Engineering; Shaoxing University; Shahrekord
   University; Qatar University; University of Tehran
RP Fang, YM (corresponding author), Shaoxing Univ, Sch Mech & Elect Engn, Shaoxing 312000, Peoples R China.
EM sapirasteh1@usx.edu.cn; ymfang@usx.edu.cn; d.mafigholami@sku.ac.ir;
   aabulibdeh@qu.edu.qa; a.nourikamari@ut.ac.ir;
   N.Khonsari.198@westcliff.edu
RI Khonsari, Nasim/KQV-1152-2024; Abulibdeh, Ammar/IXN-0523-2023
OI Abulibdeh, Ammar/0000-0002-0899-3655; Khonsari,
   Nasim/0009-0006-3402-5021
FU Institute of Arti- ficial Intelligence at Shaoxing University
FX This collaborative research represents an international effort to
   establish a strong foundation in partnership with the Institute of Arti-
   ficial Intelligence at Shaoxing University. Our focus spans
   cross-disciplinary studies, including Geospatial Artificial Intelligence
   (GeoAI) and climate change, all in alignment with the Sustainable
   Development Goals (SDGs) for 2030. It is important to note that this
   research was conducted on a voluntary basis, without any external
   funding.
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Afify MS, 2023, ASTROPHYS SPACE SCI, V368, DOI 10.1007/s10509-023-04223-0
   Alavi Mehran, 2016, Biharean Biologist, V10, P113
   ANSELIN L, 1995, GEOGR ANAL, V27, P93, DOI 10.1111/j.1538-4632.1995.tb00338.x
   Atijosan AO, 2021, INT J HYDROL SCI TEC, V12, P16, DOI 10.1504/IJHST.2021.116239
   Bathrellos GD, 2017, SCI TOTAL ENVIRON, V575, P119, DOI 10.1016/j.scitotenv.2016.10.025
   Pham BT, 2021, ECOL INFORM, V64, DOI 10.1016/j.ecoinf.2021.101389
   Pham BT, 2020, SYMMETRY-BASEL, V12, DOI 10.3390/sym12061022
   Brown J., 2017, J. Environ. Sci., V15, P345
   Chang DY, 1996, EUR J OPER RES, V95, P649, DOI 10.1016/0377-2217(95)00300-2
   Chu DA, 2013, ATMOS ENVIRON, V79, P172, DOI 10.1016/j.atmosenv.2013.06.031
   Cui GS, 2016, J FORESTRY RES, V27, P489, DOI 10.1007/s11676-015-0201-2
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Darabi H, 2019, POLLUTION, V5, P597, DOI 10.22059/poll.2018.262881.486
   Das S, 2013, ESTUAR COAST SHELF S, V134, P98, DOI 10.1016/j.ecss.2013.09.021
   Depietri Y, 2013, INT J DISAST RISK RE, V6, P98, DOI 10.1016/j.ijdrr.2013.10.001
   Ding M, 2022, SCI TOTAL ENVIRON, V828, DOI 10.1016/j.scitotenv.2022.154041
   Dong XJ, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15143641
   Dunn CJ, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab6498
   Etemadi H, 2016, THEOR APPL CLIMATOL, V126, P35, DOI 10.1007/s00704-015-1552-5
   Euskirchen ES, 2010, CAN J FOREST RES, V40, P1336, DOI 10.1139/X09-209
   FAO, 2020, Global Forest Resources Assessment 2020: Main Report
   Fernández C, 2009, STOCH ENV RES RISK A, V23, P1063, DOI 10.1007/s00477-008-0277-8
   Fischer A.P., 2016, For. Ecol. Manag., V375, P92
   Ford JD, 2004, ARCTIC, V57, P389, DOI 10.14430/arctic516
   Fortin MJ, 2005, SPATIAL ANALYSIS: A GUIDE FOR ECOLOGISTS
   Fremout T, 2020, GLOBAL CHANGE BIOL, V26, P3552, DOI 10.1111/gcb.15028
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   García S, 2008, J MACH LEARN RES, V9, P2677
   General Department of Natural Resources and Watershed Management of Lorestan Province (LNRWM), 2023, Watershed management plan of Lorestan province
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Gonzalez-Martin C, 2014, ADV AGRON, V127, P1, DOI 10.1016/B978-0-12-800131-8.00001-7
   Gradstein S. Robbert, 2008, Ecotropica-Bonn, V14, P15
   Green R., 2019, Ecol. Model., V212, P189
   Hall J, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-61164-2
   Hicke J.A., 2012, J. Geophys. Res. Biogeosci., V117
   Hosonuma N, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/4/044009
   Hu K, 2018, ENVIRON SCI POLLUT R, V25, P6909, DOI 10.1007/s11356-017-0715-6
   ICH, 2023, ABOUT US
   Ikegami M, 2018, FOREST ECOL MANAG, V409, P343, DOI 10.1016/j.foreco.2017.11.005
   Iran Meteorological Organization, 2023, About us
   Jaafari A, 2024, SUSTAIN CITIES SOC, V100, DOI 10.1016/j.scs.2023.105051
   Jaafari A, 2022, NAT HAZARDS, V114, P457, DOI 10.1007/s11069-022-05397-6
   Johnson D., 2016, Environ. Sci. Technol., V24, P567
   Jung JM, 2023, ECOL EVOL, V13, DOI 10.1002/ece3.10104
   Kamali S, 2023, WATER RESOUR MANAG, V37, P2925, DOI 10.1007/s11269-022-03268-0
   Keenan RJ, 2015, FOREST ECOL MANAG, V352, P9, DOI 10.1016/j.foreco.2015.06.014
   Kelly M., 2013, Clim. Chang., V133, P5
   Khosravi K, 2020, J HYDROL, V591, DOI 10.1016/j.jhydrol.2020.125552
   Nguyen KA, 2019, SCI TOTAL ENVIRON, V682, P31, DOI 10.1016/j.scitotenv.2019.04.069
   Kristensen E, 2008, MAR ECOL PROG SER, V370, P53, DOI 10.3354/meps07642
   Kumar H, 2019, INT J GEOHERITAGE PA, V7, P45, DOI DOI 10.1016/J.IJGEOP.2019.05.003
   Lahsen M, 2010, CURR OPIN ENV SUST, V2, P364, DOI 10.1016/j.cosust.2010.10.009
   Lapola DM, 2023, SCIENCE, V379, P349, DOI 10.1126/science.abp8622
   Leberger R, 2020, BIOL CONSERV, V241, DOI 10.1016/j.biocon.2019.108299
   Levy RC, 2010, ATMOS CHEM PHYS, V10, P10399, DOI 10.5194/acp-10-10399-2010
   Li LH, 2017, SCI REP-UK, V7, DOI [10.1038/srep40745, 10.1038/s41598-017-11063-w]
   Li W, 2023, NAT SUSTAIN, V6, DOI 10.1038/s41893-022-01020-5
   Liu HY, 2013, GLOBAL CHANGE BIOL, V19, P2500, DOI 10.1111/gcb.12217
   Liu Q, 2020, ATMOS POLLUT RES, V11, P1637, DOI 10.1016/j.apr.2020.07.001
   Macek M, 2019, LANDSCAPE ECOL, V34, P2541, DOI 10.1007/s10980-019-00903-x
   Mafi-Gholami D, 2021, J ENVIRON MANAGE, V299, DOI 10.1016/j.jenvman.2021.113573
   Maftei C., 2024, Modeling and Monitoring Extreme Hydrometeorological Events, P90
   Mahendra RS, 2011, OCEAN COAST MANAGE, V54, P302, DOI 10.1016/j.ocecoaman.2010.12.008
   Mahmoudi B, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15119008
   Mansourmoghaddam M., 2022, Desert Management, V10, P77
   MCKEE TB, 1993, P 8 C APPL CLIM AN C
   Michelsen O, 2014, INT J LIFE CYCLE ASS, V19, P1214, DOI 10.1007/s11367-014-0742-1
   Mitchel A., 2005, The ESRI Guide to GIS Analysis, Volume 2: Spartial Measurements and Statistics, V2
   Mo LD, 2023, NATURE, V624, P92, DOI 10.1038/s41586-023-06723-z
   Modarres R, 2007, STOCH ENV RES RISK A, V21, P223, DOI 10.1007/s00477-006-0058-1
   Muller E.V., 2023, Ph.D. thesis
   National Cartography Center of Iran (NCC), 2023, ABOUT US
   Nguyen TN, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16071244
   Osgouei PE, 2023, INT ARCH PHOTOGRAMM, P509, DOI 10.5194/isprs-archives-XLVIII-M-1-2023-509-2023
   Özcan O, 2018, J FORESTRY RES, V29, P709, DOI 10.1007/s11676-017-0505-5
   Padhiary J, 2022, WATER RESOUR MANAG, V36, P5163, DOI 10.1007/s11269-022-03296-w
   Ngo PTT, 2021, GEOSCI FRONT, V12, P505, DOI 10.1016/j.gsf.2020.06.013
   Pirasteh S, 2021, INT J APPL EARTH OBS, V102, DOI 10.1016/j.jag.2021.102390
   Pokhriyal P, 2020, MODEL EARTH SYST ENV, V6, P821, DOI 10.1007/s40808-019-00710-y
   Pourghasemi HR, 2019, SCI TOTAL ENVIRON, V692, P556, DOI 10.1016/j.scitotenv.2019.07.203
   Pourhashemi M, 2004, SCAND J FOREST RES, V19, P72, DOI 10.1080/14004080410034083
   Pouyan S, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-94266-6
   Powlen KA, 2023, CONSERV BIOL, V37, DOI 10.1111/cobi.14058
   Rawal RS, 2012, J MT SCI-ENGL, V9, P157, DOI 10.1007/s11629-012-2029-y
   Roshani, 2024, ECOL INFORM, V80, DOI 10.1016/j.ecoinf.2024.102494
   Roy HE, 2017, CONSERV LETT, V10, P477, DOI 10.1111/conl.12297
   Saaty T.L., 1980, Agric. Econ. Rev., V70, P10
   Schilling J., 2013, Environment and Natural Resources Research, V3, P27
   Seidl R, 2014, ECOL APPL, V24, P2063, DOI 10.1890/14-0255.1
   Sharma J, 2017, ENVIRON MANAGE, V60, P544, DOI 10.1007/s00267-017-0894-4
   Shin MJ, 2023, HYDROL RES, V54, P1299, DOI 10.2166/nh.2023.192
   SIvrIkaya F., 2012, Bartin Orman Fakultesi Dergisi, V14, P69
   Skilodimou HD, 2019, ENVIRON EARTH SCI, V78, DOI 10.1007/s12665-018-8003-4
   Smith K., 2018, Environ. Res. Lett., V28, P45
   Soheili F, 2023, WATER AIR SOIL POLL, V234, DOI 10.1007/s11270-023-06349-x
   Soltani A, 2012, ECOL ECON, V79, P60, DOI 10.1016/j.ecolecon.2012.04.019
   Soto VH, 2020, ATMOSFERA, V33, P301, DOI [10.20937/atm.52768, 10.20937/ATM.52768]
   Spehn EM, 2011, PLANT ECOL DIVERS, V4, P301, DOI 10.1080/17550874.2012.698660
   Su SL, 2015, OCEAN COAST MANAGE, V116, P1, DOI 10.1016/j.ocecoaman.2015.06.026
   Suwarno S., 2021, Int. J. Power Electron. Drive Syst. (IJPEDS), V12, P1102, DOI [10.11591/ijpeds.v12.i2.pp1102-1113, DOI 10.11591/IJPEDS.V12.I2.PP1102-1113]
   Talebi KS, 2014, PLANT VEG, V10, P1, DOI 10.1007/978-94-007-7371-4
   Thakur S, 2021, TREES FOREST PEOPLE, V6, DOI 10.1016/j.tfp.2021.100156
   Thorne JH, 2018, CLIMATIC CHANGE, V148, P387, DOI 10.1007/s10584-017-2010-4
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Upgupta S, 2015, CLIM RISK MANAG, V10, P63, DOI 10.1016/j.crm.2015.08.002
   Valavi R, 2019, THEOR APPL CLIMATOL, V137, P1015, DOI 10.1007/s00704-018-2625-z
   Varoujan K.S., 2013, Nat. Sci., V2013
   Wan JZ, 2018, SCI TOTAL ENVIRON, V621, P1633, DOI 10.1016/j.scitotenv.2017.10.065
   Wang W, 2022, BUILD ENVIRON, V209, DOI 10.1016/j.buildenv.2021.108644
   Wang X., 2019, J. Geogr. Sci., V29, P1465
   White M., 2021, Environ. Sci. Pollut. Res., V18, P123
   Wilhelmi OV, 2013, ENVIRON SCI POLICY, V26, P49, DOI 10.1016/j.envsci.2012.07.005
   Wunder S, 2014, WORLD DEV, V64, pS1, DOI 10.1016/j.worlddev.2014.03.007
   WWF, 2017, Tackling forest loss and damage
   Xia M, 2021, ECOL INDIC, V123, DOI 10.1016/j.ecolind.2020.107274
   Xiao JF, 2013, AGR FOREST METEOROL, V182, P76, DOI 10.1016/j.agrformet.2013.08.007
   Yoshikawa T, 2023, SCI REP-UK, V13, DOI 10.1038/s41598-023-31597-6
   Zhu J, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-76688-w
   Zou LD, 2020, INT J BIOMETEOROL, V64, P701, DOI 10.1007/s00484-019-01858-z
NR 121
TC 3
Z9 3
U1 21
U2 29
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD JUN 20
PY 2024
VL 930
AR 172744
DI 10.1016/j.scitotenv.2024.172744
EA MAY 2024
PG 18
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA TC0O5
UT WOS:001238943700001
PM 38685429
DA 2025-01-10
ER

PT J
AU Hoque, M
AF Hoque, Morshadul
TI The impact of floods on the livelihood of rural women farmers and their
   adaptation strategies: insights from Bangladesh
SO NATURAL HAZARDS
LA English
DT Article
DE Flood; Adaptation strategies; Local knowledge; Livelihood; Rural
   Bangladeshi women
ID CLIMATE-CHANGE ADAPTATION; LOCAL KNOWLEDGE; INDIGENOUS KNOWLEDGE;
   COASTAL; VULNERABILITY; DETERMINANTS; AGRICULTURE; LIVESTOCK; ISLAND
AB This study examines the impact of floods on the livelihood of rural Bangladeshi women farmers, such as agriculture, livestock, energy, and water resources, and their adaptation strategies. This research utilizes qualitative and quantitative approaches, focusing more on the qualitative data. Quantitative data were collected using a structured questionnaire with a series of close-ended questions. Key informant interviews and focus group discussions were mainly used to collect qualitative data. A total of 120 samples were drawn by applying snowball sampling from two flood-prone remote villages in Cox's Bazar district, Bangladesh. The sample units were rural women exclusively engaged in farming, different rural income-generating activities, and traditional household responsibilities. Thematic analysis and descriptive statistics were mainly used to analyze qualitative and quantitative data. The study's findings reveal that floods devastate the four sectors of rural women farmers in Bangladesh. However, they apply different adaptation strategies to mitigate the detrimental impact of floods. Empirical evidence also discloses that local knowledge is the primary source among women farmers for developing different adaptation strategies in four sectors such as 60% in agriculture, 70% in livestock, 65% in energy, and 55% in water resource management. According to data, 54% of women respondents reveal that community practice is their primary source of adaptation for crop diversification; in contrast, 47% of participants disclose that family practice is their main adaptation source in gathering animal feed. 7% of interviewees report that their own experience is their major adaptation source in collecting dry leaves and branches of trees for cooking. At the same time, an equal percentage of women disclose that interaction with nature is their key adaptation source in making portable stoves for cooking food during floods. The result further shows that community and family practices are the most common and dominant local knowledge sources among women farmers. This study is expected to help the policy-making community in Bangladesh to incorporate local knowledge in significant climate change-related policy documents.
C1 [Hoque, Morshadul] Univ Chittagong, Dept Publ Adm, Chittagong, Bangladesh.
C3 University of Chittagong
RP Hoque, M (corresponding author), Univ Chittagong, Dept Publ Adm, Chittagong, Bangladesh.
EM morhoque@gmail.com
FU The author is indebted and grateful to Dr. Shahjahan Bhuiyan, The
   American University in Cairo, for his valuable suggestions while
   preparing this article.; American University in Cairo
FX The author is indebted and grateful to Dr. Shahjahan Bhuiyan, The
   American University in Cairo, for his valuable suggestions while
   preparing this article.
CR Abedin M., 2013, CLIMATE CHANGE ADAPT, P165, DOI [10.1007/978-4-431-54249-0_10, DOI 10.1007/978-4-431-54249-0_10]
   Abedin MA, 2019, INT J DISAST RISK SC, V10, P28, DOI 10.1007/s13753-018-0211-8
   Acevedo M.C., 2015, EFFECT EXTREME UNPUB
   Ahmed A. M. M. M., 2007, Journal of Developments in Sustainable Agriculture, V2, P35
   Ahmed T, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13111051
   Akther Shalina, 2010, International Journal of Biodiversity Science Ecosystem Services & Management, V6, P35, DOI 10.1080/21513732.2010.505011
   Alam GMM, 2017, CLIM RISK MANAG, V17, P52, DOI 10.1016/j.crm.2017.06.006
   Alamgir M, 2018, CARDIOLOGY RES PRACT, P1, DOI DOI 10.1155/2018/1483041
   Alston, 2017, WOMEN CLIMATE CHANGE
   Anik SI, 2012, MITIG ADAPT STRAT GL, V17, P879, DOI 10.1007/s11027-011-9350-6
   [Anonymous], 2009, National Report "To the convention on Biological diversity ", P1
   Arif M, 2019, ADVANCES IN RICE RESEARCH FOR ABIOTIC STRESS TOLERANCE, P585, DOI 10.1016/B978-0-12-814332-2.00029-0
   Azad AK, 2013, INT J DISAST RISK SC, V4, P190, DOI 10.1007/s13753-013-0020-z
   Balakrishnan R., 2005, RURAL WOMEN FOOD SEC, P1
   Banerjee L, 2010, OXF DEV STUD, V38, P339, DOI 10.1080/13600818.2010.505681
   Berkes F, 2000, ECOL APPL, V10, P1251, DOI 10.2307/2641280
   Bhattacharjee K, 2018, INT J DISAST RISK RE, V31, P758, DOI 10.1016/j.ijdrr.2018.07.017
   Biswas JC, 2019, NAT HAZARDS, V99, P705, DOI 10.1007/s11069-019-03768-0
   Blakeney M., 2020, LOCAL KNOWLEDGE INTE, P67, DOI [10.1007/978-981-15-4611-2_4, DOI 10.1007/978-981-15-4611-2_4]
   Butt T. M., 2010, Journal of Agriculture and Social Sciences, V6, P53
   Campbell JR, 1999, CLIMATE CHANGE ADAPT
   Chisadza B, 2013, DISASTER PREV MANAG, V22, P312, DOI 10.1108/DPM-10-2012-0109
   Chowdhury JR, 2022, INT J DISAST RISK RE, V73, DOI 10.1016/j.ijdrr.2022.102881
   Creswell J. W., 2018, Research design: qualitative, quantitative, and mixed methods approaches
   Dewan TH, 2015, WEATHER CLIM EXTREME, V7, P36, DOI 10.1016/j.wace.2014.11.001
   Dien VT, 2014, GUIDELINE INDIGENOUS
   Duvail S, 2007, INT J BIOMETEOROL, V52, P33, DOI 10.1007/s00484-007-0105-8
   Erman A., 2021, Gender dimensions of disaster risk and resilience: existing evidence, DOI [10.1596/35202, DOI 10.1596/35202]
   Ferdushi KF, 2019, CLIMATE, V7, DOI 10.3390/cli7070085
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Ghosh MK., 2021, EUR J AGR FOOD SCI, V20, P170, DOI [10.24018/ejfood.2021.3.1.235, DOI 10.24018/EJFOOD.2021.3.1.235]
   Hiwasaki L, 2014, INT J DISAST RISK RE, V10, P15, DOI 10.1016/j.ijdrr.2014.07.007
   Son HN, 2019, AGR SYST, V176, DOI 10.1016/j.agsy.2019.102683
   Hoq MS, 2021, ENVIRON MANAGE, V67, P532, DOI 10.1007/s00267-021-01441-6
   Hossain B., 2019, Bangladesh Environ Manag Sustain Dev, V8, P46
   Hossain B, 2020, PROG DISASTER SCI, V6, DOI 10.1016/j.pdisas.2020.100079
   Hussain M, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-019-7956-4
   Islam MT, 2017, J ENVIRON MANAGE, V200, P347, DOI 10.1016/j.jenvman.2017.05.092
   Islam MN., 2011, INDIAN J POWER RIVER, V61, P159
   Islam MN, 2022, WATER RESOUR RES, V58, DOI 10.1029/2021WR030241
   JABBAR MA, 1990, DISASTERS, V14, P358, DOI 10.1111/j.1467-7717.1990.tb01081.x
   Kabir H., 2019, Disaster Adv., V12, P48
   Kabir MS, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11205842
   Keniger LE, 2013, INT J ENV RES PUB HE, V10, P913, DOI 10.3390/ijerph10030913
   Komatsu H, 2018, FOOD POLICY, V79, P256, DOI 10.1016/j.foodpol.2018.07.002
   Kundzewicz ZW, 2019, WATER-SUI, V11, DOI 10.3390/w11071399
   Mabuku MP, 2019, PHYS CHEM EARTH, V111, P20, DOI 10.1016/j.pce.2018.12.009
   Mavhura E, 2013, INT J DISAST RISK RE, V5, P38, DOI 10.1016/j.ijdrr.2013.07.001
   McNamara KE, 2011, LOCAL ENVIRON, V16, P887, DOI 10.1080/13549839.2011.615304
   Mirza MMQ, 2011, REG ENVIRON CHANGE, V11, pS95, DOI 10.1007/s10113-010-0184-7
   Mojid MA, 2020, IOP C SERIES EARTH E, V423, P1
   Mondal MSH., 2020, BANGLADESH CLIMATE, V9, P1
   Naess LO, 2013, WIRES CLIM CHANGE, V4, P99, DOI 10.1002/wcc.204
   Nhemachena C, 2020, WATER-SUI, V12, DOI 10.3390/w12102673
   Njenga M, 2021, ENERGY RES SOC SCI, V77, DOI 10.1016/j.erss.2021.102071
   Norouzi G., 2012, Middle East Journal of Scientific Research, V12, P921
   Nyong A., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P787, DOI 10.1007/s11027-007-9099-0
   Okonya J. S., 2013, Journal of Agricultural Science (Toronto), V5, P252
   Oyebola OO, 2021, ENVIRON DEV SUSTAIN, V23, P12761, DOI 10.1007/s10668-020-01183-1
   Patil P.J., 2018, International Journal of Applied Research, V4, P109
   Petzold J, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb330
   Rahman HMT, 2015, WETLANDS, V35, P487, DOI 10.1007/s13157-015-0635-5
   Rakib MA, 2020, CHEMOSPHERE, V246, DOI 10.1016/j.chemosphere.2019.125646
   Sarkar R, 2015, INT J DISAST RISK RE, V14, P411, DOI 10.1016/j.ijdrr.2015.09.007
   Shakhawat Hossain M, 2020, ECOL INDIC, V112, DOI 10.1016/j.ecolind.2020.106181
   Shaw Rajib., 2006, Journal of Science Culture, V72, P1
   Shaw Rajib., 2013, Climate Change Adaptation Actions in Bangladesh
   Shimi AC, 2010, DISASTER PREV MANAG, V19, P298, DOI 10.1108/09653561011052484
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Talukdar NR, 2021, TREES FOREST PEOPLE, V3, DOI 10.1016/j.tfp.2020.100042
   Tunde AM., 2011, ETHIOPIAN J ENV STUD, V4, P19, DOI DOI 10.4314/EJESM.V4I2.3
   Virendra Kumar Virendra Kumar, 2014, Journal of Bioremediation and Biodegradation, V5, P1000218
   Woodley E., 1991, Agriculture and Human Values, V8, P173, DOI 10.1007/BF01579672
   Ylipaa J, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11102805
   Zaki MK, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su122410373
NR 75
TC 0
Z9 0
U1 6
U2 13
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0921-030X
EI 1573-0840
J9 NAT HAZARDS
JI Nat. Hazards
PD DEC
PY 2023
VL 119
IS 3
BP 1991
EP 2009
DI 10.1007/s11069-023-06207-3
EA SEP 2023
PG 19
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA CP0P1
UT WOS:001069507500001
DA 2025-01-10
ER

PT J
AU Brown, S
   Nicholls, RJ
   Bloodworth, A
   Bragg, O
   Clauss, A
   Field, S
   Gibbons, L
   Pladaite, M
   Szuplewski, M
   Watling, J
   Shareef, A
   Khaleel, Z
AF Brown, Sally
   Nicholls, Robert J.
   Bloodworth, Alan
   Bragg, Oliver
   Clauss, Audrey
   Field, Stuart
   Gibbons, Laura
   Pladaite, Milda
   Szuplewski, Malcolm
   Watling, James
   Shareef, Ali
   Khaleel, Zammath
TI Pathways to sustain atolls under rising sea levels through land claim
   and island raising
SO ENVIRONMENTAL RESEARCH-CLIMATE
LA English
DT Article
DE sea-level rise; climate change adaptation; small islands; land claim;
   land raising
ID ARTIFICIAL REEF STRUCTURES; CLIMATE-CHANGE; ADAPTATION PATHWAYS;
   MIGRATION; RECLAMATION; RISKS; MALDIVES; RESETTLEMENT; DISPLACEMENT;
   PERCEPTIONS
AB Low-lying atoll nations (e.g. the Maldives, Kiribati, Tuvalu, Marshall Islands) are highly vulnerable to climate change, especially sea-level rise (SLR). Stringent climate change mitigation will slow but not stop SLR, which will continue for centuries, mandating additional long-term adaptation. At the same time, urbanisation is concentrating population in a few centres, especially around capital islands which creates additional pressure as most atoll nations are 'land-poor'. This paper demonstrates how structural adaptation using land claim and island raising can be utilised within an adaptation pathway approach to sustain enough islands and land area above rising sea levels to satisfy societal and economic needs over multiple centuries.This approach is illustrated using the Maldives, especially around the capital and its environs (Greater Mal & eacute;). Raising, expanding and connecting 'urban' islands can provide multiple benefits. Significant developments have already occurred in Greater Mal & eacute; and further developments there and for other urban centres in the Maldives are expected. Migration to urban centres, especially Mal & eacute;, is widespread and this adaptation approach assumes this trend continues, implying many other islands are depopulated or abandoned. Tourism is core to the Maldives economy and tourist islands require a different ambience to urban islands. They could be sustained with sympathetic soft engineering reinforcing the natural processes that produce atolls. While land advance and island raising provides a technical solution for SLR, any application must also address the additional policy, human, physical, engineering and economic/financial challenges that are raised. Nonetheless, by aligning adaptation through land advance/raising with existing development trends, atoll nations have the potential to persist and prosper for many centuries even as sea levels inevitably rise. This provides a realistic alternative to widespread assumptions about forced migration and ultimate national abandonment. The lessons here may find wider application to other small island settings and even mainland coasts.
C1 [Brown, Sally; Bragg, Oliver; Clauss, Audrey; Field, Stuart; Gibbons, Laura; Pladaite, Milda; Szuplewski, Malcolm; Watling, James] Boldrewood Innovat Campus, Fac Engn & Phys Sci, Sch Engn, Burgess Rd, Southampton SO16 7QF, England.
   [Brown, Sally; Nicholls, Robert J.] Univ East Anglia, Tyndall Ctr Climate Change Res, Norwich Res Pk, Norwich NR4 7TJ, England.
   [Bloodworth, Alan] TEDI London, Bldg 11,Quebec Way, London SE16 7LG, England.
   [Bragg, Oliver] Jacobs, 2 Colmore Sq,38 Colmore Circus Queensway, Birmingham B4 6BN, England.
   [Gibbons, Laura] JBA Consulting, 35 Perrymount Rd, Haywards Heath RH16 3XE, England.
   [Shareef, Ali; Khaleel, Zammath] Dev Advisory Serv Pvt Ltd, Male, Maldives.
C3 University of East Anglia
RP Brown, S (corresponding author), Boldrewood Innovat Campus, Fac Engn & Phys Sci, Sch Engn, Burgess Rd, Southampton SO16 7QF, England.; Brown, S (corresponding author), Univ East Anglia, Tyndall Ctr Climate Change Res, Norwich Res Pk, Norwich NR4 7TJ, England.
EM sb20@soton.ac.uk
RI Brown, Sally/I-2662-2014; Nicholls, Robert/G-3898-2010
OI Nicholls, Robert/0000-0002-9715-1109
FU European Commission [FP7-ENV-2013-two-stage-603396]; United Kingdom
   Natural Environment Research Council and United Kingdom Government
   Department of Business Energy & Industrial Strategy grant [ADJUST1.5,
   NE/P01495X/1]; School of Engineering, University of Southampton
FX S B and R J N were funded by the European Commission's Seventh Framework
   Programme's collaborative project RISES-AM- (Contract
   FP7-ENV-2013-two-stage-603396) and the United Kingdom Natural
   Environment Research Council and United Kingdom Government Department of
   Business Energy & Industrial Strategy grant 'ADJUST1.5', NE/P01495X/1. O
   B, A C, S F, L G, M P, M S and J W acknowledge funding from the School
   of Engineering, University of Southampton, where all authors (apart from
   A S and Z K) were based for the primary study. We thank La Mer and Water
   Solutions, Maldives and the Maldivian National University for
   discussions around climate change impacts and adaptation during a field
   visit in 2015. We are grateful to those who hosted and supported us
   during our visit. We thank Matthew Wadey and Derek Clark (formerly at
   the University of Southampton) for their advice during the course of
   this project and Roland Smith, Tyndall Centre for Climate Change
   Research, University of East Anglia for advice on references.
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Alsumaiei AA, 2018, HYDROL PROCESS, V32, P1137, DOI 10.1002/hyp.11480
   [Anonymous], 2001, First National Communication of the Republic of Maldives to the United Nations Framework Convention on Climate Change
   [Anonymous], 2014, Working on the Delta: The Decisions to Keep The Netherlands Safe and Liveable
   [Anonymous], 2006, Singapore Year Book of International Law and Contributors
   [Anonymous], 2001, Vijfde Nota over de Ruimtelijke Ordening 2000/2020. Deel 2, Resultaten van inspraak
   [Anonymous], 2007, Wave overtopping of sea defences and related structures: assessment manual
   Arnall A, 2015, GLOBAL ENVIRON CHANG, V31, P199, DOI 10.1016/j.gloenvcha.2015.01.011
   Aslam M, 2017, ANTHROPOCENE, V18, P57, DOI 10.1016/j.ancene.2017.05.003
   Avas, 2021, Male' city population crosses 252 Male
   Bailey RT, 2014, J HYDROL, V515, P247, DOI 10.1016/j.jhydrol.2014.04.060
   Barnett J, 2014, NAT CLIM CHANGE, V4, P1103, DOI 10.1038/NCLIMATE2383
   Barnett J, 2003, CLIMATIC CHANGE, V61, P321, DOI 10.1023/B:CLIM.0000004559.08755.88
   Barnett J, 2018, POPUL ENVIRON, V39, P339, DOI 10.1007/s11111-018-0295-5
   Barnett J, 2017, ASIA PAC VIEWP, V58, P3, DOI 10.1111/apv.12153
   Bates PD, 2010, J HYDROL, V387, P33, DOI 10.1016/j.jhydrol.2010.03.027
   Beaven R., 2017, P 16 ANN WAST MAN LA
   Becken S, 2011, ECOTOUR BK SER, P72, DOI 10.1079/9781845936792.0072
   Bendixen M, 2021, ONE EARTH, V4, P1095, DOI 10.1016/j.oneear.2021.07.008
   Bendixen M, 2019, NATURE, V571, P29, DOI 10.1038/d41586-019-02042-4
   Benedet L., 2019, Coastal Sediments 2019, DOI [10.1142/97898112044870017, DOI 10.1142/97898112044870017]
   Bettini G, 2017, GLOB POLICY, V8, P33, DOI 10.1111/1758-5899.12404
   Betzold C, 2017, REG ENVIRON CHANGE, V17, P1077, DOI 10.1007/s10113-016-1044-x
   Biermann F, 2010, GLOBAL ENVIRON POLIT, V10, P60, DOI 10.1162/glep.2010.10.1.60
   Bisaro A, 2020, CLIMATIC CHANGE, V160, P671, DOI 10.1007/s10584-019-02507-5
   Black R, 2011, NATURE, V478, P447, DOI 10.1038/478477a
   Bloemen P, 2019, POLICY SOC, V38, P58, DOI 10.1080/14494035.2018.1513731
   Lebbe TB, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.740602
   Bosomworth K, 2017, ENVIRON SCI POLICY, V76, P23, DOI 10.1016/j.envsci.2017.06.007
   Bosserelle AL, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002580
   Brown S, 2020, J FLOOD RISK MANAG, V13, DOI 10.1111/jfr3.12567
   CLARK S, 1994, B MAR SCI, V55, P724
   Clark S, 1999, AQUAT CONSERV, V9, P5, DOI 10.1002/(SICI)1099-0755(199901/02)9:1<5::AID-AQC330>3.0.CO;2-U
   Constable AL, 2017, REG ENVIRON CHANGE, V17, P1029, DOI 10.1007/s10113-016-1004-5
   Dawson RJ, 2009, CLIMATIC CHANGE, V95, P249, DOI 10.1007/s10584-008-9532-8
   DEMULDER EFJ, 1994, ENG GEOL, V37, P15, DOI 10.1016/0013-7952(94)90078-7
   Dolven B., 2015, congressional report service
   Donner SD, 2015, NAT RESOUR FORUM, V39, P191, DOI 10.1111/1477-8947.12082
   Dronkers J., 1990, Strategies for Adaption to Sea Level Rise, Report of the IPCC Coastal Zone Management Subgroup: Intergovernmental Panel on Climate Change
   Drummen I, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.615222
   Duvat VKE, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-18109-8
   Duvat VKE, 2020, ANTHROPOCENE, V32, DOI 10.1016/j.ancene.2020.100265
   Duvat VKE, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51468-3
   East HK, 2018, GEOPHYS RES LETT, V45, P11265, DOI 10.1029/2018GL079589
   Erwin R. Michael, 2007, Ecological Restoration, V25, P256, DOI 10.3368/er.25.4.256
   Facebook, 2016, Maldives Meterological Service
   Fallati L, 2017, ENVIRON MONIT ASSESS, V189, DOI 10.1007/s10661-017-6120-2
   Farbotko C, 2012, GLOBAL ENVIRON CHANG, V22, P382, DOI 10.1016/j.gloenvcha.2011.11.014
   Flemming B. W., 1994, Netherlands Journal of Aquatic Ecology, V28, P299, DOI 10.1007/BF02334198
   Flikkema MMB, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.619462
   Fox-Kemper B., 2021, Climate Change 2021: The Physical Science Basis, DOI DOI 10.1017/9781009157896.011.1212
   General Economics Division, 2018, Bangladesh Delta Plan (BDP) 2100
   Gussmann G, 2020, CLIMATIC CHANGE, V163, P931, DOI 10.1007/s10584-020-02919-8
   Haasnoot M, 2019, ENVIRON RES COMMUN, V1, DOI 10.1088/2515-7620/ab1871
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Harangozo S A., 1992, Sea Level Changes: Determination and Effects, Geophysical Monograph 69, Vvol 11, P95
   Healy MG, 2002, J COASTAL RES, P365
   Heslin A, 2019, CLIM RISK MANAGE POL, P383, DOI 10.1007/978-3-319-72026-5_16
   Higgins E, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0261964
   Hinkel J, 2018, NAT CLIM CHANGE, V8, P570, DOI 10.1038/s41558-018-0176-z
   Hoegh-Guldberg O., 2018, Global warming of 1.5C
   Hoegh-Guldberg O, 2011, REG ENVIRON CHANGE, V11, pS215, DOI 10.1007/s10113-010-0189-2
   Hulhumal Development Corporation, 2015, Hulhumal
   Ibrahim S.A., 2002, Water resources management in Maldives with an emphasis on desalination
   Jamero ML, 2017, NAT CLIM CHANGE, V7, P581, DOI [10.1038/nclimate3344, 10.1038/NCLIMATE3344]
   Jarillo S, 2022, ANTIPODE, V54, P848, DOI 10.1111/anti.12814
   Joffrion RJ, 2015, CIVIL ENG, V85, P66, DOI 10.1061/ciegag.0000966
   Jones DA, 2007, AQUAT ECOSYST HEALTH, V10, P268, DOI 10.1080/14634980701512814
   Kane HH, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001525
   Kench P S., 2012, Pitfalls of shoreline Stabilization: Selected Case Studies, DOI [10.1007/978-94-007-4123-211, DOI 10.1007/978-94-007-4123-211]
   Kench PS, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-02954-1
   Klein RJT, 2001, J COASTAL RES, V17, P531
   Kwadijk JCJ, 2010, WIRES CLIM CHANGE, V1, P729, DOI 10.1002/wcc.64
   Lee CH, 2014, OCEAN COAST MANAGE, V102, P545, DOI 10.1016/j.ocecoaman.2013.12.018
   Letman J, 2018, Rising seas give island nation a stark choice: relocate or elevate
   Li C, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aaw9490
   Lietaer S, 2021, ENVIRON SCI POLICY, V126, P11, DOI 10.1016/j.envsci.2021.09.008
   LINHAM M.M., 2010, TECHNOLOGIES CLIMATE
   Liu XJ, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11050585
   Macdonald N, 2012, PROG PHYS GEOG, V36, P125, DOI 10.1177/0309133311414607
   Magnan AK, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-14303-w
   Magnan AK, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01691-w
   Martín-Antón M, 2016, J COASTAL RES, P667, DOI 10.2112/SI75-133.1
   Masselink G, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aay3656
   Mayer B, 2017, TRANSNATL ENVIRON LA, V6, P107, DOI 10.1017/S2047102516000078
   McCabe MV, 2013, COAST ENG, V74, P33, DOI 10.1016/j.coastaleng.2012.11.010
   McLeman R, 2018, B ATOM SCI, V74, P148, DOI 10.1080/00963402.2018.1461951
   McMichael C., 2019, The Oxford Handbook of Migration Crises, P1
   Ministry of Finance & Treasury, 2018, Statistical yearbook of the Maldives 2018 population table 314 and 315
   Ministry of Housing and Environment, 2011, Survey of climate change adaptation measures in Maldives
   Ministry of Planning and National Development, 2007, Seventh National Development Plan 2006-2010 creating new opportunities Male Maldives Ministry of Planning and National Development
   Moosa L., 2021, Maldives national water accounts 2018 & 2019
   Mortreux C, 2009, GLOBAL ENVIRON CHANG, V19, P105, DOI 10.1016/j.gloenvcha.2008.09.006
   Mycoo M., 2022, Small Islands Climate Change 2022: Impacts Adaptation and Vulnerability
   Nakada S, 2012, GROUND WATER, V50, P639, DOI 10.1111/j.1745-6584.2011.00874.x
   National Geographic, 2022, Island Washington National Geographic
   Naylor AK, 2015, PROG PHYS GEOG, V39, P728, DOI 10.1177/0309133315598269
   Nicholls R J., 2015, Broad Scale Coastal Simulation: New Techniques to Understand and Manage Shorelines in the Third Millennium, DOI [10.1007/978-94-007-5258-0, DOI 10.1007/978-94-007-5258-0]
   Nicholls RJ, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P315
   Nicholls RJ, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2016.0448
   Nunn PD, 2021, OCEAN COAST MANAGE, V205, DOI 10.1016/j.ocecoaman.2021.105554
   Nunn PD, 2016, GEOSCI LETT, V3, DOI 10.1186/s40562-016-0041-8
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   Oakes R, 2019, POPUL ENVIRON, V40, P480, DOI 10.1007/s11111-019-00321-w
   Oberle FKJ, 2017, WATER-SUI, V9, DOI 10.3390/w9090650
   Oppenheimer M., 2019, The ocean and cryosphere in a changing climate
   Pernetta J C., 1989, P 1 INT M CIT WAT VE
   Perry CT, 2018, NATURE, V558, P396, DOI 10.1038/s41586-018-0194-z
   Proetzel E A., 1983, Artificial floating islands: cities of the future
   Prosser DJ, 2022, ECOL RESTOR, V40, P17, DOI 10.3368/er.40.1.17
   Prtner H.-O., 2019, IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, DOI [10.1017/9781009157964.005, DOI 10.1017/9781009157964.005, DOI 10.1017/9781009157964]
   Ranger N, 2013, EURO J DECIS PROCESS, V1, P233, DOI 10.1007/s40070-013-0014-5
   Riyaz M, 2010, J EARTHQ TSUNAMI, V4, P135, DOI 10.1142/S1793431110000704
   Rosenzweig C, 2014, GLOBAL ENVIRON CHANG, V28, P395, DOI 10.1016/j.gloenvcha.2014.05.003
   Schuhmacher H, 2005, FACIES, V51, P80, DOI 10.1007/s10347-005-0020-6
   Sengupta D, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF002927
   Sengupta D, 2020, SCI TOTAL ENVIRON, V732, DOI 10.1016/j.scitotenv.2020.139290
   Shaig A., 2008, PhD Thesis
   Shakeela A, 2015, J SUSTAIN TOUR, V23, P65, DOI 10.1080/09669582.2014.918135
   Slamet NS, 2020, OCEAN COAST MANAGE, V195, DOI 10.1016/j.ocecoaman.2020.105283
   Smith L, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-41659-3
   Sobczak-Szelc K, 2020, COMP MIGR STUD, V8, DOI 10.1186/s40878-019-0163-1
   Souravlias D, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.545637
   Sovacool BK, 2015, NAT CLIM CHANGE, V5, P616, DOI 10.1038/nclimate2665
   Sovacool BK, 2012, MITIG ADAPT STRAT GL, V17, P731, DOI 10.1007/s11027-011-9341-7
   Speelman L H, 2015, PhD Thesis
   Speelman LH, 2021, ASIAN PAC MIGR J, V30, P282, DOI 10.1177/01171968211044082
   Steibl S, 2021, ROY SOC OPEN SCI, V8, DOI 10.1098/rsos.210411
   Storlazzi CD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aap9741
   Tamis JE, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.664055
   United Nations, 2015, Paris Agree- ment, Paris
   van de Wal RSW, 2022, EARTHS FUTURE, V10, DOI 10.1029/2022EF002751
   van Ginkel KCH, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab6395
   Vinke K, 2020, MIGR STUD, V8, P626, DOI 10.1093/migration/mnaa029
   Wadey M, 2017, NAT HAZARDS, V89, P131, DOI 10.1007/s11069-017-2957-5
   Wang W, 2014, OCEAN COAST MANAGE, V102, P415, DOI 10.1016/j.ocecoaman.2014.03.009
   Watkin S., 2019, P ICE COAST MAN LOND, DOI [10.1680/cm.65147.057, DOI 10.1680/CM.65147.057]
   White G.F., 1945, Human Adjustment to Floods: A Geographical Approach to the Flood Problem in the United States, P225
   Wilmsen B, 2015, GEOFORUM, V58, P76, DOI 10.1016/j.geoforum.2014.10.016
   Wong PP, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P361
   Woodworth PL, 2005, GLOBAL PLANET CHANGE, V49, P1, DOI 10.1016/j.gloplacha.2005.04.001
   Zainal K, 2012, MAR POLLUT BULL, V64, P1452, DOI 10.1016/j.marpolbul.2012.04.004
   Zhang JJ, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9060878
NR 143
TC 6
Z9 6
U1 5
U2 5
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
EI 2752-5295
J9 ENVIRON RES-CLIM
JI Environ. Res. Clim.
PD MAR 1
PY 2023
VL 2
IS 1
AR 015005
DI 10.1088/2752-5295/acb4b3
PG 26
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA G8R1W
UT WOS:001319234800001
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Uereyen, S
   Bachofer, F
   Klein, I
   Kuenzer, C
AF Uereyen, Soner
   Bachofer, Felix
   Klein, Igor
   Kuenzer, Claudia
TI Multi-faceted analyses of seasonal trends and drivers of land surface
   variables in Indo-Gangetic river basins
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Multivariate time series analysis; Remote sensing; Climatic controls;
   Anthropogenicinfluence; Himalaya-Karakoram;
   Indus-Ganges-Brahmaputra-Meghna
ID KARAKORAM-HIMALAYA; CLIMATE-CHANGE; SNOW; DYNAMICS; WATER; ASIA;
   PATTERNS; IMPACTS; RUNOFF; CHINA
AB The Indo-Gangetic river basins feature a wide range of climatic, topographic, and land cover characteristics providing a suitable setting for the exploration of multivariate time series. Here, we collocated a comprehensive feature space for these river basins including Earth observation time series on the normalized difference vegetation index (NDVI), surface water area (SWA), and snow cover area (SCA) in combination with driving variables between December 2002 and November 2020. First, we evaluated changes using multi-faceted trend analyses. Second, we employed the causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI) to disentangle interac-tions within the feature space. PCMCI quantifies direct and indirect relationships between variables and has been rarely applied to remote sensing applications. The results showed that vegetation greening continues significantly. Irrigated croplands in the Indus basin indicated the highest trend magnitude (0.042 NDVI/decade-1). At annual and basin scale, positive trends were also identified for SWA in the Indus (837 km2/decade-1) and Ganges basin (677 km2/decade-1). Annual trends in SCA were insignificant at basin scale. Considering elevation zones, negative SCA trends were found in high altitudes of the Ganges and Brahmaputra river basins. Similarly, NDVI and SWA showed positive trends in high elevations. Furthermore, the causal analysis revealed that NDVI was controlled by water avail-ability. SWA was directly influenced by river discharge and indirectly by precipitation. In high altitudes, SWA was controlled by SCA and temperature. Precipitation and temperature were identified as important drivers of SCA with spatio-temporal variations. With amplified climate change, the joint exploitation of time series will be of increasing importance to further enhance the understanding of land surface change and complex interplays across the spheres of the Earth system. The insights of this study and used methods could greatly support the development of climate change adaptation strategies for the investigated region.
C1 [Uereyen, Soner; Bachofer, Felix; Klein, Igor; Kuenzer, Claudia] German Aerosp Ctr DLR, German Remote Sensing Data Ctr DFD, Muenchener Str 20, D-82234 Wessling, Germany.
   [Kuenzer, Claudia] Univ Wurzburg, Inst Geog & Geol, Dept Remote Sensing, Am Hubland, D-97074 Wurzburg, Germany.
C3 Helmholtz Association; German Aerospace Centre (DLR); University of
   Wurzburg
RP Uereyen, S (corresponding author), German Aerosp Ctr DLR, German Remote Sensing Data Ctr DFD, Muenchener Str 20, D-82234 Wessling, Germany.
EM soner.uereyen@dlr.de
RI Klein, Igor/KJL-2430-2024; Bachofer, Felix/AAH-1648-2020
CR Ackroyd C, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.713145
   Anderson K, 2020, GLOBAL CHANGE BIOL, V26, P1608, DOI 10.1111/gcb.14919
   Atif S, 2021, NAT HAZARDS, V108, P2357, DOI 10.1007/s11069-021-04783-w
   Azam MF, 2021, SCIENCE, V373, P869, DOI 10.1126/science.abf3668
   Barkhordarian A, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51857-8
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Bhattacharya A, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-24180-y
   Biemans H, 2019, NAT SUSTAIN, V2, P594, DOI 10.1038/s41893-019-0305-3
   Birthal PS, 2021, AGR WATER MANAGE, V255, DOI 10.1016/j.agwat.2021.106950
   Cannon F, 2016, THEOR APPL CLIMATOL, V125, P27, DOI 10.1007/s00704-015-1489-8
   Chen C, 2019, NAT SUSTAIN, V2, P122, DOI 10.1038/s41893-019-0220-7
   Coen MC, 2020, ATMOS MEAS TECH, V13, P6945, DOI 10.5194/amt-13-6945-2020
   Dangar S, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac2ceb
   Das L, 2019, EARTH-SCI REV, V198, DOI 10.1016/j.earscirev.2019.102935
   Desinayak N, 2022, ANN GEOPHYS-GERMANY, V40, P67, DOI 10.5194/angeo-40-67-2022
   Di Capua G, 2020, WEATHER CLIM DYNAM, V1, P519, DOI 10.5194/wcd-1-519-2020
   Dietz AJ, 2015, REMOTE SENS LETT, V6, P844, DOI 10.1080/2150704X.2015.1084551
   Dimri AP, 2021, SCI TOTAL ENVIRON, V788, DOI 10.1016/j.scitotenv.2021.147864
   ESA, 2017, Land Cover CCI Product User Guide Version 2.0
   European Space AgencySinergise, 2021, COP GLOB DIG EL MOD
   Farinotti D, 2020, NAT GEOSCI, V13, P8, DOI 10.1038/s41561-019-0513-5
   Gao YH, 2018, NPJ CLIM ATMOS SCI, V1, DOI 10.1038/s41612-018-0030-z
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Gouweleeuw BT, 2018, HYDROL EARTH SYST SC, V22, P2867, DOI 10.5194/hess-22-2867-2018
   GRANGER CWJ, 1969, ECONOMETRICA, V37, P424, DOI 10.2307/1912791
   Gurung DR, 2017, INT J CLIMATOL, V37, P3873, DOI 10.1002/joc.4961
   Harrigan S, 2020, EARTH SYST SCI DATA, V12, P2043, DOI 10.5194/essd-12-2043-2020
   Janes T, 2019, SCI TOTAL ENVIRON, V650, P1499, DOI 10.1016/j.scitotenv.2018.08.376
   Ji ZM, 2013, CLIM DYNAM, V41, P589, DOI 10.1007/s00382-012-1473-2
   Klein I, 2021, REMOTE SENS ENVIRON, V253, DOI 10.1016/j.rse.2020.112207
   Klein I, 2017, REMOTE SENS ENVIRON, V198, P345, DOI 10.1016/j.rse.2017.06.045
   Kolluru V, 2020, ATMOS RES, V246, DOI 10.1016/j.atmosres.2020.105121
   Konings AG, 2017, NAT GEOSCI, V10, P284, DOI [10.1038/ngeo2903, 10.1038/NGEO2903]
   Kraaijenbrink PDA, 2021, NAT CLIM CHANGE, V11, P591, DOI 10.1038/s41558-021-01074-x
   Krich C, 2020, BIOGEOSCIENCES, V17, P1033, DOI 10.5194/bg-17-1033-2020
   Kumar R, 2022, REMOTE SENS APPL, V25, DOI 10.1016/j.rsase.2022.100695
   Kvas A, 2019, J GEOPHYS RES-SOL EA, V124, P9332, DOI 10.1029/2019JB017415
   Lamchin M, 2018, SCI TOTAL ENVIRON, V618, P1089, DOI 10.1016/j.scitotenv.2017.09.145
   Lehner B., 2008, EOS T AM GEOPHYSICAL, V89, P9394, DOI [10.1029/2008EO100001, DOI 10.1029/2008EO100001]
   Li MX, 2020, INT J CLIMATOL, V40, P5744, DOI 10.1002/joc.6549
   Li XC, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9060637
   Liu YC, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-97240-4
   Lutz AF, 2022, NAT CLIM CHANGE, V12, P566, DOI 10.1038/s41558-022-01355-z
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Lutz AF, 2019, REG ENVIRON CHANGE, V19, P833, DOI 10.1007/s10113-018-1433-4
   Mahecha MD, 2020, EARTH SYST DYNAM, V11, P201, DOI 10.5194/esd-11-201-2020
   Marconcini M., 2021, GIForum, V9, P33, DOI [10.1553/giscience2021_01_s33, DOI 10.1553/GISCIENCE2021_01_S33]
   Marconcini M, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-00580-5
   Mayer-Gurr T., 2018, ITSG GRACE2018 MONTH
   Miles E, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-23073-4
   Mishra NB, 2017, SCI TOTAL ENVIRON, V587, P326, DOI 10.1016/j.scitotenv.2017.02.156
   Mishra V, 2020, NAT GEOSCI, V13, P722, DOI 10.1038/s41561-020-00650-8
   Mondal SK, 2021, SCI TOTAL ENVIRON, V789, DOI 10.1016/j.scitotenv.2021.147867
   Munoz-Sabater J., 2019, ERA5-Land Hourly Data from 1950 to Present
   Muñoz-Sabater J, 2021, EARTH SYST SCI DATA, V13, P4349, DOI 10.5194/essd-13-4349-2021
   Nepal S, 2021, SCI TOTAL ENVIRON, V795, DOI 10.1016/j.scitotenv.2021.148587
   Nie Y, 2021, NAT REV EARTH ENV, V2, P91, DOI 10.1038/s43017-020-00124-w
   Notarnicola C, 2020, REMOTE SENS ENVIRON, V243, DOI 10.1016/j.rse.2020.111781
   Palazzi E, 2017, CLIM DYNAM, V48, P3991, DOI 10.1007/s00382-016-3316-z
   Papagiannopoulou C, 2017, GEOSCI MODEL DEV, V10, P1945, DOI 10.5194/gmd-10-1945-2017
   Pekel JF, 2016, NATURE, V540, P418, DOI 10.1038/nature20584
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Pritchard HD, 2019, NATURE, V569, P649, DOI 10.1038/s41586-019-1240-1
   Priyadarshini P, 2020, LAND USE POLICY, V96, DOI 10.1016/j.landusepol.2020.104718
   Reichstein M, 2019, NATURE, V566, P195, DOI 10.1038/s41586-019-0912-1
   Rodell M, 2018, NATURE, V557, P650, DOI 10.1038/s41586-018-0123-1
   Rössler S, 2021, GEOSCIENCES, V11, DOI 10.3390/geosciences11030130
   Runge J, 2018, CHAOS, V28, DOI 10.1063/1.5025050
   Runge J, 2020, PR MACH LEARN RES, V124, P1388
   Runge J, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aau4996
   Runge J, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10105-3
   Sarmah S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa866
   Sharma C, 2021, GEOSCI FRONT, V12, DOI 10.1016/j.gsf.2021.101186
   Song XP, 2018, NATURE, V560, P639, DOI 10.1038/s41586-018-0411-9
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Teng HF, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abfeeb
   Terzago S, 2014, J HYDROMETEOROL, V15, P2293, DOI 10.1175/JHM-D-13-0196.1
   Uereyen S, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14010197
   Uereyen S, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11242951
   Uhe PF, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab10ee
   Ul Hasson S, 2017, EARTH SYST DYNAM, V8, P337, DOI 10.5194/esd-8-337-2017
   Urraca R, 2018, SOL ENERGY, V164, P339, DOI 10.1016/j.solener.2018.02.059
   Vermote E., 2015, MOD09GA MODIS TERRA, DOI [10.5067/MODIS/MOD09GA.006, DOI 10.5067/MODIS/MOD09.006, 10.5067/MODIS/MOD09.006]
   Viviroli D, 2020, NAT SUSTAIN, V3, P917, DOI 10.1038/s41893-020-0559-9
   Wang WP, 2015, J HYDROL ENG, V20, DOI 10.1061/(ASCE)HE.1943-5584.0001234
   Wang XY, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-15208-9
   Wang XLL, 2001, J CLIMATE, V14, P2204, DOI 10.1175/1520-0442(2001)014<2204:COEWHI>2.0.CO;2
   Wei ZG, 2015, ARCT ANTARCT ALP RES, V47, P611, DOI 10.1657/AAAR0014-050
   Wijngaard RR, 2018, HYDROL EARTH SYST SC, V22, P6297, DOI 10.5194/hess-22-6297-2018
   WITTICH KP, 1995, INT J BIOMETEOROL, V38, P209, DOI 10.1007/BF01245391
   Woodcock CE, 2020, REMOTE SENS ENVIRON, V238, DOI 10.1016/j.rse.2019.111558
   WorldPop CIESIN, 2018, WORLDPOP
   Wu DH, 2015, GLOBAL CHANGE BIOL, V21, P3520, DOI 10.1111/gcb.12945
   Xie XM, 2019, REMOTE SENS ENVIRON, V231, DOI 10.1016/j.rse.2019.111259
   Yang DZ, 2020, SOL ENERGY, V210, P3, DOI 10.1016/j.solener.2020.04.016
   Yuan WP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax1396
   Zhang HB, 2022, SCI TOTAL ENVIRON, V803, DOI 10.1016/j.scitotenv.2021.149889
   Zheng K, 2019, SCI TOTAL ENVIRON, V660, P236, DOI 10.1016/j.scitotenv.2019.01.022
   Zhou QM, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13010041
   Zhu Y, 2021, SCI TOTAL ENVIRON, V799, DOI 10.1016/j.scitotenv.2021.149366
NR 100
TC 8
Z9 9
U1 9
U2 41
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 15
PY 2022
VL 847
AR 157515
DI 10.1016/j.scitotenv.2022.157515
EA JUL 2022
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 6A4GZ
UT WOS:000880616400011
PM 35872191
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Setiawati, MD
   Jarzebski, MP
   Gomez-Garcia, M
   Fukushi, K
AF Setiawati, Martiwi Diah
   Jarzebski, Marcin Pawel
   Gomez-Garcia, Martin
   Fukushi, Kensuke
TI Accelerating Urban Heating Under Land-Cover and Climate Change Scenarios
   in Indonesia: Application of the Universal Thermal Climate Index
SO FRONTIERS IN BUILT ENVIRONMENT
LA English
DT Article
DE urban heating; UTCI; climate change scenario; land cover change; climate
   change adaptation; urban green
ID UTCI; STRESS; HEALTH; CHINA
AB Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981-2005) and future (2018-2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1 degrees C; however, in Surabaya, the UTCI will experience 0.84 degrees C decrease in the period 2018-2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures' planning.
C1 [Setiawati, Martiwi Diah; Fukushi, Kensuke] Univ Tokyo, Inst Future Initiat, Bunkyo Ku, Tokyo, Japan.
   [Setiawati, Martiwi Diah] Indonesian Inst Sci LIPI, Res Ctr Oceanog, Ancol Timur, Indonesia.
   [Jarzebski, Marcin Pawel] Univ Tokyo, Tokyo Coll, Bunkyo Ku, Tokyo, Japan.
   [Gomez-Garcia, Martin] Nippon Koei R&D Ctr, Climate Change & Sustainable Dev Team, Tsukuba, Ibaraki, Japan.
   [Fukushi, Kensuke] United Nations Univ, Inst Adv Study Sustainabil, Shibuya Ku, Tokyo, Japan.
C3 University of Tokyo; National Research & Innovation Agency of Indonesia
   (BRIN); Indonesian Institute of Sciences (LIPI); University of Tokyo;
   United Nations University
RP Setiawati, MD (corresponding author), Univ Tokyo, Inst Future Initiat, Bunkyo Ku, Tokyo, Japan.; Setiawati, MD (corresponding author), Indonesian Inst Sci LIPI, Res Ctr Oceanog, Ancol Timur, Indonesia.
EM martiwi1802@gmail.com
RI Setiawati, Martiwi Diah/AAY-2116-2020
OI Setiawati, Martiwi Diah/0000-0003-0465-7985
FU JSPS KAKENHI [19H01144]; JSPS Core-to-Core Program B under Asia-Africa
   Science Platforms "Center of Excellence in Health Risk Assessment for
   Adaptation to Climate Change"; Grants-in-Aid for Scientific Research
   [19H01144] Funding Source: KAKEN
FX This study was supported by JSPS KAKENHI with the grant number 19H01144
   and JSPS Core-to-Core Program B under Asia-Africa Science Platforms
   "Center of Excellence in Health Risk Assessment for Adaptation to
   Climate Change."
CR Alexander LV, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006290
   [Anonymous], 2012, UTCL UN THERM CLIM I
   Arifwidodo S., 2019, APN Sci. Bull, V9, P539, DOI [DOI 10.30852/SB.2019.539, 10.30852/sb.2019.539]
   ARTIS DA, 1982, REMOTE SENS ENVIRON, V12, P313, DOI 10.1016/0034-4257(82)90043-8
   BAPPEDA Bali, 2019, MIDT DEV PLANN BAL P
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Blazejczyk K., 2011, BIOKLIMA VER 2 6 SOF
   Blazejczyk K, 2012, INT J BIOMETEOROL, V56, P515, DOI 10.1007/s00484-011-0453-2
   Boeckmann M, 2014, BMC PUBLIC HEALTH, V14, DOI 10.1186/1471-2458-14-1112
   BPS Medan, 2018, MED FIG 2017
   Bröde P, 2013, IND HEALTH, V51, P16
   Bröde P, 2012, INT J BIOMETEOROL, V56, P481, DOI 10.1007/s00484-011-0454-1
   Data Online BMKG, 2015, IND DAIL MET DAT
   Denpasar Government, 2016, MIDT DEV PLAN DENP C
   Earth Explorer USGS, 2000, DAT DOWNL
   ECMWF, 2011, ERA INT DAIL
   Farrugia Simon, 2013, International Journal of Biodiversity Science Ecosystem Services & Management, V9, P136, DOI 10.1080/21513732.2013.782342
   Flato GM, 2011, WIRES CLIM CHANGE, V2, P783, DOI 10.1002/wcc.148
   Gallo K, 2011, J APPL METEOROL CLIM, V50, P767, DOI 10.1175/2010JAMC2460.1
   García-Herrera R, 2010, CRIT REV ENV SCI TEC, V40, P267, DOI 10.1080/10643380802238137
   GARG HP, 1983, ENERG CONVERS MANAGE, V23, P113, DOI 10.1016/0196-8904(83)90070-5
   Ge QS, 2017, THEOR APPL CLIMATOL, V128, P551, DOI 10.1007/s00704-016-1731-z
   Helen, 2020, AGRICULTURE-BASEL, V10, DOI 10.3390/agriculture10050140
   Hempel S, 2013, EARTH SYST DYNAM, V4, P219, DOI 10.5194/esd-4-219-2013
   Iamarino M, 2012, INT J CLIMATOL, V32, P1754, DOI 10.1002/joc.2390
   Jia G., 2019, CLIMATE CHANGE LAND, P131
   Jones G. W., 2010, 2010 2035 INDONESIAN
   Kjellstrom T., 2019, WORKING WARMER PLANE
   Kjellstrom T, 2009, GLOBAL HEALTH ACTION, V2, DOI [10.3402/gha.v2i0.1958, 10.3402/gha.v2i0.2047]
   Loughnan M., 2012, International Journal of Population Research, 2012, DOI [10.1155/2012/518687, DOI 10.1155/2012/518687]
   Luo M, 2018, GEOPHYS RES LETT, V45, P13060, DOI 10.1029/2018GL080306
   McGregor GR, 2012, INT J BIOMETEOROL, V56, P419, DOI 10.1007/s00484-012-0546-6
   Medan Spatial Planning Agency, 2015, DET SPAT PLANN MED C
   Milewski P, 2013, GEOGR POL, V86, P47, DOI 10.7163/GPol.2013.6
   Nassiri P, 2017, IND HEALTH, V55, P437, DOI 10.2486/indhealth.2017-0018
   Pantavou K, 2018, INT J BIOMETEOROL, V62, P1695, DOI 10.1007/s00484-018-1569-4
   Park S, 2014, LANDSCAPE URBAN PLAN, V125, P146, DOI 10.1016/j.landurbplan.2014.02.014
   Raftery AE, 2017, NAT CLIM CHANGE, V7, P637, DOI [10.1038/nclimate3352, 10.1038/NCLIMATE3352]
   Ramachandra T.V., 2013, Source: Theoretical and Empirical Researches in Urban Management, V8, P5, DOI [DOI 10.2307/24873360, 10.2307/24873360]
   Rifkin DI, 2018, SLEEP MED REV, V42, P3, DOI 10.1016/j.smrv.2018.07.007
   Russo S, 2014, J GEOPHYS RES-ATMOS, V119, P12500, DOI 10.1002/2014JD022098
   Satir O, 2016, SUSTAINABLE URBANIZATION, P205, DOI 10.5772/63051
   Sekertekin A, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12020294
   Setiawati M. D., 2021, INTEGRATED RES DISAS, P87, DOI [10.1007/978-3-030- 55563-4_6, DOI 10.1007/978-3-030-55563-4_6]
   Singh S, 2015, HEALTH PROMOT INT, V30, P239, DOI 10.1093/heapro/dat027
   Sioen GB, 2017, INT J ENV RES PUB HE, V14, DOI 10.3390/ijerph14070748
   Sobrino JA, 2008, IEEE T GEOSCI REMOTE, V46, P316, DOI 10.1109/TGRS.2007.904834
   Sulikowska A, 2020, THEOR APPL CLIMATOL, V141, P19, DOI 10.1007/s00704-020-03166-8
   Sun QH, 2019, ENVIRON INT, V128, P125, DOI 10.1016/j.envint.2019.04.025
   Surabaya Municipal Government, 2016, MIDT DEV PLANN SUR C
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Tomlinson CJ, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-42
   UN DESA, 2019, WORLD URB PROSP 2018
   USGS, 2019, LANDS 7 L7 DAT US HD
   Varquez ACG, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-66288-z
   Wagner W, 2002, J PHYS CHEM REF DATA, V31, P387, DOI 10.1063/1.1461829
   Wang YJ, 2019, ATMOS RES, V215, P116, DOI 10.1016/j.atmosres.2018.09.006
   Weedon GP, 2014, WATER RESOUR RES, V50, P7505, DOI 10.1002/2014WR015638
   Wu ZF, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13121217
   Zander KK, 2019, GLOBAL ENVIRON CHANG, V56, P18, DOI 10.1016/j.gloenvcha.2019.03.004
   Zare S, 2018, WEATHER CLIM EXTREME, V19, P49, DOI 10.1016/j.wace.2018.01.004
   Zheng GZ, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16020270
NR 62
TC 12
Z9 12
U1 3
U2 27
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2297-3362
J9 FRONT BUILT ENVIRON
JI Front. Built Environ.
PD MAY 4
PY 2021
VL 7
AR 622382
DI 10.3389/fbuil.2021.622382
PG 14
WC Construction & Building Technology; Engineering, Civil
WE Emerging Sources Citation Index (ESCI)
SC Construction & Building Technology; Engineering
GA SD6QB
UT WOS:000651498600001
OA gold
DA 2025-01-10
ER

PT J
AU Arfanuzzaman, M
   Hassan, SMT
   Abu Syed, M
AF Arfanuzzaman, Md
   Hassan, S. M. Tanvir
   Abu Syed, Md
TI Cost-benefit of promising adaptations for resilient development in
   climate hotspots: evidence from lower Teesta basin in Bangladesh
SO JOURNAL OF WATER AND CLIMATE CHANGE
LA English
DT Article
DE climate change adaptation; cost-benefit analysis; Hindu Kush Himalayan;
   lower Teesta basin; socio-economic resilience; weather extremes
AB It is very likely that climate change will increase the frequency and intensity of extreme events such as floods, flash floods, storms, heat and cold waves, riverbank erosion, and drought in the river basin of Hindu Kush Himalayan (HKH) region. This could mean detrimental impacts to the poor and marginal people in the lower Teesta basin (LTB) in Bangladesh. Though adaptation involves financial costs, the farmers' practicing adaptation in LTB experience diminished crop loss and damage. This study was aimed at assessing the promising adaptation practices, their economic return, and social welfare in the LTB through an extended cost-benefit analysis. The study suggests that among the adaptations, shallow tube-well (STW) based irrigation practice in both sandy and loamy soil has the highest marginal adaptation cost (MAC) but the lowest benefit-cost ratio (BCR). The deep tube-well (DTW) based irrigation practice generates superior benefits to the farmers compared to the STW based farming due to initial establishment by the government which is very expensive. Maize farming as an alternate and less resource consumptive cropping produces nearly five times higher economic benefits than the costs which can be acknowledged as the most profitable and resilient adaptation option in the LTB. Though MAC is relatively low for the short-duration variety (SDV) rice among the promising adaptations, its economic profitability is 62% lower than that of the maize cultivation. However, having higher BCR the maize cultivation generates US$86 higher welfare to the farmers than the SDV rice which may strengthen the farmer's preference of maize cultivation over the SDV rice. It can be stated with high confidence that strategic adaptation planning, soft credit, technological advancement, and subsidized agricultural inputs will encourage the farmers to carry out adaptation options which may reduce climate-induced loss and damages for the farmers and build socio-economic resilience in the LTB and other similar areas of South Asia.
C1 [Arfanuzzaman, Md] Food & Agr Org United Nat, Dhaka, Bangladesh.
   [Hassan, S. M. Tanvir; Abu Syed, Md] Bangladesh Ctr Adv Studies BCAS, Dhaka, Bangladesh.
C3 Food & Agriculture Organization of the United Nations (FAO)
RP Arfanuzzaman, M (corresponding author), Food & Agr Org United Nat, Dhaka, Bangladesh.
EM md.uzzaman@fao.org
RI ; Arfanuzzaman, Md./X-4721-2019; Syed, Dr. Md. Abu/E-8299-2017
OI Hassan, S. M. Tanvir/0000-0001-9340-6226; Arfanuzzaman,
   Md./0000-0003-3753-4367; Syed, Dr. Md. Abu/0000-0003-4256-6793
FU Department for International Development, UK; International Development
   Research Centre, Ottawa, Canada
FX This work was carried out by the Himalayan Adaptation, Water and
   Resilience (HI-AWARE) consortium under the Collaborative Adaptation
   Research Initiative in Africa and Asia (CARIAA). Financial assistance
   was provided by the Department for International Development, UK and the
   International Development Research Centre, Ottawa, Canada. The authors
   are also grateful to the editor of the journal and two anonymous
   reviewers for providing useful comments and suggestion to further
   improve the paper.
CR Abu Syed M, 2016, CLIMATE, V4, DOI 10.3390/cli4020021
   ADB, ADAPTING CLIMATE CHA, P40
   ADB, EC CLIM CHANG PAC, P103
   Adger W. N., 2003, Progress in Development Studies, V3, P179, DOI 10.1191/1464993403ps060oa
   Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   [Anonymous], 2005, NAT AD PROGR ACT
   Arfanuzzaman M, 2018, ENVIRON DEV SUSTAIN, V20, P963, DOI 10.1007/s10668-017-9915-y
   Arfanuzzaman M, 2016, WATER POLICY, V18, P304, DOI 10.2166/wp.2015.072
   Bajracharya S. R., STATUS GLACIERS HIND, P140
   BER (Bangladesh Economic Review), MIN FIN
   Chambwera M., PLANNING COSTING AGR, P40
   FAO, 2013, FAOSTAT COMM COUNTR
   Gain AK, 2012, WATER-SUI, V4, P345, DOI 10.3390/w4020345
   GCCASF, WORKSH SER MAINSTR C
   GoB, 2010, CLIM CHANG TRUST ACT, P12
   Hertel TW, 2014, ENERG ECON, V46, P562, DOI 10.1016/j.eneco.2014.04.014
   Hock R., 2019, IPCC SPECIAL REPORT, DOI [10.1017/9781009157964.004, DOI 10.1017/9781009157964.004]
   Huq N., CLIMATE CHANGE SUSTA, P389
   ICIMOD, 2014, HIND KUSH HIM REG
   JimenezCisneros B.E., Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
   Kirch L., WORLD RISK REPORT AN, P56
   Krishnan R., HINDU KUSH HIMALAYA
   Lim B., ADAPTATION POLICY FR, P263
   Magni CA, 2010, ENG ECON, V55, P150, DOI 10.1080/00137911003791856
   McAllister E. W., PIPELINE RULES THUMB, V8th, P673
   Noble I. R., Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
   Padgham J., AGR DEV CHANGING CLI, P198
   Palanivel T., ASIA PACIFIC HUMAN D, P264
   Rabbani G., COASTAL ZONES CLIMAT, P13
   Skoufias E., 2012, POVERTY WELFARE IMPA, P146
   Tanner T, 2014, ROUTL PERSPECT DEV, P1
   UNFCCC, 2009, C PART C PART 15 SES, P43
   UNFCCC, 2011, ASS COSTS BEN AD OPT
   Vij S, 2017, ENVIRON SCI POLICY, V78, P58, DOI 10.1016/j.envsci.2017.09.007
   Watkiss P., COSTS BEN AD RES ECO, P54
   Watkiss P., 2010, ANAL EC COSTS CLIMAT
   WB, 2008, EC AD CLIM CHANG MET, P18
   Westphal MI, 2013, EC CLIMATE CHANGE E, P216
   Wijngaard RR, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0190224
NR 39
TC 3
Z9 3
U1 2
U2 13
PU IWA PUBLISHING
PI LONDON
PA ALLIANCE HOUSE, 12 CAXTON ST, LONDON SW1H0QS, ENGLAND
SN 2040-2244
EI 2408-9354
J9 J WATER CLIM CHANGE
JI J. Water Clim. Chang.
PD FEB
PY 2021
VL 12
IS 1
BP 44
EP 59
DI 10.2166/wcc.2020.130
PG 16
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA QM7CJ
UT WOS:000621932800004
OA hybrid
DA 2025-01-10
ER

PT J
AU Ha'apio, MO
   Gonzalez, R
   Wairiu, M
AF Ha'apio, Michael Otoara
   Gonzalez, Ricardo
   Wairiu, Morgan
TI Is there any chance for the poor to cope with extreme environmental
   events? Two case studies in the Solomon Islands
SO WORLD DEVELOPMENT
LA English
DT Article
DE Climate Change Adaptation; Wantok system; Social cooperation system;
   Community resilience; Household net worth
ID CLIMATE-CHANGE; COMMUNITY RESILIENCE; VULNERABILITY; PRINCIPLES;
   DECISIONS; PROSPECTS; STRATEGY; MODEL
AB Our paper analyses the patterns and factors that explain households' responses to extreme environmental events (EEEs) in two case studies of indigenous communities in the Solomon Islands. We used the ethnographic approach to describe the case studies and carried out thematic analysis to disentangle the factors that explain such responses. The first case was that of a rural community from Ranogha Island in the Western Province that was hit by the Tsunami of April 2007; the second was of a community settled in an informal development on a flood-prone area in peri-urban Honiara that was hit by a flash flood in April 2014. Drawing from the villagers' experiences, we found that aid and support from family and community, referred to by the respondents as the "wantok" system, was key to recovering from the disasters. Many respondents identified climate change as one leading factor that explained such catastrophic events. The social cooperation system, the government's role in responding to catastrophes and household net worth were identified among the main components of household responses. These constitute an effective engine to build palliative and preventive responses against catastrophic events and climate change risks. In spite of the extreme poverty observed, and the lack of government assistance, we conclude that amenities obtained from the community (through the wantok system) and household net worth (including the availability of common pool resources) enabled them to cope with the catastrophes. These factors are critical for long-term adaptation to EEEs and climate change risks. The community responses analysed with thematic analysis showed to be consistent with the conceptualization led by a farm-household model, and the household net worth as a source of income appears to be the correct measure of wealth instead the level of income in these less monetarised communities. Learning from how these communities and households responded to such EEEs provides evidence on how other communities could successfully adapt to increasing climate change risks. (C) 2019 Elsevier Ltd. All rights reserved.
C1 [Ha'apio, Michael Otoara; Wairiu, Morgan] Univ South Pacific, Pacific Ctr Environm & Sustainable Dev PACE SD, Suva, Fiji.
   [Gonzalez, Ricardo] Univ La Frontera, Fac Agr & Forest Sci, Dept Forest Sci, Temuco, Chile.
   [Gonzalez, Ricardo] Univ La Frontera, Fac Agr & Forest Sci, Butamallin Res Ctr Global Change, Temuco, Chile.
C3 University of the South Pacific; Universidad de La Frontera; Universidad
   de La Frontera
RP Gonzalez, R (corresponding author), Univ La Frontera, Fac Agr & Forest Sci, Dept Forest Sci, Temuco, Chile.
EM mhaapio@gmail.com; ricardo.gonzalez@ufrontera.cl;
   morgan.wairiu@usp.ac.fj
OI Gonzalez Jimenez, Ricardo Esteban/0000-0001-6100-2059
FU Solomon Islands Government; University of The South Pacific
FX The authors would sincerely thank the University of The South Pacific
   and, the Solomon Islands Government for funding this study. Also many
   thanks to the research assistants, who have assisted the principal
   research personnel during the three trips to the Solomon Islands for
   data collection and, the study site village elders for their directions
   and coordination in the interview meetings.
CR Adler PaulS., 2002, ACAD MANAGE REV, V27, P17, DOI DOI 10.2307/4134367
   Aldrich D.P., 2012, Building resilience: Social capital in Post-Disaster Recovery
   Aswani S, 2002, AMBIO, V31, P272, DOI 10.1639/0044-7447(2002)031[0272:ATEOCD]2.0.CO;2
   Bateman IJ, 2011, ENVIRON RESOUR ECON, V50, P365, DOI 10.1007/s10640-011-9476-8
   Bergstrand K, 2015, SOC INDIC RES, V122, P391, DOI 10.1007/s11205-014-0698-3
   Braun V, 2021, QUAL RES PSYCHOL, V18, P328, DOI 10.1080/14780887.2020.1769238
   Brunner RonaldD., 2013, ADAPTIVE GOVERNANCE
   CHIAPPORI PA, 1988, INT ECON REV, V29, P791, DOI 10.2307/2526833
   Claessens L, 2012, AGR SYST, V111, P85, DOI 10.1016/j.agsy.2012.05.003
   Coleman P.J., 1981, GEO-MAR LETT, V1, P129, DOI DOI 10.1007/BF02463330
   Coles E., 2004, Australian Journal of Emergency Management, The, V19, P6, DOI DOI 10.3316/INFORMIT.375435145094637
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Gagahe N., 2011, SOLOMON ISLANDS HOUS
   Gottschalck A.O., 2008, Net worth and the assets of households, 2002
   Keener V.W., 2012, CLIMATE CHANGE PACIF
   Kimi D., 2012, SOLOMON ISLANDS HOUS
   Kotrlik J., 2001, Learn. Perform. J, V19, P43, DOI DOI 10.1109/LPT.2009.2020494
   Lal P. N., 2011, CLIMATE CHANGE ADAPT
   Lal P. N., 2011, MAKING INFORMED ADAP
   Leal W, 2018, MITIG ADAPT STRAT GL, V23, P579, DOI 10.1007/s11027-017-9750-3
   Lin N., 1999, Connections, V22, P28, DOI DOI 10.3217/JUCS-009-06-0501
   Liu HW, 2011, ENERG POLICY, V39, P3106, DOI 10.1016/j.enpol.2011.02.051
   Logan J.R., 2006, IMPACT KATRINA RACE
   Lopez R. E., 1986, Agricultural household models. Extensions, applications, and policy, P306
   LOPEZ RE, 1984, EUR ECON REV, V24, P61, DOI 10.1016/0014-2921(84)90013-8
   [Mach K.J. Intergovernmental Panel on Climate Change (IPCC). ( Intergovernmental Panel on Climate Change (IPCC). (], 2014, CLIMATE CHANGE 2014, P117
   Masozera M, 2007, ECOL ECON, V63, P299, DOI 10.1016/j.ecolecon.2006.06.013
   Masten AS, 2008, ECOL SOC, V13
   McAdam D, 2017, ANNU REV POLIT SCI, V20, P189, DOI 10.1146/annurev-polisci-052615-025801
   Mendelsohn R, 2006, ENVIRON DEV ECON, V11, P159, DOI 10.1017/S1355770X05002755
   Nicholson T., 2004, ANTHR ORG, P66
   Norris FH, 2008, AM J COMMUN PSYCHOL, V41, P127, DOI 10.1007/s10464-007-9156-6
   Nowak MA, 2006, SCIENCE, V314, P1560, DOI 10.1126/science.1133755
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P20
   Rosenzweig C., 2001, GLOBAL CHANGE HUMAN, V2, P90, DOI DOI 10.1023/A:1015086831467
   Seibert SE, 2001, ACAD MANAGE J, V44, P219, DOI 10.5465/3069452
   Smit B, 2003, WORKING GROUP, V8, P880
   Taylor J.E., 2003, REV ECON HOUSEHOLD, V1, P33, DOI [10.1023/A:1021847430758, DOI 10.1023/A:1021847430758]
   Twigger-Ross C., 2015, Community resilience to climate change: an evidence review
   van Klaveren C, 2008, REV ECON HOUSEHOLD, V6, P169, DOI 10.1007/s11150-007-9028-8
   Vermeulen F, 2002, J ECON SURV, V16, P533, DOI 10.1111/1467-6419.00177
   Wolff EN, 2009, J ECON INEQUAL, V7, P83, DOI 10.1007/s10888-007-9068-6
   Wolff EN, 1998, J ECON PERSPECT, V12, P131, DOI 10.1257/jep.12.3.131
NR 44
TC 11
Z9 11
U1 3
U2 33
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0305-750X
EI 1873-5991
J9 WORLD DEV
JI World Dev.
PD OCT
PY 2019
VL 122
BP 514
EP 524
DI 10.1016/j.worlddev.2019.06.023
PG 11
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA IS6ER
UT WOS:000482245600037
DA 2025-01-10
ER

PT J
AU Zhang, W
   Lei, XH
   Liu, P
   Wang, X
   Wang, H
   Song, PB
AF Zhang, Wei
   Lei, Xiaohui
   Liu, Pan
   Wang, Xu
   Wang, Hao
   Song, Peibing
TI Identifying the Relationship between Assignments of Scenario Weights and
   their Positions in the Derivation of Reservoir Operating Rules under
   Climate Change
SO WATER RESOURCES MANAGEMENT
LA English
DT Article
DE Reservoir operation; Climate change; Adaptive operating rules; GCMs
   ensemble; Scenario weights; Position and assignment
ID WATER-RESOURCES; RELIABILITY; MANAGEMENT; PERFORMANCE; GENERATION;
   ADAPTATION; IMPACTS; SYSTEM; MODEL
AB In order to mitigate the adverse impacts of climate change, adaptive operating rules (AOR) are generally derived using an ensemble of General Circulation Models (GCMs). Up to date, most of related literatures only focus on one fold of the following issues concerning the derivation of AOR using the GCMs ensemble, including: (1) consideration of different scenario weighing methods, or (2) analysis of different positions to locate scenario weights. And less concern is given to the latter compared with the former. However, few studies identify the relationship between (1) and (2) in the derivation of AOR based on the GCMs ensemble. In this study, we attempt to investigate where to use Equal and REA scenario weights in the derivation of reservoir operating rules under climate change. Equal weights (EW) and unequal weights based on the reliability ensemble average (REA) method are used in two positions: (I) the optimization objective of the reservoir operation model, which is to maximize the weighted average hydropower generation for all future scenarios; and (II) the incorporation of GCMs ensemble climate projections into the weighted climate conditions, and then it is input into the reservoir operation model with the objective of maximizing annual hydropower generation. Four AORs, including EW-AOR(I), REA-AOR(I), EW-AOR(II) and REA-AOR(II), are derived, and their optimized parameters are obtained by the simulation-based optimization (SBO) method with the Complex algorithm. The case study in the Jinxi Reservoir in China indicates that REA-AOR(I) outperforms the other three operation schemes, and EW-AOR(II) performs better than REA-AOR(II). Therefore, equal weights are preferably used to incorporate climate conditions, while unequal weights based on REA method can improve the performance of the reservoir operation model. Generally, REA-AOR(I) and EW-AOR(II) are suggested for adaptive reservoir management under climate change.
C1 [Zhang, Wei; Liu, Pan; Wang, Hao] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China.
   [Lei, Xiaohui; Wang, Xu; Wang, Hao] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.
   [Song, Peibing] Zhejiang Univ, Coll Civil Engn & Architecture, Hangzhou 310058, Zhejiang, Peoples R China.
C3 Wuhan University; China Institute of Water Resources & Hydropower
   Research; Zhejiang University
RP Lei, XH (corresponding author), China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.
EM rainfields@qq.com
RI Wang, Hao/AAU-8730-2021; lei, xiaohui/P-9669-2017; liu,
   pan/HIR-9103-2022
OI Wang, Hao/0000-0001-7594-7387
FU National Key Research and Development Project [2016YFC0402208]; National
   Natural Science Foundation of China [51709276]; National Key Technology
   RD Program [2015BAB07B03]
FX The authors would like to thank the editor and anonymous reviewers for
   their valuable suggestions, which helped to improve the quality of the
   paper. This study was supported by National Key Research and Development
   Project (2016YFC0402208), National Natural Science Foundation of China
   (Grant No.51709276) and National Key Technology R&D Program
   (2015BAB07B03).
CR Ahmadi M, 2015, WATER RESOUR MANAG, V29, P1247, DOI 10.1007/s11269-014-0871-0
   [Anonymous], 2005, WATER RESOURCES SYST
   [Anonymous], COMMON ALGORITHMS C
   Brekke LD, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR006941
   Chen J, 2017, J HYDROL, V549, P534, DOI 10.1016/j.jhydrol.2017.04.025
   Christensen NS, 2007, HYDROL EARTH SYST SC, V11, P1417, DOI 10.5194/hess-11-1417-2007
   Eum HI, 2010, WATER RESOUR MANAG, V24, P3397, DOI 10.1007/s11269-010-9612-1
   Evenson D.E., 1970, Water Resources Bulletin, V6, P725, DOI [DOI 10.1111/J.1752-1688.1970.TB01617.X, 10.1111/j.1752-1688.1970.tb01617.x]
   Feng MY, 2017, ADV WATER RESOUR, V104, P23, DOI 10.1016/j.advwatres.2017.03.003
   Giorgi F, 2002, J CLIMATE, V15, P1141, DOI 10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2
   Guo SL, 2004, HYDROLOG SCI J, V49, P959, DOI 10.1623/hysj.49.6.959.55728
   Haguma D, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000445
   HARGREAVES GH, 1982, J IRR DRAIN DIV-ASCE, V108, P225
   HASHIMOTO T, 1982, WATER RESOUR RES, V18, P14, DOI 10.1029/WR018i001p00014
   Herman JD, 2018, ENVIRON MODELL SOFTW, V99, P39, DOI 10.1016/j.envsoft.2017.09.016
   Herman JD, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000509
   Karami F, 2018, WATER RESOUR MANAG, V32, P3887, DOI 10.1007/s11269-018-2025-2
   Liu P, 2011, WATER RESOUR MANAG, V25, P3177, DOI 10.1007/s11269-011-9851-9
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Ming B, 2017, APPL ENERG, V204, P432, DOI 10.1016/j.apenergy.2017.07.046
   Mohammed R, 2017, WATER RESOUR MANAG, V31, P3557, DOI 10.1007/s11269-017-1685-7
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Nalbantis I, 1997, WATER RESOUR RES, V33, P2165, DOI 10.1029/97WR01034
   Oliveira R, 1997, WATER RESOUR RES, V33, P839, DOI 10.1029/96WR03745
   Steinschneider S, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011540
   Ward MN, 2013, CLIMATIC CHANGE, V118, P307, DOI 10.1007/s10584-012-0616-0
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Xiong LH, 1999, J HYDROL, V216, P111, DOI 10.1016/S0022-1694(98)00297-2
   Xu WZ, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000502
   Xu Y, 2010, CLIM RES, V41, P61, DOI 10.3354/cr00835
   Yang G, 2016, WATER RESOUR MANAG, V30, P1183, DOI 10.1007/s11269-015-1220-7
   Young G.K., 1967, J HYDRAULICS DIVISIO, V93, P297, DOI DOI 10.1061/JYCEAJ.0001714
   Zhang W, 2017, J HYDROL, V553, P691, DOI 10.1016/j.jhydrol.2017.08.031
   Zhang W, 2017, J HYDRO-ENVIRON RES, V16, P34, DOI 10.1016/j.jher.2017.05.003
   Zhou YL, 2013, J HYDROL, V498, P153, DOI 10.1016/j.jhydrol.2013.06.028
NR 35
TC 7
Z9 8
U1 1
U2 48
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0920-4741
EI 1573-1650
J9 WATER RESOUR MANAG
JI Water Resour. Manag.
PD JAN
PY 2019
VL 33
IS 1
BP 261
EP 279
DI 10.1007/s11269-018-2101-7
PG 19
WC Engineering, Civil; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Water Resources
GA HH0JE
UT WOS:000455401400015
DA 2025-01-10
ER

PT J
AU Scoville-Simonds, M
AF Scoville-Simonds, Morgan
TI Climate, the Earth, and God - Entangled narratives of cultural and
   climatic change in the Peruvian Andes
SO WORLD DEVELOPMENT
LA English
DT Article
DE Climate change adaptation; Narratives; Religious beliefs; Indigenous
   worldviews; Latin America; Peru
ID PERCEPTIONS; VULNERABILITY; ADAPTATION; GLACIERS; RELIGION; FARMERS;
   ANTHROPOLOGY; EPISTEMOLOGY; POWER
AB How different groups perceive climate-related problems and changes is of growing interest in research and practice, especially in relation to the adaptation of vulnerable communities to climate change. However, research on local climate perceptions to date has tended to focus on what changes are perceived, not on how those changes are interpreted in particular socio-cultural contexts and given meaning within local worldviews and systems of values and beliefs. Based on fieldwork in agro-pastoral communities in highland Cusco, Peru, this study examines climate perceptions in terms of how local community members understand and explain changing climatic conditions. Specifically, two local climate narratives are identified and found to relate to Andean re-interpretations of Catholic and Evangelical religious traditions. The Andean practice of ritual offering to the earth (pago a la tierra) is found to play a key role both in the shifting religious identifications encountered at the local level, and in giving meaning to changing climatic conditions. The article further explores how these perspectives are rooted in diverging ontological and epistemological foundations. While in the local Catholic view the earth is conceived of as a non-human sacred/social person (pachamama or Santa Tierra) with whom a relationship of reciprocity must be maintained, the local Evangelical perspective instead conceives of the earth as an object, not a subject, more closely mirroring modernist Nature/Culture dualism. More broadly, the study suggests that how people interpret changing climatic conditions cannot simply be extracted and purified from the contexts of meaning production, and proposes the concept of 'entangled narratives' as a way of accounting for the social and cultural embeddedness of climate perceptions. Fulfilling our obligation to address climate change in socially just ways will require deepening our understanding of its human dimensions, including taking seriously what these changes may mean to the impacted groups. (C) 2018 Elsevier Ltd. All rights reserved.
C1 [Scoville-Simonds, Morgan] Univ Oslo, Dept Sociol & Human Geog, Moltke Moes Vei 31, N-0851 Oslo, Norway.
C3 University of Oslo
RP Scoville-Simonds, M (corresponding author), Univ Oslo, Dept Sociol & Human Geog, Moltke Moes Vei 31, N-0851 Oslo, Norway.
EM morgans@sosgeo.uio.no
RI Scoville-Simonds, Morgan/Z-1707-2019
OI Scoville-Simonds, Morgan/0000-0001-5951-7926
FU Swiss National Science Foundation [134815, 168266]; Research Council of
   Norway [250434]
FX For encouraging and critical comments on earlier drafts of this work, I
   would like to thank Gerardo Damonte Valencia, Andrea Cabrera Roa, Marc
   Hufty, Hameedullah Jamali, Karen O'Brien, Gail Hochachka, Irmelin
   Gram-Hanssen, Milda Nordbo Rosenberg, Asnake Adane Ejigu, and two
   anonymous reviewers. The fieldwork and interviews were conducted with
   the excellent research assistance of Andrea Cabrera Roa. Without her
   early recognition of the relevance of religious affiliation to this
   study, this paper would not have been possible. The work of two field
   assistants is also graciously acknowledged. I would particularly like to
   thank the community members of Canas province involved in this study for
   sharing their time and experiences. Financial support from the Swiss
   National Science Foundation (project numbers 134815 and 168266) for the
   fieldwork, analysis and writing is greatly appreciated. Affiliation with
   the AdaptationCONNECTS project (Research Council of Norway grant number
   250434) at the Department of Sociology and Human Geography, University
   of Oslo has been crucial in supporting the final stages of this work.
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Alberti G., 1974, RECIPROCIDAD INTERCA, P13
   Alencastre Andr?s., 1953, J SOC AMERICANISTES, V42, P1
   Allen Catherine., 1997, CREATING CONTEXT AND, P73
   Allen Catherine.J., 2009, DRINK POWER SOC ANDE, P28
   Allen CatherineJ., 2002, The Hold Life Has: Coca and Cultural Identity in an Andean Community, V2nd
   ALLEN CJ, 1982, J LAT AMER LORE, V8, P179
   Allison E., 2004, The Spider and the Piglet: Proceedings of the First International Seminar on Bhutan Studies, P529
   Allison EA, 2015, WIRES CLIM CHANGE, V6, P493, DOI 10.1002/wcc.354
   [Anonymous], EA AGRARIA SIERRA PE
   [Anonymous], ESTUDIOS FILOSOFIA
   [Anonymous], END IS NEAR MINOR MA
   [Anonymous], GENDER BOUNDARIES DR
   [Anonymous], RUN VOC
   [Anonymous], ROSTRO INDIO DIOS
   [Anonymous], BELIEVERS SYMPATHIZE
   [Anonymous], B SOC SUISSE AM
   [Anonymous], MAMA COTACACHI HIST
   [Anonymous], TERRA ASI TAU RITOS
   [Anonymous], W TRIBUTARIES
   [Anonymous], LANGUAGE LNKA EUROPE
   [Anonymous], VISION VANQUISHED SP
   [Anonymous], 2002, NATIVE RELIG CULTURE
   [Anonymous], 2010, HDB RELIG AUTHORITY
   Barnes J, 2013, NAT CLIM CHANGE, V3, P541, DOI [10.1038/nclimate1775, 10.1038/NCLIMATE1775]
   Bassett TJ, 2013, GEOFORUM, V48, P42, DOI 10.1016/j.geoforum.2013.04.010
   Bastien J.W., 1992, ANDEAN COSMOLOGIES T, P137
   Bhattarai B, 2015, WORLD DEV, V70, P122, DOI 10.1016/j.worlddev.2015.01.003
   Bird-David N, 1999, CURR ANTHROPOL, V40, pS67, DOI 10.1086/200061
   Boillat S, 2013, ECOL SOC, V18, DOI 10.5751/ES-05894-180421
   Bolin I., 1998, RITUALS RESPECT SECR
   Bolin Inge., 2009, ANTHR CLIMATE CHANGE, P228
   Brandon P, 2016, PHENOMENOL COGN SCI, V15, P67, DOI 10.1007/s11097-014-9369-8
   Brekhus W, 1998, SOCIOL THEOR, V16, P34, DOI 10.1111/0735-2751.00041
   Brown P, 2017, ENERGY RES SOC SCI, V31, P215, DOI 10.1016/j.erss.2017.06.006
   Bury JT, 2011, CLIMATIC CHANGE, V105, P179, DOI 10.1007/s10584-010-9870-1
   Cadena Marisol de la., 2015, Earth Beings: Ecologies of Practice across Andean Worlds
   Canessa A, 2000, J ROY ANTHROPOL INST, V6, P705, DOI 10.1111/1467-9655.00041
   Carey M., 2010, SHADOW MELTING GLACI, P165
   Crate S.A., 2009, Anthropology and climate change: from encounters to actions
   Crate SA, 2011, ANNU REV ANTHROPOL, V40, P175, DOI 10.1146/annurev.anthro.012809.104925
   CRONON W, 1992, J AM HIST, V78, P1347, DOI 10.2307/2079346
   Cruikshank J, 2001, ARCTIC, V54, P377, DOI 10.14430/arctic795
   Esquivel JC, 2017, INT J LAT AM RELIG, V1, P5, DOI 10.1007/s41603-017-0007-4
   De Castro EV, 1998, J ROY ANTHROPOL INST, V4, P469, DOI 10.2307/3034157
   Descola P., 2015, Par-dela nature et culture
   Descola P., 1996, NATURE SOC, P82
   Descola P., 1993, LANCES CREPUSCULE RE
   Dove MR, 1997, HUM ORGAN, V56, P91, DOI 10.17730/humo.56.1.l784408q35174516
   Eriksen S., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P495, DOI [10.1007/s11027-006-3460-6, DOI 10.1007/S11027-006-3460-6]
   Flores JorgeOchoa., 1974, Journal de la Societe des Americanistes, V63, P245
   Flottum K, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.429
   GADE DW, 1983, ANTHROPOS, V78, P770
   Gergan MD, 2017, ANN AM ASSOC GEOGR, V107, P490, DOI 10.1080/24694452.2016.1209103
   Gram-Hanssen I, 2018, POLAR GEOGR, V41, P1, DOI 10.1080/1088937X.2017.1414083
   Gurgiser W, 2016, EARTH SYST DYNAM, V7, P499, DOI 10.5194/esd-7-499-2016
   HARDY F, 1975, RELIG STUD, V11, P257, DOI 10.1017/S0034412500008386
   Harvey G., 2005, ANIMISM RESPECTING L
   Huargaya Quispe Sandra Imelda, 2014, Comuni@cción, V5, P35
   *INEI, 2008, CENS NAC 2007 11 POB
   Ingram M., 2015, Journal of Environmental Policy and Planning
   Jennings Justin., 2009, Drink, Power, and Society in the Andes, P1
   Jurt C, 2015, CLIMATIC CHANGE, V133, P511, DOI 10.1007/s10584-015-1529-5
   Kaijser Anna., 2013, Interpretive Approaches to Global Climate Governance:(De) constructing the Greenhouse, P183
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Luna F., 2018, Encyclopedia of the Anthropocene, P127, DOI [DOI 10.1016/B978-0-12-809665-9.10478-1, 10.4324/9781315640051-26]
   Luseno WK, 2003, WORLD DEV, V31, P1477, DOI 10.1016/S0305-750X(03)00113-X
   MACCORMACK S, 1988, AM HIST REV, V93, P960, DOI 10.2307/1863531
   MAGNY Caroline., 2009, Anthropology of food
   MARISCOTTI A. M., 1978, PACHAMAMA SANTA TIER
   MARISCOTTI AM, 1966, Z ETHNOL, V91, P68
   Martin David., 1993, TONGUES FIRE EXPLOSI
   Mayer E., 2002, ARTICULATED PEASANT
   Mulenga BP, 2017, ENVIRON MANAGE, V59, P291, DOI 10.1007/s00267-016-0780-5
   Murphy C, 2016, CLIMATIC CHANGE, V134, P101, DOI 10.1007/s10584-015-1498-8
   Naveh Danny., 2013, The Handbook of Contemporary Animism, P27
   O'Brien K., 2010, J INTEGRAL THEORY PR, V5, P89, DOI DOI 10.5751/ES-07943-200416
   O'Brien K, 2007, CLIM POLICY, V7, P73, DOI 10.1080/14693062.2007.9685639
   O'Brien KL, 2010, WIRES CLIM CHANGE, V1, P232, DOI 10.1002/wcc.30
   O'Brien KL, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P164
   Ochoa J.Flores., 1977, Pastores de puna uywamichiq punarunakuna
   Olson E, 2006, ENVIRON PLANN A, V38, P885, DOI 10.1068/a37217
   Orlove BS, 2000, NATURE, V403, P68, DOI 10.1038/47456
   Paerregaard K, 2013, RELIGIONS, V4, P290, DOI 10.3390/rel4020290
   Paschen JA, 2014, RES POLICY, V43, P1083, DOI 10.1016/j.respol.2013.12.006
   Piquet C., 2015, Le Figaro
   Pyhälä A, 2016, ECOL SOC, V21, DOI 10.5751/ES-08482-210325
   REICHELDOLMATOFF G, 1976, MAN, V11, P307, DOI 10.2307/2800273
   Reyes-García V, 2016, WIRES CLIM CHANGE, V7, P109, DOI 10.1002/wcc.374
   Ribot J, 2010, NEW FRONT SOC POLICY, P47
   Riviere G., 2002, Entre Ciel et Terre: Climat et Societes, P357
   Roncoli Carla., 2009, Anthropology and Climate Change: From Encounters to Actions, P87
   Rosengren D, 2018, ETHNOS, V83, P607, DOI 10.1080/00141844.2016.1213760
   Saldana J, 2016, The Coding Manual for Qualitative Researchers
   Salmón E, 2000, ECOL APPL, V10, P1327, DOI 10.1890/1051-0761(2000)010[1327:KEIPOT]2.0.CO;2
   Santos-Granero Fernando., 2009, The Occult Life of Things: Native Amazonian Theories of Materiality and Personhood, P1
   Shah SH, 2017, WORLD DEV, V98, P400, DOI 10.1016/j.worlddev.2017.05.004
   Spector-Mersel G, 2014, NARRAT WORKS, V4, P1
   Spector-Mersel G, 2010, NARRAT INQ, V20, P204, DOI 10.1075/ni.20.1.10spe
   Steele PR., 2004, Handbook of Inca Mythology
   URTON G, 1981, P AM PHILOS SOC, V125, P110
   Veland S, 2018, CURR OPIN ENV SUST, V31, P41, DOI 10.1016/j.cosust.2017.12.005
   Vuille M, 2008, EARTH-SCI REV, V89, P79, DOI 10.1016/j.earscirev.2008.04.002
   Watson EE, 2012, J STUD RELIG NAT CUL, V6, P319, DOI 10.1558/jsrnc.v6i3.319
   WHITE L, 1967, SCIENCE, V155, P1203, DOI 10.1126/science.155.3767.1203
   Wiid N, 2012, S AFR GEOGR J, V94, P152, DOI 10.1080/03736245.2012.742783
NR 106
TC 38
Z9 41
U1 4
U2 45
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0305-750X
EI 1873-5991
J9 WORLD DEV
JI World Dev.
PD OCT
PY 2018
VL 110
BP 345
EP 359
DI 10.1016/j.worlddev.2018.06.012
PG 15
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA GO6BJ
UT WOS:000440118800025
OA Green Accepted
DA 2025-01-10
ER

PT C
AU Amaratunga, D
   Liyanage, C
   Haigh, R
AF Amaratunga, Dilanthi
   Liyanage, Champika
   Haigh, Richard
BE Amaratunga, D
   Haigh, R
TI A Study into the Role of International Collaborations in Higher
   Education to Enhance Research Capacity for Disaster Resilience
SO 7TH INTERNATIONAL CONFERENCE ON BUILDING RESILIENCE: USING SCIENTIFIC
   KNOWLEDGE TO INFORM POLICY AND PRACTICE IN DISASTER RISK REDUCTION
SE Procedia Engineering
LA English
DT Proceedings Paper
CT 7th International Conference on Building Resilience (ICBR) - Using
   Scientific Knowledge to Inform Policy and Practice in Disaster Risk
   Reduction
CY NOV 27-29, 2017
CL Bangkok, THAILAND
SP Univ Huddersfield, Global Disaster Resilience Ctr, Naresuan Univ, Chiang Mai Univ, Asian Disaster Preparedness Ctr
DE Barriers; Disaster Resilience (DR); Higher Education Institutions
   (HEIs); International Collaboration; Research and Innovation (R&I)
AB International collaborations in the context of Disaster Resilience (DR) is pivotal due to several reasons. It helps to propose ways to create more coherent international approaches on disaster risk reduction, climate change adaptation and resilience strengthening; it helps to enhance risk management capabilities by bridging the gap between science and legal/policy issues; it helps to address the issue of efficient management of trans-boundary crises. The need to optimise international cooperation in relation to resourcing research, capacity building to undertake research and facilitating its uptake is mentioned throughout the Sendai Framework for disaster risk reduction 2015-2030 (SFDRR). Given their different capacities, as well as the linkage between the level of support provided to them and the extent to which they will be able to implement the SFDRR, developing countries require an enhanced provision of means of implementation, including adequate, sustainable and timely resources, through international cooperation and global partnerships for development, and continued international support, so as to strengthen their efforts to reduce disaster risk. The purpose of this paper is to examine the level of engagement of Higher Education Institutions (HEIs) in developing countries in Asia in international collaborations to improve their Research and Innovation (R&I) capacities in DR. Based on a project entitled ASCENT (Advancing Skills Creation and Enhancement), the findings of the paper focuses on three Asian countries, i.e. Bangladesh, Sri Lanka and Thailand. Other than an extant literature review, the paper findings are drawn from a questionnaire survey carried out in eight HEIs from the said countries. There are already several regional initiatives that promote collaboration among HEIs towards building resilience. These networks should be supported and encouraged to grow. These global networks should collaborate with existing bodies to ensure that the role of higher education is understood and can be made use of. Findings of this paper supports the need for an enhanced international partnership to improve the science-policy interface in DR and to achieve the objectives of the SFDRR. (C) 2018 The Authors. Published by Elsevier Ltd.
C1 [Amaratunga, Dilanthi; Haigh, Richard] Univ Huddersfield, Global Disaster Resilence Ctr, Huddersfield, W Yorkshire, England.
   [Liyanage, Champika] Univ Cent Lancashire, Preston, Lancs, England.
C3 University of Huddersfield; University of Central Lancashire
RP Amaratunga, D (corresponding author), Univ Huddersfield, Global Disaster Resilence Ctr, Huddersfield, W Yorkshire, England.
EM D.Amaratunga@hud.ac.uk
RI Haigh, Richard/H-7455-2016
OI Haigh, Richard/0000-0001-7347-7043; Amaratunga,
   Dilanthi/0000-0002-1682-5301; Pouri, Rahim/0000-0002-4016-6828;
   Liyanage, Champika/0000-0001-6687-3611
FU ASCENT project - Erasmus+ Programme of the European Union
FX This research was supported by ASCENT project co-funded by the Erasmus+
   Programme of the European Union. The European Commission support for the
   production of this publication does not constitute an endorsement of the
   contents, which reflects the views only of the authors, and the
   Commission cannot be held responsible for any use, which may be made of
   the information contained therein.
CR Aitsi-Selmi A, 2016, INT J DISAST RISK SC, V7, P1, DOI 10.1007/s13753-016-0081-x
   Amaratunga D., 2017, PROJECT REPORT
   Amaratunga D., 2017, Mainstreaming disaster resilience in the construction process: professional education for a disaster resilient built environment: a report of the CADRE project: collaborative Action towards Disaster Resilience Education
   [Anonymous], 2015, MIGHTY WEB RES COLLA
   [Anonymous], INTERIM EVALUATION 7
   [Anonymous], 1997, INT HIGHER ED ASIA P
   Beaver D. deB., 1978, Scientometrics, V1, P65, DOI 10.1007/BF02016840
   Carr PL, 2009, ACAD MED, V84, P1447, DOI 10.1097/ACM.0b013e3181b6ac27
   Dell Sharon, 2014, U WORLD NEWS    0207
   FRAME JD, 1979, SOC STUD SCI, V9, P481
   Fu HZ, 2018, J NUCL SCI TECHNOL, V55, P29, DOI 10.1080/00223131.2017.1383209
   Haigh R., 2015, RES REPORT
   Interim evaluation of the Seventh Framework Programme, 2010, INTERIM EVALUATION 7
   Katz JS, 1997, RES POLICY, V26, P1, DOI 10.1016/S0048-7333(96)00917-1
   Leydesdorff L, 2008, J INFORMETR, V2, P317, DOI 10.1016/j.joi.2008.07.003
   LUUKKONEN T, 1992, SCI TECHNOL HUM VAL, V17, P101, DOI 10.1177/016224399201700106
   Niinimäki T, 2009, INT CONF GLOBAL SOFT, P153, DOI 10.1109/ICGSE.2009.23
   Noll J., 2011, ACM INROADS, V1, P66, DOI [10.1145/1835428.1835445, DOI 10.1145/1835428.1835445]
   Oxley M., 2015, WORKING PAPER
   Tan Georgette, 2016, WHY WOMEN HOLD KEY S
   UNISDR, 2015, SENDAI FRAMEWORK DIS
   Wagner CS, 2008, NEW INVISIBLE COLLEGE: SCIENCE FOR DEVELOPMENT, P1
   Yang R., 2002, INTERCULTURAL ED, V13, P81
NR 23
TC 4
Z9 5
U1 0
U2 1
PU ELSEVIER
PI AMSTERDAM
PA Radarweg 29, PO Box 211, AMSTERDAM, NETHERLANDS
SN 1877-7058
J9 PROCEDIA ENGINEER
PY 2018
VL 212
BP 1233
EP 1240
DI 10.1016/j.proeng.2018.01.159
PG 8
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Engineering, Civil; Environmental Sciences; Environmental Studies;
   Public, Environmental & Occupational Health; Management
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology; Public, Environmental & Occupational Health; Business &
   Economics
GA BP4GZ
UT WOS:000552392300158
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Flückiger, S
   Brönnimann, S
   Holzkämper, A
   Führer, J
   Krämer, D
   Pfister, C
   Rohr, C
AF Fluckiger, Simon
   Bronnimann, Stefan
   Holzkamper, Annelie
   Fuhrer, Jurg
   Kramer, Daniel
   Pfister, Christian
   Rohr, Christian
TI Simulating crop yield losses in Switzerland for historical and present
   Tambora climate scenarios
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE Tambora; weather reconstruction; crop model; year without a summer
ID SUMMER; IMPACT; MODEL
AB Severe climatic anomalies in summer 1816, partly due to the eruption of Tambora in April 1815, contributed to delayed growth and poor harvests of important crops in Central Europe. Coinciding with adverse socio-economic conditions, this event triggered the last subsistence crisis in the western World. Here, we model reductions in potential crop yields for 1816 and 1817 and address the question, what impact a similar climatic anomaly would have today. We reconstructed daily weather for Switzerland for 1816/17 on a 2 km grid using historical observations and an analogue resampling method. These data were used to simulate potential crop yields for potato, grain maize, and winter barley using the CropSyst model calibrated for current crop cultivars. We also simulated yields for the same weather anomalies, but referenced to a present-day baseline temperature. Results show that reduced temperature delayed growth and harvest considerably, and in combination with reduced solar irradiance led to a substantial reduction (20%-50%) in the potential yield of potato in 1816. Effects on winter barley were smaller. Significant reductions were also modelled for 1817 and were mainly due to a cold late spring. Relative reductions for the present-day scenario for the two crops were almost indistinguishable from the historical ones. An even stronger response was found for maize, which was not yet common in 1816/17. Waterlogging, which we assessed using a stress-day approach, likely added to the simulated reductions. The documented, strong east-west gradient in malnutrition across Switzerland in 1817/18 could not be explained by biophysical yield limitations (though excess-water limitation might have contributed), but rather by economic, political and social factors. This highlights the importance of these factors for a societies' ability to cope with extreme climate events. While the adaptive capacity of today's society in Switzerland is much greater than in the early 19th century, our results emphasize the need for interdisciplinary approaches to climate change adaptation considering not only biophysical, but also social, economic and political aspects.
C1 [Fluckiger, Simon; Bronnimann, Stefan] Univ Bern, Inst Geog, Bern, Switzerland.
   [Fluckiger, Simon; Bronnimann, Stefan; Holzkamper, Annelie; Fuhrer, Jurg; Kramer, Daniel; Pfister, Christian; Rohr, Christian] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
   [Holzkamper, Annelie; Fuhrer, Jurg] Agroscope, Zurich, Switzerland.
   [Kramer, Daniel; Pfister, Christian; Rohr, Christian] Univ Bern, Inst Hist, Bern, Switzerland.
C3 University of Bern; University of Bern; Swiss Federal Research Station
   Agroscope; University of Bern
RP Brönnimann, S (corresponding author), Univ Bern, Inst Geog, Bern, Switzerland.; Brönnimann, S (corresponding author), Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
EM stefan.broennimann@giub.unibe.ch
RI Brönnimann, Stefan/A-5737-2008
OI Holzkamper, Annelie/0000-0002-1951-1041; Bronnimann,
   Stefan/0000-0001-9502-7991; Kramer, Daniel/0000-0002-4839-0090
FU Swiss National Science Foundation; Oeschger Centre for Climate Change
   Research of the University of Bern; PAGES working group VICS (Volcanic
   Impacts on Climate and Society)
FX This work was supported by the Swiss National Science Foundation
   (projects CHIMES and EXTRA-LARGE). We acknowledge the support by Martin
   Grosjean and the Oeschger Centre for Climate Change Research of the
   University of Bern and the PAGES working group VICS (Volcanic Impacts on
   Climate and Society).
CR [Anonymous], LAST GREAT SUBSISTEN
   [Anonymous], LUFTTEMPERATUR S
   Auchmann R, 2012, CLIM PAST DISCUSS, V7, P3745
   Auchmann R, 2013, J GEOPHYS RES-ATMOS, V118, P9064, DOI 10.1002/jgrd.50759
   Bider M, 1959, ARCH MET BIOKLIM B, VB9, P360
   Brázdil R, 2016, CLIM PAST, V12, P1361, DOI 10.5194/cp-12-1361-2016
   Bronnimann S., 2016, GEOGRAPHICA BERNEN G
   Brugnara Y, 2015, CLIM PAST, V11, P1027, DOI 10.5194/cp-11-1027-2015
   Evans R O, 1984, 842567 ASAE
   Frei C, 2014, INT J CLIMATOL, V34, P1585, DOI 10.1002/joc.3786
   HARDJOAMIDJOJO S, 1982, T ASAE, V25, P922
   Klein T, 2012, AGR SYST, V111, P23, DOI 10.1016/j.agsy.2012.05.001
   Kramer Daniel., 2015, Menschen grasten nun mit dem Vieh": die letzte groSSe Hungerkrise der Schweiz 1816/17: mit einer theoretischen und methodischen Einfuhrung in die historische Hungerforschung
   Luterbacher J, 2015, NAT GEOSCI, V8, P246, DOI 10.1038/ngeo2404
   MeteoSwiss, 2013, DOC MET GRID DAT PRO
   Oppenheimer C, 2003, PROG PHYS GEOG, V27, P230, DOI 10.1191/0309133303pp379ra
   Pfister C, 2015, MODULE SWITZERLAND
   Puma MJ, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/2/024007
   Raible CC, 2016, WIRES CLIM CHANGE, V7, P569, DOI 10.1002/wcc.407
   RAVELO CJ, 1982, T ASAE, V25, P623, DOI 10.13031/2013.33585
   Stöckle CO, 2003, EUR J AGRON, V18, P289, DOI 10.1016/S1161-0301(02)00109-0
   Veale L, 2016, GEOGR J, V182, P318, DOI 10.1111/geoj.12191
   Winkler P, 2009, THEOR APPL CLIMATOL, V98, P259, DOI 10.1007/s00704-009-0108-y
NR 23
TC 17
Z9 17
U1 4
U2 28
PU IOP PUBLISHING LTD
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 1748-9326
J9 ENVIRON RES LETT
JI Environ. Res. Lett.
PD JUL
PY 2017
VL 12
IS 7
AR 074026
DI 10.1088/1748-9326/aa7246
PG 10
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA FB3CK
UT WOS:000406020000002
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Panda, A
AF Panda, Architesh
TI Exploring climate change perceptions, rainfall trends and perceived
   barriers to adaptation in a drought affected region in India
SO NATURAL HAZARDS
LA English
DT Article
DE Climate change; Drought; Perception; Adaptation; India
ID FARMERS PERCEPTIONS; ADAPTIVE CAPACITY; STRATEGIES; RIVER
AB Climate change poses major challenges to agricultural systems in drought prone regions of the world especially in the areas with high poverty, lack of irrigation facilities and low productivity. Towards this it is essential to understand the climate change perceptions, adaptation practices and barriers to effective adaptation at household and community level. This paper using household surveys and focus group discussions in one of the drought prone areas of Odisha in India, explores various aspects of perception on climate change and barriers to adaptation. It also analyses the accuracy of perceptions based on rainfall data from nearest meteorological stations. The study reinforces the argument by earlier studies that the perception by people simply cannot be wrong because they may have a just a low correlation with underlying meteorological data. Results suggest that farmers increasingly perceive the changes in the rainfall and temperature patterns. However, when compared with the trend in actual rainfall data, perceptions on rainfall are found to more closely align with the results from the nearest station as compared to the station farther from it. Analysis revealed that seasonal rainfall variability has a profound influence on the farmers' perceptions on climate change and drought in the study region. Farmers' are still dependent on the traditional forecasting system because of the lack of access to modern climate forecasting and tailored information for agricultural practice. Although farmers in the study region are already adapting to the changing climate, the study finds that while lack of access to water and irrigation, information on climate change adaptation and early warning systems are major barriers to adaptation at the household level lack of government intervention, lack of knowledge on drought resistant crops and varieties and lack of renovation of water bodies and irrigation were mentioned as the major barriers at the community level. Findings from the paper argue for better adaptation planning at the local level incorporating local level perceptions and barriers to adaptation. In such areas local level planning can be crucial in enhancing the adaptive capacity of the farmers.
C1 [Panda, Architesh] IRRI, Climate Change Unit, Los Banos, Philippines.
C3 CGIAR; International Rice Research Institute (IRRI)
RP Panda, A (corresponding author), IRRI, Climate Change Unit, Los Banos, Philippines.
EM architesh@gmail.com
RI Panda, Architesh/D-3959-2014
OI Panda, Architesh/0000-0002-1083-5314
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Agarwal PK, 2009, GLOBAL CLIMATE CHANG, P148
   [Anonymous], 2009, INT FOOD POLICY RES
   [Anonymous], 2014, EC SURV IND 2013 201
   [Anonymous], 2007, WORLD BANK POLICY RE
   [Anonymous], 2010, CLIM CHANG IND 4X4 A
   [Anonymous], WORLD AGR 2030 2050
   [Anonymous], POOR AR CIV SOC DROU
   [Anonymous], 2014, OD EC SURV 2013 2014
   Ashrit RG, 2001, GEOPHYS RES LETT, V28, P1727, DOI 10.1029/2000GL012489
   Banerjee RR, 2015, NAT HAZARDS, V75, P2829, DOI 10.1007/s11069-014-1466-z
   Basannagari B, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0077976
   Basistha A, 2009, INT J CLIMATOL, V29, P555, DOI 10.1002/joc.1706
   Below TB, 2012, GLOBAL ENVIRON CHANG, V22, P223, DOI 10.1016/j.gloenvcha.2011.11.012
   Brooks N., 2005, ADAPTATION POLICY FR, P165
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Bryant CR, 2000, CLIMATIC CHANGE, V45, P181, DOI 10.1023/A:1005653320241
   Chung CE, 2006, J CLIMATE, V19, P2036, DOI 10.1175/JCLI3820.1
   Dash SK, 2007, CLIMATIC CHANGE, V85, P299, DOI 10.1007/s10584-007-9305-9
   Dash SK, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2008JD010572
   Deressa TT, 2011, J AGR SCI-CAMBRIDGE, V149, P23, DOI 10.1017/S0021859610000687
   Economic Survey of Odisha, 2010, EC SURV OD 2010 1011
   Ghosh S, 2006, CURR SCI INDIA, V90, P396
   Ghosh S, 2007, WATER RESOUR RES, V43, DOI 10.1029/2006WR005351
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Grothmann T, 2006, NAT HAZARDS, V38, P101, DOI 10.1007/s11069-005-8604-6
   Hassan R, 2008, AFR J AGRIC RESOUR E, V2, P83
   Dang HL, 2014, MITIG ADAPT STRAT GL, V19, P531, DOI 10.1007/s11027-012-9447-6
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Jones L, 2011, GLOBAL ENVIRON CHANG, V21, P1262, DOI 10.1016/j.gloenvcha.2011.06.002
   Kumar KK, 2006, SCIENCE, V314, P115, DOI 10.1126/science.1131152
   Li CY, 2013, ENVIRON MANAGE, V52, P894, DOI 10.1007/s00267-013-0139-0
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Longobardi A, 2010, INT J CLIMATOL, V30, P1538, DOI 10.1002/joc.2001
   Manandhar S, 2011, REG ENVIRON CHANGE, V11, P335, DOI 10.1007/s10113-010-0137-1
   Mertz O, 2009, ENVIRON MANAGE, V43, P804, DOI 10.1007/s00267-008-9197-0
   Meze-Hausken E, 2004, CLIM RES, V27, P19, DOI 10.3354/cr027019
   Mohapatra M, 2006, J EARTH SYST SCI, V115, P203, DOI 10.1007/BF02702034
   NATCOM, 2012, IND 2 INT COMM UNFCC
   NATCOM, 2004, IND 1 IN COMM UNFCC
   Nielsen JO, 2010, GLOBAL ENVIRON CHANG, V20, P142, DOI 10.1016/j.gloenvcha.2009.10.002
   Orlove BS, 2002, AM SCI, V90, P428, DOI 10.1511/2002.33.791
   Panda A, 2013, GLOBAL ENVIRON CHANG, V23, P782, DOI 10.1016/j.gloenvcha.2013.03.002
   Patra JP, 2012, CLIMATIC CHANGE, V111, P801, DOI [10.1007/s10584-011-0215-5, 10.1007/S10584-011-0215-5]
   Ramanathan V, 2005, P NATL ACAD SCI USA, V102, P5326, DOI 10.1073/pnas.0500656102
   Ramesh KV, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL031613
   Ray DK, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms6989
   Roncoli C, 2006, CLIM RES, V33, P81, DOI 10.3354/cr033081
   Simelton E, 2013, CLIM DEV, V5, P123, DOI 10.1080/17565529.2012.751893
   Tambo JA, 2013, REG ENVIRON CHANGE, V13, P375, DOI 10.1007/s10113-012-0351-0
   Tanner T. M., 2007, RES REPORT
   TAYLOR CH, 1989, WATER RESOUR BULL, V25, P715
   Vedwan N, 2001, CLIM RES, V19, P109, DOI 10.3354/cr019109
   Vincent K, 2007, GLOBAL ENVIRON CHANG, V17, P12, DOI 10.1016/j.gloenvcha.2006.11.009
   vonStorch H, 1995, ANALYSIS OF CLIMATE VARIABILITY, P11
   West CT, 2008, LAND DEGRAD DEV, V19, P289, DOI 10.1002/ldr.842
   Wilhite D. A., 1985, Water International, V10, P111, DOI 10.1080/02508068508686328
   World Bank, 2008, 43946 WORLD BANK
   World Bank, 2012, WORLD POP DAT SHEET
   Xiong LH, 2004, HYDROLOG SCI J, V49, P99, DOI 10.1623/hysj.49.1.99.53998
   YU YS, 1993, J HYDROL, V150, P61, DOI 10.1016/0022-1694(93)90156-4
   Ziervogel G, 2010, CLIMATIC CHANGE, V103, P537, DOI 10.1007/s10584-009-9771-3
NR 62
TC 36
Z9 36
U1 2
U2 69
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0921-030X
EI 1573-0840
J9 NAT HAZARDS
JI Nat. Hazards
PD NOV
PY 2016
VL 84
IS 2
BP 777
EP 796
DI 10.1007/s11069-016-2456-0
PG 20
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA DZ9ZF
UT WOS:000386241300003
DA 2025-01-10
ER

PT J
AU Houghton, A
AF Houghton, Adele
TI HEALTH IMPACT ASSESSMENTS A Tool for Designing Climate Change Resilience
   into Green Building and Planning Projects
SO JOURNAL OF GREEN BUILDING
LA English
DT Article
DE climate change; public health; vulnerability; adaptation; resilience;
   health impact assessment; evidence-based; adaptive reuse; policy;
   natural disasters; heat; flooding; sustainability; LEED; greenhouse gas
   emissions
ID UNITED-STATES
AB Historical records have documented considerable changes to the global climate, with significant health, economic, and environmental consequences. Climate projections predict more intense hurricanes; increased sea level rise; and more frequent and more intense natural disasters such as heat waves, heavy rainfall, and drought in the future (1; 2). The coast along the Gulf of Mexico is particularly vulnerable to many of these environmental hazards and at particular risk when several strike simultaneously-such as a hurricane disrupting electricity transmission during a heat wave.
   Due to its significant contribution to global greenhouse gas (GHG) emissions, the building sector already plays an important role in climate change mitigation efforts (e. g., reducing emissions). For example, voluntary programs such as the LEED (Leadership in Energy and Environmental Design) Rating System (3), the Architecture 2030 Challenge (4), the American College and University Presidents' Climate Commitment (5), and the Clinton Climate Initiative (6) focus almost exclusively on reducing energy consumption and increasing renewable energy generation. Mandatory regulations such as the International Energy Conservation Code (7), the International Green Building Code (8), and CalGreen (9) also emphasize GHG emission reduction targets.
   This leadership role is necessary. After all, the United States EPA estimates that the building sector accounts for 62.7% of total annual GHG emissions in the U. S., when the construction sector, facility operations, and transportation are factored in. In fact, the construction sector alone is the third largest industrial emitter of GHGs after the oil and gas and chemical industries, contributing 1.7% of total annual emissions (10; 11).
   As significant as these contributions appear, the built environment's true contribution to climate change is much larger than the GHG emissions attributed to building construction and operations. It is also a major determinant of which populations are vulnerable to climate change-related hazards, such as heat waves and flooding (12; 13). Architecture and land use planning can therefore be used as tools for building community resilience to the climate-related environmental changes underway (13).
   Climate change regulations and voluntary programs have begun to incorporate requirements targeting the built environment's ability to work in tandem with the natural environment to both reduce greenhouse gas emissions and protect its occupants from the health consequences of a changing climate. For example, 11 states have incorporated climate change adaptation goals into their climate action plans (14). In 2010, the not-for-profit organization ICLEI: Local Governments for Sustainability launched a climate change adaptation program (15) to complement their existing mitigation program, which supports municipalities who have signed the U. S. Conference of Mayors' Climate Protection Agreement (16).
   New tools have been introduced to measure community vulnerability to the impacts of climate change. One of these tools, Health Impact Assessments (or HIAs), has emerged over the past decade as a powerful methodology to provide evidence-based recommendations to decision makers and community planning officials about the likely health co-benefits and co-harms associated with proposed policies and land use development proposals (17). While HIAs are becoming a more common feature of community planning efforts, this paper introduces them as an approach to designing climate change resilience into specific building projects.
   HIAs have been used in Europe and other parts of the world for decades to provide a science-based, balanced assessment of the risks and benefits to health associated with a proposed policy or program (18). In the U. S., they have been used over the past decade to evaluate transit-oriented developments, urban infill projects, and California's cap-and-trade legislation, among other topics (17; 19). To date, HIAs have been used mainly to inform large-scale community planning, land use, industrial, and policy decisions. However, the recommendations generated through the HIA process often bring to light previously unforeseen vulnerabilities, whether due to existing infrastructure, building technology, or socio-economic conditions.
   Designers can make use of the HIA process and its resulting recommendations to prioritize design/retrofit interventions that will result in the largest co-benefits to building owners, the surrounding community, and the environment. An HIA focused on the health impacts of climate change will likely generate recommendations that could enhance the longevity of a building project's useful life; protect its property value by contributing to the resilience of the surrounding community; and result in design decisions that prioritize strategies that maximize both short-term efficiencies and long-term environmental, economic, and social value.
EM adeleh@biositu.com
CR [Anonymous], SPAT HAZ EV LOSS DAT
   [Anonymous], 2008, Quantifying Greenhouse Gas Emissions from Key Industrial Sectors in tyhe United States
   [Anonymous], 2008, CLIMATE CHANGE 2007
   Balbus JM, 2009, J OCCUP ENVIRON MED, V51, P33, DOI 10.1097/JOM.0b013e318193e12e
   Basu R, 2008, AM J EPIDEMIOL, V168, P632, DOI 10.1093/aje/kwn170
   BORDEN KA, 2008, INT J HEALTH GEOGR, V7, P13
   *CA BUILD STAND CO, 2010, CAL GREEN BUILD STAN, P193
   Confalonieri U., 2007, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, P391
   Dannenberg AL, 2008, AM J PREV MED, V34, P241, DOI 10.1016/j.amepre.2007.11.015
   Forsyth A, 2010, ENVIRON IMPACT ASSES, V30, P42, DOI 10.1016/j.eiar.2009.05.004
   Frumkin H, 2008, AM J PUBLIC HEALTH, V98, P435, DOI 10.2105/AJPH.2007.119362
   *ICLEI LOC GOV SUS, CLIM AD
   *INT COD COUNC, 2010, INT GREEN CONSTR COD, P243
   International Code Council, 2009 INT EN CONS COD
   [Karl RT. U. S. Global Change Research Program U. S. Global Change Research Program], 2009, GLOBAL CLIMATE CHANG
   Klinenberg E, 1999, THEOR SOC, V28, P239, DOI 10.1023/A:1006995507723
   Luber G, 2008, AM J PREV MED, V35, P429, DOI 10.1016/j.amepre.2008.08.021
   Luber G, 2007, J ENVIRON HEALTH, V70, P43
   *NAT CTR ENV HLTH, CDC HLTH PLAC HLTH I
   PATZ J, 2004, HEAT ADVISORY GLOBAL
   *PEW CTR GLOB CLIM, STAT AD PLANS
   Slotterback CS, 2011, ENVIRON IMPACT ASSES, V31, P144, DOI 10.1016/j.eiar.2010.01.005
   U.S. EPA, 2009, POT RED GREENH GAS E
   U.S. Green Building Council, 2011, AB USGBC
   *US C MAY, 2007, MAY CLIM PROT CTR LI
NR 25
TC 10
Z9 12
U1 7
U2 188
PU COLL PUBL
PI GLEN ALLEN
PA 12309 LYNWOOD DR, GLEN ALLEN, VA 23059 USA
SN 1552-6100
J9 J GREEN BUILD
JI J. Green Build.
PY 2011
VL 6
IS 2
BP 66
EP 87
DI 10.3992/jgb.6.2.66
PG 22
WC Architecture
WE Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Architecture
GA 848MR
UT WOS:000297056200006
OA Bronze
DA 2025-01-10
ER

PT J
AU Uji, A
   Song, J
   Dolsak, N
   Prakash, A
AF Uji, Azusa
   Song, Jaehyun
   Dolsak, Nives
   Prakash, Aseem
TI Public support for climate adaptation aid and migrants: a conjoint
   experiment in Japan
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE climate change; aid; migration; adaptation; survey experiment; conjoint
   analysis; public support
ID FOREIGN-AID; MIGRATION; ATTITUDES; POLICY
AB We examine public support in Japan for overseas climate adaptation assistance via foreign aid and accepting immigrants. Using a survey-embedded conjoint experiment (N = 2815), we focus on seven attributes of an adaptation policy package: (a) the continent in which the country is located; (b) the types of extreme weather event this country faces; (c) the volume of climate aid; (d) the number of climate migrants (e) Japanese exports; (f) Japanese imports, (g) the country's record of voting with Japan in the United Nations. We find that while respondents are indifferent to aid volume, their support diminishes as the number of migrants increases. Moreover, support is higher for Asian countries, that provide export markets, vote with Japan, and where the effects of climate change are gradual. Importantly, we find that public support is not influenced by benchmarking of Japan's or peer G7 countries' past aid or immigration levels.
C1 [Uji, Azusa] Kyoto Univ, Kyoto, Japan.
   [Song, Jaehyun] Kansai Univ, Osaka, Japan.
   [Dolsak, Nives; Prakash, Aseem] Univ Washington, Seattle, WA 98195 USA.
C3 Kyoto University; Kansai University; University of Washington;
   University of Washington Seattle
RP Uji, A (corresponding author), Kyoto Univ, Kyoto, Japan.
EM uji.azusa.2z@kyoto-u.ac.jp
OI Song, Jaehyun/0000-0002-3692-6505
FU Japan Society for the Promotion of Science [18KK0037, 19K21685];  [EPG
   2021]; Grants-in-Aid for Scientific Research [19K21685, 18KK0037]
   Funding Source: KAKEN
FX We are thankful to Liliana Andonova, Federica Genovese, Vally Koubi,
   Christiana Parr; participants at the WPSA 2021, EPG 2021, and APSA 2021
   meetings; and three anonymous reviewers for very valuable comments. This
   research was made possible by generous funding from Japan Society for
   the Promotion of Science (#18KK0037 and #19K21685).
CR Abdelaaty L, 2022, POLIT STUD-LONDON, V70, P110, DOI 10.1177/0032321720950217
   Angelucci M, 2015, REV ECON STAT, V97, P224, DOI 10.1162/REST_a_00487
   [Anonymous], 2018, GLOB TRENDS
   Arndt C, 2017, REV DEV ECON, V21, P285, DOI 10.1111/rode.12291
   Bansak K, 2016, SCIENCE, V354, P217, DOI 10.1126/science.aag2147
   Bauhr M, 2013, INT STUD QUART, V57, P568, DOI 10.1111/isqu.12025
   Bayram AB, 2020, EUR J INT RELAT, V26, P820, DOI 10.1177/1354066119890915
   Bechtel MM, 2013, P NATL ACAD SCI USA, V110, P13763, DOI 10.1073/pnas.1306374110
   Behrman Simon., 2018, Climate Refugees: Beyond The Legallmpasse?
   Berthélemy JC, 2009, WORLD DEV, V37, P1589, DOI 10.1016/j.worlddev.2009.02.002
   Blackman AD, 2018, POLIT RELIG, V11, P522, DOI 10.1017/S1755048318000093
   Boas I, 2019, NAT CLIM CHANGE, V9, P901, DOI 10.1038/s41558-019-0633-3
   Castellano R, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0249315
   Clemens MA, 2014, INTERNATIONAL HANDBOOK ON MIGRATION AND ECONOMIC DEVELOPMENT, P152
   de Haas H, 2007, DEV CHANGE, V38, P819, DOI 10.1111/j.1467-7660.2007.00435.x
   Denney S, 2021, ETHNICITIES, V21, P120, DOI 10.1177/1468796820916609
   DiJulio B., 2016, AM VIEWS US ROLE GLO
   Doherty D, 2020, AM POLIT RES, V48, P635, DOI 10.1177/1532673X20939925
   Dolsak N, 2006, POLICY SCI, V39, P233, DOI 10.1007/s11077-006-9020-9
   Donner SD, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/5/054006
   Dowd R, 2017, INT COMP LAW Q, V66, P863, DOI 10.1017/S0020589317000343
   Dreher A, 2019, EUR ECON REV, V112, P127, DOI 10.1016/j.euroecorev.2018.12.001
   Gamso J, 2018, WORLD DEV, V110, P268, DOI 10.1016/j.worlddev.2018.05.035
   Ghosn F, 2019, J PEACE RES, V56, P118, DOI 10.1177/0022343318804581
   Hainmueller J, 2014, POLIT ANAL, V22, P1, DOI 10.1093/pan/mpt024
   Halimanjaya A, 2015, CLIM CHANG ECON, V6, DOI 10.1142/S2010007815500141
   Hedegaard TF, 2022, SCAND POLIT STUD, V45, P25, DOI 10.1111/1467-9477.12213
   Heinrich T, 2020, BRIT J POLIT SCI, V50, P103, DOI 10.1017/S0007123417000503
   Heinrich T, 2018, INT STUD QUART, V62, P195, DOI 10.1093/isq/sqx081
   Helbling M, 2020, CLIMATIC CHANGE, V160, P89, DOI 10.1007/s10584-020-02697-3
   Henson S, 2013, WORLD DEV, V42, P67, DOI 10.1016/j.worlddev.2012.07.004
   Hicks RobertL., 2010, Greening Aid: Understanding the Environmental Impact of Develoment Assitance
   Huq S, 2004, CLIM POLICY, V4, P25
   Hurst R, 2017, INT STUD QUART, V61, P442, DOI 10.1093/isq/sqx019
   Kiratli OS, 2020, INT J PUBLIC OPIN R, V32, P176, DOI 10.1093/ijpor/edz008
   Lanati M, 2018, ECON LETT, V172, P148, DOI 10.1016/j.econlet.2018.09.002
   Leeper TJ, 2020, POLIT ANAL, V28, P207, DOI 10.1017/pan.2019.30
   Levy JS, 1997, INT STUD QUART, V41, P87, DOI 10.1111/0020-8833.00034
   Lundsgaarde E, 2010, CAN J POLIT SCI, V43, P733, DOI 10.1017/S0008423910000661
   March JG, 1998, INT ORGAN, V52, P943, DOI 10.1162/002081898550699
   Marchal L., 2021, ILE WORKING PAPER SE
   Miller AR, 2007, GLOBAL ENVIRON POLIT, V7, P69, DOI 10.1162/glep.2007.7.1.69
   Milner HV, 2010, ECON POLIT-OXFORD, V22, P200, DOI 10.1111/j.1468-0343.2009.00356.x
   Milner HV, 2011, INT ORGAN, V65, P37, DOI 10.1017/S0020818310000317
   Mirza MMQ, 2003, CLIM POLICY, V3, P233, DOI 10.1016/S1469-3062(03)00052-4
   OECD, 2021, CURRENT STAT
   Paxton P, 2012, INT POLIT SCI REV, V33, P171, DOI 10.1177/0192512111406095
   Peng Ito., 2017, Gender, Migration, and the Work of Care: A Multi-Scalar Approach to the Pacific Rim, P191, DOI 10.1007/978-3-319-55086-2_9
   Peterson JC, 2020, J POLIT, V82, P600, DOI 10.1086/706889
   Rich TS, 2021, JPN J POLIT SCI, V22, P117, DOI 10.1017/S1468109921000116
   Riosmena F, 2018, POPUL DEV REV, V44, P455, DOI 10.1111/padr.12158
   Runfola D., 2016, MIGRAT DEV, V5, P275, DOI [10.1080/21632324.2015.1022969, DOI 10.1080/21632324.2015.1022969]
   Sakellari M, 2021, INT COMMUN GAZ, V83, P63, DOI 10.1177/1748048519883518
   Shehaj A, 2021, PARTY POLIT, V27, P282, DOI 10.1177/1354068819849888
   Spilker G, 2020, NAT CLIM CHANGE, V10, P622, DOI 10.1038/s41558-020-0805-1
   Stanley SK, 2021, ENVIRON POLIT, V30, P1259, DOI 10.1080/09644016.2021.1892982
   Stern Marc., 1998, DEV AID WHAT PUBLIC
   Taras Raymond., 2012, Xenophobia and Islamophobia in Europe
   TODARO MP, 1969, AM ECON REV, V59, P138
   von Hermanni H, 2019, J ETHN MIGR STUD, V45, P349, DOI 10.1080/1369183X.2018.1459183
NR 60
TC 5
Z9 5
U1 1
U2 25
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 1748-9326
J9 ENVIRON RES LETT
JI Environ. Res. Lett.
PD DEC
PY 2021
VL 16
IS 12
AR 124073
DI 10.1088/1748-9326/ac3b7b
PG 11
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA XP9ER
UT WOS:000731161600001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Romero-Muñoz, S
   Sánchez-Chaparro, T
   Sanz, VM
   Tillie, N
AF Romero-Munoz, Sara
   Sanchez-Chaparro, Teresa
   Sanz, Victor Munoz
   Tillie, Nico
TI Urban Greening Management Arrangements between Municipalities and
   Citizens for Effective Climate Adaptation Pathways: Four Case Studies
   from The Netherlands
SO LAND
LA English
DT Article
DE green cities; urban planning; social-ecological systems; citizen
   engagement; collaboration
ID INSTITUTIONAL ANALYSIS; FORESTS
AB The transition towards nature-based cities has increasingly become a central focus in political-environmental agendas and urban design practices, aiming to enhance climate adaptation, urban biodiversity, spatial equilibrium, and social well-being as part of the ongoing socio-ecological urban transition process. Climate adaptation in cities is a complex problem and one of the main collective challenges for society, but the relationships between city managers and citizens as to urban green care still face many challenges. Parks design guided by technical-expert and globalised criteria; inflexibility from bureaucratic inertia; and citizens' demands to participate in the urban green transition, sometimes without the necessary knowledge or time, are some of the challenges that require further research. In this study, we examine four long-lasting approaches to green-space management in four cities in the Netherlands, ranging from municipality-driven to community-driven management forms, and encompassing diverse spatial configurations of greenery within the urban fabric. Utilising the theoretical lens of the Social-Ecological Systems Framework, we employ a multiple-case-study approach and ethnographic fieldwork analysis to gain a comprehensive understanding of the norms, collective-choice rules, and social conventions embodied in each urban green management arrangement. The purpose of this research is applied, that is, to provide urban managers and decision-makers with a deeper understanding of drivers to promote effective collaborative management approaches, focusing on specific organisational rules that may contribute to more sustained planning and maintenance pathways for urban green spaces, regardless of changes in political leadership or significant external funding sources. The results of the investigated cases show that long-lasting collaborative management of forests and parks has established a set of collective-choice rules for resource transfer between municipalities and citizens, including non-monetary resources (such as pruning-training courses or guided tours that attract tourists and researchers). Additionally, these arrangements have been favoured by the existence of legal norms that enable co-ownership of the land, and monitoring and sanctioning mechanisms that offer a slightly different interpretation from the evidence identified so far in the scientific literature on collective resource management and organisational studies.
C1 [Romero-Munoz, Sara] Univ Politecn Madrid, Escuela Tecn Super Ingn Montes Forestal & Medio Na, Madrid 28040, Spain.
   [Sanchez-Chaparro, Teresa] Univ Politecn Madrid, Escuela Tecn Super Ingn Ind, Madrid 28040, Spain.
   [Sanz, Victor Munoz; Tillie, Nico] Delft Univ Technol, Fac Architecture & Built Environm, NL-2628 CD Delft, Netherlands.
C3 Universidad Politecnica de Madrid; Universidad Politecnica de Madrid;
   Delft University of Technology
RP Sánchez-Chaparro, T (corresponding author), Univ Politecn Madrid, Escuela Tecn Super Ingn Ind, Madrid 28040, Spain.
EM sara.romero@upm.es; teresa.sanchez@upm.es; v.munozsanz@tudelft.nl;
   n.m.j.d.tillie@tudelft.nl
RI Sanchez Chaparro, Teresa/ABE-3798-2021
OI Tillie, Nico/0000-0003-3195-1290; Sanchez-Chaparro,
   Teresa/0000-0003-3444-1501
FU Universidad Politecnica de Madrid (Programa Propio de Investigacion
   Pre-doctoral 2023); Santander Bank
FX This research has been funded by a grant from the Universidad
   Politecnica de Madrid (Programa Propio de Investigacion Pre-doctoral
   2023) in collaboration with Santander Bank to support my international
   research stay in the Delft University of Technology (The Netherlands) of
   more than 3 months.
CR Alméstar M, 2023, LAND-BASEL, V12, DOI 10.3390/land12061145
   Almstar M., 2024, The Wild City: Collaborative Practises in Urban Renaturing
   [Anonymous], 2013, Rotterdam Climate Change Adaptation Strategy
   [Anonymous], 2017, Urban green spaces: a brief for action
   Araral E, 2013, ENVIRON SCI POLICY, V25, P147, DOI 10.1016/j.envsci.2012.08.005
   Astell-Burt T, 2019, JAMA NETW OPEN, V2, DOI 10.1001/jamanetworkopen.2019.8209
   Basurto X, 2010, POLIT RES QUART, V63, P523, DOI 10.1177/1065912909334430
   Berman R, 2012, ENVIRON DEV, V2, P86, DOI 10.1016/j.envdev.2012.03.017
   Cities of Rivierenland, Regional Adaptation Strategy 2050
   City of Rotterdam, 2007, Stadsvisie Rotterdam: Ruimtelijke Ontwikkelingsstrategie 2030
   City of the Hague, Delivery of Trees to Neighbours and Schools
   City of the Hague, Eco-Building Points System
   City of Utrecht, Utrecht Spatial Strategy 2040
   City of Utrecht, MaximaPark Plan
   Cole DanielH., 2002, Pollution and Property: Comparing Ownership Institutions for Environmental Protection
   CRAWFORD SES, 1995, AM POLIT SCI REV, V89, P582, DOI 10.2307/2082975
   Cronkleton P, 2012, CONSERV SOC, V10, P91, DOI 10.4103/0972-4923.97481
   DakPark Designer, About us
   dakparkrotterdam, DakPark Website about Volunteer Activities
   Daz de Rada A., 2011, The Workspace of the Ethnographer: Materials and Tools for Ethnographic Research
   Daz de Rada A., 2012, Cultura, Antropologa y Otras Tonteras
   de la Fuente B, 2018, LAND USE POLICY, V75, P429, DOI 10.1016/j.landusepol.2018.04.002
   de la Paz D, 2022, FORESTS, V13, DOI 10.3390/f13050690
   denhaag.raadsinformatie, City of the Hague Urban Nature Memorandum (RIS305824, Appendix1)
   Dez-Picazo L., 2011, Sistema de Derecho Civil. Volumen III, V9th ed.
   Doucet TC, 2024, URBAN FOR URBAN GREE, V93, DOI 10.1016/j.ufug.2024.128220
   Dutch Butterfly Foundation, About us
   Eisenack K, 2016, ECOL ECON, V124, P153, DOI 10.1016/j.ecolecon.2016.01.016
   EISENHARDT KM, 1989, ACAD MANAGE REV, V14, P532, DOI 10.2307/258557
   EVA-Lanxmeer Energy Cooperative, About us
   Fleischman FD, 2014, INT J COMMONS, V8, P428, DOI 10.18352/ijc.416
   Fleischman FD, 2010, ECOL SOC, V15
   forestami, Metropolitan and Municipality of Milan Tree Planting Project
   Gambetta D etal, 2000, Trust: making and breaking cooperative relations, V13, P213, DOI [DOI 10.2307/591021, 10.2307/2234217]
   Giddens A., 2013, CONSEQUENCES MODERNI
   Greater Sydney Five Million Trees, Public Grant
   Groene Mient Climate Adaptation Plan, About us
   groenemient, Groene Mient Website about the Socratic Decision-Making Principles
   Herdt T, 2023, URBAN PLAN, V8, P307, DOI 10.17645/up.v8i2.6413
   Hewitt CN, 2020, AMBIO, V49, P62, DOI 10.1007/s13280-019-01164-3
   Holtan MT, 2015, ENVIRON BEHAV, V47, P502, DOI 10.1177/0013916513518064
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2021The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel On Climate Change, DOI [10.1017/9781009325844.001, DOI 10.1017/9781009157940, 10.1017/9781009157896]
   Kolimenakis A, 2022, LAND-BASEL, V11, DOI 10.3390/land11122290
   Konijnendijk CC, 2023, J FORESTRY RES, V34, P821, DOI 10.1007/s11676-022-01523-z
   lanxmeer, EVA-Lanxmeer Website about Its Origins
   lanxmeer, EVA-Lanxmeer Eco-District Urban Plan
   Larkin A, 2019, J EXPO SCI ENV EPID, V29, P447, DOI 10.1038/s41370-018-0017-1
   Libecap GD, 2011, AM ECON REV, V101, P64, DOI 10.1257/aer.101.1.64
   Lottrup L, 2015, LANDSCAPE RES, V40, P57, DOI 10.1080/01426397.2013.829806
   Madrid Metropolitan Forest Promotional, About us
   Malinowski B., 2013, Argonauts of the western Pacific: An account of native enterprise and adventure in the archipelagoes of Melanesian New Guinea, VRoutledge.
   Marshall GR, 2013, ECOL ECON, V88, P185, DOI 10.1016/j.ecolecon.2012.12.030
   maximapark, MaximaPark Website on Volunteers Foundation
   McGinnis MD, 2014, ECOL SOC, V19, DOI 10.5751/ES-06387-190230
   metropol, Metropolitan Area of Medellin Plan
   MEYER JW, 1977, AM J SOCIOL, V83, P340, DOI 10.1086/226550
   mnd, Sino-Singapore Tianjin Eco-City Project
   omslag, Eco-Housing Initiatives and International Networks Repository
   Ostrom E, 1998, AM POLIT SCI REV, V92, P1, DOI 10.2307/2585925
   Ostrom E., 1990, GOVERNING COMMONS EV
   Ostrom E, 2011, POLICY STUD J, V39, P7, DOI 10.1111/j.1541-0072.2010.00394.x
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Vallejo AMP, 2018, DERECHO PUCP, P239, DOI 10.18800/derechopucp.201801.007
   Powell A., 1991, The new institutionalism in organization analysis
   puurpermacultuur, Eco-Districts and Eco-Villages Repository in The Netherlands
   Roggero M, 2015, ECOL ECON, V118, P114, DOI 10.1016/j.ecolecon.2015.07.022
   Roman LA, 2018, URBAN FOR URBAN GREE, V31, P157, DOI 10.1016/j.ufug.2018.03.004
   Romero-Muñoz S, 2023, LAND-BASEL, V12, DOI 10.3390/land12061179
   Romero-Muoz S., 2021, Bachelors Thesis
   Rugel EJ, 2019, ENVIRON RES, V171, P365, DOI 10.1016/j.envres.2019.01.034
   Santos MM, 2021, CITIES, V114, DOI 10.1016/j.cities.2021.103176
   Sanz VM, 2022, URBAN PLAN, V7, P202, DOI 10.17645/up.v7i2.5039
   Scott WR, 2014, MANAGEMENT, V17, P136, DOI 10.3917/mana.172.0136
   Sharifi A, 2016, SUSTAIN CITIES SOC, V20, P1, DOI 10.1016/j.scs.2015.09.002
   Sijmons D., 2020, Nature Driven Urbanism, V1st ed., P9
   Solomou AD, 2019, NOT BOT HORTI AGROBO, V47, P10, DOI 10.15835/nbha47111316
   sterkopstroom, Groene Mient Energy Cooperative, the Hague
   Tillie N, 2016, ENVIRON SCI POLICY, V62, P139, DOI 10.1016/j.envsci.2016.04.016
   UN, 2016, NEW URBAN AGENDA HAB
   UNISDR (United Nations International Strategy for Disaster Reduction), 2015, Sendai Framework for Disaster Risk Reduction 2015-2030
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   van der Berg A, 2023, EUR J RISK REGUL, V14, P564, DOI 10.1017/err.2022.17
   VAN Doorn-hoekveld WJ, 2022, UTRECHT LAW REV, V18, P51, DOI 10.36633/ulr.860
   Velarde M. D., 2007, Urban Forestry & Urban Greening, V6, P199, DOI 10.1016/j.ufug.2007.07.001
   Velasco H., 1997, La Lgica de la Investigacin Etnogrfica
   Velasco H., 2006, La Sonrisa de la Institucin. Confianza y Riesgo en Sistemas Expertos
   vision2030, The Line Project in Saudi Arabia
   warmindewijk, The Hague Energy Cooperative
   Yin R. K., 2017, Case study research and applications: Design and methods, V6th
   zastromujprahu, Monitoring Website of the Tree Planting Scheme of the City of Prague
NR 90
TC 0
Z9 0
U1 1
U2 1
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD SEP
PY 2024
VL 13
IS 9
AR 1414
DI 10.3390/land13091414
PG 32
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA H5F8J
UT WOS:001323706400001
OA gold
DA 2025-01-10
ER

PT S
AU Nielsen, LW
AF Nielsen, Lisbeth Witthofft
BE Macpherson, CC
TI Climate Change Vulnerability and Health Impacts in South East Asia and
   China
SO BIOETHICAL INSIGHTS INTO VALUES AND POLICY: CLIMATE CHANGE AND HEALTH
SE Public Health Ethics Analysis
LA English
DT Article; Book Chapter
AB This chapter outlines climate vulnerabilities for countries in South East Asia and how these may influence human health in this region, and discusses the ethical issues related to the governance of climate adaptation within this context. Section 7.1 focuses on national climate adaptation strategies among countries in South East Asia, and discusses the bioethical issues arising from these strategies. It argues that the distinction between non-health and health adaptation measures gives rise to ethical concerns because the potential for preventing or alleviating the health threats from climate change long term may be overlooked. Section 7.2 focuses on vulnerabilities to climate of human health among urban populations in South East Asia and China, and discusses the ethical issues related to the governance of sustainable megacities in this region. It argues that health impacts of climate change and air pollution on urban populations must be taken into consideration in the development of governance strategies for sustainable development, with a view to ensuring that the health and wellbeing of urban populations is not compromised in the pursuit of socioeconomic development by a country as a whole. The paper concludes that bioethicists can contribute to raising awareness, among those involved in governance, of the importance of more proactive involvement of the health sector in the development of national climate adaptation strategies; and to flagging pitfalls in existing strategies regarding urban sustainable development that may compromise the health and wellbeing of urban populations, and of the urban poor in particular.
C1 [Nielsen, Lisbeth Witthofft] Dalhousie Univ, Dept Bioeth, Fac Med, Halifax, NS, Canada.
C3 Dalhousie University
RP Nielsen, LW (corresponding author), Dalhousie Univ, Dept Bioeth, Fac Med, Halifax, NS, Canada.
EM lisbeth.witthoefft.nielsen@Dal.Ca
CR [Anonymous], 18 HEI INT SCI OV CO
   [Anonymous], MYANM NAT AD PROGR A
   [Anonymous], 1987, OUR COMMON FUTURE RE
   Asian Development Bank (ADB), 2013, URB OP PLAN 2012 202
   Asian Development Bank (ADB) and Ministry of Transport People's Republic of China, 2012, URB TRANSP STRAT COM
   Banu S, 2011, TROP MED INT HEALTH, V16, P598, DOI 10.1111/j.1365-3156.2011.02734.x
   Cruz RV, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P469
   Duggan Jennifer, 2013, THE GUARDIAN    1121
   Earthscan, 2006, STUD REV CLEAN AIR C
   Environment of Air Quality and Health,, 2021, AIR QUAL HLTH
   Fang Y., 2013, CLIMATIC CHANGE, DOI [10.1007/s10584013-08478, DOI 10.1007/S10584013-08478]
   Jing Li, 2013, S CHINA MORNING 0902
   Kemp P, 2009, BARRIERS CLIMATE AWA
   Khalik Salma, 2013, STRAITS TIMES   0622
   Koh K. L., 2010, SOCIAL SPACE, P84
   Kovats S, 2008, ENVIRON URBAN, V20, P165, DOI 10.1177/0956247808089154
   Lian K.K., 2011, Carbon Clim. Law Rev, V5, P82, DOI [10.21552/CCLR/2011/1/159, DOI 10.21552/CCLR/2011/1/159]
   Loomis D., 2013, LANCET ONCOLOGY, DOI [10.1016/S14702045(13)70487X, DOI 10.1016/S14702045(13)70487X]
   National Climate Secretariat, 2012, CLIM CHANG SING CHAL
   Pipitsombat Nirawan, 2012, THAILANDS CLIMATE PO
   The Socialist Republic of Vietnam, 2011, NAT CLIM CHANG STRAT
   UN, 2012, ESAPWP224 UN
   UNHABITAT, 2006, AS PAC MIN C HOUS HU
   United National Development Programme (UNEP), 2012, AS PAC HUM DEV REP B
   Vidal J., 2013, THEGUADIAN      1108
   WHO, 2006, WHO GUID PART MATT O
   World Bank, 2013, WHAT IS GOV
NR 27
TC 0
Z9 0
U1 1
U2 5
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2211-6680
EI 2211-6699
BN 978-3-319-26167-6; 978-3-319-26165-2
J9 PUB HEALTH ETHICS AN
PY 2016
VL 4
BP 89
EP 101
DI 10.1007/978-3-319-26167-6_7
D2 10.1007/978-3-319-26167-6
PG 13
WC Ethics; Environmental Studies; Public, Environmental & Occupational
   Health; Medical Ethics
WE Book Citation Index – Social Sciences & Humanities (BKCI-SSH); Book Citation Index – Science (BKCI-S)
SC Social Sciences - Other Topics; Environmental Sciences & Ecology;
   Public, Environmental & Occupational Health; Medical Ethics
GA BJ1TQ
UT WOS:000418031000009
DA 2025-01-10
ER

PT J
AU David, JR
   Araripe, LO
   Chakir, M
   Legout, H
   Lemos, B
   Pétavy, G
   Rohmer, C
   Joly, D
   Moreteau, B
AF David, JR
   Araripe, LO
   Chakir, M
   Legout, H
   Lemos, B
   Pétavy, G
   Rohmer, C
   Joly, D
   Moreteau, B
TI Male sterility at extreme temperatures:: a significant but neglected
   phenomenon for understanding <i>Drosophila</i> climatic adaptations
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article; Proceedings Paper
CT 10th Biennal Congress of the European-Society-for-Evolutionary-Biology
   (ESEB)
CY AUG 15-20, 2005
CL Cracow, POLAND
SP European Soc Evolut Biol
DE evolutionary trade-off; spermatogenesis; thermal stress; viability; Y
   chromosome
ID REACTION NORMS; Y-CHROMOSOME; PHENOTYPIC PLASTICITY;
   NATURAL-POPULATIONS; GENETIC-VARIABILITY; HSP70 EXPRESSION; SPERM
   LENGTH; MELANOGASTER; SIMULANS; COLD
AB The thermal range for viability is quite variable among Drosophila species and it has long been known that these variations are correlated with geographic distribution: temperate species are on average more cold tolerant but more heat sensitive than tropical species. At both ends of their viability range, sterile males have been observed in all species investigated so far. This symmetrical phenomenon restricts the temperature limits within which permanent cultures can be kept in the laboratory. Thermal heat sterility thresholds are very variable across species from 23 degrees C in heat sensitive species up to 31 degrees C in heat tolerant species. In Drosophila melanogaster, genetic variations are observed among geographic populations. Tropical populations are more tolerant to heat induced sterility and recover more rapidly than temperate ones. A genetic analysis revealed that about 50% of the difference observed between natural populations was due to the Y chromosome. Natural populations have not reached a selection limit, however: thermal tolerance was still increased by keeping strains at a high temperature, close to the sterility threshold. On the low temperature side, a symmetrical reverse phenomenon seems to exist: temperate populations are more tolerant to cold than tropical ones. Compared to Mammals, drosophilids exhibit two major differences: first, male sterility occurs not only at high temperature, but also at a low temperature; second, sterility thresholds are not evolutionarily constrained, but highly variable. Altogether, significant and sometimes major genetic variations have been observed between species, between geographic races of the same species, and even between strains kept in the laboratory under different thermal regimes. In each case, it is easily argued that the observed variations correspond to adaptations to climatic conditions, and that male sterility is a significant component of fitness and a target of natural selection.
C1 CNRS, Lab Populat Genet & Evolut, F-91198 Gif Sur Yvette, France.
   Univ Estadual Campinas, Inst Biol, Dept Genet & Evolucao, BR-13081970 Campinas, SP, Brazil.
   Univ Cadi Ayyad, Fac Sci & Tech, Marrakech, Morocco.
   Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA.
C3 Universite Paris Saclay; Centre National de la Recherche Scientifique
   (CNRS); Universidade de Sao Paulo; Universidade Estadual de Campinas;
   Cadi Ayyad University of Marrakech; Harvard University
RP David, JR (corresponding author), CNRS, Lab Populat Genet & Evolut, F-91198 Gif Sur Yvette, France.
EM david@pge.cnrs-gif.fr
RI Lemos, Bernardo/AAL-2429-2020; O Araripe, Luciana/LDF-3854-2024
OI O Araripe, Luciana/0000-0001-5878-1792
CR [Anonymous], 1954, The distribution and abundance of animals, DOI DOI 10.1111/BRV
   [Anonymous], 1987, Temperature biology of animals
   Araripe LO, 2004, J THERM BIOL, V29, P73, DOI 10.1016/j.jtherbio.2003.11.006
   AYLES GB, 1973, DEV BIOL, V32, P239, DOI 10.1016/0012-1606(73)90239-X
   Ayrinhac A, 2004, FUNCT ECOL, V18, P700, DOI 10.1111/j.0269-8463.2004.00904.x
   Campbell Roosevelt V., 2001, Drosophila Information Service, V84, P6
   CAVICCHI S, 1985, GENETICS, V109, P665
   Chakir M, 2002, GENETICA, V114, P195, DOI 10.1023/A:1015154329762
   CLARK AG, 1990, GENETICS, V125, P527
   COHET Y, 1973, CR ACAD SCI D NAT, V276, P3343
   COHET Y, 1980, J THERM BIOL, V5, P69, DOI 10.1016/0306-4565(80)90002-9
   DAVID J, 1976, J GENET, V62, P93, DOI 10.1007/BF02984216
   DAVID J, 1971, CR ACAD SCI D NAT, V272, P1007
   David JR, 2005, HEREDITY, V94, P3, DOI 10.1038/sj.hdy.6800562
   David JR, 1997, J THERM BIOL, V22, P441, DOI 10.1016/S0306-4565(97)00063-6
   David JR, 2004, GENETICA, V120, P151, DOI 10.1023/B:GENE.0000017638.02813.5a
   David JR, 2003, FUNCT ECOL, V17, P425, DOI 10.1046/j.1365-2435.2003.00750.x
   DAVID JR, 1988, TRENDS GENET, V4, P106, DOI 10.1016/0168-9525(88)90098-4
   DAVID JR, 1983, GENETICS BIOL DROS D, V3, P105
   FRANKEL AWK, 1973, GENETICS, V74, P115
   Gibbs AG, 2003, J THERM BIOL, V28, P353, DOI 10.1016/S0306-4565(03)00011-1
   Gibert P, 2001, EVOLUTION, V55, P1063, DOI 10.1554/0014-3820(2001)055[1063:CCTAMC]2.0.CO;2
   Hoffmann A. A., 1997, EXTREME ENV CHANGE E
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann Ary A., 1991, Evolutionary Genetics and Environmental Stress
   JOLY D, 1994, INT J INSECT MORPHOL, V23, P85, DOI 10.1016/0020-7322(94)90002-7
   Joly D, 2004, GENETICA, V120, P233, DOI 10.1023/B:GENE.0000017644.63389.57
   JOLY D, 1989, GENET SEL EVOL, V21, P283, DOI 10.1051/gse:19890305
   Joly D, 1997, HEREDITY, V78, P354, DOI 10.1038/hdy.1997.58
   KUZNETSOVA OV, 1994, GENETIKA+, V30, P903
   Lachaise D, 2004, EVOLUTION OF POPULATION BIOLOGY, P315, DOI 10.1017/CBO9780511542619.019
   LEATHER S, 1993, ECOLOGY INSECTS OVER
   Maisonhaute C, 1999, ENVIRON ENTOMOL, V28, P116, DOI 10.1093/ee/28.1.116
   Moreteau B, 1997, CR ACAD SCI III-VIE, V320, P833, DOI 10.1016/S0764-4469(97)85020-2
   Morin JP, 1997, EVOLUTION, V51, P1140, DOI 10.1111/j.1558-5646.1997.tb03961.x
   Morin JP, 1999, J EVOLUTION BIOL, V12, P329, DOI 10.1046/j.1420-9101.1999.00038.x
   Pétavy G, 2004, EVOL ECOL RES, V6, P873
   Petavy G, 2001, J THERM BIOL, V26, P29, DOI 10.1016/S0306-4565(00)00022-X
   Precht H., 1955, Temperatur and Leben
   Rinehart JP, 2000, PHYSIOL ENTOMOL, V25, P330, DOI 10.1046/j.1365-3032.2000.00201.x
   ROBERTSON FW, 1959, GENETICS, V44, P869
   Rohmer C, 2004, J EXP BIOL, V207, P2735, DOI 10.1242/jeb.01087
   Sarup P, 2004, FUNCT ECOL, V18, P365, DOI 10.1111/j.0269-8463.2004.00863.x
   SUCHOWERSKY O, 1974, DROS INF SERV, V51, P55
   Suzuki D.T., 1975, Handbook of Genetics, P653
   Timakov B, 2000, GENETICS, V155, P179
   Vollmer JH, 2004, HEREDITY, V92, P257, DOI 10.1038/sj.hdy.6800405
   Zatsepina OG, 2001, J EXP BIOL, V204, P1869
   Zurovcova M, 1999, GENETICS, V153, P1709
NR 49
TC 168
Z9 188
U1 1
U2 66
PU BLACKWELL PUBLISHING
PI OXFORD
PA 9600 GARSINGTON RD, OXFORD OX4 2DG, OXON, ENGLAND
SN 1010-061X
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD JUL
PY 2005
VL 18
IS 4
BP 838
EP 846
DI 10.1111/j.1420-9101.2005.00914.x
PG 9
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Conference Proceedings Citation Index - Science (CPCI-S); Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 939BS
UT WOS:000230047800013
PM 16033555
OA Bronze
DA 2025-01-10
ER

PT J
AU Tawsif, S
   Paul, SK
   Khan, MS
AF Tawsif, Shehan
   Paul, Shitangsu Kumar
   Khan, Md. Shohel
TI Livelihood vulnerability assessment of slum dwellers in Rajshahi,
   Bangladesh: Capital indices-based approach
SO JOURNAL OF ENVIRONMENTAL STUDIES AND SCIENCES
LA English
DT Article; Early Access
DE Livelihood capitals; Covid-19; Financial crisis; Leadership potential
ID CLIMATE-CHANGE ADAPTATION; COMMUNITIES; SECURITY; POVERTY; IMPACTS;
   INDIA
AB The recent Covid-19 pandemic has tremendously changed the livelihoods of slum dwellers due to the sudden loss of occupations and this situation increased their vulnerability. The objective of this paper was to assess the slum dwellers' livelihood vulnerability by implementing LVI with reference to five livelihood capitals which comprise 27 sub-components. The RCC slum area was deliberately selected as the study area and it is one that is categorized into inner, middle and outer zones based on distance from the CBD. In total, 361 households were selected through simple random sampling from twelve slum areas with a 95% precision level. Primary data were gathered from the three stated slum zones using semi-structured questionnaires that investigated health, knowledge and skills, leadership potential, demographic profile, participation and connection, housing and sanitation, income and finance, total land and water as major components to assess LVI. Results revealed that the outer slum zone was the most vulnerable (0.697) based on overall LVI because financial and physical capital vulnerability were found to be higher. As well, LVI reported that inner (0.560) and middle (0.660) slum zones were categorized as moderate. The study also found that the slums located near the CBD were found to be less vulnerable because they managed to receive basic needs from relief efforts during the pandemic. Inner slum zone dwellers' human capital (health, knowledge and skills, leadership potential) vulnerability proved to be lower than in the middle and the outer zones. Social capital (demographic profile and participation and connection) vulnerability of the inner zone was better than the other two zones. Overall, less access to own/agricultural land or grazing land and water facilities in slum zones was reported in natural capital vulnerability. Radar diagrams showed all livelihood capitals vulnerability of the outer zone were to be higher than the inner zone except for natural capital. Finally, the central government should devise appropriate guidelines to reduce livelihood vulnerability which hugely compromises the lives and livelihoods of slum dwellers.
C1 [Tawsif, Shehan] Shahjalal Univ Sci & Technol, Dept Geog & Environm, Sylhet 3114, Bangladesh.
   [Tawsif, Shehan; Paul, Shitangsu Kumar] Univ Rajshahi, Dept Geog & Environm Studies, Rajshahi 6205, Bangladesh.
   [Khan, Md. Shohel] Noakhali Sci & Technol Univ, Dept Environm Sci & Disaster Management, Noakhali 3814, Bangladesh.
   [Khan, Md. Shohel] Univ Rajshahi, Inst Bangladesh Studies, Rajshahi 6205, Bangladesh.
C3 Shahjalal University of Science & Technology (SUST); University of
   Rajshahi; Noakhali Science & Technology University (NSTU); University of
   Rajshahi
RP Tawsif, S (corresponding author), Shahjalal Univ Sci & Technol, Dept Geog & Environm, Sylhet 3114, Bangladesh.; Tawsif, S (corresponding author), Univ Rajshahi, Dept Geog & Environm Studies, Rajshahi 6205, Bangladesh.
EM shehantawsif@gmail.com
RI Paul, Shitangsu/AAE-8679-2021
OI Paul, Shitangsu Kumar/0000-0003-3018-793X; Tawsif,
   Shehan/0000-0003-3394-000X
CR Aberese-Ako M, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0271551
   Acharya R, 2020, LANCET GLOB HEALTH, V8, pE1142, DOI 10.1016/S2214-109X(20)30300-4
   Adger WN, 2009, FRONT ECOL ENVIRON, V7, P150, DOI 10.1890/070148
   Ahmed MT, 2014, J WATER CLIM CHANGE, V5, P287, DOI 10.2166/wcc.2014.006
   Alam GMM, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14031071
   Alammari MR., 2013, Am J Res Commun, V1, P1, DOI DOI 10.11648/J.AJTTE.20190401.14
   [Anonymous], 2007, C WHY IS URB ASS IMP
   [Anonymous], 2020, LANCET, V395, P1089, DOI [DOI 10.1016/S0140-6736(20)30757-1, 10.1016/S0140-6736]
   [Anonymous], 2023, Coronavirus disease (COVID-19) pandemic
   [Anonymous], 2007, HUMAN DEV REPORTS
   [Anonymous], 2014, BANGLADESH POPULATIO
   Armah FA, 2017, J ENVIRON STUD SCI, V7, P69, DOI 10.1007/s13412-015-0334-9
   Azam G, 2021, GLOB SOC WELFARE, V8, P93, DOI 10.1007/s40609-019-00148-1
   Banu N, 2023, GEOJOURNAL, V88, P6435, DOI 10.1007/s10708-023-10977-5
   Barrett CB, 2010, InOxford Research Encyclopedia of International Studies
   Barros V, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, pIX
   Bennett NJ, 2016, REG ENVIRON CHANGE, V16, P907, DOI 10.1007/s10113-015-0839-5
   Bhat MS, 2023, J ENVIRON STUD SCI, V13, P253, DOI 10.1007/s13412-023-00818-9
   Botero DG, 2013, Assessing farmers' vulnerability to climate change: a case study in Karnataka, India
   Brown K, 2011, CLIM DEV, V3, P21, DOI 10.3763/cdev.2010.0062
   Can ND., 2013, J ENVIRON SCI ENG, V2, P476
   Chambers R., 1992, Discussion Paper - Institute of Development Studies, University of Sussex
   Cifdaloz O, 2010, ECOL SOC, V15
   Clemett A., 2006, WASPA Asia Project Report, V2, P1
   Constantin V, 2015, ENVIRON SCI POLICY, V52, P129, DOI 10.1016/j.envsci.2015.05.010
   Das M, 2021, INT J DISAST RISK RE, V65, DOI 10.1016/j.ijdrr.2021.102553
   de Perez EC, 2019, FOOD SECUR, V11, P57, DOI 10.1007/s12571-018-00885-9
   DFID, 1999, Sustainable livelihood guidance sheets
   Fekete A, 2014, INT J DISAST RISK SC, V5, P3, DOI 10.1007/s13753-014-0008-3
   GHOSH S., 2020, Social Sciences Humanities Open, V2, DOI [10.1016/j.ssaho.2020.100068, DOI 10.1016/J.SSAHO.2020.100068]
   Gill JC, 2014, REV GEOPHYS, V52, P680, DOI 10.1002/2013RG000445
   Giri M, 2021, J CLEAN PROD, V307, DOI 10.1016/j.jclepro.2021.127213
   Gupta AK, 2019, ECOL INDIC, V106, DOI 10.1016/j.ecolind.2019.105512
   Habib MA, 2021, APPL SCI-BASEL, V11, DOI 10.3390/app11093744
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Hasnat G.N.T., 2022, ENV CHALLENGES, V9, DOI [10.1016/j.envc.2022.100644, DOI 10.1016/J.ENVC.2022.100644]
   Heitnze H.-J., 2018, INT HUMANITARIAN ACT, P209
   Hossain MN, 2018, EARTH SYST ENVIRON, V2, P55, DOI 10.1007/s41748-018-0034-1
   Hufschmidt G, 2011, NAT HAZARDS, V58, P621, DOI 10.1007/s11069-011-9823-7
   Jakaria M, 2015, Rabindra J, V32, P157
   JRC-EC Joint Research Centre-European Commission, 2008, Handbook on constructing composite indicators: Methodology and user guide
   Khan MA, 2022, PROG DISASTER SCI, V15, DOI 10.1016/j.pdisas.2022.100243
   Khan MS, 2023, Geosfera Indonesia, V8, P133, DOI [10.19184/geosi.v8i2.39584, DOI 10.19184/GEOSI.V8I2.39584]
   Khan MS., 2023, Discover Water, V3, P27, DOI [10.1007/s43832-023-00052-y, DOI 10.1007/S43832-023-00052-Y]
   Kittiprapas S, 2022, COGENT SOC SCI, V8, DOI 10.1080/23311886.2022.2074111
   Kothari C. R., 2004, Research methodology: Methods Techniques, V3rd
   Lazzari N, 2021, SCI TOTAL ENVIRON, V784, DOI 10.1016/j.scitotenv.2021.147078
   Libório MP, 2022, GEOJOURNAL, V87, P1453, DOI 10.1007/s10708-020-10322-0
   Liu YH, 2016, APPL GEOGR, V73, P62, DOI 10.1016/j.apgeog.2016.06.004
   Marshall NA, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034022
   McEntire D, 2012, DISASTER PREV MANAG, V21, P206, DOI 10.1108/09653561211220007
   Napier AD, 2020, ANTHROPOL TODAY, V36, P1, DOI 10.1111/1467-8322.12571
   Nardo M., 2005, Analysis, EUR, V21682, P134, DOI DOI 10.1038/NRM1524
   Natarajan N, 2022, WORLD DEV, V155, DOI 10.1016/j.worlddev.2022.105898
   Nawrotzki RJ, 2023, J ENVIRON STUD SCI, V13, P473, DOI 10.1007/s13412-023-00831-y
   Nayak S, 2023, HELIYON, V9, DOI 10.1016/j.heliyon.2023.e19177
   Oluoch IO, 2022, J CONTING CRISIS MAN, V30, P41, DOI 10.1111/1468-5973.12397
   Omerkhil N, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105863
   Otaha I.J., 2013, AFRICAN RES REV, V7, P26, DOI [DOI 10.4314/AFRREV.V7I4.2, 10.4314/afrrev.v7i4.2]
   Pandey R, 2018, ECOL INDIC, V90, P379, DOI 10.1016/j.ecolind.2018.03.031
   Pandey R, 2018, ECOL INDIC, V84, P27, DOI 10.1016/j.ecolind.2017.08.021
   Pandey R, 2016, J MT SCI-ENGL, V13, P1503, DOI 10.1007/s11629-015-3499-5
   Pandey R, 2012, MITIG ADAPT STRAT GL, V17, P487, DOI 10.1007/s11027-011-9338-2
   PandeyR YangchenC, 2023, Bhutan Habitat Int, V136, DOI [10.1016/j.habitatint.2023.102817, DOI 10.1016/J.HABITATINT.2023.102817]
   Pani BS, 2022, REG SUSTAIN, V3, P110, DOI 10.1016/j.regsus.2022.07.003
   Papageorgiou K, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0233984
   Parris TM, 2003, ANNU REV ENV RESOUR, V28, P559, DOI 10.1146/annurev.energy.28.050302.105551
   Paul S.K., 2013, J LIFE EARTH SCI, V8, P63
   Pongutta S, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e07161
   Rajesh S, 2018, ECOL INDIC, V85, P93, DOI 10.1016/j.ecolind.2017.10.014
   Raju E, 2021, PROG DISASTER SCI, V10, DOI 10.1016/j.pdisas.2021.100163
   Rana IA, 2021, INT J DISAST RISK RE, V63, DOI 10.1016/j.ijdrr.2021.102442
   Sahoo G, 2021, MINER ECON, V34, P455, DOI 10.1007/s13563-021-00266-3
   Sakamoto M, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12135296
   Sarker MNI, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11061623
   Schotte S, 2023, SOC INDIC RES, V165, P1, DOI 10.1007/s11205-022-02978-7
   Senapati AK, 2020, SPAT INF RES, V28, P139, DOI 10.1007/s41324-019-00277-x
   Shen JY, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19010551
   Shermin N, 2021, J URBAN MANAG, V10, P230, DOI 10.1016/j.jum.2021.06.003
   Shuaib ASM, 2020, MANAG ENVIRON QUAL, V31, P75, DOI 10.1108/MEQ-06-2019-0138
   Su F, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11121230
   Sullivan C, 2002, WORLD DEV, V30, P1195, DOI 10.1016/S0305-750X(02)00035-9
   Tawsif S, 2023, 9 INT C WAT FLOOD MA, P429
   Tawsif S, 2024, Int J Human Capital Urban Manag, V9, P101, DOI [10.22034/IJHCUM.2024.01.08, DOI 10.22034/IJHCUM.2024.01.08]
   Tewari HR, 2014, JAMBA-J DISASTER RIS, V6, P1, DOI [10.4102/jamba.v6i1.127, DOI 10.4102/jamba.v6i1.127]
   Thornton PK, 2014, GLOBAL CHANGE BIOL, V20, P3313, DOI 10.1111/gcb.12581
   Uddin SMH, 2011, WATER SCI TECH-W SUP, V11, P545, DOI 10.2166/ws.2011.079
   Wisner B, 2004, At Risk. Natural hazards, People's Vulnerability and Disasters, DOI [10.4324/9780203714775/risk-piers-blaikie-terry-cannon-ian-davis-ben-wisner, DOI 10.4324/9780203714775/RISK-PIERS-BLAIKIE-TERRY-CANNON-IAN-DAVIS-BEN-WISNER]
   Workie E, 2020, CURR RES ENVIRON SUS, V2, DOI 10.1016/j.crsust.2020.100014
NR 89
TC 0
Z9 0
U1 1
U2 1
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 2190-6483
EI 2190-6491
J9 J ENVIRON STUD SCI
JI J. Environ. Stud. Sci.
PD 2024 OCT 17
PY 2024
DI 10.1007/s13412-024-00988-0
EA OCT 2024
PG 18
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA J0Z6G
UT WOS:001334442300001
DA 2025-01-10
ER

PT J
AU Shitara, T
   Kurokawa, H
   Oguro, M
   Sasaki, T
   Ohashi, H
   Niiyama, K
   Shibata, M
   Matsui, T
AF Shitara, Takuto
   Kurokawa, Hiroko
   Oguro, Michio
   Sasaki, Takehiro
   Ohashi, Haruka
   Niiyama, Kaoru
   Shibata, Mitsue
   Matsui, Tetsuya
TI Long-term changes in vegetation and land use in mountainous areas with
   heavy snowfalls in northern Japan: an 80-year comparison of vegetation
   maps
SO FRONTIERS IN ENVIRONMENTAL SCIENCE
LA English
DT Article
DE beech forest; climate change impact; cool temperate forest; deciduous
   oak forest; ecotone; forest underutilization; subarctic forest;
   vegetation monitoring
ID FORESTS
AB Comparison of old and new vegetation maps is an effective way to detect vegetation dynamics. Recent developments in computer technology have made it possible to accurately compare old paper vegetation maps with current digitized vegetation maps to reveal long-term vegetation dynamics. Recently, a 1:50,000 scale vegetation map of the Hakkoda Mountains in northern Japan, located in the ecotone of cool temperate and subalpine forests in northern Japan under an East Asian monsoon climate, from 1930 was discovered. We compared the 1930s vegetation map with the most recent 2010 vegetation map to test the following hypotheses: 1) the occurrence of upward expansion of the upper limit of cool-temperate deciduous forests, and 2) whether designation as a national park in 1936 would have reduced forestry and land use, expanded beech forests, and cool-temperate deciduous forests. To compare vegetation changes, 67 types of vegetation legends for the 1930 and 2010 maps were unified to 21 based on plant species composition. Consequently, vegetation has changed substantially over the past 80 years. 1) In the subalpine zone above 1,000 m, the coniferous forest area decreased by half. In the cool temperate zone below 1,000 m, the area of beech forests increased 1.48 times, and some of them could be shifted upwards, replacing subalpine fir forests in the lower part of the subalpine zone. 2) In areas below 700 m, deciduous oak forests once used as thickets were almost halved. Instead, climax and beech forests expanded. However, we also found that even after the area was declared a national park, oak forests were cleared and converted to commercial forests such as cedar plantations, cattle ranches, and horse pastures in some areas. These results will be useful for future ecosystem and biodiversity research/conservation and will provide baseline information for climate change adaptation policies.
C1 [Shitara, Takuto] Tama Sci Forest Garden Forestry & Forest Prod Res, Tokyo, Japan.
   [Kurokawa, Hiroko; Oguro, Michio; Niiyama, Kaoru; Shibata, Mitsue] Forestry & Forest Prod Res Inst, Dept Forest Vegetat, Tsukuba, Ibaraki, Japan.
   [Sasaki, Takehiro] Yokohama Natl Univ, Grad Sch Environm & Informat Sci, Yokohama, Japan.
   [Ohashi, Haruka] Forestry & Forest Prod Res Inst, Dept Wildlife Biol, Tsukuba, Ibaraki, Japan.
   [Matsui, Tetsuya] Forestry & Forest Prod Res Inst, Ctr Biodivers & Climate Change, Tsukuba, Ibaraki, Japan.
   [Matsui, Tetsuya] Univ Tsukuba, Fac Life & Environm Sci, Tsukuba, Ibaraki, Japan.
C3 Forestry & Forest Products Research Institute - Japan; Yokohama National
   University; Forestry & Forest Products Research Institute - Japan;
   Forestry & Forest Products Research Institute - Japan; University of
   Tsukuba
RP Matsui, T (corresponding author), Forestry & Forest Prod Res Inst, Ctr Biodivers & Climate Change, Tsukuba, Ibaraki, Japan.; Matsui, T (corresponding author), Univ Tsukuba, Fac Life & Environm Sci, Tsukuba, Ibaraki, Japan.
EM tematsui@affrc.go.jp
FU JSPS [JP20H04380, JP23K13986]
FX The author(s) declare financial support was received for the research,
   authorship, and/or publication of this article. This research is part of
   the JSPS Grants-in-Aid for Scientific Research, KAKENHI, JP20H04380 and
   JP23K13986.
CR A Miyawaki., 1987, Vegetation of Japan
   Aiba SI, 2023, ECOL RES, V38, P740, DOI 10.1111/1440-1703.12367
   Biodiversity Center of Japan, 2010, Existing vegetation map 1: 25,000
   Boisvert-Marsh L, 2019, J ECOL, V107, P1956, DOI 10.1111/1365-2745.13149
   Chiba Sho, 2020, Journal of the Japanese Forest Society, V102, P108, DOI 10.4005/jjfs.102.108
   Chytry M, 2019, J VEG SCI, V30, P1, DOI 10.1111/jvs.12697
   Faliñski JB, 2003, COMMUNITY ECOL, V4, P107, DOI 10.1556/ComEc.4.2003.1.15
   Forestry Agency Japan, 2019, government report
   Fujimura T, 1994, JOURNAL OF JAPANESE, V57, P211, DOI [10.5632/jila1934.57.5_211, DOI 10.5632/JILA1934.57.5_211]
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2022-Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P197, DOI [10.1017/9781009325844.004, DOI 10.1017/9781009325844.004, DOI 10.1017/9781009325844.004.198]
   Iwabuchi T., 1999, Transition of Hakkoda - exploring the history of mountains and people through historical documents - Aomori city centennial commemoration
   Japan Meteorological Agency, 2023, Historical weather data search
   Kapfer J, 2021, J VEG SCI, V32, DOI 10.1111/jvs.12854
   Kapfer J, 2017, APPL VEG SCI, V20, P164, DOI 10.1111/avsc.12269
   Kitamura K, 2015, TREE GENET GENOMES, V11, DOI 10.1007/s11295-015-0857-y
   Kurokawa H., 2014, Glob. Environ. Res, V19, P47
   Masuya Y., 2018, Outbreak of bark beetle (Polygraphus proximus)
   Matsui T, 2004, J VEG SCI, V15, P57, DOI 10.1658/1100-9233(2004)015[0057:CCODOF]2.0.CO;2
   Matsui T, 2018, ECOL RES, V33, P289, DOI 10.1007/s11284-018-1576-2
   Matsushita K., 2015, Japanese forestation policies during the 20 Years following world war II, InTech eBooks, DOI [10.5772/61268, DOI 10.5772/61268]
   Moret P, 2019, P NATL ACAD SCI USA, V116, P12889, DOI 10.1073/pnas.1904585116
   Mt Hakkoda., 1935, Topographic map 1:50,000
   Müllerová J, 2015, FOREST ECOL MANAG, V343, P88, DOI 10.1016/j.foreco.2015.02.003
   NAKASHIZUKA T, 1982, Japanese Journal of Ecology, V32, P473
   Niiyama Kaoru, 2020, Bulletin of the Forestry and Forest Products Research Institute, V19, P275
   Ohchi J., 2009, Jpn. J. For. Plann, V42, P15, DOI [10.20659/jjfp.42.1_15, DOI 10.20659/JJFP.42.1_15]
   Pedrotti F., 2013, Plant and vegetation mapping. Geobotany studies, DOI [10.1007/978-3-642-30235-0_6, DOI 10.1007/978-3-642-30235-0_6]
   Salinitro M, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-46005-1
   Sasse J., 1998, The forests of Japan, p75pp
   Settele J, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P271
   Shibata Mitsue, 2023, Bulletin of the Forestry and Forest Products Research Institute, V22, P223, DOI 10.20756/ffpri.22.4_223
   Sittaro F, 2017, GLOBAL CHANGE BIOL, V23, P3292, DOI 10.1111/gcb.13622
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Tanimoto T., 1993, Jpn. J. For. Environ, V35, P211, DOI [10.18922/jjfe.35.1_42, DOI 10.18922/JJFE.35.1_42]
   Team RC, 2021, R LANGUAGE ENV STAT
   Tsuchihashi Y, 2023, PLANT ECOL, V224, P965, DOI 10.1007/s11258-023-01351-z
   Tsuji Seiji, 1992, Japanese Journal of Ecology (Sendai), V42, P125
   Winkler K, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22702-2
   Yagihashi Tsutomu, 2003, Japanese Journal of Ecology (Otsu), V53, P85
   Yonekura K., 2003, Y-List
   Yoshii Y., 1940, Ecol. Rev, V6, P25
   Yoshii Y., 1940, Ecol. Rev, V6, P125
NR 42
TC 0
Z9 0
U1 1
U2 3
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-665X
J9 FRONT ENV SCI-SWITZ
JI Front. Environ. Sci.
PD MAR 13
PY 2024
VL 12
AR 1306062
DI 10.3389/fenvs.2024.1306062
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA MA4M5
UT WOS:001190888000001
OA gold
DA 2025-01-10
ER

PT J
AU Bärmann, L
   Kaufmann, S
   Weimann, S
   Hauck, M
AF Barmann, Lukas
   Kaufmann, Stefan
   Weimann, Sophie
   Hauck, Markus
TI Future forests and biodiversity: Effects of Douglas fir introduction
   into temperate beech forests on plant diversity
SO FOREST ECOLOGY AND MANAGEMENT
LA English
DT Article
DE Climate change adaptation; Temperate forests; Vascular plants; Exotic
   tree species; Pseudotsuga menziesii; Beech forest; Central Europe
ID LEAF-AREA INDEX; MENZIESII MIRB. FRANCO; EUROPEAN BEECH;
   PSEUDOTSUGA-MENZIESII; SPECIES-DIVERSITY; MIXED STANDS; VASCULAR PLANT;
   NORWAY SPRUCE; SOIL ACIDITY; MANAGEMENT
AB Introduction of drought-tolerant exotic tree species is seen as an important adaptation measure of forest management to climate change in Central Europe. Douglas fir (Pseudotsuga menziesii) is particularly favored in this context, because it is adapted to summer droughts due to the climate in its natural distribution range in temperate western North America and it is also fast-growing and the wood is readily marketable. In Germany, there are plans to grow Douglas fir on a large scale in mixed forests with other tree species on acidic soils. Potential ecological consequences have not yet been sufficiently scrutinized. Here, we analyze effects of Douglas fir introduction into forests of European beech (Fagus sylvatica), which would naturally predominate Central Europe's forests. We analyzed vascular plant diversity and species composition of the ground vegetation in a gradient with increasing Douglas fir canopy fraction that ranged from pure beech (0% Douglas fir) via mixed stands (25%, 50%, 75% Douglas fir) to pure (100%) Douglas fir forest. Species richness, Shannon diversity, and Simpson diversity increased with increasing Douglas fir canopy fraction. However, this increase was primarily driven by an increase of nitrogen-tolerant disturbance indicators, whereas the share of forest species that were predominant in pure beech forests decreased. Beech forest species declined gradually with increasing Douglas fir canopy fraction, but these declining species were fewer than the number of species increasing due to Douglas fir introduction. Cover of similar to 30% of species remained constant when Douglas fir was introduced. Strong changes in the ground vegetation were observed at Douglas fir canopy fractions > 40 - 50% and the original character of the ground vegetation was completely lost beyond a threshold of 75%. Therefore, we discourage from high Douglas fir proportions beyond these thresholds in production forests and from any introduction of Douglas fir where nature conservation is a priority.
C1 [Barmann, Lukas; Kaufmann, Stefan; Weimann, Sophie; Hauck, Markus] Univ Freiburg, Fac Environm & Nat Resources, Appl Vegetat Ecol, Tennenbacher Str 4, Freiburg, Germany.
C3 University of Freiburg
RP Kaufmann, S (corresponding author), Univ Freiburg, Fac Environm & Nat Resources, Appl Vegetat Ecol, Tennenbacher Str 4, Freiburg, Germany.
EM stefan.kaufmann@ecology.uni-freiburg.de
RI Kaufmann, Stefan/I-5454-2014
OI Barmann, Lukas/0000-0003-3361-5100; Hauck, Markus/0000-0002-8218-8400
FU Federal Ministry of Food and Agriculture (BMEL); Federal Ministry of
   Environment, Nature Conservation and Nuclear Safety (BMU);
   Waldklimafonds [2219WK14X4]
FX Waldklimafonds. Grant/Award Number: 2219WK14X4 (BioDiv) . Federal
   Ministry of Food and Agriculture (BMEL) ; Federal Ministry of
   Environment, Nature Conservation and Nuclear Safety (BMU) .
CR [Anonymous], 1992, Scripta Geobotanica
   [Anonymous], 2013, Potentielle Naturliche Vegetation von Baden- Wurttemberg
   Augusto L, 2003, ANN FOREST SCI, V60, P823, DOI 10.1051/forest:2003077
   Baker ME, 2010, METHODS ECOL EVOL, V1, P25, DOI 10.1111/j.2041-210X.2009.00007.x
   Barclay HJ, 2000, FOREST ECOL MANAG, V132, P121, DOI 10.1016/S0378-1127(99)00222-4
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Bauhus Jurgen, 2022, Natur und Landschaft, V97, P318, DOI 10.19217/NuL2022-07-01
   Bequet R, 2012, EUR J FOREST RES, V131, P283, DOI 10.1007/s10342-011-0500-x
   BMEL, 2014, Der Wald in Deutschland
   Boch S, 2013, BASIC APPL ECOL, V14, P496, DOI 10.1016/j.baae.2013.06.001
   Brunet Jorg, 2010, Ecological Bulletins, V53, P77
   Budde S, 2006, Auswirkungen des Douglasienanbaus auf die Bodenvegetation im nordwestdeutschen Tiefland
   Buée M, 2005, MYCORRHIZA, V15, P235, DOI 10.1007/s00572-004-0313-6
   Burton JI, 2013, ECOL APPL, V23, P1297, DOI 10.1890/12-1472.1
   Chai YF, 2016, OECOLOGIA, V180, P771, DOI 10.1007/s00442-015-3483-3
   Chao A, 2014, ECOL MONOGR, V84, P45, DOI 10.1890/13-0133.1
   CLARKE KR, 1993, AUST J ECOL, V18, P117, DOI 10.1111/j.1442-9993.1993.tb00438.x
   Cornwell WK, 2003, OIKOS, V100, P417, DOI 10.1034/j.1600-0706.2003.11697.x
   Cremer M, 2017, PLANT SOIL, V415, P393, DOI 10.1007/s11104-017-3177-1
   Cremer M, 2016, FOREST ECOL MANAG, V367, P30, DOI 10.1016/j.foreco.2016.02.020
   Dawud SM, 2017, FORESTS, V8, DOI 10.3390/f8040095
   Depauw L, 2021, APPL VEG SCI, V24, DOI 10.1111/avsc.12532
   Dittrich S, 2013, J VEG SCI, V24, P675, DOI 10.1111/j.1654-1103.2012.01490.x
   Dormann CF, 2007, ECOGRAPHY, V30, P609, DOI 10.1111/j.2007.0906-7590.05171.x
   Dormann CF, 2020, BMC ECOL, V20, DOI 10.1186/s12898-020-00311-9
   Duguid MC, 2013, FOREST ECOL MANAG, V303, P81, DOI 10.1016/j.foreco.2013.04.009
   Dyderski MK, 2018, GLOBAL CHANGE BIOL, V24, P1150, DOI 10.1111/gcb.13925
   Eberhard BR, 2021, FORESTS, V12, DOI 10.3390/f12081040
   Eckhart T, 2019, ANN FOREST SCI, V76, DOI 10.1007/s13595-019-0805-3
   Floren A, 2014, FOREST ECOL MANAG, V323, P57, DOI 10.1016/j.foreco.2014.03.028
   Foltran EC, 2023, SOIL RES, V61, P647, DOI 10.1071/SR22218
   Glatthorn J, 2017, FOREST ECOL MANAG, V389, P76, DOI 10.1016/j.foreco.2016.12.025
   Grime J. P., 1979, Plant strategies and vegetation processes.
   Halvorsen, 2014, SOMMERFELTIA, V37, P1, DOI [10.2478/som-2014-0001, DOI 10.2478/SOM-2014-0001]
   Hauck M, 2020, KLIMAWANDEL UND VEGETATION-EINE GLOBALE UBERSICHT, P1, DOI 10.1007/978-3-662-59791-0
   Heinrichs S, 2022, DIVERSITY-BASEL, V14, DOI 10.3390/d14100795
   Helbach J, 2022, ECOL EVOL, V12, DOI 10.1002/ece3.8534
   HILL MO, 1980, VEGETATIO, V42, P47, DOI 10.1007/BF00048870
   Hrivnák R, 2014, FOLIA GEOBOT, V49, P425, DOI 10.1007/s12224-013-9174-0
   Hsieh TC, 2016, METHODS ECOL EVOL, V7, P1451, DOI 10.1111/2041-210X.12613
   Ibisch P., 2022, Natur. und Landschaft, V97, P325
   IPCC, 2022, Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
   Jager E.J., 2017, ROTHMALER EXKURSIONS
   Kaufmann S, 2018, J ECOL, V106, P2421, DOI 10.1111/1365-2745.12981
   Kaufmann S, 2017, FOREST ECOL MANAG, V400, P58, DOI 10.1016/j.foreco.2017.05.043
   Kermavnar J, 2022, PLANT ECOL, V223, P229, DOI 10.1007/s11258-021-01203-8
   Kostic O, 2016, ARCH BIOL SCI, V68, P753, DOI 10.2298/ABS150911032K
   Kownatzki D, 2011, LANDBAUFORSCH-VTI AG, V344, P1
   Krah FS, 2018, J ECOL, V106, P1428, DOI 10.1111/1365-2745.12939
   Kriegel P, 2021, BIODIVERS CONSERV, V30, P1479, DOI 10.1007/s10531-021-02155-1
   Lavender D.P., 2014, Douglas-Fir: The Genus Pseudotsuga, DOI DOI 10.1073/PNAS.1031755100
   LEUSCHNER C, 2017, ECOLOGY CENTRAL EURO, DOI 10.1007/978-3-319-43042-3
   Leuschner C, 2006, PLANT ECOL, V186, P247, DOI 10.1007/s11258-006-9127-2
   Leuschner C, 2020, PERSPECT PLANT ECOL, V47, DOI 10.1016/j.ppees.2020.125576
   Leuschner C, 2009, J VEG SCI, V20, P288, DOI 10.1111/j.1654-1103.2009.05641.x
   Malchair S, 2009, SOIL BIOL BIOCHEM, V41, P831, DOI 10.1016/j.soilbio.2009.02.004
   Nadezhdina N, 2014, J HYDROL HYDROMECH, V62, P1, DOI 10.2478/johh-2014-0001
   Neff F, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abf3985
   Nicolescu V. -N., 2019, Douglas -Fir - an option for Europe. What Science Can Tell Us, V9, P33
   Norris C, 2012, J APPL ECOL, V49, P562, DOI 10.1111/j.1365-2664.2011.02084.x
   Podrazsky V., 2014, Journal of Forest Science (Prague), V60, P263, DOI 10.17221/49/2014-JFS
   Schenker N, 2001, AM STAT, V55, P182, DOI 10.1198/000313001317097960
   Schmid M, 2014, EUR J FOREST RES, V133, P13, DOI 10.1007/s10342-013-0745-7
   Schmidt M, 2011, BfN-Skripten, V299, P1
   Schonwiese C.-D., 2008, Klima-Trendatlas Deutschland 1901-2000
   Schütz JP, 2013, FOREST ECOL MANAG, V303, P175, DOI 10.1016/j.foreco.2013.04.015
   Schuldt B, 2020, BASIC APPL ECOL, V45, P86, DOI 10.1016/j.baae.2020.04.003
   Sergent AS, 2014, ANN FOREST SCI, V71, P697, DOI 10.1007/s13595-012-0220-5
   Thom D, 2020, AGR FOREST METEOROL, V291, DOI 10.1016/j.agrformet.2020.108066
   Thomas F. M., 2015, Forstarchiv, V86, P83
   Thomas FM, 2022, FOREST ECOL MANAG, V506, DOI 10.1016/j.foreco.2021.119956
   Thomas KD, 2000, CAN J FOREST RES, V30, P1698, DOI 10.1139/cjfr-30-11-1698
   Thorn S, 2019, SCIENCE, V365, P1388, DOI 10.1126/science.aaz3476
   Thurm EA, 2016, FOREST ECOL MANAG, V376, P205, DOI 10.1016/j.foreco.2016.06.020
   Thurm EA, 2017, TREES-STRUCT FUNCT, V31, P349, DOI 10.1007/s00468-016-1512-4
   Unterseher M, 2013, FUNGAL DIVERS, V60, P43, DOI 10.1007/s13225-013-0222-0
   van Loo M, 2019, Douglas -Fir - an option for Europe. What Science Can Tell Us
   Vesterdal L, 1998, CAN J FOREST RES, V28, P1636, DOI 10.1139/cjfr-28-11-1636
   Weiskittel AR, 2007, ANN FOREST SCI, V64, P121, DOI 10.1051/forest:2006096
   Willner W, 2017, APPL VEG SCI, V20, P494, DOI 10.1111/avsc.12299
   Wohlgemuth T., 2019, Douglas-Fir-An Option Eur, P57
   Zuur AF, 2010, METHODS ECOL EVOL, V1, P3, DOI 10.1111/j.2041-210X.2009.00001.x
NR 82
TC 5
Z9 5
U1 1
U2 13
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0378-1127
EI 1872-7042
J9 FOREST ECOL MANAG
JI For. Ecol. Manage.
PD OCT 1
PY 2023
VL 545
AR 121286
DI 10.1016/j.foreco.2023.121286
EA JUL 2023
PG 11
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA FE1D5
UT WOS:001143985300001
DA 2025-01-10
ER

PT J
AU Basiru, AO
   Oladoye, AO
   Adekoya, OO
   Akomolede, LA
   Oeba, VO
   Awodutire, OO
   Charity, F
   Abodunrin, EK
AF Basiru, Adeniyi Okanlawon
   Oladoye, Abiodun Olusegun
   Adekoya, Olubusayo Omotola
   Akomolede, Lucas Aderemi
   Oeba, Vincent Onguso
   Awodutire, Opeyemi Oluwaseun
   Charity, Fredrick
   Abodunrin, Emmanuel Kolawole
TI Livelihood Vulnerability Index: Gender Dimension to Climate Change and
   Variability in REDD
SO LAND
LA English
DT Article
DE livelihood; exposure; sensitivity; adaptive; capacity; index
ID ADAPTATION
AB Vulnerability to climate change and variability impacts has been identified as a major cog in the wheel of both livelihood and resilience, particularly in vulnerable groups in rural areas. This study aims to assess genders' vulnerability dimension to climate change and variability in REDD + (Reducing Emission from Deforestation and Forest Degradation+) piloted site/clusters, Cross River State, Nigeria. Data were proportionately collected from selected 200 respondents on gender disaggregated level using questionnaires. The assessment adopted the sustainable livelihood approach (livelihood vulnerability index) and compared the results with the IPCC vulnerability standard of exposure, sensitivity and adaptive capacity weighted mean. The results revealed a significant difference in the vulnerability dimension of both women and men disaggregated levels (LVI: men 0.509, women 0.618). The women category was more vulnerable to six out of seven major components of LVI assessed: (livelihood strategies (0.646), social networks (0.364), water (0.559), health (0.379), food and nutrition (0.507), and natural hazards and climate variability (0.482), while men only vulnerable to socio-demographic major component (0.346). Vulnerability indices also showed women to be more exposed (0.482), and sensitive (0.489) with the least adaptive capacities (0.462) to the climate change and variability impacts. Overall, on the IPCC-LVI index, women are more vulnerable (0.0098) to climate change and variability impacts than men (-0.0093). The study recommends that the women's category resilience and adaptive capacity should be empowered in adaptation projects in climate change such as REDD + (Reducing Emissions from Deforestation and Forest Degradation+) to reduce their vulnerability to impacts of climate change and variability in the context of exposure, sensitivity, and adaptive capacities. This will be instrumental in formulating policies to address the specific needs of gender categories in reducing vulnerability to climate change and variability. This pragmatic approach may be used to monitor gender vulnerability dimension, and livelihood enhancement and evaluate potential climate change adaptation programs. Additionally, the introduction of IPCC-LVI as a baseline instrument will enhance information on gender resilience and adaptive capacity for policy effectiveness in a data-scarce region particularly Africa.
C1 [Basiru, Adeniyi Okanlawon; Oladoye, Abiodun Olusegun] Fed Univ Agr, Dept Forestry & Wildlife Management, Coll Environm Resources Management, PMB 2240, Abeokuta, Ogun State, Nigeria.
   [Adekoya, Olubusayo Omotola; Akomolede, Lucas Aderemi] Forestry Res Inst Nigeria, PMB 5054, Ibadan, Oyo State, Nigeria.
   [Oeba, Vincent Onguso] Kenya Forestry Res Inst, Climate Change Dept, Muguga Nairobi Nakuru Highway,POB 20412-00200, Nairobi, Nairobi County, Kenya.
   [Awodutire, Opeyemi Oluwaseun] Oyo State Coll Agr, Dept Forestry Technol, PMB 10, Igboora, Oyo State, Kenya.
   [Charity, Fredrick] Univ Port Harcourt, Dept Forestry & Wildlife Management, Fac Agr, East West Rd,PMB 5323, Choba, River State, Nigeria.
   [Abodunrin, Emmanuel Kolawole] Fed Coll Forestry, Dept Forestry Technol, PMB 5054, Ibadan, Oyo State, Nigeria.
C3 University of Agriculture, Abeokuta; University of Port Harcourt
RP Basiru, AO (corresponding author), Fed Univ Agr, Dept Forestry & Wildlife Management, Coll Environm Resources Management, PMB 2240, Abeokuta, Ogun State, Nigeria.
EM okanlawon.basiru@students.jkuat.ac.ke
RI Basiru, Adeniyi/HLW-2584-2023
OI BASIRU, ADENIYI OKANLAWON/0000-0001-5399-8028; OLUSEGUN,
   OLADOYE/0000-0002-5261-0455
FU UK Research and Innovation (UKRI) [ES/P011306]; African Forest Forum
   (AFF); World Agroforestry Centre (ICRAF), Nairobi, Kenya; GCRF
   [ES/P011306/1] Funding Source: UKRI
FX This research was funded by the UK Research and Innovation (UKRI)
   through the Global Challenges Research Fund (GCRF) program, Grant Ref:
   ES/P011306/under the project Social and Environmental Trade-offs in
   African Agriculture (SENTINEL) led by the International Institute for
   Environment and Development (IIED) in part implemented by the Regional
   Universities Forum for Capacity Building in Agriculture (RUFORUM) and
   African Forest Forum (AFF), World Agroforestry Centre (ICRAF), Nairobi,
   Kenya.
CR Abate Nahusenay, 2020, Journal of Ecology and the Natural Environment, V12, P104, DOI 10.5897/JENE2018.0716
   Adekunle V.A.J., 2011, FINAL PROJ REP, V1, P1
   Adger W. N., 1999, Mitig Adapt Strateg Glob Change, V4, P253, DOI [10.1023/A:1009601904210, DOI 10.1023/A:1009601904210]
   Adu D. T., 2018, Kasetsart Journal of Social Sciences, V39, P22, DOI 10.1016/j.kjss.2017.06.009
   Agwu J., 2009, Gender and climate change in Nigeria
   Alhassan S.I., 2019, Climate change in sub-Saharan Africa: The vulnerability and adaptation of food supply chain actors, P27
   Alhassan SI, 2019, INT J CLIM CHANG STR, V11, P195, DOI 10.1108/IJCCSM-10-2016-0156
   [Anonymous], 2007, Climate Change 2007: The Physical Science Basis
   [Anonymous], 1992, Institute of Development Studies Discussion Paper No. 296.
   [Anonymous], 2007, HUMAN DEV REPORTS
   [Anonymous], 2007, DRAFT REPORT MILLENN
   [Anonymous], 1987, Introduction to Biostatistics
   [Anonymous], 2012, NIG REDD READ PROGR
   Arora-Jonsson S, 2011, GLOBAL ENVIRON CHANG, V21, P744, DOI 10.1016/j.gloenvcha.2011.01.005
   Asare-Kyei DK, 2015, INT J DISAST RISK RE, V11, P13, DOI 10.1016/j.ijdrr.2014.11.001
   Balikoowa K, 2019, CLIM DEV, V11, P839, DOI 10.1080/17565529.2019.1580555
   Basiru A.O., 2018, APPL SOC SCI INT RES, V1, P56
   Basiru A O., 2022, Journal of Agriculture, Science and Technology, V21, P66, DOI [10.4314/jagst.v21i2.6, DOI 10.4314/JAGST.V21I2.6]
   Bhattacharjee K, 2018, INT J DISAST RISK RE, V31, P758, DOI 10.1016/j.ijdrr.2018.07.017
   Boko M, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P433
   Brody A., 2008, GENDER CLIMATE CHANG
   Brown HCP, 2011, INT FOREST REV, V13, P163, DOI 10.1505/146554811797406651
   Cochran W.G., 1977, Sampling techniques, V3rd ed.
   Dankelman Irene., Gender and Climate Change: An Introduction
   Dixon R. K., 2003, Mitigation and Adaptation Strategies for Global Change, V8, P93, DOI 10.1023/A:1026001626076
   Edet AE, 1998, HYDROGEOL J, V6, P394, DOI 10.1007/s100400050162
   Ekpo F. E., 2014, Universal Journal of Environmental Research and Technology, V4, P46
   Federal Ministry of Health of Nigeria, 2015, NAT YOUTH POL
   Gerlitz JY, 2017, CLIM DEV, V9, P124, DOI 10.1080/17565529.2016.1145099
   Gunda R, 2017, AFR J PRIM HEALTH CA, V9, DOI 10.4102/phcfm.v9i1.1317
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Hertel TW, 2010, APPL ECON PERSPECT P, V32, P355, DOI 10.1093/aepp/ppq016
   Ishaya S., 2008, Journal of Geography and Regional Planning, V1, P138, DOI DOI 10.5897/JGRP.9000080
   Isyaku U., 2017, THESIS U LEICESTER
   Kakota T, 2011, CLIM DEV, V3, P298, DOI 10.1080/17565529.2011.627419
   Kanmiki EW, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0211365
   Phan LT, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11051257
   Milazzo A, 2017, DEMOGRAPHY, V54, P1119, DOI 10.1007/s13524-017-0561-7
   Naab FZ, 2019, CLIM SERV, V13, P24, DOI 10.1016/j.cliser.2019.01.007
   National Population Commission Nigeria, 2020, US
   NEEDS, 2010, NAT ENV EC DEV STUD, P45
   Nellemann C., 2011, Women at the frontline of climate change: Gender risks and hopes. A Rapid Response Assessment
   Ngigi MW, 2017, ECOL ECON, V138, P99, DOI 10.1016/j.ecolecon.2017.03.019
   Huong NTL, 2019, HUM ECOL RISK ASSESS, V25, P1157, DOI 10.1080/10807039.2018.1460801
   Nong HTT, 2020, INT J SOC ECON, V47, P953, DOI 10.1108/IJSE-09-2019-0534
   Nounkeu CD, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17134848
   Olsen KH, 2006, CLIM POLICY, V5, P599, DOI 10.1080/14693062.2006.9685581
   Onojeghuo A.O., 2016, IFE J SCI, V18, P213
   Onyekuru A. N., 2014, African Journal of Agricultural Research, V9, P1819
   Otto IM, 2017, REG ENVIRON CHANGE, V17, P1651, DOI 10.1007/s10113-017-1105-9
   Oyebo M., 2010, A preliminary assessment of the context for REDD in Nigeria?, commissioned by the Federal Ministry of Environment, the Cross River State's Forestry
   Pachauri RK, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, pVII
   Padmaja R, 2020, T ASABE, V63, P153, DOI 10.13031/trans.13568
   Pandey R, 2017, ECOL INDIC, V79, P338, DOI 10.1016/j.ecolind.2017.03.047
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Phartiyal M., 2021, ENVIS B HIMAL ECOL, V29, P78
   Radonic L, 2021, WATER ALTERN, V14, P60
   Reid H., 2007, The economic impact of climate change in Namibia: How climate change will affect the contribution of Namibia's natural resources to its economy
   Ruxton G.D, 2006, UNEQUAL VARIANCE TES
   Ruxton GD, 2006, BEHAV ECOL, V17, P688, DOI 10.1093/beheco/ark016
   Sullivan C, 2006, P INT RIVER S
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   UNDRR, 2022, UN OFF DIS RISK RED
   Tran VT, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13137106
   Wrigley-Asante C, 2019, AFR GEOGR REV, V38, P126, DOI 10.1080/19376812.2017.1340168
   Ylipaa J, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11102805
   Yobo CM, 2020, INT FOREST REV, V22, P339, DOI 10.1505/146554820830405672
NR 67
TC 4
Z9 4
U1 2
U2 19
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD AUG
PY 2022
VL 11
IS 8
AR 1240
DI 10.3390/land11081240
PG 34
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 4B1IJ
UT WOS:000845540200001
OA gold
DA 2025-01-10
ER

PT J
AU Vijhani, A
   Sinha, VSP
   Vishwakarma, CA
   Singh, P
   Sharma, SK
AF Vijhani, Ayushi
   Sinha, Vinay Shankar Prasad
   Vishwakarma, Chandrashekhar Azad
   Singh, Prashant
   Sharma, Sudhir Kumar
TI Assessment of diminishing discharge of springs in Central Himalayan
   region, India
SO HYDROLOGICAL PROCESSES
LA English
DT Article
DE GWR; Himalayan spring; MIKE hydro; SWAT; Ungauged watershed
ID GROUNDWATER POTENTIAL ZONES; SURFACE WATER INTERACTIONS; CLIMATE-CHANGE
   ADAPTATION; LAND-USE CHANGE; UNGAUGED CATCHMENTS; INTEGRATED APPROACH;
   WESTERN-HIMALAYAS; MODEL PARAMETERS; TREND ANALYSIS; MIKE SHE
AB Uttarakhand is witnessing a drastic decrease in spring discharge which leads to scarcity of drinking water for Himalayan inhabitants. This study uses a novel approach to assess the surface-subsurface interaction of water, pivotal for estimating the status of spring discharge. Hydrological modelling has been used to quantify the diminishing discharge of spring and their associated factors, including changes in land practises and precipitation patterns. The coupling of the soil water assessment tool (SWAT) and MIKE hydro NAM model was proposed in the study to assess the decreasing discharge for an ungauged watershed. The model performance evaluated between the SWAT and the MIKE hydro NAM model indicated a very good index of agreement (d = 0.81). Field-based spring discharge investigations were conducted in almost all watersheds in the study area. The MIKE hydro NAM model showed a good index of agreement (d = 0.79) with the observed spring discharge. Further, the geographically weighted regression (GWR) technique was applied over 17 driving factors based on hydrological parameters including topography, structural geology, land use/land cover and future annual precipitation (till 2030) under the RCP 4.5 scenario to understand the status of diminishing discharge of springs. The accuracy between the observed spring discharge and the GWR indicated a good index of agreement (d = 0.86). The results indicate that annual spring discharges will be significantly reduced up to 50% from 1975 to near future (2030), posing a threat to the drinking water supply. The proposed approach is replicable and scalable for ungauged river systems of the Himalayas. The study demonstrates the methods such as trend analysis of precipitation behaviour, land use change dynamics using remote sensing techniques, structural geological investigation through field measurements and hydrodynamic modelling are important for understanding surface-subsurface interaction. The findings of the study help to identify the critical recharge zones for implementing the spring revival and rejuvenation programmes.
C1 [Vijhani, Ayushi; Sinha, Vinay Shankar Prasad] TERI Sch Adv Studies, Dept Nat & Appl Sci, 10 Inst Area, New Delhi 110070, India.
   [Vishwakarma, Chandrashekhar Azad] TERI Sch Adv Studies, Dept Nat & Appl Sci, MoEF&CC Funded Project 2, New Delhi, India.
   [Singh, Prashant] DAV Postgrad Coll, Dept Chem, Dehra Dun, Uttarakhand, India.
   [Sharma, Sudhir Kumar] Govt Uttarakhand, Haldwani, India.
C3 TERI University; TERI University
RP Sinha, VSP (corresponding author), TERI Sch Adv Studies, Dept Nat & Appl Sci, 10 Inst Area, New Delhi 110070, India.
EM sinha_vinay@yahoo.co.uk
RI Singh, Pramod/A-8655-2013
OI Sinha, Vinay/0000-0001-8387-8625; Vijhani, Ayushi/0000-0002-0028-5451
FU Ministry of Environment, Forest and Climate Change
FX Ministry of Environment, Forest and Climate Change
CR Abdullah A., 2010, Electronic Journal of Geotechnical Engineering, V15, P949
   Abu El-Nasr A, 2005, HYDROL PROCESS, V19, P573, DOI 10.1002/hyp.5610
   Agarwal A, 2012, MT RES DEV, V32, P446, DOI 10.1659/MRD-JOURNAL-D-12-00054.1
   Akinlalu A. A., 2017, NRIAG Journal of Astronomy and Geophysics, V6, P184, DOI 10.1016/j.nrjag.2017.03.001
   Althoff D, 2021, J HYDROL, V600, DOI 10.1016/j.jhydrol.2021.126674
   Amin MGM, 2017, AGR WATER MANAGE, V180, P212, DOI 10.1016/j.agwat.2016.07.011
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   Arnold JG, 2005, HYDROL PROCESS, V19, P563, DOI 10.1002/hyp.5611
   Asima Jillani Asima Jillani, 2017, Environment and Ecology, V35, P2602
   Bagchi D, 2021, REMOTE SENS APPL, V23, DOI 10.1016/j.rsase.2021.100588
   Balamurugan G, 2017, J KING SAUD UNIV SCI, V29, P333, DOI 10.1016/j.jksus.2016.08.003
   Betrie GD, 2011, HYDROL EARTH SYST SC, V15, P807, DOI 10.5194/hess-15-807-2011
   Bhadwal S, 2019, ENVIRON DEV, V31, P68, DOI 10.1016/j.envdev.2019.04.008
   Bonekamp PNJ, 2018, J HYDROMETEOROL, V19, P1565, DOI 10.1175/JHM-D-17-0212.1
   Bonell M, 2010, J HYDROL, V391, P49, DOI 10.1016/j.jhydrol.2010.07.004
   Boots B, 2003, INT J GEOGR INF SCI, V17, P717
   Boskidis I, 2012, WATER RESOUR MANAG, V26, P3023, DOI 10.1007/s11269-012-0064-7
   Brutsaert W., 2005, HYDROLOGY INTRO, P618, DOI [10.1017/CBO9780511808470, DOI 10.1017/CBO9780511808470]
   Bulygina N, 2009, HYDROL EARTH SYST SC, V13, P893, DOI 10.5194/hess-13-893-2009
   Cao GL, 2014, HYDROL PROCESS, V28, P1797, DOI 10.1002/hyp.9732
   Caswell Hal, 2001, pi
   Chapagain PS, 2019, ENVIRON DEV SUSTAIN, V21, P263, DOI 10.1007/s10668-017-0036-4
   Chaubey I, 2010, J SOIL WATER CONSERV, V65, P424, DOI 10.2489/jswc.65.6.424
   Chen Q, 2016, SCI TOTAL ENVIRON, V572, P450, DOI 10.1016/j.scitotenv.2016.08.052
   Chinnasamy P., 2016, IWMI Working Paper
   Collier E, 2013, CRYOSPHERE, V7, P779, DOI 10.5194/tc-7-779-2013
   Collier E, 2015, J GEOPHYS RES-ATMOS, V120, P9882, DOI 10.1002/2015JD023266
   Coustau M, 2015, J HYDROL, V525, P781, DOI 10.1016/j.jhydrol.2015.04.022
   Dahal P, 2020, ENVIRON RES, V185, DOI 10.1016/j.envres.2020.109430
   Dar IA, 2010, J HYDROL, V394, P285, DOI 10.1016/j.jhydrol.2010.08.022
   Debele B, 2008, ENVIRON MODEL ASSESS, V13, P135, DOI 10.1007/s10666-006-9075-1
   Dessu SB, 2012, HYDROL PROCESS, V26, P4038, DOI 10.1002/hyp.9205
   Dhami B, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-017-7210-8
   DHI, 2016, MIKE HYDRORIVER US G
   Diodato N, 2014, WATER RESOUR MANAG, V28, P969, DOI 10.1007/s11269-014-0527-0
   Doummar J, 2012, J HYDROL, V426, P112, DOI 10.1016/j.jhydrol.2012.01.021
   Faiz MA, 2018, J HYDROL, V565, P599, DOI 10.1016/j.jhydrol.2018.08.057
   Fan YH, 2013, J HYDROL, V504, P57, DOI 10.1016/j.jhydrol.2013.09.023
   Fernandes AJ, 2001, HYDROGEOL J, V9, P151, DOI 10.1007/s100400000103
   Feth J.H., 1964, Groundwater, V2, P14
   Fiorillo F, 2010, HYDROGEOL J, V18, P1881, DOI 10.1007/s10040-010-0666-1
   Fiorillo F, 2009, J HYDROL, V373, P290, DOI 10.1016/j.jhydrol.2009.04.034
   Fleckenstein JH, 2010, ADV WATER RESOUR, V33, P1291, DOI 10.1016/j.advwatres.2010.09.011
   Ford D., 2007, KARST HYDROGEOLOGY G, DOI DOI 10.1002/9781118684986
   Fotheringham AS, 1996, INT J GEOGR INF SYST, V10, P605, DOI 10.1080/026937996137909
   Gao JB, 2011, APPL GEOGR, V31, P292, DOI 10.1016/j.apgeog.2010.06.003
   Gardner WP, 2010, J HYDROL, V383, P209, DOI 10.1016/j.jhydrol.2009.12.037
   Gassman PW, 2007, T ASABE, V50, P1211, DOI 10.13031/2013.23637
   Ghaffari G, 2010, HYDROL PROCESS, V24, P892, DOI 10.1002/hyp.7530
   Ghimire CP, 2012, J HYDROL, V475, P270, DOI 10.1016/j.jhydrol.2012.09.051
   Ghosh S, 2009, ATMOS SCI LETT, V10, P285, DOI 10.1002/asl.235
   Githui F, 2012, HYDROL PROCESS, V26, P1379, DOI 10.1002/hyp.8274
   GoU (Government of Uttarakhand), 2014, STAT ACT PLAN CLIM C
   Granata F, 2018, GEOFLUIDS, DOI 10.1155/2018/8328167
   Greenbaum D., 1992, Geological Society, London, Special Publications, V66, P77, DOI [DOI 10.1144/GSL.SP.1992.066.01.04, 10.1144/GSL.SP.1992.066.01.04]
   Gurung A, 2019, WATER POLICY, V21, P826, DOI 10.2166/wp.2019.245
   Habets F, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD008548
   Haga H, 2005, WATER RESOUR RES, V41, DOI 10.1029/2005WR004236
   Hajkowicz S, 2007, WATER RESOUR MANAG, V21, P1553, DOI 10.1007/s11269-006-9112-5
   Hu CH, 2008, HYDROL PROCESS, V22, P596, DOI 10.1002/hyp.6625
   Ibrahim-Bathis K, 2016, EGYPT J REMOTE SENS, V19, P223, DOI 10.1016/j.ejrs.2016.06.002
   Jahandideh-Tehrani M, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-019-8049-0
   Jain SK, 2012, CURR SCI INDIA, V102, P37
   Jaiswal RK, 2020, APPL WATER SCI, V10, DOI 10.1007/s13201-019-1122-6
   Janza M, 2010, ENVIRON EARTH SCI, V61, P909, DOI 10.1007/s12665-009-0406-9
   Jasrotia AS, 2021, J HYDROL, V593, DOI 10.1016/j.jhydrol.2020.125887
   Jeelani G, 2017, J HYDROL, V550, P239, DOI 10.1016/j.jhydrol.2017.05.001
   Jha M, 2006, J AM WATER RESOUR AS, V42, P997, DOI 10.1111/j.1752-1688.2006.tb04510.x
   Jiang LG, 2019, REMOTE SENS ENVIRON, V225, P229, DOI 10.1016/j.rse.2019.03.014
   Joshi AK, 2014, J FORESTRY RES, V25, P281, DOI 10.1007/s11676-014-0459-9
   Kahsay Kiflom Degef, 2018, Groundwater for Sustainable Development, V6, P121, DOI 10.1016/j.gsd.2017.12.002
   Kolawole M. S., 2016, J Geosci Geomatics, V4, P42, DOI DOI 10.12691/JGG-4-3-1
   Kollet SJ, 2006, ADV WATER RESOUR, V29, P945, DOI 10.1016/j.advwatres.2005.08.006
   Krause S, 2007, J HYDROL, V347, P404, DOI 10.1016/j.jhydrol.2007.09.028
   Kresic N, 2010, GROUNDWATER HYDROLOGY OF SPRINGS: ENGINEERING, THEORY, MANAGEMENT, AND SUSTAINABILITY, P1
   Krishnan R, 2019, HINDU KUSH HIMALAYA ASSESSMENT: MOUNTAINS, CLIMATE CHANGE, SUSTAINABILITY AND PEOPLE, P57, DOI 10.1007/978-3-319-92288-1_3
   Kumar V, 2010, HYDROLOG SCI J, V55, P484, DOI 10.1080/02626667.2010.481373
   Kumar V, 2018, SUST WAT RESOUR MAN, V4, P539, DOI 10.1007/s40899-017-0138-z
   Kupfer JA, 2007, LANDSCAPE ECOL, V22, P837, DOI 10.1007/s10980-006-9058-2
   Kushwaha A, 2013, WATER RESOUR MANAG, V27, P3005, DOI 10.1007/s11269-013-0329-9
   Lambrakis N, 2000, WATER RESOUR RES, V36, P875, DOI 10.1029/1999WR900353
   Leone G, 2021, STOCH ENV RES RISK A, V35, P345, DOI 10.1007/s00477-020-01908-8
   Ma L, 2016, ECOL ENG, V96, P137, DOI 10.1016/j.ecoleng.2016.01.008
   Macchi M, 2015, CLIM DEV, V7, P414, DOI 10.1080/17565529.2014.966046
   Madsen H, 2002, J HYDROL, V261, P48, DOI 10.1016/S0022-1694(01)00619-9
   Magesh NS, 2012, GEOSCI FRONT, V3, P189, DOI 10.1016/j.gsf.2011.10.007
   Mahamuni K., 2012, GROUNDWATER RESOURCE
   Makungo R, 2010, PHYS CHEM EARTH, V35, P596, DOI 10.1016/j.pce.2010.08.001
   Malcolm R, 2000, GEOL SOC SPEC PUBL, V182, P191, DOI 10.1144/GSL.SP.2000.182.01.18
   Manga M, 1999, J HYDROL, V219, P56, DOI 10.1016/S0022-1694(99)00044-X
   Marklund L., 2007, The impact of hydraulic conductivity on topography driven groundwater flow, P159
   Maussion F, 2011, HYDROL EARTH SYST SC, V15, P1795, DOI 10.5194/hess-15-1795-2011
   McMahon TA, 2013, HYDROL EARTH SYST SC, V17, P1331, DOI 10.5194/hess-17-1331-2013
   Mennis J, 2006, CARTOGR J, V43, P171, DOI 10.1179/000870406X114658
   Miller MP, 2016, WATER RESOUR RES, V52, P3547, DOI 10.1002/2015WR017963
   Mirus BB, 2015, HYDROL PROCESS, V29, P4611, DOI 10.1002/hyp.10592
   Moghaddam DD, 2015, ARAB J GEOSCI, V8, P913, DOI 10.1007/s12517-013-1161-5
   Narain V, 2014, MT RES DEV, V34, P208, DOI 10.1659/MRD-JOURNAL-D-13-00104.1
   Naudiyal N, 2017, J FORESTRY RES, V28, P431, DOI 10.1007/s11676-016-0338-7
   Nazeer M, 2018, J OCEAN U CHINA, V17, P305, DOI 10.1007/s11802-018-3380-6
   NITI-AAYOG, 2018, REPORT WORKING GROUP
   O'Sullivan D, 2003, GEOGR ANAL, V35, P272, DOI 10.1111/j.1538-4632.2003.tb01114.x
   Oh HJ, 2011, J HYDROL, V399, P158, DOI 10.1016/j.jhydrol.2010.12.027
   Pandey R, 2018, ECOL INDIC, V84, P27, DOI 10.1016/j.ecolind.2017.08.021
   Pandit B.H., 2009, J FOREST LIVELIHOOD, V6, P67
   Post DA, 1999, ECOL MODEL, V123, P91, DOI 10.1016/S0304-3800(99)00125-8
   Poudel DD, 2017, MT RES DEV, V37, P35, DOI 10.1659/MRD-JOURNAL-D-16-00039.1
   Prabhu MV, 2015, AQUAT PR, V4, P1265, DOI 10.1016/j.aqpro.2015.02.165
   Pradhan B, 2009, CENT EUR J GEOSCI, V1, P120, DOI 10.2478/v10085-009-0008-5
   Rai S.P., 1998, MANAGEMENT WATER RES, P41
   Rautela P, 2015, INT J DISAST RISK RE, V13, P281, DOI 10.1016/j.ijdrr.2015.07.004
   Samagra R., 2009, P WORLD ENV WATER RE, P1, DOI [10.1061/41036(342)527, DOI 10.1061/41036(342)527]
   Sati VishwambharPrasad., 2005, Journal of Mountain Science, V2, P76, DOI [10.1007/s11629-005-0076-3, DOI 10.1007/S11629-005-0076-3]
   Sati VP., 2013, ENVIS B HIMALAYAN EC, V21, P9
   Seiler KP, 2007, WATER SCI TECHNOL LI, V55, P1
   Senanayake IP, 2016, GEOSCI FRONT, V7, P115, DOI 10.1016/j.gsf.2015.03.002
   Setyorini A, 2017, APPL GEOMAT, V9, P191, DOI 10.1007/s12518-017-0193-z
   Shivhare N, 2018, ENGINEERING-PRC, V4, P643, DOI 10.1016/j.eng.2018.08.012
   Shrestha N., 2020, AM J APPL MATH STAT, V8, P39, DOI DOI 10.12691/AJAMS-8-2-1
   Shrestha S, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-015-5150-8
   SIMPSON B, 1983, J HYDROL, V62, P225, DOI 10.1016/0022-1694(83)90104-X
   Singh P., 2012, Analytical Chemistry Letters, V2, P198, DOI DOI 10.1080/22297928.2000.10648270
   Singh RK, 2020, AIN SHAMS ENG J, V11, P1035, DOI 10.1016/j.asej.2020.01.011
   Singh V, 2020, WATER POLICY, V22, P33, DOI 10.2166/wp.2019.329
   Sisay E, 2017, MODEL EARTH SYST ENV, V3, P693, DOI 10.1007/s40808-017-0328-6
   Soci C, 2016, TELLUS A, V68, DOI 10.3402/tellusa.v68.29879
   Sophocleous MA, 1999, J HYDROL, V214, P179, DOI 10.1016/S0022-1694(98)00289-3
   Sparks AH., 2018, J OPEN SOURCE SOFTW, V3, P1035, DOI DOI 10.21105/JOSS.01035
   Springer AE, 2009, HYDROGEOL J, V17, P83, DOI 10.1007/s10040-008-0341-y
   Sridhar V, 2018, GROUNDWATER, V56, P618, DOI 10.1111/gwat.12610
   Srinivasan R., 1998, International Journal of Water Resources Development, V14, P315, DOI 10.1080/07900629849231
   Tambe S., 2011, Current Science, V101, P165
   Tambe S., 2009, Conceptualizing Strategies to Enhance Rural Water Security in Sikkim, Eastern Himalaya, India, P1
   Tambe S, 2012, MT RES DEV, V32, P62, DOI 10.1659/MRD-JOURNAL-D-11-00079.1
   Teklay A, 2021, ECOHYDROL HYDROBIOL, V21, P315, DOI 10.1016/j.ecohyd.2020.12.001
   Thapa B, 2020, ENVIRON EARTH SCI, V79, DOI 10.1007/s12665-020-09252-4
   Thomas BC, 2009, INT J DIGIT EARTH, V2, P155, DOI 10.1080/17538940902767393
   Tiwari PC, 2000, LAND USE POLICY, V17, P101, DOI 10.1016/S0264-8377(00)00002-8
   Tiwari S, 2018, GLOBAL PLANET CHANGE, V161, P10, DOI 10.1016/j.gloplacha.2017.10.013
   Toth J., 1971, INT ASS SCI HYDROLOG, V16, P7, DOI [DOI 10.1080/02626667109493029, 10.1080/02626667109493029]
   UAPCC, 2014, UTT ACT PLAN CLIM CH
   VALDIYA KS, 1989, CURR SCI INDIA, V58, P417
   Vijhani A, 2021, J MT SCI-ENGL, V18, P2722, DOI 10.1007/s11629-021-6856-6
   Wang Q, 2018, CATENA, V170, P305, DOI 10.1016/j.catena.2018.06.022
   Weissinger R, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1491
   Wen SS, 2020, CLIMATIC CHANGE, V163, P1207, DOI 10.1007/s10584-020-02929-6
   Wheeler D., 2005, Journal of Geographical Systems, V7, P161, DOI [10.1007/s10109-005-0155-6, DOI 10.1007/S10109-005-0155-6]
   White MJ, 2017, WATER-SUI, V9, DOI 10.3390/w9060437
   White W.B., 1988, Geomorphology and Hydrology ofKarst Terrains
   Yeh HF, 2016, SUSTAIN ENVIRON RES, V26, P33, DOI 10.1016/j.serj.2015.09.005
   York JP, 2002, ADV WATER RESOUR, V25, P221, DOI 10.1016/S0309-1708(01)00021-5
   Young AR, 2006, J HYDROL, V320, P155, DOI 10.1016/j.jhydrol.2005.07.017
   Yusoff I, 2002, GEOL SOC SPEC PUBL, V193, P325, DOI 10.1144/GSL.SP.2002.193.01.24
   Zhang YK., 1996, Hydrogeol J, V4, P41, DOI DOI 10.1007/S100400050087
NR 154
TC 8
Z9 8
U1 1
U2 29
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0885-6087
EI 1099-1085
J9 HYDROL PROCESS
JI Hydrol. Process.
PD MAY
PY 2022
VL 36
IS 5
AR e14582
DI 10.1002/hyp.14582
PG 20
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Water Resources
GA 1I4IG
UT WOS:000797192900001
DA 2025-01-10
ER

PT J
AU Wouterse, F
   Andrijevic, M
   Schaeffer, M
AF Wouterse, Fleur
   Andrijevic, Marina
   Schaeffer, Michiel
TI The microeconomics of adaptation: Evidence from smallholders in Ethiopia
   and Niger
SO WORLD DEVELOPMENT
LA English
DT Article
DE Smallholders; Adaptation; Micro-regions; Regression analysis; Africa
ID SUB-SAHARAN AFRICA; CLIMATE-CHANGE ADAPTATION; FOOD SECURITY; ADAPTIVE
   CAPACITY; PRODUCTION RISK; LIVESTOCK; SYSTEMS; CROP; DIVERSIFICATION;
   DETERMINANTS
AB Climate change is expected to bring higher temperatures, changes to rainfall patterns and in many places increased frequency and severity of extreme weather. Climate change is slated to affect the global food equation both on the supply and demand side as well as local level food systems where small farm communities often depend on local and their own production. As climate change has become more pronounced, the risk to land-based food security faced by many of the world's poor, such as rural communities in Ethiopia and Niger, seems to have become more intense and less predictable. To avoid food insecurity in response to climatic and other stressors, adaptation by small-scale, subsistence farms needs to be accelerated. To effectively intervene to do so, there is a need to understand adaptive behavior in terms of its drivers and its relation with welfare outcomes such as food security. In this paper, we develop a conceptual framework of risk and adaptation, use regression and cluster analysis and the most recent version of the Living Standards Measurement Surveys data for rural areas in Ethiopia and Niger, to advance our understanding. We find that adaptation is associated with lower food insecurity in Ethiopia but not in Niger. Formal education appears as a central element of adaptive capacity and is associated with both adaptive production and income strategies. Female-headed households are much less adapted to a changing climate. Perceived risk based on past hazard experience is crucial for adaptation. Results from the cluster analysis confirm that spatial poverty traps exist. To maintain or enhance welfare in the short term and resilience in the long run in the face of a changing climate, policy makers would do well to focus on micro-regions identified as highly food insecure and build adaptive capacity through, for example, gender inclusive education interventions. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
C1 [Wouterse, Fleur; Schaeffer, Michiel] Energy Acad Europe, Global Ctr Adaptat, Nijenborgh 6, NL-9747 AG Groningen, Netherlands.
   [Andrijevic, Marina] Int Inst Appl Syst Anal, Schlosspl 1, A-2361 Laxenburg, Austria.
C3 International Institute for Applied Systems Analysis (IIASA)
RP Wouterse, F (corresponding author), Energy Acad Europe, Global Ctr Adaptat, Nijenborgh 6, NL-9747 AG Groningen, Netherlands.
EM fleur.wouterse@gca.org; andrijevic@iiasa.ac.at;
   michiel.schaeffer@gca.org
OI Schaeffer, Michiel/0000-0003-0052-5088
CR Andersson C, 2011, J DEV ECON, V94, P119, DOI 10.1016/j.jdeveco.2009.12.002
   [Anonymous], 2011, 5 CCAFS
   [Anonymous], 2019, NOTRE DAME GLOBAL AD
   [Anonymous], 2015, Global Forest Resources Assessment 2015. How Are the World's Forests Changing?, V2nd
   [Anonymous], 2014, NEW DIRECTIONS SMALL
   Asfaw S, 2016, J AFR ECON, V25, P637, DOI 10.1093/jae/ejw005
   Barrett CB, 2014, P NATL ACAD SCI USA, V111, P14625, DOI 10.1073/pnas.1320880111
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Bongaarts J, 2021, POPUL DEV REV, V47, P558
   Burton Ian., 1993, The Environment as Hazard
   Byers E, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabf45
   Chen C, 2018, MITIG ADAPT STRAT GL, V23, P101, DOI 10.1007/s11027-016-9731-y
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   Davis B., 2018, AGR AFRICA TELLING M, V1, P65
   Dedehouanou SFA, 2018, WORLD DEV, V105, P428, DOI 10.1016/j.worlddev.2017.12.005
   Delavallade C, 2015, Managing risk with insurance and savings: Experimental evidence for male and female farm managers in West Africa
   Dercon S, 1998, J DEV ECON, V55, P1, DOI 10.1016/S0304-3878(97)00054-0
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Devereux S, 2007, AGR ECON-BLACKWELL, V37, P47, DOI 10.1111/j.1574-0862.2007.00234.x
   Di Falco S, 2007, AGR ECON-BLACKWELL, V36, P147, DOI 10.1111/j.1574-0862.2007.00194.x
   Di Falco S, 2011, AM J AGR ECON, V93, P825, DOI 10.1093/ajae/aar006
   Dillon B, 2017, FOOD POLICY, V67, P64, DOI 10.1016/j.foodpol.2016.09.015
   Falco S. di, 2018, Climate smart agriculture: building resilience to climate change, P497
   Feinstein NW, 2020, CLIM POLICY, V20, P317, DOI 10.1080/14693062.2019.1701975
   Feleke ST, 2005, AGR ECON-BLACKWELL, V33, P351, DOI 10.1111/j.1574-0864.2005.00074.x
   Felli Romain., 2021, The Great Adaptation: Climate, Capitalism, and Catastrophe
   Fisher M, 2015, CLIMATIC CHANGE, V133, P283, DOI 10.1007/s10584-015-1459-2
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Hirvonen K, 2020, WORLD DEV, V131, DOI 10.1016/j.worlddev.2020.104964
   Issoufou O. H., 2017, African Crop Science Journal, V25, P207, DOI 10.4314/acsj.v25i2.6
   Kato E, 2011, AGR ECON-BLACKWELL, V42, P593, DOI 10.1111/j.1574-0862.2011.00539.x
   Kaufmann D, 2011, HAGUE J RULE LAW, V3, P220, DOI 10.1017/S1876404511200046
   Kosmowski F, 2018, AGR WATER MANAGE, V204, P11, DOI 10.1016/j.agwat.2018.02.025
   Laborde D, 2020, SCIENCE, V369, P500, DOI 10.1126/science.abc4765
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Loison SA, 2015, J DEV STUD, V51, P1125, DOI 10.1080/00220388.2015.1046445
   Lutz W, 2014, SCIENCE, V346, P1061, DOI 10.1126/science.1257975
   Marivoet W, 2019, WORLD DEV, V120, P62, DOI 10.1016/j.worlddev.2019.04.003
   Maruyama E., 2018, ZEF DISCUSSION PAPER, V251
   Masson-Delmotte V, 2018, GLOBAL WARMING 15 C
   Munich R E., 2020, Risks from floods, storm surges and flash floods
   Parry M, 2007, CLIMATE CHANGE 2007
   Proctor F.J., 2014, Rural economic diversification in sub-Saharan Africa
   Quisumbing A., 2019, ReSAKSS Annual Trends and Outlook Report 2019, DOI [10.2499/9780896293649, DOI 10.2499/9780896293649]
   Sadoulet E., 1995, QUANTITATIVE DEV POL
   Schnitzer P, 2019, J DEV STUD, V55, P75, DOI 10.1080/00220388.2019.1687877
   Shukla P.R., 2019, CLIMATE CHANGE LAND
   Singh L., 1986, Agricultural Household Models: Extensions, applications, and policy
   Thornton PK, 2015, NAT CLIM CHANGE, V5, P830, DOI [10.1038/nclimate2754, 10.1038/NCLIMATE2754]
   Vanlauwe B, 2019, EXP AGR, V55, P84, DOI 10.1017/S0014479716000193
   Walker B., 2012, RESILIENCE THINKING
   World Bank, 2019, World Development Indicators
   World Meteorological Organisation, 2019, STAT CLIM AFR
   Wouterse F, 2018, FOSTERING TRANSFORMATION AND GROWTH IN NIGER'S AGRICULTURAL SECTOR, P1, DOI 10.3920/978-90-8686-873-5
   Wouterse F, 2008, WORLD DEV, V36, P625, DOI 10.1016/j.worlddev.2007.03.009
   Wouterse F, 2017, CLIMATIC CHANGE, V145, P367, DOI 10.1007/s10584-017-2096-8
   Zougmoré RB, 2018, CAH AGRIC, V27, DOI 10.1051/cagri/2018019
NR 57
TC 11
Z9 11
U1 2
U2 12
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0305-750X
EI 1873-5991
J9 WORLD DEV
JI World Dev.
PD JUN
PY 2022
VL 154
AR 105884
DI 10.1016/j.worlddev.2022.105884
EA MAR 2022
PG 11
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA 1V0XK
UT WOS:000805823400018
OA Green Accepted, Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Hosseini, M
   Javanroodi, K
   Nik, VM
AF Hosseini, Mohammad
   Javanroodi, Kavan
   Nik, Vahid M.
TI High-resolution impact assessment of climate change on building energy
   performance considering extreme weather events and microclimate -
   Investigating variations in indoor thermal comfort and degree-days
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Climate change adaptation; Extreme climate events; Urban microclimate;
   Urban heat island; Indoor thermal comfort; Building energy performance
ID FUTURE CLIMATE; DATA SETS; SIMULATION; PREDICTION; HEAT; LOAD; MODELS;
   SYSTEM; SENSITIVITY; CONSUMPTION
AB Climate change and urbanization are two major challenges when planning for sustainable energy transition in cities. The common approach for energy demand estimation is using only typical meso-scale weather data in building energy models (BEMs), which underestimates the impacts of extreme climate and microclimate variations. To quantify the impacts of such underestimation on assessing the future energy performance of buildings, this study simulates a high spatiotemporal resolution BEM for two representative residential buildings located in a 600 x 600 m2 urban area in Southeast Sweden while accounting for both climate change and microclimate. Future climate data are synthesized using 13 future climate scenarios over 2010-2099, divided into three 30-year periods, and microclimate data are generated considering the urban morphology of the area. It is revealed that microclimate can cause 17% rise in cooling degree-day (CDD) and 7% reduction in heating degree-day (HDD) on average compared to mesoclimate. Considering typical weather conditions, CDD increases by 45% and HDD decreases by 8% from one 30-year period to another. Differences can become much larger during extreme weather conditions. For example, CDD can increase by 500% in an extreme warm July compared to a typical one. Results also indicate that annual cooling demand becomes four and five times bigger than 2010-2039 in 2040-2069 and 2070-2099, respectively. The daily peak cooling load can increase up to 25% in an extreme warm day when accounting for microclimate. In the absence of cooling systems during extreme warm days, the indoor temperature stays above 26 degrees C continuously over a week and reaches above 29.2 degrees C. Moreover, the annual overheating hours can increase up to 140% in the future. These all indicate that not accounting for influencing climate variations can result in maladaptation or insufficient adaptation of urban areas to climate change.
C1 [Hosseini, Mohammad] NTNU Norwegian Univ Sci & Technol, Fac Engn, Dept Ocean Operat & Civil Engn, Alesund, Norway.
   [Hosseini, Mohammad; Nik, Vahid M.] Lund Univ, Div Bldg Phys, Dept Bldg & Environm Technol, SE-22363 Lund, Sweden.
   [Javanroodi, Kavan; Nik, Vahid M.] Chalmers Univ Technol, Dept Architecture & Civil Engn, Div Bldg Technol, SE-41296 Gothenburg, Sweden.
   [Javanroodi, Kavan] Ecole Polytech Fed Lausanne EPFL, Solar Energy & Bldg Phys Lab LESO PB, CH-1015 Lausanne, Switzerland.
C3 Norwegian University of Science & Technology (NTNU); Lund University;
   Chalmers University of Technology; Swiss Federal Institutes of
   Technology Domain; Ecole Polytechnique Federale de Lausanne
RP Nik, VM (corresponding author), Lund Univ, Div Bldg Phys, Dept Bldg & Environm Technol, SE-22363 Lund, Sweden.; Nik, VM (corresponding author), Chalmers Univ Technol, Dept Architecture & Civil Engn, Div Bldg Technol, SE-41296 Gothenburg, Sweden.
EM mohammad.hosseini@ntnu.no; kavan.javanroodi@epfl.ch;
   vahid.nik@byggtek.lth.se
RI Nik, Vahid/K-2632-2016; Javanroodi, Kavan/ABF-5290-2021
OI Hosseini, Mohammad/0000-0002-9884-0141
FU joint programming initiative 'ERANet Smart Energy Systems' focus
   initiative on Integrated, Regional Energy Systems; European Union
   [775970, 101033683]; Centre for Innovation Research at Lund University
   (CIRCLE); Sweden's innovation agency (VINNOVA -MIRAI)
FX This work was supported by the joint programming initiative `ERANet
   Smart Energy Systems' focus initiative on Integrated, Regional Energy
   Systems, with support from the European Union's Horizon 2020 research
   and innovation programme [775970] and the European Union's Horizon 2020
   research and innovation programme under grant agreement for the
   COLLECTiEF (Collective Intelligence for Energy Flexibility) project
   (grant agreement ID: 101033683). Supports of the Centre for Innovation
   Research at Lund University (CIRCLE) and Sweden's innovation agency
   (VINNOVA -MIRAI) are acknowledged.
CR Amasyali K, 2018, RENEW SUST ENERG REV, V81, P1192, DOI 10.1016/j.rser.2017.04.095
   [Anonymous], 2014, MEASUREMENT ENERGY D
   Bacher P, 2016, ENERG BUILDINGS, V130, P107, DOI 10.1016/j.enbuild.2016.08.037
   Baker P, 2011, 10 HIST SCOTL CONS G
   Barros V, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, pIX
   Battista G, 2021, APPL SCI-BASEL, V11, DOI 10.3390/app11188327
   Berardi U, 2020, RENEW SUST ENERG REV, V121, DOI 10.1016/j.rser.2019.109681
   Bhandari M, 2012, ENERG BUILDINGS, V49, P109, DOI 10.1016/j.enbuild.2012.01.033
   Biljecki F, 2016, ISPRS ANN PHOTO REM, V4-4, P51, DOI 10.5194/isprs-annals-IV-4-W1-51-2016
   Biljecki F., 2017, THESIS TU DELFT NETH, P353
   Biswas MAR, 2016, ENERGY, V117, P84, DOI 10.1016/j.energy.2016.10.066
   Bourisli RI, 2018, J SOL ENERG-T ASME, V140, DOI 10.1115/1.4039447
   Bueno B, 2012, GEOSCI MODEL DEV, V5, P433, DOI 10.5194/gmd-5-433-2012
   Bueno B, 2014, URBAN CLIM, V9, P35, DOI 10.1016/j.uclim.2014.05.005
   Bueno B, 2013, J APPL METEOROL CLIM, V52, P472, DOI 10.1175/JAMC-D-12-083.1
   Burman E, 2017, WOOD PUBL SER CIVIL, P201, DOI 10.1016/B978-0-08-101128-7.00007-1
   Campbell R. J, 2013, WEATHER RELATED POWE, P103
   Chen Y, 2018, ANNU REV ENV RESOUR, V43, P35, DOI 10.1146/annurev-environ-102017-030052
   Crawley DB, 2008, BUILD ENVIRON, V43, P661, DOI 10.1016/j.buildenv.2006.10.027
   Crawley DruryB., 1998, Transactions-American society of heating refrigerating and air conditioning engineers, V104, P498
   Cronin J, 2018, CLIMATIC CHANGE, V151, P79, DOI 10.1007/s10584-018-2265-4
   Cui Y, 2017, APPL ENERG, V195, P890, DOI 10.1016/j.apenergy.2017.03.113
   Deb C, 2017, RENEW SUST ENERG REV, V74, P902, DOI 10.1016/j.rser.2017.02.085
   Ding YC, 2015, ENRGY PROCED, V78, P2566, DOI 10.1016/j.egypro.2015.11.283
   Ellis PG., 2005, Simulating tall buildings using EnergyPlus
   EnergyPlus, 2021, WEATH DAT SIM
   Erba S, 2017, ENRGY PROCED, V134, P545, DOI 10.1016/j.egypro.2017.09.561
   Fan C, 2021, BUILD SIMUL-CHINA, V14, P3, DOI 10.1007/s12273-020-0723-1
   FEBY, 2019, KRAVSP EN BYGGN BOST
   Femp, 2015, M&V Guidelines: Measurement and Verification for Performance-Based Contracts, Version 4.0
   Gao YJ, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103431
   Gasparrini A, 2015, LANCET, V386, P369, DOI 10.1016/S0140-6736(14)62114-0
   Good P, 2013, CLIM DYNAM, V40, P1041, DOI 10.1007/s00382-012-1410-4
   Goy S, 2020, ENERGIES, V13, DOI 10.3390/en13164244
   Huang P, 2015, ENERG BUILDINGS, V91, P26, DOI 10.1016/j.enbuild.2015.01.026
   Huang YT, 2021, J BUILD ENG, V35, DOI 10.1016/j.jobe.2020.101972
   Hulme J., 2014, IN SITU MEAS WALL U, P82
   Ioannou A, 2015, ENERG BUILDINGS, V92, P216, DOI 10.1016/j.enbuild.2015.01.055
   Janjai S, 2009, APPL ENERG, V86, P528, DOI 10.1016/j.apenergy.2008.08.008
   Javanroodi K, 2021, J PHYS CONF SER, V2042, DOI 10.1088/1742-6596/2042/1/012058
   Javanroodi K., 2018, Wind-phil architecture: optimization of high-rise buildings form for efficient summer cooling in Tehran
   Javanroodi K, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100544
   Javanroodi K, 2019, BUILDINGS-BASEL, V9, DOI 10.3390/buildings9080189
   Javanroodi K, 2018, APPL ENERG, V231, P714, DOI 10.1016/j.apenergy.2018.09.116
   Jessel S, 2019, FRONT PUBLIC HEALTH, V7, DOI 10.3389/fpubh.2019.00357
   Kallert A, 2018, ENRGY PROCED, V149, P122, DOI 10.1016/j.egypro.2018.08.176
   Kensby J., 2015, BUILDINGS THERMAL EN
   Kenward A., 2014, CLIAMTE CENTRAL, V23, P00
   Khoshnoodmotlagh S, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103228
   Kottek M., 2006, Meteor. Z., V15, P259, DOI [10.1127/0941-2948/2006/0130, DOI 10.1127/0941-2948/2006/0110]
   Lee K, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12010112
   Li YF, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103146
   Ma R, 2020, SUSTAIN CITIES SOC, V56, DOI 10.1016/j.scs.2020.102099
   Massana J, 2015, ENERG BUILDINGS, V92, P322, DOI 10.1016/j.enbuild.2015.02.007
   Masters J., 2021, Yale Climate Connections
   Menberg K, 2016, ENERG BUILDINGS, V133, P433, DOI 10.1016/j.enbuild.2016.10.005
   Mihaela-Angelica CB, 2014, PROC ECON FINANC, V10, P190, DOI 10.1016/S2212-5671(14)00293-7
   Moazami A, 2019, APPL ENERG, V238, P696, DOI 10.1016/j.apenergy.2019.01.085
   Mourshed M, 2011, APPL ENERG, V88, P3737, DOI 10.1016/j.apenergy.2011.05.024
   Naboni E, 2020, BUILD SIMUL CONF PR, P3234, DOI 10.26868/25222708.2019.210301
   Nik VM, 2021, NATL SCI REV, V8, DOI 10.1093/nsr/nwaa134
   Nik VM, 2021, APPL ENERG, V281, DOI 10.1016/j.apenergy.2020.116106
   Nik VM, 2017, ENERG BUILDINGS, V154, P30, DOI 10.1016/j.enbuild.2017.08.042
   Nik VM, 2016, APPL ENERG, V177, P204, DOI 10.1016/j.apenergy.2016.05.107
   Nik VM, 2013, BUILD ENVIRON, V60, P291, DOI 10.1016/j.buildenv.2012.11.005
   NOAA, 2021, ITS OFF JUL WAS EART
   Perera ATD, 2021, APPL ENERG, V285, DOI 10.1016/j.apenergy.2020.116430
   Perera ATD, 2020, NAT ENERGY, V5, P150, DOI 10.1038/s41560-020-0558-0
   Pezzutto S, 2019, ENERGIES, V12, DOI 10.3390/en12091760
   Ruiz GR, 2017, ENERGIES, V10, DOI 10.3390/en10101587
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Robine JM, 2008, CR BIOL, V331, P171, DOI 10.1016/j.crvi.2007.12.001
   Rogelj J, 2016, NATURE, V534, P631, DOI 10.1038/nature18307
   Ryu YH, 2012, J APPL METEOROL CLIM, V51, P842, DOI 10.1175/JAMC-D-11-098.1
   SCB, 2019, OFF STAT SWED ANN RE
   SCB, 2017, 4 8 MILL DWELL SWED
   Schiefelbein J, 2019, BUILD ENVIRON, V149, P630, DOI 10.1016/j.buildenv.2018.12.025
   Schwartz J, 2005, EPIDEMIOLOGY, V16, P67, DOI 10.1097/01.ede.0000147114.25957.71
   Sethi M, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0253904
   Seto KC, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P923
   Sorensen LS, 2013, SUSTAINABILITY-BASEL, V5, P3601, DOI 10.3390/su5083601
   Sousa J., 2012, INT WORKSH INF TECHN, P1
   Taha H, 1997, ENERG BUILDINGS, V25, P99, DOI 10.1016/S0378-7788(96)00999-1
   Thomson H, 2019, ENERG BUILDINGS, V196, P21, DOI 10.1016/j.enbuild.2019.05.014
   Tian W, 2018, RENEW SUST ENERG REV, V93, P285, DOI 10.1016/j.rser.2018.05.029
   Tsoka S, 2017, ENRGY PROCED, V122, P853, DOI 10.1016/j.egypro.2017.07.449
   Ueno T, 2020, ENERG BUILDINGS, V228, DOI 10.1016/j.enbuild.2020.110423
   United Nations, 2015, No.A/RES/70/1.
   Walch A, 2020, APPL ENERG, V262, DOI 10.1016/j.apenergy.2019.114404
   Wang C, 2021, SUSTAIN CITIES SOC, V71, DOI 10.1016/j.scs.2021.102998
   Wei YX, 2018, RENEW SUST ENERG REV, V82, P1027, DOI 10.1016/j.rser.2017.09.108
   Yang YC, 2021, APPL ENERG, V298, DOI 10.1016/j.apenergy.2021.117246
   Zhao HX, 2012, RENEW SUST ENERG REV, V16, P3586, DOI 10.1016/j.rser.2012.02.049
   Zhou Y., 2021, SUSTAIN CITIES SOC, V74, P00, DOI [10.1016/j. scs.2021.103174. Scopus, DOI 10.1016/J.SCS.2021.103174.SCOPUS]
   Zoras S, 2017, ENERG BUILDINGS, V150, P81, DOI 10.1016/j.enbuild.2017.05.060
NR 95
TC 51
Z9 50
U1 9
U2 52
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2210-6707
EI 2210-6715
J9 SUSTAIN CITIES SOC
JI Sust. Cities Soc.
PD MAR
PY 2022
VL 78
AR 103634
DI 10.1016/j.scs.2021.103634
PG 21
WC Construction & Building Technology; Green & Sustainable Science &
   Technology; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Science & Technology - Other Topics;
   Energy & Fuels
GA 0K9GM
UT WOS:000781095400001
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Almeida, I
   Rösch, C
   Saha, S
AF Almeida, Iulia
   Roesch, Christine
   Saha, Somidh
TI Converting monospecific into mixed forests: stakeholders' views on
   ecosystem services in the Black Forest Region
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE climate change; ecosystem services; forest conversion; mixed forests;
   monospecific forests; stakeholders' perceptions
ID BEECH FAGUS-SYLVATICA; CLIMATE-CHANGE; PROMOTES PRODUCTIVITY;
   BIODIVERSITY; PERCEPTIONS; MANAGEMENT; TEMPERATE; DROUGHT; STANDS;
   SCIENTISTS
AB Converting monospecific into mixed forests can increase forests' resilience against climate change-related extreme events such as droughts and storms. This insight is especially true when the tree species help each other, such as the fir in low mountain regions like the Black Forest, which improves the water supply of the beech through the hydraulic lift. However, the climate change adaptation strategy "mixed forests" impacts ecosystem services (ES) provided by these forests. Although the supply of ES is biophysically well assessed, there is little knowledge about society's views on ES, neither in terms of supply nor preferences. We aim to close this gap by investigating which ES are prioritized in mixed and monospecific forests of fir and beech at the Black Forest region. We analyzed whether differences depend on the type of forest and the stakeholders' respective interests, and their potential benefits from these services. Making stakeholders' perceptions explicit can facilitate their reflection, enhance knowledge-based and participatory decision making, and realize sustainable forest management strategies. We performed semi-structured interviews and conducted qualitative data analyses with MAXQDA software to investigate the rationale behind stakeholders' perceptions of forests ecosystem services. Our results indicate that despite individual heterogeneities in the perceived importance of ES, there was broad agreement that mixed beech fir forests are superior for providing recreation, water retention, and biodiversity among the cultural, regulating, and supporting ES. Although a minority of stakeholders preferred fir forests to provide timber yield, mixed beech-fir forests are preferred by most of the stakeholders in the long term. This preference is mainly due to the higher adaptation capacity of mixed forests toward climate change impacts and higher flexibility to market demands. We conjecture that there may be public support to convert monospecific to mixed forests in the region of the Black Forest as an effective adaptation strategy for the sustainable supply of ES in the future.
C1 [Almeida, Iulia; Roesch, Christine; Saha, Somidh] Karlsruhe Inst Technol, Inst Technol Assessment & Syst Anal, Karlsruhe, Germany.
C3 Helmholtz Association; Karlsruhe Institute of Technology
RP Almeida, I (corresponding author), Karlsruhe Inst Technol, Inst Technol Assessment & Syst Anal, Karlsruhe, Germany.
RI Almeida, Iulia/JTU-9683-2023; Saha, Somidh/F-6264-2012
OI Christine, Roesch/0000-0003-3908-1218
FU Federal Ministry for the Environment, Nature Conservation and Nuclear
   Safety (BMUB); Federal Ministry of Food and Agriculture (BMEL) [FKZ
   22WC406902]
FX We would like to thank the Federal Ministry for the Environment, Nature
   Conservation and Nuclear Safety (BMUB) and to the Federal Ministry of
   Food and Agriculture (BMEL) for funding this research project (FKZ
   22WC406902) .
CR Albrecht A., 2019, FVA EINBLICK, V2, P9
   Alcamo J., 2005, Ecosystems and human well-being
   Almeida I, 2018, FORESTS, V9, DOI 10.3390/f9100627
   [Anonymous], 2017, MAXQDA Analytics Pro
   [Anonymous], 2011, EU BIOD STRAT 2020
   Armbruster M, 2004, PLANT SOIL, V264, P13, DOI 10.1023/B:PLSO.0000047716.45245.23
   Bengtsson J, 2000, FOREST ECOL MANAG, V132, P39, DOI 10.1016/S0378-1127(00)00378-9
   Biospharengebiet Schwarzwald, 2021, NAT LEB PARTN ZWISCH
   Bodin P, 2007, FOREST ECOL MANAG, V242, P541, DOI 10.1016/j.foreco.2007.01.066
   Brang P, 2014, FORESTRY, V87, P492, DOI 10.1093/forestry/cpu018
   Brown T. C., 1984, ROCKY MOUNTAIN FORES, DOI [10.5962/bhl.title.98656, DOI 10.5962/BHL.TITLE.98656]
   Butler CD, 2006, ECOL SOC, V11
   Carnol M, 2014, FORESTRY, V87, P639, DOI 10.1093/forestry/cpu024
   Chakraborty T, 2017, FLORA, V229, P58, DOI 10.1016/j.flora.2017.02.012
   Clusterportal Baden-Wurttemberg, 2020, CLUSTERDATEN 1 HOLZ
   Danescu A, 2016, OECOLOGIA, V182, P319, DOI 10.1007/s00442-016-3623-4
   DAWSON TE, 1993, OECOLOGIA, V95, P565, DOI 10.1007/BF00317442
   de Groot RS, 2002, ECOL ECON, V41, P393, DOI 10.1016/S0921-8009(02)00089-7
   de Vries S, 2003, ENVIRON PLANN A, V35, P1717, DOI 10.1068/a35111
   Edwards DM, 2012, ECOL SOC, V17, DOI 10.5751/ES-04520-170127
   Endler C, 2011, INT J BIOMETEOROL, V55, P173, DOI 10.1007/s00484-010-0323-3
   Endler C, 2010, INT J BIOMETEOROL, V54, P45, DOI 10.1007/s00484-009-0251-2
   European Commission Brussels Belgium. European Environmental Agency (EEA), 2015, EEA TECH REP
   ForstBW, WALD LAND SCHWARZW
   Freeman R.E., 1984, STRATEG MANAG
   Gallagher Winifred., 2007, The Power of Place: How Our Surroundings Shape Our Thoughts, Emotions, and Actions
   Gamfeldt L, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms2328
   Gregow H, 2017, SCI REP-UK, V7, DOI 10.1038/srep46397
   Grilli G, 2016, FOREST POLICY ECON, V66, P11, DOI 10.1016/j.forpol.2016.02.003
   Gundersen Vegard Sverre, 2008, Urban Forestry & Urban Greening, V7, P241, DOI 10.1016/j.ufug.2008.05.001
   Hicks CC, 2013, GLOBAL ENVIRON CHANG, V23, P1444, DOI 10.1016/j.gloenvcha.2013.07.028
   Huth F., 2013, Schweizerische Zeitschrift fur Forstwesen, V164, P27, DOI 10.3188/szf.2013.0027
   Keniger LE, 2013, INT J ENV RES PUB HE, V10, P913, DOI 10.3390/ijerph10030913
   Landesanstalt fur Umwelt Baden-Wurttemberg (LUBW), 2011, KLIM ANP HINT ECK
   Landesanstalt fur Umwelt Baden-Wurttemberg (LUBW), 2020, KLIM ANP HOLZPR
   Landesanstalt fur Umwelt Baden-Wurttemberg (LUBW), 2020, SCHUTZG BAD WURTT
   Leverty S., 2008, NGOs, the UN and APA
   Loreau M, 2001, SCIENCE, V294, P804, DOI 10.1126/science.1064088
   Ludemann T., 2005, WALDUMBAU ZUKUNFTSOR, P96
   Lyytimäki J, 2020, HUM ECOL, V48, P335, DOI 10.1007/s10745-020-00155-3
   Maes J, 2012, BIOL CONSERV, V155, P1, DOI 10.1016/j.biocon.2012.06.016
   Maes J, 2016, ECOSYST SERV, V17, P14, DOI 10.1016/j.ecoser.2015.10.023
   Magh RK, 2018, TREES-STRUCT FUNCT, V32, P337, DOI 10.1007/s00468-017-1557-z
   Maier C, 2014, LAND USE POLICY, V39, P166, DOI 10.1016/j.landusepol.2014.02.018
   Martín-López B, 2014, ECOL INDIC, V37, P220, DOI 10.1016/j.ecolind.2013.03.003
   Martín-López B, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0038970
   Mayring P., 2000, QUALITATIVE CONTENT, V1, P1, DOI 10.17169/fqs-1.2.1089
   Mayring P., 2016, EINFUHRUNG QUALITATI, P114
   Meining S., 2019, WALDZUSTANDSBERICHT
   Milad M, 2013, BIODIVERS CONSERV, V22, P1181, DOI 10.1007/s10531-012-0337-8
   Morin X, 2011, ECOL LETT, V14, P1211, DOI 10.1111/j.1461-0248.2011.01691.x
   Nadrowski K, 2010, CURR OPIN ENV SUST, V2, P75, DOI 10.1016/j.cosust.2010.02.003
   Nationalpark Schwarzwald, LAG ZON
   Niedermann-Meier S., 2010, Schweizerische Zeitschrift fur Forstwesen, V161, P391, DOI 10.3188/szf.2010.0391
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Paquette A, 2011, GLOBAL ECOL BIOGEOGR, V20, P170, DOI 10.1111/j.1466-8238.2010.00592.x
   Pascual U, 2017, CURR OPIN ENV SUST, V26-27, P7, DOI 10.1016/j.cosust.2016.12.006
   Pastowski S., 2004, MESSUNG DIENSTLEISTU, DOI [10.1007/978-3-322-81768-6, DOI 10.1007/978-3-322-81768-6]
   Peterson G, 1998, ECOSYSTEMS, V1, P6, DOI 10.1007/s100219900002
   Petrás R, 2016, CENT EURO FOR J, V62, P98, DOI 10.1515/forj-2016-0010
   Plieninger T, 2013, LAND USE POLICY, V33, P118, DOI 10.1016/j.landusepol.2012.12.013
   Polley H., 2014, WALD DEUTSCHLAND AUS
   Pretsch H., 2013, NOVA ACTA LEOPOLD, V391, P159
   Pretzsch H, 2014, TREES-STRUCT FUNCT, V28, P1305, DOI 10.1007/s00468-014-1035-9
   RAPPORT DJ, 1995, ENVIRON VALUE, V4, P287, DOI 10.3197/096327195776679439
   Reed MS, 2009, J ENVIRON MANAGE, V90, P1933, DOI 10.1016/j.jenvman.2009.01.001
   RIBE RG, 1989, ENVIRON MANAGE, V13, P55, DOI 10.1007/BF01867587
   Rosenkranz L., 2018, HOLZ ZENTRALBLATT, V17, P383
   Rowley J, 2012, MANAG RES REV, V35, P260, DOI 10.1108/01409171211210154
   Schutzgemeinschaft Deutscher Wald (SDW), 2019, WALD BAD WURTT
   Schwarz JA, 2019, FRONT FOR GLOB CHANG, V2, DOI 10.3389/ffgc.2019.00079
   Schwarzwald Tourismus GmbH, 2020, NEUER REK TOUR
   Sohn JA, 2016, FOREST ECOL MANAG, V380, P261, DOI 10.1016/j.foreco.2016.07.046
   Sousa-Silva R, 2018, FOREST POLICY ECON, V90, P22, DOI 10.1016/j.forpol.2018.01.004
   Sprauer S, 2015, EUR J FOREST RES, V134, P781, DOI 10.1007/s10342-015-0889-8
   Stadt Freiburg, 2013, FREIBURG ST DTISCHES
   Strauss A., 1967, DISCOV GROUNDED THEO
   Strauss AnselmL., 1987, Qualitative analysis for social scientists, P55, DOI DOI 10.1017/CBO9780511557842
   Tauro A, 2018, ECOL SOC, V23, DOI 10.5751/ES-10457-230411
   Thunen Institut, 2012, 3 BUND ERG
   Thunen Institute, 2019, EC ACC FOR
   Thurm EA, 2016, ANN FOREST SCI, V73, P1047, DOI 10.1007/s13595-016-0588-8
   Tost H, 2019, NAT NEUROSCI, V22, P1389, DOI 10.1038/s41593-019-0451-y
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   United Nations, 2015, No.A/RES/70/1.
   van Kamp I, 2003, LANDSCAPE URBAN PLAN, V65, P7
   Vilà M, 2007, ECOL LETT, V10, P241, DOI 10.1111/j.1461-0248.2007.01016.x
   ,, 2009, CBD Technical Series
NR 88
TC 5
Z9 5
U1 4
U2 41
PU RESILIENCE ALLIANCE
PI WOLFVILLE
PA ACADIA UNIV, BIOLOGY DEPT, WOLFVILLE, NS B0P 1X0, CANADA
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PD DEC
PY 2021
VL 26
IS 4
AR 28
DI 10.5751/ES-12723-260428
PG 22
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA YJ0EH
UT WOS:000744211900013
OA gold
DA 2025-01-10
ER

PT J
AU Kakraliya, SK
   Jat, HS
   Sapkota, TB
   Singh, I
   Kakraliya, M
   Gora, MK
   Sharma, PC
   Jat, ML
AF Kakraliya, Suresh K.
   Jat, Hanuman S.
   Sapkota, Tek B.
   Singh, Ishwar
   Kakraliya, Manish
   Gora, Manoj K.
   Sharma, Parbodh C.
   Jat, Mangi L.
TI Effect of Climate-Smart Agriculture Practices on Climate Change
   Adaptation, Greenhouse Gas Mitigation and Economic Efficiency of
   Rice-Wheat System in India
SO AGRICULTURE-BASEL
LA English
DT Article
DE global warming potential; C-sequestration; climate change mitigation;
   eco-efficiency; no-tillage and residue management
ID NITROUS-OXIDE EMISSION; GANGETIC PLAINS; CARBON SEQUESTRATION; CROPPING
   SYSTEMS; FOOD SECURITY; SOUTH-ASIA; SOIL; TILLAGE; MANAGEMENT;
   OPPORTUNITIES
AB Conventional rice-wheat (RW) rotation in the Indo-Gangetic Plains (IGP) of South Asia is tillage, water, energy, and capital intensive. Coupled with these, crop residue burning contributes significantly to greenhouse gas (GHG) emission and environmental pollution. So, to evaluate the GHG mitigation potential of various climate-smart agricultural practices (CSAPs), an on-farm research trial was conducted during 2014-2017 in Karnal, India. Six management scenarios (portfolios of practices), namely, Sc1-business as usual (BAU)/conventional tillage (CT) without residue, Sc2-CT with residue, Sc3-reduced tillage (RT) with residue + recommended dose of fertilizer (RDF), Sc4-RT/zero tillage (ZT) with residue + RDF, Sc5-ZT with residue + RDF + GreenSeeker + Tensiometer, and Sc6-Sc5 + nutrient-expert tool, were included. The global warming potential (GWP) of the RW system under CSAPs (Sc4, Sc5, and Sc6) and the improved BAU (Sc2 and Sc3) were 33-40% and 4-26% lower than BAU (7653 kg CO2 eq./ha/year), respectively. This reflects that CSAPs have the potential to mitigate GWP by ~38(7) metric tons (Mt) CO2 eq./year from the 13.5 Mha RW system of South Asia. Lower GWP under CSAPs resulted in 36-44% lower emission intensity (383 kg CO2 eq./Mg/year) compared to BAU (642 kg CO2 eq./Mg/year). Meanwhile, the N-factor productivity and eco-efficiency of the RW system under CSAPs were 32-57% and 70-105% higher than BAU, respectively, which reflects that CSAPs are more economically and environmentally sustainable than BAU. The wheat yield obtained under various CSAPs was 0.62 Mg/ha and 0.84 Mg/ha higher than BAU during normal and bad years (extreme weather events), respectively. Thus, it is evident that CSAPs can cope better with climatic extremes than BAU. Therefore, a portfolio of CSAPs should be promoted in RW belts for more adaptation and climate change mitigation.
C1 [Kakraliya, Suresh K.; Singh, Ishwar; Kakraliya, Manish; Gora, Manoj K.] CCS Haryana Agr Univ, Dept Agron, Hisar 125004, Haryana, India.
   [Kakraliya, Suresh K.; Jat, Hanuman S.; Kakraliya, Manish; Sharma, Parbodh C.] ICAR Cent Soil Salin Res Inst, Karnal 132001, Haryana, India.
   [Sapkota, Tek B.; Jat, Mangi L.] NASC Complex, Int Maize & Wheat Improvement Ctr CIMMYT, New Delhi 110012, India.
   [Sapkota, Tek B.] Int Maize & Wheat Improvement Ctr CIMMYT, El Batan 56237, Texcoco, Mexico.
C3 CCS Haryana Agricultural University; Indian Council of Agricultural
   Research (ICAR); ICAR - Central Soil Salinity Research Institute; CGIAR;
   International Maize & Wheat Improvement Center (CIMMYT); CGIAR;
   International Maize & Wheat Improvement Center (CIMMYT)
RP Jat, HS (corresponding author), ICAR Cent Soil Salin Res Inst, Karnal 132001, Haryana, India.; Jat, ML (corresponding author), NASC Complex, Int Maize & Wheat Improvement Ctr CIMMYT, New Delhi 110012, India.
EM kakraliyask@gmail.com; hs.jat@icar.gov.in; t.sapkota@cgiar.org;
   skk8326@gmail.com; manishkakraliya719@gmail.com; goramanoj6@gmail.com;
   parbodh.chander@icar.gov.in; m.jat@cgiar.org
RI Sharma, Parbodh/Q-3574-2019; Singh, Ishwar/AAR-3480-2020; Jat,
   ML/O-2824-2019; Sapkota, Tek/AAC-3155-2020
OI Sharma, Parbodh Chander/0000-0002-5783-7480; JAT,
   ML/0000-0003-0582-1126; Sapkota, Tek/0000-0001-5311-0586
CR Alavaisha E, 2019, J ENVIRON MANAGE, V234, P159, DOI 10.1016/j.jenvman.2018.12.039
   [Anonymous], 1984, Statistical Procedures for Agricultural Research with Emphasis on Rice
   [Anonymous], 2002, SASSTAT USERS GUIDE
   [Anonymous], 2006, INTERGOVERNMENTAL PA, DOI DOI 10.1016/J.PHRS.2011.03.002
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P3267, DOI 10.1007/s10668-019-00345-0
   Bhatia A, 2010, AGR ECOSYST ENVIRON, V136, P247, DOI 10.1016/j.agee.2010.01.004
   Bhatia A, 2013, GREENH GASES, V3, P196, DOI 10.1002/ghg.1339
   Bouwman A.F., 2001, GLOBAL INVENTORY NH
   Bouwman AF, 2002, GLOBAL BIOGEOCHEM CY, V16, DOI [10.1029/2001GB001812, 10.1029/2001GB001811]
   Campbell BM, 2016, GLOB FOOD SECUR-AGR, V11, P34, DOI 10.1016/j.gfs.2016.06.002
   Erenstein O, 2008, SOIL TILL RES, V100, P1, DOI 10.1016/j.still.2008.05.001
   Feliciano D, 2015, CCAFS MITIGATION OPT
   Frischknecht R., 2007, Ecoinvent Rep, V1
   Gathala MK, 2014, AGR ECOSYST ENVIRON, V187, P33, DOI 10.1016/j.agee.2013.12.011
   Gathala MK, 2011, SOIL SCI SOC AM J, V75, P1851, DOI 10.2136/sssaj2010.0362
   Gupta DK, 2016, AGR ECOSYST ENVIRON, V230, P1, DOI 10.1016/j.agee.2016.05.023
   Jat HS, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-76035-z
   Jat ML, 2016, ADV AGRON, V137, P127, DOI 10.1016/bs.agron.2015.12.005
   Jat RK, 2014, FIELD CROP RES, V164, P199, DOI 10.1016/j.fcr.2014.04.015
   Ju XT, 2009, P NATL ACAD SCI USA, V106, P3041, DOI 10.1073/pnas.0813417106
   Kakraliya SK, 2018, AGR WATER MANAGE, V202, P122, DOI 10.1016/j.agwat.2018.02.020
   Kakraliya S.K., 2019, Indian Journal of Fertilisers, V15, P852
   Kakraliya S.K., 2017, INT J CURR MICROBIOL, V6, P152, DOI [DOI 10.20546/IJCMAS.2017.603.017, 10.20546/ijcmas.2017.603.017]
   Ladha JK, 2003, FIELD CROP RES, V81, P159, DOI 10.1016/S0378-4290(02)00219-8
   Ogle SM, 2005, BIOGEOCHEMISTRY, V72, P87, DOI 10.1007/s10533-004-0360-2
   Qiao J, 2012, AGR ECOSYST ENVIRON, V146, P103, DOI 10.1016/j.agee.2011.10.014
   Saharawat Y. S., 2012, Journal of Soil Science and Environmental Management, V3, P9
   Sapkota TB, 2017, SOIL USE MANAGE, V33, P81, DOI 10.1111/sum.12331
   Sapkota TB, 2019, SCI TOTAL ENVIRON, V655, P1342, DOI 10.1016/j.scitotenv.2018.11.225
   Sapkota TB, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9061044
   Sapkota TB, 2015, J INTEGR ENVIRON SCI, V12, P31, DOI 10.1080/1943815X.2015.1110181
   Sapkota TB, 2014, FIELD CROP RES, V155, P233, DOI 10.1016/j.fcr.2013.09.001
   Smith P, 1997, GLOBAL CHANGE BIOL, V3, P67, DOI 10.1046/j.1365-2486.1997.00055.x
   Soni P, 2018, ENERGY REP, V4, P554, DOI 10.1016/j.egyr.2018.09.001
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Wang W, 2015, SOIL TILL RES, V152, P8, DOI 10.1016/j.still.2015.03.011
   West TO, 2002, SOIL SCI SOC AM J, V66, P1930, DOI 10.2136/sssaj2002.1930
   Yadvinder-Singh, 2010, NUTR CYCL AGROECOSYS, V88, P471, DOI 10.1007/s10705-010-9370-8
NR 38
TC 17
Z9 17
U1 7
U2 28
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2077-0472
J9 AGRICULTURE-BASEL
JI Agriculture-Basel
PD DEC
PY 2021
VL 11
IS 12
AR 1269
DI 10.3390/agriculture11121269
PG 20
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA XW6NN
UT WOS:000735733500001
OA gold
DA 2025-01-10
ER

PT J
AU Zam, P
   Shrestha, S
   Budhathoki, A
AF Zam, Phub
   Shrestha, Sangam
   Budhathoki, Aakanchya
TI Assessment of climate change impact on hydrology of a transboundary
   river of Bhutan and India
SO JOURNAL OF WATER AND CLIMATE CHANGE
LA English
DT Article
DE climate change; hydrology; Raidak river; transboundary river; wangchu
   river
ID UNCERTAINTY ANALYSIS; WATER-RESOURCES; SWAT MODEL; BASIN; GLACIER;
   CALIBRATION; HIMALAYA; RUNOFF; SEKONG; SESAN
AB Assessing the impacts of climate change on a transboundary river plays an important role in sustaining water security within as well as beyond the national boundaries. At times, the unilateral decision taken by one country can increase the risk of negative effect on the riparian countries and if the impact is felt strongly by the other country, it can lead to international tension between them. This study examines the impact of climate change on hydrology between a shared river which is Wangchu river in Bhutan and Raidak river in India. The river is mainly used to produce hydropower in the two largest hydropower plants on which the majority of Bhutan's economic development depends and is mainly used for agriculture in India. The Soil and Water Assessment Tool (SWAT) was used for future flow simulation. Future climate was projected for near future (NF) from 2025-2050 and far future (FF) from 2074-2099 using an ensemble of three regional climate models (ACCESS, CNRM-CM5 and MPI-ESM-LR) for two RCPs (Representative Concentration Pathways), RCP 4.5 and RCP 8.5 scenario. The ensemble results indicated that, in future, the study area would become warmer with temperature increase of 1.5 degrees C under RCP 4.5 and 3.6 degrees C under RCP 8.5. However, as per RCP 4.5 and RCP 8.5, rainfall over the study area is projected to decrease by 1.90% and 1.38% respectively. As a consequence of the projected decrease in rainfall, the flow in river is projected to decrease by 5.77% under RCP 4.5 and 4.73% under RCP 8.5. Overall, the results indicated that the degree of hydrological change is expected to be higher, particularly for low flows in both Wangchu and Raidak River. Since transboundary water is a shared for economic growth, climate change adaptation and opportunities should also be considered by both the nations for better water management.
C1 [Zam, Phub] Druk Green Power Corp, Thimphu, Bhutan.
   [Zam, Phub; Shrestha, Sangam; Budhathoki, Aakanchya] Asian Inst Technol, Water Engn & Management, Sch Engn & Technol, Pathum Thani 12120, Thailand.
C3 Asian Institute of Technology
RP Shrestha, S (corresponding author), Asian Inst Technol, Water Engn & Management, Sch Engn & Technol, Pathum Thani 12120, Thailand.
EM sangam@ait.ac.th
OI Shrestha, Sangam/0000-0002-4972-3969
FU Asian Institute of Technology (AIT); Thai Pipe Industry Co. Ltd
FX The authors would like to acknowledge the National Center for Hydrology
   and Meteorology, Bhutan for providing the required data, and the Asian
   Institute of Technology (AIT) and Thai Pipe Industry Co. Ltd for
   providing the necessary support to conduct the study.
CR Abbaspour KC., 2008, SWAT CUP2 SWAT CALIB
   Akhtar M, 2008, J HYDROL, V355, P148, DOI 10.1016/j.jhydrol.2008.03.015
   Alfonso K, 2015, INT J MOL SCI, V115
   Arnold JG, 2012, T ASABE, V55, P1491
   Babel MS, 2014, THEOR APPL CLIMATOL, V115, P639, DOI 10.1007/s00704-013-0910-4
   Bharati L., 2014, MT RES DEV
   Biswas AK, 2011, HYDROLOG SCI J, V56, P662, DOI 10.1080/02626667.2011.572886
   Brouziyne Y, 2021, ECOL INFORM, V61, DOI 10.1016/j.ecoinf.2021.101219
   Budhathoki A, 2021, ECOHYDROL HYDROBIOL, V21, P79, DOI 10.1016/j.ecohyd.2020.07.001
   cerkasova N, 2018, ECOL ENG, V124, P99, DOI 10.1016/j.ecoleng.2018.09.025
   Khoi DN, 2015, GLOB ECOL CONSERV, V4, P538, DOI 10.1016/j.gecco.2015.10.007
   Eum HI, 2017, J HYDROL, V544, P327, DOI 10.1016/j.jhydrol.2016.11.034
   Fakhruddin S.H.M, 2015, J. Geogr. Geol., V7, DOI [10.5539/jgg.v7n2p70, DOI 10.5539/JGG.V7N2P70]
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Gebre S.L., 2015, J. Climatol. Weather Forecast, V3, P2, DOI DOI 10.4172/2332-2594.1000121
   GOLDENMAN G, 1990, ECOL LAW QUART, V17, P741
   Hajihosseini M, 2020, J WATER CLIM CHANGE, V11, P1695, DOI 10.2166/wcc.2019.100
   Immerzeel W, 2008, INT J CLIMATOL, V28, P243, DOI 10.1002/joc.1528
   Kaini S, 2021, INT J WATER RESOUR D, V37, P929, DOI 10.1080/07900627.2020.1826292
   Khan M.N., 2017, INDIAS WATER ISSUES
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Mello C.R., 2014, REV BRAS RECUR HIDRI, V19, P177, DOI [10.21168/rbrh.v19n1.p177-188, DOI 10.21168/RBRH.V19N1.P177-188]
   Moriasi DN, 2015, T ASABE, V58, P1763
   Muleta MK, 2005, J HYDROL, V306, P127, DOI 10.1016/j.jhydrol.2004.09.005
   NEC, 2016, WANGCH BAS MAN PLAN
   Neitsch S.L., 2005, Soil water assessment tool theoretical document, version 2005
   Trang NTT, 2017, SCI TOTAL ENVIRON, V576, P586, DOI 10.1016/j.scitotenv.2016.10.138
   Nikam BR, 2018, ARAB J GEOSCI, V11, DOI 10.1007/s12517-018-3936-1
   Oertli B, 2005, AQUAT CONSERV, V15, P665, DOI 10.1002/aqc.744
   Oeurng C, 2016, J HYDROL-REG STUD, V8, P95, DOI 10.1016/j.ejrh.2016.07.004
   Palazzoli I, 2015, AGR SYST, V133, P143, DOI 10.1016/j.agsy.2014.10.016
   Rajib MA, 2016, ENVIRON MODELL SOFTW, V75, P498, DOI 10.1016/j.envsoft.2015.10.032
   Richter BD, 1998, REGUL RIVER, V14, P329
   Rostamian R, 2008, HYDROLOG SCI J, V53, P977, DOI 10.1623/hysj.53.5.977
   Sen Singh D, 2017, QUATERN INT, V444, P172, DOI 10.1016/j.quaint.2016.07.025
   Shrestha A, 2021, J CLEAN PROD, V279, DOI 10.1016/j.jclepro.2020.123483
   Shrestha M, 2017, METEOROL APPL, V24, P531, DOI 10.1002/met.1655
   Stefanidis K, 2016, SCI TOTAL ENVIRON, V573, P1492, DOI 10.1016/j.scitotenv.2016.08.046
   Yang J, 2008, J HYDROL, V358, P1, DOI 10.1016/j.jhydrol.2008.05.012
NR 39
TC 12
Z9 12
U1 6
U2 23
PU IWA PUBLISHING
PI LONDON
PA REPUBLIC-EXPORT BLDG, UNITS 1 04 & 1 05, 1 CLOVE CRESCENT, LONDON,
   ENGLAND
SN 2040-2244
EI 2408-9354
J9 J WATER CLIM CHANGE
JI J. Water Clim. Chang.
PD NOV
PY 2021
VL 12
IS 7
SI SI
BP 3224
EP 3239
DI 10.2166/wcc.2021.338
EA JUN 2021
PG 16
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA WT7TW
UT WOS:000669927100001
OA gold
DA 2025-01-10
ER

PT J
AU Asad, R
   Ahmed, I
   Vaughan, J
   von Meding, J
AF Asad, Rumana
   Ahmed, Iftekhar
   Vaughan, Josephine
   von Meding, Jason
TI Traditional water knowledge: challenges and opportunities to build
   resilience to urban floods
SO INTERNATIONAL JOURNAL OF DISASTER RESILIENCE IN THE BUILT ENVIRONMENT
LA English
DT Article
DE Resilience; Urban development; Flooding; Built environment; Water;
   Traditional ecological knowledge; Flood resilience
ID CLIMATE-CHANGE ADAPTATION; INDIGENOUS KNOWLEDGE; ECOLOGICAL KNOWLEDGE;
   RISK-MANAGEMENT; GOVERNANCE; DESIGN; LANDSCAPE; WISDOM; TEK; FRAMEWORK
AB Purpose
   Urban flooding in developing countries of the Global South is growing due to extreme rainfall and sea-level rise induced by climate change, as well as the proliferation of impervious, built-up areas resulting from unplanned urbanisation and development. Continuous loss of traditional knowledge related to local water management practices, and the de-valuing of such knowledge that goes hand-in-hand with globalised aspirations, is inhibiting flood resilience efforts. This paper aims to address the need to include traditional water knowledge (TWK) in urban living and development processes in the Global South.
   Design/methodology/approach
   This paper commences with a review of existing frameworks that focus on natural resource management, critically assessing two existing frameworks of traditional ecological knowledge (TEK). The assessment of the existing approaches contributes to this paper's development of a novel framework to promote TWK with regard to resilience and risk reduction, specifically for developing flood adaptive strategies, which is the second stage of this paper. Finally, the paper explains how the framework can contribute to the field of urban design and planning using examples from the literature to demonstrate challenges and opportunities related to the adaptation of such a framework.
   Findings
   The framework developed in this paper reveals three proposed vertices of TWK, named as place-based landscape knowledge, water use and management and water values. This framework has the potential to produce context-specific knowledge that can contribute to flood-resilient built-environment through urban design and practices.
   Research limitations/implications
   The framework developed in this paper reveals three proposed vertices of TWK, named place-based landscape knowledge, water use and management and water values. This framework has the potential to produce context-specific knowledge that can contribute to flood-resilient built-environment through urban design and practices.
   Originality/value
   Within the field of TEK research, very few researchers have explored the field of developing flood resilience in an urban context. The proposed TWK framework presented in this paper will help to fill that gap.
C1 [Asad, Rumana; Ahmed, Iftekhar; Vaughan, Josephine] Univ Newcastle, Sch Architecture & Built Environm, Callaghan, NSW, Australia.
   [Asad, Rumana] Khulna Univ, Architecture Discipline, Khulna, Bangladesh.
   [von Meding, Jason] Univ Florida, Florida Inst Built Environm Resilience, Gainesville, FL USA.
C3 University of Newcastle; Khulna University; State University System of
   Florida; University of Florida
RP Asad, R (corresponding author), Univ Newcastle, Sch Architecture & Built Environm, Callaghan, NSW, Australia.; Asad, R (corresponding author), Khulna Univ, Architecture Discipline, Khulna, Bangladesh.
EM rumana.asad@uon.edu.au
RI Asad, Rumana/AAP-1288-2020; Ahmed, Iftekhar/GPW-8881-2022; Vaughan,
   Josephine/G-7434-2013; von Meding, Jason/D-6499-2013
OI Ahmed, Iftekhar/0000-0001-5316-4584; Vaughan,
   Josephine/0000-0003-4730-9892; von Meding, Jason/0000-0002-2040-9298
FU RTP Allowance
FX This paper is part of PhD research work of the first author of this
   paper. The author likes to acknowledge the support that got from RTP
   Stipend and RTP Allowance to pursue this research.
CR [Anonymous], 2013, Designed Ecologies: the Landscape Architecture of Kongjian Yu
   [Anonymous], 2013, RESILIENCE ECOLOGY U
   Asad, 2017, INTEGRATED WATER INF
   Berkes F, 2000, ECOL APPL, V10, P1251, DOI 10.2307/2641280
   Berkes F., 1999, Sacred ecology: Traditional ecological knowledge and resource management
   Bhattacharya S, 2015, INT LETT NAT SCI, V37, P30, DOI 10.18052/www.scipress.com/ILNS.37.30
   Bussey J, 2016, J FOREST, V114, P97, DOI 10.5849/jof.14-130
   Buurman J, 2018, J ENVIRON PLANN MAN, V61, P2531, DOI 10.1080/09640568.2017.1404972
   Bwambale B, 2018, JAMBA-J DISASTER RIS, V10, DOI 10.4102/jamba.v10i1.536
   Chen CD, 2014, ECOL ENG, V71, P584, DOI 10.1016/j.ecoleng.2014.07.008
   Chowdhury RB, 2017, J CLEAN PROD, V150, P371, DOI 10.1016/j.jclepro.2015.10.060
   Dean AJ, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159063
   Dudgeon R.C., 2003, NATURE CULTURES, P75, DOI DOI 10.1007/978-94-017-0149-5_4
   Ellis SC, 2005, ARCTIC, V58, P66
   Escott H, 2015, LAND USE POLICY, V49, P382, DOI 10.1016/j.landusepol.2015.08.003
   Finn M, 2011, ECOSYSTEMS, V14, P1232, DOI 10.1007/s10021-011-9476-0
   Fratini CF, 2012, URBAN WATER J, V9, P317, DOI 10.1080/1573062X.2012.668913
   Gao J, 2015, ECOL ENG, V76, P7, DOI 10.1016/j.ecoleng.2014.06.035
   Gautam D., 2014, WATER MANAGEMENT IND
   Gomez-Baggethun Erik, 2013, Hum Ecol Interdiscip J, V41, DOI 10.1007/s10745-013-9577-9
   Gómez-Baggethun E, 2013, ECOL SOC, V18, DOI 10.5751/ES-06288-180472
   Gómez-Baggethun E, 2012, GLOBAL ENVIRON CHANG, V22, P640, DOI 10.1016/j.gloenvcha.2012.02.005
   Haverkort B., 2010, Traditional knowledge in policy and practice: Approaches to development and human well-being, P12, DOI [10.18356/f69d7617-en, DOI 10.18356/F69D7617-EN]
   Hiwasaki L, 2014, INT J DISAST RISK RE, V10, P15, DOI 10.1016/j.ijdrr.2014.07.007
   Houde N, 2007, ECOL SOC, V12, DOI 10.5751/es-02270-120234
   Iloka Nnamdi G, 2016, Jamba, V8, P272, DOI 10.4102/jamba.v8i1.272
   Jackson S., 2005, Australasian Journal of Environmental Management, V12, P136
   Jackson S, 2006, AUST GEOGR, V37, P19, DOI 10.1080/00049180500511947
   Jalilov SM, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10010122
   Jameson S, 2016, HABITAT INT, V54, P112, DOI 10.1016/j.habitatint.2015.12.015
   Jiang Y, 2018, ENVIRON SCI POLICY, V80, P132, DOI 10.1016/j.envsci.2017.11.016
   Kernecker M, 2017, ECOL SOC, V22, DOI [10.5751/ES-09787-220437, 10.5751/es-09787-220437]
   Kim EJA, 2017, CAN J SCI MATH TECHN, V17, P258, DOI 10.1080/14926156.2017.1380866
   Klijn F, 2015, MITIG ADAPT STRAT GL, V20, P845, DOI 10.1007/s11027-015-9638-z
   Krzyzak A., 2014, Autobusy, V15, P78
   Lennon M, 2014, J URBAN DES, V19, P745, DOI 10.1080/13574809.2014.944113
   Leonard S, 2013, GLOBAL ENVIRON CHANG, V23, P623, DOI 10.1016/j.gloenvcha.2013.02.012
   Liao KH, 2016, LANDSCAPE URBAN PLAN, V155, P69, DOI 10.1016/j.landurbplan.2016.01.014
   Liao KH, 2012, ECOL SOC, V17, DOI 10.5751/ES-05231-170448
   Maclean K, 2015, GEOFORUM, V59, P142, DOI 10.1016/j.geoforum.2014.12.008
   Manuel M., 2018, Water History, V10, P13, DOI 10.1007/s12685-017-0200-7
   Martin JF, 2010, ECOL ENG, V36, P839, DOI 10.1016/j.ecoleng.2010.04.001
   Mavhura E, 2013, INT J DISAST RISK RE, V5, P38, DOI 10.1016/j.ijdrr.2013.07.001
   McGregor D., 2008, Canadian Woman Studies, V26
   McGregor D, 2014, ALTERNATIVE, V10, P493, DOI 10.1177/117718011401000505
   Mercer J, 2010, DISASTERS, V34, P214, DOI 10.1111/j.1467-7717.2009.01126.x
   Molden OC, 2018, URBAN GEOGR, V39, P763, DOI 10.1080/02723638.2017.1393921
   Mowla Q. A., 2013, The Online Journal of Science and Technology (TOJSAT), V3, P205
   Novotny V., 2010, WATER CENTRIC SUSTAI
   Orlove B, 2010, ANNU REV ANTHROPOL, V39, P401, DOI 10.1146/annurev.anthro.012809.105045
   Pandey DN, 2003, CURR SCI INDIA, V85, P46
   Piesik, 2017, HABITAT VERNACULAR A
   Remmington G, 2018, J ARID ENVIRON, V151, P134, DOI 10.1016/j.jaridenv.2017.10.003
   Ripa M.N., 2017, PLURIMONDI
   Ross Anne., 2011, INDIGENOUS PEOPLES C
   Schwann A, 2018, J URBAN MANAG, V7, P172, DOI 10.1016/j.jum.2018.05.004
   Scott M, 2013, PLAN THEORY PRACT, V14, P103, DOI 10.1080/14649357.2012.761904
   Shannon K., 2008, Water Urbanisms
   Shannon K., 2013, WATER URBANISMS E EM
   Shannon Kelly., 2013, Resilience in Ecology and Urban Design [electronic resource]: Linking Theory and Practice for Sustainable Cities, P163, DOI 10.1007/978-94-007-5341-9_8
   Shrestha R.P., 2016, J INT DEV COOPERATIO, V22, P47
   Spirn, 2014, ECOLOGICAL URBANISM
   Steiner F, 2014, LANDSCAPE URBAN PLAN, V125, P304, DOI 10.1016/j.landurbplan.2014.01.023
   Nguyen TH, 2017, WATER ALTERN, V10, P134
   Usher PJ, 2000, ARCTIC, V53, P183, DOI 10.14430/arctic849
   von der Porten S, 2016, J CAN STUD, V50, P214, DOI 10.3138/jcs.2016.50.1.214
   Watson J.N., 2013, SUBTROPICAL CITIES 2
   Wenzel GW, 2004, ARCTIC ANTHROPOL, V41, P238, DOI 10.1353/arc.2011.0067
   Wilson NJ, 2019, WATER-SUI, V11, DOI 10.3390/w11030624
   Wilson NJ, 2014, GEOFORUM, V57, P1, DOI 10.1016/j.geoforum.2014.08.005
   Yli-Pelkonen V., 2005, SUSTAINABILITY-BASEL, V1, P3, DOI [DOI 10.1080/15487733.2005.11907960, 10.1080/15487733.2005.11907960]
   Young R.F., 2019, ECOLOGICAL WISDOM
   Young RF, 2016, LANDSCAPE URBAN PLAN, V155, P91, DOI 10.1016/j.landurbplan.2016.04.012
   Yu, 2017, LANDSCAPE ARCHITECTU
   Yu K., 2008, Journal of Landscape Architecture, V3, P6, DOI DOI 10.1080/18626033.2008.9723400
NR 75
TC 3
Z9 3
U1 2
U2 29
PU EMERALD GROUP PUBLISHING LTD
PI BINGLEY
PA HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND
SN 1759-5908
EI 1759-5916
J9 INT J DISASTER RESIL
JI Int. J. Disaster Resil. Built Environ.
PD JAN 7
PY 2022
VL 13
IS 1
BP 1
EP 13
DI 10.1108/IJDRBE-08-2020-0091
EA MAR 2021
PG 13
WC Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA YC5JV
UT WOS:000636360700001
DA 2025-01-10
ER

PT J
AU Iravani, M
   White, SR
   Farr, DR
   Habib, TJ
   Kariyeva, J
   Faramarzi, M
AF Iravani, Majid
   White, Shannon R.
   Farr, Daniel R.
   Habib, Thomas J.
   Kariyeva, Jahan
   Faramarzi, Monireh
TI Assessing the provision of carbon-related ecosystem services across a
   range of temperate grassland systems in western Canada
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Biogeochemical processes; Calibration and uncertainty; Climate change;
   Grazing management; Plant biomass production; Soil carbon stock
ID AGRICULTURAL SOILS; CLIMATE-CHANGE; GRAZING INTENSITY; MODEL; DYNAMICS;
   STORAGE; IMPACT; UNCERTAINTY; CALIBRATION; QUALITY
AB Reliable data on the provision of ecosystem services (ES) is essential to the design and implementation of policies that incorporate ES into grassland conservation and restoration. We developed and applied an innovative approach for regional parameterization, and calibration of the CENTURY ecosystem model. We quantified spatio temporal variation of soil organic carbon stock (SOC) and above ground plant biomass production (AGB) and examined their responses to the recent climate change across a diverse range of native grassland systems in Alberta, western Canada. The simultaneous integration of SOC and AGB into calibration and analysis accounted for most of the spatio temporal variability in the SOC and AGB measurements and resulted in reduced simulation uncertainty across nine grassland regions. These findings suggest the importance of the systematic parameterization and calibration for the reliable assessment of carbon-related ES across a wide geographic area with heterogeneous ecological conditions. Simulation results showed a pronounced variation in the spatial distribution of SOC and AGB and their associated uncertainty across grassland regions. Under baseline grazing intensity regime, an overall negative effect of recent climatic changes on the SOC, and a less consistent effect on the AGO were found. While, an overall positive or slightly negative impact of recent climate change on the SOC and AGB was found under a proposed 10% lower grazing intensity regime. These heterogeneities in the magnitude and direction of climate change effects under different grazing regimes suggest needs for a range of climate change adaptation strategies to maintain carbon-related ES in Alberta's grasslands. The modeling framework developed in this study can be used to improve the spatially explicit assessment of carbon-related ES in other geographically vast grassland areas and examine the effectiveness of alternative management scenarios to ensure the long-term provision of carbon-related ES in grassland systems. (C) 2019 Elsevier B.V. All rights reserved.
C1 [Iravani, Majid; White, Shannon R.; Habib, Thomas J.; Kariyeva, Jahan] Univ Alberta, Alberta Biodivers Monitoring Inst, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada.
   [Iravani, Majid; Faramarzi, Monireh] Univ Alberta, Watershed Sci & Modelling Lab, Dept Earth & Atmospher Sci, Edmonton, AB T6G 2E3, Canada.
   [Farr, Daniel R.] Govt Alberta, Environm Monitoring & Sci Div, Edmonton, AB T5J 5C6, Canada.
C3 University of Alberta; University of Alberta
RP Iravani, M (corresponding author), Univ Alberta, Alberta Biodivers Monitoring Inst, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada.; Iravani, M (corresponding author), Univ Alberta, Watershed Sci & Modelling Lab, Dept Earth & Atmospher Sci, Edmonton, AB T6G 2E3, Canada.
EM iravani@ualberta.ca
OI Habib, Thomas/0000-0003-3035-8268
FU Alberta Innovates [BIO-12-006]; Alberta Agriculture and Forestry
   [2012S007S, 2016E017R]; Natural Sciences and Engineering Research
   Council of Canada Discovery Grants Program [RES0043463]; Campus Alberta
   Innovation Program (CAIP) Chair Award [RES0034497]
FX We gratefully acknowledge funding from the Alberta Innovates (Grant
   #BIO-12-006), the Alberta Agriculture and Forestry (Grants #2012S007S &
   2016E017R), the Natural Sciences and Engineering Research Council of
   Canada Discovery Grants Program (Grant #RES0043463), and the Campus
   Alberta Innovation Program (CAIP) Chair Award (Grant #RES0034497). We
   thank the Rangeland Branch of Alberta Environment and Parks for
   providing information on longterm trends in grassland biomass production
   across the province of Alberta. We appreciate constructive comments
   fromanonymous referees. We also appreciate feedback from Carlos
   Tornquist, Todd Campbell, AmyNixon, Carrie Selin, Craig DeMaere, Donna
   Lawrence, Cameron Carlyle, and Edward Bork on this work.
CR Abbaspour KC, 2007, J HYDROL, V333, P413, DOI 10.1016/j.jhydrol.2006.09.014
   Abdalla M, 2018, AGR ECOSYST ENVIRON, V253, P62, DOI 10.1016/j.agee.2017.10.023
   ABMI (Alberta Biodiversity Monitoring Institute), 2016, 2014 HUM FOOTPR MAP
   ABMI (Alberta Biodiversity Monitoring Institute), 2016, TERR FIELD DAT COLL
   Adhikari K, 2016, GEODERMA, V262, P101, DOI 10.1016/j.geoderma.2015.08.009
   AESRD (Alberta Environment & Sustainable Resource Development), 2015, 2014 RANG REF AR REP
   Alberta Environment, 2006, AC DEP ASS ALB
   Alvaro-Fuentes J, 2012, AGR ECOSYST ENVIRON, V155, P87, DOI 10.1016/j.agee.2012.04.001
   [Anonymous], 2017, R LANG ENV STAT COMP
   [Anonymous], 4 GPSR USDA AGR RES
   [Anonymous], NAT SCI REP
   [Anonymous], GOVT ALBERTA PUB T
   [Anonymous], 2012, ABMI wall-to-wall Land Cover Map circa 2000
   Blair J., 2014, ECOLOGY ENV
   Brandani CB, 2015, GCB BIOENERGY, V7, P646, DOI 10.1111/gcbb.12175
   Brierley J.A., 2001, AGRASID 3 0 AGR REG
   Brown J, 2010, RANGELAND ECOL MANAG, V63, P147, DOI 10.2111/08-089.1
   Campbell EE, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/12/123004
   Cerri CEP, 2007, AGR ECOSYST ENVIRON, V122, P46, DOI 10.1016/j.agee.2007.01.007
   Chang XF, 2015, AGR ECOSYST ENVIRON, V212, P278, DOI 10.1016/j.agee.2015.07.014
   Chetner S., 2003, AGR ATL ALB 1971 200
   Cleveland CC, 1999, GLOBAL BIOGEOCHEM CY, V13, P623, DOI 10.1029/1999GB900014
   Cord AF, 2017, TRENDS ECOL EVOL, V32, P416, DOI 10.1016/j.tree.2017.03.003
   Cuddington K, 2013, ECOSPHERE, V4, DOI 10.1890/ES12-00178.1
   Daily GC, 2009, FRONT ECOL ENVIRON, V7, P21, DOI 10.1890/080025
   de Gruijter JJ, 2016, GEODERMA, V265, P120, DOI 10.1016/j.geoderma.2015.11.010
   Didan K., 2015, MOD13A2 MODIS/Terra Vegetation Indices 16Day L3 Global 1 km SIN Grid V006, DOI [DOI 10.5067/MODIS/MOD13A2.006, DOI 10.5067/MODIS/MOD13Q1.006, 10.5067/MODIS/MOD13A2.006]
   Dimassi B, 2018, GEODERMA, V311, P25, DOI 10.1016/j.geoderma.2017.09.038
   Faramarzi M, 2017, J HYDROL-REG STUD, V9, P48, DOI 10.1016/j.ejrh.2016.11.003
   Faramarzi M, 2015, ENVIRON MODELL SOFTW, V74, P48, DOI 10.1016/j.envsoft.2015.09.006
   Feng XM, 2011, ECOL INDIC, V11, P175, DOI 10.1016/j.ecolind.2009.07.002
   Gibson D.J., 2009, Grasses and Grassland Ecology.
   Gilmanov TG, 1997, ECOL MODEL, V96, P191, DOI 10.1016/S0304-3800(96)00067-1
   Grigera G, 2007, AGR SYST, V94, P637, DOI 10.1016/j.agsy.2007.01.001
   Gu YX, 2015, REMOTE SENS ENVIRON, V171, P291, DOI 10.1016/j.rse.2015.10.018
   Gu YX, 2013, ECOL INDIC, V24, P31, DOI 10.1016/j.ecolind.2012.05.024
   Gupta HV, 1998, WATER RESOUR RES, V34, P751, DOI 10.1029/97WR03495
   Havstad KM, 2007, ECOL ECON, V64, P261, DOI 10.1016/j.ecolecon.2007.08.005
   Hewins DB, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-19785-1
   HOLLAND EA, 1992, AM NAT, V140, P685, DOI 10.1086/285435
   Hou Y, 2013, J ENVIRON MANAGE, V127, pS117, DOI 10.1016/j.jenvman.2012.12.002
   Howe C, 2014, GLOBAL ENVIRON CHANG, V28, P263, DOI 10.1016/j.gloenvcha.2014.07.005
   Hungate BA, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1601880
   Jack BK, 2008, P NATL ACAD SCI USA, V105, P9465, DOI 10.1073/pnas.0705503104
   Jellinek S, 2019, J APPL ECOL, V56, P246, DOI 10.1111/1365-2664.13248
   Jönsson P, 2004, COMPUT GEOSCI-UK, V30, P833, DOI 10.1016/j.cageo.2004.05.006
   Kariyeva J, 2012, AGR ECOSYST ENVIRON, V162, P77, DOI 10.1016/j.agee.2012.08.006
   Kwon H, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0172861
   Lapp SL, 2013, QUATERN INT, V310, P47, DOI 10.1016/j.quaint.2012.09.011
   Li WH, 2018, CURR OPIN ENV SUST, V33, P124, DOI 10.1016/j.cosust.2018.05.008
   López-Marsico L, 2015, PLANT SOIL, V392, P155, DOI 10.1007/s11104-015-2452-2
   Lugato E, 2014, GLOBAL CHANGE BIOL, V20, P313, DOI 10.1111/gcb.12292
   Meersmans J, 2013, PEDOSPHERE, V23, P422, DOI 10.1016/S1002-0160(13)60035-1
   Murphy KL, 2002, J VEG SCI, V13, P395, DOI 10.1111/j.1654-1103.2002.tb02063.x
   Necpálová M, 2015, ENVIRON MODELL SOFTW, V66, P110, DOI 10.1016/j.envsoft.2014.12.011
   Niquil N, 2011, TREATISE ON ESTUARINE AND COASTAL SCIENCE, VOL 9: ESTUARINE AND COASTAL ECOSYSTEM MODELLING, P115
   Oelbermann M, 2011, AGROFOREST SYST, V82, P37, DOI 10.1007/s10457-010-9351-6
   Ogle SM, 2007, ECOL MODEL, V205, P453, DOI 10.1016/j.ecolmodel.2007.03.007
   Ogle SM, 2010, GLOBAL CHANGE BIOL, V16, P810, DOI 10.1111/j.1365-2486.2009.01951.x
   Parton W, 2004, J ARID ENVIRON, V59, P605, DOI 10.1016/j.jaridenv.2004.03.024
   Parton W. J., 1989, Ecology of arable land-perspectives and challenges. Proceedings of an International Symposium, 9-12 June 1987, Swedish Univ. Agric. Sci., Uppsala, Sweden., P99
   PARTON WJ, 1995, GLOBAL CHANGE BIOL, V1, P13, DOI 10.1111/j.1365-2486.1995.tb00002.x
   PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173, DOI 10.2136/sssaj1987.03615995005100050015x
   PARTON WJ, 1993, GLOBAL BIOGEOCHEM CY, V7, P785, DOI 10.1029/93GB02042
   PARTON WJ, 1988, BIOGEOCHEMISTRY, V5, P109, DOI 10.1007/BF02180320
   Rafique R, 2015, ECOL MODEL, V297, P196, DOI 10.1016/j.ecolmodel.2014.11.022
   Rafique R, 2013, WATER AIR SOIL POLL, V224, DOI 10.1007/s11270-013-1677-z
   Sándor R, 2018, SCI TOTAL ENVIRON, V642, P292, DOI 10.1016/j.scitotenv.2018.06.020
   SCHIMEL DS, 1994, GLOBAL BIOGEOCHEM CY, V8, P279, DOI 10.1029/94GB00993
   Schulp CJE, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0109643
   Smith P, 1997, GEODERMA, V81, P153, DOI 10.1016/S0016-7061(97)00087-6
   Smith WN, 2009, CLIMATIC CHANGE, V93, P319, DOI 10.1007/s10584-008-9493-y
   Smith WN, 1997, CAN J SOIL SCI, V77, P219, DOI 10.4141/S96-113
   Stamp R. M., 2008, CANADIAN ENCY
   VandenBygaart AJ, 2008, CAN J SOIL SCI, V88, P671, DOI 10.4141/CJSS07015
   Wang FG, 2013, ECOL MODEL, V259, P16, DOI 10.1016/j.ecolmodel.2013.03.008
   Wang TL, 2012, J APPL METEOROL CLIM, V51, P16, DOI 10.1175/JAMC-D-11-043.1
   Wang XY, 2014, RANGELAND ECOL MANAG, V67, P333, DOI 10.2111/REM-D-14-00006.1
   Wang YH, 2008, ECOL MODEL, V217, P72, DOI 10.1016/j.ecolmodel.2008.05.010
   Wiesmeier M, 2019, GEODERMA, V333, P149, DOI 10.1016/j.geoderma.2018.07.026
   Xiong X, 2015, GEODERMA, V251, P105, DOI 10.1016/j.geoderma.2015.03.028
NR 81
TC 6
Z9 6
U1 2
U2 65
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD AUG 25
PY 2019
VL 680
BP 151
EP 168
DI 10.1016/j.scitotenv.2019.05.083
PG 18
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA HZ5AQ
UT WOS:000468863400016
PM 31103894
DA 2025-01-10
ER

PT J
AU Uppanunchai, A
   Chitmanat, C
   Lebel, L
AF Uppanunchai, Anuwat
   Chitmanat, Chanagun
   Lebel, Louis
TI Mainstreaming climate change adaptation into inland aquaculture policies
   in Thailand
SO CLIMATE POLICY
LA English
DT Article
DE aquaculture policy; climate change; climate sensitivity; extreme events;
   inland aquaculture; mainstreaming; Thailand
ID LEAST DEVELOPED-COUNTRIES; TILAPIA CAGE CULTURE; NORTHERN THAILAND;
   IMPACTS; VULNERABILITY; PERCEPTIONS; COMMUNITIES; MANAGEMENT;
   BANGLADESH; FISHERIES
AB While there have been many pilot projects on adaptation undertaken in the fisheries and aquaculture sector, state policies are only just beginning to address let alone refer to climate change. This study explores the climate-related content, climate sensitivities, and opportunities to incorporate climate change concerns in a set of aquaculture policies by the government of Thailand. The analysis is based on content analysis of policy documents and in-depth interviews with 14 officials that had roles in the design or implementation of 8 Department of Fisheries policies. The Aquaculture Master Plan 2011-2016 and the now abandoned Tilapia Strategy refer directly to climate variability or change. The Master Plan also suggests measures or strategies, such as investment in research, and the transfer of technologies, which would be helpful to sustainability and adaptation. Other policies suggest, or at the very least include, practices which could contribute to strengthening management of climate-related risks, for example: a registration policy included provisions for compensation; extension programme policy recognizes the importance of extreme events; and a standards policy gives guidance on site selection and water management. Most existing aquaculture policies appear to be sensitive to the impacts of climate change; for instance, the zoning policy is sensitive to spatial shifts in climate. Stakeholders had ideas on how policies could be made more robust; in the case of zoning, by periodically reviewing boundaries and adjusting them as necessary.
   POLICY RELEVANCE
   This study is one of the first evaluations of the coverage and sensitivity of aquaculture policies to climate change. It shows that while existing policies in Thailand are beginning to refer explicitly to climate change, they do not yet include much in the way of adaptation responses, underlining the need for identifying entry points as has been done in this analysis. Further mainstreaming is one option; another possibility is to adopt a more segregated approach, at least initially, and to collect various policy ideas under a new strategic policy for the aquaculture sector as a whole.
C1 [Uppanunchai, Anuwat] Minist Agr & Cooperat, Dept Fisheries, Lamphun Inland Fisheries Res & Dev Ctr, Bangkok, Thailand.
   [Chitmanat, Chanagun] Maejo Univ, Fac Fisheries Technol & Aquat Resources, Chiang Mai, Thailand.
   [Lebel, Louis] Chiang Mai Univ, Fac Social Sci, USER, Chiang Mai, Thailand.
C3 Ministry of Agriculture & Cooperatives - Thailand; Maejo University;
   Chiang Mai University
RP Lebel, L (corresponding author), Chiang Mai Univ, Fac Social Sci, USER, Chiang Mai, Thailand.
EM llebel@loxinfo.co.th
FU International Development Research Centre, Ottawa, Canada [107087]
FX The work was carried out with the aid of a grant from the International
   Development Research Centre, Ottawa, Canada [grant number 107087] as a
   contribution to the AQUADAPT project.
CR [Anonymous], 2012, 11 NAT EC SOC DEV PL
   [Anonymous], 2014, STAT WORLD FISH AQ
   [Anonymous], 2006, EFFECTS CLIMATE CHAN
   [Anonymous], 2009, INT CLIM CHANG AD DE
   Ayers JM, 2014, WIRES CLIM CHANGE, V5, P37, DOI 10.1002/wcc.226
   Badjeck MC, 2010, MAR POLICY, V34, P375, DOI 10.1016/j.marpol.2009.08.007
   Beach Robert H., 2008, Aquaculture Economics and Management, V12, P25, DOI 10.1080/13657300801959613
   Bell JD, 2013, NAT CLIM CHANGE, V3, P591, DOI 10.1038/NCLIMATE1838
   Belton B, 2011, DEV POLICY REV, V29, P459, DOI 10.1111/j.1467-7679.2011.00542.x
   Béné C, 2016, WORLD DEV, V79, P177, DOI 10.1016/j.worlddev.2015.11.007
   Bennett NJ, 2015, CLIM DEV, V7, P124, DOI 10.1080/17565529.2014.886993
   Brouwer S, 2013, ENVIRON PLANN C, V31, P134, DOI 10.1068/c11134
   Brugere C., 2010, 542 FAO UN
   Burton I, 2002, CLIM POLICY, V2, P145, DOI 10.1016/S1469-3062(02)00038-4
   Dany V, 2017, ENVIRON DEV SUSTAIN, V19, P1167, DOI 10.1007/s10668-016-9788-5
   Dany V, 2016, CLIM POLICY, V16, P237, DOI 10.1080/14693062.2014.1003523
   Das MK, 2013, AQUAT ECOSYST HEALTH, V16, P415, DOI 10.1080/14634988.2013.851585
   De Silva SS, 2012, BIODIVERS CONSERV, V21, P3187, DOI 10.1007/s10531-012-0360-9
   DeSilva SS, 2010, SUCCESS STORIES IN ASIAN AQUACULTURE, P1
   DOF, 2013, STRAT PLAN WORK CAP
   DOF, 2013, FISH STAT THAIL 2554
   DOF, 2011, DEV STRAT TIL FARM 2
   FAO, 2014, 1088 FAO UN
   Friend R, 2014, URBAN CLIM, V7, P6, DOI 10.1016/j.uclim.2013.08.001
   Huq S, 2004, CLIM POLICY, V4, P25
   Lebel L, 2011, REG ENVIRON CHANGE, V11, P45, DOI 10.1007/s10113-010-0118-4
   Lebel L, 2010, ENVIRON SCI POLICY, V13, P291, DOI 10.1016/j.envsci.2010.03.005
   Lebel P, 2015, INT J GLOBAL WARM, V8, P534, DOI 10.1504/IJGW.2015.073054
   Lebel P, 2015, INT J CLIM CHANG STR, V7, P476, DOI 10.1108/IJCCSM-01-2014-0018
   Lebel P, 2015, RISK MANAG-UK, V17, P1, DOI 10.1057/rm.2015.4
   Li S, 2016, AQUAC RES, V47, P1537, DOI 10.1111/are.12614
   MOAC, 2013, SUIT ZON AQ
   MOAC, 2004, 74052004 MOAC TAS NA
   NRMMC, 2010, NAT CLIM CHANG ACT P
   ONEP, 2010, THAIL 2 NAT COMM UN
   Pauw WP, 2015, CLIM POLICY, V15, P583, DOI 10.1080/14693062.2014.953906
   Pickering TimothyD., 2011, Vulnerability of aquaculture in the tropical pacific to climate change. Vulnerability of Tropical Pacific Fisheries and Aquaculture to Climate Change, P647
   Rattanachot W, 2015, TRANSPORT POLICY, V41, P159, DOI 10.1016/j.tranpol.2015.03.001
   Saito N, 2013, MITIG ADAPT STRAT GL, V18, P825, DOI 10.1007/s11027-012-9392-4
   Scottish Government, 2013, CLIM READ SCOTL SCOT
   Shameem MIM, 2015, CLIMATIC CHANGE, V133, P253, DOI 10.1007/s10584-015-1470-7
   Soto, 2009, CLIMATE CHANGE IMPLI
   Sriyasak P., 2015, International Aquatic Research, V7, P287
   Tennekes J, 2014, J ENVIRON POL PLAN, V16, P241, DOI 10.1080/1523908X.2013.836961
   Uppanunchai A, 2015, ENVIRON MANAGE, V56, P859, DOI 10.1007/s00267-015-0547-4
   VSG, 2008, FISH VICT MAN REP SE, V66
   Yamprayoon J, 2010, J WORLD AQUACULT SOC, V41, P274, DOI 10.1111/j.1749-7345.2010.00355.x
NR 47
TC 13
Z9 14
U1 1
U2 35
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PY 2018
VL 18
IS 1
BP 86
EP 98
DI 10.1080/14693062.2016.1242055
PG 13
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA FZ0PH
UT WOS:000427272500009
DA 2025-01-10
ER

PT J
AU Masud, MB
   Khaliq, MN
   Wheater, HS
AF Masud, M. B.
   Khaliq, M. N.
   Wheater, H. S.
TI Projected changes to short- and long-duration precipitation extremes
   over the Canadian Prairie Provinces
SO CLIMATE DYNAMICS
LA English
DT Article
DE Climate change; Precipitation extremes; Regional frequency analysis;
   NARCCAP; Canadian Prairie Provinces
ID MULTIMODEL ENSEMBLE; CLIMATE MODELS; FUTURE CHANGES; TEMPERATURE;
   PERFORMANCE; DROUGHTS; EUROPE
AB The effects of climate change on April-October short- and long-duration precipitation extremes over the Canadian Prairie Provinces were evaluated using a multi-Regional Climate Model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by the National Centre for Environmental Prediction (NCEP) reanalysis II product for the 1981-2000 period and those driven by four Atmosphere-Ocean General Circulation Models (AOGCMs) for the current 1971-2000 and future 2041-2070 periods (i.e. a total of 11 current-to-future period simulation pairs). A regional frequency analysis approach was used to develop 2-, 5-, 10-, 25-, and 50-year return values of precipitation extremes from NCEP and AOGCM-driven current and future period simulations that respectively were used to study the performance of RCMs and projected changes for selected return values at regional, grid-cell and local scales. Performance errors due to internal dynamics and physics of RCMs studied for the 1981-2000 period reveal considerable variation in the performance of the RCMs. However, the performance errors were found to be much smaller for RCM ensemble averages than for individual RCMs. Projected changes in future climate to selected regional return values of short-duration (e.g. 15- and 30-min) precipitation extremes and for longer return periods (e.g. 50-year) were found to be mostly larger than those to the longer duration (e.g. 24- and 48-h) extremes and short return periods (e.g. 2-year). Overall, projected changes in precipitation extremes were larger for southeastern regions followed by southern and northern regions and smaller for southwestern and western regions of the study area. The changes to return values were also found to be statistically significant for the majority of the RCM-AOGCM simulation pairs. These projections might be useful as a key input for the future planning of urban drainage infrastructure and development of strategic climate change adaptation measures.
C1 [Masud, M. B.; Khaliq, M. N.; Wheater, H. S.] Univ Saskatchewan, Global Inst Water Secur, 11 Innovat Blvd, Saskatoon, SK S7N 3H5, Canada.
   [Masud, M. B.; Khaliq, M. N.; Wheater, H. S.] Univ Saskatchewan, Sch Environm & Sustainabil, 11 Innovat Blvd, Saskatoon, SK S7N 3H5, Canada.
   [Khaliq, M. N.] Natl Res Council Canada, Ocean Coastal & River Engn, 1200 Montreal Rd,Bldg M-32, Ottawa, ON K1A 0R6, Canada.
C3 University of Saskatchewan; Global Institute for Water Security;
   University of Saskatchewan; National Research Council Canada
RP Masud, MB (corresponding author), Univ Saskatchewan, Global Inst Water Secur, 11 Innovat Blvd, Saskatoon, SK S7N 3H5, Canada.; Masud, MB (corresponding author), Univ Saskatchewan, Sch Environm & Sustainabil, 11 Innovat Blvd, Saskatoon, SK S7N 3H5, Canada.
EM mbm806@mail.usask.ca
FU Canada Excellence Research Chair in Water Security and School of
   Environment and Sustainability, University of Saskatchewan
FX The authors would like to thank the NARCCAP project team for the RCM
   simulations used in this study. The financial support from the Canada
   Excellence Research Chair in Water Security and School of Environment
   and Sustainability, University of Saskatchewan, is also acknowledged.
   The language editing support provided by Michelle-Andre Martel from the
   GIWS is much appreciated. We would like to thank two anonymous referees
   for their very useful comments which helped improve the quality of
   various analyses presented in the paper.
CR [Anonymous], 1993, An Introduction To The Bootstrap
   [Anonymous], 2013, CLIMATE CHANGE 2013
   [Anonymous], 2009, Eos, Transactions American Geophysical Union, DOI [DOI 10.1029/2009EO360002, 10.1175/BAMS-D-11-00223.1]
   [Anonymous], 2001, INTRO STAT MODELING
   [Anonymous], 1997, REGIONAL FREQUENCY A, DOI DOI 10.1017/CBO9780511529443
   Asong ZE, 2014, STOCH ENV RES RISK A, DOI [10.1007/s0047-014-0918-z, DOI 10.1007/S0047-014-0918-Z]
   Asong ZE, 2016, CLIM DYNAM, V47, P2901, DOI 10.1007/s00382-016-3004-z
   Beniston M, 2007, CLIMATIC CHANGE, V81, P71, DOI 10.1007/s10584-006-9226-z
   Bevington P.R., 2002, DATA REDUCTION ERROR, Vthird, P320
   Boé J, 2007, INT J CLIMATOL, V27, P1643, DOI 10.1002/joc.1602
   Caldwell P, 2010, J APPL METEOROL CLIM, V49, P2147, DOI 10.1175/2010JAMC2388.1
   Christensen J.H., 2009, 2009: ENSEMBLES: Climate change and its impacts: Summary of research and results from the ENSEMBLES project, P47
   Christensen JH, 2007, CLIMATIC CHANGE, V81, P1, DOI 10.1007/s10584-006-9211-6
   de Elía R, 2008, CLIM DYNAM, V30, P113, DOI 10.1007/s00382-007-0288-z
   DEY B, 1982, J CLIMATOL, V2, P233, DOI 10.1002/joc.3370020303
   Foley AM, 2010, PROG PHYS GEOG, V34, P647, DOI 10.1177/0309133310375654
   Gan TY, 2000, WATER RESOUR MANAG, V14, P111, DOI 10.1023/A:1008195827031
   Ganguli P, 2016, J AM WATER RESOUR AS, V52, P138, DOI 10.1111/1752-1688.12374
   Gao Y, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/4/044025
   Gao YH, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2010JD015278
   Giorgi F, 2015, ANNU REV ENV RESOUR, V40, P467, DOI 10.1146/annurev-environ-102014-021217
   Green PJ, 1993, NONPARAMTERIC REGRES
   Haddad K, 2014, HDB ENG HYDROLOGY MO, P634
   Hagedorn R, 2005, TELLUS A, V57, P219, DOI 10.1111/j.1600-0870.2005.00103.x
   Hall MJ, 2004, HYDROL EARTH SYST SC, V8, P235, DOI 10.5194/hess-8-235-2004
   Hanel M, 2012, J HYDROL, V412, P141, DOI 10.1016/j.jhydrol.2011.02.007
   Hare F.K., 1979, CLIMATE CANADA, V2nd
   Hogg EH, 2000, J CLIMATE, V13, P4229, DOI 10.1175/1520-0442(2000)013<4229:PFODFP>2.0.CO;2
   Jeong DI, 2016, CLIM DYNAM, V47, P1351, DOI 10.1007/s00382-015-2906-5
   Jeong DI, 2016, CLIM DYNAM, V46, P3163, DOI 10.1007/s00382-015-2759-y
   Jeong DI, 2014, CLIMATIC CHANGE, V127, P289, DOI 10.1007/s10584-014-1248-3
   Khaliq MN, 2015, CLIM DYNAM, V44, P255, DOI 10.1007/s00382-014-2235-0
   Khaliq MN, 2009, J HYDROL, V368, P117, DOI 10.1016/j.jhydrol.2009.01.035
   Khaliq MN, 2015, CLIMATIC CHANGE, P10
   Knutti R, 2013, NAT CLIM CHANGE, V3, P369, DOI [10.1038/nclimate1716, 10.1038/NCLIMATE1716]
   Kumar D, 2014, CLIM DYNAM, V43, P2491, DOI 10.1007/s00382-014-2070-3
   Mailhot A, 2012, INT J CLIMATOL, V32, P1151, DOI 10.1002/joc.2343
   Masud MB, 2017, CLIM DYNAM, V48, P2685, DOI 10.1007/s00382-016-3232-2
   May W, 2008, CLIM DYNAM, V30, P581, DOI 10.1007/s00382-007-0309-y
   Mearns LO, 2012, B AM METEOROL SOC, V93, P1337, DOI 10.1175/BAMS-D-11-00223.1
   Mladjic B, 2011, J CLIMATE, V24, P2565, DOI 10.1175/2010JCLI3937.1
   Monette A, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2012JD017543
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Nikulin G, 2011, TELLUS A, V63, P41, DOI 10.1111/j.1600-0870.2010.00466.x
   Phillips David., 1990, CLIMATES CANADA
   Poitras V, 2011, J HYDROMETEOROL, V12, P1395, DOI 10.1175/JHM-D-10-05002.1
   Schiermeier Q, 2013, NATURE, V496, P284, DOI 10.1038/496284a
   Sillmann J, 2013, J GEOPHYS RES-ATMOS, V118, P2473, DOI 10.1002/jgrd.50188
   Sushama L, 2006, INT J CLIMATOL, V26, P2141, DOI 10.1002/joc.1362
   Sushama L, 2010, GLOBAL PLANET CHANGE, V74, P1, DOI 10.1016/j.gloplacha.2010.07.004
   Tebaldi C, 2007, PHILOS T R SOC A, V365, P2053, DOI 10.1098/rsta.2007.2076
   van Pelt SC, 2012, HYDROL EARTH SYST SC, V16, P4517, DOI 10.5194/hess-16-4517-2012
   Wehner MF, 2013, CLIM DYNAM, V40, P59, DOI 10.1007/s00382-012-1393-1
   Wheater H, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2012.0409
   Wuebbles D, 2014, B AM METEOROL SOC, V95, P571, DOI 10.1175/BAMS-D-12-00172.1
NR 55
TC 12
Z9 13
U1 0
U2 24
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 0930-7575
EI 1432-0894
J9 CLIM DYNAM
JI Clim. Dyn.
PD SEP
PY 2017
VL 49
IS 5-6
BP 1597
EP 1616
DI 10.1007/s00382-016-3404-0
PG 20
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA FF2HJ
UT WOS:000408718200007
DA 2025-01-10
ER

PT J
AU Mi, CR
   Falk, H
   Guo, YM
AF Mi, Chunrong
   Falk, Huettmann
   Guo, Yumin
TI Climate envelope predictions indicate an enlarged suitable wintering
   distribution for Great Bustards (<i>Otis tarda dybowskii</i>) in China
   for the 21st century
SO PEERJ
LA English
DT Article
DE Climate change; Species distribution models (SDMs); Great Bustard (Otis
   tarda dybowskii); Random Forest; China
ID SPECIES DISTRIBUTION MODELS; IMPACTS
AB The rapidly changing climate makes humans realize that there is a critical need to incorporate climate change adaptation into conservation planning. Whether the wintering habitats of Great Bustards (Otis tarda dybowskii), a globally endangered migratory subspecies whose population is approximately 1,500-2,200 individuals in China, would be still suitable in a changing climate environment, and where this could be found, is an important protection issue. In this study, we selected the most suitable species distribution model for bustards using climate envelopes from four machine learning models, combining two modelling approaches (TreeNet and Random Forest) with two sets of variables (correlated variables removed or not). We used common evaluation methods area under the receiver operating characteristic curves (AUC) and the True Skill Statistic (TSS) as well as independent test data to identify the most suitable model. As often found elsewhere, we found Random Forest with all environmental variables outperformed in all assessment methods. When we projected the best model to the latest IPCC-CMIP5 climate scenarios (Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 in three Global Circulation Models (GCMs)), and averaged the project results of the three models, we found that suitable wintering habitats in the current bustard distribution would increase during the 21st century. The Northeast Plain and the south of North China were projected to become two major wintering areas for bustards. However, the models suggest that some currently suitable habitats will experience a reduction, such as Dongting Lake and Poyang Lake in the Middle and Lower Yangtze River Basin. Although our results suggested that suitable habitats in China would widen with climate change, greater efforts should be undertaken to assess and mitigate unstudied human disturbance, such as pollution, hunting, agricultural development, infrastructure construction, habitat fragmentation, and oil and mine exploitation. All of these are negatively and intensely linked with global change.
C1 [Mi, Chunrong; Guo, Yumin] Beijing Forestry Univ, Coll Nat Conservat, Beijing, Peoples R China.
   [Mi, Chunrong] Univ Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China.
   [Falk, Huettmann] Univ Alaska Fairbanks, Inst Arctic Biol, Dept Biol & Wildlife, EWHALE Lab, Fairbanks, AK USA.
C3 Beijing Forestry University; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS; Institute of Geographic Sciences &
   Natural Resources Research, CAS; University of Alaska System; University
   of Alaska Fairbanks
RP Guo, YM (corresponding author), Beijing Forestry Univ, Coll Nat Conservat, Beijing, Peoples R China.
EM guoyumin@bjfu.edu.cn
FU State Forestry Administration of China
FX This research was funded by The State Forestry Administration of China.
   The funders had no role in study design, data collection and analysis,
   decision to publish, or preparation of the manuscript.
CR Allouche O, 2006, J APPL ECOL, V43, P1223, DOI 10.1111/j.1365-2664.2006.01214.x
   Alonso Juan C., 2010, Chinese Birds, V1, P141
   [Anonymous], 2002, Chinese Cranes, Rails and Bustard
   Araújo MB, 2006, SCIENCE, V313, P1396, DOI 10.1126/science.1131758
   Araújo MB, 2006, J BIOGEOGR, V33, P1677, DOI 10.1111/j.1365-2699.2006.01584.x
   Araújo MB, 2012, ECOLOGY, V93, P1527, DOI 10.1890/11-1930.1
   Baltensperger AP, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0132054
   Beiring M., 2014, THESIS U VIENNA AUST
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Breiman L, 2001, STAT SCI, V16, P199, DOI 10.1214/ss/1009213726
   Chan S, 1998, ACTION PLAN CONSERVA
   Collar N. J., 2001, THREATENED BIRDS ASI
   Costa GC, 2010, BIODIVERS CONSERV, V19, P883, DOI 10.1007/s10531-009-9746-8
   Czaplewski R.L., 1994, Variance Approximations for Assessments of Classification Accuracy, pRM
   Drew CA, 2011, PREDICTIVE SPECIES AND HABITAT MODELING IN LANDSCAPE ECOLOOGY: CONCEPTS AND APPLICATIONS, P291, DOI 10.1007/978-1-4419-7390-0_15
   DYER JM, 1995, ECOL MODEL, V79, P199, DOI 10.1016/0304-3800(94)00038-J
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Friedman JH, 2002, COMPUT STAT DATA AN, V38, P367, DOI 10.1016/S0167-9473(01)00065-2
   Goroshko OA., 2010, 1 INT S CONS GREAT B, P10
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Hole DG, 2009, ECOL LETT, V12, P420, DOI 10.1111/j.1461-0248.2009.01297.x
   Hu JH, 2010, OECOLOGIA, V164, P555, DOI 10.1007/s00442-010-1732-z
   Hughes L, 2000, TRENDS ECOL EVOL, V15, P56, DOI 10.1016/S0169-5347(99)01764-4
   Iverson LR, 1998, ECOL MONOGR, V68, P465, DOI 10.1890/0012-9615(1998)068[0465:PAOTSF]2.0.CO;2
   Jiang J, 2003, THESIS NE FORESTRY U
   Kennerley P., 1987, HONG KONG BIRD REPOR, P97
   Kong You-Qin, 2005, Chinese Journal of Zoology, V40, P111
   Liu B., 1997, NATURAL RESOURCES ST, V4, P61
   Liu CR, 2005, ECOGRAPHY, V28, P385, DOI 10.1111/j.0906-7590.2005.03957.x
   Masatomi Y, 2007, POPUL ECOL, V49, P297, DOI 10.1007/s10144-007-0048-2
   Meng D., 2010, 1 CHIN INT SEM PROT
   Pearce J, 2000, ECOL MODEL, V133, P225, DOI 10.1016/S0304-3800(00)00322-7
   Pearson RG, 2004, ECOGRAPHY, V27, P285, DOI 10.1111/j.0906-7590.2004.03740.x
   Pearson RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361, DOI 10.1046/j.1466-822X.2003.00042.x
   Pearson RG, 2007, J BIOGEOGR, V34, P102, DOI 10.1111/j.1365-2699.2006.01594.x
   Peterson AT, 2002, NATURE, V416, P626, DOI 10.1038/416626a
   Prasad AM, 2006, ECOSYSTEMS, V9, P181, DOI 10.1007/s10021-005-0054-1
   Raab R, 2012, BIRD CONSERV INT, V22, P299, DOI 10.1017/S0959270911000463
   Stanton JC, 2012, METHODS ECOL EVOL, V3, P349, DOI 10.1111/j.2041-210X.2011.00157.x
   Strange N, 2011, BIOL CONSERV, V144, P2968, DOI 10.1016/j.biocon.2011.08.022
   Sykes MT, 1996, CLIMATIC CHANGE, V34, P161, DOI 10.1007/BF00224628
   Tanneberger F, 2010, IBIS, V152, P347, DOI 10.1111/j.1474-919X.2010.01016.x
   王强, 1999, [电力电子技术, Power Electronics], P1
   WOODWARD FI, 1987, VEGETATIO, V69, P189, DOI 10.1007/BF00038700
   Wu Wei-wei, 2012, Journal of Ecology and Rural Environment, V28, P243
   Wu X. Ben, 2000, Landscape and Urban Planning, V51, P11, DOI 10.1016/S0169-2046(00)00095-5
   Wu Y, 2001, ANHUI FORESTRY SCI T, V4, P30
   Xia CW, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0042528
   Yang Chen, 2007, Acta Zoologica Sinica, V53, P215
   Zhai T, 2003, ACTA ECOLOGICA SINIC, V9, P1353
   Zhang Lei, 2011, Chinese Journal of Plant Ecology, V35, P1091, DOI 10.3724/SP.J.1258.2011.01091
NR 53
TC 26
Z9 28
U1 3
U2 57
PU PEERJ INC
PI LONDON
PA 341-345 OLD ST, THIRD FLR, LONDON, EC1V 9LL, ENGLAND
SN 2167-8359
J9 PEERJ
JI PeerJ
PD FEB 1
PY 2016
VL 4
AR e1630
DI 10.7717/peerj.1630
PG 14
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA DC7NY
UT WOS:000369408400003
PM 26855870
OA Green Submitted, Green Published, gold
DA 2025-01-10
ER

PT J
AU Solar, A
   Stampar, F
AF Solar, Anita
   Stampar, Franci
TI Performance of Hazelnut Cultivars from Oregon in Northeastern Slovenia
SO HORTTECHNOLOGY
LA English
DT Article
DE Corylus avellana; phenology; nut and kernel quality; weevil; climatic
   adaptation
AB Three cultivars and three selections from Oregon State University's (OSU) hazelnut (Corylus avellana) breeding program were investigated in a yield trial during the period 1997 to 2007 in northeastern Slovenia with the Italian 'Tonda Gentile delle Langhe' as the standard. All OSU genotypes had higher cumulative yield and yield efficiency than the standard, all exceeded the kernel percentage of 45%, and all had at least 76% good kernels. OSU 228.084 is promising due to good vegetative growth and the highest yields and yield efficiency. It set many catkins and had the highest percentage of marketable kernels. Its disadvantage could be early flowering and large yield reduction due to low temperatures in early spring. Cultivars/selections that were late flowering ('Lewis' and OSU 244.001) had longer durations of pistillate flower receptivity (Willamette' and OSU 238.125) and had lower sensitivity to unfavorable weather conditions in early spring ('Clark') expressed the best climatic adaptation. Unmarketable nuts were mainly blanks and poorly filled nuts. 'Clark' is precocious early maturing, and well-suited to the kernel market. Due to its upright growth habit, 'Clark' could be planted more densely than others. 'Lewis' yielded well and had medium yield efficiency, and is suitable for in-shell and kernel markets. Excellent pellicle removal was observed in OSU 244.001 and OSU 238.125. All OSU cultivars and selections showed relatively low susceptibility to hazelnut weevil (Balaninus nucum).
C1 [Solar, Anita] Univ Ljubljana, Dept Agron, Biotech Fac, Expt Field Nut Crops Maribor, SI-2000 Maribor, Slovenia.
   [Stampar, Franci] Univ Ljubljana, Dept Agron, Biotech Fac, SI-1000 Ljubljana, Slovenia.
C3 University of Maribor; University of Ljubljana; University of Ljubljana
RP Solar, A (corresponding author), Univ Ljubljana, Dept Agron, Biotech Fac, Expt Field Nut Crops Maribor, Vinarska 14, SI-2000 Maribor, Slovenia.
EM anita.solar@bf.uni-lj.si
FU Slovenian Ministry of Higher Education, Science, and Technology
   [P4-0013-0481]
FX This work is a part of the program Horticulture No. P4-0013-0481 granted
   by the Slovenian Ministry of Higher Education, Science, and Technology.
CR AliNiazee MT, 1997, ACTA HORTIC, P469, DOI 10.17660/ActaHortic.1997.445.60
   [Anonymous], 2003, QUALIFIED HLTH CLAIM
   Baldwin B, 2005, ACTA HORTIC, P47, DOI 10.17660/ActaHortic.2005.686.4
   Botu I., 2005, ACTA HORTIC, V686, P91
   Germain E., 2004, Le noisetier
   GERMAIN E, 1981, P 1 C RECH FRUIT BOR, P197
   Grau P, 2005, ACTA HORTIC, P57, DOI 10.17660/ActaHortic.2005.686.5
   *HAZ COUNC, 2009, HAZ NUTR OV
   *INT PLANT GEN RES, 2008, DESCR HAZ COR AV L
   Karadeniz T, 1997, ACTA HORTIC, P91, DOI 10.17660/ActaHortic.1997.445.13
   MCCLUSKEY R, 2008, 7 INT C HAZ 23 27 JU, P22
   McCluskey RL, 2001, ACTA HORTIC, P89, DOI 10.17660/ActaHortic.2001.556.11
   McCluskey RL, 1997, ACTA HORTIC, P13, DOI 10.17660/ActaHortic.1997.445.2
   Mehlenbacher SA, 1997, THEOR APPL GENET, V94, P360, DOI 10.1007/s001220050424
   Mehlenbacher SA, 2004, HORTSCIENCE, V39, P1498, DOI 10.21273/HORTSCI.39.6.1498
   Mehlenbacher SA, 2000, HORTSCIENCE, V35, P314, DOI 10.21273/HORTSCI.35.2.314
   Mehlenbacher SA, 2001, HORTSCIENCE, V36, P995, DOI 10.21273/HORTSCI.36.5.995
   Mehlenbacher SA., 1991, ACTA HORTIC, V290, P791, DOI DOI 10.17660/ACTAHORTIC.1991.290.18
   MEHLENBACHER SA, 2008, 7 INT C HAZ 23 27 JU, P15
   *MOP, 2009, POVZ KLIM AN LETN ME
   *MOP, 2009, KLIM POD MAR REF OBD
   *NAT ARB, 2009, USDA PLANT HARD ZON
   Okay AN, 2001, ACTA HORTIC, P235, DOI 10.17660/ActaHortic.2001.556.33
   ROMISONDO P, 1976, P 1 C INT ALM AV REU, P97
   ROVIRA M, 2001, ACTA HORTIC, V556, P171
   ROVIRA M, 2005, ACTA HORTIC, V686, P41
   Santos A, 2001, ACTA HORTIC, P97, DOI 10.17660/ActaHortic.2001.556.12
   SCHEPERS HTA, 2005, ACTA HORTIC, V686, P87
   SOLAR A, 2008, 7 INT C HAZ 23 27 JU, P109
   THOMPSON MM, 1974, P NUT GROWERS SOC OR, V57, P47
   TOUS J, 2009, WORLD HAZELNUT PRODU
   Valentini N, 2005, ACTA HORTIC, P485, DOI 10.17660/ActaHortic.2005.686.66
   Valentini N, 2001, ACTA HORTIC, P103, DOI 10.17660/ActaHortic.2001.556.13
   XIE M, 2005, ACTA HORTIC, V686, P65
NR 34
TC 12
Z9 15
U1 0
U2 5
PU AMER SOC HORTICULTURAL SCIENCE
PI ALEXANDRIA
PA 113 S WEST ST, STE 200, ALEXANDRIA, VA 22314-2851 USA
SN 1063-0198
EI 1943-7714
J9 HORTTECHNOLOGY
JI HortTechnology
PD JUL-SEP
PY 2009
VL 19
IS 3
BP 653
EP 659
DI 10.21273/HORTSCI.19.3.653
PG 7
WC Horticulture
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 613XE
UT WOS:000279016800027
OA Bronze
DA 2025-01-10
ER

PT J
AU Gschweng, M
   Eisenbarth, C
   Haase, W
   Sawodny, O
   Böhm, M
AF Gschweng, Melanie
   Eisenbarth, Christina
   Haase, Walter
   Sawodny, Oliver
   Boehm, Michael
TI Modellierung und Analyse textiler Fassaden mit vertikalem
   Wassertransport
SO AT-AUTOMATISIERUNGSTECHNIK
LA Spanish
DT Article
DE modeling; distributed parameter systems; operational strategy; numerical
   simulation; modeling; distributed parameter systems; operational
   strategy; numerical simulation
AB Climate adaptation facades (CAF) can mitigate urban heat islands in densely built-up areas. Due to rainwater adsorption and water evaporation on hot days, their application is particularly suitable for high rise buildings with large facade surfaces. To investigate the dynamic system behavior, an CAF is modeled phenomenologically utilizing partial differential equations. The model is derived on the basis of a transport equation and energy balances. Recommendations for operating strategies are made by analyzing stationary states.
C1 [Gschweng, Melanie; Sawodny, Oliver; Boehm, Michael] Univ Stuttgart, Inst Syst Dynam, Waldburgstr 19, D-70563 Stuttgart, Germany.
   [Eisenbarth, Christina; Haase, Walter] Univ Stuttgart, Inst Leichtbau Entwerfen & Konstruieren, Pfaffenwaldring 7, D-70569 Stuttgart, Germany.
C3 University of Stuttgart; University of Stuttgart
RP Gschweng, M (corresponding author), Univ Stuttgart, Inst Syst Dynam, Waldburgstr 19, D-70563 Stuttgart, Germany.
EM melanie.gschweng@isys.uni-stuttgart.de;
   christina.eisenbarth@ilek.uni-stuttgart.de;
   walter.haase@ilek.uni-stuttgart.de;
   oliver.sawodny@isys.uni-stuttgart.de;
   michael.boehm@isys.uni-stuttgart.de
RI Böhm, Michael/C-3638-2011
FU Gefordert durch die Deutsche Forschungsgemeinschaft (DFG) [279064222,
   SFB1244, B04, C01]
FX Gefordert durch die Deutsche Forschungsgemeinschaft (DFG) - Projekt-ID
   279064222 - SFB1244, B04 und C01.
CR Alexandri E, 2007, BUILD ENVIRON, V42, P2835, DOI 10.1016/j.buildenv.2006.07.004
   Bakhshoodeh R, 2022, ENERG BUILDINGS, V270, DOI 10.1016/j.enbuild.2022.112223
   Blandini L., 2024, Faade Design Challenges and Future Perspective
   Del Serrone G, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13101586
   Eisenbarth C, 2022, STRUCT ARCHITECT, V2, P739, DOI 10.1201/9781003023555-88
   Eisenbarth Christina, 2022, Civil Engineering Design, V4, P14, DOI 10.1002/cend.202200003
   Gschweng M., 2024, 2024 IEEE SICE INT S
   Heaviside Clare, 2017, Curr Environ Health Rep, V4, P296, DOI 10.1007/s40572-017-0150-3
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Rentz Anja, 2022, 2022 IEEE Conference on Control Technology and Applications (CCTA), P418, DOI 10.1109/CCTA49430.2022.9966186
   Schfer M., 2022, Computational Engineering Introduction to Numerical Methods, V2nd ed, P1374
   Shen C, 2016, SOL ENERGY, V137, P55, DOI 10.1016/j.solener.2016.07.055
   Sun YL, 2022, ADV MATER TECHNOL-US, V7, DOI 10.1002/admt.202100803
   Vietinghoff H., 2000, Die Verdunstung freier WasserflachenGrundlagen, Einflussfaktoren und Methoden der Ermittlung
   Yamanashi T, 2011, ARCHIT DESIGN, P100, DOI 10.1002/ad.1326
NR 15
TC 0
Z9 0
U1 0
U2 0
PU WALTER DE GRUYTER GMBH
PI BERLIN
PA GENTHINER STRASSE 13, D-10785 BERLIN, GERMANY
SN 0178-2312
EI 2196-677X
J9 AT-AUTOM
JI AT-Autom.
PD AUG 27
PY 2024
VL 72
IS 8
DI 10.1515/auto-2024-5059
PG 13
WC Automation & Control Systems
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Automation & Control Systems
GA E5Y9E
UT WOS:001303769100007
DA 2025-01-10
ER

PT J
AU Ali, S
   Umair, M
   Makanda, TA
   Shi, SQ
   Hussain, SA
   Ni, J
AF Ali, Shahzad
   Umair, Muhammad
   Makanda, Tyan Alice
   Shi, Siqi
   Hussain, Shaik Althaf
   Ni, Jian
TI Modeling Current and Future Potential Land Distribution Dynamics of
   Wheat, Rice, and Maize under Climate Change Scenarios Using MaxEnt
SO LAND
LA English
DT Article
DE geographic suitability; land suitability dynamics; bioclimatic
   variables; big data; MaxEnt model; South Asia
ID SPECIES DISTRIBUTION MODELS; IMPACT; PERFORMANCE; YIELD; PRODUCTIVITY;
   TEMPERATURE; COTTON
AB Accurately predicting changes in the potential distribution of crops resulting from climate change has great significance for adapting to and mitigating the impacts of climate change and ensuring food security. After understanding the spatial and temporal suitability of wheat (Triticum aestivum), rice (Oryza sativa), and maize (Zea mays), as well as the main bioclimatic variables affecting crop growth, we used the MaxEnt model. The accuracy of the MaxEnt was extremely significant, with mean AUC (area under curve) values ranging from 0.876 to 0.916 for all models evaluated. The results showed that for wheat, annual mean temperature (Bio-1) and mean temperature of the coldest quarter (Bio-11) contributed 39.2% and 13.4%, respctively; for rice, precipitation of the warmest quarter (Bio-18) and elevation contributed 34.9% and 19.9%, respectively; and for maize, Bio-1 and precipitation of the driest quarter (Bio-17) contributed 36.3% and 14.3%, respectively. The map drawn indicates that the suitability of wheat, rice, and corn in South Asia may change in the future. Understanding the future distribution of crops can help develop transformative climate change adaptation strategies that consider future crop suitability. The study showed an average significant improvement in high-suitable areas of 8.7%, 30.9%, and 13.1%, for wheat, rice, and maize, respectively; moderate-suitable area increases of 3.9% and 8.6% for wheat and rice, respectively; and a decrease of -8.3% for maize as compared with the current values. The change in the unsuitable areas significantly decreases by -2.5%, -13.5%, and -1.7% for wheat, rice, and maize, respectively, compared to current land suitability. The results of this study are crucial for South Asia as they provide policy-makers with an opportunity to develop appropriate adaptation and mitigation strategies to sustain wheat, rice, and corn production in future climate scenarios.
C1 [Ali, Shahzad] Zhejiang Normal Univ, Coll Chem & Mat Sci, Jinhua 321004, Peoples R China.
   [Umair, Muhammad] Shanghai Jiao Tong Univ, Sch Agr & Biol, Shanghai 200240, Peoples R China.
   [Makanda, Tyan Alice; Ni, Jian] Zhejiang Normal Univ, Coll Life Sci, Jinhua 321004, Peoples R China.
   [Shi, Siqi] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7500 AE Enschede, Netherlands.
   [Hussain, Shaik Althaf] King Saud Univ, Dept Zool, Coll Sci, BOX 2454, Riyadh 11451, Saudi Arabia.
C3 Zhejiang Normal University; Shanghai Jiao Tong University; Zhejiang
   Normal University; University of Twente; King Saud University
RP Ali, S (corresponding author), Zhejiang Normal Univ, Coll Chem & Mat Sci, Jinhua 321004, Peoples R China.
EM shahzadali320@aup.edu.pk
RI Shi, Siqi/KII-0922-2024; Ali, Shahzad/LKN-4319-2024; Shaik,
   Althaf/GZB-2792-2022; Umair, Muhammad/HMU-8795-2023
OI MUHAMMAD, UMAIR/0000-0003-2411-2499; shaik, althaf
   hussain/0000-0001-6389-9146; Shi, Siqi/0000-0001-9155-9149
FU King Saud University, Riyadh, Saudi Arabia; Zhejiang Normal University
   [ZC304022952]; Shandong Natural Science Youth Project;  [RSP2024R371]; 
   [ZR2020QF281]
FX The authors extend their appreciation to the Researchers Supporting
   Project number (RSP2024R371), King Saud University, Riyadh, Saudi
   Arabia; Zhejiang Normal University (ZC304022952), and Shandong Natural
   Science Youth Project (ZR2020QF281), China.
CR Akpoti K, 2020, SCI TOTAL ENVIRON, V709, DOI 10.1016/j.scitotenv.2019.136165
   Ashoori A, 2018, EUR ZOOL J, V85, P372, DOI 10.1080/24750263.2018.1510994
   Asseng S, 2015, NAT CLIM CHANGE, V5, P143, DOI [10.1038/nclimate2470, 10.1038/NCLIMATE2470]
   Asseng S, 2011, GLOBAL CHANGE BIOL, V17, P997, DOI 10.1111/j.1365-2486.2010.02262.x
   Booth TH, 2014, DIVERS DISTRIB, V20, P1, DOI 10.1111/ddi.12144
   Brown JL, 2017, PEERJ, V5, DOI 10.7717/peerj.4095
   Bu Kun Bu Kun, 2017, Zhongguo Shengtai Nongye Xuebao / Chinese Journal of Eco-Agriculture, V25, P419
   Bunn C, 2019, CLIM SERV, V16, DOI 10.1016/j.cliser.2019.100123
   CARPENTER G, 1993, BIODIVERS CONSERV, V2, P667, DOI 10.1007/BF00051966
   Chemura A, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-87647-4
   Chersich MF, 2019, GLOBALIZATION HEALTH, V15, DOI 10.1186/s12992-019-0466-x
   Duan JQ., 2012, CHIN ACAD METEOROL S, V45, P218, DOI [10.3864/j.issn.0578-1752.2012.02.003, DOI 10.3864/J.ISSN.0578-1752.2012.02.003]
   Elith J, 2011, DIVERS DISTRIB, V17, P43, DOI 10.1111/j.1472-4642.2010.00725.x
   Fan M, 2017, SCI TOTAL ENVIRON, V599, P451, DOI 10.1016/j.scitotenv.2017.05.010
   Feng L, 2021, FIELD CROP RES, V263, DOI 10.1016/j.fcr.2021.108069
   Fischer G, 2005, PHILOS T R SOC B, V360, P2067, DOI 10.1098/rstb.2005.1744
   Fodor N, 2017, PLANT CELL PHYSIOL, V58, P1833, DOI 10.1093/pcp/pcx141
   Fourcade Y, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0097122
   Franchini M, 2015, EUR J INTERN MED, V26, P1, DOI 10.1016/j.ejim.2014.12.008
   Franklin J, 2013, DIVERS DISTRIB, V19, P1217, DOI 10.1111/ddi.12125
   Gao Y, 2021, LAND-BASEL, V10, DOI 10.3390/land10030295
   GBIF, 2021, About us, DOI [10.15468/dl.cjnj2p, DOI 10.15468/DL.CJNJ2P]
   Gong LJ, 2021, INT J PLANT PROD, V15, P363, DOI 10.1007/s42106-021-00145-5
   Habtemariam LT, 2017, AGR SYST, V152, P58, DOI 10.1016/j.agsy.2016.12.006
   [何奇瑾 He Qijin], 2012, [生态学报, Acta Ecologica Sinica], V32, P3931
   Hong De-Yuan, 2017, Biodiversity Science, V25, P781, DOI 10.17520/biods.2017129
   Hou Wen-jia, 2015, Yingyong Shengtai Xuebao, V26, P249
   Huang CC, 2015, SCI TOTAL ENVIRON, V536, P173, DOI 10.1016/j.scitotenv.2015.07.014
   Ihlow F, 2012, GLOBAL CHANGE BIOL, V18, P1520, DOI 10.1111/j.1365-2486.2011.02623.x
   IPCC, 2023, Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [DOI 10.59327/IPCC/AR6-9789291691647, 10.59327/IPCC/AR6-9789291691647.001]
   남종민, 2015, [Journal of Wetlands Researh, 한국습지학회지], V17, P19
   Kogo BK, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9110727
   Kramer-Schadt S, 2013, DIVERS DISTRIB, V19, P1366, DOI 10.1111/ddi.12096
   Kulhanek SA, 2011, ECOL APPL, V21, P203, DOI 10.1890/09-1639.1
   Li YC, 2020, FORESTS, V11, DOI 10.3390/f11030302
   Liu BY, 2020, PEST MANAG SCI, V76, P3096, DOI 10.1002/ps.5861
   Liu BY, 2019, SCI TOTAL ENVIRON, V664, P203, DOI 10.1016/j.scitotenv.2019.01.301
   Liu ZhiJuan Liu ZhiJuan, 2017, Scientia Agricultura Sinica, V50, P1606
   Luo Mei, 2017, Yingyong Shengtai Xuebao, V28, P4001, DOI 10.13287/j.1001-9332.201712.011
   Mabhaudhi T, 2019, PLANTA, V250, P695, DOI 10.1007/s00425-019-03129-y
   Mall RK, 2004, AGR FOREST METEOROL, V121, P113, DOI 10.1016/S0168-1923(03)00157-6
   Marcer A, 2013, BIOL CONSERV, V166, P221, DOI 10.1016/j.biocon.2013.07.001
   Mohammadi S, 2019, ECOL INFORM, V52, P7, DOI 10.1016/j.ecoinf.2019.04.003
   Montoya F, 2017, AGR WATER MANAGE, V193, P30, DOI 10.1016/j.agwat.2017.08.001
   Motuma M, 2016, APPL GEOMAT, V8, P57, DOI 10.1007/s12518-016-0168-5
   Mustafa A.A., 2011, Researcher, V3, P61, DOI DOI 10.7537/MARSRSJ031211.14
   Ncube B, 2020, APPL GEOGR, V117, DOI 10.1016/j.apgeog.2020.102172
   Nyathi MK, 2018, AGR WATER MANAGE, V208, P107, DOI 10.1016/j.agwat.2018.06.012
   Ohta S, 2007, AGR FOREST METEOROL, V147, P186, DOI 10.1016/j.agrformet.2007.07.009
   Ortiz R, 2008, AGR ECOSYST ENVIRON, V126, P46, DOI 10.1016/j.agee.2008.01.019
   Peterson A. T., 2011, Ecological Niches and Geographic Distributions
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2008, ECOGRAPHY, V31, P161, DOI 10.1111/j.0906-7590.2008.5203.x
   Phillips SJ, 2017, ECOGRAPHY, V40, P887, DOI 10.1111/ecog.03049
   Qin AL, 2020, GLOB ECOL CONSERV, V22, DOI 10.1016/j.gecco.2020.e01032
   Shabani F, 2016, J AGR SCI-CAMBRIDGE, V154, P175, DOI 10.1017/S0021859615000398
   Shabani F, 2016, ECOL EVOL, V6, P5973, DOI 10.1002/ece3.2332
   Angelieri CCS, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0145232
   Slater H, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0032202
   Su P, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031580
   SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615
   Teichmann C, 2021, CLIM DYNAM, V57, P1269, DOI 10.1007/s00382-020-05494-x
   Trenberth KE, 2014, NAT CLIM CHANGE, V4, P17, DOI 10.1038/NCLIMATE2067
   Walke N, 2012, COMPUT GEOSCI-UK, V41, P108, DOI 10.1016/j.cageo.2011.08.020
   [王丽 Wang Li], 2016, [生态学报, Acta Ecologica Sinica], V36, P4465
   Wang WQ, 2020, ADV AGRON, V159, P135, DOI 10.1016/bs.agron.2019.07.006
   Wisz MS, 2008, DIVERS DISTRIB, V14, P763, DOI 10.1111/j.1472-4642.2008.00482.x
   Xu L.L., 2017, Mod. Agric. Sci. Technol, V18, P183
   Yao HZ, 2020, GEOGR SUSTAIN, V1, P163, DOI 10.1016/j.geosus.2020.06.002
   Yin X., 2019, WORLD AGR, V11, P65
   Yue YJ, 2019, SCI TOTAL ENVIRON, V688, P1308, DOI 10.1016/j.scitotenv.2019.06.153
   Zhang KL, 2018, SCI TOTAL ENVIRON, V634, P1326, DOI 10.1016/j.scitotenv.2018.04.112
   Zheng C, 2022, CROP J, V10, P280, DOI 10.1016/j.cj.2021.06.003
   Zipper SC, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094021
NR 74
TC 0
Z9 0
U1 52
U2 52
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD AUG
PY 2024
VL 13
IS 8
AR 1156
DI 10.3390/land13081156
PG 26
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA E8K0E
UT WOS:001305421700001
OA gold
DA 2025-01-10
ER

PT J
AU Blondeel, H
   Guillemot, J
   Martin-StPaul, N
   Druel, A
   Bilodeau-Gauthier, S
   Bauhus, J
   Grossiord, C
   Hector, A
   Jactel, H
   Jensen, J
   Messier, C
   Muys, B
   Serrano-Leon, H
   Auge, H
   Barsoum, N
   Birhane, E
   Bruelheide, H
   Cavender-Bares, J
   Chu, CJ
   Cumming, JR
   Damtew, A
   Eisenhauer, N
   Ferlian, O
   Fiedler, S
   Ganade, G
   Godbold, DL
   Gravel, D
   Hall, JS
   Hoelscher, D
   Hulvey, KB
   Koricheva, J
   Kreft, H
   Lapadat, C
   Liang, JJ
   Liu, XJ
   Meredieu, C
   Mereu, S
   Montgomery, R
   Morillas, L
   Nock, C
   Paquette, A
   Parker, JD
   Parker, WC
   Paterno, GB
   Perring, MP
   Ponette, Q
   Potvin, C
   Reich, P
   Rentch, J
   Rewald, B
   Sanden, H
   Sinacore, K
   Standish, RJ
   Stefanski, A
   Tobin, PC
   van Breugel, M
   Fagundes, MV
   Weih, M
   Williams, LJ
   Zhou, M
   Scherer-Lorenzen, M
   Verheyen, K
   Baeten, L
AF Blondeel, Haben
   Guillemot, Joannes
   Martin-StPaul, Nicolas
   Druel, Arsene
   Bilodeau-Gauthier, Simon
   Bauhus, Juergen
   Grossiord, Charlotte
   Hector, Andrew
   Jactel, Herve
   Jensen, Joel
   Messier, Christian
   Muys, Bart
   Serrano-Leon, Hernan
   Auge, Harald
   Barsoum, Nadia
   Birhane, Emiru
   Bruelheide, Helge
   Cavender-Bares, Jeannine
   Chu, Chengjin
   Cumming, Jonathan R.
   Damtew, Abebe
   Eisenhauer, Nico
   Ferlian, Olga
   Fiedler, Sebastian
   Ganade, Gislene
   Godbold, Douglas L.
   Gravel, Dominique
   Hall, Jefferson S.
   Hoelscher, Dirk
   Hulvey, Kristin B.
   Koricheva, Julia
   Kreft, Holger
   Lapadat, Cathleen
   Liang, Jingjing
   Liu, Xiaojuan
   Meredieu, Celine
   Mereu, Simone
   Montgomery, Rebecca
   Morillas, Lourdes
   Nock, Charles
   Paquette, Alain
   Parker, John D.
   Parker, William C.
   Paterno, Gustavo B.
   Perring, Michael P.
   Ponette, Quentin
   Potvin, Catherine
   Reich, Peter
   Rentch, James
   Rewald, Boris
   Sanden, Hans
   Sinacore, Katherine
   Standish, Rachel J.
   Stefanski, Artur
   Tobin, Patrick C.
   van Breugel, Michiel
   Fagundes, Marina Vergara
   Weih, Martin
   Williams, Laura J.
   Zhou, Mo
   Scherer-Lorenzen, Michael
   Verheyen, Kris
   Baeten, Lander
TI Tree diversity reduces variability in sapling survival under drought
SO JOURNAL OF ECOLOGY
LA English
DT Article
DE climate change adaptation; functional traits; IDENT; relative
   extractable water (REW); standardized precipitation evapotranspiration
   index (SPEI); tree mortality; TreeDivNet
ID FUNCTIONAL DIVERSITY; FOREST RESILIENCE; HYDRAULIC SAFETY; BIODIVERSITY;
   RESISTANCE; ECOLOGY; RESTORATION; TOLERANCE; STABILITY; EMBOLISM
AB Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantations. We conducted an analysis of seedling and sapling survival from 34 globally distributed tree diversity experiments (363,167 trees, 168 species, 3744 plots, 7 biomes) to answer two questions: (1) Do drought and tree diversity alter the mean and variability in plot-level tree survival, with higher and less variable survival as diversity increases? and (2) Do species that survive poorly in monocultures survive better in mixtures and do specific functional traits explain monoculture survival? Tree species richness reduced variability in plot-level survival, while functional diversity (Rao's Q entropy) increased survival and also reduced its variability. Importantly, the reduction in survival variability became stronger as drought severity increased. We found that species with low survival in monocultures survived comparatively better in mixtures when under drought. Species survival in monoculture was positively associated with drought resistance (indicated by hydraulic traits such as turgor loss point), plant height and conservative resource-acquisition traits (e.g. low leaf nitrogen concentration and small leaf size). Synthesis. The findings highlight: (1) The effectiveness of tree diversity for decreasing the variability in seedling and sapling survival under drought; and (2) the importance of drought resistance and associated traits to explain altered tree species survival in response to tree diversity and drought. From an ecological perspective, we recommend mixing be considered to stabilize tree survival, particularly when functionally diverse forests with drought-resistant species also promote high survival of drought-sensitive species.
   Rising climate extremes, such as drought, can cause major uncertainty in the survival of young trees. Tree diversity can reduce survival variability and stabilize tree survival. Functionally diverse communities with drought-tolerant species can promote the survival of drought-sensitive species.image
C1 [Blondeel, Haben; Verheyen, Kris; Baeten, Lander] Univ Ghent, Dept Environm, Forest & Nat Lab, Campus Gontrode, Melle Gontrode, Belgium.
   [Guillemot, Joannes] CIRAD, UMR Eco&Sols, Montpellier, France.
   [Guillemot, Joannes] Univ Montpellier, Inst Agro, Eco&Sols, CIRAD,INRAE,IRD, Montpellier, France.
   [Guillemot, Joannes] Univ Sao Paulo, Forest Sci Dept, ESALQ, Piracicaba, Brazil.
   [Martin-StPaul, Nicolas; Druel, Arsene] Ecol Forets Mediterraneennes URFM, INRAe, Avignon, France.
   [Bilodeau-Gauthier, Simon] Minist Ressources Naturelles & Forets, Direct Rech forestiere, Quebec City, PQ, Canada.
   [Bauhus, Juergen; Serrano-Leon, Hernan] Univ Freiburg, Fac Environm & Nat Resources, Chair Silviculture, Freiburg, Germany.
   [Grossiord, Charlotte] Ecole Polytech Fed Lausanne EPFL, Plant Ecol Res Lab PERL, Lausanne, Switzerland.
   [Grossiord, Charlotte] Inst Fed Rech WSL, Lausanne, Switzerland.
   [Hector, Andrew] Univ Oxford, Dept Biol, Oxford, England.
   [Jactel, Herve] Univ Bordeaux, INRAE, UMR BioGeCo, Cestas, France.
   [Jensen, Joel; Weih, Martin] Swedish Univ Agr Sci, Dept Crop Prod Ecol, Uppsala, Sweden.
   [Messier, Christian] Dept Sci Biol, Montreal, PQ, Canada.
   [Muys, Bart; Damtew, Abebe] Dept Forest Nat & Landscape, KU Leuven, Leuven, Belgium.
   [Auge, Harald] UFZ Helmholtz Ctr Environm Res, Dept Community Ecol, Halle, Germany.
   [Auge, Harald; Bruelheide, Helge; Eisenhauer, Nico; Ferlian, Olga] German Ctr Integrat Biodivers Res iDiv, Halle Jena Leipzig, D-04103 Leipzig, Germany.
   [Barsoum, Nadia] Forest Res Alice Holt Lodge, Ctr Ecosyst Soc & Biosecur, Farnham GU10 4LH, Surrey, England.
   [Birhane, Emiru; Damtew, Abebe] Mekelle Univ, Dept Land Resource Management & Environm Protect, Mekelle, Ethiopia.
   [Birhane, Emiru] Norwegian Univ Life Sci NMBU, Fac Environm Sci & Nat Resource Management, As, Norway.
   [Bruelheide, Helge] Martin Luther Univ Halle Wittenberg, Inst Biol Geobot & Bot Garden, Halle, Germany.
   [Cavender-Bares, Jeannine; Lapadat, Cathleen] Univ Minnesota, Dept Ecol Evolut & Behav, St Paul, MN USA.
   [Chu, Chengjin] Sun Yat Sen Univ, Sch Ecol, State Key Lab Biocontrol, Guangzhou, Peoples R China.
   [Cumming, Jonathan R.] Univ Maryland Eastern Shore, Dept Nat Sci, Princess Anne, MD USA.
   [Fiedler, Sebastian] Univ Gottingen, Dept Ecosyst Modeling, Gottingen, Germany.
   [Ganade, Gislene; Fagundes, Marina Vergara] Univ Fed Rio Grande Norte UFRN, Ctr Biociencias, DECOL, Natal, Brazil.
   [Godbold, Douglas L.; Rewald, Boris; Sanden, Hans] Univ Nat Resources & Life Sci BOKU, Inst Forest Ecol, Dept Forest & Soil Sci, Vienna, Austria.
   [Gravel, Dominique] Univ Sherbrooke, Fac Sci, Dept Biol, Sherbrooke, PQ, Canada.
   [Hall, Jefferson S.] Smithsonian Trop Res Inst, Forest GEO, Panama City, Panama.
   [Hoelscher, Dirk] Univ GOttingen, Trop Silviculture & Forest Ecol, Gottingen, Germany.
   [Hulvey, Kristin B.] Working Lands Conservat, Logan, UT USA.
   [Koricheva, Julia] Royal Holloway Univ London, Dept Biol Sci, Egham, Surrey, England.
   [Kreft, Holger; Paterno, Gustavo B.] Georg August Univ Gottingen, Biodivers Macroecol & Biogeog, Gottingen, Germany.
   [Liang, Jingjing; Zhou, Mo] Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN USA.
   [Liu, Xiaojuan] Inst Bot, CAS, Beijing, Peoples R China.
   [Meredieu, Celine] INRAE, Biogeco, F-33610 Cestas, France.
   [Mereu, Simone] Inst Bioecon CNR IBE, Natl Res Council, Sassari, Italy.
   [Montgomery, Rebecca; Reich, Peter] Univ Minnesota, Dept Forest Resources, St Paul, MN USA.
   [Morillas, Lourdes] Univ Seville, Dept Plant Biol & Ecol, Seville, Spain.
   [Nock, Charles] Univ Alberta, Fac Agr Life & Environm Sci, Dept Renewable Resources, Edmonton, AB, Canada.
   [Paquette, Alain] Univ Quebec Montreal, Ctr Forest Res, Dept Sci Biol, Montreal, PQ, Canada.
   [Parker, John D.] Smithsonian Environm Res Ctr, Edgewater, MD USA.
   [Parker, William C.] Ontario Forest Res Inst, Sault Ste Marie, ON, Canada.
   [Perring, Michael P.] UK Ctr Ecol & Hydrol, Environm Ctr Wales, Bangor, Gwynedd, Wales.
   [Ponette, Quentin] Catholic Univ Louvain, Environm Sci Earth & Life Inst, Louvain la Neuve, Belgium.
   [Potvin, Catherine] Stewart Biol Bldg, Montreal, PQ, Canada.
   [Reich, Peter] Univ Michigan, Inst Global Change Biol, Ann Arbor, MI USA.
   [Rentch, James] West Virginia Univ, Morgantown, WV USA.
   [Sinacore, Katherine] Smithsonian Trop Res Inst, Agua Salud Project, ForestGEO, Panama City, Panama.
   [Standish, Rachel J.] Murdoch Univ, Murdoch, WA, Australia.
   [Stefanski, Artur; Williams, Laura J.] Univ Minnesota, Dept Forest Resources, St Paul, MN USA.
   [Tobin, Patrick C.] Univ Washington, Sch Environm & Forest Sci, Seattle, WA USA.
   [van Breugel, Michiel] Natl Univ Singapore, Dept Geog, Singapore, Singapore.
   [van Breugel, Michiel] Natl Univ Singapore, Yale NUS Coll, Singapore, Singapore.
   [Williams, Laura J.] Western Sydney Univ, Hawkesbury Inst Environm, Penrith, NSW, Australia.
   [Scherer-Lorenzen, Michael] Univ Freiburg, Fac Biol, Freiburg, Germany.
C3 Ghent University; Institut Agro; Montpellier SupAgro; CIRAD; Institut de
   Recherche pour le Developpement (IRD); INRAE; Universite de Montpellier;
   Institut Agro; Montpellier SupAgro; CIRAD; Institut de Recherche pour le
   Developpement (IRD); Universidade de Sao Paulo; INRAE; University of
   Freiburg; Swiss Federal Institutes of Technology Domain; Ecole
   Polytechnique Federale de Lausanne; Swiss Federal Institutes of
   Technology Domain; Swiss Federal Institute for Forest, Snow & Landscape
   Research; University of Oxford; Universite de Bordeaux; INRAE; Swedish
   University of Agricultural Sciences; KU Leuven; Helmholtz Association;
   Helmholtz Center for Environmental Research (UFZ); Mekelle University;
   Norwegian University of Life Sciences; Martin Luther University Halle
   Wittenberg; University of Minnesota System; University of Minnesota Twin
   Cities; Sun Yat Sen University; University System of Maryland;
   University of Maryland Eastern Shore; University of Gottingen;
   Universidade Federal do Rio Grande do Norte; BOKU University; University
   of Sherbrooke; Smithsonian Institution; Smithsonian Tropical Research
   Institute; University of Gottingen; University of London; Royal Holloway
   University London; University of Gottingen; Purdue University System;
   Purdue University; Chinese Academy of Sciences; INRAE; University of
   Minnesota System; University of Minnesota Twin Cities; University of
   Sevilla; University of Alberta; University of Quebec; University of
   Quebec Montreal; Smithsonian Institution; Smithsonian Environmental
   Research Center; UK Centre for Ecology & Hydrology (UKCEH); Universite
   Catholique Louvain; University of Michigan System; University of
   Michigan; West Virginia University; Smithsonian Institution; Smithsonian
   Tropical Research Institute; Murdoch University; University of Minnesota
   System; University of Minnesota Twin Cities; University of Washington;
   University of Washington Seattle; National University of Singapore;
   National University of Singapore; Yale NUS College; Western Sydney
   University; University of Freiburg
RP Blondeel, H (corresponding author), Univ Ghent, Dept Environm, Forest & Nat Lab, Campus Gontrode, Melle Gontrode, Belgium.
EM haben.blondeel@ugent.be
RI mereu, simone/AAN-1877-2021; Eisenhauer, Nico/I-5932-2012; Chu,
   Cheng-Jin/B-3573-2010; Godbold, Douglas/AGH-4181-2022; Bruelheide,
   Helge/G-3907-2013; Liu, Xiaojuan/B-4947-2017; Guillemot,
   Joannès/O-8701-2016; Williams, Laura/AAI-9757-2021; van Breugel,
   Michiel/A-8453-2017; Perring, Michael/B-1323-2011; Ganade,
   Gislene/F-4863-2016; Birhane, Emiru/JBJ-0779-2023; Weih,
   Martin/H-5093-2011; Blondeel, Haben/ABA-8040-2021; Paterno,
   Gustavo/S-9199-2019; Scherer-Lorenzen, Michael/AGB-4140-2022; Stefanski,
   Artur/ADB-7743-2022; Baeten, Lander/G-1490-2010; hulvey, k/L-4227-2019;
   Morillas, Lourdes/AAD-4342-2020; Fiedler, Sebastian/KHU-0877-2024;
   Meredieu, Céline/ABA-5282-2021; Auge, Harald/D-4802-2015; Parker,
   John/F-9761-2010; Rewald, Boris/L-2735-2019; Kreft, Holger/A-4736-2008;
   Grossiord, Charlotte/KIH-1024-2024; Bauhus, Jurgen/G-4449-2013
OI Auge, Harald/0000-0001-7432-8453; Sinacore,
   Katherine/0000-0002-8719-9248; Parker, John/0000-0002-3632-7625;
   Williams, Laura/0000-0003-3555-4778; Baeten, Lander/0000-0003-4262-9221;
   Liu, Xiaojuan/0000-0002-9292-4432; Blondeel, Haben/0000-0001-9939-5994;
   Jensen, Joel/0000-0003-4803-8393; Rewald, Boris/0000-0001-8098-0616;
   Kreft, Holger/0000-0003-4471-8236; Grossiord,
   Charlotte/0000-0002-9113-3671; Bauhus, Jurgen/0000-0002-9673-4986;
   GUILLEMOT, Joannes/0000-0003-4385-7656; Scherer-Lorenzen,
   Michael/0000-0001-9566-590X; Weih, Martin/0000-0003-3823-9183; JACTEL,
   Herve/0000-0002-8106-5310
FU BiodivClim ERA-Net COFUND Programme; BNP Paribas foundation through its
   Climate & Biodiversity initiative [ANR-20-EBI5-0003]; Agence Nationale
   de la Recherche [451394862]; BELSPO, DFG [I 5086-B]; FAPESP, FWF;
   Svenska Forskningsradet Formas [DFG-FZT 118, 202548816]; IDiv through
   the workshop 'Using Tree Diversity as an Insurance - German Research
   Foundation [Ei 862/29, Ei 862/31-1]; DFG; ForestGEO; Panama Canal
   Authority (ACP); Ministry of the Environment; HSBC; Hoch Family
   [192626868-SFB 990, CRC990]; Deutsche Forschungsgemeinschaft (DFG)
   German Research Foundation; Walloon forest service (Service Public de
   Wallonie-Departement de la Nature et des Forets); Division of Forestry
   and Natural Resources, West Virginia University [LTER DEB 1831944]; NSF;
   Department of Community Ecology of the UFZ; College of Dryland
   Agriculture and Natural Resources (Mekelle University); Smithsonian
   Tropical Research Institute; NSERC; University of Freiburg
   (Innovationsfonds Forschung); Thuringian Forestry Research and
   Competence Center (Thuringer Forstliches Forschungs- und
   Kompetenzzentrum, Gotha, Germany); Austrian Science Fund [I 4372-B];
   U.S. National Science Foundation, Biological Integration Institutes
   grant [NSF-DBI-2021898]; Agence Nationale de la Recherche (ANR)
   [ANR-20-EBI5-0003] Funding Source: Agence Nationale de la Recherche
   (ANR)
FX We thank all the site managers, field technicians and researchers who
   have made the collaborative work within the TreeDivNet possible. The
   research in this study was funded through the research project CAMBIO,
   funded by the BNP Paribas foundation through its Climate & Biodiversity
   initiative. This research was funded through the 2019-2020 BiodivERsA
   joint call for research proposals, under the BiodivClim ERA-Net COFUND
   Programme (MixForChange project), and with the funding organizations
   Agence Nationale de la Recherche (ANR-20-EBI5-0003), BELSPO, DFG
   (project number 451394862), FAPESP, FWF (I 5086-B) and Svenska
   Forskningsradet Formas. This research was supported by iDiv through the
   workshop 'Using Tree Diversity as an Insurance for the Stable
   Functioning of Forest Ecosystems - sTree Div', which took place in
   Leipzig in 2014, and where the data gathering process for a
   TreeDivNet-wide survival study was first discussed and initiated. NE
   (Nico Eisenhauer) and OF (Olga Ferlian) acknowledge the support of iDiv,
   funded by the German Research Foundation (DFG-FZT 118, 202548816) and
   funding by the DFG (Ei 862/29-1 and Ei 862/31-1). Agua Salud is part of
   ForestGEO and is a collaboration with the Panama Canal Authority (ACP),
   the Ministry of the Environment (MiAmbiente) of Panama and other
   partners. The plantation establishment of Agua Salud was supported by
   the HSBC and the ACP. Funding for this work came from Stanley Motta,
   Frank and Kristin Levinson and the Hoch Family. EFForTS-BEE was financed
   by the Deutsche Forschungsgemeinschaft (DFG) German Research
   Foundation-project number 192626868-SFB 990 in the framework of the
   collaborative German-Indonesian research project CRC990 EFForTS
   (http://www.unigoettingen.de/crc990). We thank Anne Gerard, Delphine
   Clara Zemp, Wollni Meike, Leti Sundawati, Bambang Irawan and Eduard
   Siahaan for their support in EFForTS-BEE. We thank Jamie Pullen for site
   management and data collection in BiodiversiTREE. We would like to thank
   the Walloon forest service (Service Public de Wallonie-Departement de la
   Nature et des Forets) for its financial support to the installation and
   maintenance of the FORBIO-Gedinne site through the 5-year research
   programme 'Accord-cadre de recherches et de vulgarisation forestieres'.
   SIDE was supported by the Division of Forestry and Natural Resources,
   West Virginia University. We thank Allison Scott, Sarah Hobbie and the
   NSF (LTER DEB 1831944) for their support in IDENT FAB. We thank
   Josephine Haase, Daniel Prati and Felix Gottschall, the Department of
   Community Ecology of the UFZ, and the Team of the Bad Lauchstadt field
   station of the UFZ for contributing to the establishment, maintenance
   and measurements in the Kreinitz experiment. We thank Richard Hobbs, Tim
   Morald and Rebecca Campbell for their support in Ridgefield. We thank
   Wei Lin, Zhiyi C hen, Zhiqiang Shen, Buhang Li, Bingwei Zhand and
   Yuanzhi Li for their support in CADE. We thank Abadi Tesfay, Sisay
   Yemae, Asmelash Aynalem, Tesfahunegn Abraha and the College of Dryland
   Agriculture and Natural Resources (Mekelle University) for their support
   in IDENT Ethiopia. We thank Cornelia Garbe and Jon Urgoiti for
   collecting data in IDENT Montreal. We thank Daniel Lesieur for preparing
   and sharing various IDENT data as well as data from the Sardinilla site.
   The Sardinilla site was supported by the Smithsonian Tropical Research
   Institute as well as an NSERC grant to C. Potvin. We thank Jose Monteza
   for his invaluable help in the field in Sardinilla.The IDENT Freiburg
   experiment has been supported by the University of Freiburg
   (Innovationsfonds Forschung, grant to MSL and JB). We thank the
   Sardinian Forest Authority 'Forestas' for hosting the IDENT-Macomer
   experiment and contributing to its establishment and management. The
   BIOTREE experiments have been established by the Max-Planck-Institute
   for Biogeochemistry Jena (Germany), with support by the Federal Forestry
   Office Thueringer Wald (Bundesforstamt Thueringer Wald, Bad Salzungen,
   Germany) and the Thuringian Forestry Research and Competence Center
   (Thueringer Forstliches Forschungs- und Kompetenzzentrum, Gotha,
   Germany). We thank Bernard Issenhuth and INRAE-Forest experimental
   Facility UEFP (https://doi.org/10.15454/1.5483264699193726) for the
   coordination, establishment, maintenance and measurements in ORPHEE. The
   B-tree experiments were supported by the Austrian Science Fund grant I
   4372-B. IDENT-Cloquet was supported by the U.S. National Science
   Foundation, Biological Integration Institutes grant NSF-DBI-2021898.
CR Aerts R, 2007, RESTOR ECOL, V15, P129, DOI 10.1111/j.1526-100X.2006.00197.x
   Agnew C.T., 2000, Drought Netw. News, V12, P6
   Allen CD, 2007, ECOSYSTEMS, V10, P797, DOI 10.1007/s10021-007-9057-4
   Ammer C, 2019, NEW PHYTOL, V221, P50, DOI 10.1111/nph.15263
   Anderegg WRL, 2020, NAT CLIM CHANGE, V10, P1091, DOI 10.1038/s41558-020-00919-1
   Aquilué N, 2020, ECOL APPL, V30, DOI 10.1002/eap.2095
   Baeten L, 2019, J APPL ECOL, V56, P733, DOI 10.1111/1365-2664.13308
   Baeten L, 2013, PERSPECT PLANT ECOL, V15, P281, DOI 10.1016/j.ppees.2013.07.002
   Banin LF, 2023, PHILOS T R SOC B, V378, DOI 10.1098/rstb.2021.0090
   Baret F, 2013, REMOTE SENS ENVIRON, V137, P299, DOI 10.1016/j.rse.2012.12.027
   Bartlett MK, 2012, ECOL LETT, V15, P393, DOI 10.1111/j.1461-0248.2012.01751.x
   Batllori E, 2020, P NATL ACAD SCI USA, V117, P29720, DOI 10.1073/pnas.2002314117
   Bauhus J., 2017, Mixed-Species Forests: Ecology and Management, DOI [DOI 10.1007/978-3-662-54553-97, DOI 10.1007/978-3-662-54553-9]
   Beguería S, 2014, INT J CLIMATOL, V34, P3001, DOI 10.1002/joc.3887
   Blondeel H., 2024, DATA TREE DIVERSITY, DOI [10.6084/m9.figshare.25359751.v1, DOI 10.6084/M9.FIGSHARE.25359751.V1]
   Bradford JB, 2022, J APPL ECOL, V59, P549, DOI 10.1111/1365-2664.14073
   Bretfeld M, 2018, NEW PHYTOL, V219, P885, DOI 10.1111/nph.15071
   Brodribb TJ, 2020, SCIENCE, V368, P261, DOI 10.1126/science.aat7631
   Bürkner PC, 2017, J STAT SOFTW, V80, P1, DOI 10.18637/jss.v080.i01
   Bukoski JJ, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-31380-7
   Büntgen U, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10174-4
   Chiang F, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22314-w
   Choat B, 2018, NATURE, V558, P531, DOI 10.1038/s41586-018-0240-x
   Damgaard CF, 2019, J ECOL, V107, P2747, DOI 10.1111/1365-2745.13200
   De Frenne P, 2019, NAT ECOL EVOL, V3, P744, DOI 10.1038/s41559-019-0842-1
   Díaz S, 2016, NATURE, V529, P167, DOI 10.1038/nature16489
   Dinerstein E, 2017, BIOSCIENCE, V67, P534, DOI 10.1093/biosci/bix014
   Doak DF, 1998, AM NAT, V151, P264, DOI 10.1086/286117
   Douma JC, 2019, METHODS ECOL EVOL, V10, P1412, DOI 10.1111/2041-210X.13234
   Elliott S, 2023, PHILOS T R SOC B, V378, DOI 10.1098/rstb.2021.0073
   Faria J. C., 2023, BPCA BIPLOT MULTIVAR
   Felton A, 2016, AMBIO, V45, pS124, DOI 10.1007/s13280-015-0749-2
   Fichtner A, 2020, J ECOL, V108, P865, DOI 10.1111/1365-2745.13353
   Fichtner A, 2017, ECOL LETT, V20, P892, DOI 10.1111/ele.12786
   Figge F, 2004, BIODIVERS CONSERV, V13, P827, DOI 10.1023/B:BIOC.0000011729.93889.34
   Fleischman F, 2020, BIOSCIENCE, V70, P947, DOI 10.1093/biosci/biaa094
   Forrester DI, 2015, TREE PHYSIOL, V35, P289, DOI 10.1093/treephys/tpv011
   Forzieri G, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21399-7
   Gamfeldt L, 2007, OIKOS, V116, P700, DOI 10.1111/j.2007.0030-1299.15382.x
   Gessler A, 2020, NEW PHYTOL, V228, P1704, DOI 10.1111/nph.16703
   Gillerot L, 2021, ECOSYSTEMS, V24, P20, DOI 10.1007/s10021-020-00501-y
   Goffner D, 2019, REG ENVIRON CHANGE, V19, P1417, DOI 10.1007/s10113-019-01481-z
   Granier A, 1999, ECOL MODEL, V116, P269, DOI 10.1016/S0304-3800(98)00205-1
   Greenwood S, 2017, ECOL LETT, V20, P539, DOI 10.1111/ele.12748
   Grossiord C, 2020, NEW PHYTOL, V228, P42, DOI 10.1111/nph.15667
   Grossiord C, 2014, P NATL ACAD SCI USA, V111, P14812, DOI 10.1073/pnas.1411970111
   Grossman JJ, 2018, ENVIRON EXP BOT, V152, P68, DOI 10.1016/j.envexpbot.2017.12.015
   Guillemot J, 2022, GLOBAL CHANGE BIOL, V28, P2622, DOI 10.1111/gcb.16082
   Hajek P, 2022, GLOBAL CHANGE BIOL, V28, P3365, DOI 10.1111/gcb.16146
   Hammond WM, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-29289-2
   Hisano M, 2019, ECOL LETT, V22, P999, DOI 10.1111/ele.13259
   Holyoak M., 2020, UNSOLVED PROBLEMS EC, P25, DOI [10.1515/9780691195322-005, DOI 10.1515/9780691195322-005]
   Ingrisch J, 2018, TRENDS ECOL EVOL, V33, P251, DOI 10.1016/j.tree.2018.01.013
   Jactel H, 2017, CURR FOR REP, V3, P223, DOI 10.1007/s40725-017-0064-1
   Kattge J, 2011, GLOBAL CHANGE BIOL, V17, P2905, DOI 10.1111/j.1365-2486.2011.02451.x
   King RA, 2023, RESTOR ECOL, V31, DOI 10.1111/rec.13927
   Kothari S, 2021, J ECOL, V109, P2000, DOI 10.1111/1365-2745.13637
   Kröber W, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0109211
   Kruschke J. K., 2015, Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan, V2nd
   Kunert N, 2020, J PLANT ECOL, V13, P754, DOI 10.1093/jpe/rtaa059
   Lacaze R, 2015, INT ARCH PHOTOGRAMM, V47, P53, DOI 10.5194/isprsarchives-XL-7-W3-53-2015
   Larter M, 2017, NEW PHYTOL, V215, P97, DOI 10.1111/nph.14545
   Lehman CL, 2000, AM NAT, V156, P534, DOI 10.1086/303402
   Lens F, 2016, PLANT PHYSIOL, V172, P661, DOI 10.1104/pp.16.00829
   Lewis SL, 2019, NATURE, V568, P25, DOI 10.1038/d41586-019-01026-8
   Lhomme JP, 2002, THEOR POPUL BIOL, V62, P271, DOI 10.1006/tpbi.2002.1612
   Liu H, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aav1332
   Liu XJ, 2022, J ECOL, V110, P2522, DOI 10.1111/1365-2745.13970
   Lobo A, 2018, FOREST ECOL MANAG, V424, P53, DOI 10.1016/j.foreco.2018.04.031
   Loreau M., 2001, Nature (London), V412, P72, DOI 10.1038/35083573
   Loreau M, 2021, BIOL REV, V96, P2333, DOI 10.1111/brv.12756
   Martin-StPaul N, 2017, ECOL LETT, V20, P1437, DOI 10.1111/ele.12851
   McDowell NG, 2022, NAT REV EARTH ENV, V3, P294, DOI 10.1038/s43017-022-00272-1
   McElreath R, 2016, TEXT STAT SCI, pXI
   Messier C, 2022, CONSERV LETT, V15, DOI 10.1111/conl.12829
   Muñoz-Sabater J, 2021, EARTH SYST SCI DATA, V13, P4349, DOI 10.5194/essd-13-4349-2021
   Newton AC, 2015, NEW FOREST, V46, P645, DOI 10.1007/s11056-015-9489-1
   Nock C. A., 2017, TERRESTRIAL ECOSYSTE, P119, DOI DOI 10.1201/9781315368252-6
   Paquette A, 2018, NAT ECOL EVOL, V2, P763, DOI 10.1038/s41559-018-0544-0
   Poggio L, 2021, SOIL-GERMANY, V7, P217, DOI 10.5194/soil-7-217-2021
   Poorter L, 2019, NAT ECOL EVOL, V3, P928, DOI 10.1038/s41559-019-0882-6
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Reich PB, 2014, J ECOL, V102, P275, DOI 10.1111/1365-2745.12211
   Réjou-Méchain M, 2017, METHODS ECOL EVOL, V8, P1163, DOI 10.1111/2041-210X.12753
   Ruffault J, 2022, GEOSCI MODEL DEV, V15, P5593, DOI 10.5194/gmd-15-5593-2022
   Ruffault J, 2013, CLIMATIC CHANGE, V117, P103, DOI 10.1007/s10584-012-0559-5
   Sanchez-Martinez P, 2020, ECOL LETT, V23, P1599, DOI 10.1111/ele.13584
   Schindler DE, 2015, FRONT ECOL ENVIRON, V13, P257, DOI 10.1890/140275
   Schindler DE, 2010, NATURE, V465, P609, DOI 10.1038/nature09060
   Schleuter D, 2010, ECOL MONOGR, V80, P469, DOI 10.1890/08-2225.1
   Schnabel F, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abk1643
   Searle EB, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2013171119
   Seddon N, 2021, GLOBAL CHANGE BIOL, V27, P1518, DOI 10.1111/gcb.15513
   Seddon N, 2019, NAT CLIM CHANGE, V9, P84, DOI 10.1038/s41558-019-0405-0
   Senf C, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-19924-1
   Senf C, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-07539-6
   Serra-Maluquer X, 2021, J ECOL, V109, P1561, DOI 10.1111/1365-2745.13579
   Sinacore K, 2019, FORESTS, V10, DOI 10.3390/f10020153
   Sinacore K, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0185934
   Sjöman H, 2015, URBAN FOR URBAN GREE, V14, P858, DOI 10.1016/j.ufug.2015.08.004
   Skelton RP, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2008987118
   Slette IJ, 2019, GLOBAL CHANGE BIOL, V25, P3193, DOI 10.1111/gcb.14747
   Song YJ, 2022, J EXP BOT, V73, P1033, DOI 10.1093/jxb/erab449
   Spinoni J, 2019, J HYDROL-REG STUD, V22, DOI 10.1016/j.ejrh.2019.100593
   Su R, 2022, FRONT ECOL EVOL, V10, DOI 10.3389/fevo.2022.974004
   Tilman D, 1997, ECOLOGY, V78, P81, DOI 10.1890/0012-9658(1997)078[0081:CIRLAG]2.0.CO;2
   Tobner CM, 2014, OECOLOGIA, V174, P609, DOI 10.1007/s00442-013-2815-4
   Trugman AT, 2021, TRENDS ECOL EVOL, V36, P520, DOI 10.1016/j.tree.2021.02.001
   Urgoiti J, 2023, J ECOL, V111, P2010, DOI 10.1111/1365-2745.14158
   Van de Peer T, 2018, FOREST ECOL MANAG, V409, P614, DOI 10.1016/j.foreco.2017.12.001
   Van de Peer T, 2016, J APPL ECOL, V53, P1777, DOI 10.1111/1365-2664.12721
   van der Plas F, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11109
   Van Meerbeek K, 2021, J ECOL, V109, P3114, DOI 10.1111/1365-2745.13651
   Verdone M, 2017, RESTOR ECOL, V25, P903, DOI 10.1111/rec.12512
   Verheyen K, 2016, AMBIO, V45, P29, DOI 10.1007/s13280-015-0685-1
   Verheyen K, 2013, PLANT ECOL EVOL, V146, P26, DOI 10.5091/plecevo.2013.803
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Villéger S, 2008, ECOLOGY, V89, P2290, DOI 10.1890/07-1206.1
   Westoby M, 1998, PLANT SOIL, V199, P213, DOI 10.1023/A:1004327224729
   Wright IJ, 2004, NATURE, V428, P821, DOI 10.1038/nature02403
   Xu L, 2019, INT J CLIMATOL, V39, P2375, DOI 10.1002/joc.5958
   Yachi S, 1999, P NATL ACAD SCI USA, V96, P1463, DOI 10.1073/pnas.96.4.1463
   Zabin CJ, 2022, FRONT ECOL ENVIRON, V20, P310, DOI 10.1002/fee.2471
   Zhu SD, 2018, FOREST ECOL MANAG, V418, P41, DOI 10.1016/j.foreco.2017.09.016
   Ziegler C, 2019, ANN FOREST SCI, V76, DOI 10.1007/s13595-019-0905-0
NR 125
TC 5
Z9 5
U1 22
U2 53
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0022-0477
EI 1365-2745
J9 J ECOL
JI J. Ecol.
PD MAY
PY 2024
VL 112
IS 5
BP 1164
EP 1180
DI 10.1111/1365-2745.14294
EA APR 2024
PG 17
WC Plant Sciences; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences; Environmental Sciences & Ecology
GA PS7V1
UT WOS:001198352600001
OA Green Published
DA 2025-01-10
ER

PT J
AU Maksymova, I
   Kurilyak, V
   Mietule, I
   Arbidane, I
   Kurilyak, M
AF Maksymova, Iryna
   Kurilyak, Vitalina
   Mietule, Iveta
   Arbidane, Iluta
   Kurilyak, Maksym
TI DIGITALLY DRIVEN MODEL OF A CLIMATENEUTRAL ECONOMY IN TERMS OF GLOBAL
   FINANCIAL CAPACITY
SO FINANCIAL AND CREDIT ACTIVITY-PROBLEMS OF THEORY AND PRACTICE
LA English
DT Article
DE global economy; green finance; digitalization; digital transformation;
   climate-neutral economy; Green Climate Fund
ID ADAPTATION
AB The article explores the conditions and drivers for the development of a climate-neutral economy model, emphasizing the pivotal role of digital transformation. A crucial lever in deploying this model is the proactive engagement of international financial entities within the realm of global green financing. The study highlights the instrumental role of green funds as key players in shaping global financial capacity and providing multilateral support for climate change adaptation worldwide. It delves into the overarching frameworks and mechanisms of such assistance. Employing a systematic analysis alongside case studies of the Green Climate Fund's projects, the authors aim to identify the most impactful sectors for cultivating a climate-neutral economy. The research identifies four essential segments for achieving climate neutrality: digitalization for climate, strengthening the financial capacity and business sustainability, rethinking ecosystem development, and community empowerment. The investigation draws on extensive data regarding the execution of 240 climate projects across major beneficiaries of climate finance in Eastern Europe, Africa, the Asia-Pacific, and Latin America. It shows that modern climate finance demonstrates signs of geopolitical dependency and polarization in global influence. The findings argue for bolstering the regional presence of climate funds to increase the financial capacity to implement climate-neutral projects at the local level. The article underscores the scale of financial support required across each segment, as well as the leading role of pre-project preparation. The authors substantiate the overarching and twofold role of digitalization in the model of a climate-neutral economy. The digital transformation produces a whole cluster of independent and versatile IT products for green businesses, industries and governance. On the other hand, digitalization creates an informational environment and a powerful digital infrastructure for better efficacy of other crucial segments. Specifically, it provides digital decisions for financial solvency and sustainability of green businesses in terms of green lending, grants and Fintech; strengthens information awareness and involvement of vulnerable communities in green economy processes; promotes digital support for overall ecosystem adaptation.
C1 [Maksymova, Iryna] State Univ Econ & Technol, Econ Sci, Kryvyi Rih, Ukraine.
   [Maksymova, Iryna] State Univ Econ & Technol, Dept Int Relat, Kryvyi Rih, Ukraine.
   [Kurilyak, Vitalina] West Ukrainian Natl Univ, BD Havrylyshyn Inst Int Relat, Ternopol, Ukraine.
   [Kurilyak, Vitalina; Kurilyak, Maksym] West Ukrainian Natl Univ, Dept Int Econ, Ternopol, Ukraine.
   [Mietule, Iveta] Rezekne Acad Technol, Rezekne, Latvia.
   [Arbidane, Iluta] Rezekne Acad Technol, Fac Econ & Management, Rezekne, Latvia.
   [Kurilyak, Maksym] West Ukrainian Natl Univ, Econ Sci, Ternopol, Ukraine.
C3 Ministry of Education & Science of Ukraine; State University of
   Economics & Technology; Ministry of Education & Science of Ukraine;
   State University of Economics & Technology; Ministry of Education &
   Science of Ukraine; West Ukrainian National University; Ministry of
   Education & Science of Ukraine; West Ukrainian National University;
   Rezekne Academy of Technologies; Rezekne Academy of Technologies;
   Ministry of Education & Science of Ukraine; West Ukrainian National
   University
RP Maksymova, I (corresponding author), State Univ Econ & Technol, Econ Sci, Kryvyi Rih, Ukraine.; Maksymova, I (corresponding author), State Univ Econ & Technol, Dept Int Relat, Kryvyi Rih, Ukraine.
EM maksimova_ii@kneu.dp.ua
RI Arbidane, Iluta/ABG-5356-2020; Kurilyak, Maksym/LPQ-6980-2024; Kuryliak,
   Vitalina/GOV-4929-2022; Mietule, Iveta/AAM-4272-2020; Maksymova,
   Iryna/X-8882-2018; Mietule, Iveta/A-5299-2016
OI Maksymova, Iryna/0000-0001-9754-0414; Mietule,
   Iveta/0000-0001-7662-9866; Arbidane, Iluta/0000-0002-9762-3874;
   Kuryliak, Maksym/0000-0003-1540-0915
CR Alonso A, 1916, AARN: Political Ecology (Topic), DOI DOI 10.2139/SSRN.3471742
   [Anonymous], 2022, Emissions Gap Report 2022
   Ari I, 2022, FRONT CLIM, V4, DOI 10.3389/fclim.2022.813406
   Balogun AL, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101888
   Bracking S, 2021, WIRES CLIM CHANGE, V12, DOI 10.1002/wcc.709
   Brechin SR, 2017, CLIMATIC CHANGE, V142, P311, DOI 10.1007/s10584-017-1938-8
   Bretschger L, 2019, ENVIRON DEV ECON, V24, P560, DOI 10.1017/S1355770X19000184
   Caldwell M., 2021, Improving access to the Green Climate Fund: How the fund can better support developing country institutions, DOI [10.46830/wriwp.19.00132, DOI 10.46830/WRIWP.19.00132]
   Capros P, 2019, ENERG POLICY, V134, DOI 10.1016/j.enpol.2019.110960
   Clark R, 2018, LAND USE POLICY, V71, P335, DOI 10.1016/j.landusepol.2017.12.013
   Cui LB, 2020, CLIM POLICY, V20, P95, DOI 10.1080/14693062.2019.1690968
   Dahiya D, 2022, AIMS MICROBIOL, V8, P83, DOI 10.3934/microbiol.2022008
   Eisner E, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14042293
   Firoiu D, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14063343
   Galanti S, 2022, IFC Bulletin
   Global Climate Fund GCF, 2023, Progress Report. GCF's first replenishment period 2020-2023
   Gonzalez C. I, 2021, Banco de Espana Article, V30/21
   Green Climate Fund GCF, 2024, Open Data Library Dataset
   Haberly D, 2019, GEOFORUM, V106, P167, DOI 10.1016/j.geoforum.2019.08.009
   International Development Finance Club IDFC, 2023, IDFC Green Finance Mapping
   Ke JM, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.873880
   Maksymova I., 2023, Journal of European Economy, V22, P94
   Maksymova I, 2023, Environment. Technologies. Resources, DOI [10.17770/etr2023vol1.7291, DOI 10.17770/ETR2023VOL1.7291]
   Muhammad M., 2023, Ekonomika, V102, P130, DOI [10.15388/Ekon.2023.102.2.7, DOI 10.15388/EKON.2023.102.2.7]
   Nalau J, 2018, ENVIRON SCI POLICY, V89, P357, DOI 10.1016/j.envsci.2018.08.014
   Orindi V, 2017, Building a Climate Resilient Economy and Society, DOI [10.4337/9781785368455.00028, DOI 10.4337/9781785368455.00028]
   Pasqualino R, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132111564
   Petkovski I, 2022, J COMPETITIVENESS, V14, P79, DOI 10.7441/joc.2022.02.05
   Ravichandran S, 2022, Indian Journal of Economics and Finance, V2, P34, DOI [10.54105/ijef.B2526.112222, DOI 10.54105/IJEF.B2526.112222]
   Salazar V, 2022, INT J-TORONTO, V77, P368, DOI 10.1177/00207020221130306
   Schreyer F, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb852
   Stoll PP, 2021, CLIMATIC CHANGE, V167, DOI 10.1007/s10584-021-03190-1
   Zhao WJ, 2022, NATL SCI REV, V9, DOI 10.1093/nsr/nwac115
NR 33
TC 0
Z9 0
U1 6
U2 6
PU FINTECHALIANCE
PI Kyiv
PA Highway Kharkivska, bldg 180/21, Kyiv, UKRAINE
SN 2306-4994
EI 2310-8770
J9 FINANC CREDIT ACT
JI Financ. Credit Act.
PY 2024
VL 3
IS 56
BP 334
EP 349
DI 10.55643/fcaptp.3.56.2024.4399
PG 16
WC Business, Finance
WE Emerging Sources Citation Index (ESCI)
SC Business & Economics
GA XR0O3
UT WOS:001263290800025
OA gold
DA 2025-01-10
ER

PT J
AU Mendonca, CC
   Samuelson, LJ
   Stokes, TA
   Ramirez, MR
   Gonzalez-Benecke, C
   Aspinwall, MJ
AF Mendonca, Caren C.
   Samuelson, Lisa J.
   Stokes, Tom A.
   Ramirez, Michael R.
   Gonzalez-Benecke, Carlos
   Aspinwall, Michael J.
TI Soil moisture and vapor pressure deficit controls of longleaf pine
   physiology: results from a throughfall reduction study
SO TREES-STRUCTURE AND FUNCTION
LA English
DT Article
DE Plant water relations; Climate change adaptation; Drought; Stomatal
   conductance; Vapor pressure deficit
ID CANOPY STOMATAL CONDUCTANCE; PHOTOSYNTHETIC CAPACITY; HYDRAULIC
   ARCHITECTURE; TREE MORTALITY; DROUGHT; SENSITIVITY; LEAF; WATER; FOREST;
   LIMITATIONS
AB Key messageLongleaf pine demonstrated general resistance to reduced soil moisture and increased VPD, but results highlight the soil and atmospheric conditions that could trigger declines in longleaf pine function and productivity.Low soil moisture and high atmospheric vapor pressure deficit (VPD) independently limit tree function and forest productivity. However, questions remain about how large, established trees respond to dry soil and high VPD over longer time periods. We carried out a 3-year throughfall reduction experiment in a young (12-14-year-old) longleaf pine plantation in west Georgia (USA). We hypothesized that throughfall reduction would reduce soil moisture, leaf-scale stomatal conductance (g(s)), and net photosynthesis (P-net), but increase intrinsic water-use efficiency (iWUE). We also hypothesized that throughfall reduction would reduce canopy conductance (G(s)) at a reference VPD of 1 kPa and G(s) sensitivity to VPD. In addition, we used G(s) data collected across both treatments to identify breakpoints in the relative control of soil moisture and VPD on G(s). Throughfall reduction decreased soil moisture and caused small reductions in g(s) ( - 21%) and P-net ( - 13%), but no change in iWUE. As expected, reduced throughfall decreased G(s) and G(s) sensitivity to VPD by 20 and 8%, respectively. Despite this, throughfall reduction had very little effect on tree growth or forest productivity. Importantly, G(s) sensitivity to VPD was similar at intermediate soil moisture, but highest and lowest at soil moistures above field capacity and below the permanent wilting point, respectively. Consequently, we could identify thresholds in the relative control of soil moisture and VPD over G(s). These results demonstrate the general resistance of longleaf pine plantations to reduced soil moisture and increased VPD but highlight the soil and atmospheric conditions that could trigger declines in longleaf pine function and productivity.
C1 [Mendonca, Caren C.; Samuelson, Lisa J.; Stokes, Tom A.; Ramirez, Michael R.; Aspinwall, Michael J.] Auburn Univ, Coll Forestry Wildlife & Environm, 602 Duncan Dr, Auburn, AL 36849 USA.
   [Stokes, Tom A.] Weyerhaueser Co, 169 Weyerhaeuser Rd, Aiken, SC 29801 USA.
   [Gonzalez-Benecke, Carlos] Oregon State Univ, Coll Forestry, Dept Forest Engn Resources & Management, Corvallis, OR 97331 USA.
   [Aspinwall, Michael J.] Format Environm LLC, Sacramento, CA 95816 USA.
C3 Auburn University System; Auburn University; Oregon State University
RP Mendonca, CC; Aspinwall, MJ (corresponding author), Auburn Univ, Coll Forestry Wildlife & Environm, 602 Duncan Dr, Auburn, AL 36849 USA.; Aspinwall, MJ (corresponding author), Format Environm LLC, Sacramento, CA 95816 USA.
EM czc0117@auburn.edu; mjaspinwall@gmail.com
RI Aspinwall, Michael/ABH-9774-2020; Aspinwall, Michael/M-2083-2014
OI Aspinwall, Michael/0000-0003-0199-2972; Gonzalez-Benecke,
   Carlos/0000-0002-6359-6214; Mendonca, Caren/0000-0002-0187-6624
FU USDA National Institute of Food and Agriculture McIntire Stennis Program
   [1018413, BENNING-IGSA-16-00]; USDA National Institute of Food and
   Agriculture McIntire Stennis Program [1018413]; U.S. Army-through the
   Natural Resources Branch at Fort Benning [BENNING-IGSA-16-00]; Auburn
   University [BENNING-IGSA-16-00]; Auburn University Intramural Grants
   Program [180286]; Alabama Agricultural Experiment Station-Agriculture
   Research Enhancement & Seed Funding Program [1025522]; The Nature
   Conservancy [2282-1]
FX Support for this work was provided by USDA National Institute of Food
   and Agriculture McIntire Stennis Program (Award 1018413), the
   Intergovernmental Support Agreement between the U.S. Army-through the
   Natural Resources Branch at Fort Benning-and Auburn University (Award
   BENNING-IGSA-16-00), the Auburn University Intramural Grants Program
   (Award 180286), and the Alabama Agricultural Experiment
   Station-Agriculture Research Enhancement & Seed Funding Program (Award
   1025522). The authors thank Jake Blackstock for assistance with
   experiment installation and data collection, Dr. George Matusick for
   assistance with project funding, site selection and maintenance, the
   Georgia Department of Natural Resources for permitting site access and
   housing, and The Nature Conservancy (Grant no. 2282-1) for assisting
   with site maintenance, housing, and funds for the sap flow equipment.
CR Addington RN, 2006, PLANT CELL ENVIRON, V29, P535, DOI 10.1111/j.1365-3040.2005.01430.x
   Addington RN, 2004, TREE PHYSIOL, V24, P561, DOI 10.1093/treephys/24.5.561
   Akalusi Matthew E, 2021, Plant Environ Interact, V2, P206, DOI 10.1002/pei3.10059
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Asbjornsen H, 2021, TREE PHYSIOL, V41, P1819, DOI 10.1093/treephys/tpab056
   Aspinwall MJ, 2011, TREE PHYSIOL, V31, P78, DOI 10.1093/treephys/tpq107
   Atkin OK, 2015, NEW PHYTOL, V206, P614, DOI 10.1111/nph.13253
   Bartkowiak SM, 2015, FOREST ECOL MANAG, V354, P87, DOI 10.1016/j.foreco.2015.06.033
   Bartlett MK, 2012, ECOL LETT, V15, P393, DOI 10.1111/j.1461-0248.2012.01751.x
   Blackman CJ, 2019, TREE PHYSIOL, V39, P910, DOI 10.1093/treephys/tpz016
   Castillo AC, 2018, FORESTS, V9, DOI 10.3390/f9110727
   Cermák J, 2004, TREES-STRUCT FUNCT, V18, P529, DOI 10.1007/s00468-004-0339-6
   Choat B, 2008, NEW PHYTOL, V177, P608, DOI 10.1111/j.1469-8137.2007.02317.x
   Choat B, 2018, NATURE, V558, P531, DOI 10.1038/s41586-018-0240-x
   Clark KL, 2012, AGR FOREST METEOROL, V166, P50, DOI 10.1016/j.agrformet.2012.07.007
   Creek D, 2020, J EXP BOT, V71, P1151, DOI 10.1093/jxb/erz474
   Diaz-Espejo A, 2007, PLANT CELL ENVIRON, V30, P922, DOI 10.1111/j.1365-3040.2007.001686.x
   Domec JC, 2009, PLANT CELL ENVIRON, V32, P980, DOI 10.1111/j.1365-3040.2009.01981.x
   Drake JE, 2016, NEW PHYTOL, V211, P850, DOI 10.1111/nph.13978
   Engelbrecht BMJ, 2017, INT ASS ECOLOGY SHOR
   Ewers BE, 2000, TREE PHYSIOL, V20, P579
   Ficklin DL, 2017, J GEOPHYS RES-ATMOS, V122, P2061, DOI 10.1002/2016JD025855
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Flexas J, 2004, PLANT BIOLOGY, V6, P269, DOI 10.1055/s-2004-820867
   Flexas J, 2002, ANN BOT-LONDON, V89, P183, DOI 10.1093/aob/mcf027
   Fuchs EE, 1996, PLANT CELL ENVIRON, V19, P1091, DOI 10.1111/j.1365-3040.1996.tb00216.x
   Gonzalez-Benecke CA, 2010, TREE PHYSIOL, V30, P361, DOI 10.1093/treephys/tpp129
   Gonzalez-Benecke CA, 2011, CAN J FOREST RES, V41, P509, DOI 10.1139/X10-230
   GRANIER A, 1987, TREE PHYSIOL, V3, P309, DOI 10.1093/treephys/3.4.309
   Grossiord C, 2017, J ECOL, V105, P163, DOI 10.1111/1365-2745.12662
   Helle G, 2004, PLANT CELL ENVIRON, V27, P367, DOI 10.1111/j.0016-8025.2003.01159.x
   Hochberg U, 2017, PLANT PHYSIOL, V174, P764, DOI 10.1104/pp.16.01816
   Hubbard RM, 2001, PLANT CELL ENVIRON, V24, P113, DOI 10.1046/j.1365-3040.2001.00660.x
   Klein T, 2014, FUNCT ECOL, V28, P1313, DOI 10.1111/1365-2435.12289
   Lal A, 1996, PHOTOSYNTH RES, V49, P57, DOI 10.1007/BF00029428
   Martin-StPaul N, 2017, ECOL LETT, V20, P1437, DOI 10.1111/ele.12851
   McDowell N, 2008, NEW PHYTOL, V178, P719, DOI 10.1111/j.1469-8137.2008.02436.x
   McKibben B, 2014, NEW YORK REV BOOKS, V61, P46
   Medlyn BE, 2002, PLANT CELL ENVIRON, V25, P1167, DOI 10.1046/j.1365-3040.2002.00891.x
   Mendonca CC, 2022, FOREST ECOL MANAG, V517, DOI 10.1016/j.foreco.2022.120246
   Mitchell PJ, 2016, GLOBAL CHANGE BIOL, V22, P1677, DOI 10.1111/gcb.13177
   Novick K, 2009, ADV WATER RESOUR, V32, P809, DOI 10.1016/j.advwatres.2009.02.004
   Novick KA, 2016, NAT CLIM CHANGE, V6, P1023, DOI [10.1038/nclimate3114, 10.1038/NCLIMATE3114]
   Oishi A. Christopher, 2016, SoftwareX, V5, P139, DOI 10.1016/j.softx.2016.07.003
   Oren R, 1999, PLANT CELL ENVIRON, V22, P1515, DOI 10.1046/j.1365-3040.1999.00513.x
   Oren R, 2001, OECOLOGIA, V126, P21, DOI 10.1007/s004420000497
   Parry MAJ, 2002, ANN BOT-LONDON, V89, P833, DOI 10.1093/aob/mcf103
   Pelloux J, 2001, PLANT CELL ENVIRON, V24, P123, DOI 10.1046/j.1365-3040.2001.00665.x
   Phillips RP, 2016, FOREST ECOL MANAG, V380, P309, DOI 10.1016/j.foreco.2016.08.043
   Roman DT, 2015, OECOLOGIA, V179, P641, DOI 10.1007/s00442-015-3380-9
   Rowland L, 2015, NATURE, V528, P119, DOI 10.1038/nature15539
   Samuelson LJ, 2019, FOREST ECOL MANAG, V451, DOI 10.1016/j.foreco.2019.117557
   Samuelson LJ, 2017, ECOL APPL, V27, P244, DOI 10.1002/eap.1439
   Samuelson LJ, 2012, FOREST SCI, V58, P472, DOI 10.5849/forsci.11-049
   Samuelson LJ, 2012, FOREST ECOL MANAG, V274, P108, DOI 10.1016/j.foreco.2012.02.017
   Shestakova TA, 2017, FUNCT ECOL, V31, P1359, DOI 10.1111/1365-2435.12857
   Siqueira MB, 2006, GLOBAL CHANGE BIOL, V12, P1189, DOI 10.1111/j.1365-2486.2006.01158.x
   Starr G, 2016, FORESTS, V7, DOI 10.3390/f7050098
   Starr J.L., 2002, METHODS SOIL ANAL, P463
   Vilagrosa A, 2003, J EXP BOT, V54, P2015, DOI 10.1093/jxb/erg221
   Wear DN., 2013, SO FOREST FUTURES PR, DOI [DOI 10.2737/SRS-GTR-178, 10.2737/SRS-GTR-178]
NR 61
TC 1
Z9 1
U1 4
U2 13
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0931-1890
EI 1432-2285
J9 TREES-STRUCT FUNCT
JI Trees-Struct. Funct.
PD AUG
PY 2023
VL 37
IS 4
BP 1249
EP 1265
DI 10.1007/s00468-023-02423-3
EA JUN 2023
PG 17
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA M1FV3
UT WOS:001003892200001
DA 2025-01-10
ER

PT J
AU Smolenaars, WJ
   Jamil, MK
   Dhaubanjar, S
   Lutz, AF
   Immerzeel, W
   Ludwig, F
   Biemans, H
AF Smolenaars, Wouter Julius
   Jamil, Muhammad Khalid
   Dhaubanjar, Sanita
   Lutz, Arthur F.
   Immerzeel, Walter
   Ludwig, Fulco
   Biemans, Hester
TI Exploring the potential of agricultural system change as an integrated
   adaptation strategy for water and food security in the Indus basin
SO ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
LA English
DT Article
DE Indus basin; Climate change adaptation; Water stress; Food security;
   Water security; Agricultural development; Sustainable Development Goals;
   Hydrological modeling
ID LAND-USE; VULNERABILITY ASSESSMENT; RISK-ASSESSMENT; LAKE WATER;
   QUALITY; IMPACTS; POLLUTION; DYNAMICS; BHOPAL
AB Water security and food security in the Indus basin are highly interlinked and subject to severe stresses. Irrigation water demands presently already exceed what the basin can sustainably provide, but per-capita food availability remains limited. Rapid population growth and climate change are projected to further intensify pressure on the interdependencies between water and food security. The agricultural system of the Indus basin must therefore change and adapt to be able to achieve the associated Sustainable Development Goals (SDGs). The development of robust policies to guide such changes requires a thorough understanding of the synergies and trade-offs that different strategies for agricultural development may have for water and food security. In this study, we defined three contrasting trajectories for agricultural system change based on a review of scientific literature on regional agricultural developments and a stakeholder consultation workshop. We assessed the consequences of these trajectories for water and food security with a spatially explicit modeling framework for two scenarios of climatic and socio-economic change over the period 1980-2080. Our results demonstrate that agricultural system changes can ensure per capita food production in the basin remains sufficient under population growth. However, such changes require additional irrigation water resources and may strongly aggravate water stress. Conversely, a shift to sustainable water management can reduce water stress but has the consequence that basin-level food self-sufficiency may not be feasible in future. This suggests that biophysical limits likely exist that prevent agricultural system changes to ensure both sufficient food production and improve water security in the Indus basin under strong population growth. Our study concludes that agricultural system changes are an important adaptation mechanism toward achieving water and food SDGs, but must be developed alongside other strategies that can mitigate its adverse trade-offs.
C1 [Smolenaars, Wouter Julius; Jamil, Muhammad Khalid; Biemans, Hester] Wageningen Univ, Water Syst & Global Change Grp, Wageningen, Netherlands.
   [Jamil, Muhammad Khalid] Pakistan Agr Res Council, Islamabad, Pakistan.
   [Dhaubanjar, Sanita; Lutz, Arthur F.; Immerzeel, Walter] Univ Utrecht, Dept Phys Geog, Utrecht, Netherlands.
   [Dhaubanjar, Sanita] Int Ctr Integrated Mt Dev, Kathmandu, Nepal.
   [Biemans, Hester] Wageningen Environm Res, Wageningen, Netherlands.
C3 Wageningen University & Research; National Agricultural Research Council
   - Pakistan; Utrecht University; Wageningen University & Research
RP Smolenaars, WJ (corresponding author), Wageningen Univ, Water Syst & Global Change Grp, Wageningen, Netherlands.
EM wouter.smolenaars@wur.nl
RI Ludwig, Fulco/N-7732-2013
OI Smolenaars, Wouter/0000-0003-0511-7905
FU NWO Wotro
FX Work of all the authors is supported by the SustainIndus project funded
   by NWO Wotro (Project W 07.30318.002), the Interdisciplinary Research
   and Education Fund (INREF) of Wageningen University and Research, and
   Utrecht University. HB would like to acknowledge partial funding from
   Wageningen University and the Food Security and Valuing Water research
   program supported by the Dutch Ministry of Agriculture, Nature and Food
   Security. SD acknowledges partially support by Sustainable Development
   Investment Portfolio (SDIP), the Department of Foreign Affairs and Trade
   (DFAT), Government of Australia, the Swiss Agency for Development and
   Cooperation (SDC) and by core funds from ICIMOD contributed by the
   governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan,
   China, India, Myanmar, Nepal, Norway, Pakistan, Switzerland and the
   United Kingdom. The views and interpretations in this publication are
   those of the authors, and they are not necessarily attributable to their
   organizations.
CR Baer-Nawrocka A, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0213448
   Basharat M., 2015, Groundwater management in Indus Plain and integrated water resources management approach
   Basharat M, 2014, WATER POLICY, V16, P397, DOI 10.2166/wp.2013.060
   Biemans H, 2019, NAT SUSTAIN, V2, P594, DOI 10.1038/s41893-019-0305-3
   Biemans H, 2019, CURR OPIN ENV SUST, V40, P108, DOI 10.1016/j.cosust.2019.10.005
   Biemans H, 2016, HYDROL EARTH SYST SC, V20, P1971, DOI 10.5194/hess-20-1971-2016
   Bijl DL, 2016, ENVIRON SCI POLICY, V55, P75, DOI 10.1016/j.envsci.2015.09.005
   Bishwajit G., 2013, Agriculture Food Security, V2, P10, DOI 10.1186/2048-7010-2-10/TABLES/1
   Bondeau A, 2007, GLOBAL CHANGE BIOL, V13, P679, DOI 10.1111/j.1365-2486.2006.01305.x
   Cheema MJM, 2014, GROUNDWATER, V52, P25, DOI 10.1111/gwat.12027
   Clapp J, 2017, FOOD POLICY, V66, P88, DOI 10.1016/j.foodpol.2016.12.001
   Droppers B, 2022, AGR FOREST METEOROL, V321, DOI 10.1016/j.agrformet.2022.108971
   Farah N., 2019, J AGR RES, V57
   Fathian M, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-10947-x
   Gerten D, 2011, J HYDROMETEOROL, V12, P885, DOI 10.1175/2011JHM1328.1
   Goldewijk KK, 2011, GLOBAL ECOL BIOGEOGR, V20, P73, DOI 10.1111/j.1466-8238.2010.00587.x
   Hubert B, 2010, CROP SCI, V50, pS33, DOI 10.2135/cropsci2009.09.0530
   Immerzeel WW, 2020, NATURE, V577, P364, DOI 10.1038/s41586-019-1822-y
   Jägermeyr J, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/2/025002
   Jamil M. K., 2023, SPATIAL QUANTI UNPUB
   Khan I, 2021, ENVIRON SCI POLLUT R, V28, P7994, DOI 10.1007/s11356-020-11166-4
   Kirby M, 2017, AGR WATER MANAGE, V179, P34, DOI 10.1016/j.agwat.2016.06.001
   Laghari AN, 2012, HYDROL EARTH SYST SC, V16, P1063, DOI 10.5194/hess-16-1063-2012
   Liu JG, 2016, SCI REP-UK, V6, DOI 10.1038/srep30104
   Lutz A., 2022, NAT CLIM CHANGE, P1
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Lutz AF, 2019, REG ENVIRON CHANGE, V19, P833, DOI 10.1007/s10113-018-1433-4
   Lutz AF, 2016, INT J CLIMATOL, V36, P3988, DOI 10.1002/joc.4608
   MacAllister DJ, 2022, NAT GEOSCI, V15, P390, DOI 10.1038/s41561-022-00926-1
   MoCI, 2021, ANN REP 2020 2021
   Muzammil M, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-02913-9
   Ostad-Ali-Askari K., 2017, HDB DROUGHT WATER SC, P375
   Ostad-Ali-Askari K, 2022, APPL WATER SCI, V12, DOI 10.1007/s13201-022-01646-y
   Pastor AV, 2019, NAT SUSTAIN, V2, P499, DOI 10.1038/s41893-019-0287-1
   PBS, 2021, ANN AN REP EXT TRAD
   Portmann FT, 2010, GLOBAL BIOGEOCHEM CY, V24, DOI 10.1029/2008GB003435
   Rasul G, 2016, ENVIRON DEV, V18, P14, DOI 10.1016/j.envdev.2015.12.001
   Rasul G, 2014, ENVIRON SCI POLICY, V39, P35, DOI 10.1016/j.envsci.2014.01.010
   Salam M., 2020, BIG DATA WATER RESOU, V1, P13, DOI [DOI 10.26480/BDWRE.01.2020.13.18, 10.26480/bdwre.01.2020.10.15, DOI 10.26480/BDWRE.01.2020.10.15]
   Shahbaz P, 2022, ENVIRON SCI POLLUT R, V29, P16925, DOI 10.1007/s11356-021-16844-5
   Sidhu BS, 2021, GROUNDWATER SUST DEV, V12, DOI 10.1016/j.gsd.2020.100498
   Singh S, 2018, FOOD SECUR, V10, P965, DOI 10.1007/s12571-018-0823-2
   Smolenaars WJ, 2022, HYDROL EARTH SYST SC, V26, P861, DOI 10.5194/hess-26-861-2022
   Smolenaars WJ, 2021, FUTURES, V133, DOI 10.1016/j.futures.2021.102831
   Tariq A., 2014, Pakistan Journal of Commerce and Social Sciences (PJCSS), V8, P540
   Vinca A, 2021, NAT SUSTAIN, V4, P331, DOI 10.1038/s41893-020-00654-7
   Vörösmarty CJ, 2000, SCIENCE, V289, P284, DOI 10.1126/science.289.5477.284
   Wada Y, 2019, ONE EARTH, V1, P185, DOI 10.1016/j.oneear.2019.10.006
   Watto MA, 2015, J SCI FOOD AGR, V95, P1860, DOI 10.1002/jsfa.6887
   Wijngaard RR, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0190224
   Wijngaard RR, 2018, HYDROL EARTH SYST SC, V22, P6297, DOI 10.5194/hess-22-6297-2018
   Yang YCE, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000710
   Yoon T, 2015, WATER RESOUR RES, V51, P787, DOI 10.1002/2013WR014201
NR 53
TC 3
Z9 4
U1 3
U2 8
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1387-585X
EI 1573-2975
J9 ENVIRON DEV SUSTAIN
JI Environ. Dev. Sustain.
PD JUN
PY 2024
VL 26
IS 6
BP 15177
EP 15212
DI 10.1007/s10668-023-03245-6
EA APR 2023
PG 36
WC Green & Sustainable Science & Technology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA RX2E7
UT WOS:000973216200004
OA hybrid
DA 2025-01-10
ER

PT J
AU Lane, RA
   Coxon, G
   Freer, J
   Seibert, J
   Wagener, T
AF Lane, Rosanna A.
   Coxon, Gemma
   Freer, Jim
   Seibert, Jan
   Wagener, Thorsten
TI A large-sample investigation into uncertain climate change impacts on
   high flows across Great Britain
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID RIVER FLOW; PROBABILISTIC IMPACTS; HYDROLOGICAL MODELS; WATER-RESOURCES;
   BIAS CORRECTION; FUTURE; UK; PROJECTIONS; FREQUENCY; ENSEMBLE
AB Climate change may significantly increase flood risk globally, but there are large uncertainties in both future climatic changes and how these propagate into changing river flows. Here, the impact of climate change on the magnitude and frequency of high flows is analysed for Great Britain (GB) to provide the first spatially consistent GB projections to include both climate ensembles and hydrological model parameter uncertainties. We use the latest high-resolution (12 km) regional climate model ensemble from the UK Climate Projections (UKCP18). These projections are based on a perturbed-physics ensemble of 12 regional climate model simulations and allow exploration of climate model uncertainty beyond the variability caused by the use of different models. We model 346 larger (>144 km(2)) catchments across GB using the DECIPHeR hydrological modelling framework. Generally, results indicated an increase in the magnitude and frequency of high flows (Q10, Q1, and annual maximum) along the western coast of GB in the future (2050-2075), with increases in annual maximum flows of up to 65 % for western Scotland. In contrast, median flows (Q50) were projected to decrease across GB. Even when using an ensemble based on a single regional climate model (RCM) structure, all flow projections contained large uncertainties. While the RCM parameters were the largest source of uncertainty overall, hydrological modelling uncertainties were considerable in eastern and south-eastern England. Regional variations in flow projections were found to relate to (i) differences in climatic change and (ii) catchment conditions during the baseline period as characterised by the runoff coefficient (mean discharge divided by mean precipitation). Importantly, increased heavy-precipitation events (defined by an increase in 99th percentile precipitation) did not always result in increased flood flows for catchments with low runoff coefficients, highlighting the varying factors leading to changes in high flows. These results provide a national overview of climate change impacts on high flows across GB, which will inform climate change adaptation, and highlight the impact of hydrological model parameter uncertainties when modelling climate change impact on high flows.
C1 [Lane, Rosanna A.; Coxon, Gemma; Freer, Jim] Univ Bristol, Sch Geog Sci, Bristol BS8 1SS, Avon, England.
   [Coxon, Gemma; Freer, Jim; Wagener, Thorsten] Univ Bristol, Cabot Inst, Bristol BS8 1UJ, Avon, England.
   [Freer, Jim] Univ Saskatchewan, Ctr Hydrol, Canmore, AB T1W 3G1, Canada.
   [Seibert, Jan] Univ Zurich, Dept Geog, Zurich, Switzerland.
   [Wagener, Thorsten] Univ Bristol, Dept Civil Engn, Bristol BS8 1TR, Avon, England.
   [Wagener, Thorsten] Univ Potsdam, Inst Environm Sci & Geog, D-14476 Potsdam, Germany.
   [Lane, Rosanna A.] UK Ctr Ecol & Hydrol, Wallingford OX10 8BB, Oxon, England.
C3 University of Bristol; University of Bristol; University of
   Saskatchewan; University of Zurich; University of Bristol; University of
   Potsdam; UK Centre for Ecology & Hydrology (UKCEH)
RP Lane, RA (corresponding author), Univ Bristol, Sch Geog Sci, Bristol BS8 1SS, Avon, England.; Lane, RA (corresponding author), UK Ctr Ecol & Hydrol, Wallingford OX10 8BB, Oxon, England.
EM roslan@ceh.ac.uk
RI Seibert, Jan/B-1432-2009; Lane, Rosanna/ABH-5708-2020; Wagener,
   Thorsten/C-2062-2008
OI Seibert, Jan/0000-0002-6314-2124; Coxon, Gemma/0000-0002-8837-460X;
   Lane, Rosanna/0000-0003-4176-9214; Wagener, Thorsten/0000-0003-3881-5849
FU Engineering and Physical Sciences Research Council as part of the Water
   Informatics Science and Engineering Centre for Doctoral Training
   [EP/L016214/1]; FLF [MR/V022857/1] Funding Source: UKRI
FX This work has been supported by the Engineering and Physical Sciences
   Research Council (grant no. EP/L016214/1), as part of the Water
   Informatics Science and Engineering Centre for Doctoral Training.
CR Addor N, 2014, WATER RESOUR RES, V50, P7541, DOI 10.1002/2014WR015549
   Addor N, 2014, HYDROL PROCESS, V28, P4823, DOI 10.1002/hyp.10238
   Arnell NW, 2011, HYDROL EARTH SYST SC, V15, P897, DOI 10.5194/hess-15-897-2011
   Bell VA, 2007, INT J CLIMATOL, V27, P1657, DOI 10.1002/joc.1539
   Bell VA, 2016, CLIMATIC CHANGE, V136, P539, DOI 10.1007/s10584-016-1637-x
   Bosshard T, 2013, WATER RESOUR RES, V49, P1523, DOI 10.1029/2011WR011533
   Brown CM, 2015, WATER RESOUR RES, V51, P6110, DOI 10.1002/2015WR017114
   Buurman J, 2016, POLICY SOC, V35, P137, DOI 10.1016/j.polsoc.2016.05.002
   Centre for Ecology and Hydrology, 2016, NAT RIV FLOW ARCH
   Chan WCH, 2022, PROG PHYS GEOG, V46, P589, DOI 10.1177/03091333221079201
   Charlton MB, 2014, J HYDROL, V519, P1723, DOI 10.1016/j.jhydrol.2014.09.008
   Chegwidden OS, 2019, EARTHS FUTURE, V7, P623, DOI 10.1029/2018EF001047
   Chen J, 2011, WATER RESOUR RES, V47, DOI 10.1029/2011WR010602
   Clark MP, 2016, CURR CLIM CHANGE REP, V2, P55, DOI 10.1007/s40641-016-0034-x
   Cloke HL, 2013, Q J ROY METEOR SOC, V139, P282, DOI 10.1002/qj.1998
   Collet L, 2018, HYDROL EARTH SYST SC, V22, P5387, DOI 10.5194/hess-22-5387-2018
   Coxon G., 2019, ZENODO, DOI [10.5281/zenodo.2604120, DOI 10.5281/ZENODO.2604120]
   Coxon G, 2020, EARTH SYST SCI DATA, V12, P2459, DOI 10.5194/essd-12-2459-2020
   Coxon G, 2019, GEOSCI MODEL DEV, V12, P2285, DOI 10.5194/gmd-12-2285-2019
   De Niel J, 2019, WATER RESOUR MANAG, V33, P4319, DOI 10.1007/s11269-019-02370-0
   Dixon H, 2013, HYDROLOG SCI J, V58, P1383, DOI 10.1080/02626667.2013.787486
   Eicker A, 2016, J GEOPHYS RES-ATMOS, V121, P733, DOI 10.1002/2015JD023808
   Engin BE, 2017, ENVIRON MONIT ASSESS, V189, DOI 10.1007/s10661-017-6059-3
   Environment Agency, NAT FLOOD COAST ER R
   Environment Agency, FLOOD RISK ASS CLIM
   Fowler HJ, 2009, INT J CLIMATOL, V29, P385, DOI 10.1002/joc.1827
   Hannaford J, 2015, PROG PHYS GEOG, V39, P29, DOI 10.1177/0309133314536755
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Huntington TG, 2006, J HYDROL, V319, P83, DOI 10.1016/j.jhydrol.2005.07.003
   Ivancic TJ, 2015, CLIMATIC CHANGE, V133, P681, DOI 10.1007/s10584-015-1476-1
   Johnson F, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010464
   Kay AL, 2008, J HYDROL, V358, P221, DOI 10.1016/j.jhydrol.2008.06.005
   Kay AL, 2021, ADV WATER RESOUR, V151, DOI 10.1016/j.advwatres.2021.103909
   Kay AL, 2014, INT J CLIMATOL, V34, P3368, DOI 10.1002/joc.3913
   Kay AL, 2014, REG ENVIRON CHANGE, V14, P1243, DOI 10.1007/s10113-013-0564-x
   Kay AL, 2014, REG ENVIRON CHANGE, V14, P1215, DOI 10.1007/s10113-013-0563-y
   Kay AL, 2009, CLIMATIC CHANGE, V92, P41, DOI 10.1007/s10584-008-9471-4
   Kay AL, 2020, HYDROL PROCESS, V34, P1081, DOI 10.1002/hyp.13644
   Keller VDJ, 2015, EARTH SYST SCI DATA, V7, P143, DOI 10.5194/essd-7-143-2015
   Köplin N, 2014, HYDROL PROCESS, V28, P2567, DOI 10.1002/hyp.9757
   Kundzewicz ZW, 2018, ENVIRON SCI POLICY, V79, P1, DOI 10.1016/j.envsci.2017.10.008
   Laizé CLR, 2010, J HYDROL, V389, P186, DOI 10.1016/j.jhydrol.2010.05.048
   Lane R., 2021, DECIPHER MPR 1 0, DOI [10.5281/zenodo.4646179, DOI 10.5281/ZENODO.4646179]
   Lane RA, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR028393
   Lane RA, 2019, HYDROL EARTH SYST SC, V23, P4011, DOI 10.5194/hess-23-4011-2019
   Lane RAA, 2021, FRONT WATER, V3, DOI 10.3389/frwa.2021.684982
   Lowe J. A., 2019, UKCP18 science overview report
   Mendoza PA, 2015, J HYDROMETEOROL, V16, P762, DOI 10.1175/JHM-D-14-0104.1
   Meresa HK, 2017, HYDROL EARTH SYST SC, V21, P4245, DOI 10.5194/hess-21-4245-2017
   Met Office, REG 12 KM LOC 2 2 KM
   Met Office, 2019, UK CLIMATE PROJECTIO
   Met Office Hadley Centre, 2019, UKCP18 GUID DAT AV
   Met Office Hadley Centre, 2018, UKCP18 REG CLIM MOD
   Mizukami N, 2017, WATER RESOUR RES, V53, P8020, DOI 10.1002/2017WR020401
   Moon H, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4169
   Murphy J. M., 2018, UKCP18 Land Projections: Science Report
   Nikulin G, 2011, TELLUS A, V63, P41, DOI 10.1111/j.1600-0870.2010.00466.x
   Ning L, 2012, J CLIMATE, V25, P509, DOI 10.1175/2011JCLI4091.1
   Petrow T, 2009, J HYDROL, V371, P129, DOI 10.1016/j.jhydrol.2009.03.024
   Pool S, 2018, HYDROLOG SCI J, V63, P1941, DOI 10.1080/02626667.2018.1552002
   Prudhomme C, 2013, HYDROL EARTH SYST SC, V17, P1365, DOI 10.5194/hess-17-1365-2013
   Prudhomme C, 2012, HYDROL PROCESS, V26, P1115, DOI 10.1002/hyp.8434
   Prudhomme C, 2009, CLIMATIC CHANGE, V93, P197, DOI 10.1007/s10584-008-9461-6
   Reynard NS, 2017, PROG PHYS GEOG, V41, P222, DOI 10.1177/0309133317702566
   Robinson E.L., 2016, Climate hydrology and ecology research support system potential evapotranspiration dataset for Great Britain (1961-2017) CHESS-PE
   Rudd AC, 2019, CLIMATIC CHANGE, V156, P323, DOI 10.1007/s10584-019-02528-0
   Samaniego L, 2017, HYDROL EARTH SYST SC, V21, P4323, DOI 10.5194/hess-21-4323-2017
   Samaniego L, 2010, WATER RESOUR RES, V46, DOI 10.1029/2008WR007327
   Sawicz KA, 2014, HYDROL EARTH SYST SC, V18, P273, DOI 10.5194/hess-18-273-2014
   Schwalm CR, 2020, P NATL ACAD SCI USA, V117, P19656, DOI 10.1073/pnas.2007117117
   Seibert J, 2018, HYDROL PROCESS, V32, P1120, DOI 10.1002/hyp.11476
   Sharma A, 2018, WATER RESOUR RES, V54, P8545, DOI 10.1029/2018WR023749
   Shrestha B, 2016, J HYDROL, V540, P1088, DOI 10.1016/j.jhydrol.2016.07.019
   Shuttleworth WJames., 2012, TERRESTRIAL HYDROMET
   Singh R, 2014, HYDROLOG SCI J, V59, P29, DOI 10.1080/02626667.2013.819431
   Smith A, 2014, HYDROL PROCESS, V28, P2810, DOI 10.1002/hyp.9815
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Svensson C, 2005, HYDROLOG SCI J, V50, P811, DOI 10.1623/hysj.2005.50.5.811
   Tanguy M., 2014, GRIDDED ESTIMATES DA, DOI [10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e, DOI 10.5285/5DC179DC-F692-49BA-9326-A6893A503F6E]
   Teutschbein C, 2012, J HYDROL, V456, P12, DOI 10.1016/j.jhydrol.2012.05.052
   Thober S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa9e35
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   Veijalainen N, 2010, J HYDROL, V391, P333, DOI 10.1016/j.jhydrol.2010.07.035
   Velázquez JA, 2013, HYDROL EARTH SYST SC, V17, P565, DOI 10.5194/hess-17-565-2013
   von Christierson B, 2012, J HYDROL, V424, P48, DOI 10.1016/j.jhydrol.2011.12.020
   Wagener T, 2010, WATER RESOUR RES, V46, DOI 10.1029/2009WR008906
   Wang GQ, 2012, HYDROL EARTH SYST SC, V16, P231, DOI 10.5194/hess-16-231-2012
   Watts G, 2015, PROG PHYS GEOG, V39, P6, DOI 10.1177/0309133314542957
   Wilby RL, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004065
NR 89
TC 11
Z9 11
U1 4
U2 14
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1027-5606
EI 1607-7938
J9 HYDROL EARTH SYST SC
JI Hydrol. Earth Syst. Sci.
PD NOV 7
PY 2022
VL 26
IS 21
BP 5535
EP 5554
DI 10.5194/hess-26-5535-2022
PG 20
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA 5Y7FY
UT WOS:000879447800001
OA gold, Green Accepted, Green Submitted, Green Published
DA 2025-01-10
ER

PT J
AU Libanda, B
AF Libanda, Brigadier
TI Public Institutional Structures for Disaster Preparedness in the Cereal
   Value Chain: A Zambian Case Study
SO GEOHAZARDS
LA English
DT Article
DE climate change; adaptation; food security; institutional capacity;
   governance
ID CLIMATE-CHANGE ADAPTATION; EXTREME EVENTS; INSURANCE; RISK
AB Increasing extreme climate events and cyclonic activities provide clear evidence that the Southern African Development Community (SADC) region is a hotspot for climate change-driven natural disasters which critically disrupt agricultural production cycles. This is especially true with regard to the production of cereal, produce widely used to represent food security. Although studies have attempted to disentangle the effect of demand vis a vis projected population growth on cereal production across the region, the contradiction between cereal production and climate disaster preparedness remains poorly resolved. Therefore, literature on the subject matter is scanty. The present study is motivated by the need to overcome this paucity of literature and thus, deepen our understanding of cereal production and climate disaster preparedness in the region. Therefore, the main aim of this study is to assess public institutional support structures that are currently being employed for climate disaster preparedness in the cereal value chain across Zambia as perceived by small scale farmers. After a comprehensive assessment of focus group discussions (FGDs), several points emerge specifically highlighting four salient findings: first, results show that a government-led Farmer Input Support Programme (FISP) is the only strategy particularly targeted at disaster preparedness. All other initiatives are targeted at improving or safeguarding livelihoods with some components having a ripple effect on the cereal value chain. Second, results show that climate forecasts that are supposed to trigger early action are generally characterized by low prediction skill with more false alarms and misses than hits. Third, forecasts were found to lack geographical specificity with generalities over large areas being common thus, diminishing their usefulness at the local scale. Fourth, end-users found forecasts to usually contain technical jargon that is difficult to decipher especially that most small-scale farmers are illiterate. This study concludes that to fully support the cereal value chain and realize food security in Zambia, policy formulation that champion the establishment of an effective early warning and early action system (EWEAS) involving multiple interest groups and actors should be considered a matter of urgency.
C1 [Libanda, Brigadier] Univ Potsdam, Potsdam Ctr Publ Policy & Management, August Bebel Str 89,Haus 7, D-14482 Potsdam, Germany.
C3 University of Potsdam
RP Libanda, B (corresponding author), Univ Potsdam, Potsdam Ctr Publ Policy & Management, August Bebel Str 89,Haus 7, D-14482 Potsdam, Germany.
EM brigadier.libanda@uni-potsdam.de
RI , Libanda/N-9781-2019
OI Libanda, Brigadier/0000-0001-8215-5572
FU Deutscher Akademischer Austauschdienst (DAAD)
FX The author was supported by the Deutscher Akademischer Austauschdienst
   (DAAD; German Academic Exchange Service). Ngonga Chilekana is
   acknowledged for leading the data collection process and for reviewing
   the initial draft of this manuscript. Pertinent comments from two
   anonymous Reviewers, the Editor, Taylor Schildgen, Markus Seyfried, and
   the MPM 2020 of the University of Potsdam are also acknowledged.
CR ACAPS, 2019, Zambia Drought-Southern Province
   Alexandratos N., 2012, ESA Working Paper, DOI 10.22004/ag.econ.288998
   [Anonymous], 2017, ACAPS Briefing Note: Floods.
   [Anonymous], 2010, CLIM SMART AGR POL P
   [Anonymous], 2021, FAO GIEWS Country Brief: Zambia
   [Anonymous], 2021, IFRC African Floods.
   Anríquez G, 2013, FOOD POLICY, V38, P190, DOI 10.1016/j.foodpol.2012.02.010
   Chapoto A., 2019, Gates Open Res, V3, P1168, DOI [10.21955/gatesopenres.1116019.1, DOI 10.21955/GATESOPENRES.1116019.1]
   Chilufya W., 2019, Beyond Maize: Exploring Agricultural Diversification in Zambia
   Dworkin SL, 2012, ARCH SEX BEHAV, V41, P1319, DOI 10.1007/s10508-012-0016-6
   Engelbrecht CJ, 2013, INT J CLIMATOL, V33, P173, DOI 10.1002/joc.3420
   FAO, 2019, GLOB INF EARL WARN S
   FAO ECA Regional Overview of Food Security and Nutrition, 2018, Addressing the Threat from Climate Variability and Extremes for Food Security and Nutrition
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Galvin R, 2015, J BUILD ENG, V1, P2, DOI 10.1016/j.jobe.2014.12.001
   Hichambwa M, 2011, Agricultural Commercialization and Landholding Size in Zambia's Small- and Medium-Scale Farm Sector
   Houghton JT, 2001, CLIMATE CHANGE 2001: THE SCIENTIFIC BASIS, P1
   Hughes S, 2015, URBAN CLIM, V14, P17, DOI 10.1016/j.uclim.2015.06.003
   IPC Zambia, 2021, Acute Food Insecurity Projection Update February-March 2021
   Knoema, 2018, Zambia-Land under Cereal Production
   Kunreuther H, 2015, GENEVA PAP R I-ISS P, V40, P741, DOI 10.1057/gpp.2015.14
   Kuteya A.N., 2012, Is the government of Zambia's subsidy to maize millers benefiting the consumer?
   Libanda B, 2019, J ARID LAND, V11, P180, DOI 10.1007/s40333-019-0053-2
   Madhumita P, 2020, Food Insecurity in Southern Africa up 10%
   Makondo CC, 2020, THEOR APPL CLIMATOL, V140, P271, DOI 10.1007/s00704-019-03029-x
   Matsueda M, 2015, METEOROL APPL, V22, P213, DOI 10.1002/met.1444
   McNeeley SM, 2014, WEATHER CLIM SOC, V6, P506, DOI 10.1175/WCAS-D-13-00027.1
   Miglietta PP, 2021, AGRIC FINANCE REV, V81, P237, DOI 10.1108/AFR-04-2020-0061
   Mubaya CP, 2017, CLIM RISK MANAG, V16, P93, DOI 10.1016/j.crm.2017.03.003
   Musonda B, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11121268
   Mwenda M, 2019, The Drought in Zambia is Causing Starvation, a Power Crisis and Threatening the Victoria Falls
   New M, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006289
   OCHA Zambia, 2020, Prolonged Drought Increases Food Insecurity
   Patnaik U, 2016, GLOB BUS REV, V17, P161, DOI 10.1177/0972150915610712
   Pieterse A, 2021, DEV SO AFR, V38, P493, DOI 10.1080/0376835X.2020.1760790
   RAYNER S, 1992, SOCIAL THEORIES OF RISK, P83
   Red Cross, 2009, Early Warning-Early Action: Mechanisms for Rapid Decision Making. Drought Preparedness and Response in the Arid and Semi-Arid Lands of Ethiopia, Kenya, Uganda, and in the East African Region
   ReliefWeb Zambia, 2020, Prolonged Drought Increases Food Insecurity
   Rossel J.D., 2008, The Impact of Climatic Shocks on Child Nutrition in Peru, P1
   Smolka A, 2006, PHILOS T R SOC A, V364, P2147, DOI 10.1098/rsta.2006.1818
   Suarez P., 2010, Towards forecast-based humanitarian decisions: Climate science to get from early warning to early action
   Thompson Michael., 1998, HUMAN CHOICE CLIMATE
   UNDP, 2017, Real-Time Weather Forecasts are Helping Zambian Women Farmers Win Their Battle against the Impact of Climate Change
   Wang B, 2014, NAT HAZARDS, V74, P1649, DOI 10.1007/s11069-014-1260-y
   Xu Z, 2020, LANCET RESP MED, V8, P420, DOI 10.1016/S2213-2600(20)30076-X
NR 45
TC 3
Z9 3
U1 0
U2 0
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2624-795X
J9 GEOHAZARDS-BASEL
JI Geohazards
PD DEC
PY 2021
VL 2
IS 4
BP 352
EP 365
DI 10.3390/geohazards2040019
PG 14
WC Geosciences, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Geology
GA LN4K0
UT WOS:001187467400001
OA gold
DA 2025-01-10
ER

PT J
AU Hoerterer, C
   Schupp, MF
   Benkens, A
   Nickiewicz, D
   Krause, G
   Buck, BH
AF Hoerterer, Christina
   Schupp, Maximilian F.
   Benkens, Andreas
   Nickiewicz, Dustin
   Krause, Gesche
   Buck, Bela H.
TI Stakeholder Perspectives on Opportunities and Challenges in Achieving
   Sustainable Growth of the Blue Economy in a Changing Climate
SO FRONTIERS IN MARINE SCIENCE
LA English
DT Article
DE adaptation; fisheries; tourism; North Sea; aquaculture; blue growth;
   saefood
ID MANAGEMENT; IMPACTS; HABITATS; TOURISM; SHIFTS
AB Coastal marine environments provide livelihoods as billions of people around the world depend greatly on sustainability efforts in the Blue Economy. In this study, we investigated how stakeholders from important Blue Economy sectors along the German North Sea coast perceive the impacts of climate change on their daily work life and the growth of the Blue Economy. In a two-stage approach we first conducted two stakeholder workshops with representatives from the regional sea food sector, science, NGOs and local authorities, in order to identify important issues linked to climate change affecting environment, society, economy and policy. In the second stage, we conducted semi-structured interviews with key knowledge holders from the Blue Economy, to evaluate and validate the most important issues identified during the first stage, and the impacts on the respective sectors. The workshop participants identified perceptible effects of climate change on their marine environment. Early career scientists showed that they possess a clear focus on measures for climate change adaptation, transdisciplinary approaches and knowledge transfer. The interviews revealed that the climate change effects could be perceived as both negative and positive, depending on the sector. Other issues, especially political decisions and developments are perceived to have a greater immediate impact on the Blue Economy than the slow progress of climate change effects. Additionally, increased human activities, in the form of new or intensified uses like marine renewable energy generation, have a greater influence and lead to conflicts between the Blue Economy sectors. Our study showed that economic and societal stakeholders in Germanys North Sea region are aware of climate change and already perceive its effects on their businesses. Synergies and conflicts between the sectors and political decisions might influence sustainable growth of the Blue Economy in highly contested regions, such as the North Sea basin, much stronger than the effects of climate change. This calls for a more flexible and adaptive approach to policymaking, taking into account the changing environmental, social and economic realities.
C1 [Hoerterer, Christina; Schupp, Maximilian F.; Benkens, Andreas; Nickiewicz, Dustin; Krause, Gesche; Buck, Bela H.] Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Bremerhaven, Germany.
   [Schupp, Maximilian F.] Univ Dundee, Sch Social Sci, Dundee, Scotland.
   [Buck, Bela H.] Univ Appl Sci Bremerhaven, Appl Marine Biol & Aquaculture, Fac 1, Bremerhaven, Germany.
C3 Helmholtz Association; Alfred Wegener Institute, Helmholtz Centre for
   Polar & Marine Research; University of Dundee
RP Hoerterer, C (corresponding author), Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Bremerhaven, Germany.
EM Christina.Hoerterer@awi.de
RI Benkens, Andreas/HKO-9661-2023; Hoerterer, Christina/GXF-7124-2022;
   Krause, Gesche/L-7394-2017; Benkens, Andreas/Q-5550-2016; Buck, Bela
   H/B-8772-2012
OI Schupp, Maximilian Felix/0000-0001-7546-1694; Krause,
   Gesche/0000-0001-7917-7121; Hoerterer, Christina/0000-0001-5627-456X;
   Benkens, Andreas/0000-0001-7943-7843; Buck, Bela H/0000-0001-7491-3273
FU umbrella of the "Earth System Knowledge Platform (ESKP)" Call for Tender
   at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
   Research [PAGESKP077, IP80770003]
FX The projects "Biodiversity and Climate Change: Impacts on Local
   Stakeholder on the North Sea Coast" (BioDiv; grant no. PAGESKP077) and
   "Blue Growth in a Changing Environment" (BlueChange; grant no.
   IP80770003) were funded under the umbrella of the "Earth System
   Knowledge Platform (ESKP)" Call for Tender at the Alfred Wegener
   Institute, Helmholtz Centre for Polar and Marine Research. The "Earth
   System Knowledge Platform (ESKP)" is the knowledge platform of the
   Research Field Earth and Environment of the Helmholtz Association. It
   centers around knowledge transfer between science and society. The first
   workshop (WS1) with a broad audience was endorsed by the "European
   Maritime Day 2016."
CR AFW and COFAD, 2007, STRAT INT ORTL ENT F
   Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   Attrill MJ, 2007, LIMNOL OCEANOGR, V52, P480, DOI 10.4319/lo.2007.52.1.0480
   Barbesgaard M, 2018, J PEASANT STUD, V45, P130, DOI 10.1080/03066150.2017.1377186
   Baudron AR, 2015, FISH FISH, V16, P563, DOI 10.1111/faf.12079
   Brander K., 2003, International Council for the Exploration of the Sea (ICES) Journal of Marine Science, V219, P261
   Brander K, 2010, J MARINE SYST, V79, P389, DOI 10.1016/j.jmarsys.2008.12.015
   Brown J., 2007, The world cafe: shaping our futrues through conversations that matter
   Bundesgesetzblatt, 2009, VER RAUM DTSCH AUSSC
   Burge CA, 2014, ANNU REV MAR SCI, V6, P249, DOI 10.1146/annurev-marine-010213-135029
   Callaway R, 2012, AQUAT CONSERV, V22, P389, DOI 10.1002/aqc.2247
   Carstensen D., 2014, OKOLOGISCHER OKONOMI
   Cheung WWL, 2017, FISH FISH, V18, P254, DOI 10.1111/faf.12177
   Cheung WWL, 2012, AQUAT CONSERV, V22, P368, DOI 10.1002/aqc.2248
   Childs J, 2019, J POLIT ECOL, V26, P323, DOI 10.2458/v26i1.23162
   de Jonge VN, 2000, CONT SHELF RES, V20, P1655, DOI 10.1016/S0278-4343(00)00042-X
   Defra, 2019, GUID FISH SECT PREP
   Döring M, 2018, J COAST CONSERV, V22, P131, DOI 10.1007/s11852-016-0478-0
   Doney SC, 2012, ANNU REV MAR SCI, V4, P11, DOI 10.1146/annurev-marine-041911-111611
   Douvere F, 2009, J ENVIRON MANAGE, V90, P77, DOI 10.1016/j.jenvman.2008.07.004
   Dulvy NK, 2008, J APPL ECOL, V45, P1029, DOI 10.1111/j.1365-2664.2008.01488.x
   Edwards M, 2004, NATURE, V430, P881, DOI 10.1038/nature02808
   Eikeset AM, 2018, MAR POLICY, V87, P177, DOI 10.1016/j.marpol.2017.10.019
   Emeis KC, 2015, J MARINE SYST, V141, P18, DOI 10.1016/j.jmarsys.2014.03.012
   EU, 2016, WORKSH BACKGR PAP
   European Commission (EC), 2017, COMM STAFF WORK DOC
   FBG and COFAD, 2016, STRAT INT ORTL ENT F
   Franke HD, 2004, HELGOLAND MAR RES, V58, P303, DOI 10.1007/s10152-004-0193-3
   Gaines SD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao1378
   Harley CDG, 2006, ECOL LETT, V9, P228, DOI 10.1111/j.1461-0248.2005.00871.x
   Hawkins AJS, 2013, J SHELLFISH RES, V32, P237, DOI 10.2983/035.032.0201
   Heath MR, 2012, AQUAT CONSERV, V22, P337, DOI 10.1002/aqc.2244
   Hellmann JJ, 2008, CONSERV BIOL, V22, P534, DOI 10.1111/j.1523-1739.2008.00951.x
   Hörterer C, 2018, SPRINGERBR EARTH SYS, P31, DOI 10.1007/978-3-319-75919-7_5
   Horterer C., 2017, PEOPLE N SEA CHANGIN
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jones SJ, 2010, J BIOGEOGR, V37, P2243, DOI 10.1111/j.1365-2699.2010.02386.x
   Klein RA, 2011, J HOSP TOUR MANAG, V18, P107, DOI 10.1375/jhtm.18.1.107
   Koch M., 2015, KLIMAANPASSUNGSSTRAT
   Lowe J.A., 2009, UK CLIMATE PROJECTIO
   Metcalf SJ, 2015, ECOL SOC, V20, DOI 10.5751/ES-07509-200235
   Mortensen LO, 2018, MAR POLICY, V87, P1, DOI 10.1016/j.marpol.2017.09.031
   nordwest2050, 2014, INT ROADM CHANG FAHR
   Occhipinti-Ambrogi A, 2007, MAR POLLUT BULL, V55, P342, DOI 10.1016/j.marpolbul.2006.11.014
   Peperzak L, 2003, ACTA OECOL, V24, pS139, DOI 10.1016/S1146-609X(03)00009-2
   Perry AL, 2005, SCIENCE, V308, P1912, DOI 10.1126/science.1111322
   RegionNord, 2015, INTEGRIERTE ENTWICKL
   Reise K, 2005, HELGOLAND MAR RES, V59, P9, DOI 10.1007/s10152-004-0202-6
   Rijnsdorp AD, 2009, ICES J MAR SCI, V66, P1570, DOI 10.1093/icesjms/fsp056
   Schuchardt B., 2012, VULNERABILITAT METRO
   Schupp MF, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00165
   Seitz RD, 2014, ICES J MAR SCI, V71, P648, DOI 10.1093/icesjms/fst152
   Silver JJ, 2015, J ENVIRON DEV, V24, P135, DOI 10.1177/1070496515580797
   Sims R, 2009, J SUSTAIN TOUR, V17, P321, DOI 10.1080/09669580802359293
   Sorte CJB, 2010, GLOBAL ECOL BIOGEOGR, V19, P303, DOI 10.1111/j.1466-8238.2009.00519.x
   Stoll JS, 2015, ECOL SOC, V20, DOI 10.5751/ES-07686-200240
   Tiller R, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00267
   United Nations, 2017, OCEAN C
   United Nations, 2014, BLUE EC CONC PAP
   Vensim, 2015, SOFTW 7 3
   Voyer M, 2019, RESOUR POLICY, V62, P102, DOI 10.1016/j.resourpol.2019.02.020
   Voyer M, 2018, J ENVIRON POL PLAN, V20, P595, DOI 10.1080/1523908X.2018.1473153
   Westerbom M, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00292
   Westlund L., 2007, 479 FAO
   Wiltshire KH, 2010, ESTUAR COAST, V33, P295, DOI 10.1007/s12237-009-9228-y
NR 65
TC 17
Z9 19
U1 1
U2 51
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-7745
J9 FRONT MAR SCI
JI Front. Mar. Sci.
PD JAN 14
PY 2020
VL 6
AR 795
DI 10.3389/fmars.2019.00795
PG 12
WC Environmental Sciences; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology
GA KD6MI
UT WOS:000507978400001
OA gold, Green Published
DA 2025-01-10
ER

PT C
AU Bizarro, AF
   Alexandre, LV
AF Bizarro, Alcides F.
   Alexandre, Luis, V
GP IOP
TI STORM Policies and Recommendations - a new vision for authorities, first
   responders and civil protection towards an effective protection of
   cultural heritage
SO INTERNATIONAL CONFERENCE FLORENCE HERI-TECH: THE FUTURE OF HERITAGE
   SCIENCE AND TECHNOLOGIES
SE IOP Conference Series-Materials Science and Engineering
LA English
DT Proceedings Paper
CT 2nd International Conference on Florence Heri-Tech - The Future of
   Heritage Science and Technologies
CY OCT 14-16, 2020
CL ELECTR NETWORK
SP European Union, European Reg Dev Fund, Sharing Solut Better Reg Policies
AB Every year, cultural heritage all over the world is lost or damaged under the devastating impact of climate change and natural hazards. Many times these damages are irreversible and often result from insufficient and disjointed preparedness systems, unable to cope with these threats. Awareness of this situation and the urgent need to find solutions for it has been a motivational call to taking actions towards the raising of consciousness of all involved, the incentive to training and the sharing of good practices. Project STORM - Safeguarding Cultural Heritage through Technical and Organisational Resources Management (funded by the European Union's Horizon 2020 research and innovation programme - H2020-DRS-11-2015: Disaster Resilience & Climate), introduced a new vision for authorities, first responders and civil protection services towards cultural heritage, by proposing new policies and recommendations. This new paradigm based on the STORM experience sets the way towards the implementation of an overtly risk-oriented approach to the preservation of heritage sites, following the objectives that guided the STORM project through the development of new operative proposal - STORM 5 Cs - for different levels of intervention and responsibilities, namely: Heritage Conservation and management guidelines and procedures at site and government levels; Communication between climate researchers and heritage managers, including government authorities, in particular concerning the scientific body of knowledge built on climate change, aiming to improve adaptation strategies; Coping and adaptive capacities of heritage sites and organisations to meet their specific risks, and namely the actions that may enhance their resilience facing disasters; Cooperation between the different actors involved in the disaster risk management (DRM) of cultural heritage, which is demonstrably a cross-sectorial endeavour; Capacity building of heritage professionals, as well as of other pertinent stakeholders, via training and education at diverse levels in site-specific DRM measures and climate change adaptation. Regarding the safeguarding policies for cultural heritage to face natural hazards, STORM recommends the adoption of disaster reduction policies that lead to the creation of effective natural disaster reduction, i.e., the adoption of a new pathway that takes us from safeguard to effective protection of cultural heritage.
C1 [Bizarro, Alcides F.; Alexandre, Luis, V] Municipio Grandola, Rua Dr Jose Pereira Barradas 11, P-7570281 Grandola, Portugal.
RP Bizarro, AF (corresponding author), Municipio Grandola, Rua Dr Jose Pereira Barradas 11, P-7570281 Grandola, Portugal.
EM alcides.bizarro@cm-grandola.pt; luis.alexandre@cm-grandola.pt
CR [Anonymous], 2015, AUST J EMERG MANAG, V30, P9
   [Anonymous], 2015, HERIT SOC, V8, P144, DOI 10.1080/2159032X.2015.1126115
   [Anonymous], AM J MED SCI, DOI [DOI 10.1007/s11270-007-9372-6, DOI 10.1016/J.AMJMS.2021.03.001,00089-6]
   [Anonymous], 2016, EU climate policy explained
   Avrami E., 2000, VALUES HERITAGE CONS, P3
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Birkmann J., 2013, MEASURING VULNERABIL
   ECHO, 2019, DIS PREP FACTSH
   STORM Consortium, 2019, D2 2 SAF CULT HER RE
   STORM Consortium, 2018, D5 3 RISK MAN GUID P
   STORM Consortium, 2017, D1 3 COST EFF CONS R
   United Nations, 2005, HYOG DECL FRAM ACT 2
NR 12
TC 2
Z9 2
U1 0
U2 14
PU IOP PUBLISHING LTD
PI BRISTOL
PA DIRAC HOUSE, TEMPLE BACK, BRISTOL BS1 6BE, ENGLAND
SN 1757-8981
J9 IOP CONF SER-MAT SCI
PY 2020
VL 949
AR 012108
DI 10.1088/1757-899X/949/1/012108
PG 8
WC Archaeology; Architecture; Materials Science, Multidisciplinary;
   Physics, Applied; Imaging Science & Photographic Technology
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Archaeology; Architecture; Materials Science; Physics; Imaging Science &
   Photographic Technology
GA BR3LK
UT WOS:000647639100111
OA gold
DA 2025-01-10
ER

PT J
AU Nhem, S
   Lee, YJ
AF Nhem, Sareth
   Lee, Young Jin
TI Using Q methodology to investigate the views of local experts on the
   sustainability of community-based forestry in Oddar Meanchey province,
   Cambodia
SO FOREST POLICY AND ECONOMICS
LA English
DT Article
DE Community-based forestry; Criteria, Q-method; Factor loading; Cambodia
ID ENVIRONMENTAL PARADIGM SCALE; CLIMATE-CHANGE ADAPTATION; KAMPONG THOM
   PROVINCE; ECOSYSTEM SERVICES; EMPIRICAL-EVIDENCE; PROTECTED AREAS;
   PUBLIC-PARTICIPATION; RESOURCES ASSESSMENT; RURAL LIVELIHOODS; INCOME
   INEQUALITY
AB Deforestation has become an issue of public interest and sensitivity in Cambodia. Community-based forestry (CBF) and the accompanying local institutional community forestry (CF) arrangements are increasingly recognized as successful mechanisms to achieve sustainable forest management. However, in most community-managed forestry studies, there has still been no significant exploration of the viewpoints of local people to determine the monitoring and actions needed to enable CBF to achieve sustainable forest management. Therefore this study examines the perspectives of local experts across a range of issues and challenges facing CBF sustainability, using Q-methodology. This paper adapted and used four criteria for sustainable forest management to design the 43 Q-statements to guide examination of the subjectivity of local experts concerning CBF sustainability in Cambodia. The 52 respondents were purposively selected from the 13 Community Forestry sites to Q-sort the Q-statements. The findings revealed that most local experts felt that the environmental condition (criteria I), the loss of forest, is critical but one factor strongly disagreed. Considering socio-economic benefits and needs (criteria II), there were similarly polar views about whether the community desperately needs external finance now or whether they have the collective will to act and need to show that first. Only one of the factors supported further REDD+ projects reasonably strongly; others valued eco-tourism opportunities. None of the factors ranked the quality of community-based forest management practices (criteria III) strongly although there was mild agreement about a lack of CF management accountability. There were contrasting views on the legal, policy, and institutional framework and governance (criteria IV), with disagreement about the importance of local enforcement, and quality of local communication and consultation. All agreed, however, that the current position does not give them meaningful ownership and control over forest resources.
C1 [Nhem, Sareth] Natl Univ Management, Grad Sch, St 96 Christopher Howes, Khan Daun Penh, Phnom Penh, Cambodia.
   [Lee, Young Jin] Konju Natl Univ, Coll Ind Sci, Grad Sch Nat Sci, Dept Forest Resources, Yesan Eup, Yesan Gun, South Korea.
RP Lee, YJ (corresponding author), Konju Natl Univ, Coll Ind Sci, Grad Sch Nat Sci, Dept Forest Resources, Yesan Eup, Yesan Gun, South Korea.
EM leeyj@kongju.ac.kr
FU 'R&D Program for Forest Science Technology' by Korea Forest Service
   (Korea Forestry Promotion Institute) [2013069D101919AA03]; Asian Forest
   Cooperation Organization (AFoCO)
FX This study was carried out with the support of 'R&D Program for Forest
   Science Technology (Project No. 2013069D101919AA03)' provided by Korea
   Forest Service (Korea Forestry Promotion Institute). The authors would
   like to thank Asian Forest Cooperation Organization (AFoCO) for
   providing a full PhD scholarship (March 2016 - February 2019) to Dr.
   Nhem Sareth, our first author.
CR Addams Helen., 2000, SOCIAL DISCOURSE ENV
   Adhikari S, 2014, FOREST POLICY ECON, V44, P1, DOI 10.1016/j.forpol.2014.04.003
   Agarwal B, 2009, ECOL ECON, V68, P2296, DOI 10.1016/j.ecolecon.2009.02.017
   Agyei FK, 2017, FOREST POLICY ECON, V80, P34, DOI 10.1016/j.forpol.2017.03.003
   Albizua A, 2014, ENVIRON POLICY GOV, V24, P405, DOI 10.1002/eet.1658
   Alderson S, 2018, BMJ QUAL SAF, V27, P737, DOI 10.1136/bmjqs-2017-007380
   Alemagi D, 2010, FOREST POLICY ECON, V12, P554, DOI 10.1016/j.forpol.2010.07.008
   Alexander KS, 2018, AGR SYST, V160, P1, DOI 10.1016/j.agsy.2017.10.018
   Ali A, 2018, J RURAL STUD, V57, P44, DOI 10.1016/j.jrurstud.2017.10.001
   Amare D, 2017, ECOL ECON, V142, P177, DOI 10.1016/j.ecolecon.2017.06.002
   Angelsen A., 2003, CIFOR occasional paper, P1
   Angelsen A, 2014, WORLD DEV, V64, pS12, DOI 10.1016/j.worlddev.2014.03.006
   [Anonymous], 1987, REP WORLD COMM ENV D
   [Anonymous], 2014, NAT STRAT DEV PLAN 2
   [Anonymous], 2016, STAT WORLDS FOR FOR
   [Anonymous], 1997, The Kyoto Protocol
   [Anonymous], 2013, GENDER REDD ASSESSME
   [Anonymous], USING CRITERIA INDIC
   [Anonymous], CENS AGR CAMB 2013
   [Anonymous], 1992, United Nations Framework Convention on Climate Change
   [Anonymous], CAMB FOR OUTL STUD
   [Anonymous], 2016, PHNOM PENH POST
   [Anonymous], NAT FOR PROGR 2010 2
   [Anonymous], 2016, ANN REP 2016
   [Anonymous], COMM FOR STAT CAMB 2
   [Anonymous], 2014, Cambodia Country Poverty Analysis 2014
   Armatas CA, 2014, ECOL ECON, V107, P447, DOI 10.1016/j.ecolecon.2014.09.010
   Arnold J.E.M., 2001, Forests and people: 25 years of community forestry
   Arnold J. E. M., 1991, FAO COMMUNITY FOREST
   Babigumira R, 2014, WORLD DEV, V64, pS67, DOI 10.1016/j.worlddev.2014.03.002
   Rahut DB, 2015, FOREST POLICY ECON, V61, P20, DOI 10.1016/j.forpol.2015.06.006
   Balana BB, 2010, J ENVIRON MANAGE, V91, P1294, DOI 10.1016/j.jenvman.2010.02.005
   Baynes J, 2015, GLOBAL ENVIRON CHANG, V35, P226, DOI 10.1016/j.gloenvcha.2015.09.011
   Beauchamp E, 2018, ECOL SOC, V23, DOI 10.5751/ES-10049-230228
   Beauchamp E, 2018, LAND USE POLICY, V71, P431, DOI 10.1016/j.landusepol.2017.11.021
   Becker D.R., 2003, ENVIRON IMPACT ASSES, V23, P367, DOI DOI 10.1016/S0195-9255(02)00098-7
   Benitez-Capistros F, 2016, AMBIO, V45, P706, DOI 10.1007/s13280-016-0774-9
   Börner J, 2014, GLOBAL ENVIRON CHANG, V29, P294, DOI 10.1016/j.gloenvcha.2014.04.021
   BRADLEY MM, 1994, J BEHAV THER EXP PSY, V25, P49, DOI 10.1016/0005-7916(94)90063-9
   Bredin YK, 2015, ECOL ECON, V118, P198, DOI 10.1016/j.ecolecon.2015.07.005
   Brown S. R., 1980, Political subjectivity: Applications of Q methodology in political science
   Brown S.R., 1993, Operant subjectivity, V16, P91, DOI DOI 10.22488/OKSTATE.93.100504
   Byrne R, 2017, ENERG POLICY, V110, P40, DOI 10.1016/j.enpol.2017.08.007
   Caballero G, 2015, FOREST POLICY ECON, V50, P347, DOI 10.1016/j.forpol.2014.07.013
   Cambodia MoE, 2018, Cambodia Forest Cover
   Castaneda F., 2000, UNASYLVA, V51, P3
   Chaitieng T., 2013, THAILAND, V9, P436
   Chapman R, 2015, EXTR IND SOC, V2, P540, DOI 10.1016/j.exis.2015.04.008
   Cheng AS, 2011, FOREST POLICY ECON, V13, P89, DOI 10.1016/j.forpol.2010.09.005
   Chomba S, 2015, FOREST POLICY ECON, V58, P37, DOI 10.1016/j.forpol.2014.11.011
   Chuang TJ, 2017, FOREST POLICY ECON, V78, P173, DOI 10.1016/j.forpol.2017.01.020
   Clements T, 2010, ECOL ECON, V69, P1283, DOI 10.1016/j.ecolecon.2009.11.010
   Cuppen E, 2010, ECOL ECON, V69, P579, DOI 10.1016/j.ecolecon.2009.09.005
   Dash M., 2016, FOREST POLICY ECON, V73, DOI [10.1016/j.forpol.2016.09, DOI 10.1016/J.FORPOL.2016.09]
   Dennis K. E., 1986, ADV NURS SCI
   Denton F., 2002, Gender and Development, V10, P10, DOI 10.1080/13552070215903
   Dixon B. R., 2018, PERCEPTIONS STUDY AB
   Dressler WH, 2015, FOREST POLICY ECON, V58, P1, DOI 10.1016/j.forpol.2015.04.006
   Dunlap RE, 2008, J ENVIRON EDUC, V40, P3, DOI 10.3200/JOEE.40.1.3-18
   Dupuis J., 2013, ADAPTATION POLICY PA, V18, P4
   Ellingsen IT, 2010, INT J SOC RES METHOD, V13, P395, DOI 10.1080/13645570903368286
   Elliott V., 2011, BIODIVERSITY ASSESSM
   Fang C., 2018, EURASIA Journal of Mathematics, Science and Technology Education, V14, P2731, DOI [10.29333/ejmste/90555, DOI 10.29333/EJMSTE/90555]
   FAO, 2018, STAT WORLD FOR FOR P
   Fleming A, 2018, J RES NURS, V23, P141, DOI 10.1177/1744987118757837
   Gbedomon RC, 2016, FOREST POLICY ECON, V64, P46, DOI 10.1016/j.forpol.2016.01.001
   Gilmour D., 2016, FAO Forestry Paper
   Hawcroft LJ, 2010, J ENVIRON PSYCHOL, V30, P143, DOI 10.1016/j.jenvp.2009.10.003
   Hermelingmeier V, 2017, ECOL ECON, V136, P255, DOI 10.1016/j.ecolecon.2017.01.006
   Howard RJ, 2016, ENVIRON SCI POLICY, V56, P100, DOI 10.1016/j.envsci.2015.11.009
   Hugé J, 2016, J ENVIRON MANAGE, V183, P988, DOI 10.1016/j.jenvman.2016.09.046
   Jalilova G, 2012, FOREST POLICY ECON, V21, P32, DOI 10.1016/j.forpol.2012.01.010
   Jaung WG, 2016, ECOSYST SERV, V22, P51, DOI 10.1016/j.ecoser.2016.09.010
   Jiao X, 2015, LAND USE POLICY, V48, P317, DOI 10.1016/j.landusepol.2015.06.008
   Jumbe CBL, 2006, LAND ECON, V82, P562, DOI 10.3368/le.82.4.562
   Kalaba FK, 2016, FOREST POLICY ECON, V69, P40, DOI 10.1016/j.forpol.2016.04.004
   Kangas A, 2010, FOREST POLICY ECON, V12, P213, DOI 10.1016/j.forpol.2009.10.006
   Karimova M., 2014, Q METHODOLOGICAL STU
   Keenan RJ, 2015, FOREST ECOL MANAG, V352, P9, DOI 10.1016/j.foreco.2015.06.014
   Keeney S., 2011, The Delphi technique in nursing and health research
   Keerthiratne S, 2018, WORLD DEV, V105, P217, DOI 10.1016/j.worlddev.2018.01.001
   Kerr N, 2018, ENERGY RES SOC SCI, V42, P90, DOI 10.1016/j.erss.2018.02.018
   Khatri DB, 2018, FOREST POLICY ECON, V92, P1, DOI 10.1016/j.forpol.2018.03.005
   Khundi F, 2011, FOREST POLICY ECON, V13, P199, DOI 10.1016/j.forpol.2010.11.002
   Kim SB, 2015, FOR SCI TECHNOL, V11, P166, DOI 10.1080/21580103.2014.977358
   Kim S, 2006, FOREST POLICY ECON, V8, P625, DOI 10.1016/j.forpol.2004.12.001
   Kindermann G, 2013, LAND USE POLICY, V31, P472, DOI 10.1016/j.landusepol.2012.08.011
   Kline P., 2014, An easy guide to factor analysis, V2nd
   Köhl M, 2015, FOREST ECOL MANAG, V352, P21, DOI 10.1016/j.foreco.2015.05.036
   Koga K, 2013, J PHYSIOL ANTHROPOL, V32, DOI 10.1186/1880-6805-32-7
   Kozova M., 2016, NETWORK PARTICIPATOR, DOI [10.1016/j.forpol.2016.09.016, DOI 10.1016/J.FORPOL.2016.09.016]
   Krippendorff K., 2018, CONTENT ANAL INTRO I
   Laudari H. K., 2013, NEPALS PROPOOR LEASE, DOI [10.3126/init.v5i0.10258, DOI 10.3126/INIT.V5I0.10258]
   Le Billon P, 2000, DEV CHANGE, V31, P785, DOI 10.1111/1467-7660.00177
   Lee Eun-jin, 2017, International Review of Public Administration, V22, P380
   Liu ZM, 2018, ECOL ECON, V143, P199, DOI 10.1016/j.ecolecon.2017.07.023
   Loring P. A., 2015, FOR ECOL MANAG, V352, P47, DOI [10.1016/j, DOI 10.1016/J]
   Louah L, 2017, LAND USE POLICY, V67, P86, DOI 10.1016/j.landusepol.2017.05.001
   Lu M, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041051
   MacDicken K, 2015, FOREST ECOL MANAG, V352, P1, DOI 10.1016/j.foreco.2015.06.018
   MacDicken KG, 2015, FOREST ECOL MANAG, V352, P47, DOI 10.1016/j.foreco.2015.02.005
   Manly B.F.J., 1998, Multivariate Statistical Methods
   Maraseni Tek Narayan, 2015, International Journal of Environmental Studies, V72, P288, DOI 10.1080/00207233.2014.993569
   Markova-Nenova N, 2017, FOREST POLICY ECON, V80, P71, DOI 10.1016/j.forpol.2017.02.005
   Mckay AJ, 2017, ENVIRON IMPACT ASSES, V64, P16, DOI 10.1016/j.eiar.2017.01.002
   McKeown B.Thomas., 2013, Q METHODOLOGY, V2nd
   McKeown Bruce., 1988, Q METHODOLOGY, DOI [10.4135/9781412985512, DOI 10.4135/9781412985512]
   Moffat SO, 2001, FOREST POLICY ECON, V2, P307, DOI 10.1016/S1389-9341(01)00033-8
   Mollick AS, 2018, FOREST POLICY ECON, V95, P123, DOI 10.1016/j.forpol.2018.07.014
   MoP, 2016, CAMB SOC EC SURV 201
   Morales-Hidalgo D, 2015, FOREST ECOL MANAG, V352, P68, DOI 10.1016/j.foreco.2015.06.011
   Nathan I, 2017, GEOFORUM, V83, P26, DOI 10.1016/j.geoforum.2017.04.020
   Nhem S, 2018, FOR SCI TECHNOL, V14, P192, DOI 10.1080/21580103.2018.1520744
   Nhem S, 2018, J MT SCI-ENGL, V15, P2531, DOI 10.1007/s11629-018-5021-3
   Nhem S, 2018, J SUSTAIN FOREST, V37, P97, DOI 10.1080/10549811.2017.1369887
   Nhem S, 2017, FOREST POLICY ECON, V85, P10, DOI 10.1016/j.forpol.2017.08.011
   Niedzialkowski K, 2018, ECOL ECON, V145, P401, DOI 10.1016/j.ecolecon.2017.11.018
   Nijnik M, 2018, FOREST POLICY ECON, V92, P210, DOI 10.1016/j.forpol.2018.01.001
   Noe F.P., 1990, J ENVIRON EDUC, V21, P20, DOI DOI 10.1080/00958964.1990.9941934
   Nordhagen S, 2017, ECOL ECON, V137, P99, DOI 10.1016/j.ecolecon.2017.02.025
   O' Byrne B., 2018, PHNOM PENH POST, V86, P76
   Ormerod KJ, 2017, GEOFORUM, V86, P76, DOI 10.1016/j.geoforum.2017.09.004
   Orsi F, 2011, ECOL INDIC, V11, P337, DOI 10.1016/j.ecolind.2010.06.001
   Pandit R, 2018, FOREST POLICY ECON, V91, P107, DOI 10.1016/j.forpol.2018.02.002
   Parry LJ, 2019, BRIT POLIT, V14, P290, DOI 10.1057/s41293-018-0089-5
   Pätäri S, 2016, FOREST POLICY ECON, V66, P38, DOI 10.1016/j.forpol.2015.10.009
   Paudyal K, 2017, LAND USE POLICY, V63, P342, DOI 10.1016/j.landusepol.2017.01.046
   Pokharel RK, 2015, FOREST POLICY ECON, V58, P75, DOI 10.1016/j.forpol.2014.11.006
   Prabhu R., 1998, 23A RUR DEV FOR NETW
   Prabhu R., 1999, GUIDELINES DEV TEST
   Price L. R., 2017, Psychometric methods: Theory into practice
   Q' Byrne B., 2018, PHNOM PENH POST
   Rahut D. B., 2016, Forests, Trees and Livelihoods, V25, P187, DOI 10.1080/14728028.2016.1162754
   Rai SC, 2007, J MT SCI-ENGL, V4, P248, DOI 10.1007/s11629-007-0248-4
   Rakatama A, 2017, FOREST POLICY ECON, V75, P103, DOI 10.1016/j.forpol.2016.08.006
   Rastogi A, 2013, BIOL CONSERV, V161, P182, DOI 10.1016/j.biocon.2013.03.013
   Rastogi A, 2010, BIOL CONSERV, V143, P2956, DOI 10.1016/j.biocon.2010.04.039
   Ray L., 2011, Sustainability: Science, Practice & Policy, V7, P18
   Rega C, 2018, ENVIRON IMPACT ASSES, V73, P60, DOI 10.1016/j.eiar.2018.07.004
   Ritchie B., 2000, Criteria and Indicators of Sustainability in Community Managed Forest Landscapes:: An Introductory Guide
   Robbins P, 2000, PROF GEOGR, V52, P636, DOI 10.1111/0033-0124.00252
   Robbins P., 2005, ENCY SOCIAL MEASUREM, V3, P209, DOI [10.1016/B0-12-369398-5/00356-X, DOI 10.1016/B0-12-369398-5/00356-X]
   Roberts W., 2016, WORLD DEV PERSPECTIV, V1, P15, DOI [10.1016/j.wdp.2016.05.003, DOI 10.1016/J.WDP.2016.05.003]
   Rodriguez-pin S., 2012, INCORPORATING VALUES, P167, DOI [10.1007/s11842-011-9182-y, DOI 10.1007/S11842-011-9182-Y]
   Rodríguez-Piñeros S, 2015, AMBIO, V44, P99, DOI 10.1007/s13280-014-0544-5
   Rodriguez-Piñeros S, 2013, J ENVIRON MANAGE, V128, P52, DOI 10.1016/j.jenvman.2013.04.051
   Sandra RP, 2018, FOREST POLICY ECON, V88, P1, DOI 10.1016/j.forpol.2017.12.002
   Scheidel A, 2018, LAND USE POLICY, V77, P9, DOI 10.1016/j.landusepol.2018.04.057
   Schmolck P., 2015, PQMETHOD MANUAL, V39
   Schultz T, 2018, SCI COMMUN, V40, P199, DOI 10.1177/1075547018760902
   Seangly P., 2013, THE PHNOM PENH POST, P2
   Seangly P., 2018, PHNOM PENH POST, P1
   Sengkong B., 2016, PHNOM PENH POST, V18, P95
   Sexton D, 1998, TOP EARLY CHILD SPEC, V18, P95, DOI 10.1177/027112149801800205
   Skutsch M, 2017, FOREST POLICY ECON, V75, P58, DOI 10.1016/j.forpol.2016.11.014
   Sloan S, 2015, FOREST ECOL MANAG, V352, P134, DOI 10.1016/j.foreco.2015.06.013
   Smith J, 2018, OCEAN COAST MANAGE, V161, P147, DOI 10.1016/j.ocecoaman.2018.04.026
   Sochua M., 2012, NY TIMES, P1
   Sorola M., 2017, ASSESSING POTENTIAL
   Sotirov M, 2017, FOREST POLICY ECON, V85, P256, DOI 10.1016/j.forpol.2016.11.011
   Spiegel S, 2016, LAND USE POLICY, V54, P559, DOI 10.1016/j.landusepol.2016.03.015
   Spiegel SJ, 2014, J RURAL STUD, V36, P300, DOI 10.1016/j.jrurstud.2014.09.007
   Spruijt P, 2016, ENVIRON SCI POLICY, V59, P44, DOI 10.1016/j.envsci.2016.02.003
   Stenner P., 2008, The sage handbook of qualitative research in psychology, P215
   Stevenson H., 2015, CONT DISCOURSES ENV
   Stupak I, 2011, BIOMASS BIOENERG, V35, P3287, DOI 10.1016/j.biombioe.2010.11.032
   Sunderlin WD, 2006, FOREST POLICY ECON, V8, P386, DOI 10.1016/j.forpol.2005.08.008
   Swedeen P, 2006, ECOL ECON, V57, P190, DOI 10.1016/j.ecolecon.2005.04.003
   Terra Global Capital, 2012, RED EM DEGR DEF COMM
   The World bank, 2007, POV ENV UND LINK HOS
   Thomson L.P., 2018, Exploring student perceptions ofEd.D. program benefits: A Q method examination
   Phan THD, 2017, FOREST POLICY ECON, V80, P141, DOI 10.1016/j.forpol.2017.03.017
   Touch V, 2016, J ENVIRON MANAGE, V182, P238, DOI 10.1016/j.jenvman.2016.07.039
   Trautmann J, 2018, J NURS SCHOLARSHIP, V50, P392, DOI 10.1111/jnu.12395
   Travers H, 2015, LAND USE POLICY, V43, P186, DOI 10.1016/j.landusepol.2014.11.007
   UNCED, 1992, UN C ENV DEV UNCED R, V19
   Upton V, 2019, FOREST POLICY ECON, V99, P77, DOI 10.1016/j.forpol.2017.09.016
   Van Exel JDGG, 2005, Q methodology: A sneak preview
   Watts S., 2012, Doing Q methodological research
   Watts S., 2012, Doing Q methodological research: Theory, method and interpretation, DOI DOI 10.4135/9781446251911
   Webler T., 2006, 4 PERSPECTIVES PUBLI, V34
   Webler T., 2009, USING Q METHOD REVEA, P1
   Wijewardana D, 2008, ECOL INDIC, V8, P115, DOI 10.1016/j.ecolind.2006.11.003
   Worku A, 2014, FOREST POLICY ECON, V41, P51, DOI 10.1016/j.forpol.2014.01.001
   Wunder S, 2014, WORLD DEV, V64, pS1, DOI 10.1016/j.worlddev.2014.03.007
   Ying Z, 2011, FOREST POLICY ECON, V13, P513, DOI 10.1016/j.forpol.2011.06.005
   Zabala A., 2015, MOTIVATIONS INCENTIV, DOI [10.17863/CAM.16432, DOI 10.17863/CAM.16432]
   Zabala A, 2018, CONSERV BIOL, V32, P1185, DOI 10.1111/cobi.13123
   Zabala A, 2017, ECOL ECON, V135, P234, DOI 10.1016/j.ecolecon.2017.01.011
   Zivojinovic I, 2015, URBAN FOR URBAN GREE, V14, P1079, DOI 10.1016/j.ufug.2015.10.007
   Zwick W. R., 1984, COMPARISION 5 RULES
NR 191
TC 10
Z9 11
U1 2
U2 39
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1389-9341
EI 1872-7050
J9 FOREST POLICY ECON
JI Forest Policy Econ.
PD SEP
PY 2019
VL 106
AR 101961
DI 10.1016/j.forpol.2019.101961
PG 20
WC Economics; Environmental Studies; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Business & Economics; Environmental Sciences & Ecology; Forestry
GA IP9BZ
UT WOS:000480344100010
DA 2025-01-10
ER

PT J
AU Yamegueu, D
   Alokore, Y
   Corso, G
AF Yamegueu, Daniel
   Alokore, Yunus
   Corso, Giulia
TI Potential of microfinanced solar water pumping systems for irrigation in
   rural areas of Burkina Faso
SO ENERGY SUSTAINABILITY AND SOCIETY
LA English
DT Article
DE Climate change adaptation; Diesel water pump; Solar water pump;
   Productive use of energy; Microfinance
ID PERFORMANCE; IMPACT; MODEL
AB BackgroundThe population in Burkina Faso is rapidly adopting irrigation to adapt to negative impacts of climate change like prolonged drought, rainfall variability and desertification. The solar water pumping systems (SWPS) could be an attractive option in view of climate change impacts, increasing diesel costs and grid electricity scarcity that the country suffers. However, due to high initial cost SWPS, population mainly uses diesel water pumps (DWPs). The main objective of this study is to assess the potential of microfinanced SWPS for irrigation in rural areas of Burkina Faso.MethodsBased on ground data collection and profitability analysis, this study investigates the best SWPS market segments for irrigation in rural areas of Burkina Faso. The case study of the village of Korsimoro was considered. Especially, the study is focused on the onion crop as it is the most cultivated crop in the area of study.ResultsIt was found that there are three main SWPS market segments in the area of study: market segment 1 which is that of farmers individually owning and using a DWP with rated power between 1.5 and 3kW, market segment 2 which is composed of farmers individually owning a DWP of rated power ranging from 4 to 7.5kW and market segment 3 which is that of farmers paying for pumping services offered by a pump owner in market segment 2. The study revealed that replacing polyvinyl chloride (PVC) water storage tank by DWPs to be used on cloudy days is profitable for all the market segments. The study showed also that at 9.5% interest charged on agricultural equipment, only SWPS for the market segments 2 and 3 can be fully financed through microloan without risk of long payback period.ConclusionsThe results imply that more attention should be given to SWPS in the context of rural areas of Burkina Faso to enhance the productive use of energy and also mitigate the impacts of climate change on the environment. In addition, the study provides detailed information to farmers about how they can make more profitable their activities.
C1 [Yamegueu, Daniel] Int Inst Water & Environm Engn 2iE, Dept Elect Ind & Energy Engn, Renewable Energies & Energy Efficiency Lab, Rue Sci 01,BP 594, Ouagadougou 01, Burkina Faso.
   [Alokore, Yunus] Viva Energy Int Ltd, Plot 31 Pakwach Rd,POB 460, Arua, Uganda.
   [Corso, Giulia] Microenergy Int Gmbh, Potsdamer Str 143, D-10783 Berlin, Germany.
RP Yamegueu, D (corresponding author), Int Inst Water & Environm Engn 2iE, Dept Elect Ind & Energy Engn, Renewable Energies & Energy Efficiency Lab, Rue Sci 01,BP 594, Ouagadougou 01, Burkina Faso.
EM daniel.yamegueu@2ie-edu.org
OI YAMEGUEU, Daniel/0000-0002-1789-8377
FU German Ministry of Education and Research (BMBF)
FX This work was supported by the German Ministry of Education and Research
   (BMBF) in the framework of the Mikroklima West Africa Project.
CR Allen R.G., 1998, FAO Irrigation and Drainage Paper
   [Anonymous], Spain Moves to Raise'
   [Anonymous], 2014, RESP FIN MARK OV BUR
   [Anonymous], 2017, UN SUSTAINABLE DEV G
   Bhattacharyya SC, 2014, GREEN ENERGY TECHNOL, P1, DOI 10.1007/978-3-319-04816-1
   Bouraima AK, 2015, INT J AGR BIOL ENG, V8, P58, DOI 10.3965/j.ijabe.20150802.1290
   Bruderle A., 2011, Productive Use of Energy-PRODUSE A Manual for Electrification Practitioners
   Chandel SS, 2017, RENEW SUST ENERG REV, V76, P163, DOI 10.1016/j.rser.2017.03.019
   Charan Jaykaran, 2013, Indian J Psychol Med, V35, P121, DOI 10.4103/0253-7176.116232
   Chen CS, 2012, ENRGY PROCED, V14, P411, DOI 10.1016/j.egypro.2011.12.951
   CLIMATEMPS, 2009, CLIM TEMP
   de Fraiture C, 2014, AGR WATER MANAGE, V131, P212, DOI 10.1016/j.agwat.2013.07.001
   Evans AEV, 2012, 149 IWMI, DOI [10.5337/2012.211, DOI 10.5337/2012.211]
   Food and Agriculture Organization, 2014, FAO BURK FAS AR INL
   Gael Ndanga, 2011, MEMOIRE DE MASTER
   Geslain P, 2014, ETUDE IDENTIFICATION
   Hammill A, 2008, IDS BULL-I DEV STUD, V39, P113, DOI 10.1111/j.1759-5436.2008.tb00484.x
   Helms B., 2006, Access for All. Consultative Group to Assist the Poor
   Hosenuzzaman M, 2015, RENEW SUST ENERG REV, V41, P284, DOI 10.1016/j.rser.2014.08.046
   Jenkins T, 2013, 670 NEW MEX STAT U
   KREFT S, 2015, GLOBAL CLIMATIC RISK
   Lin CH, 2011, IEEE T IND APPL, V47, P1884, DOI 10.1109/TIA.2011.2154292
   Mvondo Ayissi J, 2010, DEV IRRIGATION TALEM
   Nisha P, 2013, I J C SCI, V2, P272
   Program WF, 2016, FIN INCL P4P EXP SYS
   Sally H., 2011, Water Alternatives, V4, P365
   Tiwari AK, 2018, RENEW ENERG, V118, P919, DOI 10.1016/j.renene.2017.11.004
   Tiwari AK, 2016, RENEW ENERG, V97, P737, DOI 10.1016/j.renene.2016.06.021
   Treephak K, 2015, JJAP, V54, P1
   Wang YM, 2009, AFR J AGR RES, V4, P1493
   World Bank, 2015, END EXTR POV SHAR PR
   World Bank, 2016, WORLD BANK BURK FAS
NR 32
TC 10
Z9 10
U1 2
U2 15
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 2192-0567
J9 ENERGY SUSTAIN SOC
JI Energy Sustain. Soc.
PD FEB 28
PY 2019
VL 9
AR 8
DI 10.1186/s13705-019-0190-7
PG 13
WC Green & Sustainable Science & Technology; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Energy & Fuels
GA HN5MX
UT WOS:000460230000001
OA gold
DA 2025-01-10
ER

PT J
AU Wells, S
   Ray, GC
   Gjerde, KM
   White, AT
   Muthiga, N
   Creel, JEB
   Causey, BD
   Mccormick-Ray, J
   Salm, R
   Gubbay, S
   Kelleher, G
   Reti, J
AF Wells, Sue
   Ray, G. Carleton
   Gjerde, Kristina M.
   White, Alan T.
   Muthiga, Nyawira
   Bezaury Creel, Juan E.
   Causey, Billy D.
   Mccormick-Ray, Jerry
   Salm, Rod
   Gubbay, Sue
   Kelleher, Graeme
   Reti, Joe
TI Building the future of MPAs - lessons from history
SO AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS
LA English
DT Article; Proceedings Paper
CT 6th IUCN World Parks Congress
CY NOV, 2014
CL Sydney, AUSTRALIA
SP IUCN
DE ocean; coastal; marine protected area; no-take zones; biodiversity
ID MARINE PROTECTED AREAS; FISHERIES MANAGEMENT; COASTAL ZONE; CORAL-REEFS;
   RESERVES; CONSERVATION; TARGETS; GOVERNANCE; CHALLENGES; ISSUES
AB 1. Marine protected areas (MPAs) have a long history, originating in traditional and cultural initiatives often focused on reserving resources for food security. A handful of 'parks' were established between the 1870s and 1940s and, following World War II, increased awareness of threats to the ocean led to global programmes that started in the 1970-1980s.
   2. Initially IUCN became the leader, piloting a science-based 'critical marine habitats' approach, by which MPAs were aimed at conserving the healthiest and most diverse ecosystems, endangered and charismatic species, and high-profile habitats.
   3. During the 1970s, with the support of WWF, UNESCO, UNEP, and growing national efforts, the MPA concept evolved to include biosphere reserves, marine reserves and sanctuaries, large ocean reserves, and other designations that aimed to reconcile long-term protection with human use.
   4. From the 1980s, MPAs greatly expanded in number and scope. By the turn of the millennium, MPAs were proliferating, and principles and methodologies were available to guide their establishment and management in a harmonized manner. Zoning for different uses was widespread, but questions were being raised about the efficacy of biodiversity conservation in areas where extractive uses were permitted.
   5. MPA implementation accelerated once targets were introduced by the Convention on Biological Diversity. Campaigns and fundraising by non-governmental organizations and further national efforts resulted in a rapid increase although, by 2015, less than 4% of ocean surface was protected.
   6. Current challenges include: (1) understanding the role of MPAs in maintaining ecosystem services, fishery management, climate change adaptation and mitigation, and other emergent problems; (2) more rigorous network design; (3) effective governance and demonstration of 'success'; and (4) integrating MPAs with marine spatial planning. 7. While MPAs have provided one of the most viable and politically acceptable approaches to marine conservation for 50 years, their role in developing a fully effective marine ecosystems management regime has yet to be fully explored and understood. Copyright (C) 2016 John Wiley & Sons, Ltd.
C1 [Wells, Sue] IUCN WCPA Marine, Cambridge, England.
   [Ray, G. Carleton] Univ Virginia, Dept Environm Sci, Clark Hall, Charlottesville, VA 22903 USA.
   [Gjerde, Kristina M.] IUCN Global Marine & Polar Programme, Cambridge, MA USA.
   [Gjerde, Kristina M.] WCPA High Seas MPA Specialist Grp, Cambridge, MA USA.
   [White, Alan T.] Nature Conservancy, Asia Pacific Program, Honolulu, HI USA.
   [Muthiga, Nyawira] Wildlife Conservat Soc, Marine Program, Mombasa, Kenya.
   [Bezaury Creel, Juan E.] Nature Conservancy, Mexico & Cent Amer Program, Mexico City, DF, Mexico.
   [Causey, Billy D.] NOAAs Off Natl Marine Sanctuaries, Southeast Atlantic, Gulf Mexico & Caribbean Reg, Mexico City, DF, Mexico.
   [Mccormick-Ray, Jerry] Univ Virginia, Charlottesville, VA USA.
   [Salm, Rod] Nature Conservancy, Pacific Div Marine Program, Honolulu, HI USA.
   [Kelleher, Graeme] WCPA Marine & IUCN Ocean Elder, Sydney, NSW, Australia.
   [Reti, Joe] Western Samoa, Sydney, NSW, Australia.
C3 University of Virginia; Nature Conservancy; University of Virginia;
   Nature Conservancy
RP Wells, S (corresponding author), IUCN WCPA Marine, Cambridge, England.
EM suewells1212@gmail.com
CR Abdulla A.A., 2013, Marine Natural Heritage and the World Heritage List: Interpretation of World Heritage Criteria in Marine Systems, Analysis of Biogeographic Representation of Sites, and a Roadmap for Addressing Gaps
   Agardy T, 2003, AQUAT CONSERV, V13, P353, DOI 10.1002/aqc.583
   Agardy T, 2011, MAR POLICY, V35, P226, DOI 10.1016/j.marpol.2010.10.006
   [Anonymous], IUCN PUBL
   [Anonymous], 2012, EST AR MAR COST PROT
   [Anonymous], 1953, The Silent World: A Story of Undersea Discovery and Adventure
   [Anonymous], MAR CONS ZON PROJ EC
   [Anonymous], IUCN PUBLICATIONS
   [Anonymous], 1 WORLD C NAT PARKS
   [Anonymous], BIOMASS YIELDS GEOGR
   [Anonymous], 2015, WORLD HERITAGE MARIN
   [Anonymous], 2011, MARINE CONSERVATION
   [Anonymous], HISTORY
   [Anonymous], IUCN BEST PRACTICE P
   [Anonymous], CONSERVATION LETT
   [Anonymous], 8 UNESCOS IUCN
   [Anonymous], EST INT WHAL COMM SA
   [Anonymous], PROTECTED AREAS SYST
   [Anonymous], FRAM PAN ARCT NETW M
   [Anonymous], 2013, PLAN BLEU PAPERS
   [Anonymous], COAST ZON 89 P 6 S C
   [Anonymous], 1 NAT CONS
   [Anonymous], UNESCO IUCN SAN FRAN
   [Anonymous], 1993, Global marine biological diversity: A strategy for building conservation into decision making
   [Anonymous], GLOBAL OCEAN PROTECT
   [Anonymous], PROTECTING EARTHS LA
   [Anonymous], NAT 2000 MAR ENV
   [Anonymous], ENV EVIDENCE
   [Anonymous], TECHNICAL REPORT
   [Anonymous], FAO TECHN GUID RESP
   [Anonymous], 2008, NAT REG NETW MAR PRO
   [Anonymous], SPEC S MAR PARKS 11
   [Anonymous], 2 WORLD C NAT PARKS
   [Anonymous], SSRF780 NOAA NMFS
   [Anonymous], ENCY BIODIVERSITY
   [Anonymous], AQUATIC CONSERVATION
   [Anonymous], WORLD NATL PARKS PRO
   [Anonymous], ENV MANAGEMENT DEEP
   [Anonymous], UNESCO IUCN WORKSH A
   [Anonymous], USITC PUBL
   [Anonymous], CONS MEAS 29 14 BOTT
   [Anonymous], ARE MARINE PROTECTED
   [Anonymous], EARTH NEGOTIATIONS B
   [Anonymous], 2013, 18 EUR MAR BOARD
   [Anonymous], 2011, Reefs at Risk Revisited
   [Anonymous], P 2 WORLD C NAT PARK
   [Anonymous], ROYAL NAT PARK HEALT
   [Anonymous], SCI MAR RES
   [Anonymous], 1999, GUIDELINES MARINE PR
   [Anonymous], DELT BRET NAT WILDL
   [Anonymous], 1 WORLD C NAT PARKS
   [Anonymous], MARINE COASTAL PROTE
   [Anonymous], 2007, Guidelines for the establishment of the Natura 2000 network in the marine environment . Application of the Habitats and Birds Directives
   Aswani S, 2012, MAR POLICY, V36, P1, DOI 10.1016/j.marpol.2011.02.014
   Ballantine B, 2014, BIOL CONSERV, V176, P297, DOI 10.1016/j.biocon.2014.01.014
   Balmford A, 2004, P NATL ACAD SCI USA, V101, P9694, DOI 10.1073/pnas.0403239101
   BATISSE M, 1990, ENVIRON CONSERV, V17, P111, DOI 10.1017/S0376892900031878
   Bennett NJ, 2014, MAR POLICY, V50, P96, DOI 10.1016/j.marpol.2014.05.005
   Bjorklund M.I., 1974, Environmental Conserv, V1, P205
   Boonzaier L, 2016, ORYX, V50, P27, DOI 10.1017/S0030605315000848
   Botsford LW, 2014, ADV MAR BIOL, V69, P205, DOI 10.1016/B978-0-12-800214-8.00006-2
   Brander L., 2015, The Benefits to People of Expanding Marine Protected Areas
   Carson R., 1951, The Sea Around Us
   Caveen A., 2015, The Controversy over Marine Protected Areas Science Meets Policy
   Caveen AJ, 2012, ENVIRON CONSERV, V39, P199, DOI 10.1017/S0376892912000033
   *CCAMLR, 2009, CONS MEAS 91 03 PROT
   Cheung WWL, 2009, FISH FISH, V10, P235, DOI 10.1111/j.1467-2979.2008.00315.x
   Cinner JE, 2012, GLOBAL ENVIRON CHANG, V22, P651, DOI 10.1016/j.gloenvcha.2012.03.002
   Claudet J., 2011, Marine protected areas: a multidisciplinary approach
   Clifton J, 2003, MAR POLICY, V27, P389, DOI 10.1016/S0308-597X(03)00026-5
   Common Wadden Sea Secretariat, 2010, 11 TRIL GOV C PROT W
   Costello MJ, 2015, TRENDS ECOL EVOL, V30, P507, DOI 10.1016/j.tree.2015.06.011
   da Silva IM, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0111774
   Day J.C., 2012, Guidelines for Applying the IUCN Protected Area Management Categories to MPAs
   De Santo EM, 2013, J ENVIRON MANAGE, V124, P137, DOI 10.1016/j.jenvman.2013.01.033
   Devillers R, 2015, AQUAT CONSERV, V25, P480, DOI 10.1002/aqc.2445
   Dunn DC, 2014, MAR POLICY, V49, P137, DOI 10.1016/j.marpol.2013.12.002
   Dygico M, 2013, MAR POLICY, V41, P87, DOI 10.1016/j.marpol.2012.12.031
   Edgar GJ, 2014, NATURE, V506, P216, DOI 10.1038/nature13022
   Elbers J, 2011, LAS AREAS PROTEGIDAS
   Fox HE, 2014, COAST MANAGE, V42, P207, DOI 10.1080/08920753.2014.904178
   Gibson J, 1998, OCEAN COAST MANAGE, V39, P229, DOI 10.1016/S0964-5691(98)00007-6
   Goessens A, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0105069
   Govan H., 2009, SPC TRADITIONAL MARI
   Govan H., 2008, LOCALLY MANAGED MARI
   Green A., 2013, DESIGNING MARINE PRO
   Green AL, 2015, BIOL REV, V90, P1215, DOI 10.1111/brv.12155
   Guarderas AP, 2008, CONSERV BIOL, V22, P1630, DOI 10.1111/j.1523-1739.2008.01023.x
   Gubbay S., 1995, MARINE PROTECTED ARE
   Gubbay S., 2005, A WWF-UK Discussion Document
   HAYDEN BP, 1984, ENVIRON CONSERV, V11, P199, DOI 10.1017/S0376892900014211
   Hilborn R, 2004, OCEAN COAST MANAGE, V47, P197, DOI 10.1016/j.ocecoaman.2004.04.001
   Hockings M., 2006, EVALUATING EFFECTIVE, V2nd
   Hoyt Erich., 2005, MARINE PROTECTED ARE
   Hughes TP, 2015, NAT CLIM CHANGE, V5, P508, DOI 10.1038/nclimate2604
   IUCN-WCPA, 2008, EST RES MAR PROT AR
   JOHANNES RE, 1978, ANNU REV ECOL SYST, V9, P349, DOI 10.1146/annurev.es.09.110178.002025
   Jones P.J. S., 2014, GOVERNING MARINE PRO
   Jones PJS, 2012, ENVIRON CONSERV, V39, P248, DOI 10.1017/S0376892912000136
   Jones PJS, 2001, REV FISH BIOL FISHER, V11, P197, DOI 10.1023/A:1020327007975
   Judd AD, 2015, ENVIRON SCI POLICY, V54, P254, DOI 10.1016/j.envsci.2015.07.008
   Kelleher G., 1995, GLOBAL REPRESENTATIV, V1
   KELLEHER GG, 1982, AMBIO, V11, P262
   Kelleher Graeme., 1992, Guidelines for establishing marine protected areas
   KENCHINGTON RA, 1990, ENVIRON CONSERV, V17, P39, DOI 10.1017/S0376892900017276
   Lauck T, 1998, ECOL APPL, V8, pS72, DOI 10.1890/1051-0761(1998)8[S72:ITPPIF]2.0.CO;2
   Lester SE, 2009, MAR ECOL PROG SER, V384, P33, DOI 10.3354/meps08029
   Lubchenco J, 2015, SCIENCE, V350, P382, DOI 10.1126/science.aad5443
   Mace GM, 2014, SCIENCE, V345, P1558, DOI 10.1126/science.1254704
   Maina J, 2008, ECOL MODEL, V212, P180, DOI 10.1016/j.ecolmodel.2007.10.033
   Maypa AP, 2012, COAST MANAGE, V40, P510, DOI 10.1080/08920753.2012.709465
   McClanahan TR, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0093385
   Mcleod E, 2013, FRONT ECOL ENVIRON, V11, P20, DOI 10.1890/110240
   McNeely JeffreyA., 1984, NATL PARKS CONSERVAT
   Muthiga NA, 2009, OCEAN COAST MANAGE, V52, P417, DOI 10.1016/j.ocecoaman.2009.06.001
   O'Leary BC, 2012, MAR POLICY, V36, P598, DOI 10.1016/j.marpol.2011.11.003
   Pala C, 2013, SCIENCE, V339, P640, DOI 10.1126/science.339.6120.640
   Philpots J.R., 1890, OYSTERS ALL THEM BEI, Vsecond, DOI [10.5962/bhl.title.1566, DOI 10.5962/BHL.TITLE.1566]
   Pomeroy R., 2004, How is your MPA doing? A guidebook of natural and social indicators for evaluating Marine Protected Area management effectiveness
   Possingham H, 1998, QUANTITATIVE METHODS FOR CONSERVATION BIOLOGY, P291
   Rakotoson LR, 2006, OCEAN COAST MANAGE, V49, P855, DOI 10.1016/j.ocecoaman.2006.08.003
   Ray C., 1956, UNDERWATER GUIDE MAR
   Ray G.C., 2014, Marine conservation: Science, policy, and management
   Ray G.C., 1976, International Conference on Marine Parks and Reserves, Tokyo, Japan, 12-14 May 1975, P15
   Ray GC, 2016, ECOL APPL, V26, P24, DOI 10.1890/15-0430
   Ray GC, 2015, AQUAT CONSERV, V25, P1, DOI 10.1002/aqc.2555
   Ray GC, 1999, AQUAT CONSERV, V9, P607
   Rice J, 2012, OCEAN COAST MANAGE, V69, P217, DOI 10.1016/j.ocecoaman.2012.08.001
   Roberts Callum., 2007, UNNATURAL HIST SEA
   Roberts CallumM., 2000, FULLY PROTECTED MARI
   Roberts CM, 1997, TRENDS ECOL EVOL, V12, P35, DOI 10.1016/S0169-5347(96)20109-0
   Rocliffe S, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103000
   Russ GR, 1999, CORAL REEFS, V18, P307, DOI 10.1007/s003380050203
   Salm R.V., 2000, MARINE COASTAL PROTE
   Shamberger KEF, 2014, GEOPHYS RES LETT, V41, P499, DOI 10.1002/2013GL058489
   Sobel J., 2004, Marine Reserves: a guide to science, design and use
   Spalding MD, 2007, BIOSCIENCE, V57, P573, DOI 10.1641/B570707
   Spalding MD, 2013, OCEAN YEARB, V27, P213, DOI 10.1163/22116001-90000160
   Stolton S., 2008, Edited by Nigel Dudley Including IUCN WCPA Best Practice Guidance on Recognising Protected Areas and Assigning Management Categories and Governance Types Guidelines for Applying Protected Area Management Categories
   Thomas HL, 2014, AQUAT CONSERV, V24, P8, DOI 10.1002/aqc.2511
   UNESCO, 2009, IOC TECHNICAL SERIES, V84
   van Woesik R, 2015, ROY SOC OPEN SCI, V2, DOI 10.1098/rsos.150181
   Watson JEM, 2016, CONSERV BIOL, V30, P243, DOI 10.1111/cobi.12645
   White A.T., 1987, Environ. Conserv, V14, P355
   White AT, 2014, COAST MANAGE, V42, P87, DOI 10.1080/08920753.2014.878177
   White AT, 2002, COAST MANAGE, V30, P1, DOI 10.1080/08920750252692599
   Wilhelm TA, 2014, AQUAT CONSERV, V24, P24, DOI 10.1002/aqc.2499
   Wood LJ, 2008, ORYX, V42, P340, DOI 10.1017/S003060530800046X
NR 148
TC 32
Z9 35
U1 2
U2 98
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1052-7613
EI 1099-0755
J9 AQUAT CONSERV
JI Aquat. Conserv.-Mar. Freshw. Ecosyst.
PD SEP
PY 2016
VL 26
SU 2
BP 101
EP 125
DI 10.1002/aqc.2680
PG 25
WC Environmental Sciences; Marine & Freshwater Biology; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology; Water
   Resources
GA DW5FL
UT WOS:000383668500009
OA Bronze
DA 2025-01-10
ER

PT J
AU Reidsma, P
   Bakker, MM
   Kanellopoulos, A
   Alam, SJ
   Paas, W
   Kros, J
   de Vries, W
AF Reidsma, Pytrik
   Bakker, Martha M.
   Kanellopoulos, Argyris
   Alam, Shah J.
   Paas, Wim
   Kros, Johannes
   de Vries, Wim
TI Sustainable agricultural development in a rural area in the Netherlands?
   Assessing impacts of climate and socio-economic change at farm and
   landscape level
SO AGRICULTURAL SYSTEMS
LA English
DT Article
DE Integrated assessment; Global change; Sustainability; Agriculture; Farm
   structural change; Spatially explicit; Climate smart agriculture
ID AFFECTING LAND-USE; INTEGRATED ASSESSMENT; MULTIOBJECTIVE OPTIMIZATION;
   TRADE-OFFS; SYSTEMS; UNCERTAINTIES; POLICIES; FUTURE; ADAPTATION;
   SCENARIOS
AB Changes in climate, technology, policy and prices affect agricultural and rural development. To evaluate whether this development is sustainable, impacts of these multiple drivers need to be assessed for multiple indicators. In a case study area in the Netherlands, a bio-economic farm model, an agent-based land-use change model, and a regional emission model have been used to simulate rural development under two plausible global change scenarios at both farm and landscape level. Results show that in this area, climate change will have mainly negative economic impacts (dairy gross margin, arable gross margin, economic efficiency, milk production) in the warmer and drier W+ scenario, while impacts are slightly positive in the G scenario with moderate climate change. Dairy farmers are worse off than arable farmers in both scenarios. Conversely, when the W+ scenario is embedded in the socio-economic Global Economy (GE) scenario, changes in technology, prices, and policy are projected to have a positive economic impact, more than offsetting the negative climate impacts. Important is, however, that environmental impacts (global warming, terrestrial and aquatic eutrophication) are largely negative and social impacts (farm size, number of farms, nature area, odour) are mixed. In the G scenario combined with the socio-economic Regional Communities (RC) scenario the average dairy gross margin in particular is negatively affected. Social impacts are similarly mixed as in the GE scenario, while environmental impacts are less severe. Our results suggest that integrated assessments at farm and landscape level can be used to guide decision-makers in spatial planning policies and climate change adaptation. As there will always be trade-offs between economic, social, and environmental impacts stakeholders need to interact and decide upon most important directions for policies. This implies a choice between production and income on the one hand and social and environmental services on the other hand. (C) 2015 Elsevier Ltd. All rights reserved.
C1 [Reidsma, Pytrik; Kanellopoulos, Argyris; Paas, Wim] Wageningen Univ, Plant Prod Syst Grp, NL-6700 AK Wageningen, Netherlands.
   [Bakker, Martha M.] Wageningen Univ, Land Use Planning Grp, NL-6700 AA Wageningen, Netherlands.
   [Kanellopoulos, Argyris] Wageningen Univ, Operat Res & Logist Grp, NL-6706 KN Wageningen, Netherlands.
   [Alam, Shah J.] Habib Univ, Sch Sci & Engn, Karachi, Pakistan.
   [Kros, Johannes; de Vries, Wim] Alterra Wageningen UR, NL-6700AA Wageningen, Netherlands.
   [de Vries, Wim] Wageningen Univ, Environm Syst Anal Grp, NL-6700 AA Wageningen, Netherlands.
C3 Wageningen University & Research; Wageningen University & Research;
   Wageningen University & Research; Wageningen University & Research;
   Wageningen University & Research
RP Reidsma, P (corresponding author), Wageningen Univ, Plant Prod Syst Grp, Dept Plant Sci, POB 430, NL-6700 AK Wageningen, Netherlands.
EM pytrik.reidsma@wur.nl
RI Kanellopoulos, Antonis/I-5437-2015; Paas, Wim/W-8046-2019
OI Reidsma, Pytrik/0000-0003-2294-809X; de Vries, Wim/0000-0001-9974-0612;
   Paas, Wim/0000-0001-9025-1652
FU research programme Sustainable Spatial Development of Ecosystems,
   Landscapes, Seas and Regions - Dutch Ministry of Economic Affairs
   [KB-14-004-025]
FX This research was carried out within the project Climate Adaptation for
   Rural Areas (CARE), part of the Dutch research programme Knowledge for
   Climate. Co-funding came from the research programme Sustainable Spatial
   Development of Ecosystems, Landscapes, Seas and Regions funded by the
   Dutch Ministry of Economic Affairs (KB-14-004-025). We thank Jan-Cees
   Voogd for support in the simulations and making figures.
CR Asseng S, 2013, NAT CLIM CHANGE, V3, P827, DOI [10.1038/nclimate1916, 10.1038/NCLIMATE1916]
   Bakker M, 2015, LANDSCAPE ECOL, V30, P791, DOI 10.1007/s10980-014-0145-5
   Bakker MM, 2015, LANDSCAPE ECOL, V30, P273, DOI 10.1007/s10980-014-0116-x
   Barthel R, 2012, WATER RESOUR MANAG, V26, P1929, DOI 10.1007/s11269-012-0001-9
   Bezlepkina I, 2011, AGR SYST, V104, P105, DOI 10.1016/j.agsy.2010.11.002
   Binder CR, 2010, ENVIRON IMPACT ASSES, V30, P71, DOI 10.1016/j.eiar.2009.06.002
   Briner S, 2012, AGR ECOSYST ENVIRON, V149, P50, DOI 10.1016/j.agee.2011.12.011
   de Vries W, 2003, NUTR CYCL AGROECOSYS, V66, P71, DOI 10.1023/A:1023354109910
   Déqué M, 2007, CLIMATIC CHANGE, V81, P53, DOI 10.1007/s10584-006-9228-x
   Diogo V., 2014, ANAL CLIMATE CHANGE
   Dolman MA, 2014, J CLEAN PROD, V73, P245, DOI 10.1016/j.jclepro.2014.02.043
   Ewert F, 2005, AGR ECOSYST ENVIRON, V107, P101, DOI 10.1016/j.agee.2004.12.003
   FARRELL MJ, 1957, J R STAT SOC SER A-G, V120, P253, DOI 10.2307/2343100
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Food and Agriculture Organization (FAO), 2014, INT YEAR FAM FARM
   Fraser EDG, 2005, FUTURES, V37, P465, DOI 10.1016/j.futures.2004.10.011
   Groot JCJ, 2012, AGR SYST, V110, P63, DOI 10.1016/j.agsy.2012.03.012
   Hazell P, 2010, WORLD DEV, V38, P1349, DOI 10.1016/j.worlddev.2009.06.012
   Hellmann F, 2011, BIOMASS BIOENERG, V35, P2411, DOI 10.1016/j.biombioe.2008.09.003
   Helming K, 2011, ECOL SOC, V16
   Helming K, 2011, ECOL SOC, V16
   Holzkämper A, 2015, ENVIRON MODELL SOFTW, V66, P27, DOI 10.1016/j.envsoft.2014.12.012
   Janssen S, 2009, ENVIRON SCI POLICY, V12, P573, DOI 10.1016/j.envsci.2009.01.007
   Kanellopoulos A, 2014, EUR J AGRON, V52, P69, DOI 10.1016/j.eja.2013.10.003
   Kirchner M, 2015, ECOL ECON, V109, P161, DOI 10.1016/j.ecolecon.2014.11.005
   Klapwijk CJ, 2014, CURR OPIN ENV SUST, V6, P110, DOI 10.1016/j.cosust.2013.11.012
   KNMI, 2014, KNMI 14 KLIM NED LEI
   Kros J, 2015, LANDSCAPE ECOL, V30, P871, DOI 10.1007/s10980-014-0131-y
   Leclére D, 2013, ECOL ECON, V87, P1, DOI 10.1016/j.ecolecon.2012.11.010
   Louhichi K, 2010, AGR SYST, V103, P585, DOI 10.1016/j.agsy.2010.06.006
   Mandryk M, 2014, REG ENVIRON CHANGE, V14, P1463, DOI 10.1007/s10113-014-0589-9
   Mandryk M, 2012, LANDSCAPE ECOL, V27, P509, DOI [10.1007/s10980-012-9714-7, 10.1007/s10980-012-9721-8]
   Murphy JM, 2004, NATURE, V430, P768, DOI 10.1038/nature02771
   Myhre G, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P659
   Naeff H.S.D., 2003, GEOGRAFISCHE INFORM
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Nelson GC, 2014, P NATL ACAD SCI USA, V111, P3274, DOI 10.1073/pnas.1222465110
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Olsson JA, 2009, ENVIRON SCI POLICY, V12, P562, DOI 10.1016/j.envsci.2009.01.012
   Paas W.H., 2013, THESIS
   Pannell DJ, 1999, J SUSTAIN AGR, V13, P57, DOI 10.1300/J064v13n04_06
   Petit J, 2003, J ENVIRON MANAGE, V68, P377, DOI 10.1016/S0301-4797(03)00105-1
   Podhora A, 2013, ENVIRON SCI POLICY, V31, P85, DOI 10.1016/j.envsci.2013.03.002
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Potschin MB., 2008, Sustainability impact assessment of land use policies, P425, DOI [DOI 10.1007/978-3-540-78648-1_21, 10.1007/978-3-540-78648-1_21]
   POTTER C, 1993, LAND USE POLICY, V10, P267, DOI 10.1016/0264-8377(93)90037-B
   Reidsma P, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/4/045004
   Reidsma P, 2012, ENVIRON SCI POLICY, V18, P66, DOI 10.1016/j.envsci.2012.01.003
   Reidsma P, 2011, LAND USE POLICY, V28, P604, DOI 10.1016/j.landusepol.2010.11.009
   Riedijk A., 2007, SL06 VU MNP
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Rosenzweig C, 2013, AGR FOREST METEOROL, V170, P166, DOI 10.1016/j.agrformet.2012.09.011
   Rotmans J, 1996, CLIMATIC CHANGE, V34, P327, DOI 10.1007/BF00139296
   Schaap BF, 2013, EUR J AGRON, V48, P30, DOI 10.1016/j.eja.2013.02.004
   Schosser B, 2010, J LAND USE SCI, V5, P159, DOI 10.1080/1747423X.2010.485727
   Singh RK, 2012, ECOL INDIC, V15, P281, DOI 10.1016/j.ecolind.2011.01.007
   Steenwerth KL., 2014, Agric Food Secur, V3, P1, DOI [10.1186/2048-7010-3-11, DOI 10.1186/2048-7010-3-11]
   Sutton MA, 1998, ENVIRON POLLUT, V102, P349, DOI 10.1016/S0269-7491(98)80054-7
   Tilman D, 2002, NATURE, V418, P671, DOI 10.1038/nature01014
   Troost C, 2015, AM J AGR ECON, V97, P833, DOI 10.1093/ajae/aau076
   Tsutsumi Y., 2015, THESIS
   Turner BL, 2007, P NATL ACAD SCI USA, V104, P20666, DOI 10.1073/pnas.0704119104
   van Asselt ED, 2014, ECOL INDIC, V43, P315, DOI 10.1016/j.ecolind.2014.02.027
   Van Calker KJ, 2005, AGR HUM VALUES, V22, P53, DOI [10.1004/s10460-004-7230-3, 10.1007/s10460-004-7230-3]
   van den Berg AE, 2010, SOC SCI MED, V70, P1203, DOI 10.1016/j.socscimed.2010.01.002
   Van den Hurk B., 2006, KNMI Climate Change scenarios for 2006
   van Ittersum MK, 2008, AGR SYST, V96, P150, DOI 10.1016/j.agsy.2007.07.009
   Van Teeffelen AJA, 2015, LANDSCAPE ECOL, V30, P937, DOI 10.1007/s10980-015-0187-3
   Van Vliet J.A., 2015, DE MYSTIFYING FAMILY, V5, P11
   Veraart JA, 2014, REG ENVIRON CHANGE, V14, P851, DOI 10.1007/s10113-013-0567-7
   Witte JPM, 2015, LANDSCAPE ECOL, V30, P835, DOI 10.1007/s10980-014-0086-z
   Wolf J, 2011, AGRIADAPT REPORTS
   Wolf J, 2015, AGR SYST, V140, P56, DOI 10.1016/j.agsy.2015.08.010
   Zimmermann A, 2009, ENVIRON SCI POLICY, V12, P601, DOI 10.1016/j.envsci.2009.01.014
NR 74
TC 52
Z9 55
U1 2
U2 136
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0308-521X
EI 1873-2267
J9 AGR SYST
JI Agric. Syst.
PD DEC
PY 2015
VL 141
BP 160
EP 173
DI 10.1016/j.agsy.2015.10.009
PG 14
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture
GA CX0EW
UT WOS:000365370700016
DA 2025-01-10
ER

PT J
AU Norris, C
   Hobson, P
   Ibisch, PL
AF Norris, Catherine
   Hobson, Peter
   Ibisch, Pierre L.
TI Microclimate and vegetation function as indicators of forest
   thermodynamic efficiency
SO JOURNAL OF APPLIED ECOLOGY
LA English
DT Article
DE biomass; climate change conference; complex systems; CSR model; entropy;
   exergy; temperature attenuation; thermodynamic efficiency; vegetation
   function
ID CLIMATE-CHANGE; ECOSYSTEM; IMPACT; BRANDENBURG; EXERGY; LIFE; TOOL
AB 1. Resilient and functional landscapes are essential for climate change adaptation. Thermodynamic theory has been applied increasingly to ecological studies to understand ecosystem resilience and integrity. Resilient ecosystems have complex structure and greater levels of biomass and functional diversity, which act to enhance the degradation of solar energy. Forests that exhibit these characteristics express thermodynamic efficiency through a greater capacitance effect that promotes cooler surface temperatures under extreme weather conditions. 2. With forest disturbance, complex structures and functional linkages are simplified, reducing the capacity of the system to degrade energy. Such changes can lead to dysfunctional ecosystem states, impaired provision of ecosystem services and a weakened resilience. 3. This study has applied indicators based on thermodynamic theory to a chronosequence of forest ecosystems in the UK, Germany and Ukraine. Surface temperatures were measured to test thermodynamic theories relating to energy degradation and temperature moderation. Grimes CSR model was applied to plant data to compare functional complexity in vegetation between stands. 4. Old-growth woodlands are shown to attenuate surface temperature more effectively than native species plantations. Consistently lower temperatures were observed in European old-growth forests with high proportions of biomass when compared to managed stands of similar species composition, suggesting a greater efficiency of energy degradation in complex forest ecosystems, particularly at higher temperatures. 5. Analysis of plant species data using Grimes CSR model indicated that old-growth forests ordinate towards competitive and stress-tolerant communities in contrast to intensively managed forests, which had a greater proportion of generalist and ruderal species. High CSR functional scores were associated with moderated temperature extremes. 6. Synthesis and applications. Our results suggest an important thermodynamic basis for conservation in the context of climate change. Conservation practice and management policy, which is based on preserving ecosystem complexity and function, can aid in mitigating the effects of extreme temperatures, enhancing vital services such as climate regulation, primary production and water retention. Old-growth forests have a significant climate mitigation role alongside other recognised ecosystem services such as carbon sequestration.
C1 [Norris, Catherine; Hobson, Peter] Writtle Coll, Chelmsford CM1 3RR, Essex, England.
   [Norris, Catherine; Hobson, Peter; Ibisch, Pierre L.] Ctr Econ & Ecosyst Management, D-16225 Eberswalde, Germany.
   [Ibisch, Pierre L.] Eberswalde Univ Sustainable Dev, Fac Forest & Environm, D-16225 Eberswalde, Germany.
C3 Anglia Ruskin University; Eberswalde University for Sustainable
   Development
RP Norris, C (corresponding author), Writtle Coll, Lordships Rd, Chelmsford CM1 3RR, Essex, England.
EM catherine.norris2@writtle.ac.uk
FU Brandenburg State Forestry Enterprise
FX We thank Prof. Dr Fedir Hamor (Director), Vasyl Pokynchereda (Deputy
   Director) and the staff of the Carpathian Biosphere Reserve, Ukraine,
   for their support with this project, the Brandenburg State Forestry
   Enterprise and specifically Volkmar Ebert for their support at the
   Eberswalde sites. We also thank the Woodland Trust. P. Ibisch
   acknowledges the research professorship 'Biodiversity and Natural
   Resource Management under Global Change' awarded by Eberswalde
   University of Sustainable Development.
CR Achten W. M. J., 2008, P 6 INT C LIF CYCL A
   [Anonymous], ECOSYSTEM ECOLOGY NE
   [Anonymous], P INT WORKSH ADV EN
   Bendoricchio G, 1997, ECOL MODEL, V102, P5, DOI 10.1016/S0304-3800(97)00091-4
   Centre for Ecology & Hydrology, 2009, MOD AN VEG INF SYST
   Clewell AF, 2006, CONSERV BIOL, V20, P420, DOI 10.1111/j.1523-1739.2006.00340.x
   Craft C, 2003, ECOL APPL, V13, P1417, DOI 10.1890/02-5086
   Dale VH, 1997, ECOL APPL, V7, P753, DOI 10.1890/1051-0761(1997)007[0753:TRBLUC]2.0.CO;2
   Foley JA, 2003, FRONT ECOL ENVIRON, V1, P38, DOI 10.2307/3867963
   Fraser R. A., 2002, THERMAL REMOTE SENSI, P1
   GRIME JP, 1977, AM NAT, V111, P1169, DOI 10.1086/283244
   HALL J.E., 2004, NATL VEGETATION CLAS
   Hammer Oyvind, 2001, Palaeontologia Electronica, V4, pUnpaginated
   Hobson P. R., 2010, TECHNICAL SERIES SEC, P127
   Hojdova M., 2005, SILVA GABRETA, V11, P13
   Holsten A, 2009, ECOL MODEL, V220, P2076, DOI 10.1016/j.ecolmodel.2009.04.038
   Hunt R, 2004, APPL VEG SCI, V7, P163, DOI 10.1111/j.1654-109X.2004.tb00607.x
   Jackson RB, 2008, ENVIRON RES LETT, V3, DOI 10.1088/1748-9326/3/4/044006
   Jorgensen SE, 2006, ECOL INDIC, V6, P24, DOI 10.1016/j.ecolind.2005.08.003
   Jorgensen SE, 2000, ECOL MODEL, V126, P249, DOI 10.1016/S0304-3800(00)00268-4
   KAY JJ, 1992, ECOLOGICAL INDICATORS, VOLS 1 AND 2, P159
   Kuemmerle T, 2007, ECOL APPL, V17, P1279, DOI 10.1890/06-1661.1
   Kutsch W. L., 1998, ECO TARGETS GOAL FUN, P87
   Lasch P, 2002, FOREST ECOL MANAG, V162, P73, DOI 10.1016/S0378-1127(02)00051-8
   Lin H., 2011, ECOLOGICAL MODELLING, V222, P15
   Lin H, 2009, ECOL MODEL, V220, P784, DOI 10.1016/j.ecolmodel.2009.01.003
   Lindner M, 2010, FOREST ECOL MANAG, V259, P698, DOI 10.1016/j.foreco.2009.09.023
   Lu F., 2003, ECOLOGICAL MODELLING, V170, P1
   Luvall J. C., 2007, 7 S URB S 10 13 SEPT
   LUVALL JC, 1989, REMOTE SENS ENVIRON, V27, P1, DOI 10.1016/0034-4257(89)90032-1
   Marland G, 2003, CLIM POLICY, V3, P149, DOI 10.1016/S1469-3062(03)00028-7
   Maycock Paul Frederick, 2000, Fragmenta Floristica et Geobotanica, V45, P281
   Mickleburgh P., 2011, THESIS U ESSEX
   Milad M, 2011, FOREST ECOL MANAG, V261, P829, DOI 10.1016/j.foreco.2010.10.038
   Müller F, 2006, ECOL INDIC, V6, P63, DOI 10.1016/j.ecolind.2005.08.017
   Natural England, 2010, NECR038 NAT ENGL
   Noss R. F., 2001, CONSERV BIOL, V15, P3
   ODUM EP, 1985, BIOSCIENCE, V35, P419, DOI 10.2307/1310021
   ODUM EP, 1969, SCIENCE, V164, P262, DOI 10.1126/science.164.3877.262
   Pivec J., 2002, EKOLOGIA, V21, P1
   Pugnaire F., 2007, FUNCTIONAL PLANT ECO, VSecond
   Reynolds CS, 2002, ECOL MODEL, V158, P181, DOI 10.1016/S0304-3800(02)00230-2
   Robinson DT, 2009, ECOL MODEL, V220, P1325, DOI 10.1016/j.ecolmodel.2009.02.020
   Rodwell J.S., 2006, NATL VEGETATION CLAS
   Ryan JG, 2007, ECOL COMPLEX, V4, P113, DOI 10.1016/j.ecocom.2007.03.004
   Schneider E.D., 1995, Reflections on the Future of Biology eds, V8, P161
   SCHNEIDER ED, 1994, MATH COMPUT MODEL, V19, P25, DOI 10.1016/0895-7177(94)90188-0
   Silow EA, 2010, ENTROPY-SWITZ, V12, P902, DOI 10.3390/e12040902
   Stoy P.C., 2010, Ecosystem Ecology: A New Synthesis, P40
   Teuling AJ, 2010, NAT GEOSCI, V3, P722, DOI 10.1038/NGEO950
   Wagendorp T, 2006, ENERGY, V31, P112, DOI 10.1016/j.energy.2005.01.002
   Whiteman CD, 2000, J ATMOS OCEAN TECH, V17, P77, DOI 10.1175/1520-0426(2000)017<0077:EOAITD>2.0.CO;2
   Xu W, 2001, AGR ECOSYST ENVIRON, V83, P215, DOI 10.1016/S0167-8809(00)00159-6
   Zhang HY, 2002, ECOL MODEL, V153, P69, DOI 10.1016/S0304-3800(01)00502-6
NR 54
TC 83
Z9 91
U1 3
U2 82
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0021-8901
EI 1365-2664
J9 J APPL ECOL
JI J. Appl. Ecol.
PD JUN
PY 2012
VL 49
IS 3
BP 562
EP 570
DI 10.1111/j.1365-2664.2011.02084.x
PG 9
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 950PF
UT WOS:000304660500006
DA 2025-01-10
ER

PT J
AU Johns, RA
   Dixon, B
   Pontes, R
AF Johns, Rebecca A.
   Dixon, Barnali
   Pontes, Rachelle
TI Tale of two neighbourhoods: biophysical and socio-economic vulnerability
   to climate change in Pinellas County, Florida
SO LOCAL ENVIRONMENT
LA English
DT Article
DE Climate resilience; community-based adaptation; social networks; severe
   weather; perceptions of preparedness; qualitative research
ID COMMUNITY-BASED ADAPTATION; RESILIENCE; HEALTH
AB Defining vulnerability and identifying vulnerable areas and populations is critical to climate adaptation and resilience. Neighbourhoods are not homogeneous in terms of their socio-economic and physical vulnerability to flooding and other climate related impacts resulting in diverse challenges. Working with communities to better identify their concerns, liabilities, and strengths in the face of climate challenges will help build resiliency for all residents of the Tampa Bay area. This research identifies the weaknesses in knowledge, preparedness and ability to adapt in two communities in Pinellas County, Florida: examining a neighbourhood that is socio-economically vulnerable and a neighbourhood that experiences only physical (locational) vulnerability. We also identify opportunities for inclusive disaster planning, climate adaptation plans and to increase resiliency through long-term interactions between residents, community leaders, and local officials.
C1 [Johns, Rebecca A.] Univ S Florida, Dept Soc Culture & Language, 140 Seventh Ave South, St Petersburg, FL 33701 USA.
   [Dixon, Barnali] Univ S Florida, Geospatial Analyt Lab, St Petersburg, FL 33701 USA.
   [Pontes, Rachelle] Univ S Florida, Florida Studies, St Petersburg, FL 33701 USA.
C3 State University System of Florida; University of South Florida; State
   University System of Florida; University of South Florida; State
   University System of Florida; University of South Florida
RP Johns, RA (corresponding author), Univ S Florida, Dept Soc Culture & Language, 140 Seventh Ave South, St Petersburg, FL 33701 USA.
EM Rjohns@usf.edu
OI Johns Krishnaswami, Rebecca/0000-0003-4204-3597
CR Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Adger WN, 1999, WORLD DEV, V27, P249, DOI 10.1016/S0305-750X(98)00136-3
   Aldrich D.P., 2012, Building resilience: Social capital in Post-Disaster Recovery
   [Anonymous], 2000, Linking social and ecological systems: management practices and social mechanisms for building resilience
   [Anonymous], 2020, SUSTAINABILITY BASEL, DOI DOI 10.3390/SU12062168
   [Anonymous], 2003, EC GEOGRAPHY, DOI DOI 10.1111/ECGE.2003.79.ISSUE-4
   Arthurson K, 2015, LOCAL ENVIRON, V20, P1, DOI 10.1080/13549839.2013.818951
   Ayers J, 2009, ENVIRONMENT, V51, P22, DOI 10.3200/ENV.51.4.22-31
   Berkes F, 2013, SOC NATUR RESOUR, V26, P5, DOI 10.1080/08941920.2012.736605
   Betzold C, 2015, CLIMATIC CHANGE, V133, P481, DOI 10.1007/s10584-015-1408-0
   Blaikie P., 1994, At Risk: Natural hazards, people's vulnerability, and disasters
   Brody SD, 2008, ENVIRON BEHAV, V40, P72, DOI 10.1177/0013916506298800
   Brooks N., 2003, Tyndall Centre for Climate Change Research, DOI DOI 10.1086/379713
   Buchanan Allan A., 2017, WEEKLY CHALLENG 0928
   Cains MG, 2019, CURR OPIN ENV SUST, V39, P24, DOI 10.1016/j.cosust.2019.06.005
   Casteel MJ, 2006, J ENVIRON SCI HEAL A, V41, P173, DOI 10.1080/10934520500351884
   Chapman S, 2017, LANDSCAPE ECOL, V32, P1921, DOI 10.1007/s10980-017-0561-4
   Clarke T, 2019, ISL STUD J, V14, P59, DOI 10.24043/isj.80
   Confalonieri U, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P391
   Cross J.A., 2001, Environmental Hazards, V3, P63, DOI DOI 10.3763/EHAZ.2001.0307
   Cutter SL, 2006, ANN AM ACAD POLIT SS, V604, P102, DOI 10.1177/0002716205285515
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Cutter Susan L., 2003, SOCIAL SCI Q, V84
   DPHP.gov, 2016, DISP
   Emrich C. T, 2005, THESIS
   Fletcher R, 2017, J ENVIRON EDUC, V48, P226, DOI 10.1080/00958964.2016.1139534
   Hedger M.M., 2008, Evaluation of adaptation to climate change from a development perspective
   iCAR, 2018, IN COAST AD RES ANN
   IPCC, 2014, CLIM CHANG 2014 IMP, V1
   Iturriza M, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100613
   Ivers LC, 2006, CURR OPIN INFECT DIS, V19, P408, DOI 10.1097/01.qco.0000244044.85393.9e
   Janssen MA, 2011, INT J COMMONS, V5, P340
   Jensen O, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12083413
   Jordan JC, 2015, CLIM DEV, V7, P110, DOI 10.1080/17565529.2014.934771
   Jurjonas M, 2018, OCEAN COAST MANAGE, V162, P137, DOI 10.1016/j.ocecoaman.2017.10.010
   Keenan JM, 2018, ENVIRON SCI POLICY, V88, P116, DOI 10.1016/j.envsci.2018.06.015
   Keim ME, 2008, AM J PREV MED, V35, P508, DOI 10.1016/j.amepre.2008.08.022
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Kim H, 2018, GEOFORUM, V96, P129, DOI 10.1016/j.geoforum.2018.08.006
   Kim H, 2016, SOC NATUR RESOUR, V29, P981, DOI 10.1080/08941920.2015.1080336
   Kirkby P, 2018, CLIM DEV, V10, P577, DOI 10.1080/17565529.2017.1372265
   Lindley S., 2011, Climate change, justice and vulnerability
   Linnekamp F, 2011, HABITAT INT, V35, P447, DOI 10.1016/j.habitatint.2010.12.003
   MacGillivray BH, 2018, ENVIRON SCI POLICY, V89, P116, DOI 10.1016/j.envsci.2018.07.014
   Mallin MA, 2006, ESTUAR COAST, V29, P1046, DOI 10.1007/BF02798667
   Martin Susan Taylor, 2013, NO FAIR DEAL LOWLAND
   Morrow BH, 1999, DISASTERS, V23, P1, DOI 10.1111/1467-7717.00102
   Nateghi R, 2018, IEEE ACCESS, V6, P13478, DOI 10.1109/ACCESS.2018.2792680
   Oleson K W, 2013, CLIMATIC CHANGE, V129, P525, DOI DOI 10.1007/S10584-013-0936-8
   Paavola J, 2017, ENVIRON HEALTH-GLOB, V16, P61, DOI 10.1186/s12940-017-0328-z
   Pelling Mark., 1998, J INT DEV, V10, P469, DOI DOI 10.1002/(SICI)1099-1328(199806)10:43.0.CO;2-4
   Reid H., 2007, Community-based adaptation: A vital approach to the threat climate change poses to the poor
   Reid H., 2009, Participatory Learning and Action, V60, P11
   Reid H, 2016, CLIM DEV, V8, P4, DOI 10.1080/17565529.2015.1034233
   Reid H, 2014, CLIM DEV, V6, P291, DOI 10.1080/17565529.2014.973720
   Reid H, 2014, COMMUNITY-BASED ADAPTATION TO CLIMATE CHANGE: SCALING IT UP, P3
   Rygel L., 2006, MITIG ADAPT STRAT GL, V11, P741, DOI [10.1007/s11027-006-0265-6, DOI 10.1007/S11027-006-0265-6]
   Satterthwaite D., 2009, ADAPTING CITIES CLIM, P3
   Statisticalatlas, 2018, FOOD STAMPS GREAT PI
   Sweet WV, 2016, B AM METEOROL SOC, V97, pS25, DOI 10.1175/BAMS-D-16-0117.1
   Tapsell SM, 2002, PHILOS T R SOC A, V360, P1511, DOI 10.1098/rsta.2002.1013
   Tavakol A, 2020, ATMOS RES, V239, DOI 10.1016/j.atmosres.2020.104907
   Timmerman P., 1981, VULNERABILITY RESILI, V1
   Warren John A, 2005, Int J Circumpolar Health, V64, P487
   Woolcock M., 2001, ISUMA CANADIAN J POL, V2, P11, DOI DOI 10.1017/CB09781107415324.004
   Zhou HJ, 2010, NAT HAZARDS, V53, P21, DOI 10.1007/s11069-009-9407-y
NR 66
TC 12
Z9 13
U1 0
U2 12
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1354-9839
EI 1469-6711
J9 LOCAL ENVIRON
JI Local Environ.
PD SEP 1
PY 2020
VL 25
IS 9
BP 697
EP 724
DI 10.1080/13549839.2020.1825356
EA SEP 2020
PG 28
WC Green & Sustainable Science & Technology; Environmental Studies;
   Geography; Regional & Urban Planning; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Geography; Public Administration; Urban Studies
GA NW3XT
UT WOS:000573668700001
DA 2025-01-10
ER

PT J
AU Manga, SJT
AF Manga, Sylvestre-Jose-Tidiane
TI When digital technology innovation enhances Indigenous Peoples'
   e-participation in climate change resilience-building: perspectives
   under the "e-GIS Smart, Inclusive, and, Climate-resilient Indigenous
   Peoples Landscape and Community Clearing-House Mechanism Solution"
SO JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT
LA English
DT Article
DE Indigenous Peoples Affairs Global Agenda; climate change adaptation;
   Indigenous Peoples' sovereignty; Indigenous information; Indigenous
   Peoples' e-participation; Indigenous Peoples' right to decision-making;
   technology solutions and innovation; Landscape Geomatics Engineering
   Technology trends
ID CELLULAR-AUTOMATA
AB Web-based multilingual tools to facilitate communication between Local and Indigenous Communities is an environmental technology approach emerging under the United Nations Biodiversity Global Agenda. To better address present climate resilience-building challenges in the current smart world, this contribution presents innovative avenues leading to the development of the << e-GIS Smart, Inclusive, and, Climate-resilient Indigenous Peoples Landscape and Community Clearing-House Mechanism Solution >> which is meant to be used in the mobile-friendly website environment and the e-app environment. This technology policy paper shows that digital GIS, remote sensing products of observation satellites, and smartphone applications products derived from telecommunication satellites can help facilitate Indigenous Peoples' contribution to climate resilience-building within their territories in terms of biodiversity and within their communities in terms of poverty eradication throughout the implementation of the United Nations Indigenous Peoples' Affairs Global Agenda. The methodology used consists, therefore, of a plural technology interface that promises, among many other benefits, to facilitate Indigenous Peoples' participation in decision-making processes. This research reminds us of the importance of state responsibility in these matters. It shows the importance of Indigenous Peoples' participation in the implementation of global instances' agendas through national reporting. It highlights the key role of Indigenous information decolonization and governance as principles of Indigenous Peoples' sovereignty over Indigenous information. The results of this research are illustrated with case studies, when possible, to show the potential of the Solution to achieve its goals in climate resilience-building in Indigenous Peoples Landscapes and Communities with Indigenous Peoples and the financial support of state governments and inter-governmental institutions. In Canada, the use of the Solution to move forward in the Indigenous Peoples Affairs' agenda, has the potential, among others, to enhance the expected outcome of the Canadian First Nations Data Governance Strategy (FNDGS) which is adopted as a response to an evolving smart planet to ensure no First Nation is left behind.
C1 [Manga, Sylvestre-Jose-Tidiane] UNCBD Parties, Int consultant, Montreal, PQ, Canada.
   [Manga, Sylvestre-Jose-Tidiane] UNCCD Int Consultant, Bonn, Germany.
   [Manga, Sylvestre-Jose-Tidiane] McGill Univ, Affiliated Ctr Int Sustainable Dev Law, Montreal, PQ, Canada.
C3 McGill University
RP Manga, SJT (corresponding author), UNCBD Parties, Int consultant, Montreal, PQ, Canada.; Manga, SJT (corresponding author), UNCCD Int Consultant, Bonn, Germany.; Manga, SJT (corresponding author), McGill Univ, Affiliated Ctr Int Sustainable Dev Law, Montreal, PQ, Canada.
EM sylvestremanga7@outlook.com
CR Brown K, 2020, SOC SCI MED, V258, DOI 10.1016/j.socscimed.2020.113015
   ESRI, 2021, WHAT IS GIS FRAM ORG
   First Nations Data Governance Strategy, 2020, 1 NAT DAT GOV STRAT
   First Nations Information Governance Center (FNIGC), 2022, FNIGC
   First Nations Information Governance Centre (FNIGC), 2020, 1 NAT DAT GOV STRAT
   GDC Foundation, 2022, GDC FDN CHER LYNN RU
   Geoghegan J, 1997, ECOL ECON, V23, P251, DOI 10.1016/S0921-8009(97)00583-1
   Healy B., 2020, 1 NATIONS DATA GOVER
   Highet C., 2019, DIGITAL TRANSFORMATI
   Hilferink M., 1999, J. Geogr. Syst, V1, P155, DOI [DOI 10.1007/S101090050010, 10.1007/s101090050010]
   Jensen T., 2019, IT IS TIME DECOLONIZ
   Kalacska M, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9060623
   Ke LH, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9020114
   Kingston R., 2000, Computers, Environment and Urban Systems, V24, P109, DOI 10.1016/S0198-9715(99)00049-6
   Li X, 2000, INT J GEOGR INF SCI, V14, P131, DOI 10.1080/136588100240886
   Li X, 2002, INT J GEOGR INF SCI, V16, P323, DOI 10.1080/13658810210137004
   Liang K, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9060588
   Lyons SR, 2000, COLL COMPOS COMMUN, V51, P447, DOI 10.2307/358744
   Manga SJT, 2020, J RURAL COMMUNITY D, V15, P39
   Mindy D., 2020, 1 NAT DAT GOV STRAT
   Morgan R, 2004, SOC LEGAL STUD, V13, P481, DOI 10.1177/0964663904047330
   Native Nations Institute-University of Arizona, 2022, STRENGTH IND GOV
   Noronha N., 2021, International Journal of Child and Adolescent Resilience/Revue internationale de la resilience des enfants et des adolescents, V8, P1, DOI DOI 10.7202/1077724AR
   Ontario Institute for Studies in Education, 2020, DEEP KNOWL AB ED AND
   Ouyang ZT, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9010044
   Rounce DR, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9070654
   Sieber R, 2006, ANN ASSOC AM GEOGR, V96, P491, DOI 10.1111/j.1467-8306.2006.00702.x
   Tan C, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9020150
   UNCBD, 2017, GOV AGR CONTR TRAD K
   United Nations, 2008, INDIGENOUS PEOPLES I
   United Nations, 2009, C IND PEOPL CLIM CHA
   United Nations, 2008, C IND PEOPL CLIM CHA
   United Nations CBD, 2021, BIODIVERSITY KNOWLED
   United Nations Convention on Biological Diversity, 2003, CBD TECHNICAL SERIES, V10
   United Nations Convention on Biological Diversity, 2009, UNCBD TECHN SER, V41
   United Nations Convention on Biological Diversity, 2006, TECHNICAL SERIES, V4, P34
   United Nations Convention on Biological Diversity, 2022, TOP IND PEOPL LOC CO
   United Nations Convention on Biological Diversity-Clearing-House Mechanism/Government of Canada Biodivcanada, 2019, SUMMARY CANADAS 6 NA
   United Nations Division for Social Policy and Development, 2008, UN PERMANENT FORUM I
   United Nations Framework Conference on Climate Change, 2007, FCCCCP20076
   United Nations Human Rights Committee, 2022, MON CIV POL RIGHTS
   United Nations Human Rights-Office of the High Commissioner, 2019, IND PEOPL HUM RIGHTS
   United Nations Human Rights-Office of the High Commissioner, 2019, 42 SESS HRC
   USGS, 2021, WHAT IS GEOGR INF SY
   Verburg P. H., 2004, GeoJournal, V61, P309, DOI 10.1007/s10708-004-4946-y
   Wang SS, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9030256
   Wu Fulong., 1999, Journal of Geographical Systems, V1, P199
   Yang J, 2013, NAT CLIM CHANGE, V3, P1002, DOI 10.1038/NCLIMATE2033
NR 48
TC 2
Z9 2
U1 3
U2 17
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0964-0568
EI 1360-0559
J9 J ENVIRON PLANN MAN
JI J. Environ. Plan. Manag.
PD OCT 15
PY 2023
VL 66
IS 12
BP 2467
EP 2486
DI 10.1080/09640568.2022.2078690
EA MAY 2022
PG 20
WC Development Studies; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Development Studies; Public Administration
GA N3VD2
UT WOS:000812680300001
DA 2025-01-10
ER

PT S
AU Norbäck, D
AF Norback, Dan
BE Kishi, R
   Norback, D
   Araki, A
TI Future Directions of Research on Indoor Environment, Indoor Air Quality
   (IAQ), and Health
SO INDOOR ENVIRONMENTAL QUALITY AND HEALTH RISK TOWARD HEALTHIER
   ENVIRONMENT FOR ALL
SE Current Topics in Environmental Health and Preventive Medicine
LA English
DT Editorial Material; Book Chapter
DE Dampness; Mould; Climate change; Energy efficiency; Biomarkers; New
   building materials; Chemical emissions; Indoor environment; Respiratory
   health; Allergies
ID RESPIRATORY SYMPTOMS; HOME DAMPNESS; ASTHMA; BIOMARKERS; POLLUTION;
   CLIMATE; MOLD
AB The impact of the indoor environment on human health will continue to be an important topic in the future. Large prospective studies and intervention studies are needed in different indoor environments, including homes, schools, day care centers, offices, and hospitals. More epidemiological studies using biomarkers of health effects are needed. There can be different sensitive subgroups in the population reacting more strongly to indoor air pollution, linked to age, gender, allergic disposition (atopy), personality traits, stress, dietary habits, and certain types of medication. More research is needed on sensitive subgroups in a broader perspective. Investigations are needed on gene-environment interaction and gene expression in relation to different types of indoor exposure. There is a needed to continuously evaluate the health consequences of new building technologies and to perform small-scale testing of new building materials in real buildings before they are commonly used in large-scale production. It is a different task to control chemical emissions from building materials. Emission testing of building materials at dry laboratory conditions may not be relevant to evaluate chemical emissions in building with dampness. More research is needed to identify types of dampness-related exposure and etiology behind health effects of dampness and mould in buildings. There is a need to apply modern statistical methods to study multiple interactions between different VOC and other indoor factors in indoor environments with respect to health effects. Existing computer-based simulation models should be used to evaluate the risk of dampness and indoor mould growth when designing new buildings. Risk constructions, known to have a high probability for dampness and mould, should be avoided. Relevant authorities on national and international levels should set standards for concentrations of specific VOC in indoor air. Hopefully, in the future, there will be mandatory check-ups and checklists for quality improvements in the built environment. Epidemiological studies are needed on health consequences of energy use and energy saving in buildings in different climate zones, as well as on health consequences of climate change. Adaption of buildings and architectural interventions are needed to counteract the health consequences of climate change.
C1 [Norback, Dan] Uppsala Univ, Dept Med Sci, Uppsala, Sweden.
C3 Uppsala University
RP Norbäck, D (corresponding author), Uppsala Univ, Dept Med Sci, Uppsala, Sweden.
EM dan.norback@medsci.uu.se
CR de Oliveira BFA, 2014, J TOXICOL ENV HEAL B, V17, P369, DOI 10.1080/10937404.2014.976893
   Amaral AFS, 2014, THORAX, V69, P558, DOI 10.1136/thoraxjnl-2013-204574
   Cai GH, 2011, J ENVIRON MONITOR, V13, P2018, DOI 10.1039/c0em00553c
   Castro-Giner F, 2009, ENVIRON HEALTH PERSP, V117, P1919, DOI 10.1289/ehp.0900589
   Demain JG, 2018, CURR ALLERGY ASTHM R, V18, DOI 10.1007/s11882-018-0777-7
   Deng Q, 2008, ENVIRON RES, V165, P23
   Gotzsche PC, 2008, COCHRANE DB SYST REV, DOI 10.1002/14651858.CD001187.pub3
   Gunnbjörnsdóttir MI, 2006, THORAX, V61, P221, DOI 10.1136/thx.2005.057430
   Haines A, 2019, NEW ENGL J MED, V380, P263, DOI 10.1056/NEJMra1807873
   Ho SM, 2012, ILAR J, V53, P289, DOI 10.1093/ilar.53.3-4.289
   Kim JL, 2005, INDOOR AIR, V15, P170, DOI 10.1111/j.1600-0668.2005.00334.x
   Kuiper IN, 2018, BMC PULM MED, V18, DOI 10.1186/s12890-018-0687-4
   Lampa E, 2014, ENVIRON HEALTH-GLOB, V13, DOI 10.1186/1476-069X-13-57
   Locher Wolfgang Gerhard, 2007, Environ Health Prev Med, V12, P238, DOI 10.1007/BF02898030
   LUNDHOLM M, 1990, ARCH ENVIRON HEALTH, V45, P135, DOI 10.1080/00039896.1990.9936706
   Norbäck D, 2017, INDOOR AIR, V27, P921, DOI 10.1111/ina.12375
   Norbäck D, 2002, INT ARCH OCC ENV HEA, V75, P298, DOI 10.1007/s00420-002-0314-8
   Norbäck D, 2019, ENVIRON INT, V125, P252, DOI 10.1016/j.envint.2019.01.036
   Norbäck D, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0112960
   Norbäck D, 2013, OCCUP ENVIRON MED, V70, P325, DOI 10.1136/oemed-2012-100963
   Oeder S, 2012, AM J RESP CELL MOL, V47, P575, DOI 10.1165/rcmb.2012-0139OC
   Prior JH, 2018, PUBLIC HEALTH RES PR, V28, DOI 10.17061/phrp2841831
   Radon K, 2006, OCCUP ENVIRON MED, V63, P73, DOI 10.1136/oem.2004.017616
   Rocchi S, 2017, REV MAL RESPIR, V34, P635, DOI 10.1016/j.rmr.2016.06.007
   Runeson R, 2004, INDOOR AIR, V14, P394, DOI 10.1111/j.1600-0668.2004.00261.x
   Sauni R, 2015, COCHRANE DATABASE SY, V2015
   Sparks JA, 2019, BMC MUSCULOSKEL DIS, V20, DOI 10.1186/s12891-018-2381-3
   Spartano NL, 2019, J DIABETES RES, V2019, DOI 10.1155/2019/2718465
   Su MW, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0030694
   Svanes C, 2017, INT J EPIDEMIOL, V46, P235, DOI 10.1093/ije/dyw151
   Thomson H, 2013, COCHRANE DB SYST REV, DOI 10.1002/14651858.CD008657.pub2
   Timm S, 2019, EUR J EPIDEMIOL, V34, P601, DOI 10.1007/s10654-019-00491-9
   Tsai CH, 2011, OCCUP ENVIRON MED, V68, P771, DOI 10.1136/oem.2010.060970
   Wang IJ, 2012, ENVIRON RES, V118, P72, DOI 10.1016/j.envres.2012.07.009
   Wieslander G, 1997, INT ARCH OCC ENV HEA, V69, P115
NR 35
TC 8
Z9 10
U1 3
U2 15
PU SPRINGER-VERLAG SINGAPORE PTE LTD
PI SINGAPORE
PA 152 BEACH ROAD, #21-01/04 GATEWAY EAST, SINGAPORE, 189721, SINGAPORE
SN 2364-8333
EI 2364-8341
BN 978-981-32-9182-9; 978-981-32-9181-2
J9 CURR TOP ENV HEAL PR
PY 2020
BP 321
EP 333
DI 10.1007/978-981-32-9182-9_17
D2 10.1007/978-981-32-9182-9
PG 13
WC Public, Environmental & Occupational Health
WE Book Citation Index – Science (BKCI-S)
SC Public, Environmental & Occupational Health
GA BR1CW
UT WOS:000631636800018
DA 2025-01-10
ER

PT J
AU Limantol, AM
   Keith, BE
   Azabre, BA
   Lennartz, B
AF Limantol, Andrew Manoba
   Keith, Bruce Edward
   Azabre, Bismark Atiayure
   Lennartz, Bernd
TI Farmers' perception and adaptation practice to climate variability and
   change: a case study of the Vea catchment in Ghana
SO SPRINGERPLUS
LA English
DT Article
DE Climate change; Farmers' perception; Adaptations; Barriers; Vea
   catchment
ID RAINFALL; IMPACTS
AB Background: Rain-fed agriculture remains the source of employment for a majority of Ghana's population, particularly in northern Ghana where annual rainfall is low. The purpose of this study is to examine farmers' perceptions and adaptation practices to climate change and variability in accordance with actual recorded weather data of the Vea catchment in Upper East Region of northern Ghana during the time interval from 1972 to 2012.
   Methods: Climatic data over 41-years (1972-2012) from four stations in vicinity of the catchment was evaluated to identify actual weather outcomes. A survey questionnaire targeting farmers with at least 30-years of farming experience in the area was administered in six of the eleven agricultural enumeration areas in the catchment covering 305 km(2). Of the 466 farmers interviewed, 79 % utilized rain-fed practices while 21 % utilized some form of irrigation.
   Results: Results indicate that nearly 90 % of the farmers interviewed believe that temperature increased over the past 30-years, while over 94 % of the farmers believe that amount of rainfall, duration, intensity and rainy days has decreased. Nearly 96 % of the farmers believe that their farms are extremely vulnerable to decreased rainfall, droughts and changed timing of rainfall events. Climatic data of the catchment indicates a rising trend in temperature but no long-term changes in annual and monthly rainfall, thereby possibly increasing levels of evapotranspiration. While no statistical differences were found between rain-fed and irrigation agricultural types regarding receipt of external support, their approaches to climatic change adaptation do differ. Patently, 94 and 90 % of farmers relying on rain-fed and irrigation strategies respectively receive some form of support, primarily via extension services. Farmers using rain-fed practices adjust to climate variability by varying crop types via rotation without fertilizer while farmers employing irrigation practices are more likely to offset climate variability with a greater use of fertilizer application.
   Conclusion: The Vea catchment faces rising temperature and evapotranspiration trends. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support. Adequate extension services and irrigation facilities are needed to assist farmers in order to sustain their livelihoods on the long run.
C1 [Limantol, Andrew Manoba] Univ Abomey Calavi, West African Sci Serv Ctr Climate Change & Adapte, Grad Res Program GRP Climate Change & Water Resou, Cotonou, Benin.
   [Keith, Bruce Edward] US Mil Acad, Ctr Nation Reconstruct & Capac Dev, Dept Syst Engn, West Point, NY 10996 USA.
   [Azabre, Bismark Atiayure] Univ Dev Studies, Planning & Management Dept, Wa Campus, Wa, Ghana.
   [Lennartz, Bernd] Univ Rostock, Agr & Environm Sci, D-18055 Rostock, Germany.
C3 University of Abomey Calavi; United States Military Academy; United
   States Department of Defense; United States Army; University for
   Development Studies; University of Rostock
RP Limantol, AM (corresponding author), Univ Abomey Calavi, West African Sci Serv Ctr Climate Change & Adapte, Grad Res Program GRP Climate Change & Water Resou, Cotonou, Benin.
EM limantol@yahoo.co.uk
RI Lennartz, Bernd/M-3823-2019
OI Lennartz, Bernd/0000-0003-3020-7312
FU German Ministry of Education and Research (BMBF)
FX This work has been conducted as part of a doctorate research scholarship
   under West African Science Service Center on Climate Change and Adapted
   Land Use (WASCAL) project funded by the German Ministry of Education and
   Research (BMBF). The funders had no role in the design of the study and
   collection, analysis, and interpretation of data and in preparation of
   the manuscript, or decision to publish.
CR Abeygunawardena P., 2003, Poverty and Climate Change. Reducing the Vulnerability of the Poor through Adaptation
   [Anonymous], 2009, INT FOOD POLICY RES
   [Anonymous], 2013, Population and Housing Census 2010: Regional Analytical Report, Northern Region
   [Anonymous], 5468 WORLD BANK
   [Anonymous], RIP BUFF ZON POL MAN
   [Anonymous], 2007, CLIMATE CHANGE 2007
   Antwi-Agyei P, 2012, 105 U LEEDS CTR CLIM, V37
   Apata TG., 2011, ENV EC, V2, P74
   Bhatti AU, 2012, SOIL ENVRON, V31, P1
   Blench R., 2006, WORKING PAPER BACKGR
   Burke M, 2010, ADV GLOB CHANGE RES, V37, P133, DOI 10.1007/978-90-481-2953-9_8
   Butt TA, 2006, CLIM POLICY, V5, P583, DOI 10.1080/14693062.2006.9685580
   Chishakwe N., 2012, Building climate change adaptation on community experiences
   Denscombe M., 2010, GOOD RES GUIDE SMALL
   Diao X, 2010, GLOB FOR AGR 29 30 N
   EPA, 2007, EPA POL ADV SER, V1
   Foltz B, 2013, POPULATION VARIANCE, DOI DOI 10.1007/s10668-012-9339-7
   Food and Agriculture Organisation of the United Nations [FAO], 2007, AD CLIM CHANG AGR FO
   Food and Agriculture Organisation of the United Nations [FAO], 2011, FAO AD FRAM PROGR CL
   Food and Agriculture Organisation of the United Nations [FAO], 2008, CLIM CHANG AD MIT FO
   Food and Agriculture Organization of the United Nations, 2010, CLIM SMART AGR POL P
   Food and Agriculture Organization of the United Nations [FAO], 1985, GUID EXT TRAIN
   Fosu-Mensah B. Y., 2012, Environment Development and Sustainability, V14, P495, DOI 10.1007/s10668-012-9339-7
   Guug S.S., 2014, INT J INTERDISCIP EN, V8, P15, DOI [10.18848/2329-1621/CGP/v08i02/15-35, DOI 10.18848/2329-1621/CGP/V08I02/15-35]
   Gyasi EA, 2006, REPORTS MEMBERS STUD, DOI DOI 10.1098/rstb.2013.0089
   Harvey CA, 2014, PHILOS T R SOC B, V369, DOI 10.1098/rstb.2013.0089
   HUBERT P, 1987, J HYDROL, V95, P165, DOI 10.1016/0022-1694(87)90123-5
   Ibrahim B, 2011, PHYS CHARACTERISTICS
   Jerrold HZ, 1984, STAT ANAL
   Juana JS, 2013, J AGR SCI, V5, P122
   Kalungu J. W., 2013, Journal of Environment and Earth Science, V3, P129
   Kanlisi K.S., 2013, EUROPEAN SCI J, V9, P144
   Kemausuor F., 2011, Journal of Agricultural and Biological Science, V6, P26
   Kendall M., 1975, Rank Correlation Methods, V4th
   Kirsty GM, 2009, ADV GUARD CLIMATE CH, DOI DOI 10.1016/j.jhydrol.2007.12.022
   Lubes-Niel H., 1998, REV SCI EAU, V11, P383, DOI [10.7202/705313ar, DOI 10.7202/705313AR, DOI 10.1257/aer.99.3.1006]
   Ma ZM, 2008, J HYDROL, V352, P239, DOI 10.1016/j.jhydrol.2007.12.022
   MacCini S, 2009, AM ECON REV, V99, P1006, DOI 10.1257/aer.99.3.1006
   Maddison D, 2007, 4308 WORLD BANK, P21, DOI DOI 10.1016/j.gloenvcha.2011.11.002
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   McDowell JZ, 2012, GLOBAL ENVIRON CHANG, V22, P342, DOI 10.1016/j.gloenvcha.2011.11.002
   Ministry of Water Resources Works and Housing (MWRWH) Ghana, 2007, GHAN NAT WAT POL
   MoFA, 2011, AGR GHAN FACTS FIG 2
   MOFA (Ministry of Food and Agriculture Republic of Ghana), 2007, FOOD AGR SECT DEV PO
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Mu XM, 2007, HYDROL PROCESS, V21, P2124, DOI 10.1002/hyp.6391
   Nagayet O., 2005, FUTURE SMALL FARMS P, P355
   Nakuja T., 2012, African Journal of Agricultural Research, V7, P298
   Nyanga P. H., 2011, Journal of Sustainable Development, V4, P73
   Obeng F. K., 2014, International Journal of AgriScience, V4, P109
   Ofori-Sarpong E., 2001, West. Afr. J. Appl. Ecol, V2, P21
   Onoz B., 2003, Turkish Journal of Engineering and Environmental Sciences, V27, P247
   Ovuka M, 2000, GEOGR ANN A, V82A, P107, DOI 10.1111/j.0435-3676.2000.00116.x
   Pettitt A. N., 1979, Applied Statistics, V28, P126, DOI 10.2307/2346729
   Ringler C, 2011, RES BRIEF SERIES, DOI DOI 10.1016/j.jaridenv.2008.06.011
   Sanchez PA, 2005, SCIENCE, V307, P357, DOI 10.1126/science.1109057
   Slegers MFW, 2008, J ARID ENVIRON, V72, P2106, DOI 10.1016/j.jaridenv.2008.06.011
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   UNDP, 2010, GHAN COUNTR AN
   United Nations Framework Convention on Climate Change [UNFCCC], 2011, HIGHL CONTR NAIR WOR
   Ward AD, 1995, ENV HYDROLOGY, P37, DOI DOI 10.1007/s10113-013-0532-5
   Wittig R, 2007, ENVIRON SCI POLLUT R, V14, P182, DOI 10.1065/espr2007.02.388
   Zampaligré N, 2014, REG ENVIRON CHANGE, V14, P769, DOI 10.1007/s10113-013-0532-5
NR 63
TC 90
Z9 92
U1 1
U2 46
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2193-1801
J9 SPRINGERPLUS
JI SpringerPlus
PD JUN 22
PY 2016
VL 5
AR 830
DI 10.1186/s40064-016-2433-9
PG 38
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics
GA DP4OJ
UT WOS:000378475000007
PM 27386279
OA Green Published, gold
DA 2025-01-10
ER

PT C
AU De Soucy, RH
AF De Soucy, R. Haudry
BE PerezCabal, M
   Gutierrez, JP
   Cervantes, I
   Alcalde, MJ
TI Investing in the development of South American campesino camelid
   economies: the experience of the International Fund for Agricultural
   Development (IFAD)
SO FIBRE PRODUCTION IN SOUTH AMERICAN CAMELIDS AND OTHER FIBRE ANIMALS
LA English
DT Proceedings Paper
CT 5th European Symposium on South American Camelids / 1st European Meeting
   on Fibre Animals
CY OCT 06-08, 2010
CL Seville, SPAIN
SP Complutense Univ Madrid, Univ Seville, European Assoc Anim Product
DE development; camelid economy; campesino
AB The Andean region has three million domesticated South American camelids and one million in the wild, a valuable asset with underused potential for contributing to climate change adaptation, high-quality fine-fibre textiles, and the meat, leather and other industries. Camelid raising is unique in two respects: it is practised mainly at altitudes of 3,000 meters and above, in the fragile ecosystems where it evolved and to which it is perfectly adapted; and it is an asset of the poorest people living in this region. In short, this is essentially an activity of campesinos in the Andean highlands. In the past 20 years, the International Fund for Agricultural Development (IFAD) has invested in bringing together knowers and knowledge. Breeders, fibre sorters, artisans and microentrepreneurs linked to the camelid economy have exchanged and scaled up knowledge, with tangible results. IFAD has also cofinanced their enterprises and initiatives with support from national and local governments, businesses and other sources of cooperation. An estimated US$ 30 million has been invested in the sector in the past 15 years, generating an impact or incremental value of US$ 90 million in the pockets of producers. These are only the first steps in the process of developing the camelid economy and its contribution to mitigating climate change and combating rural poverty. In the four countries concerned, the sector could generate three times the current annual sales (US$ 300 million in the campesino sector and US$ 1,000 million if one includes the textile and garment industries and livestock sales). Such an increase will hinge on expanding incipient markets for meat (dried and fresh), leather manufactures and livestock by-products, as well as the textile market for vicuna fibre (guanaco fibre is still virtually unused). Knowledge exchanges need to be multiplied among local and international talents, because the thresholds for learning simple technologies and prerequisites to access solvent markets are beyond reach for many campesinos and artisans. This calls for cofinancing knowledge exchanges between subregions and countries, scaling up such knowledge to the majority, and selectively cofinancing the most promising and environmentally relevant initiatives to contribute positively to climate change (for instance, by substituting camelids for exotic livestock such as cattle and sheep in moist paramos or high steppe areas).
C1 Int Fund Agr Dev, I-00142 Rome, Italy.
RP De Soucy, RH (corresponding author), Int Fund Agr Dev, Via Paolo di Dono 44, I-00142 Rome, Italy.
EM r.haudry@ifad.org
NR 0
TC 2
Z9 2
U1 0
U2 5
PU WAGENINGEN ACAD PUBL
PI WAGENINGEN
PA POSTBUS 220, 6700 AE WAGENINGEN, NETHERLANDS
BN 978-90-8686-727-1; 978-90-8686-172-9
PY 2011
BP 195
EP 199
PG 5
WC Agriculture, Dairy & Animal Science; Veterinary Sciences
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture; Veterinary Sciences
GA BA4IX
UT WOS:000335817000025
DA 2025-01-10
ER

PT J
AU Raum, S
   Hossu, CA
   Lupp, G
   Pauleit, S
   Egerer, M
AF Raum, Susanne
   Hossu, Constantina-Alina
   Lupp, Gerd
   Pauleit, Stephan
   Egerer, Monika
TI Stakeholder exposure to and knowledge of tree pests and diseases and
   their management in urban areas
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE Tree health; Risk; Tree pathogens; Biosecurity; Resilience; Urban
   forests; Green infrastructure; Green space; Germany; Urban trees
ID NATURAL DISTURBANCE; PUBLIC PERCEPTIONS; FOREST; BEETLE; HEALTH; RISK;
   WILLINGNESS; BIOSECURITY; DIVERSITY; PATHOGENS
AB Urban trees and forests provide many benefits to the urban environment and are important for climate change adaptation. Yet, they are increasingly threatened by insect pests and diseases, hereafter tree pests/diseases. There is little evidence of the risk awareness and knowledge of different urban stakeholders of this growing threat, how they are affected by tree pests/diseases, and how they might respond to it. To fill this gap, we undertook an online survey of different key stakeholder groups associated with urban trees and forests in Germany. A majority of 75.8% of the 186 respondents consider urban tree pests/diseases a severe problem and 51.1 % reported high knowledge of tree pests/diseases. There was a lack of knowledge of certain reportable quarantine pests/diseases (e.g., canker stain of plane, emerald ash borer, Xylella) and pest/disease management options (e.g., manual treatment methods and tree diversification). Respondents were most affected by the horse chestnut leafminer (61.3 %), ash dieback (58.1 %) and oak processionary moth (50.0 %). The most widely used pest remedial measures were improvements of tree living conditions (60.8 %) and purchases of plants from certified or trusted local sources (59.7 %). Multiple correspondence analysis showed a significant association between levels of knowledge of tree pests/diseases and pest management responses (11.7 %). Our results suggest that future efforts to improve urban tree health should be enhanced and tailored to the different requirements of various stakeholder groups. The findings of this first comprehensive study with a purely urban focus will inform the development of future activities that prevent or reduce the spread of tree pests/diseases in urban areas. Data Availability: The survey respondents did not give permission for the full data to be accessed or used by third parties.
C1 [Raum, Susanne] Imperial Coll London, Ctr Environm Policy, London, England.
   [Raum, Susanne; Hossu, Constantina-Alina; Lupp, Gerd; Pauleit, Stephan] Tech Univ Munich, Chair Strateg Landscape Planning & Management, Munich, Germany.
   [Hossu, Constantina-Alina] Univ Bucharest, Ctr Environm Res & Impact Studies, Bucharest, Romania.
   [Egerer, Monika] Tech Univ Munich, Urban Prod Ecosyst Lab, Munich, Germany.
C3 Imperial College London; Technical University of Munich; University of
   Bucharest; Technical University of Munich
RP Raum, S (corresponding author), Imperial Coll London, Ctr Environm Policy, London, England.
EM susanne.raum@tum.de; alina.hossu@tum.de; gerd.lupp@tum.de;
   pauleit@tum.de; monika.egerer@tum.de
RI Pauleit, Stephan/ISV-4685-2023; Raum, Susanne/JSK-6900-2023
OI Raum, Susanne/0000-0003-3795-3836
FU European Union [101023713]; Alexander von Humboldt Foundation;
   EU-Horizon [101084628]; Horizon Europe - Pillar II [101084628] Funding
   Source: Horizon Europe - Pillar II; Marie Curie Actions (MSCA)
   [101023713] Funding Source: Marie Curie Actions (MSCA)
FX The study reported in this paper has received funding from the Eu-ropean
   Union's Horizon 2020 research and innovation programme under the Marie
   Sklodowska-Curie grant agreement NO. 101023713 for the first author. SR
   is also a member of the EU COST Action network "URBAN TREE
   GUARD-Safeguarding European urban trees and forests through improved
   biosecurity". AH acknowledges support by a grant from the Alexander von
   Humboldt Foundation and GL from the EU-Horizon project TRANS-lighthouses
   GA Number 101084628. The article reflects only the author's views, and
   the Agency is not responsible for the information it contains. The
   authors would like to thank the anonymous reviewers for their helpful
   comments and suggestions on earlier drafts of the manuscript. We also
   thank the networks/associa-tions for kindly promoting the survey, the
   survey participants for taking part in the survey, Ronja Franke for
   helping to prepare the online questionnaire and Lilly Eisermann for
   helping with data synthesis.
CR Annesi T, 2015, DREWNO, V58, P5, DOI 10.12841/wood.1644-3985.136.01
   Babbie E., 2013, The practice of social research
   BDSG, 2018, Bundesdatenschutzgesetz 2018
   BPB, 2021, Bevolkerungsstand
   Brasier CM, 2008, PLANT PATHOL, V57, P792, DOI 10.1111/j.1365-3059.2008.01886.x
   Britannica, 2023, Germany
   Brockerhoff Eckehard G., 2010, New Zealand Journal of Forestry Science, V40, pS117
   Chang WY, 2009, FOREST ECOL MANAG, V257, P1333, DOI 10.1016/j.foreco.2008.11.031
   Creswell JW, 2022, Research design: Qualitative, quantitative and mixed method approaches, V6th
   Czaja M, 2020, FORESTS, V11, DOI 10.3390/f11090932
   Dehnen-Schmutz K., 2010, Aspects of Applied Biology, P13
   Destatis, 2022, Bevolkerung in Deutschland
   Dillman D.A., 2017, Sage Research Methods
   Dziegielewska M, 2017, ECOL QUEST, V27, P25, DOI 10.12775/EQ.2017.025
   EPPO, 2023, EPPO's activities on plant quarantine
   EU, 2016, Plant Health Regulation 2016/2031 on protective measures against plant pests
   EU, 2019, COMM IMPL REG EU 201
   Fazit A.A., 2023, Tatsachen uber Deutschland
   Fielding N., 2017, SAGE HDB ONLINE RES
   Flannigan John, 2005, Arboricultural Journal, V28, P219
   Flint CG, 2006, FOREST ECOL MANAG, V227, P207, DOI 10.1016/j.foreco.2006.02.036
   FLL, 2006, Die ZTV Baumpflege
   Fuller L, 2016, ENVIRON SCI POLICY, V59, P18, DOI 10.1016/j.envsci.2016.02.007
   Green S, 2023, NEOBIOTA, V84, P9, DOI 10.3897/neobiota.84.95761
   Gupta Angela, 2010, New Zealand Journal of Forestry Science, V40, P123
   Gupta N, 2022, BIOL INVASIONS, V24, P123, DOI 10.1007/s10530-021-02631-3
   Gutsch M, 2019, URBAN FOR URBAN GREE, V41, P248, DOI 10.1016/j.ufug.2019.03.003
   Haack RA, 1997, J FOREST, V95, P11
   Haack RA, 2010, ANNU REV ENTOMOL, V55, P521, DOI 10.1146/annurev-ento-112408-085427
   Harper Richard W., 2017, Arboricultural Journal, V39, P162, DOI 10.1080/03071375.2017.1369774
   Hathaway J.M., 1981, Gen. Tech. Rep. Nc., V397
   Heimlich Joseph, 2008, Arboriculture & Urban Forestry, V34, P47
   Hitchmough J.D., 1997, LANDSCAPE RES, V22, P327
   Hossu C.A., 2019, Synerg. Trade-offs Mult. users. Ecosyst. Serv., V37
   Hurley BP, 2012, AGR FOREST ENTOMOL, V14, P306, DOI 10.1111/j.1461-9563.2012.00570.x
   Husson F., 2011, Exploratory Multivariate Analysis by Example Using R
   Jacobi W. R., 2011, Arboriculture & Urban Forestry, V37, P126
   Kendal D, 2014, URBAN FOR URBAN GREE, V13, P411, DOI 10.1016/j.ufug.2014.04.004
   Klobucar B, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12145589
   Koch FH, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0102105
   Le Roux Brigitte, 2010, Multiple Correspondence Analysis
   Lehtijärvi A, 2018, FOREST PATHOL, V48, DOI 10.1111/efp.12375
   Leiner D. J., 2019, SoSci survey (version 2.5. 00-i)computer software
   Liebhold AM, 2012, FRONT ECOL ENVIRON, V10, P135, DOI 10.1890/110198
   Lupp G., 2017, Schweiz. Z. F. uR. Forstwes., V68, P261
   Marzano M, 2020, FORESTS, V11, DOI 10.3390/f11060617
   Marzano M, 2020, FORESTS, V11, DOI 10.3390/f11020199
   Marzano M, 2019, FORESTRY, V92, P554, DOI 10.1093/forestry/cpz022
   Marzano M, 2016, FOREST POLICY ECON, V70, P164, DOI 10.1016/j.forpol.2016.06.030
   Marzano M, 2015, BIOL INVASIONS, V17, P1961, DOI 10.1007/s10530-015-0850-2
   Mathiesen Karl., 2014, GUARDIAN
   McFarlane BL, 2006, BIOL CONSERV, V130, P340, DOI 10.1016/j.biocon.2005.12.029
   Mell I, 2017, INT PLAN STUD, V22, P333, DOI 10.1080/13563475.2017.1291334
   Molnar J.J., 2003, Bull, V649
   Müller M, 2009, BIOL CONSERV, V142, P375, DOI 10.1016/j.biocon.2008.10.037
   Mullaney J, 2015, LANDSCAPE URBAN PLAN, V134, P157, DOI 10.1016/j.landurbplan.2014.10.013
   Munchner Wochen Anzeiger, 2012, Feldkirchen - Bedrohung aus Asien
   Munchner Wochen Anzeiger, 2016, Der Asiatische Laubholzbockkafer
   Orlova-Bienkowskaja MJ, 2020, ANN FOREST SCI, V77, DOI 10.1007/s13595-020-0930-z
   Petter F, 2023, FORESTS, V14, DOI 10.3390/f14071461
   Porth EF, 2015, HUM ECOL, V43, P669, DOI 10.1007/s10745-015-9788-3
   Potter C, 2017, FOREST POLICY ECON, V79, P61, DOI 10.1016/j.forpol.2016.06.024
   Quarles W., 2008, IPM Practitioner, V30, P1
   Quine CP, 2011, PHILOS T R SOC B, V366, P2010, DOI 10.1098/rstb.2010.0397
   Ramsetty A, 2020, J AM MED INFORM ASSN, V27, P1147, DOI 10.1093/jamia/ocaa078
   Ramsfield TD, 2016, FORESTRY, V89, P245, DOI 10.1093/forestry/cpw018
   Raum S, 2023, URBAN ECOSYST, V26, P587, DOI 10.1007/s11252-022-01317-5
   Raum S, 2018, ECOSYST SERV, V29, P170, DOI 10.1016/j.ecoser.2018.01.001
   Reed MS, 2015, J INTEGR ENVIRON SCI, V12, P15, DOI 10.1080/1943815X.2014.975723
   Roman LA, 2021, AMBIO, V50, P615, DOI 10.1007/s13280-020-01396-8
   Roy S, 2012, URBAN FOR URBAN GREE, V11, P351, DOI 10.1016/j.ufug.2012.06.006
   Savin-Baden M., 2023, Qualitative research: The essential guide to theory and practice
   Sheremet O, 2017, J AGR ECON, V68, P781, DOI 10.1111/1477-9552.12210
   Sjöman H, 2012, URBAN FOR URBAN GREE, V11, P31, DOI 10.1016/j.ufug.2011.09.004
   Slawson DD, 2020, INSECTS, V11, DOI 10.3390/insects11090550
   Stenlid J, 2011, FORESTS, V2, P486, DOI 10.3390/f2020486
   Trkulja V, 2022, PLANT PATHOLOGY J, V38, P551, DOI 10.5423/PPJ.RW.09.2022.0127
   Turner J. A., 2004, New Zealand Journal of Forestry Science, V34, P324
   Tyrvainen L., 2005, URBAN FORESTS TREES, P81
   Urquhart J, 2017, ENVIRON SCI POLICY, V77, P172, DOI 10.1016/j.envsci.2017.08.020
   Urquhart J, 2017, BIOL INVASIONS, V19, P2567, DOI 10.1007/s10530-017-1467-4
   Wang CC, 2023, SUSTAIN CITIES SOC, V93, DOI 10.1016/j.scs.2023.104531
   Webber Joan, 2010, New Zealand Journal of Forestry Science, V40, pS45
   Williams GM, 2023, ANNU REV PHYTOPATHOL, V61, P377, DOI 10.1146/annurev-phyto-021722-024626
NR 84
TC 1
Z9 1
U1 5
U2 5
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 1618-8667
EI 1610-8167
J9 URBAN FOR URBAN GREE
JI Urban For. Urban Green.
PD OCT
PY 2024
VL 100
AR 128456
DI 10.1016/j.ufug.2024.128456
EA AUG 2024
PG 12
WC Plant Sciences; Environmental Studies; Forestry; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Plant Sciences; Environmental Sciences & Ecology; Forestry; Urban
   Studies
GA C7L2S
UT WOS:001291141200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Zhou, YK
   Liu, JY
AF Zhou, Yuekuan
   Liu, Jiangyang
TI Advances in emerging digital technologies for energy efficiency and
   energy integration in smart cities
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Energy digitalization; Internet of energy; Machine learning; Digital
   twin; Energy flexibility; Energy resilience
ID TOTAL HEAT-RECOVERY; ARTIFICIAL NEURAL-NETWORK; RENEWABLE ENERGY;
   ELECTRIC VEHICLE; HIERARCHICAL CONTROL; LIQUID DESICCANT; PUMP SYSTEM;
   OPTIMIZATION; MANAGEMENT; DESIGN
AB Advances and fast development in emerging digital technologies trigger the next generation revolution in energy areas and smart cities, while roles and mechanisms of digital technologies for smart and sustainable transition is unclear. Furthermore, energy flexibility enhancement in intermittent renewable -stochastic demand power management and survival capability in minimizing frequency of power outrage are still not clear, when suffering from climate change and extreme events with emerging digital technologies. In this study, advances in emerging digital technologies have been systematically and comprehensively reviewed, in terms of current development status and mechanisms for energy efficiency and energy integration in energy -efficient systems. Afterwards, roles of energy digitalization technologies are provided for high -efficiency, low -carbon and intelligent building energy systems, including artificial intelligence for dynamic performance predictions, advanced model predictive controls and optimisations of nonlinear systems (e.g., PVs, heat pumps, heat recovery systems and multi -energy storages). Furthermore, digital twin -based building energy digitalization technologies are applied for 3D modeling, monitoring, real-time visualization and virtual reality interaction. Frontier multi -agent based distributed energy systems are comprehensively proposed with multi -agent energy management, including REbattery-building-EV, RE -building -hydrogen vehicles, and both centralised and distributed energy management systems. Considering the multi -energy system capability for power management (intermittent renewable energy and energy demands) and survival capability when suffering from high -impact and low -probability events, both energy flexibility and energy resilience with energy digitalization technologies are interconnected, for climate change adaption and internet of energy. This study provides a systematic and comprehensive review on emerging digital technologies for energy efficiency and energy integration in smart cities, providing guidelines on sustainable and smart transitions with multi -agent based distributed energy management and energy digitalization technologies.
C1 [Zhou, Yuekuan; Liu, Jiangyang] Hong Kong Univ Sci & Technol Guangzhou, Sustainable Energy & Environm Thrust, Funct Hub, Guangzhou 511400, Guangdong, Peoples R China.
   [Zhou, Yuekuan] Hong Kong Univ Sci & Technol, Dept Mech & Aerosp Engn, Clear Water Bay, Hong Kong, Peoples R China.
   [Zhou, Yuekuan] HKUST Shenzhen Hong Kong Collaborat Innovat Res In, Hong Kong, Peoples R China.
   [Zhou, Yuekuan] Hong Kong Univ Sci & Technol, Div Emerging Interdisciplinary Areas, Clear Water Bay, Hong Kong, Peoples R China.
C3 Hong Kong University of Science & Technology (Guangzhou); Hong Kong
   University of Science & Technology; Hong Kong University of Science &
   Technology
RP Zhou, YK (corresponding author), Hong Kong Univ Sci & Technol Guangzhou, Sustainable Energy & Environm Thrust, Funct Hub, Guangzhou 511400, Guangdong, Peoples R China.
EM yuekuanzhou@hkust-gz.edu.cn
RI Zhou, Yuekuan/ABE-4194-2020
FU National Development and Reform Commission [2023-Dual Carbon-3]; Natural
   Science Foundation Project (General Project)-Guangdong Basic and Applied
   Basic Research Fund [2414050003253]; Regional joint fund youth fund
   project [2022A1515110364, P00038-1002]; Guangdong Basic and Applied
   Basic Research Foundation [2023A04J1035, P00121-1003]; Joint Funding of
   Institutes and Enterprises in 2023 [2023A03J0104, P00054-1003,1004];
   Green Tech Fund in the Hong Kong Special Administrative Region
   'Developing low-cost PEM electrolysis at scale by optimizing transport
   components and electrode interfaces' [GTF202220034]; HKUST
   (GZ)-enterprise cooperation project [R00017-2001]; HKUST (GZ)-enterprise
   cooperation project 'Optimization Design of Proton Exchange Membrane
   Fuel Cell Plate' [R00072-2001]; HKUST (GZ)-enterprise cooperation
   project 'Next -generation radiant cooling for built environment'
   [R00079-2001]; Hong Kong University of Science and Technology
   (Guangzhou) startup grant [G0101000059]; Project of Hetao Shenzhen-Hong
   Kong Science and Technology Innovation Cooperation Zone
   [HZQB-KCZYB-2020083]
FX This work was supported by National Development and Reform Commission
   (2023-Dual Carbon-3) , Natural Science Foundation Project (General
   Project)-Guangdong Basic and Applied Basic Research Fund (2414050003253)
   , Regional joint fund youth fund project (2022A1515110364, P00038-1002)
   , Guangdong Basic and Applied Basic Research Foundation 2023
   (2023A04J1035, P00121-1003) , Joint Funding of Institutes and
   Enterprises in 2023 (2023A03J0104, P00054-1003,1004) , Green Tech Fund
   in the Hong Kong Special Administrative Region 'Developing low-cost PEM
   electrolysis at scale by optimizing transport components and electrode
   interfaces' (GTF202220034) . HKUST (GZ)-enterprise cooperation project
   (R00017-2001) , HKUST (GZ)-enterprise cooperation project 'Optimization
   Design of Proton Ex-change Membrane Fuel Cell Plate' (R00072-2001) ,
   HKUST (GZ)-enterprise cooperation project 'Next -generation radiant
   cooling for built environment' (R00079-2001) . This research is
   supported by The Hong Kong University of Science and Technology
   (Guangzhou) startup grant (G0101000059) . This work was also supported
   in part by the Project of Hetao Shenzhen-Hong Kong Science and
   Technology Innovation Cooperation Zone (HZQB-KCZYB-2020083) .
CR Abadi MK, 2023, ENERGY, V273, DOI 10.1016/j.energy.2023.127239
   Abomazid AM, 2022, IEEE T SUSTAIN ENERG, V13, P1457, DOI 10.1109/TSTE.2022.3161891
   Afrasiabi M, 2019, ENERGY, V186, DOI 10.1016/j.energy.2019.115873
   Agostinelli S, 2021, ENERGIES, V14, DOI 10.3390/en14082338
   Ahl A, 2020, RENEW SUST ENERG REV, V117, DOI 10.1016/j.rser.2019.109488
   Ahmad T, 2018, SUSTAIN CITIES SOC, V39, P401, DOI 10.1016/j.scs.2018.03.002
   Ahmadisedigh H, 2019, APPL ENERG, V253, DOI 10.1016/j.apenergy.2019.113495
   Al-Yasiri Q, 2023, ENERG BUILDINGS, V279, DOI 10.1016/j.enbuild.2022.112680
   Alassaad F, 2023, BUILD ENVIRON, V229, DOI 10.1016/j.buildenv.2022.109915
   Albogamy FR, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14031792
   Alghamdi NS, 2021, CMC-COMPUT MATER CON, V66, P2509, DOI 10.32604/cmc.2021.014180
   Allouhi A, 2023, ENERGY REP, V9, P3305, DOI 10.1016/j.egyr.2023.02.005
   Allouhi H, 2022, ENERG CONVERS MANAGE, V270, DOI 10.1016/j.enconman.2022.116261
   Argyroudis SA, 2022, CLIM RISK MANAG, V35, DOI 10.1016/j.crm.2021.100387
   Ayele G, 2020, Exploiting the synergies from coupled electricity and heat distribution networks: modelling, simulation and optimization based on an extended energy hub approach
   Ayele GT, 2021, ENERG CONVERS MANAGE, V243, DOI 10.1016/j.enconman.2021.114430
   Azeroual M, 2020, WIND ENG, V44, P661, DOI 10.1177/0309524X19862755
   Babaei M, 2020, J ENERGY STORAGE, V28, DOI 10.1016/j.est.2020.101221
   Badami M, 2019, ENERGY, V173, P400, DOI 10.1016/j.energy.2019.02.007
   Bai HY, 2022, RENEW SUST ENERG REV, V162, DOI 10.1016/j.rser.2022.112417
   Barone G, 2020, RENEW ENERG, V159, P1165, DOI 10.1016/j.renene.2020.05.101
   Bedi P., 2022, AI and IoT for Smart City Applications, P115, DOI [10.1007/978-981-16-7498-3_8, DOI 10.1007/978-981-16-7498-3_8]
   Ben Arab M, 2023, APPL ENERG, V335, DOI 10.1016/j.apenergy.2023.120767
   Bre F, 2023, APPL ENERG, V336, DOI 10.1016/j.apenergy.2023.120806
   Brusokas Jonas, 2021, e-Energy '21: Proceedings of the Twelfth International Conference on Future Energy Systems, P160, DOI 10.1145/3447555.3464866
   Buonomano A, 2019, APPL ENERG, V245, P31, DOI 10.1016/j.apenergy.2019.03.206
   Calautit K, 2023, ENERG CONVERS MAN-X, V20, DOI 10.1016/j.ecmx.2023.100457
   Calfa C, 2023, SCI TECHNOL BUILT EN, V29, P1011, DOI 10.1080/23744731.2023.2261810
   Calise F, 2020, RENEW ENERG, V160, P633, DOI 10.1016/j.renene.2020.06.075
   Cao SL, 2016, ENERG CONVERS MANAGE, V123, P153, DOI 10.1016/j.enconman.2016.06.033
   Cao SL, 2015, APPL ENERG, V158, P568, DOI 10.1016/j.apenergy.2015.08.009
   Ceusters G, 2021, APPL ENERG, V303, DOI 10.1016/j.apenergy.2021.117634
   Chadly A, 2022, ENERGY, V247, DOI 10.1016/j.energy.2022.123466
   Chae S, 2023, ENERGY REP, V10, P460, DOI 10.1016/j.egyr.2023.06.051
   Chakir A, 2022, ENERGY REP, V8, P383, DOI 10.1016/j.egyr.2022.07.018
   Chen LQ, 2023, ENERGY, V284, DOI 10.1016/j.energy.2023.129228
   Chen TY, 2022, IEEE T SMART GRID, V13, P715, DOI 10.1109/TSG.2021.3124465
   Chen X, 2023, GEOTHERMICS, V111, DOI 10.1016/j.geothermics.2023.102713
   Chen Y, 2023, J BUILD ENG, V77, DOI 10.1016/j.jobe.2023.107442
   Chen ZD, 2023, APPL ENERG, V341, DOI 10.1016/j.apenergy.2023.121125
   Cho HJ, 2023, APPL THERM ENG, V231, DOI 10.1016/j.applthermaleng.2023.120989
   Cioccolanti L, 2022, ENERG CONVERS MANAGE, V269, DOI 10.1016/j.enconman.2022.116159
   Comodi G, 2019, APPL ENERG, V256, DOI 10.1016/j.apenergy.2019.113901
   Coskun A, 2023, J THERM ANAL CALORIM, V148, P5625, DOI 10.1007/s10973-023-12122-3
   Dan ZH, 2024, ENERGY, V299, DOI 10.1016/j.energy.2024.131469
   de Araújo LR, 2022, ENERG CONVERS MANAGE, V271, DOI 10.1016/j.enconman.2022.116275
   Dehkordi BS, 2022, SUSTAIN ENERGY TECHN, V52, DOI 10.1016/j.seta.2022.102112
   Di Giorgio P, 2022, APPL ENERG, V315, DOI 10.1016/j.apenergy.2022.118935
   Di Silvestre ML, 2018, RENEW SUST ENERG REV, V93, P483, DOI 10.1016/j.rser.2018.05.068
   de Garayo SD, 2022, APPL THERM ENG, V204, DOI 10.1016/j.applthermaleng.2021.117832
   Dileep G, 2020, RENEW ENERG, V146, P2589, DOI 10.1016/j.renene.2019.08.092
   Dong SH, 2023, SUSTAIN CITIES SOC, V97, DOI 10.1016/j.scs.2023.104758
   Dreher A, 2022, ENERG CONVERS MANAGE, V258, DOI 10.1016/j.enconman.2022.115401
   Du YJ, 2024, ENVIRON TECHNOL, V45, P4467, DOI 10.1080/09593330.2023.2254487
   Ekici B, 2022, ENERGIES, V15, DOI 10.3390/en15020660
   El-Zonkoly A, 2023, ELECTR POW SYST RES, V223, DOI 10.1016/j.epsr.2023.109708
   Embrandiri S, 2018, 2018 INT C CIRC SYST, P1, DOI [10.1109/ICCSDET.2018.8821206, DOI 10.1109/ICCSDET.2018.8821206]
   Esen H, 2008, RENEW ENERG, V33, P1814, DOI 10.1016/j.renene.2007.09.025
   Esen H, 2008, ENERG BUILDINGS, V40, P1074, DOI 10.1016/j.enbuild.2007.10.002
   Essayeh C, 2023, APPL ENERG, V336, DOI 10.1016/j.apenergy.2023.120846
   Evens M, 2022, APPL THERM ENG, V216, DOI 10.1016/j.applthermaleng.2022.119154
   Fan C, 2018, ENERG BUILDINGS, V159, P296, DOI 10.1016/j.enbuild.2017.11.008
   Fang XH, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103163
   Farouk N, 2022, J BUILD ENG, V50, DOI 10.1016/j.jobe.2022.104073
   Filis V, 2021, ENERG BUILDINGS, V234, DOI 10.1016/j.enbuild.2020.110689
   Fu HX, 2017, APPL THERM ENG, V118, P345, DOI 10.1016/j.applthermaleng.2017.03.006
   Gamage D, 2022, 2022 7TH IEEE WORKSHOP ON THE ELECTRONIC GRID (EGRID), DOI 10.1109/eGRID57376.2022.9990026
   Gang WJ, 2014, APPL ENERG, V136, P1138, DOI 10.1016/j.apenergy.2014.04.005
   Goitia-Zabaleta N, 2023, APPL ENERG, V348, DOI 10.1016/j.apenergy.2023.121552
   Goldanlou AS, 2020, J BUILD ENG, V32, DOI 10.1016/j.jobe.2020.101545
   Guo YB, 2018, APPL ENERG, V221, P16, DOI 10.1016/j.apenergy.2018.03.125
   Guven AF, 2022, ENERGY, V253, DOI 10.1016/j.energy.2022.124089
   Hai T, 2023, SUSTAIN ENERGY TECHN, V55, DOI 10.1016/j.seta.2022.102895
   Hai T, 2022, SUSTAIN ENERGY TECHN, V53, DOI 10.1016/j.seta.2022.102531
   Halilovic S, 2022, ENERGY, V238, DOI 10.1016/j.energy.2021.121607
   Hamid K, 2022, ENERGY, V238, DOI 10.1016/j.energy.2021.121819
   Han D, 2020, ENERGY, V199, DOI 10.1016/j.energy.2020.117417
   Hassan Q, 2023, INT J HYDROGEN ENERG, V48, P30247, DOI 10.1016/j.ijhydene.2023.03.413
   He F, 2023, J ENERGY STORAGE, V58, DOI 10.1016/j.est.2022.106359
   Hervás-Zaragoza J, 2022, RENEW ENERG, V199, P308, DOI 10.1016/j.renene.2022.08.132
   Hosseini SA, 2024, IEEE T IND INFORM, V20, P2223, DOI 10.1109/TII.2023.3288883
   Hu JF, 2021, RENEW SUST ENERG REV, V136, DOI 10.1016/j.rser.2020.110422
   Hu YF, 2023, THERM SCI ENG PROG, V39, DOI 10.1016/j.tsep.2023.101726
   Huang CY, 2023, ENERG CONVERS MANAGE, V287, DOI 10.1016/j.enconman.2023.117032
   Huang KL, 2023, ENERG BUILDINGS, V284, DOI 10.1016/j.enbuild.2023.112875
   Huang SF, 2023, APPL THERM ENG, V234, DOI 10.1016/j.applthermaleng.2023.121163
   Huang WH, 2022, SUSTAIN COMPUT-INFOR, V36, DOI 10.1016/j.suscom.2022.100781
   Huang WJ, 2022, IEEE T POWER SYST, V37, P2906, DOI 10.1109/TPWRS.2021.3123074
   Izadi A, 2022, ENERG CONVERS MANAGE, V260, DOI 10.1016/j.enconman.2022.115593
   Jain A., Digital twins for efficient modeling and control of buildings an integrated solution with scada systems
   Jamali MB, 2023, SUSTAIN CITIES SOC, V95, DOI 10.1016/j.scs.2023.104598
   Janota L, 2023, ENERGY REP, V10, P1211, DOI 10.1016/j.egyr.2023.07.057
   Javadi MS, 2022, SUSTAIN CITIES SOC, V79, DOI 10.1016/j.scs.2022.103747
   Jeyaprabha SB, 2015, ENERG BUILDINGS, V96, P40, DOI 10.1016/j.enbuild.2015.03.012
   Jia CX, 2021, ALEX ENG J, V60, P337, DOI 10.1016/j.aej.2020.08.019
   Jia MD, 2019, AUTOMAT CONSTR, V101, P111, DOI 10.1016/j.autcon.2019.01.023
   Kaif AMAD, 2024, ENERGY REP, V11, P261, DOI 10.1016/j.egyr.2023.11.061
   Kaitouni SI, 2023, SOL ENERGY, V263, DOI 10.1016/j.solener.2023.111959
   Kalbasi R, 2022, SUSTAIN ENERGY TECHN, V50, DOI 10.1016/j.seta.2021.101848
   Kashanizadeh B, 2022, J ENERGY STORAGE, V52, DOI 10.1016/j.est.2022.104825
   Khan M, 2022, J BUILD ENG, V53, DOI 10.1016/j.jobe.2022.104506
   Khan MW, 2019, SUSTAIN CITIES SOC, V44, P855, DOI 10.1016/j.scs.2018.11.009
   Kim J, 2023, SOL ENERGY, V262, DOI 10.1016/j.solener.2023.111834
   Kim S, 2023, ENERG BUILDINGS, V286, DOI 10.1016/j.enbuild.2023.112978
   Kolahan A, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103316
   Komerska A., 2023, Building Energy Flexibility and Demand Management, P145, DOI [10.1016/B978-0-323-99588-7.00005-5, DOI 10.1016/B978-0-323-99588-7.00005-5]
   Kutty AA, 2023, CITIES, V137, DOI 10.1016/j.cities.2023.104293
   Kutty AA, 2022, J CLEAN PROD, V378, DOI 10.1016/j.jclepro.2022.134203
   Lee D, 2019, ENERGIES, V12, DOI 10.3390/en12173247
   Lee SW, 2023, APPL ENERG, V333, DOI 10.1016/j.apenergy.2022.120572
   Lei Q, 2022, APPL THERM ENG, V215, DOI 10.1016/j.applthermaleng.2022.118524
   Lei YT, 2022, ENERG ECON, V115, DOI 10.1016/j.eneco.2022.106375
   Levin T, 2023, NAT ENERGY, V8, P1199, DOI 10.1038/s41560-023-01340-6
   Li B, 2019, J BUILD ENG, V21, P343, DOI 10.1016/j.jobe.2018.10.025
   Li H, 2020, RENEW ENERG, V146, P25, DOI 10.1016/j.renene.2019.06.058
   Li JY, 2023, ENERGY AI, V11, DOI 10.1016/j.egyai.2022.100208
   Li SJ, 2022, ENERG BUILDINGS, V270, DOI 10.1016/j.enbuild.2022.112255
   Li SY, 2023, SEP PURIF TECHNOL, V324, DOI 10.1016/j.seppur.2023.124435
   Li T, 2023, ENERG BUILDINGS, V299, DOI 10.1016/j.enbuild.2023.113601
   Li ZM, 2022, IEEE T SMART GRID, V13, P213, DOI 10.1109/TSG.2021.3119972
   Li ZT, 2018, IEEE T IND INFORM, V14, P3690, DOI 10.1109/TII.2017.2786307
   Liang CJY, 2023, APPL THERM ENG, V235, DOI 10.1016/j.applthermaleng.2023.121433
   Liu H, 2020, IET SMART GRID, V3, P479, DOI 10.1049/iet-stg.2019.0268
   Liu J, 2023, ENERG CONVERS MANAGE, V298, DOI 10.1016/j.enconman.2023.117768
   Liu J, 2022, APPL ENERG, V321, DOI 10.1016/j.apenergy.2022.119312
   Liu J, 2021, APPL ENERG, V298, DOI 10.1016/j.apenergy.2021.117206
   Liu J, 2021, APPL ENERG, V290, DOI 10.1016/j.apenergy.2021.116733
   Liu J, 2021, APPL ENERG, V281, DOI 10.1016/j.apenergy.2020.116038
   Liu JY, 2022, RENEW ENERG, V191, P625, DOI 10.1016/j.renene.2022.04.082
   Liu JY, 2022, J ENERGY STORAGE, V46, DOI 10.1016/j.est.2021.103877
   Liu JH, 2021, INT J HYDROGEN ENERG, V46, P28855, DOI 10.1016/j.ijhydene.2020.11.229
   Liu JM, 2024, COMPUT OPER RES, V163, DOI 10.1016/j.cor.2023.106513
   Liu SL, 2023, ENERGY, V263, DOI 10.1016/j.energy.2022.125942
   Liu XL, 2023, APPL ENERG, V347, DOI 10.1016/j.apenergy.2023.121435
   Liu YF, 2023, J BUILD ENG, V79, DOI 10.1016/j.jobe.2023.107949
   Liu Z, 2019, ELECTRONICS-SWITZ, V8, DOI 10.3390/electronics8070724
   Liu ZG, 2023, ENERGY, V263, DOI 10.1016/j.energy.2022.126082
   Liu ZX, 2023, ENERG BUILDINGS, V297, DOI 10.1016/j.enbuild.2023.113436
   Long JB, 2023, ENERG BUILDINGS, V298, DOI 10.1016/j.enbuild.2023.113594
   Lucchino EC, 2023, ENERG BUILDINGS, V285, DOI 10.1016/j.enbuild.2023.112881
   Luo LL, 2023, ENERGY, V282, DOI 10.1016/j.energy.2023.128220
   Luo LL, 2022, J BUILD ENG, V54, DOI 10.1016/j.jobe.2022.104613
   Luo XJ, 2020, SUSTAIN CITIES SOC, V61, DOI 10.1016/j.scs.2020.102283
   Lv ZH, 2023, APPL ENERG, V338, DOI 10.1016/j.apenergy.2023.120907
   Lydon GP, 2019, ENERG BUILDINGS, V202, DOI 10.1016/j.enbuild.2019.07.015
   Lyu N, 2023, APPL THERM ENG, V235, DOI 10.1016/j.applthermaleng.2023.121430
   Ma GY, 2023, ENERG BUILDINGS, V291, DOI 10.1016/j.enbuild.2023.113104
   Ma N, 2023, APPL ENERG, V332, DOI 10.1016/j.apenergy.2022.120443
   Ma Yicheng, 2023, Chemosphere, V338, P139453, DOI 10.1016/j.chemosphere.2023.139453
   Manfren M, 2023, ENERGY AI, V14, DOI 10.1016/j.egyai.2023.100304
   Manni M, 2023, BUILD ENVIRON, V246, DOI 10.1016/j.buildenv.2023.110946
   Mansouri SA, 2022, ENERGY, V245, DOI 10.1016/j.energy.2022.123228
   Martin-Chivelet N, 2022, ENERG BUILDINGS, V262, DOI 10.1016/j.enbuild.2022.111998
   Martinez A, 2022, APPL ENERG, V309, DOI 10.1016/j.apenergy.2021.118443
   Maurer B, 2023, BUILD ENVIRON, V245, DOI 10.1016/j.buildenv.2023.110922
   Megaptche CAM, 2023, ENERG CONVERS MANAGE, V291, DOI 10.1016/j.enconman.2023.117245
   Mehmood S, 2023, J ENERGY STORAGE, V72, DOI 10.1016/j.est.2023.108377
   Mehrjerdi H, 2019, INT J HYDROGEN ENERG, V44, P11574, DOI 10.1016/j.ijhydene.2019.03.158
   Mehrjerdi H, 2019, ENERGY, V168, P919, DOI 10.1016/j.energy.2018.11.131
   Merabet A, 2022, ENERG CONVERS MANAGE, V252, DOI 10.1016/j.enconman.2021.115116
   Mesaric P, 2015, ENERG BUILDINGS, V108, P1, DOI 10.1016/j.enbuild.2015.09.001
   Miao Z, 2023, FRONT ENERGY RES, V11, DOI 10.3389/fenrg.2023.1142243
   Mohamed MA, 2020, ENERGY, V208, DOI 10.1016/j.energy.2020.118306
   Moniruzzaman M, 2023, INT J ELEC POWER, V151, DOI 10.1016/j.ijepes.2023.109111
   Nazir K, 2023, J BUILD ENG, V68, DOI 10.1016/j.jobe.2023.106115
   Nezhad MM, 2024, RENEW SUST ENERG REV, V191, DOI 10.1016/j.rser.2023.114065
   Ning ZZ, 2023, J ENERGY STORAGE, V64, DOI 10.1016/j.est.2023.107114
   Niveditha N, 2022, APPL ENERG, V324, DOI 10.1016/j.apenergy.2022.119713
   Noye S, 2022, RENEW SUST ENERG REV, V153, DOI 10.1016/j.rser.2021.111685
   Nykyri M, 2022, ENERGY, V253, DOI 10.1016/j.energy.2022.124180
   Oldenbroek V, 2021, ENERG CONVERS MAN-X, V9, DOI 10.1016/j.ecmx.2021.100077
   Onile AE, 2021, ENERGY REP, V7, P997, DOI 10.1016/j.egyr.2021.01.090
   Pan D, 2023, J CLEAN PROD, V416, DOI 10.1016/j.jclepro.2023.137921
   Pang ZH, 2020, RENEW ENERG, V156, P279, DOI 10.1016/j.renene.2020.04.042
   Passos LAD, 2023, ENERG CONVERS MANAGE, V276, DOI 10.1016/j.enconman.2022.116573
   Pekdogan T, 2021, J BUILD ENG, V35, DOI 10.1016/j.jobe.2020.102009
   Ping X, 2020, SUSTAIN ENERGY TECHN, V42, DOI 10.1016/j.seta.2020.100898
   Polo J, 2022, ENERGIES, V15, DOI 10.3390/en15114173
   Puttige AR, 2021, ENERGIES, V14, DOI 10.3390/en14061750
   Qin L, 2023, ENERGY, V265, DOI 10.1016/j.energy.2022.126332
   Radhakrishnan BM, 2016, ENERGY, V103, P192, DOI 10.1016/j.energy.2016.02.117
   Rai V, 2016, NAT CLIM CHANGE, V6, P556, DOI 10.1038/NCLIMATE2967
   Razipour R, 2019, J ENERGY STORAGE, V22, P144, DOI 10.1016/j.est.2019.02.001
   Reynolds J, 2018, ENERGY, V151, P729, DOI 10.1016/j.energy.2018.03.113
   Ribé O, 2019, APPL THERM ENG, V149, P854, DOI 10.1016/j.applthermaleng.2018.12.076
   Robledo CB, 2018, APPL ENERG, V215, P615, DOI 10.1016/j.apenergy.2018.02.038
   Roudbari A, 2021, SUSTAIN ENERGY GRIDS, V28, DOI 10.1016/j.segan.2021.100547
   Royo PM, 2021, IEEE ACCESS, V9, P77742, DOI 10.1109/ACCESS.2021.3081932
   Ruan YJ, 2023, J BUILD ENG, V78, DOI 10.1016/j.jobe.2023.107657
   Samadi E, 2020, INT J ELEC POWER, V122, DOI 10.1016/j.ijepes.2020.106211
   Saravi VS, 2024, SUSTAIN CITIES SOC, V100, DOI 10.1016/j.scs.2023.105039
   Saurbayeva A, 2023, J BUILD ENG, V64, DOI 10.1016/j.jobe.2022.105603
   Savolainen R, 2022, ENERGY, V243, DOI 10.1016/j.energy.2021.123046
   Seker UE, 2023, RENEW ENERG, V204, P372, DOI 10.1016/j.renene.2023.01.025
   Selvaraj R, 2023, SUSTAIN ENERGY TECHN, V56, DOI 10.1016/j.seta.2023.103090
   Serrano-Luján L, 2022, APPL ENERG, V315, DOI 10.1016/j.apenergy.2022.119015
   Shang S, 2017, APPL ENERG, V207, P613, DOI 10.1016/j.apenergy.2017.05.169
   Shao ZT, 2023, APPL ENERG, V334, DOI 10.1016/j.apenergy.2023.120682
   Shen YL, 2023, ENERG BUILDINGS, V281, DOI 10.1016/j.enbuild.2022.112746
   Shin WG, 2022, ENERGIES, V15, DOI 10.3390/en15072589
   Singh S, 2020, SUSTAIN CITIES SOC, V63, DOI 10.1016/j.scs.2020.102364
   Singh SK, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103364
   Song AY, 2023, J CLEAN PROD, V415, DOI 10.1016/j.jclepro.2023.137797
   Song AY, 2023, RENEW ENERG, V212, P1020, DOI 10.1016/j.renene.2023.05.050
   Spudys P, 2023, ENERG BUILDINGS, V290, DOI 10.1016/j.enbuild.2023.113106
   Srithapon C, 2023, APPL ENERG, V347, DOI 10.1016/j.apenergy.2023.121500
   Stennikov V, 2022, COMPUTATION, V10, DOI 10.3390/computation10120222
   Stennikov V, 2022, APPL ENERG, V309, DOI 10.1016/j.apenergy.2021.118487
   Svetozarevic B, 2019, NAT ENERGY, V4, P671, DOI 10.1038/s41560-019-0424-0
   Taheri B, 2023, SUSTAIN CITIES SOC, V95, DOI 10.1016/j.scs.2023.104594
   Tamer T, 2022, RENEW SUST ENERG REV, V162, DOI 10.1016/j.rser.2022.112396
   Tan Y, 2022, ENERG BUILDINGS, V270, DOI 10.1016/j.enbuild.2022.112271
   Tao ZM, 2021, RENEW SUST ENERG REV, V136, DOI 10.1016/j.rser.2020.110405
   Tariq R, 2023, INT COMMUN HEAT MASS, V140, DOI 10.1016/j.icheatmasstransfer.2022.106538
   Taser A, 2023, SOL ENERGY, V251, P171, DOI 10.1016/j.solener.2022.12.039
   Tian XY, 2023, ENERGY, V263, DOI 10.1016/j.energy.2022.125911
   Tiwari S, 2022, J ENERGY STORAGE, V51, DOI 10.1016/j.est.2022.104479
   Tkachuk RV, 2023, SUSTAIN ENERGY GRIDS, V35, DOI 10.1016/j.segan.2023.101146
   Tostado-Veliz M, 2022, SUSTAIN CITIES SOC, V84, DOI 10.1016/j.scs.2022.104019
   Tuncbilek E., 2023, Building Energy Flexibility and Demand Management, P89, DOI [10.1016/B978-0-323-99588-7.00004-3, DOI 10.1016/B978-0-323-99588-7.00004-3]
   Tushar W, 2020, NAT ENERGY, V5, P834, DOI 10.1038/s41560-020-0671-0
   Ullah MH, 2019, IEEE ENER CONV, P3462, DOI [10.1109/ecce.2019.8912976, 10.1109/ECCE.2019.8912976]
   Ullah Z, 2020, COMPUT COMMUN, V154, P313, DOI 10.1016/j.comcom.2020.02.069
   Van Cutsem O, 2020, INT J ELEC POWER, V117, DOI 10.1016/j.ijepes.2019.105643
   van Kleef LMT, 2019, APPL ENERG, V251, DOI 10.1016/j.apenergy.2019.01.071
   Vering C, 2020, BUILD SIMUL CONF PR, P1304, DOI 10.26868/25222708.2019.210257
   Vivekh P, 2023, INT J REFRIG, V147, P163, DOI 10.1016/j.ijrefrig.2022.10.011
   Vulic N, 2023, ENERGY, V270, DOI 10.1016/j.energy.2023.126885
   Walker S, 2020, ENERG BUILDINGS, V209, DOI 10.1016/j.enbuild.2019.109705
   Wang BZ, 2022, APPL ENERG, V325, DOI 10.1016/j.apenergy.2022.119873
   Wang CY, 2023, APPL ENERG, V352, DOI 10.1016/j.apenergy.2023.122000
   Wang HC, 2022, ENERGY, V250, DOI 10.1016/j.energy.2022.123846
   Wang LZ, 2023, INT J ELEC POWER, V148, DOI 10.1016/j.ijepes.2022.108933
   Wang PC, 2023, ENERGY, V268, DOI 10.1016/j.energy.2023.126753
   Wang WX, 2022, SUSTAIN ENERGY TECHN, V50, DOI 10.1016/j.seta.2021.101897
   Wang YL, 2023, INT J HYDROGEN ENERG, V48, P15154, DOI 10.1016/j.ijhydene.2022.12.334
   Wang YF, 2019, APPL THERM ENG, V159, DOI 10.1016/j.applthermaleng.2019.113901
   Wang ZY, 2017, RENEW SUST ENERG REV, V75, P796, DOI 10.1016/j.rser.2016.10.079
   Weerasinghe NP, 2022, J CLEAN PROD, V374, DOI 10.1016/j.jclepro.2022.133997
   Wei ML, 2015, APPL THERM ENG, V86, P326, DOI 10.1016/j.applthermaleng.2015.04.061
   Weigert Andreas, 2020, Energy Informatics, V3, DOI 10.1186/s42162-020-00124-6
   Wen SF, 2021, SUSTAIN CITIES SOC, V68, DOI 10.1016/j.scs.2021.102748
   Wu QY, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151813638
   Wu YL, 2022, RENEW ENERG, V200, P558, DOI 10.1016/j.renene.2022.09.118
   Wu YL, 2022, RENEW ENERG, V181, P10, DOI 10.1016/j.renene.2021.09.036
   Xie YW, 2023, ENERGY, V273, DOI 10.1016/j.energy.2023.127196
   Xiong LY, 2020, APPL ENERG, V259, DOI 10.1016/j.apenergy.2019.114140
   Xu B, 2020, APPL ENERG, V262, DOI 10.1016/j.apenergy.2020.114514
   Xu ZW, 2021, IEEE T GREEN COMMUN, V5, P1077, DOI 10.1109/TGCN.2021.3061789
   Xue PN, 2020, ENERG BUILDINGS, V223, DOI 10.1016/j.enbuild.2020.110161
   Yadav S, 2024, APPL ENERG, V353, DOI 10.1016/j.apenergy.2023.122076
   Yang B, 2022, BUILDINGS-BASEL, V12, DOI 10.3390/buildings12060856
   Yang B, 2022, APPL THERM ENG, V215, DOI 10.1016/j.applthermaleng.2022.118952
   Yang B, 2020, ENERGY, V190, DOI 10.1016/j.energy.2019.116429
   Yang RJ, 2023, BUILD ENVIRON, V243, DOI 10.1016/j.buildenv.2023.110675
   Yang SY, 2020, APPL ENERG, V271, DOI 10.1016/j.apenergy.2020.115147
   Yin JW, 2020, ENERG BUILDINGS, V208, DOI 10.1016/j.enbuild.2019.109645
   Yin Q, 2017, APPL ENERG, V202, P153, DOI 10.1016/j.apenergy.2017.05.072
   You ML, 2022, APPL ENERG, V305, DOI 10.1016/j.apenergy.2021.117899
   You T, 2023, RENEW ENERG, V210, P159, DOI 10.1016/j.renene.2023.04.058
   Younesi A, 2024, J CLEAN PROD, V434, DOI 10.1016/j.jclepro.2023.139794
   Yun SI, 2022, BUILD ENVIRON, V211, DOI 10.1016/j.buildenv.2022.108765
   Zahir MH, 2023, J ENERGY STORAGE, V64, DOI 10.1016/j.est.2023.107156
   Zang XY, 2023, J ENERGY STORAGE, V72, DOI 10.1016/j.est.2023.108462
   Zhang CH, 2020, APPL THERM ENG, V173, DOI 10.1016/j.applthermaleng.2020.115223
   Zhang GZ, 2022, ENERG CONVERS MANAGE, V255, DOI 10.1016/j.enconman.2022.115340
   Zhang HT, 2023, J BUILD ENG, V78, DOI 10.1016/j.jobe.2023.107647
   Zhang L, 2018, ENERG BUILDINGS, V172, P493, DOI 10.1016/j.enbuild.2018.04.028
   Zhang TR, 2023, ENERGY, V271, DOI 10.1016/j.energy.2023.126938
   Zhang XF, 2022, RENEW ENERG, V187, P801, DOI 10.1016/j.renene.2022.01.050
   Zhang XH, 2024, ENERG BUILDINGS, V307, DOI 10.1016/j.enbuild.2024.113949
   Zhang YQ, 2024, RENEW ENERG, V220, DOI 10.1016/j.renene.2023.119739
   Zhang Y, 2018, SUSTAIN CITIES SOC, V41, P349, DOI 10.1016/j.scs.2018.05.044
   Zhang YL, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151813511
   Zhang YF, 2023, ENERGY AI, V12, DOI 10.1016/j.egyai.2022.100223
   Zhao HY, 2023, BUILD ENVIRON, V244, DOI 10.1016/j.buildenv.2023.110831
   Zhao L, 2022, ENERG CONVERS MANAGE, V259, DOI 10.1016/j.enconman.2022.115586
   Zhao L, 2021, ADV CIV ENG, V2021, DOI 10.1155/2021/6638897
   Zheng SQ, 2022, ENERGY, V248, DOI 10.1016/j.energy.2022.123634
   Zheng XY, 2024, ENERGY, V288, DOI 10.1016/j.energy.2023.129649
   Zhou F, 2023, ENERG CONVERS MANAGE, V296, DOI 10.1016/j.enconman.2023.117679
   Zhou FL, 2022, ENERG BUILDINGS, V260, DOI 10.1016/j.enbuild.2022.111916
   Zhou KL, 2016, RENEW SUST ENERG REV, V56, P215, DOI 10.1016/j.rser.2015.11.050
   Zhou K, 2022, J BUILD ENG, V53, DOI 10.1016/j.jobe.2022.104554
   Zhou L, 2024, ENERG CONVERS MANAGE, V300, DOI 10.1016/j.enconman.2023.117984
   Zhou L, 2023, ENERG CONVERS MANAGE, V277, DOI 10.1016/j.enconman.2022.116610
   Zhou Y., 2022, Energy Rev, V1, P100001, DOI [10.1016/j.enrev.2022.100001, DOI 10.1016/J.ENREV.2022.100001]
   Zhou Y, 2023, Energy Rev, DOI [10.1016/j.enrev.2023.100026, DOI 10.1016/J.ENREV.2023.100026]
   Zhou YT, 2022, ENERGY, V261, DOI 10.1016/j.energy.2022.125187
   Zhou YK, 2024, RENEW SUST ENERG REV, V199, DOI 10.1016/j.rser.2024.114466
   Zhou YK, 2024, RENEW ENERG, V225, DOI 10.1016/j.renene.2024.120280
   Zhou YK, 2024, ENERG BUILDINGS, V308, DOI 10.1016/j.enbuild.2024.114004
   Zhou YK, 2024, RENEW ENERG, V221, DOI 10.1016/j.renene.2023.119738
   Zhou YK, 2024, RENEW SUST ENERG REV, V192, DOI 10.1016/j.rser.2023.114184
   Zhou YK, 2023, ENERG CONVERS MANAGE, V297, DOI 10.1016/j.enconman.2023.117733
   Zhou YK, 2022, ENERGY AI, V10, DOI 10.1016/j.egyai.2022.100182
   Zhou YK, 2023, RENEW ENERG, V207, P177, DOI 10.1016/j.renene.2023.02.125
   Zhou YK, 2022, APPL ENERG, V328, DOI 10.1016/j.apenergy.2022.120196
   Zhou YK, 2023, RENEW ENERG, V202, P1324, DOI 10.1016/j.renene.2022.12.026
   Zhou YK, 2022, ENERGY AI, V10, DOI 10.1016/j.egyai.2022.100187
   Zhou YK, 2023, ENERG BUILDINGS, V279, DOI 10.1016/j.enbuild.2022.112649
   Zhou YK, 2022, RENEW ENERG, V199, P204, DOI 10.1016/j.renene.2022.08.128
   Zhou YK, 2022, ENERGY, V256, DOI 10.1016/j.energy.2022.124668
   Zhou YK, 2022, RENEW SUST ENERG REV, V162, DOI 10.1016/j.rser.2022.112444
   Zhou YK, 2022, APPL ENERG, V318, DOI 10.1016/j.apenergy.2022.119131
   Zhou YK, 2020, ENERG CONVERS MANAGE, V214, DOI 10.1016/j.enconman.2020.112891
   Zhou YK, 2020, J CLEAN PROD, V253, DOI 10.1016/j.jclepro.2020.119964
   Zhou YK, 2020, APPL ENERG, V262, DOI 10.1016/j.apenergy.2019.114416
   Zhu DF, 2020, APPL ENERG, V272, DOI 10.1016/j.apenergy.2020.115225
   Zhu JG, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-29837-w
   Zhuang CQ, 2023, APPL ENERG, V341, DOI 10.1016/j.apenergy.2023.121111
NR 311
TC 11
Z9 11
U1 30
U2 37
PU ELSEVIER SCIENCE SA
PI LAUSANNE
PA PO BOX 564, 1001 LAUSANNE, SWITZERLAND
SN 0378-7788
EI 1872-6178
J9 ENERG BUILDINGS
JI Energy Build.
PD JUL 15
PY 2024
VL 315
AR 114289
DI 10.1016/j.enbuild.2024.114289
EA MAY 2024
PG 43
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA TZ2S4
UT WOS:001245021000001
DA 2025-01-10
ER

PT J
AU Wang, A
   Gao, XR
   Zhou, ZY
   Siddique, KHM
   Yang, H
   Wang, JC
   Zhang, SY
   Zhao, XN
AF Wang, Ai
   Gao, Xuerui
   Zhou, Zeyu
   Siddique, Kadambot H. M.
   Yang, Hao
   Wang, Jichao
   Zhang, Shuyu
   Zhao, Xining
TI A novel index for vegetation drought assessment based on plant water
   metabolism and balance under vegetation restoration on the Loess Plateau
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Loess Plateau; Vegetation; Drought index; Water deficit; Climate change
ID CO2 FERTILIZATION; RIVER-BASIN; CLIMATE; EVAPOTRANSPIRATION; MODELS;
   STOCKS
AB Vegetation is vital to the ecosystem, contributing to the global carbon balance, but susceptible to the impacts of climate change. Monitoring vegetation drought remains challenging due to the lack of widely accepted drought indices. This study focused on vegetation, and simulated the vegetation suitable water demand and soil available water supply (calculated by Remote-sensing-based Water Balance Assessment Tool model). The standardized Vegetation Water deficit Index (SVWDI) was established by calculating the vegetation water deficit, which reflects the response of vegetation to drought. We examined the spatiotemporal evolution of vegetation drought on the Loess Plateau and evaluated the applicability of standardized vegetation water deficit index. Our findings revealed that the standardized vegetation water deficit index demonstrated an overall upward trend across different time scales from 1991 to 2020. Drought conditions were concentrated in the first 20 years of the study period, but vegetation drought on the Loess Plateau has been alleviated in the past decade. Moreover, as the time scale extended, the trend of SVWDI generally decreased, with approximately 49.50 % (1-month scale), 46.66 % (3 -month scale), 47.08 % (12 -month scale), and 32.16 % (24 -month scale) of the grid areas experiencing increased SVWDI. The correlation between SVWDI and tree -ring width index (TRWI) performed well under all precipitation gradients, but the Palmer drought severity index (PDSI) was only highly correlated with TRWI in regions with low precipitation. In terms of the relationship with vegetation health, SVWDI demonstrated the highest correlation with the normalized difference vegetation index (NDVI) across different time scales, followed by PDSI and standardized precipitation evapotranspiration index (SPEI). This study provides insights into the evolution of vegetation drought in response to climate change. The findings can guide initiatives such as returning farmland to forest and grassland on the Loess Plateau to aid climate change adaptation strategies.
C1 [Wang, Ai; Yang, Hao; Wang, Jichao] Northwest A&F Univ, Coll Water Resources & Architectural Engn, Yangling 712100, Shaanxi, Peoples R China.
   [Wang, Ai; Yang, Hao; Wang, Jichao] Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid Area, Minist Educ, Yangling 712100, Shaanxi, Peoples R China.
   [Gao, Xuerui; Zhao, Xining] Northwest A&F Univ, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China.
   [Zhou, Zeyu] Design & Res Co Ltd, China Water Resources Beifang Invest, Tianjin 300222, Peoples R China.
   [Siddique, Kadambot H. M.] Univ Western Australia, UWA Inst Agr, Perth, WA, Australia.
   [Zhang, Shuyu] Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen, Peoples R China.
C3 Northwest A&F University - China; Northwest A&F University - China;
   Northwest A&F University - China; Chinese Academy of Sciences; Institute
   of Soil & Water Conservation (ISWC), CAS; University of Western
   Australia; Southern University of Science & Technology
RP Gao, XR; Zhao, XN (corresponding author), Northwest A&F Univ, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China.
EM gaoxuerui666@163.com; zxn@nwsuaf.edu.cn
RI wang, jichao/IZE-3341-2023; Siddique, Kadambot H.M./B-3462-2011
OI Siddique, Kadambot H.M./0000-0001-6097-4235
FU National Natural Science Foundation of China [42125705, U22A20613];
   National Key Research and Development Program of China [2021YFD1900701]
FX <STRONG> </STRONG>The authors thank the National Natural Science
   Foundation of China (U22A20613) , National Natural Science Foundation of
   China (42125705) , and National Key Research and Development Program of
   China (2021YFD1900701) .
CR Ahlström A, 2015, SCIENCE, V348, P895, DOI 10.1126/science.aaa1668
   Bai ZF, 2022, ECOL INFORM, V70, DOI 10.1016/j.ecoinf.2022.101750
   Barkhordarian A, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51857-8
   Bastos A, 2019, ATMOS CHEM PHYS, V19, P12361, DOI 10.5194/acp-19-12361-2019
   Beck HE, 2011, REMOTE SENS ENVIRON, V115, P2547, DOI 10.1016/j.rse.2011.05.012
   Berg A, 2021, NAT CLIM CHANGE, V11, P331, DOI 10.1038/s41558-021-01007-8
   Chang JX, 2016, J HYDROL, V540, P824, DOI 10.1016/j.jhydrol.2016.06.064
   Chen SL, 2021, ECOL INDIC, V121, DOI 10.1016/j.ecolind.2020.107092
   Chen YP, 2022, AGR FOREST METEOROL, V322, DOI 10.1016/j.agrformet.2022.108999
   Chi DK, 2018, ECOL INDIC, V92, P141, DOI 10.1016/j.ecolind.2017.04.014
   Dai A, 2004, J HYDROMETEOROL, V5, P1117, DOI 10.1175/JHM-386.1
   Dai R, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15071915
   Damour G, 2010, PLANT CELL ENVIRON, V33, P1419, DOI 10.1111/j.1365-3040.2010.02181.x
   De Simon G, 2012, EUR J FOREST RES, V131, P1297, DOI 10.1007/s10342-012-0599-4
   Donohue RJ, 2013, GEOPHYS RES LETT, V40, P3031, DOI 10.1002/grl.50563
   Fan Jia-Zhi, 2016, Chinese Journal of Plant Ecology, V40, P631, DOI 10.17521/cjpe.2015.0480
   [冯凯 Feng Kai], 2020, [农业工程学报, Transactions of the Chinese Society of Agricultural Engineering], V36, P103
   Fu Z, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28652-7
   Gao XR, 2017, SCI TOTAL ENVIRON, V595, P191, DOI 10.1016/j.scitotenv.2017.03.226
   Gauthier PPG, 2014, J EXP BOT, V65, P6471, DOI 10.1093/jxb/eru367
   Ge CH, 2022, J HYDROL, V614, DOI 10.1016/j.jhydrol.2022.128605
   Gonsamo A, 2021, GLOBAL CHANGE BIOL, V27, P3336, DOI 10.1111/gcb.15658
   He B, 2019, AGR FOREST METEOROL, V278, DOI 10.1016/j.agrformet.2019.107663
   Hetherington AM, 2003, NATURE, V424, P901, DOI 10.1038/nature01843
   Hu ZM, 2009, AGR FOREST METEOROL, V149, P1410, DOI 10.1016/j.agrformet.2009.03.014
   Huang JP, 2016, NAT CLIM CHANGE, V6, P166, DOI [10.1038/NCLIMATE2837, 10.1038/nclimate2837]
   Jensen E., 1982, Water Consumption and Irrigation Demand
   Jia L, 2022, INT J CLIMATOL, V42, P4830, DOI 10.1002/joc.7506
   Jiang TL, 2022, J ENVIRON MANAGE, V305, DOI 10.1016/j.jenvman.2021.114356
   Koutroulis AG, 2019, SCI TOTAL ENVIRON, V655, P482, DOI 10.1016/j.scitotenv.2018.11.215
   Li JZ, 2020, HYDROL RES, V51, P942, DOI 10.2166/nh.2020.184
   Lian X, 2021, NAT REV EARTH ENV, V2, P232, DOI 10.1038/s43017-021-00144-0
   Liu XF, 2023, GLOBAL CHANGE BIOL, V29, P3072, DOI 10.1111/gcb.16657
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Medlyn BE, 2011, GLOBAL CHANGE BIOL, V17, P2134, DOI 10.1111/j.1365-2486.2010.02375.x
   Park CE, 2018, NAT CLIM CHANGE, V8, P70, DOI 10.1038/s41558-017-0034-4
   Sheffield J, 2012, NATURE, V491, P435, DOI 10.1038/nature11575
   SHUTTLEWORTH WJ, 1985, Q J ROY METEOR SOC, V111, P839, DOI 10.1256/smsqj.46909
   Song Y, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002634
   Swann ALS, 2018, CURR CLIM CHANGE REP, V4, P192, DOI 10.1007/s40641-018-0097-y
   Swann ALS, 2016, P NATL ACAD SCI USA, V113, P10019, DOI 10.1073/pnas.1604581113
   Trotsiuk V, 2016, FOREST ECOL MANAG, V373, P108, DOI 10.1016/j.foreco.2016.04.038
   Ukkola AM, 2016, NAT CLIM CHANGE, V6, P75, DOI [10.1038/nclimate2831, 10.1038/NCLIMATE2831]
   van Oel PR, 2018, HYDROLOG SCI J, V63, P979, DOI 10.1080/02626667.2018.1470632
   Vicente-Serrano SM, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2011JD016039
   Wang A, 2022, ECOL INDIC, V143, DOI 10.1016/j.ecolind.2022.109423
   Wang JC, 2023, J HYDROL, V617, DOI 10.1016/j.jhydrol.2022.129030
   Wang T, 2022, J CLEAN PROD, V347, DOI 10.1016/j.jclepro.2022.131248
   Wei YJ, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14153803
   Weng Z, 2023, SCI TOTAL ENVIRON, V859, DOI 10.1016/j.scitotenv.2022.160300
   Won J, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15020337
   Yang J, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11123256
   Yuan WP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax1396
   Zeng JY, 2023, SCI DATA, V10, DOI 10.1038/s41597-023-02255-3
   Zhang P, 2020, SCIENCE, V370, P1095, DOI 10.1126/science.abb3368
   Zhang YQ, 2019, REMOTE SENS ENVIRON, V222, P165, DOI 10.1016/j.rse.2018.12.031
   Zhang Y, 2021, AGR WATER MANAGE, V255, DOI 10.1016/j.agwat.2021.107028
   Zhao Q, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10060838
   Zhu ZC, 2016, NAT CLIM CHANGE, V6, P791, DOI [10.1038/NCLIMATE3004, 10.1038/nclimate3004]
NR 59
TC 1
Z9 1
U1 28
U2 59
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD MAR 25
PY 2024
VL 918
AR 170549
DI 10.1016/j.scitotenv.2024.170549
EA FEB 2024
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA KY0U9
UT WOS:001183417800001
PM 38309335
DA 2025-01-10
ER

PT J
AU Liu, JX
   Lin, ZW
   Chau, KW
   Shi, YL
   Yang, LC
AF Liu, Jianxiao
   Lin, Ziwei
   Chau, K. W.
   Shi, Yaling
   Yang, Linchuan
TI Urban resilience in face of the pandemic: Tracing changes in public
   events before, amid and after the fifth wave of COVID-19 in Hong Kong
SO CITIES
LA English
DT Article
DE Urban vitality; Public activity; K-medoids; Social sensing; Urban
   informatics
ID CLIMATE-CHANGE ADAPTATION; LESSONS; IMPACT
AB Urban resilience studies often prioritize the investigation of sudden and short-lived natural disasters, while overlooking the gradual emergence and enduring nature of pandemics. The COVID-19 crisis, a quintessential example of such a challenge, has elicited significant but underexplored shifts in the landscape of urban public events. This research, drawing on social sensing geospatial datasets, aims to examine the changes in public events prior to, during, and after the fifth wave of COVID-19 in Hong Kong. Employing a dynamic time warping-based clustering algorithm alongside multiple linear regression analysis, we endeavor to address two pivotal questions: (1) How have the patterns of public events transformed in response to the pandemic? (2) What factors significantly influence these changes? The findings reveal that: Temporally, the implementation of social distancing measures is correlated with a marked reduction in public event frequency, reflecting the extensive impact of the COVID-19 crisis. Spatial analysis reveals that while public events are concentrated in Hong Kong's central areas, the spread of confirmed COVID-19 cases is more evenly distributed, with only a weak correlation observed between event hotspots and case distributions. Furthermore, our analysis identifies three distinct temporal patterns of public event changes, underscoring a higher resilience of events in urban centers against pandemicinduced disruptions. Additionally, built environment factors are found to be positively correlated with the decline in events as per the impact ratio, while socio-demographic factors more significantly affect the recovery ratio of events post-pandemic. This study not only pioneers in providing a comprehensive framework for monitoring urban events during a pandemic but also offers crucial insights into urban dynamics and vitality. These findings are invaluable for shaping more effective public health policies and crisis management strategies, enhancing urban resilience in face of future pandemics.
C1 [Liu, Jianxiao; Lin, Ziwei; Chau, K. W.] Univ Hong Kong, Fac Architecture, Dept Real Estate & Construct, Hong Kong, Peoples R China.
   [Chau, K. W.] Univ Hong Kong, Ronald Coase Ctr Property Rights Res, HKUrbanLabs, Hong Kong, Peoples R China.
   [Shi, Yaling] Chengdu Univ Technol, Coll Geog & Planning, Chengdu, Peoples R China.
   [Yang, Linchuan] Southwest Jiaotong Univ, Sch Architecture, Dept Urban & Rural Planning, Chengdu, Peoples R China.
C3 University of Hong Kong; University of Hong Kong; Chengdu University of
   Technology; Southwest Jiaotong University
RP Yang, LC (corresponding author), Southwest Jiaotong Univ, Sch Architecture, Dept Urban & Rural Planning, Chengdu, Peoples R China.
EM yanglc0125@swjtu.edu.cn
RI Yang, Linchuan/ABF-1874-2021
OI Yang, Linchuan/0000-0001-6070-9044; LIN, Ziwei/0000-0002-9892-2331
FU National Natural Science Foundation of China [52278080]; Modern Design
   and Culture Research Center [MD22Z004]
FX This work was supported by the National Natural Science Foundation of
   China (No. 52278080) and Modern Design and Culture Research Center
   (MD22Z004) . The authors are grateful to the five reviewers for their
   constructive comments.
CR Aloi A, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093870
   [Anonymous], 2018, City Resilience Profiling Tool
   Apple, 2022, Mobility Trends Reports
   Arbelaitz O, 2013, PATTERN RECOGN, V46, P243, DOI 10.1016/j.patcog.2012.07.021
   Arcodia C, 2006, J CONV EVENT TOUR, V8, P1, DOI 10.1300/J452v08n02_01
   Banica A, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9020270
   Brown A, 2012, ENVIRON URBAN, V24, P531, DOI 10.1177/0956247812456490
   Brown K, 2014, PROG HUM GEOG, V38, P107, DOI [10.1177/0309132513498837, 10.1177/0361684313496549]
   Brugmann J, 2012, ENVIRON URBAN, V24, P215, DOI 10.1177/0956247812437130
   Campanella TJ, 2006, J AM PLANN ASSOC, V72, P141, DOI 10.1080/01944360608976734
   Coudriet, 2020, Forbes Billionaires Editors' PickApril 22
   de Koning K, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101981
   Donaire JA, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13084356
   Eliezer, 2021, The Music NetworkOctober 25
   Fatmi MR, 2020, J URBAN MANAG, V9, P270, DOI 10.1016/j.jum.2020.08.002
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Goodchild MF, 2007, GEOJOURNAL, V69, P211, DOI 10.1007/s10708-007-9111-y
   Google, 2022, Google Covid-19 Community Mobility Reports
   Gu SY, 2021, J THEOR APPL EL COMM, V16, P2263, DOI 10.3390/jtaer16060125
   Hermann S., 2009, Journal of Customer Behaviour, V8, P177, DOI DOI 10.1362/147539209X459796
   Leichenko R, 2011, CURR OPIN ENV SUST, V3, P164, DOI 10.1016/j.cosust.2010.12.014
   Li ZY, 2020, J DESTIN MARK MANAGE, V18, DOI 10.1016/j.jdmm.2020.100502
   Liu JX, 2023, TUNN UNDERGR SP TECH, V133, DOI 10.1016/j.tust.2022.104912
   Liu JX, 2021, APPL GEOGR, V130, DOI 10.1016/j.apgeog.2021.102416
   Liu JX, 2020, GEOGR SUSTAIN, V1, P284, DOI 10.1016/j.geosus.2020.12.001
   Liu Y, 2015, ANN ASSOC AM GEOGR, V105, P512, DOI 10.1080/00045608.2015.1018773
   McEvoy D, 2013, PLAN PRACT RES, V28, P280, DOI 10.1080/02697459.2013.787710
   McKenzie G, 2020, APPL GEOGR, V125, DOI 10.1016/j.apgeog.2020.102363
   Meerow S, 2016, LANDSCAPE URBAN PLAN, V147, P38, DOI 10.1016/j.landurbplan.2015.11.011
   Meerow S, 2015, J IND ECOL, V19, P236, DOI 10.1111/jiec.12252
   Mukaka MM, 2012, MALAWI MED J, V24, P69
   Niennattrakul V, 2007, MUE: 2007 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING, PROCEEDINGS, P733
   O'Hare P, 2013, PLAN PRACT RES, V28, P275, DOI 10.1080/02697459.2013.787721
   Pickett S.T., 2013, Resilience in ecology and urban design: linking theory and practice for sustainable cities, V3
   Pierce JC, 2011, ENVIRON POLIT, V20, P566, DOI 10.1080/09644016.2011.589580
   Rakthanmanon T, 2013, ACM T KNOWL DISCOV D, V7, DOI 10.1145/2500489
   Ruan JE, 2021, INT J DISAST RISK RE, V66, DOI 10.1016/j.ijdrr.2021.102578
   Sarda-Espinosa A., 2017, R Package Vignette, V12, P41
   Sharifi A., 2021, COVID 19 SYSTEMIC RI, DOI [10.1007/978-3-030-71587-8_16, DOI 10.1007/978-3-030-71587-8_16]
   Sharifi A, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12155918
   Shaw K., 2013, PUBLIC POLICY ADMIN, V28, P43, DOI DOI 10.1177/0952076711432578
   Solecki W, 2011, CURR OPIN ENV SUST, V3, P135, DOI 10.1016/j.cosust.2011.03.001
   Spaans M, 2017, CITIES, V61, P109, DOI 10.1016/j.cities.2016.05.011
   Stokes EC, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-12211-7
   The Recovery Village, 2022, Does Income Level Help You Cope With COVID-19?
   Thombre A, 2021, TRANSPORT POLICY, V110, P335, DOI 10.1016/j.tranpol.2021.06.010
   Wilkinson, 2020, DJ MagDecember 14
   Yang LC, 2023, TRANSPORT RES D-TR E, V114, DOI 10.1016/j.trd.2022.103571
   Yang LC, 2022, TUNN UNDERGR SP TECH, V125, DOI 10.1016/j.tust.2022.104528
   Yang LC, 2021, J TRANSP GEOGR, V94, DOI 10.1016/j.jtrangeo.2021.103099
   Zhang N, 2021, CLIN INFECT DIS, V73, pE1142, DOI 10.1093/cid/ciaa1818
   Zimmerman R, 2011, CURR OPIN ENV SUST, V3, P181, DOI 10.1016/j.cosust.2010.12.004
NR 52
TC 5
Z9 5
U1 16
U2 26
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0264-2751
EI 1873-6084
J9 CITIES
JI Cities
PD APR
PY 2024
VL 147
AR 104827
DI 10.1016/j.cities.2024.104827
EA FEB 2024
PG 12
WC Urban Studies
WE Social Science Citation Index (SSCI)
SC Urban Studies
GA KI7J6
UT WOS:001179393200001
DA 2025-01-10
ER

PT J
AU Marra, F
   Koukoula, M
   Canale, A
   Peleg, N
AF Marra, Francesco
   Koukoula, Marika
   Canale, Antonio
   Peleg, Nadav
TI Predicting extreme sub-hourly precipitation intensification based on
   temperature shifts
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID RAINFALL EXTREMES; FUTURE CHANGES; CLIMATE; FREQUENCY; STATISTICS;
   INCREASE
AB Extreme sub-hourly precipitation, typically convective in nature, is capable of triggering natural disasters such as floods and debris flows. A key component of climate change adaptation and resilience is quantifying the likelihood that sub-hourly extreme precipitation will exceed historical levels in future climate scenarios. Despite this, current approaches to estimating future sub-hourly extreme precipitation return levels are deemed insufficient. The reason for this can be attributed to two factors: there is limited availability of data from convection-permitting climate models (capable of simulating sub-hourly precipitation adequately) and the statistical methods we use to extrapolate extreme precipitation return levels do not capture the physics governing global warming. We present a novel physical-based statistical method for estimating the extreme sub-hourly precipitation return levels. The proposed model, named TEmperature-dependent Non-Asymptotic statistical model for eXtreme return levels (TENAX), is based on a parsimonious non-stationary and non-asymptotic theoretical framework that incorporates temperature as a covariate in a physically consistent manner. We first explain the theory and present the TENAX model. Using data from several stations in Switzerland as a case study, we demonstrate the model's ability to reproduce sub-hourly precipitation return levels and some observed properties of extreme precipitation. We then illustrate how the model can be utilized to project changes in extreme sub-hourly precipitation in a future warmer climate only based on climate model projections of temperatures during wet days and on foreseen changes in precipitation frequency. We conclude by discussing the uncertainties associated with the model, its limitations, and its advantages. With the TENAX model, one can project sub-hourly precipitation extremes at different return levels based on daily scale projections from climate models in any location globally where observations of sub-hourly precipitation data and near-surface air temperature are available.
C1 [Marra, Francesco] Univ Padua, Dept Geosci, Padua, Italy.
   [Marra, Francesco] CNR, Inst Atmospher Sci & Climate, Bologna, Italy.
   [Koukoula, Marika; Peleg, Nadav] Univ Lausanne, Inst Earth Surface Dynam, Lausanne, Switzerland.
   [Canale, Antonio] Univ Padua, Dept Stat Sci, Padua, Italy.
C3 University of Padua; Consiglio Nazionale delle Ricerche (CNR); Istituto
   di Scienze dell'Atmosfera e del Clima (ISAC-CNR); University of
   Lausanne; University of Padua
RP Marra, F (corresponding author), Univ Padua, Dept Geosci, Padua, Italy.; Marra, F (corresponding author), CNR, Inst Atmospher Sci & Climate, Bologna, Italy.; Peleg, N (corresponding author), Univ Lausanne, Inst Earth Surface Dynam, Lausanne, Switzerland.
EM francesco.marra@unipd.it; nadav.peleg@unil.ch
RI Marra, Francesco/I-3520-2019; Peleg, Nadav/Q-9719-2016
OI Marra, Francesco/0000-0003-0573-9202; Peleg, Nadav/0000-0001-6863-2934
FU Department of Geosciences of the University of Padova (TENAX project) as
   part of The Geosciences for Sustainable Development project [CUP
   C93C23002690001]; Fondazione Cassa di Risparmio di Padova e Rovigo;
   Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen
   Forschung [194649]
FX This research has been supported by the Department of Geosciences of the
   University of Padova (TENAX project) as part of The Geosciences for
   Sustainable Development project (CUP C93C23002690001), the Fondazione
   Cassa di Risparmio di Padova e Rovigo (Excellence Grant 2021, Resilience
   project) and the Schweizerischer Nationalfonds zur Forderung der
   Wissenschaftlichen Forschung (grant no. 194649, Rainfall and floods in
   future cities).
CR Ali H, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2021GL093798
   Ali H, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2020GL090317
   Ali H, 2018, GEOPHYS RES LETT, V45, P6972, DOI 10.1029/2018GL078689
   Ban NI, 2020, CLIM DYNAM, V55, P61, DOI 10.1007/s00382-018-4339-4
   Berg P, 2013, NAT GEOSCI, V6, P181, DOI 10.1038/ngeo1731
   Borga M, 2014, J HYDROL, V518, P194, DOI 10.1016/j.jhydrol.2014.05.022
   Caillaud C, 2021, CLIM DYNAM, V56, P1717, DOI 10.1007/s00382-020-05558-y
   Cheng LY, 2014, SCI REP-UK, V4, DOI 10.1038/srep07093
   Coles S., 2001, An Introduction to Statistical Modeling of Extreme Values, DOI DOI 10.1007/978-1-4471-3675-0
   Cristiano E, 2017, HYDROL EARTH SYST SC, V21, P3859, DOI 10.5194/hess-21-3859-2017
   Dallan E, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2021GL096727
   Dallan E, 2023, HYDROL EARTH SYST SC, V27, P1133, DOI 10.5194/hess-27-1133-2023
   Drobinski P, 2016, J GEOPHYS RES-ATMOS, V121, P3100, DOI 10.1002/2015JD023497
   Evin G, 2019, THEOR APPL CLIMATOL, V135, P811, DOI 10.1007/s00704-018-2404-x
   Fatichi S, 2016, EARTHS FUTURE, V4, P240, DOI 10.1002/2015EF000336
   Fischer AM, 2022, CLIM SERV, V26, DOI 10.1016/j.cliser.2022.100288
   Fisher RA, 1928, P CAMB PHILOS SOC, V24, P180, DOI 10.1017/S0305004100015681
   Fowler HJ, 2021, NAT REV EARTH ENV, V2, P107, DOI 10.1038/s43017-020-00128-6
   Fowler HJ, 2021, PHILOS T R SOC A, V379, DOI 10.1098/rsta.2019.0541
   Gnedenko B, 1943, ANN MATH, V44, P423, DOI 10.2307/1968974
   Huang J, 2022, URBAN CLIM, V42, DOI 10.1016/j.uclim.2022.101124
   Iliopoulou T, 2020, J HYDROL, V588, DOI 10.1016/j.jhydrol.2020.125005
   Jones RH, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL045081
   Katz RW, 2002, ADV WATER RESOUR, V25, P1287, DOI 10.1016/S0309-1708(02)00056-8
   Landl B., 2009, EMS2009-453
   Lenderink G, 2008, NAT GEOSCI, V1, P511, DOI 10.1038/ngeo262
   Lengfeld K., 2023, EGU23-7371, DOI [10.5194/egusphere-egu23-7371, DOI 10.5194/EGUSPHERE-EGU23-7371]
   Libertino A, 2019, GEOPHYS RES LETT, V46, P7437, DOI 10.1029/2019GL083371
   Maity SS, 2022, WATER RESOUR MANAG, V36, P5371, DOI 10.1007/s11269-022-03313-y
   Marani M, 2015, ADV WATER RESOUR, V79, P121, DOI 10.1016/j.advwatres.2015.03.001
   Marra Francesco, 2023, Zenodo, DOI 10.5281/ZENODO.8345905
   Marra F, 2023, ADV WATER RESOUR, V173, DOI 10.1016/j.advwatres.2023.104388
   Marra F, 2022, HYDROL EARTH SYST SC, V26, P1439, DOI 10.5194/hess-26-1439-2022
   Marra F, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2020GL091823
   Marra F, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2020GL090209
   Marra Francesco, 2020, Zenodo, DOI 10.5281/ZENODO.3971558
   Marra F, 2019, ADV WATER RESOUR, V127, P280, DOI 10.1016/j.advwatres.2019.04.002
   Molnar P, 2015, HYDROL EARTH SYST SC, V19, P1753, DOI 10.5194/hess-19-1753-2015
   Moustakis Y, 2021, EARTHS FUTURE, V9, DOI 10.1029/2020EF001824
   Overeem A, 2008, J HYDROL, V348, P124, DOI 10.1016/j.jhydrol.2007.09.044
   Palazzi E, 2019, CLIM DYNAM, V52, P2685, DOI 10.1007/s00382-018-4287-z
   Panthou G, 2014, J HYDROMETEOROL, V15, P1999, DOI 10.1175/JHM-D-14-0020.1
   Papalexiou SM, 2013, WATER RESOUR RES, V49, P187, DOI 10.1029/2012WR012557
   Peleg N, 2022, ADV WATER RESOUR, V166, DOI 10.1016/j.advwatres.2022.104258
   Peleg N, 2018, J HYDROMETEOROL, V19, P715, DOI 10.1175/JHM-D-17-0158.1
   Pfahl S, 2017, NAT CLIM CHANGE, V7, P423, DOI [10.1038/NCLIMATE3287, 10.1038/nclimate3287]
   Poschlod B, 2021, NAT HAZARD EARTH SYS, V21, P3573, DOI 10.5194/nhess-21-3573-2021
   Prosdocimi I, 2021, STOCH ENV RES RISK A, V35, P307, DOI 10.1007/s00477-020-01940-8
   Ragno E, 2019, ADV WATER RESOUR, V130, P270, DOI 10.1016/j.advwatres.2019.06.007
   Rubel F, 2017, METEOROL Z, V26, P115, DOI 10.1127/metz/2016/0816
   Serinaldi F, 2015, ADV WATER RESOUR, V77, P17, DOI 10.1016/j.advwatres.2014.12.013
   Sippel S, 2015, WEATHER CLIM EXTREME, V9, P25, DOI 10.1016/j.wace.2015.06.004
   Sorland SL, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100196
   Tabari H, 2021, J HYDROL, V593, DOI 10.1016/j.jhydrol.2020.125932
   Trenberth KE, 2003, B AM METEOROL SOC, V84, P1205, DOI 10.1175/BAMS-84-9-1205
   Utsumi N, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL048426
   Vidrio-Sahagun CT, 2022, ADV WATER RESOUR, V166, DOI 10.1016/j.advwatres.2022.104244
   Visser JB, 2021, J CLIMATE, V34, P9535, DOI 10.1175/JCLI-D-21-0292.1
   Wang L.-P., 2020, EGU2020-6061, DOI [10.5194/egusphere-egu2020-6061, DOI 10.5194/EGUSPHERE-EGU2020-6061]
   Wasko C, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aad135
   Wasko C, 2014, WATER RESOUR RES, V50, P3608, DOI 10.1002/2013WR015194
   Westra S, 2014, REV GEOPHYS, V52, P522, DOI 10.1002/2014RG000464
   Wilson PS, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL022465
   Yan L, 2021, WIRES WATER, V8, DOI 10.1002/wat2.1519
   Yin JB, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR028491
   Zorzetto E, 2016, GEOPHYS RES LETT, V43, P8076, DOI 10.1002/2016GL069445
NR 66
TC 9
Z9 9
U1 3
U2 3
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1027-5606
EI 1607-7938
J9 HYDROL EARTH SYST SC
JI Hydrol. Earth Syst. Sci.
PD JAN 31
PY 2024
VL 28
IS 2
BP 375
EP 389
DI 10.5194/hess-28-375-2024
PG 15
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA A3E3J
UT WOS:001281390200001
OA Green Published, gold
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Guelmami, A
AF Guelmami, A.
TI Large-scale mapping of existing and lost wetlands: Earth Observation
   data and tools to support restoration in the Sebou and Medjerda river
   basins
SO EURO-MEDITERRANEAN JOURNAL FOR ENVIRONMENTAL INTEGRATION
LA English
DT Article
DE Wetland habitats; Earth Observation; Large scale; Restoration;
   Nature-based Solutions; Sebou; Medjerda
ID ECOSYSTEM SERVICES; INDEX
AB Mediterranean wetlands are the richest and most productive ecosystems in the region, and are essential for climate change adaptation and mitigation. However, despite their importance, they have suffered significant destruction over time. We estimate that half of the natural wetlands have been lost since the 1970s, and the regional trend shows no signs of slowing down. It is therefore urgent to implement concrete solutions that can preserve the remaining wetlands and restore those that have been lost. The increasing availability of free and open Earth Observation (EO) data and tools has provided a basis for mapping these ecosystems and monitoring their status and trends. In this paper, we show how EO-based data and tools can support the pre-identification of candidate sites for wetlands restoration at large scale through the mapping and delineation of existing and lost wetland habitats, their current land use status, and the estimation of the efforts needed to recreate the lost and transformed ones. We used this approach in the Sebou river basin in Morocco and the transboundary Medjerda watershed between Algeria and Tunisia. The resulting products, i.e., Potential Wetland Areas and Potentially Restorable Wetlands maps, enabled the identification of more than 7000 km2 and 1700 km2 of lost wetland habitats that could be regained in the Sebou and Medjerda basins, respectively. These results hold immense value for water resources management and land planning as they can enhance and assist prioritization efforts for wetland restoration at local, national, and regional scales. They can serve as baseline data to identify candidate sites to implement wetland restoration actions as Nature-based Solutions, regenerate their habitats, and restore the ecosystem services they provide to society.
C1 [Guelmami, A.] Tour Du Valat Res Inst Conservat Mediterranean Wet, Arles, France.
RP Guelmami, A (corresponding author), Tour Du Valat Res Inst Conservat Mediterranean Wet, Arles, France.
EM guelmami@tourduvalat.org
OI Guelmami, Anis/0000-0002-3906-6424
FU Donors' Initiative for Mediterranean Freshwater Ecosystems (DIMFE); MAVA
   Foundation through the "WAMAN-Sebou"
FX This work was supported by the PRIMA funded project OurMED, the
   "Upscaling the Sebou Water Fund" project financed by the Donors'
   Initiative for Mediterranean Freshwater Ecosystems (DIMFE), the Horizon
   Europe RESTORE4Cs funded project, and the MAVA Foundation through the
   "WAMAN-Sebou" and "MedGIRE" funded projects.
CR Abidi S., 2019, J Int Sci, VIV, P223
   Abou Diwan G., 2012, B ARCHEOL ARCHIT LIB, V16, P215
   Ågren AM, 2014, HYDROL EARTH SYST SC, V18, P3623, DOI 10.5194/hess-18-3623-2014
   Barchiesi S, 2022, WETLANDS, V42, DOI 10.1007/s13157-022-01562-6
   Beltrame C., 2015, MEDITERRANEE, V125, P97, DOI [https://doi.org/10.4000/mediterranee.8046, DOI 10.4000/MEDITERRANEE.8046]
   Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI DOI 10.1080/02626667909491834
   Bridgewater Peter., 2008, Rev Eur Commun Int Environ Law, P100, DOI DOI 10.1111/J.1467-9388.2008.00582.X
   Bwangoy JRB, 2010, REMOTE SENS ENVIRON, V114, P73, DOI 10.1016/j.rse.2009.08.004
   Chaumont C, 1998, P AT DRAIN PLAIN GHA
   Cherif, 1995, RECHERCHE MAGHREB CO, V1, P192
   Cherif A., 1998, CAHIERS SERES SERIE, V20, P101
   Clerici N, 2013, ECOL INDIC, V24, P211, DOI 10.1016/j.ecolind.2012.06.002
   Cohen-Shacham E., 2016, Nature-based Solutions to address global societal challenges, V97, P2016, DOI [DOI 10.2305/IUCN.CH.2016.13.EN, DOI 10.2305/IUCN.CH.2016.13.ENB.P001/REF]
   Congalton R.G., 2019, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices
   Costanza R, 1997, NATURE, V387, P253, DOI 10.1038/387253a0
   Costanza R, 2014, GLOBAL ENVIRON CHANG, V26, P152, DOI 10.1016/j.gloenvcha.2014.04.002
   CUTTELOD A., 2009, Wildlife in a Changing World - An Analysis of the 2008 IUCN Red List of Threatened Species, P89
   Dakki M, 2015, GIZ ACCN, P56
   Davidson NC, 2018, MAR FRESHWATER RES, V69, P1525, DOI 10.1071/MF17377
   de Groot R, 2012, ECOSYST SERV, V1, P50, DOI 10.1016/j.ecoser.2012.07.005
   Debbarh A., 1991, HOMMES TERRE EAUX, V21, P28
   El Madihi M, 2017, PLANT ECOL DIVERS, V10, P197, DOI 10.1080/17550874.2017.1346716
   Esch T, 2013, IEEE GEOSCI REMOTE S, V10, P1617, DOI 10.1109/LGRS.2013.2272953
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Fluet-Chouinard E, 2023, NATURE, V614, P281, DOI 10.1038/s41586-022-05572-6
   Geijzendorffer IR, 2019, FRONT ECOL EVOL, V7, DOI 10.3389/fevo.2019.00021
   Geijzendorffer IR., 2018, ATLAS ECOSYSTEM SERV, DOI [10.1007/978-3-319-96229-0, DOI 10.1007/978-3-319-96229-0]
   Gleason RA, 2005, 92 US GEOL SURV JAME
   Gleason RA, 2007, 20071159 US GEOL SUR, P36
   Green AJ, 2002, BIOL CONSERV, V104, P71, DOI 10.1016/S0006-3207(01)00155-0
   Grillas P, 2021, INLAND WATERS, V11, P492, DOI 10.1080/20442041.2021.1962688
   Guejjoud H, 2019, THESIS I AGRONOMIQUE, P77
   Guelmami A., 2023, IGI GLOB, V2023, P12, DOI [10.4018/978-1-7998-9289-2.ch002, DOI 10.4018/978-1-7998-9289-2.CH002]
   Hadour A, 2021, INT J SEDIMENT RES, V36, P268, DOI 10.1016/j.ijsrc.2020.07.001
   Hiestermann J, 2015, S AFR J SCI, V111, P32, DOI 10.17159/SAJS.2015/20140179
   Horvath EK, 2017, ECOL INDIC, V83, P463, DOI 10.1016/j.ecolind.2017.07.026
   Klemas V, 2013, J COASTAL RES, V29, P958, DOI 10.2112/JCOASTRES-D-12-00170.1
   Kotti F, 2018, P INT ASS HYDROL SCI, V377, P67, DOI 10.5194/piahs-377-67-2018
   La Via Charles, 2014, THEMATIC COLLECTION
   Leberger R, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01655-0
   Ling JE, 2018, WETL ECOL MANAG, V26, P805, DOI 10.1007/s11273-018-9611-1
   Ludwig C, 2019, REMOTE SENS ENVIRON, V224, P333, DOI 10.1016/j.rse.2019.01.017
   Maltby E, 2011, HYDROLOG SCI J, V56, P1341, DOI 10.1080/02626667.2011.631014
   Marchese C, 2015, GLOB ECOL CONSERV, V3, P297, DOI 10.1016/j.gecco.2014.12.008
   McCauley LA, 2005, ECOL APPL, V15, P1199, DOI 10.1890/04-0647
   McInnes RJ, 2013, WETLANDS, V33, P1001, DOI 10.1007/s13157-013-0458-1
   McLaughlin DL, 2013, ECOL APPL, V23, P1619, DOI 10.1890/12-1489.1
   Mediterranean Wetlands Observatory, 2018, MED WETL OUTL 2 SOL
   Merot P, 2003, ECOL MODEL, V163, P51, DOI 10.1016/S0304-3800(02)00387-3
   Mitsch WJ, 2000, ECOL ECON, V35, P25, DOI 10.1016/S0921-8009(00)00165-8
   Mittermeier R.A., 2011, Biodiversity hotspots: Distribution and protection of conservation priority areas, P3, DOI DOI 10.1007/978-3-642-20992-5_1
   Moussa M., 2005, Revue des Sciences de l'Eau, P13
   O'Neill MP, 1997, RESTOR ECOL, V5, P85, DOI 10.1111/j.1526-100X.1997.00085.x
   Office Regional de Mise en Valeur du Gharb, 1997, FURTH IMPR NEED ADM, P19
   Ouni R, 2021, INVENTAIRE BIODIVERS, P120
   Pekel JF, 2016, NATURE, V540, P418, DOI 10.1038/nature20584
   Perennou C., 2020, Water resources in the Mediterranean region, P297, DOI [10.1016/b978-0-12-818086-0.00011-x, DOI 10.1016/B978-0-12-818086-0.00011-X]
   Perennou C, 2018, ADV ECOL RES, V58, P243, DOI 10.1016/bs.aecr.2017.12.002
   Perennou Christian, 2012, Ecologia Mediterranea, V38, P53
   Popoff N, 2021, BIODIVERS CONSERV, V30, P3067, DOI 10.1007/s10531-021-02236-1
   Qadem A, 2015, THESIS U M BENABDELA, P360
   Rajosoa AS, 2021, SUST WAT RESOUR MAN, V7, DOI 10.1007/s40899-021-00566-0
   Ramsar Convention on Wetlands, 2018, GLOB WETL OUTL STAT
   Rapinel S, 2019, J ENVIRON MANAGE, V247, P829, DOI 10.1016/j.jenvman.2019.06.098
   Rapinel S, 2023, HELIYON, V9, DOI 10.1016/j.heliyon.2023.e13482
   Samaali H, 2011, THESIS FACULTE SCI H
   Schuerch M, 2018, NATURE, V561, P231, DOI 10.1038/s41586-018-0476-5
   Sergent Edm., 1947, Histoire d'un marais algerien.
   Silva E, 2023, J APPL ECOL, V60, P1194, DOI 10.1111/1365-2664.14395
   Sorensen R, 2006, HYDROL EARTH SYST SC, V10, P101, DOI 10.5194/hess-10-101-2006
   Taky A, 2008, MAITRISE EXCES EAU H
   Taky A, 2020, SCI EAUX TERRITOIRES, V32, P19, DOI [10.14758/SET-REVUE.2020.2.04.https://www.cairn.info/revue-sciences-eaux-et-territoires-2020-2-page-19.htm, DOI 10.14758/SET-REVUE.2020.2.04.HTTPS://WWW.CAIRN.INFO/REVUE-SCIENCES-EAUX-ET-TERRITOIRES-2020-2-PAGE-19.HTM]
   Thorslund J, 2017, ECOL ENG, V108, P489, DOI 10.1016/j.ecoleng.2017.07.012
   Trombetti M, 2022, MAPPING ASSESSMENT S, P84
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   Vercueil J, 1982, SYSTEMES SUIVI DEVEL, P84
   Verniest F, 2022, CONSERV SCI PRACT, V4, DOI 10.1111/csp2.12807
   Weise K, 2020, REMOTE SENS ENVIRON, V247, DOI 10.1016/j.rse.2020.111892
   Xu HG, 2021, NAT ECOL EVOL, V5, P411, DOI 10.1038/s41559-020-01375-y
NR 79
TC 0
Z9 0
U1 2
U2 4
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 2365-6433
EI 2365-7448
J9 EURO-MEDITERR J ENVI
JI Euro-Mediterr. J. Environ. Integrat.
PD MAR
PY 2024
VL 9
IS 1
BP 169
EP 182
DI 10.1007/s41207-023-00443-6
EA DEC 2023
PG 14
WC Environmental Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA JQ5F0
UT WOS:001129877400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Agbohessou, Y
   Delon, C
   Mougin, E
   Grippa, M
   Tagesson, T
   Diedhiou, M
   Ba, SYA
   Ngom, D
   Vezy, R
   Ndiaye, O
   Assouma, MH
   Diawara, M
   Roupsard, O
AF Agbohessou, Yelognisse
   Delon, Claire
   Mougin, Eric
   Grippa, Manuela
   Tagesson, Torbern
   Diedhiou, Moussa
   Ba, Seydina
   Ngom, Daouda
   Vezy, Remi
   Ndiaye, Ousmane
   Assouma, Mohamed H.
   Diawara, Mamadou
   Roupsard, Olivier
TI To what extent are greenhouse-gas emissions offset by trees in a
   Sahelian silvopastoral system?
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Silvopastoral systems; Greenhouse gas emissions; Livestock; Trees;
   Process-based model
ID CARBON EXCHANGE FLUXES; IN-SITU MEASUREMENTS; SOIL ORGANIC-MATTER;
   VEGETATION INDEXES; FIELD-MEASUREMENTS; GRAZED ECOSYSTEM; MODEL; N2O;
   CO2; SAVANNA
AB To assess the extent to which trees in a semi-arid silvopastoral system (SPS) can offset the greenhouse-gas (GHG) emissions of the system's livestock, this study used two process-based models (STEP-GENDEC-N2O and DynACof) to simulate 9 years of agricultural activity and resulting emissions in a SPS that has been operating in sahelian Senegal. STEP-GENDEC-N2O simulated soil N2O and CO2 fluxes, plus growth of the herbaceous layer, while DynACof focused on the tree layer. Outputs from the models included simulated time series of vegetative growth, water fluxes, and emissions. This output was validated through the use of published data, and measurements that were made at the SPS. Overall, the outputs from STEP-GENDEC-N2O agreed well with validation data for water fluxes, soil N, soil C, herbaceous biomass, and N2O emissions. Good agreement was also found between the measured fluxes of the SPS ecosystem, and the simulated values that were generated by combining STEPGENDEC-N2O's simulations (of the herbaceous layer's heterotrophic respiration, autotrophic respiration, and gross primary productivity (GPP)) with DynACof's simulations of the tree layer's autotrophic respiration and GPP. Among the insights gained from the simulations was that in this SPS's sandy soils, nitrification was the dominant process that leads to N2O emissions. Our results show that the trees, at their current density (81 ha-1) offset 18 % to 41 % of the GHG emissions from livestock. With further development, the model set-up can be used for estimating the GHG offset at other tree densities, and will be useful for guiding future policies regarding climate-change adaptation and mitigation in the management of the Sahel's SPSs.
C1 [Agbohessou, Yelognisse; Diedhiou, Moussa; Ba, Seydina; Ngom, Daouda] Univ Cheikh Anta Diop, Dakar, Senegal.
   [Agbohessou, Yelognisse; Ndiaye, Ousmane] Inst Senegalais Rech Agr, Dakar, Senegal.
   [Agbohessou, Yelognisse; Ba, Seydina; Roupsard, Olivier] Ctr IRD ISRA Bel Air, LMI IESOL, Dakar, Senegal.
   [Delon, Claire] Univ Toulouse, Lab Aerol, CNRS, UPS, Toulouse, France.
   [Mougin, Eric; Grippa, Manuela] Univ Toulouse, Geosci Environm Toulouse, CNES, CNRS,IRD,UPS, Toulouse, France.
   [Tagesson, Torbern] Univ Copenhagen, Dept Geosci & Nat Resource Management, Copenhagen, Denmark.
   [Tagesson, Torbern] Lund Univ, Dept Phys Geog & Ecosyst Sci, Solvegatan 12, S-22362 Lund, Sweden.
   [Vezy, Remi] CIRAD, UMR AMAP, F-34398 Montpellier, France.
   [Vezy, Remi] Univ Montpellier, AMAP, CIRAD, CNRS,INRAE,IRD, Montpellier, France.
   [Ndiaye, Ousmane] Inst Senegalais Rech Agr, Ctr Rech Zootech Dahra, Dakar, Senegal.
   [Assouma, Mohamed H.] Univ Montpellier, SELMET, CIRAD, INRA,Montpellier SupAgro, Montpellier, France.
   [Assouma, Mohamed H.] Int Ctr Res & Dev Livestock Subhumid Reg CIRDES, Bobo Dioulasso, Burkina Faso.
   [Diawara, Mamadou] Univ Sci Tech & Technol Bamako USTTB, Dept Biol, Fac Sci & Tech FST, BP 3206, Bamako, Mali.
   [Roupsard, Olivier] CIRAD, UMR Eco &Sols, Dakar, Senegal.
   [Roupsard, Olivier] Univ Montpellier, Inst Agro, Eco &Sols, CIRAD,INRAE,IRD, Montpellier, France.
C3 University Cheikh Anta Diop Dakar; Universite de Toulouse; Universite
   Toulouse III - Paul Sabatier; Centre National de la Recherche
   Scientifique (CNRS); LAERO; Centre National de la Recherche Scientifique
   (CNRS); Institut de Recherche pour le Developpement (IRD); Universite de
   Toulouse; Universite Toulouse III - Paul Sabatier; University of
   Copenhagen; Lund University; CIRAD; Centre National de la Recherche
   Scientifique (CNRS); Institut de Recherche pour le Developpement (IRD);
   Universite de Montpellier; Centre National de la Recherche Scientifique
   (CNRS); Universite de Montpellier; CIRAD; INRAE; Institut de Recherche
   pour le Developpement (IRD); INRAE; CIRAD; Institut Agro; Montpellier
   SupAgro; Universite de Montpellier; University of Science & Technology
   of Bamako; CIRAD; Universite de Montpellier; INRAE; Institut Agro;
   Montpellier SupAgro; CIRAD; Institut de Recherche pour le Developpement
   (IRD)
RP Agbohessou, Y (corresponding author), Univ Cheikh Anta Diop, Dakar, Senegal.
EM yelognissefredi.agbohessou@ucad.edu.sn
RI Tagesson, Torbern/AGG-5627-2022; VEZY, Rémi/K-6511-2015; ASSOUMA,
   Mohamed/V-7368-2019; roupsard, olivier/C-1219-2008; Ndiaye,
   Ousmane/JYQ-0844-2024
OI DIAWARA, Mamadou Oumar/0000-0002-7958-4525; agbohessou,
   yelognisse/0000-0002-2681-0162; ASSOUMA, Mohamed
   Habibou/0000-0002-8163-0340
FU European Union [FOOD/2019/410-169, 871944]; FORMAS [2021-00644]; Swedish
   National Space Agency [SNSA 2021-00144, 2021-00111]; Marie Curie Actions
   (MSCA) [871944] Funding Source: Marie Curie Actions (MSCA)
FX This work was supported by the "Carbon sequestration and green -house
   gas emissions in (agro) silvopastoral ecosystems in the Sahelian CILSS
   states" (CaSSECS) project (FOOD/2019/410-169), which was it-self
   supported by European Union under the "Development of Smart Innovation
   through Research in Agriculture" (DeSIRA) Initiative; and The European
   Union's Horizon 2020 research and innovation programme under the Marie
   Sklodowska-Curie grant agreement (871944). Additional <STRONG>Funding
   </STRONG>for TT was provided by FORMAS (Dnr. 2021-00644) and the Swedish
   National Space Agency (SNSA 2021-00144 and 2021-00111).
CR Assouma MH, 2017, J ARID LAND, V9, P210, DOI 10.1007/s40333-017-0001-y
   Aulakh M. S., 1992, Advances in Soil Science, Volume 18., P2
   AULAKH MS, 1991, SOIL BIOL BIOCHEM, V23, P1161, DOI 10.1016/0038-0717(91)90029-J
   Bajracharya RM, 2000, SOIL SCI SOC AM J, V64, P286, DOI 10.2136/sssaj2000.641286x
   Bateman EJ, 2005, BIOL FERT SOILS, V41, P379, DOI 10.1007/s00374-005-0858-3
   Bentzon-Tarp A., 2023, AGR ECOSYST ENVIRON, V343, DOI [10.1016/j.agee.2022, DOI 10.1016/J.AGEE.2022]
   Bigaignon L., 2020, Understanding N2O emissions in African ecosystems: assessments from a semi-arid Savanna Grassland in Senegal and sub-tropical agricultural fields in Kenya, P26
   Brümmer C, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL037351
   Brümmer C, 2008, J GEOPHYS RES-BIOGEO, V113, DOI 10.1029/2007JG000583
   Brumme R, 1999, GLOBAL BIOGEOCHEM CY, V13, P1137, DOI 10.1029/1999GB900017
   Butterbach-Bahl K, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18359-y
   CARTER JP, 1995, APPL ENVIRON MICROB, V61, P2852, DOI 10.1128/AEM.61.8.2852-2858.1995
   Chapman M, 2020, GLOBAL CHANGE BIOL, V26, P4357, DOI 10.1111/gcb.15121
   Chapuis-Lardy L, 2007, GLOBAL CHANGE BIOL, V13, P1, DOI 10.1111/j.1365-2486.2006.01280.x
   Cisse M. I., 1980, Browse in Africa, P205
   Dangal SRS, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abaa79
   Davidson EA, 2000, GLOBAL BIOGEOCHEM CY, V14, P1035, DOI 10.1029/1999GB001223
   Delon C, 2017, ATMOS ENVIRON, V156, P36, DOI 10.1016/j.atmosenv.2017.02.024
   Delon C, 2015, BIOGEOSCIENCES, V12, P3253, DOI 10.5194/bg-12-3253-2015
   Delon C, 2022, NUTR CYCL AGROECOSYS, V124, P17, DOI 10.1007/s10705-022-10220-6
   Delon C, 2019, BIOGEOSCIENCES, V16, P2049, DOI 10.5194/bg-16-2049-2019
   Elberling B, 2003, AGR ECOSYST ENVIRON, V96, P37, DOI 10.1016/S0167-8809(03)00010-0
   Elberling B., 2003, Geogr. Tidsskr.-Den., V103, P47
   FAOSTAT, 2022, FAOSTAT database collections
   Fensholt R, 2005, INT J REMOTE SENS, V26, P2561, DOI 10.1080/01431160500033724
   Fensholt R, 2006, IEEE T GEOSCI REMOTE, V44, P1774, DOI 10.1109/TGRS.2006.875940
   FIRESTONE MK, 1989, LIFE SCI R, V47, P7
   Gilbert M, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.227
   Godde CM, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab7395
   Grippa M, 2017, J HYDROMETEOROL, V18, P1847, DOI [10.1175/jhm-d-16-0170.1, 10.1175/JHM-D-16-0170.1]
   Hanan NP, 1998, GLOBAL CHANGE BIOL, V4, P523, DOI 10.1046/j.1365-2486.1998.t01-1-00126.x
   Hiernaux P, 2022, J ARID ENVIRON, V200, DOI 10.1016/j.jaridenv.2022.104719
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2022-Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P197, DOI [10.1017/9781009325844.004, DOI 10.1017/9781009325844.004, DOI 10.1017/9781009325844.004.198]
   IPCC, 2006, IPCC. Guidelines for National Greenhouse Gas Inventory
   Jarvis P, 2007, TREE PHYSIOL, V27, P929, DOI 10.1093/treephys/27.7.929
   Kim DG, 2016, BIOGEOSCIENCES, V13, P4789, DOI 10.5194/bg-13-4789-2016
   KNOWLES R, 1982, MICROBIOL REV, V46, P43, DOI 10.1128/MMBR.46.1.43-70.1982
   Latham J., 2014, Global land cover share (GLC-SHARE) database beta-release version 1.02014, V29
   Li CS, 2000, NUTR CYCL AGROECOSYS, V58, P259, DOI 10.1023/A:1009859006242
   Li HL, 2019, ECOL INDIC, V107, DOI 10.1016/j.ecolind.2019.105541
   Liu Y., 1996, Modeling the Emissions of Nitrous Oxide (N O) and Methane (CH) from the Terrestrial Biosphere to the Atmosphere
   Liu YD, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14153797
   Ll CS, 2007, SOIL SCI PLANT NUTR, V53, P344, DOI 10.1111/j.1747-0765.2007.00133.x
   MANABE S, 1969, MON WEATHER REV, V97, P739, DOI 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2
   Manlay RJ, 2004, AGR SYST, V79, P83, DOI 10.1016/S0308-521X(03)00054-4
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P61, DOI 10.1016/j.cosust.2013.10.014
   Mbow C, 2013, J ARID ENVIRON, V97, P56, DOI 10.1016/j.jaridenv.2013.05.011
   Meng H, 2017, J ENVIRON MANAGE, V198, P41, DOI 10.1016/j.jenvman.2017.04.066
   MILLER RICHARD D., 1964, SOIL SCI SOC AMER PROC, V28, P644
   Ministere de l'Environnement du Developpement durable et de la Transition ecologique du Senegal, 2015, Contribution prevue determinee au niveau national (CPDN)
   Torres CMME, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-16821-4
   Montagnini F, 2013, BOIS FOR TROP, P3
   Monteith J L, 1965, Symp Soc Exp Biol, V19, P205
   MOORHEAD DL, 1991, ECOL MODEL, V56, P197, DOI 10.1016/0304-3800(91)90200-K
   Mougin E, 2014, AGR FOREST METEOROL, V198, P155, DOI 10.1016/j.agrformet.2014.08.006
   MOUGIN E, 1995, REMOTE SENS ENVIRON, V52, P181, DOI 10.1016/0034-4257(94)00126-8
   Newbold T, 2015, NATURE, V520, P45, DOI 10.1038/nature14324
   Ojeda JJ, 2017, GCB BIOENERGY, V9, P796, DOI 10.1111/gcbb.12384
   Pachauri RK., 2015, CLIMATE CHANGE 2014, P151
   Parton WJ, 1996, GLOBAL BIOGEOCHEM CY, V10, P401, DOI 10.1029/96GB01455
   Patureau D, 2000, MICROB ECOL, V39, P145, DOI 10.1007/s002480000009
   Poupon H., 1980, Structure et dynamique de la strate ligneuse d'une steppe sahelienne au nord du Senegal, Travaux et Documents de l'ORSTOM
   Reth S, 2005, PLANT SOIL, V268, P21, DOI 10.1007/s11104-005-0175-5
   Robertson GP, 2000, METHODS IN ECOSYSTEM SCIENCE, P104
   Savary S, 2012, CROP PROT, V34, P6, DOI 10.1016/j.cropro.2011.11.009
   Schlecht E, 2004, NUTR CYCL AGROECOSYS, V68, P199, DOI 10.1023/B:FRES.0000019453.19364.70
   Sobol IM, 2001, MATH COMPUT SIMULAT, V55, P271, DOI 10.1016/S0378-4754(00)00270-6
   Sommers L. E., 1981, SSSA Special Publication, P97
   Stackhouse P.W., 2018, POWER Release 8 . 0 . 1 (with GIS Applications) Methodology (Data Parameters, Sources, Validation)
   STEWART B. A., 1963, SOIL SCI SOC AMER PROC, V27, P377
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tagesson T, 2016, GEOGR TIDSSKR-DEN, V116, P93, DOI 10.1080/00167223.2016.1178072
   Tagesson T, 2016, AGR FOREST METEOROL, V226, P108, DOI 10.1016/j.agrformet.2016.05.013
   Tagesson T, 2015, AGR ECOSYST ENVIRON, V205, P15, DOI 10.1016/j.agee.2015.02.017
   Tian HQ, 2020, NATURE, V586, P248, DOI 10.1038/s41586-020-2780-0
   Tian Hanqin, 2015, Ecosystem Health and Sustainability, V1, P4, DOI 10.1890/EHS14-0015.1
   Van Wart J, 2015, AGR FOREST METEOROL, V209, P49, DOI 10.1016/j.agrformet.2015.02.020
   Vezy Remi, 2021, Zenodo, DOI 10.5281/ZENODO.7019749
   Vezy R, 2020, ENVIRON MODELL SOFTW, V124, DOI 10.1016/j.envsoft.2019.104609
   Walkley A, 1934, SOIL SCI, V37, P29, DOI 10.1097/00010694-193401000-00003
   Wang YP, 1997, J GEOPHYS RES-ATMOS, V102, P28013, DOI 10.1029/97JD02063
   Ward B.B., 2013, Reference Module in Earth Systems and Environmental Sciences, DOI DOI 10.1016/B978-0-12-409548-9.00697-7
   Wen Y, 2017, SOIL BIOL BIOCHEM, V112, P228, DOI 10.1016/j.soilbio.2017.05.011
   White JW, 2008, AGR FOREST METEOROL, V148, P1574, DOI 10.1016/j.agrformet.2008.05.017
   White JW, 2011, AGRON J, V103, P1242, DOI 10.2134/agronj2011.0038
   Xia YS, 2022, SOIL SCI SOC AM J, V86, P1043, DOI 10.1002/saj2.20416
   Zeppetello LRV, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28388-4
   Zhang KC, 2023, GLOBAL CHANGE BIOL, V29, P3114, DOI 10.1111/gcb.16672
   Zhao Q, 2021, LANCET PLANET HEALTH, V5, pE415, DOI 10.1016/S2542-5196(21)00081-4
NR 89
TC 2
Z9 2
U1 1
U2 10
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0168-1923
EI 1873-2240
J9 AGR FOREST METEOROL
JI Agric. For. Meteorol.
PD DEC 15
PY 2023
VL 343
AR 109780
DI 10.1016/j.agrformet.2023.109780
EA OCT 2023
PG 14
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA W8WI8
UT WOS:001094373600001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Jarzebski, MP
   Su, J
   Abrahamyan, A
   Lee, JS
   Kawasaki, J
   Chen, BX
   Andriatsitohaina, RNN
   Ocen, I
   Sioen, GB
   Lambino, R
   Saito, O
   Elmqvist, T
   Gasparatos, A
AF Jarzebski, Marcin Pawel
   Su, Jie
   Abrahamyan, Armine
   Lee, Jason
   Kawasaki, Jintana
   Chen, Bixia
   Andriatsitohaina, R. Ntsiva N.
   Ocen, Ismael
   Sioen, Giles Bruno
   Lambino, Ria
   Saito, Osamu
   Elmqvist, Thomas
   Gasparatos, Alexandros
TI Developing biodiversity-based solutions for sustainable food systems
   through transdisciplinary Sustainable Development Goals Labs (SDG-Labs)
SO FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
LA English
DT Article
DE sustainability-oriented experiment; transdisciplinarity;
   solutions-oriented approach; biodiversity-food-climate nexus;
   sustainability; co-benefits; agriculture
ID URBAN LIVING LABS; GENETIC DIVERSITY; CITIES; TRANSITIONS; ENERGY;
   SECURITY
AB Although biodiversity is a central component of food systems, conventional food systems have become one of the major drivers of biodiversity loss globally. There is an increasing need to transform food systems to provide sufficient and nutritious food, but with minimal negative impacts on the environment and society. One of the possible avenues to enable the sustainable transformation of food systems might be through the development of locally appropriate biodiversity-based solutions. In this paper we report the insights and lessons learned during the design and implementation of transdisciplinary projects that employed the concept of Sustainable Development Goals labs (SDG-Labs) to create biodiversity-based solutions to transform food systems. The six SDG-Labs outlined in this paper were implemented in Armenia, China, Japan, Madagascar, Thailand, and Uganda. Collectively they developed very diverse biodiversity-based solutions that used different components of biodiversity, ranging from novel cultivation systems with endangered plants, to gardens using tree species for wind breaks, or novel tea-forestry production systems. Beyond their ability to leverage different components of biodiversity to transform local food systems (also conserving biodiversity in the process), all solutions had multiple co-benefits such as climate change adaptation/mitigation and livelihoods generation, among other sustainability domains. Through a Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis we synthesized the experiences gained during the design and implementation of all six SDG-Labs. The findings suggest the great promise of these transdisciplinary approaches for developing solutions at the biodiversity-food-climate nexus. However, this synthesis paper also points to the multiple context-specific challenges that should be overcomed to maximize the potential of SDG-Labs to both enable the sustainable transformation of (local) food systems and/or be scaled up effectively.
C1 [Jarzebski, Marcin Pawel; Gasparatos, Alexandros] United Nations Univ, Inst Adv Study Sustainabil UNU IAS, Tokyo, Japan.
   [Jarzebski, Marcin Pawel; Lambino, Ria] Univ Tokyo, Tokyo Coll, Tokyo, Japan.
   [Jarzebski, Marcin Pawel; Sioen, Giles Bruno] Global Hub Japan, Future Earth, Tokyo, Japan.
   [Su, Jie; Gasparatos, Alexandros] Univ Tokyo, Inst Future Initiat, Tokyo, Japan.
   [Abrahamyan, Armine] Armenian Natl Agrarian Univ, Int Res Programme Coordinating Unit, Yerevan, Armenia.
   [Abrahamyan, Armine] Univ Florida, Florida Museum Nat Hist, Gainesville, FL USA.
   [Lee, Jason] Southwest Forestry Univ, Fa Foreign Languages, Kunming, Peoples R China.
   [Kawasaki, Jintana; Saito, Osamu] Inst Global Environm Strategies, Hayama, Japan.
   [Chen, Bixia] Univ Ryukyus, Fac Agr, Subtrop Field Sci Ctr, Nishihara, Japan.
   [Andriatsitohaina, R. Ntsiva N.] Madagascar Forests & Communities Caretakers Assoc, Antananarivo, Madagascar.
   [Andriatsitohaina, R. Ntsiva N.] Univ Antananarivo, Ecole Super Sci Agron ESSA, Ment Foresterie & Environm, Antananarivo, Madagascar.
   [Ocen, Ismael] Ocean One Social Res Ctr, Soroti, Uganda.
   [Sioen, Giles Bruno] Natl Inst Environm Studies, Tsukuba, Japan.
   [Lambino, Ria] Res Inst Humanity & Nat, Kyoto, Japan.
   [Elmqvist, Thomas] Stockholm Univ, Stockholm Resilience Ctr, Stockholm, Sweden.
C3 United Nations University; University of Tokyo; University of Tokyo;
   State University System of Florida; University of Florida; Southwest
   Forestry University - China; University of the Ryukyus; University
   Antananarivo; National Institute for Environmental Studies - Japan;
   Research Institute for Humanity & Nature (RIHN); Stockholm University
RP Jarzebski, MP (corresponding author), United Nations Univ, Inst Adv Study Sustainabil UNU IAS, Tokyo, Japan.; Jarzebski, MP (corresponding author), Univ Tokyo, Tokyo Coll, Tokyo, Japan.; Jarzebski, MP (corresponding author), Global Hub Japan, Future Earth, Tokyo, Japan.
EM marcin.p.jarzebski@unu.edu
RI Gasparatos, Alexandros/AAT-4403-2020; Sioen, Giles/AFL-0351-2022; Saito,
   Osamu/AAH-6091-2020; Liu, Jason/HLX-2144-2023
OI Su, Jie/0000-0002-1780-5708
FU The Alliance for Global Sustainability (AGS) Endowment fund at the
   University of Tokyo supported SDG-Labs. MJ, BC, and AG acknowledge the
   financial support of the Japan Society for the Promotion of Science
   (JSPS) through the Grant-in-Aid for Scientific Res; Alliance for Global
   Sustainability (AGS) Endowment fund at the University of Tokyo
   [23K11530]; Japan Society for the Promotion of Science (JSPS)
   [JPMJSC20A3]; Japan Science and Technology Agency (JST); Grants-in-Aid
   for Scientific Research [23K11530] Funding Source: KAKEN
FX The general SDG-Lab approach was designed during the 7th ICSS
   (Stockholm, 2018). We acknowledge the inspiration of the organising team
   of this event.r The Alliance for Global Sustainability (AGS) Endowment
   fund at the University of Tokyo supported SDG-Labs. MJ, BC, and AG
   acknowledge the financial support of the Japan Society for the Promotion
   of Science (JSPS) through the Grant-in-Aid for Scientific Research (C),
   project 23K11530 "Aging and shrinking population-driven transition of
   the nature conservation (ASP-NC)". AG acknowledges the financial support
   of the Japan Science and Technology Agency (JST) through the AJ-Core
   programme (Project FORENS, JPMJSC20A3).
CR Aernouts N., 2020, Towards a definition of socially-oriented LivingLabs, P163
   [Anonymous], 2020, The International Union for Conservation of Nature (IUCN) Red List of Threatened Species Version 2020-1
   Begna T., 2021, Inter J Agric Sci Food Technol, V7, P164
   Béné C, 2019, WORLD DEV, V113, P116, DOI 10.1016/j.worlddev.2018.08.011
   Bergmann M, 2021, SUSTAIN SCI, V16, P541, DOI 10.1007/s11625-020-00886-8
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Brons A, 2022, CITIES, V123, DOI 10.1016/j.cities.2021.103552
   Bulkeley H, 2016, CURR OPIN ENV SUST, V22, P13, DOI 10.1016/j.cosust.2017.02.003
   Bulkeley H, 2013, T I BRIT GEOGR, V38, P361, DOI 10.1111/j.1475-5661.2012.00535.x
   CBD, 2021, CBD/WG2020/3/3
   CBD, 2006, Article 2. Use of terms
   Chausson A, 2020, GLOBAL CHANGE BIOL, V26, P6134, DOI 10.1111/gcb.15310
   Christiaensen L, 2021, FOOD POLICY, V99, DOI 10.1016/j.foodpol.2020.101963
   Cohen-Shacham E., 2016, Nature-based Solutions to address global societal challenges, V97, P2016, DOI [DOI 10.2305/IUCN.CH.2016.13.EN, DOI 10.2305/IUCN.CH.2016.13.ENB.P001/REF]
   Vargas CAC, 2020, CLIM DEV, V12, P564, DOI 10.1080/17565529.2019.1664376
   Crenna E, 2019, J CLEAN PROD, V227, P378, DOI 10.1016/j.jclepro.2019.04.054
   Crippa M, 2021, NAT FOOD, V2, P198, DOI 10.1038/s43016-021-00225-9
   Crist E, 2017, SCIENCE, V356, P260, DOI 10.1126/science.aal2011
   Dawson IK, 2019, NEW PHYTOL, V224, P37, DOI 10.1111/nph.15895
   de Oliveira JAP, 2011, BIOL CONSERV, V144, P1302, DOI 10.1016/j.biocon.2010.12.007
   Dhyani S, 2021, FORESTS, V12, DOI 10.3390/f12030303
   Di Maddaloni F, 2022, INT J PROJ MANAG, V40, P778, DOI 10.1016/j.ijproman.2022.08.007
   Duarte CM, 2020, NATURE, V580, P39, DOI 10.1038/s41586-020-2146-7
   El Bilali H, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116260
   Eliasson K, 2023, J CLEAN PROD, V382, DOI 10.1016/j.jclepro.2022.135195
   Esquinas-Alcázar J, 2005, NAT REV GENET, V6, P946, DOI 10.1038/nrg1729
   Fischer J, 2017, TRENDS ECOL EVOL, V32, P335, DOI 10.1016/j.tree.2017.02.009
   Frac M, 2018, FRONT MICROBIOL, V9, DOI 10.3389/fmicb.2018.00707
   Gamache G, 2020, ENVIRON INNOV SOC TR, V37, P93, DOI 10.1016/j.eist.2020.08.002
   García-Martín M, 2022, NAT FOOD, V3, P814, DOI 10.1038/s43016-022-00612-w
   Gassner A, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abae2b
   Glover D, 2020, FRONT SUSTAIN FOOD S, V4, DOI 10.3389/fsufs.2020.00101
   Haase D, 2017, HABITAT INT, V64, P41, DOI 10.1016/j.habitatint.2017.04.005
   Hawkins I. W., 2018, Promoting biodiversity in food systems, V1st edition
   Henry RJ, 2020, CURR OPIN PLANT BIOL, V56, P168, DOI 10.1016/j.pbi.2019.11.004
   Herens MC, 2022, GLOB FOOD SECUR-AGR, V32, DOI 10.1016/j.gfs.2021.100592
   Hoban S, 2020, BIOL CONSERV, V248, DOI 10.1016/j.biocon.2020.108654
   Hossain M, 2019, J CLEAN PROD, V213, P976, DOI 10.1016/j.jclepro.2018.12.257
   Hvitsand C, 2022, AGR SYST, V199, DOI 10.1016/j.agsy.2022.103403
   Ioppolo G, 2013, LAND USE POLICY, V31, P460, DOI 10.1016/j.landusepol.2012.08.010
   Jacob M. C. M., 2021, Local food plants of Brazil ethnobiology, P3, DOI [10.1007/978-3-030-69139-4_1, DOI 10.1007/978-3-030-69139-4_1]
   Kaufman S, 2021, ENVIRON INNOV SOC TR, V40, P586, DOI 10.1016/j.eist.2021.10.010
   Kok KPW, 2021, SUSTAIN SCI, V16, P1811, DOI 10.1007/s11625-021-01033-7
   Kok KPW, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11247176
   Krause T, 2022, AMBIO, V51, P103, DOI 10.1007/s13280-021-01547-5
   Lawrence MG, 2022, ONE EARTH, V5, P44, DOI 10.1016/j.oneear.2021.12.010
   Leclère D, 2020, NATURE, V585, P551, DOI 10.1038/s41586-020-2705-y
   Leist A., 2018, Supporting youth in African countries to advance local economies and community health: The SDG lab on microfinance for youth and clean water
   Lind CE, 2012, REV AQUACULT, V4, P125, DOI 10.1111/j.1753-5131.2012.01068.x
   Longsheng C, 2022, RENEW ENERG, V195, P1438, DOI 10.1016/j.renene.2022.06.112
   Loorbach D, 2017, ANNU REV ENV RESOUR, V42, P599, DOI 10.1146/annurev-environ-102014-021340
   Lupp G, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13010188
   Mabhaudhi T, 2019, PLANTA, V250, P695, DOI 10.1007/s00425-019-03129-y
   Markard J, 2016, ENVIRON INNOV SOC TR, V18, P215, DOI 10.1016/j.eist.2015.05.003
   Martin G, 2015, AGR ECOSYST ENVIRON, V199, P301, DOI 10.1016/j.agee.2014.10.006
   Masuda H, 2022, SUSTAIN CITIES SOC, V82, DOI 10.1016/j.scs.2022.103883
   McCrory G, 2022, ENVIRON INNOV SOC TR, V43, P99, DOI 10.1016/j.eist.2022.03.004
   McCrory G, 2020, J CLEAN PROD, V277, DOI 10.1016/j.jclepro.2020.123202
   Miralles-Wilhelm F., 2021, Nature-based solutions in agriculture-sustainable management and conservation of land, water, and biodiversity, DOI [10.4060/cb3140-n, DOI 10.4060/CB3140EN]
   Mottet A, 2018, ANIMAL, V12, pS188, DOI 10.1017/S1751731118002215
   Mujeeb-Kazi A, 2013, ADV AGRON, V122, P179, DOI 10.1016/B978-0-12-417187-9.00004-8
   Nevens F, 2013, J CLEAN PROD, V50, P111, DOI 10.1016/j.jclepro.2012.12.001
   Offermans A., 2020, Urban living labs on food, water and energy: Evaluative scheme and manual
   Ojea E, 2020, ONE EARTH, V2, P544, DOI 10.1016/j.oneear.2020.05.012
   Oliver TH, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms10122
   Pawera L, 2020, FOODS, V9, DOI 10.3390/foods9091240
   Pereira LM, 2022, SUSTAIN SCI, DOI 10.1007/s11625-022-01182-3
   Pimm S, 2022, NAT FOOD, V3, P310, DOI 10.1038/s43016-022-00503-0
   Rasul G, 2022, INT J AGR SUSTAIN, V20, P1117, DOI 10.1080/14735903.2022.2057642
   Rockström J, 2020, NAT FOOD, V1, P3, DOI 10.1038/s43016-019-0010-4
   Rockstrom J., 2016, New way of viewing the sustainable development goals and how they are all linked to food
   Roe D, 2019, LANCET PLANET HEALTH, V3, pE287, DOI 10.1016/S2542-5196(19)30113-5
   Rolls RJ, 2018, BIOL REV, V93, P971, DOI 10.1111/brv.12381
   Schäpke N, 2018, GAIA, V27, P85, DOI 10.14512/gaia.27.S1.16
   Schmidt TS, 2013, ENERGY SUSTAIN DEV, V17, P581, DOI 10.1016/j.esd.2013.10.001
   Sengers F, 2019, TECHNOL FORECAST SOC, V145, P153, DOI 10.1016/j.techfore.2016.08.031
   Shabani F, 2020, ECOL INDIC, V116, DOI 10.1016/j.ecolind.2020.106436
   Snyman-van der Walt L., 2020, The Palgrave handbook of climate resilient societies, P1, DOI [10.1007/978-3-030-32811-5_48-1, DOI 10.1007/978-3-030-32811-5_48-1]
   Sowinska-Swierkosz Barbara., 2022, Nature-Based Solutions, V2, P100009, DOI DOI 10.1016/J.NBSJ.2022.100009
   Springmann M, 2018, NATURE, V562, P519, DOI 10.1038/s41586-018-0594-0
   Subedi R, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10081129
   Sunderland TCH, 2011, INT FOREST REV, V13, P265, DOI 10.1505/146554811798293908
   Tschora H, 2020, GLOB ECOL CONSERV, V22, DOI 10.1016/j.gecco.2020.e00919
   UNEP FAO and UNDP, 2023, Rethinking our food systems: A guide for multi-stakeholder collaboration
   Vans BAE, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-70934-x
   von Wirth T, 2019, EUR PLAN STUD, V27, P229, DOI 10.1080/09654313.2018.1504895
   Voytenko Y, 2016, J CLEAN PROD, V123, P45, DOI 10.1016/j.jclepro.2015.08.053
   Wani SH, 2022, ADV AGRON, V171, P255, DOI 10.1016/bs.agron.2021.08.006
   WFF, 2023, Opportunities and barriers for advancing Agrifood systems: Empowering Young people for a sustainable future
   Wolfert J, 2010, COMPUT ELECTRON AGR, V70, P389, DOI 10.1016/j.compag.2009.07.015
   Wrangsten C., 2022, Urban Transform, V4, DOI [10.1186/s42854-022-00034-8, DOI 10.1186/S42854-022-00034-8]
   Zavratnik V, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11143797
   Zimmerer KS, 2019, ANTHROPOCENE, V25, DOI 10.1016/j.ancene.2019.100192
NR 93
TC 2
Z9 2
U1 6
U2 14
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2571-581X
J9 FRONT SUSTAIN FOOD S
JI Front. Sustain. Food Syst.
PD OCT 4
PY 2023
VL 7
AR 1144506
DI 10.3389/fsufs.2023.1144506
PG 16
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA U5DS9
UT WOS:001085009300001
OA gold
DA 2025-01-10
ER

PT J
AU Gordon, JE
   Brown, EJ
   Bridgland, DR
   Brazier, V
AF Gordon, John E.
   Brown, Eleanor J.
   Bridgland, David R.
   Brazier, Vanessa
TI Valuing the Quaternary - Nature conservation and geoheritage
SO PROCEEDINGS OF THE GEOLOGISTS ASSOCIATION
LA English
DT Article
DE Quaternary geoheritage; Geoconservation; Quaternary climate change;
   Palaeoenvironmental archives; Ecosystem services; Human impacts; Nature
   restoration and recovery; Quaternary geoarchaeology
ID CLIMATE-CHANGE; BIODIVERSITY CONSERVATION; ECOSYSTEM SERVICES; MARINE
   GEOCONSERVATION; INFORM CONSERVATION; LANDSCAPE EVOLUTION; DOVER STRAIT;
   GEODIVERSITY; HISTORY; MANAGEMENT
AB This paper introduces the Special Issue of the Proceedings of the Geologists' Association on 'Valuing the Quaternary - Nature Conservation and Geoheritage', arising from the International Union for Quaternary Research (INQUA) Congress in Dublin, in July 2019. It presents an overview of the values of Quaternary geoheritage, which merit recognition as an integral part of nature conservation, to protect priority sites and features for scientific research and education, and to deliver wider ecological, cultural and aesthetic benefits. The paper highlights the benefits of incorporating knowledge and understanding of Quaternary geoheritage for nature conservation and society. Palaeoenvironmental, palaeoecological and palaeobiological archives are a key source of ecological and environmental data that allow learning from the past to help address contemporary conservation challenges such as biodiversity loss, anthropogenic pressures and climate change. Quaternary science plays a vital part in supporting the wider nature conservation agenda, including strengthening the role of protected and conserved areas in the sustainable management of natural capital and ecosystem services, climate change adaptation, marine conservation, nature restoration and recovery, connecting people and nature and informing nature-based solutions to threats faced by society. However, challenges remain to achieve protection of key geoheritage sites and landscapes globally, and to integrate better understanding of geodiversity in nature conservation research, policy development and practice to help address the twin crises facing nature conservation - biodiversity loss and climate change. Quaternary studies provide temporal and spatial perspectives to inform forward-looking nature conservation that is dynamic rather than static in outlook. (c) 2023 The Geologists' Association. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
C1 [Gordon, John E.] Univ St Andrews, Sch Geog & Sustainable Dev, St Andrews KY16 9AL, Scotland.
   [Brown, Eleanor J.] Nat England, Cty Hall,Spetchley Rd, Worcester WR5 2NP, England.
   [Bridgland, David R.] Univ Durham, Dept Geog, Lower Mountjoy, Durham DH1 3LE, England.
   [Brazier, Vanessa] NatureScot, Elmwood Campus,Carslogie Rd, Cupar KY15 4JB, Scotland.
C3 University of St Andrews; Durham University
RP Gordon, JE (corresponding author), Univ St Andrews, Sch Geog & Sustainable Dev, St Andrews KY16 9AL, Scotland.
EM jeg4@st-andrews.ac.uk
RI Gordon, John/ISA-2835-2023; Bridgland, David/JJG-2309-2023
CR Addy S., 2016, CRW201410 CREW
   Alahuhta J, 2022, LANCET PLANET HEALTH, V6, pE987, DOI 10.1016/S2542-5196(22)00259-5
   Alsos IG, 2022, SCI ADV, V8, DOI 10.1126/sciadv.abo7434
   Anders AM, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00024
   Anderson MG, 2015, CONSERV BIOL, V29, P680, DOI 10.1111/cobi.12503
   Anderson MG, 2023, P NATL ACAD SCI USA, V120, DOI 10.1073/pnas.2204434119
   Anderson MG, 2014, CONSERV BIOL, V28, P959, DOI 10.1111/cobi.12272
   Anderson MG, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0011554
   Anderson NJ, 2006, TRENDS ECOL EVOL, V21, P696, DOI 10.1016/j.tree.2006.09.005
   [Anonymous], 2008, Resolution 4 040: Conservation of Geodiversity and Geological Heritage IUCN
   [Anonymous], 2014, The History of the Quaternary Research Association
   Aytac A.S., 2023, Proceedings of the Geologists' Association
   Bailey J.J., 2022, Protected areas and nature recovery. Achieving the goal to protect 30% of UK land and seas for nature by 2030
   Ballantyne CK, 2019, EARTH ENV SCI T R SO, V110, P133, DOI 10.1017/S175569101800004X
   Barak RS, 2016, INT J PLANT SCI, V177, P90, DOI 10.1086/683394
   Barnosky AD, 2017, SCIENCE, V355, DOI 10.1126/science.aah4787
   Beier P, 2015, CONSERV BIOL, V29, P613, DOI 10.1111/cobi.12511
   Beller EE, 2020, GLOB ECOL CONSERV, V21, DOI 10.1016/j.gecco.2019.e00836
   Bennion H, 2011, J PALEOLIMNOL, V45, P533, DOI 10.1007/s10933-010-9419-3
   Bétard F, 2023, GEOHERITAGE, V15, DOI 10.1007/s12371-023-00824-x
   Birks HJB, 2019, PLANT ECOL DIVERS, V12, P189, DOI 10.1080/17550874.2019.1646831
   Birks H. John B., 2012, International Journal of Biodiversity Science Ecosystem Services & Management, V8, P292, DOI 10.1080/21513732.2012.701667
   Bjune AE, 2015, HOLOCENE, V25, P17, DOI 10.1177/0959683614556386
   Boivin N, 2021, NAT ECOL EVOL, V5, P273, DOI 10.1038/s41559-020-01361-4
   Boivin NL, 2016, P NATL ACAD SCI USA, V113, P6388, DOI 10.1073/pnas.1525200113
   Boon P., 2012, River conservation and management
   Brazier V, 2017, P GEOLOGIST ASSOC, V128, P151, DOI 10.1016/j.pgeola.2016.11.008
   Brazier V, 2012, SCOT GEOGR J, V128, P211, DOI 10.1080/14702541.2012.737015
   Briant R.M, 2019, The Quaternary Fluvial Archives of the Major English Rivers. INQUA Field Guide
   Bridgland D.R., 2019, The Quaternary Fluvial Archives of the Major English Rivers: Field Guide, P97
   Bridgland D.R., 1994, QUATERNARY THAMES
   Bridgland DR, 2014, P GEOLOGIST ASSOC, V125, P600, DOI 10.1016/j.pgeola.2014.10.009
   Bridgland DR, 2013, P GEOLOGIST ASSOC, V124, P612, DOI 10.1016/j.pgeola.2012.10.004
   Bridgland DR, 2013, P GEOLOGIST ASSOC, V124, P417, DOI 10.1016/j.pgeola.2012.03.006
   Brilha J, 2018, ENVIRON SCI POLICY, V86, P19, DOI 10.1016/j.envsci.2018.05.001
   Brilha J, 2016, GEOHERITAGE, V8, P119, DOI 10.1007/s12371-014-0139-3
   Brooks SJ, 2012, QUATERNARY SCI REV, V41, P67, DOI 10.1016/j.quascirev.2012.03.007
   Brovkin V, 2021, NAT GEOSCI, V14, P550, DOI 10.1038/s41561-021-00790-5
   Brown AG, 2021, QUATERNARY SCI REV, V260, DOI 10.1016/j.quascirev.2021.106929
   Brown AG, 2018, EARTH-SCI REV, V180, P185, DOI 10.1016/j.earscirev.2018.02.001
   Brown E.J., 2019, The Quaternary Fluvial Archives of the Major English Rivers: Field Guide, P37
   Brown SC, 2020, NAT CLIM CHANGE, V10, P244, DOI 10.1038/s41558-019-0682-7
   Büntgen U, 2021, NAT GEOSCI, V14, P190, DOI 10.1038/s41561-021-00698-0
   Buhl-Mortensen L, 2015, J SEA RES, V100, P46, DOI 10.1016/j.seares.2014.10.014
   Buma B, 2019, LANDSCAPE ECOL, V34, P17, DOI 10.1007/s10980-018-0754-5
   Burek CV, 2008, GEOL SOC SPEC PUBL, V300, P1, DOI 10.1144/SP300.1
   Burek CV, 2013, P GEOLOGIST ASSOC, V124, P581, DOI 10.1016/j.pgeola.2012.10.003
   Castilla-Beltrán A, 2020, BIOL CONSERV, V242, DOI 10.1016/j.biocon.2019.108397
   Chakraborty A, 2020, J NAT CONSERV, V56, DOI 10.1016/j.jnc.2020.125862
   Chambers FM, 1999, J APPL ECOL, V36, P719, DOI 10.1046/j.1365-2664.1999.00435.x
   Chambers FM, 2007, BIOL CONSERV, V137, P197, DOI 10.1016/j.biocon.2007.02.002
   Chaplin-Kramer R, 2022, NAT ECOL EVOL, DOI 10.1038/s41559-022-01934-5
   Chen A, 2015, SPRING GEOGR, P1, DOI 10.1007/978-3-662-46697-1
   Chiverrell RC, 2019, EARTH SURF PROC LAND, V44, P2366, DOI 10.1002/esp.4650
   Chylinska D, 2019, GEOHERITAGE, V11, P531, DOI 10.1007/s12371-018-0308-x
   Clark CD, 2022, BOREAS, V51, P699, DOI 10.1111/bor.12594
   Cohen-Shacham E., 2016, Nature-based Solutions to address global societal challenges, V97, P2016, DOI [DOI 10.2305/IUCN.CH.2016.13.EN, DOI 10.2305/IUCN.CH.2016.13.ENB.P001/REF]
   Cole LES, 2022, ANTHROPOCENE, V37, DOI 10.1016/j.ancene.2022.100324
   Coratza P, 2019, WATER-SUI, V11, DOI 10.3390/w11102112
   Cotterill CJ, 2017, QUATERNARY SCI REV, V171, P136, DOI 10.1016/j.quascirev.2017.07.006
   Crees JJ, 2015, BIOL CONSERV, V186, P143, DOI 10.1016/j.biocon.2015.03.007
   Crofts R., 2019, Int. J. Geoheritage Parks, V7, P211, DOI [10.1016/j.ijgeop.2019.12.002, DOI 10.1016/J.IJGEOP.2019.12.002]
   Crofts R., 2020, Guidelines for geoconservation in protected and conserved areas
   Crofts R, 2018, GEOHERITAGE, V10, P231, DOI 10.1007/s12371-017-0239-y
   Crofts R, 2014, P GEOLOGIST ASSOC, V125, P263, DOI 10.1016/j.pgeola.2014.03.002
   Cunha P.P., 2023, P GEOLOGIST ASSOC
   Dale L.C., 2023, Proceedings of the Geologists' Association
   Dasgupta P, 2021, The economics of biodiversity: The Dasgupta review
   DAVIES AL, 2010, OPEN J ECOL, V0003
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   De Wever P, 2023, GEOSCIENCES, V13, DOI 10.3390/geosciences13030069
   De Wever P, 2015, GEOHERITAGE, V7, P205, DOI 10.1007/s12371-015-0151-2
   DeArellano JVG, 2015, ATMOSPHERIC BOUNDARY LAYER: INTEGRATING AIR CHEMISTRY AND LAND INTERACTIONS, P1, DOI 10.1177/2053019615579128
   Dearing JA, 2012, P NATL ACAD SCI USA, V109, pE1111, DOI 10.1073/pnas.1118263109
   Dearing JA, 2010, ECOL SOC, V15
   Defra, 2022, Nature Recovery Network
   Delcourt HR, 1988, LANDSCAPE ECOL, V2, P23, DOI 10.1007/BF00138906
   Dempster M., 2023, Proceedings of the Geologists' Association
   Díaz S, 2018, SCIENCE, V359, P270, DOI 10.1126/science.aap8826
   Díaz S, 2015, CURR OPIN ENV SUST, V14, P1, DOI 10.1016/j.cosust.2014.11.002
   Dietl GP, 2015, ANNU REV EARTH PL SC, V43, P79, DOI 10.1146/annurev-earth-040610-133349
   Dudley N., 2008, Guidelines for applying protected area management categories, DOI 10.2305/IUCN.CH.2008.PAPS.2.en
   Edwards KJ, 2019, EARTH ENV SCI T R SO, V110, P199, DOI 10.1017/S1755691018000208
   Ellerton D, 2022, NAT GEOSCI, V15, P1017, DOI 10.1038/s41561-022-01062-6
   Ellis EC, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2023483118
   Ellis N, 2011, P GEOLOGIST ASSOC, V122, P353, DOI 10.1016/j.pgeola.2011.03.008
   Evans D., 2023, Geoconservation: Principles and Practice, VNE802
   Fairbairn W.A., 2022, U.K. Quaternary International, V631, P11
   Falco N., 2021, Scientific Reports, V11, P15259
   Fordham DA, 2020, SCIENCE, V369, P1072, DOI 10.1126/science.abc5654
   Foster I, 2016, RIVER SCIENCE: RESEARCH AND MANAGEMENT FOR THE 21ST CENTURY, P61
   Froyd CA, 2008, QUATERNARY SCI REV, V27, P1723, DOI 10.1016/j.quascirev.2008.06.006
   Galway-Witham J, 2019, J QUATERNARY SCI, V34, P355, DOI 10.1002/jqs.3137
   Garcia-Cortes A., 2019, CONCEPTUAL BASE METH
   García-Moreno D, 2019, QUATERNARY SCI REV, V203, P209, DOI 10.1016/j.quascirev.2018.11.011
   Garcin Y, 2022, NATURE, V612, P277, DOI 10.1038/s41586-022-05389-3
   Garvey A, 2022, ENVIRON POLICY GOV, V32, P3, DOI 10.1002/eet.1955
   Gatley S., 2016, IRISH J EARTH SCI, V34, P79, DOI DOI 10.3318/IJES.2016.34.79
   Geirsdóttir A, 2020, QUATERNARY SCI REV, V249, DOI 10.1016/j.quascirev.2020.106633
   Giles D, 2017, Q J ENG GEOL HYDROGE, V50, P369, DOI 10.1144/qjegh2017-104
   Gill JL, 2015, CONSERV BIOL, V29, P640, DOI 10.1111/cobi.12504
   Gillson L, 2019, ECOL SOC, V24, DOI 10.5751/ES-11022-240314
   Gillson L, 2014, TRENDS ECOL EVOL, V29, P317, DOI 10.1016/j.tree.2014.03.010
   Gordon J.E., 2021, Landscapes and Landforms of Scotland, P481
   Gordon J.E., 2019, International Journal of Geoheritage and Parks, V7, P199, DOI [DOI 10.1016/J.IJGEOP.2019.12.005, 10.1016/j.ijgeop.2019.12.005]
   Gordon J.E., 2021, Landscapes and Landforms of Scotland, P333, DOI DOI 10.1007/978
   Gordon J.E., 2018, Geoheritage, P213, DOI 10.1016/B978-0-12-809531-7.00012-5
   Gordon JE, 2022, GEOHERITAGE, V14, DOI 10.1007/s12371-022-00753-1
   Gordon JE, 2019, EARTH ENV SCI T R SO, V110, P257, DOI 10.1017/S1755691019000069
   Gordon JE, 2018, GEOSCIENCES, V8, DOI 10.3390/geosciences8040136
   Gordon JE, 2018, GEOHERITAGE, V10, P191, DOI 10.1007/s12371-017-0240-5
   Gordon JE, 2016, P GEOLOGIST ASSOC, V127, P716, DOI 10.1016/j.pgeola.2016.10.002
   Gordon JE, 2013, SCOT J GEOL, V49, P41, DOI 10.1144/sjg2011-465
   Grace M, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2019.0297
   Grant MJ, 2008, VEG HIST ARCHAEOBOT, V17, P551, DOI 10.1007/s00334-007-0100-3
   GRAY M., 2013, Geodiversity: Valuing and Conserving Abiotic Nature, V2nd
   Gray M, 2021, P GEOLOGIST ASSOC, V132, P605, DOI 10.1016/j.pgeola.2021.09.001
   Gray M, 2013, P GEOLOGIST ASSOC, V124, P659, DOI 10.1016/j.pgeola.2013.01.003
   Greiser Caroline, 2018, International Journal of Biodiversity Science Ecosystem Services & Management, V14, P210, DOI 10.1080/21513732.2018.1523229
   Griffiths J.S., 2017, Engineering Geology and Geomorphology of Glaciated and Periglaciated Terrains-Engineering Group Working Party Report, V28
   Gupta S, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms15101
   Harding P, 2012, P GEOLOGIST ASSOC, V123, P584, DOI 10.1016/j.pgeola.2012.03.003
   Hartman S, 2017, GLOBAL PLANET CHANGE, V156, P123, DOI 10.1016/j.gloplacha.2017.04.007
   Hawthorne D., 2023, Proceedings of the Geologists' Association
   Hazell Z., 2023, Proceedings of the Geologists' Association
   Higgitt D.L., 2001, GEOMORPHOLOGICAL PRO
   Hjort J, 2015, CONSERV BIOL, V29, P630, DOI 10.1111/cobi.12510
   Hobbs RJ, 2014, FRONT ECOL ENVIRON, V12, P557, DOI 10.1890/130300
   Hobbs RJ, 2009, TRENDS ECOL EVOL, V24, P599, DOI 10.1016/j.tree.2009.05.012
   Hoogakker BAA, 2016, CLIM PAST, V12, P51, DOI 10.5194/cp-12-51-2016
   Hose TA, 2016, GEOL SOC SPEC PUBL, V417, P1, DOI 10.1144/SP417.15
   Hu A, 2020, ISME J, V14, P931, DOI 10.1038/s41396-019-0574-x
   Huddart D., 2002, Geological Conservation Review Series, V25, P230
   Innes JB, 2017, MICROPALEAEONTOLOGIC, P55
   Innes JB, 2013, QUATERNARY SCI REV, V77, P80, DOI 10.1016/j.quascirev.2013.07.012
   IUCN [International Union for Conservation of Nature], 2012, WCC-2012-Res-048, Valuing and Conserving Geoheritage within the IUCN Programme 2013-2016
   IUCN [International Union for Conservation of Nature], 2020, WCC-2020-Res-074-EN.
   Jackson ST, 2009, SCIENCE, V325, P567, DOI 10.1126/science.1172977
   Jeffers ES, 2015, QUATERNARY SCI REV, V112, P17, DOI 10.1016/j.quascirev.2014.12.018
   Kaskela AM, 2017, CONT SHELF RES, V142, P1, DOI 10.1016/j.csr.2017.05.013
   Kemp ME, 2020, P ROY SOC B-BIOL SCI, V287, DOI 10.1098/rspb.2020.0447
   Kiernan K, 2015, GEOHERITAGE, V7, P177, DOI 10.1007/s12371-014-0128-6
   Kjær KH, 2022, NATURE, V612, P283, DOI 10.1038/s41586-022-05453-y
   Knowles P., 2021, Earth Heritage Magazine, V55, P16
   Knudson C, 2018, NAT CLIM CHANGE, V8, P678, DOI 10.1038/s41558-018-0188-8
   Koster E.A., 2005, The physical geography of Western Europe
   Lane SN, 2007, EARTH SURF PROC LAND, V32, P429, DOI 10.1002/esp.1404
   Lane SN, 2017, WIRES WATER, V4, DOI 10.1002/wat2.1211
   Larwood JG, 2013, P GEOLOGIST ASSOC, V124, P720, DOI 10.1016/j.pgeola.2013.04.001
   Last J, 2013, P GEOLOGIST ASSOC, V124, P625, DOI 10.1016/j.pgeola.2013.02.002
   Lausch A, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12223690
   Lausch A, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11202356
   Lawler JJ, 2015, CONSERV BIOL, V29, P618, DOI 10.1111/cobi.12505
   Lear CH, 2021, J GEOL SOC LONDON, V178, DOI 10.1144/jgs2020-239
   Leo KL, 2019, OCEAN COAST MANAGE, V175, P180, DOI 10.1016/j.ocecoaman.2019.03.019
   Lowe J, 2015, RECONSTRUCTING QUATERNARY ENVIRONMENTS, 3RD EDITION
   Lowe J, 2021, P GEOLOGIST ASSOC, V132, P24, DOI 10.1016/j.pgeola.2020.09.005
   Lucatelli D, 2020, GEO-MAR LETT, V40, P911, DOI 10.1007/s00367-019-00614-x
   Lukanina E, 2022, PALAEOGEOGR PALAEOCL, V605, DOI 10.1016/j.palaeo.2022.111218
   Mace GM, 2014, SCIENCE, V345, P1558, DOI 10.1126/science.1254704
   MacKinnon K., 2020, Parks Stewardship Forum, DOI [10.5070/P536248273, DOI 10.5070/P536248273]
   Macklin MG, 2010, QUATERNARY SCI REV, V29, P1555, DOI 10.1016/j.quascirev.2009.06.010
   May VJ, 2019, P GEOLOGIST ASSOC, V130, P463, DOI 10.1016/j.pgeola.2019.04.003
   McCarroll J, 2017, QUATERN INT, V432, P39, DOI 10.1016/j.quaint.2014.12.068
   McCarroll J, 2016, J NAT CONSERV, V30, P90, DOI 10.1016/j.jnc.2016.02.002
   McGuire JL, 2023, P NATL ACAD SCI USA, V120, DOI 10.1073/pnas.2201950120
   McKeever PJ, 2021, Geological World Heritage: a revised global framework for the application of criterion (viii) of the World Heritage Convention Gland Switzerland: IUCN
   Miao YF, 2022, SCIENCE, V378, P1074, DOI 10.1126/science.abo2475
   Migon P, 2016, GEOL SOC SPEC PUBL, V417, P215, DOI 10.1144/SP417.2
   Moore R, 2022, Q J ENG GEOL HYDROGE, V55, DOI 10.1144/qjegh2021-122
   Moreno PI, 2023, QUATERNARY SCI REV, V300, DOI 10.1016/j.quascirev.2022.107899
   Mottl O, 2021, SCIENCE, V372, P860, DOI 10.1126/science.abg1685
   Murton JB, 2015, P GEOLOGIST ASSOC, V126, P18, DOI 10.1016/j.pgeola.2014.11.003
   Napier JD, 2022, GLOBAL ECOL BIOGEOGR, V31, P138, DOI 10.1111/geb.13416
   Neiva J, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-19620-7
   Newbold T, 2019, EMERG TOP LIFE SCI, V3, P207, DOI 10.1042/ETLS20180135
   Nieto-Lugilde D, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac1b59
   Nogué S, 2021, SCIENCE, V372, P488, DOI 10.1126/science.abd6706
   Nogués-Bravo D, 2016, NAT CLIM CHANGE, V6, P1115, DOI [10.1038/NCLIMATE3146, 10.1038/nclimate3146]
   Nogués-Bravo D, 2018, TRENDS ECOL EVOL, V33, P765, DOI 10.1016/j.tree.2018.07.005
   Palli J, 2023, ECOL APPL, V33, DOI 10.1002/eap.2758
   Palmer A.P., 2021, Landscapes and Landforms of Scotland, P299
   Parkes M., 2020, The Geological Heritage of County Leitrim. An Audit of County Geological Sites in County Leitrim
   Pearson RG, 2016, TRENDS ECOL EVOL, V31, P366, DOI 10.1016/j.tree.2016.02.005
   Pearson S, 2015, HOLOCENE, V25, P366, DOI 10.1177/0959683614558650
   Pereira DI, 2015, P GEOLOGIST ASSOC, V126, P252, DOI 10.1016/j.pgeola.2015.01.003
   Pressey RL, 2007, TRENDS ECOL EVOL, V22, P583, DOI 10.1016/j.tree.2007.10.001
   Prosser C.D., 2018, Geoheritage, P193
   Prosser CD, 2013, P GEOLOGIST ASSOC, V124, P561, DOI 10.1016/j.pgeola.2013.04.003
   Radley JD, 2013, P GEOLOGIST ASSOC, V124, P653, DOI 10.1016/j.pgeola.2012.07.001
   Rea BR, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aar8327
   Rex CL, 2023, QUATERNARY SCI REV, V299, DOI 10.1016/j.quascirev.2022.107882
   Reynard E., 2020, The geotourism industry in the 21st century, P147
   Reynard E., 2018, Geoheritage, P147
   Rick TC, 2013, CONSERV BIOL, V27, P45, DOI 10.1111/j.1523-1739.2012.01920.x
   Riedinger-Whitmore MA, 2016, MAR FRESHWATER RES, V67, P707, DOI 10.1071/MF14319
   Rivera-Núñez T, 2021, ENVIRON CONSERV, V48, P1, DOI 10.1017/S0376892920000399
   Roche JR, 2018, FORESTS, V9, DOI 10.3390/f9060350
   Rodrigues J, 2023, GEOHERITAGE, V15, DOI 10.1007/s12371-023-00800-5
   Rull V, 2015, QUATERNARY SCI REV, V115, P28, DOI 10.1016/j.quascirev.2015.03.003
   Rull V., 2020, QUATERNARY ECOLOGY E
   Rull V, 2015, J VEG SCI, V26, P603, DOI 10.1111/jvs.12278
   Salama A., 2020, Parks, V26, P37
   Sayama K, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su142114096
   Schillereff DN, 2019, GLOBAL PLANET CHANGE, V182, DOI 10.1016/j.gloplacha.2019.102998
   Schlaepfer MA, 2023, WIRES CLIM CHANGE, V14, DOI 10.1002/wcc.798
   Schrodt F, 2019, P NATL ACAD SCI USA, V116, P16155, DOI 10.1073/pnas.1911799116
   Seddon AWR, 2014, J ECOL, V102, P256, DOI 10.1111/1365-2745.12195
   Shaw H., 2013, Cultural severance and the environment: The ending of traditional and customary practice on commons and landscapes managed in common, V2, P311
   Shumilovskikh L, 2021, BIODIVERS CONSERV, V30, P4061, DOI 10.1007/s10531-021-02292-7
   Simensen T, 2021, NORSK GEOGR TIDSSKR, V75, P79, DOI 10.1080/00291951.2021.1892177
   Smeaton C, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.593324
   Spicer RA, 2020, PLANT DIVERSITY, V42, P229, DOI 10.1016/j.pld.2020.06.011
   Stallins JA, 2018, GEOMORPHOLOGY, V305, P76, DOI 10.1016/j.geomorph.2017.09.012
   Stewart IS, 2021, GEOL SOC SPEC PUBL, V508, P265, DOI 10.1144/SP508-2020-101
   Stewart IS, 2013, P GEOLOGIST ASSOC, V124, P699, DOI 10.1016/j.pgeola.2012.08.008
   Svenning JC, 2002, BIOL CONSERV, V104, P133, DOI 10.1016/S0006-3207(01)00162-8
   Temmerman S, 2013, NATURE, V504, P79, DOI 10.1038/nature12859
   Theobald DM, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0143619
   Thomas MF, 2012, SCOT GEOGR J, V128, P195, DOI 10.1080/14702541.2012.725863
   Thompson JC, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abf9776
   Tierney JE, 2020, SCIENCE, V370, P680, DOI 10.1126/science.aay3701
   Tisdall E., 2023, Proceedings of the Geologists' Association
   Toivanen M, 2019, J BIOGEOGR, V46, P1711, DOI 10.1111/jbi.13648
   Trew BT, 2021, GLOBAL ECOL BIOGEOGR, V30, P768, DOI 10.1111/geb.13272
   Tscharntke T, 2012, BIOL REV, V87, P661, DOI 10.1111/j.1469-185X.2011.00216.x
   Tukiainen H., 2022, Geological Society, London, Spe- cial Publications, V530, P31
   Tukiainen H, 2023, CONSERV BIOL, V37, DOI 10.1111/cobi.14024
   Turvey ST, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2019.0208
   Tye GJ, 2016, J QUATERNARY SCI, V31, P75, DOI 10.1002/jqs.2840
   UK Statutory Nature Conservation Bodies, 2022, Nature recovery for our survival, prosperity and wellbeing. A joint statement by the Statutory Nature Conservation Bodies of the UK
   UNESCO, 2016, UNESCO GLOB GEOP CEL
   UNESCO, 2017, UNESCO Global Geoparks Contributing to the Sustainable Development Goals: Celebrating Earth Heritage, Sustaining Local Communities
   van der Leeuw S, 2011, ECOL SOC, V16, DOI 10.5751/ES-04341-160402
   Van Meerbeek K, 2019, BIOSCIENCE, V69, P997, DOI 10.1093/biosci/biz106
   Vegas-Vilarrúbia T, 2011, QUATERNARY SCI REV, V30, P2361, DOI 10.1016/j.quascirev.2011.05.006
   Wallis GP, 2016, TRENDS ECOL EVOL, V31, P916, DOI 10.1016/j.tree.2016.08.009
   Wenban-Smith F., 2013, OXFORD ARCHAEOLOGY M, V20
   White T.S., 2023, Proceedings of the Geologists' Association
   Whyte Ian, 2006, International Journal of Biodiversity Science & Management, V2, P138
   Wignall RML, 2018, P GEOLOGIST ASSOC, V129, P120, DOI 10.1016/j.pgeola.2017.11.003
   Willis KJ, 2006, SCIENCE, V314, P1261, DOI 10.1126/science.1122667
   Willis KJ, 2010, TRENDS ECOL EVOL, V25, P583, DOI 10.1016/j.tree.2010.07.006
   Willis KJ, 2007, PHILOS T R SOC B, V362, P175, DOI 10.1098/rstb.2006.1977
   Willis KJ, 2010, SYST BIODIVERS, V8, P3, DOI 10.1080/14772000903495833
   Willis KJ, 2009, SCIENCE, V326, P806, DOI 10.1126/science.1178838
   Wilson OJ, 2021, QUATERNARY SCI REV, V264, DOI 10.1016/j.quascirev.2021.107005
   Wimbledon W.A.P., 2012, Geoheritage in Europe and its conservation, P1
   Wingard GL, 2017, FRONT ECOL EVOL, V5, DOI 10.3389/fevo.2017.00011
   Yin QZ, 2015, QUATERNARY SCI REV, V120, P28, DOI 10.1016/j.quascirev.2015.04.008
   Young KR, 2020, ANN AM ASSOC GEOGR, V111, P880, DOI 10.1080/24694452.2020.1785833
NR 251
TC 1
Z9 1
U1 3
U2 15
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0016-7878
J9 P GEOLOGIST ASSOC
JI Proc. Geol. Assoc.
PD AUG
PY 2023
VL 134
IS 4
BP 375
EP 387
DI 10.1016/j.pgeola.2023.07.003
EA AUG 2023
PG 13
WC Geology; Paleontology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Paleontology
GA S4NQ5
UT WOS:001070955200001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Maharjan, KL
   Singh, M
   Gonzalvo, CM
AF Maharjan, Keshav Lall
   Singh, Manjeshwori
   Gonzalvo, Clarisse Mendoza
TI Drivers of environmental conservation agriculture and women farmer
   empowerment in Namobuddha municipality, Nepal
SO JOURNAL OF AGRICULTURE AND FOOD RESEARCH
LA English
DT Article
DE Environmental conservation agriculture; Climate change mitigation;
   Organic farming; Namobuddha municipality; Women farmer empowerment;
   Climate -smart agriculture
ID HILLS
AB In 2045, Nepal aims to be carbon neutral by reducing its net emissions in various sectors, most especially in agriculture. Environmental conservation agriculture (ECA) is proven to mitigate climate change effects; however, more efforts are needed to increase its uptake in Nepal. This study, therefore, identified factors that influence ECA continuation among farmers in Namobuddha municipality-one of Nepal's central hubs for organic farming. Using binary logistic regression, seven ECA drivers were identified, with the rise of sea temperature or extremely hot days (under perceived climate change effects) and incentives or subsidies from the government decreasing the odds of ECA continuation among Namobuddha farmers. Meanwhile, the five positive ECA drivers arranged in decreasing odds ratio are: 1) ECA interest; 2) local market/hat bazar (periodical open-market) (under selling place of ECA products); 3) resource-use decision-making (under women decision-making in ECA); 4) ameliorating pests/ diseases (under climate change adaptation); and 5) perception that ECA is economically, socially, and environmen-tally sustainable. This study also reaffirms the knowledge gap between farmers' understanding of ECA and its actual climate change mitigation capabilities, which was also observed in previous studies that identified ECA drivers. The strategic dissemination of information about ECA is thus recommended to further increase farmers' interest in ECA, which was identified as the number one factor driving ECA continuation. Communication of ECA's economic, environmental, and social sustainability is also critical, as farmers are still mostly unaware of this matter. In terms of women empowerment, this study suggests engaging women more in resource-use de-cision-making (i.e., technology, labor, energy usage, etc.), which could also increase women's ECA continuation. Lastly, this research also found that the lack of knowledge, training, and opportunities remains the primary obstacle to women's engagement in ECA, whereas profitability, better livelihood, and resource availability serve as the main motivators.
C1 [Maharjan, Keshav Lall; Gonzalvo, Clarisse Mendoza] Hiroshima Univ, Grad Sch Humanities & Social Sci, Higashihiroshima, Japan.
   [Singh, Manjeshwori] Nepal Dev Res Inst, Gender & Livelihood Program Intermittent, Lalitpur, Nepal.
C3 Hiroshima University
RP Maharjan, KL (corresponding author), Hiroshima Univ, Grad Sch Humanities & Social Sci, Higashihiroshima, Japan.
EM mkeshav@hiroshima-u.ac.jp
RI Gonzalvo, Clarisse/KDN-2297-2024; Maharjan, Keshav Lall/B-6851-2014
OI Gonzalvo, Clarisse/0000-0001-5988-2827; Maharjan, Keshav
   Lall/0000-0001-5885-4162
CR Adegbeye MJ, 2020, J CLEAN PROD, V242, DOI 10.1016/j.jclepro.2019.118319
   [Anonymous], 2010, CLIM SMART AGR POL P
   [Anonymous], 2008, The millennium development goals report
   Balayar R, 2021, WORLD DEV PERSPECT, V21, DOI 10.1016/j.wdp.2021.100298
   Baniya R., 2018, J TOURISM HOSPITALIT, V8, P77, DOI [10.3126/jthe.v8i0.20012, DOI 10.3126/JTHE.V8I0.20012]
   Bhatta G. D., 2010, Journal of Agriculture and Environment, V11, P26
   Brown C, 2007, RENEW AGR FOOD SYST, V22, P20, DOI 10.1017/S1742170507001561
   Devkota D., 2017, Journal of Agriculture and Forestry University, V1, P35
   Food and Agriculture Organization of the United Nations, 2019, CONS AGR TRAIN GUID
   Food and Agriculture Organization of the United Nations, 2002, GEND ACC LAND
   Food and Agriculture Organization of United Nations, 2017, The Future of Food and agriculture: Trends and Challenges
   Global Green Growth Institute, 2018, NAM MUN NEP SIT AN G
   Gonzalvo CM, 2020, J RURAL STUD, V74, P10, DOI 10.1016/j.jrurstud.2019.11.007
   Gonzalvo CM, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14137919
   Gonzalvo CM, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11090857
   Government of Nepal, 2021, NEP LONG TERM STRAT
   Government of Nepal Ministry of Finance, 2021, EC SURVEY 2020 21
   Halbrendt J, 2014, MT RES DEV, V34, P214, DOI 10.1659/MRD-JOURNAL-D-13-00083.1
   International Labor Organization (ILO), 2019, Eight Ways to Grow Nepals Agricultural Sector: A Rapid Market Assessment and Ranking of Agricultural Sub-Sectors
   Johnson JMF, 2007, ENVIRON POLLUT, V150, P107, DOI 10.1016/j.envpol.2007.06.030
   Joshi N.P., 2010, Journal of International Development and Coorporation, V16, P1, DOI DOI 10.15027/29802
   Kakamoukas G, 2021, TELECOM, V2, P52, DOI 10.3390/telecom2010005
   Khatri-Chhetri A, 2020, CLIMATIC CHANGE, V158, P29, DOI 10.1007/s10584-018-2350-8
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Maharjan KL, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14169881
   Maharjan KL, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095296
   Maharjan KL, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132011312
   Maharjan S.K., 2020, J CONTEMPINDIA STUD, V10, P17, DOI [10.15027/49124, DOI 10.15027/49124]
   Ministry of Agriculture Forestry and Fisheries (MAFF), 2020, SUMMARY ANN REP FOOD
   Ministry of Agriculture Forestry and Fisheries (MAFF), BAS CONC ENV CONS TY
   Mona S, 2021, CHEMOSPHERE, V275, DOI 10.1016/j.chemosphere.2021.129856
   Nyasimi M., 2017, Agriculture for Development, P37
   Ojha HR, 2017, J RURAL STUD, V53, P156, DOI 10.1016/j.jrurstud.2017.05.012
   Paudel B, 2020, ENVIRON RES, V188, DOI 10.1016/j.envres.2020.109711
   Pillarisetti RamJ., 1998, Development Policy Review, V16, P197, DOI DOI 10.1111/1467-7679.00059
   Rai R, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11195267
   Raut N., 2013, CGIAR RES PROGRAM CL, V47
   Resurrección BP, 2013, WOMEN STUD INT FORUM, V40, P33, DOI 10.1016/j.wsif.2013.03.011
   Shisler RC, 2019, SOC NATUR RESOUR, V32, P875, DOI 10.1080/08941920.2019.1597234
   Singh M., 2017, Sustainability of Organic Farming in Nepal, P21, DOI [10.1007/978-981-10-5619-2_2, DOI 10.1007/978-981-10-5619-2_2]
   Takeshi F., 2015, J INT EC STUDIES, P29
   Ulak N., 2022, The Gaze Journal of Tourism and Hospitality, V13, P1
   United Nations, 2015, SUSTAIN DEV
   van der Heijden T, 2013, AGREKON, V52, P68, DOI 10.1080/03031853.2013.778466
   Zewdu A., 2016, J CULTURE SOC DEV, V26, P20
   Zollet S, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13020866
NR 46
TC 6
Z9 6
U1 0
U2 6
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2666-1543
J9 J AGR FOOD RES
JI J. Agric. Food Res.
PD SEP
PY 2023
VL 13
AR 100631
DI 10.1016/j.jafr.2023.100631
EA MAY 2023
PG 11
WC Agriculture, Multidisciplinary; Food Science & Technology
WE Emerging Sources Citation Index (ESCI)
SC Agriculture; Food Science & Technology
GA I6XW4
UT WOS:001004204900001
OA gold
DA 2025-01-10
ER

PT J
AU Aschale, TM
   Palazzolo, N
   Peres, DJ
   Sciuto, G
   Cancelliere, A
AF Aschale, Tagele Mossie
   Palazzolo, Nunziarita
   Peres, David J.
   Sciuto, Guido
   Cancelliere, Antonino
TI An Assessment of Trends of Potential Evapotranspiration at Multiple
   Timescales and Locations in Sicily from 2002 to 2022
SO WATER
LA English
DT Article
DE climate change; temperature; drought; irrigation; Mediterranean area;
   Penman-Monteith
ID RIVER-BASIN; SPATIOTEMPORAL VARIATIONS; CLIMATE-CHANGE; WIND-SPEED;
   CHINA; VARIABILITY; DROUGHT
AB Climate change and the related temperature rise can cause an increase in evapotranspiration. Thus, the assessment of potential evapotranspiration (PET) trends is important to identify possible ongoing signals of climate change, in order to develop adaptation measures for water resource management and improve irrigation efficiency. In this study, we capitalize on the data available from a network of 46 complete meteorological stations in Sicily that cover a period of about 21 years (2002-2022) to estimate PET by the Food and Agriculture Organization (FAO) using the Penman-Monteith method at the daily time scale in Sicily (southern Italy). We then analyse the trends of PET and assess their significance by Sen's Slope and the Mann-Kendall test at multiple temporal scales (monthly, seasonal, and annual). Most of the locations do not show significant trends. For instance, at the annual timescale, only five locations have a significantly increasing trend. However, there are many locations where the monthly trend is statistically significant. The number of locations where monthly trend is significant is maximum for August, where 18 out of these 46 stations have an increasing trend. In contrast, in March, there are no locations with a significant trend. The location with the highest increasing trend of PET indicates trend slopes of 1.73, 3.42, and 10.68 mm/year at monthly (August), seasonal (summer), and annual timescales, respectively. In contrast, decreasing PET trends are present only at the monthly and seasonal scales, with a maximum of, respectively, -1.82 (July) and -3.28 (summer) mm/year. Overall, the findings of this study are useful for climate change adaptation strategies to be pursued in the region.
C1 [Aschale, Tagele Mossie; Palazzolo, Nunziarita; Peres, David J.; Cancelliere, Antonino] Univ Catania, Dept Civil Engn & Architecture, Via A Doria 6, I-95125 Catania, Italy.
   [Aschale, Tagele Mossie] Debre Markos Univ, Dept Geog & Environm Studies, POB 269, Debre Markos, Ethiopia.
   [Sciuto, Guido] Ambiens Srl, Via Roma 44, I-94019 Valguarnera Caropepe, Italy.
C3 University of Catania
RP Peres, DJ (corresponding author), Univ Catania, Dept Civil Engn & Architecture, Via A Doria 6, I-95125 Catania, Italy.
EM djperes@dica.unict.it
RI Cancelliere, Antonino/G-9775-2013; PALAZZOLO, NUNZIARITA/ABC-5745-2021;
   Peres, David/AAG-9289-2020
OI Palazzolo, Nunziarita/0000-0002-4885-1889; Peres,
   David/0000-0003-4387-6291; Aschale, Tagele Mossie/0000-0002-4082-9716
FU Ambiens S.r.l; University of Catania;  [LIFE17CCA/IT/000115-CUP
   C65H18000550006]
FX This research was funded by Ambiens S.r.l through a grant with
   University of Catania signed on 23 July 2020, and it was partially
   carried out within the project HydrEx-Hydrological extremes in a
   changing climate-Piano di incentivi per la ricerca di Ateneo
   (Pia.ce.ri.), 2020-2022, Universita di Catania. Nunziarita Palazzolo is
   supported by post-doctoral contract "Eventi idrologici estremi e
   resilienza ai cambiamenti climatici", funded within the activities of
   the research project "LIFE SimetoRES-Urban adaption and community
   learning for a RESilient Simeto Valley"-grant agreement no.
   LIFE17CCA/IT/000115-CUP C65H18000550006.
CR Ahmad I, 2015, ADV METEOROL, V2015, DOI 10.1155/2015/431860
   Aieb A, 2022, MODEL EARTH SYST ENV, V8, P5251, DOI 10.1007/s40808-022-01453-z
   Alemu H, 2015, WATER-SUI, V7, P4914, DOI 10.3390/w7094914
   Aschale TM, 2023, WATER-SUI, V15, DOI 10.3390/w15030470
   Bian YM, 2020, THEOR APPL CLIMATOL, V140, P1161, DOI 10.1007/s00704-020-03154-y
   Bonaccorso B, 2015, J HYDROL, V526, P136, DOI 10.1016/j.jhydrol.2015.01.070
   Capra A, 2013, WATER RESOUR MANAG, V27, P601, DOI 10.1007/s11269-012-0204-0
   Chaouche K, 2010, CR GEOSCI, V342, P234, DOI 10.1016/j.crte.2010.02.001
   Chu RH, 2019, INT J CLIMATOL, V39, P4072, DOI 10.1002/joc.6060
   Crespi A, 2021, INT J CLIMATOL, V41, P162, DOI 10.1002/joc.6614
   Darshana, 2013, STOCH ENV RES RISK A, V27, P1407, DOI 10.1007/s00477-012-0677-7
   Ding YX, 2021, THEOR APPL CLIMATOL, V145, P79, DOI 10.1007/s00704-021-03625-w
   Diop L., 2016, Eur. Sci. J, V12, P231, DOI [DOI 10.19044/ESJ.2016.V12N12P231, 10.19044/esj.2016.v12n12p231]
   Dong Q, 2020, INT J CLIMATOL, V40, P235, DOI 10.1002/joc.6206
   Elferchichi A, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9122337
   Eymen A, 2019, METEOROL ATMOS PHYS, V131, P601, DOI 10.1007/s00703-018-0591-8
   Fischer EM, 2021, NAT CLIM CHANGE, V11, P689, DOI 10.1038/s41558-021-01092-9
   Guo Q, 2020, WATER-SUI, V12, DOI 10.3390/w12113250
   Han XY, 2015, METEOROL APPL, V22, P586, DOI 10.1002/met.1490
   He D, 2013, FRONT EARTH SCI-PRC, V7, P417, DOI 10.1007/s11707-013-0381-z
   Hu MC, 2019, WATER-SUI, V11, DOI 10.3390/w11091782
   Huang HP, 2015, ADV METEOROL, V2015, DOI 10.1155/2015/519207
   Hui-Mean F, 2018, ATMOS RES, V201, P102, DOI 10.1016/j.atmosres.2017.10.014
   Hwang JH, 2020, PADDY WATER ENVIRON, V18, P235, DOI 10.1007/s10333-019-00777-4
   Jerin JN, 2021, THEOR APPL CLIMATOL, V144, P793, DOI 10.1007/s00704-021-03566-4
   Kamal N., 2019, Int. Jour. Comput. Appl, V177, P7, DOI [10.5120/ijca2019919453, DOI 10.5120/IJCA2019919453]
   Lang DX, 2017, WATER-SUI, V9, DOI 10.3390/w9100734
   Li WZ, 2021, EARTH SYST ENVIRON, V5, P285, DOI 10.1007/s41748-021-00213-w
   Li XC, 2013, QUATERN INT, V304, P133, DOI 10.1016/j.quaint.2013.02.027
   Li ZX, 2014, QUATERN INT, V336, P127, DOI 10.1016/j.quaint.2013.12.045
   Liu Q, 2018, THEOR APPL CLIMATOL, V132, P387, DOI 10.1007/s00704-017-2060-6
   Liuzzo L, 2016, THEOR APPL CLIMATOL, V123, P43, DOI 10.1007/s00704-014-1342-5
   Luo Y, 2021, WATER-SUI, V13, DOI 10.3390/w13091222
   Macek U, 2018, AGR FOREST METEOROL, V260, P183, DOI 10.1016/j.agrformet.2018.06.014
   Maruyama Atsushi, 2004, Journal of Agricultural Meteorology, V60, P1, DOI 10.2480/agrmet.60.1
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   [Masson-Delmotte V. IPCC. IPCC.], 2018, Global warming of 1.5C: Ipcc special report on impacts of global warming of 1.5C above pre-industrial levels in context of strengthening response to climate change, sustainable development, and efforts to eradicate poverty, P616, DOI [DOI 10.1017/9781009157940, 10.1017/9781009157940, DOI 10.1017/9781009157940.003]
   Nam WH, 2015, AGR WATER MANAGE, V150, P129, DOI 10.1016/j.agwat.2014.11.019
   Ndiaye PM, 2020, WATER-SUI, V12, DOI 10.3390/w12071957
   Ndulue E, 2021, THEOR APPL CLIMATOL, V143, P1285, DOI 10.1007/s00704-020-03505-9
   Palumbo A. D., 2011, Irrigation and Drainage Systems, V25, P395, DOI 10.1007/s10795-012-9132-7
   Panda A, 2019, ATMOS SCI LETT, V20, DOI 10.1002/asl.932
   Páscoa P, 2021, WEATHER CLIM EXTREME, V32, DOI 10.1016/j.wace.2021.100320
   Peng LL, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-05660-y
   Peng SZ, 2017, AGR FOREST METEOROL, V233, P183, DOI 10.1016/j.agrformet.2016.11.129
   Peng ZJ, 2017, J HYDROL ENG, V22, DOI 10.1061/(ASCE)HE.1943-5584.0001558
   Peres DJ, 2019, WATER-SUI, V11, DOI 10.3390/w11122531
   Piticar A, 2016, THEOR APPL CLIMATOL, V124, P1133, DOI 10.1007/s00704-015-1490-2
   Pour SH, 2020, ATMOS RES, V246, DOI 10.1016/j.atmosres.2020.105096
   Ranzi R, 2021, INT J CLIMATOL, V41, P181, DOI 10.1002/joc.6678
   Ruiz-Alvarez M, 2021, WATER-SUI, V13, DOI 10.3390/w13020222
   Shadmani M, 2012, WATER RESOUR MANAG, V26, P211, DOI 10.1007/s11269-011-9913-z
   Shan N, 2015, AGR FOREST METEOROL, V200, P322, DOI 10.1016/j.agrformet.2014.10.008
   Shi TT, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2008JD010174
   Stefanidis S, 2021, HYDROLOGY-BASEL, V8, DOI 10.3390/hydrology8040160
   Tellen V.A., 2017, Earth Perspect, V4, P17, DOI [10.1186/s40322-017-0039-1, DOI 10.1186/S40322-017-0039-1]
   Todisco F, 2008, AGR FOREST METEOROL, V148, P1, DOI 10.1016/j.agrformet.2007.08.014
   Tomas-Burguera M, 2021, INT J CLIMATOL, V41, pE1860, DOI 10.1002/joc.6817
   Torina A, 2006, EXP APPL ACAROL, V38, P75, DOI 10.1007/s10493-005-5629-1
   Utset A, 2004, AGR WATER MANAGE, V66, P205, DOI 10.1016/j.agwat.2003.12.003
   Vergni L, 2011, AGR FOREST METEOROL, V151, P301, DOI 10.1016/j.agrformet.2010.11.005
   Vicente-Serrano SM, 2014, GLOBAL PLANET CHANGE, V121, P26, DOI 10.1016/j.gloplacha.2014.06.005
   Vila-Traver J, 2021, SCI TOTAL ENVIRON, V760, DOI 10.1016/j.scitotenv.2020.143399
   Wang R, 2022, INT J CLIMATOL, V42, P10126, DOI 10.1002/joc.7887
   Wang ZL, 2017, J HYDROL, V544, P97, DOI 10.1016/j.jhydrol.2016.11.021
   Wu H, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0252840
   Yang JH, 2021, J WATER CLIM CHANGE, V12, P325, DOI 10.2166/wcc.2020.221
   Yu WJ, 2016, ADV METEOROL, V2016, DOI 10.1155/2016/9586896
   Zeng JX, 2022, ATMOS OCEAN SCI LETT, V15, DOI 10.1016/j.aosl.2021.100143
   Zhang F, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-74384-3
   Zhao YF, 2018, THEOR APPL CLIMATOL, V133, P711, DOI 10.1007/s00704-017-2216-4
   Zuo DP, 2012, HYDROL PROCESS, V26, P1149, DOI 10.1002/hyp.8206
NR 72
TC 1
Z9 1
U1 0
U2 4
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD APR
PY 2023
VL 15
IS 7
AR 1273
DI 10.3390/w15071273
PG 17
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA D7GO8
UT WOS:000970376100001
OA gold
DA 2025-01-10
ER

PT J
AU Zerfass, C
   Lehmann, R
   Ueberschaar, N
   Sanchez-Arcos, C
   Totsche, KU
   Pohnert, G
AF Zerfass, Christian
   Lehmann, Robert
   Ueberschaar, Nico
   Sanchez-Arcos, Carlos
   Totsche, Kai Uwe
   Pohnert, Georg
TI Groundwater metabolome responds to recharge in fractured sedimentary
   strata
SO WATER RESEARCH
LA English
DT Article
DE Groundwater; Dissolved Organic Matter; Recharge; Discharge;
   Metabolomics; Aquifer
ID DISSOLVED ORGANIC-MATTER; MASS-SPECTROMETRY; FLOW PATHS; LAND-USE;
   AQUIFERS; SOIL; PERSISTENCE; MODELS; CYCLE
AB Understanding the sources, structure and fate of dissolved organic matter (DOM) in groundwater is paramount for the protection and sustainable use of this vital resource. On its passage through the Critical Zone, DOM is subject to biogeochemical conversions. Therefore, it carries valuable cross-habitat information for monitoring and predicting the stability of groundwater ecosystem services and assessing these ecosystems' response to fluctuations caused by external impacts such as climatic extremes. Challenges arise from insufficient knowledge on groundwater metabolite composition and dynamics due to a lack of consistent analytical approaches for long-term monitoring. Our study establishes groundwater metabolomics to decipher the complex biogeochemical transport and conversion of DOM. We explore fractured sedimentary bedrock along a hillslope recharge area by a 5-year untargeted metabolomics monitoring of oxic perched and anoxic phreatic groundwater. A summer with extremely high temperatures and low precipitation was included in the monitoring. Water was accessed by a monitoring well-transect and regularly collected for liquid chromatography-mass spectrometry (LC-MS) investigation. Dimension reduction of the resulting complex data set by principal component analysis revealed that metabolome dissimilarities between distant wells coincide with transient cross-stratal flow indicated by groundwater levels. Time series of the groundwater metabolome data provides detailed insights into subsurface responses to recharge dynamics. We demonstrate that dissimilarity variability between groundwater bodies with contrasting aquifer properties coincides with recharge dynamics. This includes groundwater high- and lowstands as well as recharge and recession phases. Our monitoring approach allows to survey groundwater ecosystems even under extreme conditions. Notably, the metabolome was highly variable lacking seasonal patterns and did not segregate by geographical location of sampling wells, thus ruling out vegetation or (agricultural) land use as a primary driving factor. Patterns that emerge from metabolomics monitoring give insight into subsurface ecosystem functioning and water quality evolution, essential for sustainable groundwater use and climate change-adapted management.
C1 [Zerfass, Christian; Sanchez-Arcos, Carlos; Pohnert, Georg] Friedrich Schiller Univ, Inst Inorgan & Analyt Chem, Dept Bioorgan Analyt, Jena, Germany.
   [Lehmann, Robert; Totsche, Kai Uwe] Friedrich Schiller Univ, Inst Geosci, Dept Hydrogeol, Jena, Germany.
   [Ueberschaar, Nico] Friedrich Schiller Univ, Fac Chem & Earth Sci, Mass Spectrometry Platform, Jena, Germany.
   [Sanchez-Arcos, Carlos] Univ Cologne, Fac Math & Sci, Inst Zool, Cologne, Germany.
C3 Friedrich Schiller University of Jena; Friedrich Schiller University of
   Jena; Friedrich Schiller University of Jena; University of Cologne
RP Pohnert, G (corresponding author), Friedrich Schiller Univ, Inst Inorgan & Analyt Chem, Dept Bioorgan Analyt, Jena, Germany.
EM georg.pohnert@uni-jena.de
RI Pohnert, Georg/D-3721-2013; Zerfaß, Christian/JEO-8793-2023; Totsche,
   Kai Uwe/E-2086-2013
OI Totsche, Kai Uwe/0000-0002-2692-213X; Zerfass,
   Christian/0000-0001-8960-1926; Ueberschaar, Nico/0000-0002-4192-490X;
   Sanchez-Arcos, Carlos/0000-0001-7576-8063
FU DFG [SFB 1076, 218627073, EXC 2051, 390713860]
FX DFG SFB 1076, project number 218627073, "AquaDiva". EXC 2051 Project-ID
   390713860 "Balance of the Microverse".
CR [Anonymous], 1994, Groundwater Ecology, DOI DOI 10.1016/B978-0-08-050762-0.50011-5
   Antonelli J, 2019, METABOLITES, V9, DOI 10.3390/metabo9070143
   Aukes PJK, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0253972
   Benischke R, 2021, HYDROGEOL J, V29, P67, DOI 10.1007/s10040-020-02278-9
   Benk SA, 2019, FRONT EARTH SC-SWITZ, V7, DOI 10.3389/feart.2019.00296
   Benk SA, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00168
   Benton HP, 2010, BIOINFORMATICS, V26, P2488, DOI 10.1093/bioinformatics/btq441
   Bonneau J, 2018, J HYDROL, V561, P413, DOI 10.1016/j.jhydrol.2018.04.022
   Bowen GJ, 2019, ANNU REV EARTH PL SC, V47, P453, DOI 10.1146/annurev-earth-053018-060220
   Chambers MC, 2012, NAT BIOTECHNOL, V30, P918, DOI 10.1038/nbt.2377
   Chorover J, 2001, GEOCHIM COSMOCHIM AC, V65, P95, DOI 10.1016/S0016-7037(00)00511-1
   Cooksey R.W., 2020, Illus Stat Proc, DOI [DOI 10.1007/978-981-15-2537-75, 10.1007/978-981-15-2537-7_5, 10.1007/978-981-15-2537-7_5$, DOI 10.1007/978-981-15-2537-7_5$, DOI 10.1007/978-981-15-2537-7_5]
   Crimmins BS, 2019, ADV EXP MED BIOL, V1140, P731, DOI 10.1007/978-3-030-15950-4_43
   Danczak RE, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-19989-y
   Drake TW, 2020, GLOBAL CHANGE BIOL, V26, P1374, DOI 10.1111/gcb.14889
   Erian W., 2021, GAR Special Report on Drought 2021
   Fernandes JP, 2021, TOXICS, V9, DOI 10.3390/toxics9100257
   Franco D, 2017, GROUNDWATER, V55, P784, DOI 10.1111/gwat.12529
   Garayburu-Caruso VA, 2020, METABOLITES, V10, DOI 10.3390/metabo10120518
   Grant GE, 2017, WATER RESOUR RES, V53, P2605, DOI 10.1002/2017WR020835
   Haug K, 2020, NUCLEIC ACIDS RES, V48, pD440, DOI 10.1093/nar/gkz1019
   Hawkes JA, 2020, LIMNOL OCEANOGR-METH, V18, P235, DOI 10.1002/lom3.10364
   Hofmann R, 2020, FRONT MICROBIOL, V11, DOI 10.3389/fmicb.2020.543567
   Huber W, 2015, NAT METHODS, V12, P115, DOI [10.1038/NMETH.3252, 10.1038/nmeth.3252]
   Hudak P.F, 2004, PRINCIPLES HYDROGEOL, DOI [10.1201/9781420057911, DOI 10.1201/9781420057911]
   Humphrey V, 2016, SURV GEOPHYS, V37, P357, DOI 10.1007/s10712-016-9367-1
   Ivanisevic J, 2019, METABOLITES, V9, DOI 10.3390/metabo9120308
   Jasechko S, 2014, WATER RESOUR RES, V50, P8845, DOI 10.1002/2014WR015809
   Jiang S., 2021, ENVIRON REV, V29, P242, DOI [10.1139/er-2020-0093, DOI 10.1139/ER-2020-0093]
   Kaiser K, 2012, SOIL BIOL BIOCHEM, V52, P29, DOI 10.1016/j.soilbio.2012.04.002
   Kohlhepp B, 2017, HYDROL EARTH SYST SC, V21, P6091, DOI 10.5194/hess-21-6091-2017
   Küsel K, 2016, FRONT EARTH SC-SWITZ, V4, DOI 10.3389/feart.2016.00032
   Nguyen LH, 2019, PLOS COMPUT BIOL, V15, DOI 10.1371/journal.pcbi.1006907
   Lazar CS, 2019, SCI TOTAL ENVIRON, V679, P35, DOI 10.1016/j.scitotenv.2019.04.281
   Lehmann J, 2015, NATURE, V528, P60, DOI 10.1038/nature16069
   Lehmann R, 2020, J HYDROL, V580, DOI 10.1016/j.jhydrol.2019.124291
   Li L, 2017, EARTH-SCI REV, V165, P280, DOI 10.1016/j.earscirev.2016.09.001
   Lu QY, 2020, SCI TOTAL ENVIRON, V742, DOI 10.1016/j.scitotenv.2020.140491
   Lynch LM, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-08406-8
   Miller MJ, 2015, J INHERIT METAB DIS, V38, P1029, DOI 10.1007/s10545-015-9843-7
   Patriarca C, 2021, J AM SOC MASS SPECTR, V32, P394, DOI 10.1021/jasms.0c00353
   Pemberton JA, 2020, RAPID COMMUN MASS SP, V34, DOI 10.1002/rcm.8618
   Phillips T, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052495
   Portner H.-O., 2022, IPCC, 2022: Climate Change 2022: Impacts, Adaptation
   Raats M. M., 1991, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Raeke J, 2017, WATER RES, V113, P149, DOI 10.1016/j.watres.2017.01.066
   Richardson J.B, 2017, ENCY GEOCHEMISTRY, DOI [10.1007/978-3-319-39193-9_355-1, DOI 10.1007/978-3-319-39193-9_355-1]
   Riebe CS, 2017, EARTH SURF PROC LAND, V42, P128, DOI 10.1002/esp.4052
   Riedel T, 2020, HYDROGEOL J, V28, P1939, DOI 10.1007/s10040-020-02165-3
   Rodell M, 2018, NATURE, V557, P650, DOI 10.1038/s41586-018-0123-1
   Rodríguez-Cardona BM, 2022, GLOBAL CHANGE BIOL, V28, P98, DOI 10.1111/gcb.15965
   Roth VN, 2019, NAT GEOSCI, V12, P755, DOI 10.1038/s41561-019-0417-4
   Sanchez-Arcos C, 2022, WATER RES, V219, DOI 10.1016/j.watres.2022.118566
   Schmidt MWI, 2011, NATURE, V478, P49, DOI 10.1038/nature10386
   Schwab VF, 2017, BIOGEOSCIENCES, V14, P2697, DOI 10.5194/bg-14-2697-2017
   Seifert AG, 2016, SCI TOTAL ENVIRON, V571, P142, DOI 10.1016/j.scitotenv.2016.07.033
   Smith CA, 2006, ANAL CHEM, V78, P779, DOI 10.1021/ac051437y
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tanentzap AJ, 2019, P NATL ACAD SCI USA, V116, P24689, DOI 10.1073/pnas.1904896116
   Tautenhahn R, 2008, BMC BIOINFORMATICS, V9, DOI 10.1186/1471-2105-9-504
   Tweed SO, 2005, HYDROGEOL J, V13, P771, DOI 10.1007/s10040-004-0348-y
   Ueberschaar N, 2021, FRONT EARTH SC-SWITZ, V8, DOI 10.3389/feart.2020.563379
   Wada Y, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010562
   Wang B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118537
   White WB, 2012, GROUND WATER, V50, P180, DOI 10.1111/j.1745-6584.2012.00923.x
   Wologo E, 2021, GLOBAL BIOGEOCHEM CY, V35, DOI 10.1029/2020GB006719
   Worley B, 2013, CURR METABOL, V1, P92, DOI 10.2174/2213235X11301010092
   Yan LJ, 2021, WATER RES, V201, DOI 10.1016/j.watres.2021.117290
   Yan LJ, 2020, WATER RES, V170, DOI 10.1016/j.watres.2019.115341
   YUILL RS, 1971, GEOGR ANAL, VB 53, P28, DOI 10.2307/490885
   ZerfaSS Christian, 2022, Metabolights
   Zhang JC, 2021, ENVIRON SCI TECHNOL, V55, P7741, DOI 10.1021/acs.est.1c01283
NR 72
TC 2
Z9 2
U1 3
U2 36
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0043-1354
EI 1879-2448
J9 WATER RES
JI Water Res.
PD SEP 1
PY 2022
VL 223
AR 118998
DI 10.1016/j.watres.2022.118998
PG 11
WC Engineering, Environmental; Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Environmental Sciences & Ecology; Water Resources
GA 6M3ZU
UT WOS:000888810300005
PM 36030668
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Silva, LCR
   Wood, MC
   Johnson, BR
   Coughlan, MR
   Brinton, H
   McGuire, K
   Bridgham, SD
AF Silva, Lucas C. R.
   Wood, Mary C.
   Johnson, Bart R.
   Coughlan, Michael R.
   Brinton, Heather
   McGuire, Krista
   Bridgham, Scott D.
TI A generalizable framework for enhanced natural climate solutions
SO PLANT AND SOIL
LA English
DT Article
DE Climate change mitigation; Climate change adaptation; Data science;
   Environmental justice
ID WILLAMETTE VALLEY; CARBON; URBAN; LANDSCAPE; FIRE; SOIL; ACCUMULATION;
   BIODIVERSITY; MANAGEMENT; FORESTS
AB Background The natural removal of carbon dioxide (CO2) from the atmosphere through land conservation, restoration, and management is receiving increasing attention as a scalable approach for climate change mitigation. However, different land-use sectors compete for resources and incentives within and across geopolitical regions, resulting in divergent goals and inefficient prioritization of CO2 removal efforts. Thus, a unifying framework is needed to accelerate basic research and coordinated interventions to accelerate climate change mitigation.
   Scope We propose a generalizable framework for Enhanced Natural Climate Solutions (NCS +), which we define as activities that can be coordinated to increase carbon drawdown and permanence on land while improving livelihoods and the provision of natural resources in vulnerable communities and ecosystems. The framework builds on interdisciplinary scientific convergence, including critical socioecological interactions, to inform both top-down policy incentives and bottom-up adoption by industries and managers. To achieve this goal, we suggest a multi-tiered approach for the prioritization of projects at local to regional scales that would simultaneously accelerate scientific discovery and broad implementation of CO2 removal projects.
   Conclusions Our vision leverages input from hundreds of researchers and land managers, including social and environmental scientists as well as representatives from tribal governments, state, and federal agencies in the Pacific Northwest of the USA, as a model system. Five guiding principles orient the framework which would be applicable in any region. As evidence of feasibility, we provide a synthesis of interdisciplinary studies that illustrate how coordinated action, with explicit consideration of system-specific technical and socioecological limitations, can lead to scalable projects with multiple co-benefits. Using theory as a linchpin for innovation, we propose that NCS + could better align climate change mitigation, adaptation, and justice goals at multiple scales.
C1 [Silva, Lucas C. R.; McGuire, Krista; Bridgham, Scott D.] Univ Oregon, Inst Ecol & Evolut, Eugene, OR 97403 USA.
   [Silva, Lucas C. R.] Univ Oregon, Environm Studies & Biol, Eugene, OR 97403 USA.
   [Silva, Lucas C. R.; McGuire, Krista; Bridgham, Scott D.] Univ Oregon, Dept Biol, Eugene, OR 97403 USA.
   [Silva, Lucas C. R.] Univ Oregon, Eugene, OR 97403 USA.
   [Wood, Mary C.; Brinton, Heather] Univ Oregon, Environm & Nat Resources Law Ctr, Eugene, OR 97403 USA.
   [Johnson, Bart R.] Univ Oregon, Dept Landscape Architecture, Eugene, OR 97403 USA.
   [Coughlan, Michael R.] Univ Oregon, Inst Sustainable Environm, Eugene, OR 97403 USA.
   [Bridgham, Scott D.] Univ Oregon, Environm Studies Program, Eugene, OR 97403 USA.
C3 University of Oregon; University of Oregon; University of Oregon;
   University of Oregon; University of Oregon; University of Oregon;
   University of Oregon; University of Oregon
RP Silva, LCR (corresponding author), Univ Oregon, Eugene, OR 97403 USA.
EM lsilva7@uoregon.edu
RI Johnson, Bart/KVZ-0728-2024; Silva, Lucas/IUM-2802-2023; coughlan,
   michael/X-7634-2019; Bridgham, Scott/R-1557-2017; Silva,
   Lucas/E-1202-2016
OI Bridgham, Scott/0000-0003-0614-2678; Silva, Lucas/0000-0002-4838-327X;
   Coughlan, Michael/0000-0001-6071-1873
FU National Science Foundation Convergence Accelerator Program (Landscape
   Carbon Sequestration for Atmospheric Recovery) [1939511]; Office Of The
   Director; Office of Integrative Activities [1939511] Funding Source:
   National Science Foundation
FX We thank the National Science Foundation Convergence Accelerator Program
   (Landscape Carbon Sequestration for Atmospheric Recovery. Grant
   #1939511) and all participating scientists, practitioners, policy
   scholars, state and tribal representatives whose pilot ideas helped
   inspire this piece. As organizers of the first NCS+ conference we would
   like to thank all contributors listed below:
CR Abatzoglou JT, 2016, P NATL ACAD SCI USA, V113, P11770, DOI 10.1073/pnas.1607171113
   Abatzoglou JT, 2012, INT J CLIMATOL, V32, P772, DOI 10.1002/joc.2312
   Ager AA, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0172867
   Anderies JM, 2019, P NATL ACAD SCI USA, V116, P5277, DOI 10.1073/pnas.1802885115
   Anderson CM, 2019, SCIENCE, V363, P933, DOI 10.1126/science.aaw2741
   [Anonymous], 2016, WORLDS CITIES 2016, DOI DOI 10.18356/8519891F-EN
   [Anonymous], 2019, J. Open Res. Softw, DOI DOI 10.5334/JORS.232
   Bak-Coleman JB, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2025764118
   Baldocchi D, 2019, GLOBAL CHANGE BIOL, V25, pE5, DOI 10.1111/gcb.14654
   Beerling DJ, 2020, NATURE, V583, P242, DOI 10.1038/s41586-020-2448-9
   Betts RA, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2016.0452
   Bomfim B, 2020, SCI TOTAL ENVIRON, V714, DOI 10.1016/j.scitotenv.2020.136780
   Bomfim B, 2019, BIOGEOCHEMISTRY, V142, P137, DOI 10.1007/s10533-018-0525-z
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Bossio DA, 2020, NAT SUSTAIN, V3, P391, DOI 10.1038/s41893-020-0491-z
   Braunreiter L, 2021, ENERGY RES SOC SCI, V80, DOI 10.1016/j.erss.2021.102220
   Brodrick PG, 2019, GEOPHYS RES LETT, V46, P2752, DOI 10.1029/2018GL081108
   Brown C, 2019, NAT CLIM CHANGE, V9, P203, DOI 10.1038/s41558-019-0400-5
   Brown MA, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2100008118
   BUSCH KC, 2019, INT J SCI ED, P1
   Chadwick KD, 2018, ECOL LETT, V21, P978, DOI 10.1111/ele.12963
   Chen ZG, 2015, J CLEAN PROD, V87, P558, DOI 10.1016/j.jclepro.2014.10.057
   Correa-Díaz A, 2019, J GEOPHYS RES-BIOGEO, V124, P166, DOI 10.1029/2018JG004687
   Cox E, 2021, FRONT CLIM, V3, DOI 10.3389/fclim.2021.576294
   Damon M, 2019, REV ENV ECON POLICY, V13, P23, DOI 10.1093/reep/rey017
   Daszak P, 2020, BIOSAF HEALTH, V2, P6, DOI 10.1016/j.bsheal.2020.01.003
   Davis EJ, 2020, FOREST POLICY ECON, V111, DOI 10.1016/j.forpol.2019.102042
   Di Marco M, 2020, P NATL ACAD SCI USA, V117, P3888, DOI 10.1073/pnas.2001655117
   Duarte-Guardia S, 2019, MITIG ADAPT STRAT GL, V24, P355, DOI 10.1007/s11027-018-9815-y
   Durrer A, 2021, BIOGEOCHEMISTRY, V152, P179, DOI 10.1007/s10533-020-00743-x
   Erb KH, 2018, NATURE, V553, P73, DOI 10.1038/nature25138
   ESRI, 2019, US CENS POP PLAC AR
   Fargione JE, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aat1869
   Ferguson L, 2017, LANDSCAPE URBAN PLAN, V157, P447, DOI 10.1016/j.landurbplan.2016.08.014
   Fischer AP, 2017, ECOL SOC, V22, DOI 10.5751/ES-08867-220123
   Georgiou K, 2021, BIOGEOCHEMISTRY, V156, P5, DOI 10.1007/s10533-021-00819-2
   Goldman EB, 2019, CLIMATE SCI RES US U
   Goldstein A, 2020, NAT CLIM CHANGE, V10, P287, DOI 10.1038/s41558-020-0738-8
   Graham BS, 2018, NAT IMMUNOL, V19, P20, DOI 10.1038/s41590-017-0007-9
   Graves RA, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0230424
   Groffman PM, 2017, ECOSYSTEMS, V20, P38, DOI 10.1007/s10021-016-0053-4
   Günther A, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15499-z
   Hahm WJ, 2014, P NATL ACAD SCI USA, V111, P3338, DOI 10.1073/pnas.1315667111
   Harris NL, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00976-6
   Harrison DP, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5ef5
   Hasegawa T, 2018, NAT CLIM CHANGE, V8, P699, DOI 10.1038/s41558-018-0230-x
   Hilaire J, 2019, CLIMATIC CHANGE, V157, P189, DOI 10.1007/s10584-019-02516-4
   Hulse D, 2016, LANDSCAPE URBAN PLAN, V156, P26, DOI 10.1016/j.landurbplan.2016.05.012
   Jaeger WK, 2019, NAT SUSTAIN, V2, P710, DOI 10.1038/s41893-019-0326-y
   Jaeger WK, 2017, P NATL ACAD SCI USA, V114, P11884, DOI 10.1073/pnas.1706847114
   Johnson BR, 2022, ROUTLEDGE HDB SUSTAI, DOI 10.4324/9781003033530
   Johnson L, 2014, ECON GEOGR, V90, P155, DOI 10.1111/ecge.12048
   Jones JA, 2020, HYDROL PROCESS, V34, P4814, DOI 10.1002/hyp.13910
   Kelemen P, 2019, FRONT CLIM, V1, DOI 10.3389/fclim.2019.00009
   Kramer HA, 2018, INT J WILDLAND FIRE, V27, P329, DOI 10.1071/WF17135
   Lake FK, 2017, J FOREST, V115, P343, DOI 10.5849/jof.2016-043R2
   Lehmann J, 2020, NATURE, V583, P204, DOI 10.1038/d41586-020-01965-7
   Liang YL, 2019, SCI TOTAL ENVIRON, V648, P116, DOI 10.1016/j.scitotenv.2018.07.341
   Liles GC, 2013, SOIL SCI SOC AM J, V77, P2173, DOI 10.2136/sssaj2013.02.0057
   Lombardi M, 2017, ENVIRON IMPACT ASSES, V66, P43, DOI 10.1016/j.eiar.2017.06.005
   Lovelock CE, 2015, NATURE, V526, P559, DOI 10.1038/nature15538
   Marull J, 2018, SCI TOTAL ENVIRON, V619, P1272, DOI 10.1016/j.scitotenv.2017.11.196
   MAXWELL T, 2020, TRENDS PLANT SCI
   Maxwell TM, 2018, P NATL ACAD SCI USA, V115, pE4219, DOI 10.1073/pnas.1718864115
   Mills M, 2016, CONSERV LETT, V9, P361, DOI 10.1111/conl.12213
   Müller B, 2017, GLOBAL ENVIRON CHANG, V46, P23, DOI 10.1016/j.gloenvcha.2017.06.010
   Mueller RC, 2016, FUNCT ECOL, V30, P1845, DOI 10.1111/1365-2435.12651
   National Research Council, 2014, Convergence: facilitating transdisciplinary integration of life sciences, physical sciences, engineering, and beyond
   Nave LE, 2018, P NATL ACAD SCI USA, V115, P2776, DOI 10.1073/pnas.1719685115
   Nielsen-Pincus M, 2015, LANDSCAPE URBAN PLAN, V137, P1, DOI 10.1016/j.landurbplan.2014.11.020
   Nowak DJ, 2018, URBAN FOR URBAN GREE, V32, P32, DOI 10.1016/j.ufug.2018.03.006
   Ostrom E, 2010, GLOBAL ENVIRON CHANG, V20, P550, DOI 10.1016/j.gloenvcha.2010.07.004
   OSU, 2022, INT MAP
   Penteado HM, 2013, LANDSCAPE ECOL, V28, P1909, DOI 10.1007/s10980-013-9940-7
   Penteado HM, 2021, URBAN ECOSYST, V24, P753, DOI 10.1007/s11252-020-01074-3
   Pierson D, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.527803
   Poteete AR, 2010, WORKING TOGETHER: COLLECTIVE ACTION, THE COMMONS, AND MULTIPLE METHODS IN PRACTICE, P1
   Qiu CJ, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abf1332
   Radeloff VC, 2018, P NATL ACAD SCI USA, V115, P3314, DOI 10.1073/pnas.1718850115
   Ramos-Castillo A, 2017, CLIMATIC CHANGE, V140, P1, DOI 10.1007/s10584-016-1873-0
   Reise J., 2022, Nature-based solutions and global climate protection
   Roe S, 2021, GLOBAL CHANGE BIOL, V27, P6025, DOI 10.1111/gcb.15873
   Ruwaimana M, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb853
   Schell CJ, 2020, SCIENCE, V369, P1446, DOI 10.1126/science.aay4497
   Schlesinger WH, 2019, GLOBAL CHANGE BIOL, V25, P386, DOI 10.1111/gcb.14478
   Schultz CA, 2019, SCIENCE, V366, P38, DOI 10.1126/science.aay3727
   Seddon N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0120
   Sheil D, 2016, ENVIRON CONSERV, V43, P231, DOI 10.1017/S0376892916000011
   Silva LCR, 2021, PLANT SOIL, V461, P5, DOI 10.1007/s11104-020-04427-1
   Silva LCR, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-020-20184-2
   Silva LCR, 2015, ECOL APPL, V25, P1226, DOI 10.1890/14-2151.1
   Silva LCR, 2013, ECOL APPL, V23, P1345, DOI 10.1890/12-1957.1
   Skidmore AK, 2019, SCIENCE, V366, DOI 10.1126/science.aaz0111
   Smith RM, 2018, OECOLOGIA, V187, P1107, DOI [10.1007/s00442-018-4194-3, 10.10]
   Spence E, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-03050-y
   Spies TA, 2014, ECOL SOC, V19, DOI 10.5751/ES-06584-190309
   Strefler J, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa9c4
   Tobias S, 2018, LAND DEGRAD DEV, V29, P2015, DOI 10.1002/ldr.2919
   Turner WR, 2018, NAT CLIM CHANGE, V8, P18, DOI 10.1038/s41558-017-0048-y
   UN Climate Change Conference UK, 2021, HOME UN CLIMATE CHAN
   Verbruggen E, 2021, PLANTS PEOPLE PLANET, V3, P445, DOI 10.1002/ppp3.10179
   Wheaton M, 2016, J SUSTAIN TOUR, V24, P594, DOI 10.1080/09669582.2015.1081600
   Winsome T, 2017, FOREST ECOL MANAG, V384, P415, DOI 10.1016/j.foreco.2016.10.036
   Wood, 2016, ENV LAW, DOI 10.2307/43432851
   Wu H, 2019, RIVER RES APPL, V35, P818, DOI 10.1002/rra.3454
   Wu H, 2015, LANDSCAPE URBAN PLAN, V144, P74, DOI 10.1016/j.landurbplan.2015.08.012
   Zald HSJ, 2018, ECOL APPL, V28, P1068, DOI 10.1002/eap.1710
NR 107
TC 7
Z9 8
U1 3
U2 23
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0032-079X
EI 1573-5036
J9 PLANT SOIL
JI Plant Soil
PD OCT
PY 2022
VL 479
IS 1-2
SI SI
BP 3
EP 24
DI 10.1007/s11104-022-05472-8
EA JUN 2022
PG 22
WC Agronomy; Plant Sciences; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences
GA 6G9WF
UT WOS:000812455700001
DA 2025-01-10
ER

PT J
AU Nishikawa, S
   Wakamatsu, T
   Ishizaki, H
   Sakamoto, K
   Tanaka, Y
   Tsujino, H
   Yamanaka, G
   Kamachi, M
   Ishikawa, Y
AF Nishikawa, Shiro
   Wakamatsu, Tsuyoshi
   Ishizaki, Hiroshi
   Sakamoto, Kei
   Tanaka, Yusuke
   Tsujino, Hiroyuki
   Yamanaka, Goro
   Kamachi, Masafumi
   Ishikawa, Yoichi
TI Development of high-resolution future ocean regional projection datasets
   for coastal applications in Japan
SO PROGRESS IN EARTH AND PLANETARY SCIENCE
LA English
DT Article
DE Ocean future projection; Dynamical downscaling; Ocean model; CMIP5
ID VOLUME TRANSPORT; WARM CURRENT; KUROSHIO; MODEL; VARIABILITY; STRAITS;
   CMIP5; STATE; WATER; SEA
AB In this study, we developed two high-resolution future ocean regional projection datasets for coastal applications in Japan, in which we made use of dynamical downscaling via regional ocean models with atmospheric forcing from two climate models (i.e., MIROC5 and MRI-CGCM3) participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) under historical, representative concentration pathway (RCP) 2.6, and RCP8.5 scenarios. The first dataset was an eddy-resolving 10-km resolution product covering the North Pacific Ocean area and ranging continuously from 1981 to 2100, in which the Kuroshio current and mesoscale structures were reasonably resolved. The second dataset was a 2-km resolution product covering the regional domain surrounding Japan and comprising 10-15-year time slices, in which the coastal geometry and current structure were resolved even more realistically. An important feature of these datasets was the availability of reference datasets based on atmospheric and oceanic reanalysis data for cross-validation during the historical run period. Using these reference datasets, biases of regional surface thermal properties and the Kuroshio states during the historical run period were evaluated, which constitute important information for users of the datasets. In these downscaled datasets, the future surface thermal responses were generally consistent with those of their original data. Utilizing the high-resolution property of the downscaled data, possible future impact analyses regarding coastal phenomena such as strait throughflows, coastal sea level variability, and the Kuroshio intrusion phenomenon into bays ("Kyucho" phenomenon) were demonstrated and the important role of the Kuroshio state representation was indicated, which had proved difficult to analyze using the low-resolution projection data. Given these properties, the present datasets would be useful in climate change adaptation studies regarding the Japanese coastal region.
C1 [Nishikawa, Shiro; Ishizaki, Hiroshi; Tanaka, Yusuke; Kamachi, Masafumi; Ishikawa, Yoichi] Japan Agcy Marine Earth Sci & Technol, Kanazawa Ku, 3173-25 Showa Machi, Yokohama, Kanagawa 2360001, Japan.
   [Wakamatsu, Tsuyoshi] Nansen Ctr, Bergen, Norway.
   [Wakamatsu, Tsuyoshi] Bjerknes Ctr Climate Res, Bergen, Norway.
   [Sakamoto, Kei; Tsujino, Hiroyuki; Yamanaka, Goro] Japan Meteorol Agcy, Meteorol Res Inst, Tsukuba, Ibaraki, Japan.
C3 Japan Agency for Marine-Earth Science & Technology (JAMSTEC); Bjerknes
   Centre for Climate Research; Meteorological Research Institute - Japan;
   Japan Meteorological Agency
RP Nishikawa, S (corresponding author), Japan Agcy Marine Earth Sci & Technol, Kanazawa Ku, 3173-25 Showa Machi, Yokohama, Kanagawa 2360001, Japan.
EM snishika@jamstec.go.jp
OI TSUJINO, Hiroyuki/0000-0003-3336-0275
FU Nansen Center (NERSC); Social Implementation Program on Climate Change
   Adaptation Technology (SI-CAT) [JPMXD0715667163]; Integrated Research
   Program for Advancing Climate Models (TOUGOU) - Ministry of Education,
   Culture, Sports, Science and Technology of Japan [JPMXD0717935561]
FX TW was supported partially by the Nansen Center (NERSC) basic funding.
   This study was supported by the Social Implementation Program on Climate
   Change Adaptation Technology (SI-CAT: grant no. JPMXD0715667163) and the
   Integrated Research Program for Advancing Climate Models (TOUGOU: grant
   no. JPMXD0717935561) sponsored by the Ministry of Education, Culture,
   Sports, Science and Technology of Japan.
CR Alexander MA, 2020, J CLIMATE, V33, P405, DOI 10.1175/JCLI-D-19-0117.1
   Alexander MA, 2018, ELEMENTA-SCI ANTHROP, V6, DOI 10.1525/elementa.191
   [Anonymous], 2020, SI CAT SI CAT REPORT
   Aoki K, 2008, J OCEANOGR, V64, P49, DOI 10.1007/s10872-008-0004-6
   Fukudome K, 2010, J OCEANOGR, V66, P539, DOI 10.1007/s10872-010-0045-5
   Han S, 2016, OCEAN DYNAM, V66, P59, DOI 10.1007/s10236-015-0896-9
   Hermann AJ, 2016, DEEP-SEA RES PT II, V134, P30, DOI 10.1016/j.dsr2.2015.11.001
   Hermans THJ, 2020, CLIM DYNAM, V54, P1987, DOI 10.1007/s00382-019-05104-5
   Imawaki S, 2001, GEOPHYS RES LETT, V28, P17, DOI 10.1029/2000GL011796
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Isobe A, 2002, J GEOPHYS RES-OCEANS, V107, DOI 10.1029/2000JC000702
   Ito T, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2003GL017522
   Kobayashi S, 2015, J METEOROL SOC JPN, V93, P5, DOI 10.2151/jmsj.2015-001
   Levitus S., 1994, TEMPERATURE, P99
   Levitus S., 1994, Temperature, V4, P117
   Li R, 2017, J GEOPHYS RES-OCEANS, V122, P2871, DOI 10.1002/2016JC012468
   Liu ZJ, 2016, J OCEANOGR, V72, P905, DOI 10.1007/s10872-016-0390-0
   Matsuyama M, 1999, CONT SHELF RES, V19, P1561, DOI 10.1016/S0278-4343(99)00031-X
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Nishikawa H, 2020, PROG EARTH PLANET SC, V7, DOI 10.1186/s40645-020-00342-2
   Ohshima KI, 2017, J PHYS OCEANOGR, V47, P999, DOI 10.1175/JPO-D-16-0210.1
   Oppenheimer M., IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, DOI [10.1017/9781009157964.006, DOI 10.1017/9781009157964.006, DOI 10.1126/SCIENCE.AAM6284]
   Pedlosky J., 1996, OCEAN CIRCULATION TH
   Qiu B, 2006, J PHYS OCEANOGR, V36, P457, DOI 10.1175/JPO2849.1
   Sakamoto K, 2019, OCEAN DYNAM, V69, P1181, DOI 10.1007/s10236-019-01291-1
   Sakamoto K, 2016, OCEAN DYNAM, V66, P77, DOI 10.1007/s10236-015-0908-9
   Sakamoto TT, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023384
   Sato Y, 2006, J METEOROL SOC JPN, V84, P295, DOI 10.2151/jmsj.84.295
   Stocker TF., 2013, The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P3
   Sun CJ, 2012, J CLIMATE, V25, P2947, DOI 10.1175/JCLI-D-11-00159.1
   Suzuki T, 2018, J OCEANOGR, V74, P421, DOI 10.1007/s10872-017-0458-5
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Toste R, 2018, CLIM DYNAM, V51, P143, DOI 10.1007/s00382-017-3911-7
   Troselj J., 2018, J Japan Soc Civ Eng Ser B2 (Coastal Eng), V74, pI_1357, DOI [10.2208/kaigan.74.i_1357, 10.2208/kaigan.74.I_1357, DOI 10.2208/KAIGAN.74.I_1357]
   Tsujino H, 2017, TECHNICAL REPORTS MR, V80
   Tsujino H, 2010, TECHNICAL REPORTS MR
   Tsujino H, 2008, J OCEANOGR, V64, P141, DOI 10.1007/s10872-008-0011-7
   Usui N, 2016, OCEANIC FRONTS JETS, DOI [10.1007/978-4-431-56053-1_1, DOI 10.1007/978-4-431-56053-1_1]
   Usui N, 2017, J OCEANOGR, V73, P205, DOI 10.1007/s10872-016-0398-5
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P95, DOI 10.1007/s10584-011-0152-3
   Watanabe M, 2010, J CLIMATE, V23, P6312, DOI 10.1175/2010JCLI3679.1
   Xiu P, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-21247-7
   Yasuda I, 2003, J OCEANOGR, V59, P389, DOI 10.1023/A:1025580313836
   Yukimoto S, 2012, J METEOROL SOC JPN, V90A, P23, DOI 10.2151/jmsj.2012-A02
NR 44
TC 23
Z9 23
U1 1
U2 53
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 2197-4284
J9 PROG EARTH PLANET SC
JI Prog. Earth Planet. Sci.
PD JAN 14
PY 2021
VL 8
IS 1
AR 7
DI 10.1186/s40645-020-00399-z
PG 22
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA PR9GE
UT WOS:000607538300001
OA gold
DA 2025-01-10
ER

PT J
AU Tan, XC
   Zhu, KW
   Meng, XY
   Gu, BH
   Wang, Y
   Meng, FX
   Liu, GY
   Tu, TQ
   Li, H
AF Tan, Xianchun
   Zhu, Kaiwei
   Meng, Xiaoyan
   Gu, Baihe
   Wang, Yi
   Meng, Fanxin
   Liu, Gengyuan
   Tu, Tangqi
   Li, Hui
TI Research on the status and priority needs of developing countries to
   address climate change
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Addressing climate change; Climate change mitigation and adaptation;
   Addressing climate change needs; Developing countries
ID SOUTH-SOUTH COOPERATION; NORTH-SOUTH; AGRICULTURAL PRODUCTIVITY;
   TECHNOLOGY-TRANSFER; ENERGY DEVELOPMENT; LIVESTOCK SYSTEMS; CHANGE
   MITIGATION; CHANGE ADAPTATION; FOOD SECURITY; IMPACT
AB Identifying what developing countries need to address climate change is of great significance for promoting North-South and South-South climate cooperation and implementing the Paris Agreement. In this study, based on questionnaires surveys of 143 representative government officials, experts, scholars, and industry engineers from developing countries who have been engaged in climate change, the current situation and priority requirements of developing countries in terms of policies and actions, technology, financing, capacity building, and international cooperation for addressing climate change were systematically analyzed. We found that 1. Most developing countries have already taken national general actions and sectoral and industry-level actions focus on renewable or clean energy, waste management and recycling, sustainable urban transport and forestry carbon sequestration. 2. The demands for climate change mitigation are mainly concentrated in technology and capital, and the priority areas are energy and electricity and waste management; for climate change adaptation, the demands differ significantly among regions. 3. Developing countries show high preferences for emission reduction and energy-saving technology, solar energy, wind energy and bio-energy, whereas a low preference for supercritical and ultra supercritical power units, nuclear energy and tidal energy. 4. Agroforestry, energy conservation and efficiency, renewable energy and water resources are priority areas for climate change financing. 5. Building institutional capacity, improving technology R&D networks and institutions, formulation and implementation ability of planning schemes, and data statistics and verification are priority areas needed for capacity building. To better address climate change, developing countries need to establish and improve information exchange channels or platforms and strengthen South-South climate cooperation while optimizing the allocation of climate change resources according to the priority needs.
   (c) 2020 Elsevier Ltd. All rights reserved.
C1 [Tan, Xianchun; Zhu, Kaiwei; Meng, Xiaoyan; Gu, Baihe; Wang, Yi; Tu, Tangqi; Li, Hui] Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China.
   [Tan, Xianchun; Zhu, Kaiwei; Wang, Yi; Tu, Tangqi] Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing 100190, Peoples R China.
   [Meng, Fanxin; Liu, Gengyuan] Beijing Normal Univ, State Key Joint Lab Environm Simulat & Pollut Con, Sch Environm, Beijing 100875, Peoples R China.
C3 Chinese Academy of Sciences; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS; Beijing Normal University
RP Meng, XY (corresponding author), Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China.
EM mengxiaoyan@casisd.cn
RI lu, hao/HZH-4458-2023; ZHU, Kaiwei/JJD-7081-2023; Li, Yan/JRW-0176-2023
OI Meng, Fanxin/0000-0002-8956-4149; Gu, Baihe/0000-0003-2257-8471
FU National Natural Science Foundation of China [71904184]; President Youth
   Fund of the Institutes of Science and Development, Chinese Academy of
   Sciences [E0X3821Q]
FX Support from the National Natural Science Foundation of China (Grant No.
   71904184) and President Youth Fund of the Institutes of Science and
   Development, Chinese Academy of Sciences (Grant No. E0X3821Q) are
   acknowledged.
CR Adenle AA, 2015, J ENVIRON MANAGE, V161, P261, DOI 10.1016/j.jenvman.2015.05.040
   Afonso O, 2013, ECON MODEL, V35, P481, DOI 10.1016/j.econmod.2013.07.036
   Ahmed SA, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/034004
   Amanor KS, 2016, WORLD DEV, V81, P13, DOI 10.1016/j.worlddev.2015.11.021
   [Anonymous], 2016, IEEE ASME T MECHATRO, VPP, P1, DOI DOI 10.1109/ARRAY.2016.7832589
   [Anonymous], 2012, MYANM NAT AD PROGR A
   [Anonymous], PHYS CHEM EARTH
   [Anonymous], 2014, AR5 SYNTHESIS REPORT
   Aronsson T, 2010, RESOUR ENERGY ECON, V32, P292, DOI 10.1016/j.reseneeco.2009.12.001
   Bazilian M, 2011, ENERG POLICY, V39, P3750, DOI 10.1016/j.enpol.2011.04.003
   Begg K, 2001, CLIM POLICY, V1, P285, DOI 10.3763/cpol.2001.0130
   Black G, 2015, RENEW SUST ENERG REV, V43, P83, DOI 10.1016/j.rser.2014.11.011
   Bocchiola D, 2019, AGR SYST, V171, P113, DOI 10.1016/j.agsy.2019.01.008
   Bontenbal M, 2009, HABITAT INT, V33, P100, DOI 10.1016/j.habitatint.2008.05.003
   Borota T, 2012, J INT ECON, V87, P365, DOI 10.1016/j.jinteco.2012.01.002
   Buchner B., 2014, Climate Policy Initiative, V32, P1
   Cao X, 2003, RESOUR POLICY, V29, P61, DOI 10.1016/j.resourpol.2004.05.001
   Chen H, 2015, FOREIGN THEOR TRENDS, V3, P27
   Chen YN, 2018, ENERG POLICY, V116, P1, DOI 10.1016/j.enpol.2017.12.051
   Chen YN, 2018, ENERG POLICY, V115, P561, DOI 10.1016/j.enpol.2017.11.051
   Choi E.K., 2007, International Review of Economics and Finance, V16, P347
   Chu AC, 2015, REV ECON DYNAM, V18, P227, DOI 10.1016/j.red.2014.04.001
   Cimoli M, 2019, RES POLICY, V48, P125, DOI 10.1016/j.respol.2018.08.002
   CSTEC, 2011, S S COOP SCI TECHN A
   Das GG, 2012, TECHNOL FORECAST SOC, V79, P620, DOI 10.1016/j.techfore.2011.05.013
   Dedinec A, 2015, J CLEAN PROD, V88, P234, DOI 10.1016/j.jclepro.2014.05.048
   Dey A, 2014, PROCD SOC BEHV, V157, P317, DOI 10.1016/j.sbspro.2014.11.034
   Drennen TE, 1996, ENERG POLICY, V24, P9, DOI 10.1016/0301-4215(95)00117-4
   Eastin J, 2018, WORLD DEV, V107, P289, DOI 10.1016/j.worlddev.2018.02.021
   Ec, 2018, BUDG SUPP TRENDS RES
   Eeaa, 2016, EG 3 NAT COMM, P1
   Elsharouny MRMM, 2016, PROCEDIA ENVIRON SCI, V34, P348, DOI 10.1016/j.proenv.2016.04.031
   EVANS D, 1987, WORLD DEV, V15, P657, DOI 10.1016/0305-750X(87)90009-X
   Funatsu BM, 2019, GLOBAL ENVIRON CHANG, V57, DOI 10.1016/j.gloenvcha.2019.05.007
   Gampfer R, 2014, GLOBAL ENVIRON CHANG, V29, P118, DOI 10.1016/j.gloenvcha.2014.08.006
   Gancia G, 2008, J INT ECON, V76, P276, DOI 10.1016/j.jinteco.2008.03.010
   Huang D., 2018, ANAL ASEAN COUNTRIES
   Huenteler J, 2016, J CLEAN PROD, V128, P6, DOI 10.1016/j.jclepro.2014.06.056
   Huq S, 2018, RESILIENCE: THE SCIENCE OF ADAPTATION TO CLIMATE CHANGE, P63, DOI 10.1016/B978-0-12-811891-7.00005-0
   International Cooperation and Development Fund (ICDF), 2019, 2018 ANN REP
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Islam Md Monirul, 2019, Aquaculture and Fisheries, V4, P183, DOI 10.1016/j.aaf.2019.02.007
   Islam MM, 2014, MAR POLICY, V43, P208, DOI 10.1016/j.marpol.2013.06.007
   Jones L, 2011, GLOBAL ENVIRON CHANG, V21, P1262, DOI 10.1016/j.gloenvcha.2011.06.002
   Lal R, 2019, SOIL TILL RES, V188, P27, DOI 10.1016/j.still.2017.12.015
   Lattanzio R.K., 2015, GLOBAL CLIMATE CHANG
   Makuvaro V, 2018, J ARID ENVIRON, V152, P75, DOI 10.1016/j.jaridenv.2018.01.016
   Martinot E, 2002, ANNU REV ENERG ENV, V27, P309, DOI 10.1146/annurev.energy.27.122001.083444
   Matenga TFL, 2019, HEALTH RES POLICY SY, V17, DOI 10.1186/s12961-018-0409-7
   Mboumboue E, 2016, RENEW SUST ENERG REV, V61, P266, DOI 10.1016/j.rser.2016.04.003
   McCollum DL, 2018, NAT ENERGY, V3, P589, DOI 10.1038/s41560-018-0179-z
   Meltzer J.P., 2016, Financing low carbon, climate resilient infrastructure: The role of climate finance and green financial systems
   Mendelsohn R, 2017, ATMOSFERA, V30, P77, DOI [10.20937/ATM.2017.30.02.01, 10.20937/atm.2017.30.02.01]
   Mertz O, 2009, ENVIRON MANAGE, V43, P743, DOI 10.1007/s00267-008-9259-3
   Mirza MMQ, 2003, CLIM POLICY, V3, P233, DOI 10.1016/S1469-3062(03)00052-4
   Monasterolo I, 2019, ECOL ECON, V163, P177, DOI 10.1016/j.ecolecon.2019.05.012
   Muhr T, 2015, INT J EDUC DEV, V43, P126, DOI 10.1016/j.ijedudev.2015.04.005
   Nfaoui H, 2004, RENEW ENERG, V29, P1407, DOI 10.1016/S0960-1481(03)00143-5
   Nhemachena C, 2010, CLIM CHANG ECON, V1, DOI 10.1142/S2010007810000066
   Ouyang, 2018, J CONT ASAIA PACIFIC, V2, P92
   Pardoe J, 2018, ENVIRON SCI POLICY, V90, P46, DOI 10.1016/j.envsci.2018.09.020
   Pfeiffer B, 2013, ENERG ECON, V40, P285, DOI 10.1016/j.eneco.2013.07.005
   Rowhani P, 2011, AGR FOREST METEOROL, V151, P449, DOI 10.1016/j.agrformet.2010.12.002
   Rübbelke DTG, 2006, ENERG POLICY, V34, P1600, DOI 10.1016/j.enpol.2004.12.009
   Rübbelke DTG, 2011, ECOL ECON, V70, P1470, DOI 10.1016/j.ecolecon.2011.03.007
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   Schweikert A, 2014, PROCEDIA ENGINEER, V78, P306, DOI 10.1016/j.proeng.2014.07.072
   Seaman JA, 2014, CLIM RISK MANAG, V4-5, P59, DOI 10.1016/j.crm.2014.10.001
   Shahsavari A, 2018, RENEW SUST ENERG REV, V90, P275, DOI 10.1016/j.rser.2018.03.065
   Shankland A, 2016, WORLD DEV, V81, P35, DOI 10.1016/j.worlddev.2016.01.002
   Stadelmann M, 2014, GLOBAL ENVIRON CHANG, V29, P413, DOI 10.1016/j.gloenvcha.2014.04.011
   Stepanok I, 2018, EUR ECON REV, V101, P546, DOI 10.1016/j.euroecorev.2017.10.023
   Suzuki M, 2015, J CLEAN PROD, V98, P229, DOI 10.1016/j.jclepro.2014.08.070
   Nguyen TC, 2013, ECOL ECON, V86, P117, DOI 10.1016/j.ecolecon.2012.11.009
   Thoai TQ, 2018, LAND USE POLICY, V70, P224, DOI 10.1016/j.landusepol.2017.10.023
   Thornton PK, 2009, AGR SYST, V101, P113, DOI 10.1016/j.agsy.2009.05.002
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Uk, 2017, WE WORK
   Unep, 2011, ANG NAT AD PROGR ACT
   Unfccc, 2019, IMPL FRAMW CAP BUILD, P1
   Unfccc, 2017, IMPL FRAM CAP BUILD, P1
   Unfccc, 2013, 3 SYNTH REP TECHN NE, P1
   Unfccc, 2018, SUMM COUNTR PRIOR TE, P1
   Urban F, 2018, ENERG POLICY, V113, P320, DOI 10.1016/j.enpol.2017.11.007
   Urban F, 2015, ENERGY SUSTAIN DEV, V28, P29, DOI 10.1016/j.esd.2015.06.004
   Usa, 2019, WE WORK
   Vietnam, 2019, 3 NATL COMMUNICATION, P1
   Wu, 2011, ENV EC Z, VZ1, P39
   Wu FZ, 2012, J CONTEMP CHINA, V21, P827, DOI 10.1080/10670564.2012.684966
   Younger PL, 2007, GEOFORUM, V38, P828, DOI 10.1016/j.geoforum.2005.10.006
   Zhao X., 2006, ADV CLIM CHANG RES, V2, P250
   Zhao Y, 2005, SPACE POLICY, V21, P213, DOI 10.1016/j.spacepol.2005.05.003
   Zhou XX, 2017, PHYS CHEM EARTH, V101, P214, DOI 10.1016/j.pce.2017.06.011
   1990, FOOD POL, V15, P86
NR 94
TC 31
Z9 33
U1 8
U2 79
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-6526
EI 1879-1786
J9 J CLEAN PROD
JI J. Clean Prod.
PD MAR 20
PY 2021
VL 289
AR 125669
DI 10.1016/j.jclepro.2020.125669
EA JAN 2021
PG 18
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology
GA QK3IP
UT WOS:000620274500004
DA 2025-01-10
ER

PT J
AU Duvat, VKE
   Anisimov, A
   Magnan, AK
AF Duvat, Virginie K. E.
   Anisimov, Ariadna
   Magnan, Alexandre K.
TI Assessment of coastal risk reduction and adaptation-labelled responses
   in Mauritius Island (Indian Ocean)
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Coastal risk reduction; Climate change adaptation; Small Island
   Developing States; Hard protection; Ecosystem-based adaptation; Indian
   Ocean
ID SEA-LEVEL RISE; CLIMATE-CHANGE; CORAL-REEFS; DEVELOPING STATES; TROPICAL
   PACIFIC; PROTECTION; FACE; VULNERABILITY; 21ST-CENTURY; DECISIONS
AB This study assesses changes in coastal risk reduction and adaptation-labelled responses in Mauritius Island since the 1960s. Using research documents, interviews, field observations, image analysis, and case studies, it analyses evolutions in public and private stakeholders' strategies, and the levers and barriers at play. Based on 60 beach sites, it reveals the prevalence (76.7%) of hard protection compared with no response (8.3%), ecosystem-based responses (3.3%), and combined responses (11.7%) and a nation-wide shift from hard and one-size-fits-all responses to soft and place-specific responses. This shift was driven by the failure of initial hard protection measures, which has pushed the Government of Mauritius to improve beach management practices, promote retreat where hard protection had failed, resort to external expertise and funding to design a well-informed risk reduction and adaptation policy, and implement demonstration projects. The "learning-by-doing" process and increased external support have thus allowed progress in risk reduction and adaptation at publicly managed beach sites. In contrast, privately managed (i.e. by residents and hotel companies) beach sites often exhibit increased risks, as a result of the proliferation of uncoordinated technical interventions, related cascading (beach loss, spread of coastal erosion downdrift), and lock-in effects. This study provides guidance for the ground-rooted and systematic analysis of coastal risk reduction and adaptation responses and their drivers at the local and national scale. It could serve as a first basis for framing nation-wide assessments aimed at taking stock of recent progress in coastal risk reduction and adaptation worldwide and help overcome barriers to adaptation.
C1 [Duvat, Virginie K. E.; Magnan, Alexandre K.] La Rochelle Univ, CNRS, UMR 7266, LIENSs, La Rochelle, France.
   [Anisimov, Ariadna; Magnan, Alexandre K.] Sci Po, Iddri, Paris, France.
C3 Centre National de la Recherche Scientifique (CNRS); CNRS - Institute of
   Ecology & Environment (INEE); Institut d'Etudes Politiques Paris
   (Sciences Po)
RP Duvat, VKE (corresponding author), La Rochelle Univ, CNRS, UMR 7266, LIENSs, La Rochelle, France.
EM virginie.duvat@univ-lr.fr; ariadnia.anisimov@iddri.org;
   alexandre.magnan@iddri.org
RI Magnan, Alexandre/I-3377-2017; Duvat, Virginie/GLN-3102-2022
FU French National Research Agency [ANR-15-CE03-0003, ANR-10-LABX-14-01];
   Agence Nationale de la Recherche (ANR) [ANR-15-CE03-0003] Funding
   Source: Agence Nationale de la Recherche (ANR)
FX This work was supported by the French National Research Agency under the
   STORISK (Small island addressing climate change: towards storylines of
   risk and adaptation) research project (No. ANR-15-CE03-0003) and the
   "Investissement d'avenir" programme (NoANR-10-LABX-14-01).
CR Adaptation Fund-UNDP, CLIM CHANG AD PROGR
   Adaptation Fund-UNDP, 2015, CLIM CHANG AD PROGR
   Adaptation Fund-UNDP, 2019, CLIM CHANG AD PROGR
   Anisimov A, 2020, ENVIRON SCI POLICY, V108, P93, DOI 10.1016/j.envsci.2020.03.016
   [Anonymous], 2004, LITTORAUX MASCAREIGN
   [Anonymous], 2013, J GEOGR NATL DISASTE, DOI DOI 10.4172/2167-0587.S1-003
   Bairds WF & Associates coastal engineers Ltd, 2003, STUD COAST ER MAUR, V2
   Bairds WF & Associates coastal engineers Ltd, 2003, STUD COAST ER MAUR, V1
   Beck MW, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04568-z
   Becker M, 2019, TROPICAL EXTREMES: NATURAL VARIABILITY AND TRENDS, P203, DOI 10.1016/B978-0-12-809248-4.0007-8
   Bhatia KT, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-08471-z
   Bheeroo RA, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-5311-4
   Bindoff NL, 2019, CHANGING OCEAN MARIN
   Cohen-Shacham E, 2016, GLAND
   Donner SD, 2014, SUSTAIN SCI, V9, P331, DOI 10.1007/s11625-014-0242-z
   Duvat V, 2009, WIT TRANS ECOL ENVIR, V126, P149, DOI 10.2495/CP090141
   Duvat V, 2013, SUSTAIN SCI, V8, P363, DOI 10.1007/s11625-013-0205-9
   Duvat VKE, 2017, EVALUATION IMPACTS P
   DUVAT VKE, 2019, SCI REP-UK, V9, DOI DOI 10.1038/S41598-019-51
   Elliff CI, 2017, MAR ENVIRON RES, V127, P148, DOI 10.1016/j.marenvres.2017.03.007
   Ferrario F, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4794
   Gattuso JP, 2015, SCIENCE, V349, DOI 10.1126/science.aac4722
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Hinkel J, 2018, NAT CLIM CHANGE, V8, P570, DOI 10.1038/s41558-018-0176-z
   Hughes TP, 2017, NATURE, V546, P82, DOI 10.1038/nature22901
   JICA, 2016, GUID CLIM CHANG AD S
   JICA, 2015, PROJ CAP DEV COAST P, P1
   Kench PS., 2012, Coast. Res. Libr, V3, P165, DOI [DOI 10.1007/978-94-007-4123-2_11, 10.1007/978-94-007-4123-2_11]
   Klöck C, 2019, J ENVIRON DEV, V28, P196, DOI 10.1177/1070496519835895
   Lavenue A, 2010, THESIS
   Lovelock CE, 2015, NATURE, V526, P559, DOI 10.1038/nature15538
   Magnan AK, 2018, ENVIRON SCI POLICY, V89, P393, DOI 10.1016/j.envsci.2018.09.002
   Martínez-Asensio A, 2019, GLOBAL PLANET CHANGE, V176, P132, DOI 10.1016/j.gloplacha.2019.03.008
   McClanahan TR, 2019, NAT CLIM CHANGE, V9, P845, DOI 10.1038/s41558-019-0576-8
   McIntire WG, 1964, 15 LOUIS STAT U COAS, P582
   McLean R, 2015, WIRES CLIM CHANGE, V6, P445, DOI 10.1002/wcc.350
   Mentaschi L, 2017, GEOPHYS RES LETT, V44, P2416, DOI 10.1002/2016GL072488
   Meriwether A, 2018, MAR POLICY, V93, P284, DOI 10.1016/j.marpol.2018.01.018
   MMS (Mauritius Meteorological Services), 2008, DAT SOURTH SWELL EP
   Naylor AK, 2015, PROG PHYS GEOG, V39, P728, DOI 10.1177/0309133315598269
   Nunn PD, 2009, CLIM RES, V40, P211, DOI 10.3354/cr00806
   Onaka S., 2015, Handbook of Coastal Disaster Mitigation for Engineers and Planners, DOI [10.1016/B978-0-12-801060-0.00026-5, DOI 10.1016/B978-0-12-801060-0.00026-5]
   Onaka S, 2018, ASIAN AND PACIFIC COASTS 2017: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON APAC 2017, P651
   Oppenheimer M., IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, DOI [10.1017/9781009157964.006, DOI 10.1017/9781009157964.006, DOI 10.1126/SCIENCE.AAM6284]
   Perry CT, 2019, FUNCT ECOL, V33, P976, DOI 10.1111/1365-2435.13247
   Perry CT, 2018, NATURE, V558, P396, DOI 10.1038/s41586-018-0194-z
   Quataert E, 2015, GEOPHYS RES LETT, V42, P6407, DOI 10.1002/2015GL064861
   Ramessur RT, 2002, REG ENVIRON CHANGE, V3, P99, DOI 10.1007/s10113-002-0045-0
   RoM-MESD (Ministry of Environment and Sustainable Development), 2019, LIST PUBL BEACH
   RoM-MFED (Ministry of Finance and Economic Development), 2017, STAT MAUR DIG ENV ST, V16, P204
   RoM-MHL (Ministry of Housing and Lands), 2004, RES COAST DEV
   RoM-MoE (Ministry of Environment), 2004, TECHNICAL REPORT
   RoM-MoT (Ministry of Tourism), 2018, DIG INT TRAV TOUR ST, P45
   Shope JB, 2016, GLOBAL PLANET CHANGE, V141, P25, DOI 10.1016/j.gloplacha.2016.03.009
   Siders AR, 2019, SCIENCE, V365, P761, DOI 10.1126/science.aax8346
   Storlazzi CD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aap9741
   Temmerman S, 2013, NATURE, V504, P79, DOI 10.1038/nature12859
NR 57
TC 13
Z9 13
U1 1
U2 14
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD SEP 5
PY 2020
VL 20
IS 4
AR 110
DI 10.1007/s10113-020-01699-2
PG 15
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA NM9SW
UT WOS:000568431200002
DA 2025-01-10
ER

PT J
AU Westbrook, CJ
   Ronnquist, A
   Bedard-Haughn, A
AF Westbrook, Cherie J.
   Ronnquist, Amanda
   Bedard-Haughn, Angela
TI Hydrological functioning of a beaver dam sequence and regional dam
   persistence during an extreme rainstorm
SO HYDROLOGICAL PROCESSES
LA English
DT Article
DE 2013 Alberta flood; beaver dams; Canadian Rockies; Castor canadensis;
   nature-based flood solutions; surface hydrology
ID CLIMATE-CHANGE; FLOOD; STREAMS; RESTORATION; WETLANDS; WATER; FAILURE;
   FOREST; BASIN; RIVER
AB It is becoming increasingly popular to reintroduce beaver to streams with the hopes of restoring riparian ecosystem function or reducing some of the hydrological impacts of climate change. One of the risks of relying on beaver to enhance ecosystem water storage is that their dams are reportedly more apt to fail during floods which can exacerbate flood severity. Missing are observations of beaver dam persistence and water storage capacity during floods, information needed to evaluate the risk of relying on beaver as a nature-based flood solution. A June rainstorm in 2013 triggered the largest recorded flood in the Canadian Rocky Mountains west of Calgary, Alberta. We opportunistically recorded hydrometric data during the rainfall event at a beaver-occupied peatland that has been studied for more than a decade. We supplemented these observations with a post-event regional analysis of beaver dam persistence. Results do not support two long-held hypotheses-that beaver ponds have limited flood attenuation capacity and commonly fail during large flood events. Instead we found that 68% of the beaver dam cascade systems across the region were intact or partially intact after the event. Pond fullness, in addition to the magnitude of the water-sediment surge, emerged as important factors in determining the structural fate of dam cascade sequences. Beaver ponds at the instrumented site quickly filled in the first few hours of the rain event and levels were dynamic during the event. Water storage offered by the beaver ponds, even ones that failed, delayed downstream floodwater transmission. Study findings have important implications for reintroducing beaver as part of nature-based restoration and climate change adaptation strategies.
C1 [Westbrook, Cherie J.; Ronnquist, Amanda] Univ Saskatchewan, Ctr Hydrol, Dept Geog & Planning, Saskatoon, SK S7N 5C8, Canada.
   [Bedard-Haughn, Angela] Univ Saskatchewan, Dept Soil Sci, Saskatoon, SK, Canada.
C3 University of Saskatchewan; University of Saskatchewan
RP Westbrook, CJ (corresponding author), Univ Saskatchewan, Ctr Hydrol, Dept Geog & Planning, Saskatoon, SK S7N 5C8, Canada.
EM cherie.westbrook@usask.ca
RI Rønnquist, Anders/AAB-9987-2019
OI Bedard-Haughn, Angela/0000-0002-3971-8509; Westbrook,
   Cherie/0000-0003-1666-3979
FU Canada Foundation for Innovation [13163]; Global Institute of Water
   Security; Global Water Futures; Natural Sciences and Engineering
   Research Council of Canada [463960-2015, RGPIN-2017-05873]; ICANWISE
   undergraduate scholarship
FX Canada Foundation for Innovation, Grant/Award Number: 13163; Global
   Institute of Water Security; Global Water Futures; ICANWISE
   undergraduate scholarship; Natural Sciences and Engineering Research
   Council of Canada, Grant/Award Numbers: 463960-2015, RGPIN-2017-05873
CR Alberta WaterSMART, 2013, 2013 GREAT ALB FLOOD, P27
   Andersen DC, 2010, ECOHYDROLOGY, V3, P325, DOI 10.1002/eco.113
   [Anonymous], 2018, CLIMATIC CHANGE, DOI DOI 10.1007/s10584-017-1972-6
   Beschta RL, 2013, ENVIRON MANAGE, V51, P474, DOI 10.1007/s00267-012-9964-9
   Bokhove O, 2019, RIVER RES APPL, V35, P1402, DOI 10.1002/rra.3507
   Burchsted D, 2014, GEOMORPHOLOGY, V205, P36, DOI 10.1016/j.geomorph.2012.12.029
   Burns DA, 1998, J HYDROL, V205, P248, DOI 10.1016/S0022-1694(98)00081-X
   Butler D.R., 1989, GEOGR BULL, V31, P29
   Butler DR, 2005, GEOMORPHOLOGY, V71, P48, DOI 10.1016/j.geomorph.2004.08.016
   Case B., 2003, GEOHAZARDS 2003, P85
   Cosens B., 2012, ENVIRON LAW, V42, P241
   Dittbrenner BJ, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0192538
   Ecke F, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa8979
   Fang X, 2016, HYDROL PROCESS, V30, P2754, DOI 10.1002/hyp.10910
   Gochis D, 2015, B AM METEOROL SOC, V96, P1461, DOI 10.1175/BAMS-D-13-00241.1
   Green K. C., 2009, BC Journal of Ecosystems and Management, V10, P68
   Grygoruk M, 2014, FORESTS, V5, P2276, DOI 10.3390/f5092276
   Gurnell AM, 1998, PROG PHYS GEOG, V22, P167, DOI 10.1191/030913398673990613
   HEY DL, 1995, RESTOR ECOL, V3, P4, DOI 10.1111/j.1526-100X.1995.tb00070.x
   Hillman GR, 1998, WETLANDS, V18, P21, DOI 10.1007/BF03161439
   Hood GA, 2008, BIOL CONSERV, V141, P556, DOI 10.1016/j.biocon.2007.12.003
   Hopkinson C., 2008, IP3 LIDAR COLLABORAT, P23
   Jakob M, 2016, CAN WATER RESOUR J, V41, P161, DOI 10.1080/07011784.2015.1028451
   Janzen K., 2011, CANADIAN WATER RESOU, V34, P341
   Karran DJ, 2018, ECOHYDROLOGY, V11, DOI 10.1002/eco.1923
   Karran DJ, 2017, HYDROL EARTH SYST SC, V21, P1039, DOI 10.5194/hess-21-1039-2017
   Klimenko DE, 2015, BIOL BULL+, V42, P882, DOI 10.1134/S1062359015100064
   Kundzewicz ZW, 2014, HYDROLOG SCI J, V59, P1, DOI 10.1080/02626667.2013.857411
   Liu AQ, 2016, HYDROL PROCESS, V30, P4899, DOI 10.1002/hyp.10906
   Macias-Fauria M, 2013, P NATL ACAD SCI USA, V110, P8117, DOI 10.1073/pnas.1221278110
   Marston R.A., 1994, Revue de geographie de Lyon, V69, P11
   MCCOMB WC, 1990, GREAT BASIN NAT, V50, P273
   Milrad SM, 2015, MON WEATHER REV, V143, P2817, DOI 10.1175/MWR-D-14-00236.1
   Morrison A, 2018, J FLOOD RISK MANAG, V11, P291, DOI 10.1111/jfr3.12315
   Morrison A, 2015, WETLANDS, V35, P95, DOI 10.1007/s13157-014-0595-1
   NAIMAN RJ, 1988, BIOSCIENCE, V38, P753, DOI 10.2307/1310784
   Neumayer M, 2020, WATER-SUI, V12, DOI 10.3390/w12010300
   Nyssen J, 2011, J HYDROL, V402, P92, DOI 10.1016/j.jhydrol.2011.03.008
   Painter KJ, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00167.1
   Parker M., 1985, 1 N AM RIP C APR 16
   Persico L, 2009, QUATERNARY RES, V71, P340, DOI 10.1016/j.yqres.2008.09.007
   Pilliod DS, 2018, ENVIRON MANAGE, V61, P58, DOI 10.1007/s00267-017-0957-6
   Pomeroy JW, 2016, CAN WATER RESOUR J, V41, P105, DOI 10.1080/07011784.2015.1089190
   Public Safety Canada, 2019, CAN DIS DAT
   Puttock A, 2017, SCI TOTAL ENVIRON, V576, P430, DOI 10.1016/j.scitotenv.2016.10.122
   Staddon Chad, 2018, Environment Systems & Decisions, V38, P330, DOI 10.1007/s10669-018-9702-9
   Sutton-Grier AE, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10020523
   Tamminga AD, 2015, EARTH SURF PROC LAND, V40, P1464, DOI 10.1002/esp.3728
   Toop D.C., 2002, Hydrogeology of the Canmore Corridor and Northwestern Kananaskis Country, Alberta. Alberta Environment
   Vionnet V, 2020, HYDROL EARTH SYST SC, V24, P2141, DOI 10.5194/hess-24-2141-2020
   Vivian B. C., 2017, 37 ARCH SURV ALB
   Wallace J. N., 1927, PASSES ROCKY MOUNTAI, P8
   Wang XY, 2016, GEODERMA, V273, P73, DOI 10.1016/j.geoderma.2016.03.012
   Watson KB, 2016, ECOL ECON, V130, P16, DOI 10.1016/j.ecolecon.2016.05.015
   Westbrook CJ, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004560
   Westbrook CJ, 2017, SCI TOTAL ENVIRON, V574, P183, DOI 10.1016/j.scitotenv.2016.09.045
   Westbrook CJ, 2016, FOREST CHRON, V92, P37, DOI 10.5558/tfc2016-011
   Whitfield CJ, 2015, AMBIO, V44, P7, DOI 10.1007/s13280-014-0575-y
   Williams JE, 2015, FISHERIES, V40, P304, DOI 10.1080/03632415.2015.1049692
   Wingfield T, 2019, AREA, V51, P743, DOI 10.1111/area.12535
   WOO MK, 1990, ARCTIC, V43, P223
NR 61
TC 35
Z9 39
U1 3
U2 52
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0885-6087
EI 1099-1085
J9 HYDROL PROCESS
JI Hydrol. Process.
PD AUG 30
PY 2020
VL 34
IS 18
BP 3726
EP 3737
DI 10.1002/hyp.13828
EA JUL 2020
PG 12
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA MX6KU
UT WOS:000546491400001
DA 2025-01-10
ER

PT J
AU Ali, E
   Egbendewe, AYG
   Abdoulaye, T
   Sarpong, DB
AF Ali, Essossinam
   Egbendewe, Aklesso Y. G.
   Abdoulaye, Tahirou
   Sarpong, Daniel B.
TI Willingness to pay for weather index-based insurance in semi-subsistence
   agriculture: evidence from northern Togo
SO CLIMATE POLICY
LA English
DT Article
DE Agriculture; climate change; adaptation policy; weather index-based
   insurance
ID DROUGHT TOLERANT MAIZE; CLIMATE-CHANGE; CROP INSURANCE; CONTINGENT
   VALUATION; TECHNOLOGY ADOPTION; RAINFALL INSURANCE; ADAPTATION; DEMAND;
   IMPACT; FARMERS
AB The effects of climate change on agricultural production are pushing countries to reconsider risk management policies in their development plans. Opportunities exist to increase agricultural production and improve the policy environment. However, policymakers lack local empirical evidence to provide local solutions to agricultural development in many developing countries, including Togo. This paper assesses farmers' willingness to pay for weather index-based insurance (WII) as a market option for sharing climatic risks. A choice modeling approach is used based on data collected from 704 randomly selected households in northern Togo, West Africa. Statistical analysis of the data shows that dry spells are the major concern of farmers and maize is perceived as the most affected food crop. Results also indicate that respondents are willing to participate in a WII market and would prefer insuring crops, such as maize over sorghum and rice against drought by paying on average about $14.5 per hectare. The results show that WII should not be offered standalone, but interlinked with other factors such as providing drought tolerant and high yielding varieties; loans to organized farmers' groups; and weather information through TV, radio and mobile phones in local languages, while encouraging education to enable the diffusion of more advisory services. These factors are likely to influence positively farmers' preferences in participating in a WII market. Key policy insights
   Very often, insurance is seen as a magic bullet in agricultural risk management policy discussions. A standalone WII could suffer from low adoption, a problem that calls for other policy options. As a climate change adaptation policy, WII could be bundled with other risk-reducing options for a better uptake and to improve farmers' welfare. WII can be an effective channel for farm credit facilities and advisory services, as well as other agricultural risk management interventions.
C1 [Ali, Essossinam] Univ Kara, Fac Econ & Management Sci, Kara, Togo.
   [Egbendewe, Aklesso Y. G.] Univ Lome, Fac Econ & Management Sci, Lome, Togo.
   [Abdoulaye, Tahirou] IITA, Ibadan, Nigeria.
   [Sarpong, Daniel B.] Univ Ghana, Dept Agr Econ & Agribusiness, Accra, Ghana.
C3 University of Lome; CGIAR; International Institute of Tropical
   Agriculture (IITA); University of Ghana
RP Ali, E (corresponding author), Univ Kara, Fac Econ & Management Sci, Kara, Togo.
EM joachimali@hotmail.fr
RI Sarpong, Daniel/P-9584-2019; Ali, Essossinam/T-1225-2019
OI Abdoulaye, Tahirou/0000-0002-8072-1363; Ali,
   Essossinam/0000-0002-7614-7426
FU Alliance for a Green Revolution in Africa (AGRA); International
   Development Research Centre (IDRC); West and Central Africa Council for
   Agricultural Research and Development (CORAF/WECARD); International
   Institute of Tropical Agriculture (IITA)
FX The authors acknowledge the financial support of the Alliance for a
   Green Revolution in Africa (AGRA), International Development Research
   Centre (IDRC), the West and Central Africa Council for Agricultural
   Research and Development (CORAF/WECARD) and the International Institute
   of Tropical Agriculture (IITA) through the grant for thesis writing.
CR *AFDB, 2016, AFR EC OUTL CIT STRU
   Ali Essossinam, 2019, Sarhad Journal of Agriculture, V35, P663, DOI 10.17582/journal.sja/2019/35.3.663.674
   Ali E, 2019, HELIYON, V5, DOI 10.1016/j.heliyon.2019.e01550
   Ali E, 2018, J AGRIC ENVIRON INT, V112, P321, DOI 10.12895/jaeid.20182.778
   [Anonymous], 2014, CLIMATE CHANGE, P2014
   Armendariz Beatriz., 2007, EC MICROFINANCE
   Arrow K., 1993, Fed. Reg, V58, P4601, DOI DOI 10.1002/QJ.49703213905
   Asfaw S, 2016, J AFR ECON, V25, P637, DOI 10.1093/jae/ejw005
   Barnett BJ, 2007, AM J AGR ECON, V89, P1241, DOI 10.1111/j.1467-8276.2007.01091.x
   BESLEY T, 1995, J DEV ECON, V46, P1, DOI 10.1016/0304-3878(94)00045-E
   Bhattacharya H., 2014, Agricultural and Resource Economics Review, V43, P438
   Blamey R, 1999, AUST J AGR RESOUR EC, V43, P337, DOI 10.1111/1467-8489.00083
   Bogale A, 2015, CLIM DEV, V7, P246, DOI 10.1080/17565529.2014.934769
   BOYLE KJ, 1988, AM J AGR ECON, V70, P20, DOI 10.2307/1241972
   Broberg M, 2020, CLIM POLICY, V20, P693, DOI 10.1080/14693062.2019.1641461
   Budhathoki NK, 2019, LAND USE POLICY, V85, P1, DOI 10.1016/j.landusepol.2019.03.029
   Carter MR, 2016, J DEV ECON, V118, P59, DOI 10.1016/j.jdeveco.2015.08.008
   Chambers RG, 2007, AM J AGR ECON, V89, P596, DOI 10.1111/j.1467-8276.2007.00987.x
   Chantarat S, 2007, AM J AGR ECON, V89, P1262, DOI 10.1111/j.1467-8276.2007.01094.x
   Clarke DJ, 2016, AM ECON J-MICROECON, V8, P283, DOI 10.1257/mic.20140103
   Dale A, 2020, CLIM POLICY, V20, P866, DOI 10.1080/14693062.2019.1651244
   Davenport F, 2018, CLIMATIC CHANGE, V147, P491, DOI 10.1007/s10584-018-2149-7
   de Aghion BA, 2000, ECON TRANSIT, V8, P401
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Deschênes O, 2007, AM ECON REV, V97, P354, DOI 10.1257/aer.97.1.354
   Di Falco S, 2014, EUR REV AGRIC ECON, V41, P405, DOI 10.1093/erae/jbu014
   Di Falco S, 2011, AM J AGR ECON, V93, P825, DOI 10.1093/ajae/aar006
   Doelle M, 2020, CLIM POLICY, V20, P669, DOI 10.1080/14693062.2019.1630353
   Du XD, 2014, AM J AGR ECON, V96, P232, DOI 10.1093/ajae/aat057
   Duncan J, 2000, AM J AGR ECON, V82, P842, DOI 10.1111/0002-9092.00085
   Egbendewe AYG, 2017, CLIMATIC CHANGE, V145, P101, DOI 10.1007/s10584-017-2083-0
   Enjolras G., 2012, Agricultural Economics Review, V13, P5
   FAO, 2015, Report
   Fisher M, 2015, CLIMATIC CHANGE, V133, P283, DOI 10.1007/s10584-015-1459-2
   Fuchs A, 2011, AM J AGR ECON, V93, P505, DOI 10.1093/ajae/aaq137
   Gaurav S, 2011, J MARKETING RES, V48, pS150, DOI 10.1509/jmkr.48.SPL.S150
   Gine X, 2008, WORLD BANK ECON REV, V22, P539, DOI 10.1093/wber/lhn015
   Giné X, 2009, J DEV ECON, V89, P1, DOI 10.1016/j.jdeveco.2008.09.007
   Glauber J. W., 2004, American Journal of Agricultural Economics, V86, P1179, DOI 10.1111/j.0002-9092.2004.00663.x
   GOODWIN BK, 1993, AM J AGR ECON, V75, P425, DOI 10.2307/1242927
   Greatrex H., 2015, Scaling up index insurance for smallholder farmers: Recent evidence and insights
   Hamukwala P, 2019, J AGR ECON, V70, P81, DOI 10.1111/1477-9552.12273
   HANEMANN WM, 1984, AM J AGR ECON, V66, P332, DOI 10.2307/1240800
   HANEMANN WM, 1994, J ECON PERSPECT, V8, P19, DOI 10.1257/jep.8.4.19
   Hanley N, 2001, J ECON SURV, V15, P435, DOI 10.1111/1467-6419.00145
   Hill R. V., 2011, FLEXIBLE INSURANCE H
   Hill RV, 2019, J DEV ECON, V136, P1, DOI 10.1016/j.jdeveco.2018.09.003
   Hill RV, 2013, AGR ECON-BLACKWELL, V44, P385, DOI 10.1111/agec.12023
   Hönle SE, 2019, CLIM POLICY, V19, P688, DOI 10.1080/14693062.2018.1559793
   Horton JB, 2019, CLIM POLICY, V19, P820, DOI 10.1080/14693062.2019.1607716
   Jensen ND, 2017, J DEV ECON, V129, P14, DOI 10.1016/j.jdeveco.2017.08.002
   Kodongo O, 2013, REV DEV FINANC, V3, P99, DOI 10.1016/j.rdf.2013.05.001
   Kwak K, 2016, J CHOICE MODEL, V21, P42, DOI 10.1016/j.jocm.2016.07.001
   LANCASTER KJ, 1966, J POLIT ECON, V74, P132, DOI 10.1086/259131
   Lloyd-Smith P, 2018, J CHOICE MODEL, V26, P19, DOI 10.1016/j.jocm.2017.12.002
   Mahul O, 2001, AM J AGR ECON, V83, P593, DOI 10.1111/0002-9092.00180
   McIntosh C, 2013, AGR ECON-BLACKWELL, V44, P399, DOI 10.1111/agec.12024
   MENDELSOHN R, 1994, AM ECON REV, V84, P753
   *MIN AGR IND, 2012, ANN REP 2011 2012
   MIRANDA MJ, 1991, AM J AGR ECON, V73, P233, DOI 10.2307/1242708
   Miranda MJ, 1997, AM J AGR ECON, V79, P206, DOI 10.2307/1243954
   Nordhaus WD, 1996, AM ECON REV, V86, P741
   Nordlander L, 2020, CLIM POLICY, V20, P704, DOI 10.1080/14693062.2019.1671163
   Parkes B, 2018, CLIMATIC CHANGE, V151, P205, DOI 10.1007/s10584-018-2290-3
   Richards DJ, 2004, AM J AGR ECON, V86, P1005, DOI 10.1111/j.0002-9092.2004.00649.x
   Ricome A, 2017, AGR SYST, V156, P149, DOI 10.1016/j.agsy.2017.05.015
   Rolfe J., 1999, Economic Analysis and Policy, V29, P187, DOI [DOI 10.1016/S0313-5926(99)50020-9, 10.1016/S0313-5926(99)50020-9]
   ROSENZWEIG C, 1994, NATURE, V367, P133, DOI 10.1038/367133a0
   Sarris A, 2013, AGR ECON-BLACKWELL, V44, P381, DOI 10.1111/agec.12022
   Shakhawat Hossain M, 2019, ECOL ECON, V164, DOI 10.1016/j.ecolecon.2019.106354
   Sherrick BJ, 2004, AM J AGR ECON, V86, P103, DOI 10.1111/j.0092-5853.2004.00565.x
   Sherrick BJ, 2003, REV AGR ECON, V25, P415, DOI 10.1111/1467-9353.00147
   Shi HL, 2018, J CHOICE MODEL, V26, P48, DOI 10.1016/j.jocm.2017.07.002
   Shirsath P, 2019, CLIM RISK MANAG, V25, DOI 10.1016/j.crm.2019.100189
   Sibiko KennethW., 2018, AGR FOOD SECURITY, V7, P53, DOI [DOI 10.1186/S40066-018-0200-6, 10.1186/s40066-018-0200-6, 10.1186/S40066-018-0200-6/TABLES/6]
   Smith VH, 1996, AM J AGR ECON, V78, P428, DOI 10.2307/1243714
   Tadesse A.M., 2015, AGR FOOD ECON, V3, P26, DOI [10.1186/s40100-015-0044-3, DOI 10.1186/S40100-015-0044-3]
   Tchinguilou A., 2012, W AFRICAN AGR CLIMAT
   Tesfaye A, 2019, ECOL ECON, V162, P157, DOI 10.1016/j.ecolecon.2019.04.019
   Turvey CG, 2006, AM J AGR ECON, V88, P696, DOI 10.1111/j.1467-8276.2006.00889.x
   Ward PS, 2020, ECON DEV CULT CHANGE, V68, P607, DOI 10.1086/700632
   Ward PS, 2014, WORLD DEV, V64, P125, DOI 10.1016/j.worlddev.2014.05.017
   Wossen T, 2017, J ENVIRON MANAGE, V203, P106, DOI 10.1016/j.jenvman.2017.06.058
   Xu W, 2008, AM J AGR ECON, V90, P979, DOI 10.1111/j.1467-8276.2008.01154.x
NR 84
TC 26
Z9 26
U1 5
U2 37
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PD MAY 27
PY 2020
VL 20
IS 5
BP 534
EP 547
DI 10.1080/14693062.2020.1745742
EA APR 2020
PG 14
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA LU7DK
UT WOS:000526291600001
DA 2025-01-10
ER

PT J
AU Burdon, FJ
   Ramberg, E
   Sargac, J
   Forio, MAE
   de Saeyer, N
   Mutinova, PT
   Moe, TF
   Pavelescu, MO
   Dinu, V
   Cazacu, C
   Witing, F
   Kupilas, B
   Grandin, U
   Volk, M
   Risnoveanu, G
   Goethals, P
   Friberg, N
   Johnson, RK
   McKie, BG
AF Burdon, Francis J.
   Ramberg, Ellinor
   Sargac, Jasmina
   Forio, Marie Anne Eurie
   de Saeyer, Nancy
   Mutinova, Petra Thea
   Moe, Therese Fosholt
   Pavelescu, Mihaela Oprina
   Dinu, Valentin
   Cazacu, Constantin
   Witing, Felix
   Kupilas, Benjamin
   Grandin, Ulf
   Volk, Martin
   Risnoveanu, Geta
   Goethals, Peter
   Friberg, Nikolai
   Johnson, Richard K.
   McKie, Brendan G.
TI Assessing the Benefits of Forested Riparian Zones: A Qualitative Index
   of Riparian Integrity Is Positively Associated with Ecological Status in
   European Streams
SO WATER
LA English
DT Article
DE benthic invertebrates; land use; agriculture; urbanization; riparian
   management; riparian buffer; nature-based solutions; blue-green
   infrastructure; climate-change adaptation; protocols
ID BENTHIC INVERTEBRATE COMMUNITIES; CLIMATE-CHANGE; LAND-USE; RIVER
   RESTORATION; RESPONSE RATIOS; BUFFER ZONES; WATER; LANDSCAPE;
   MACROINVERTEBRATES; MANAGEMENT
AB Developing a general, predictive understanding of ecological systems requires knowing how much structural and functional relationships can cross scales and contexts. Here, we introduce the CROSSLINK project that investigates the role of forested riparian buffers in modified European landscapes by measuring a wide range of ecosystem attributes in stream-riparian networks. CROSSLINK involves replicated field measurements in four case-study basins with varying levels of human development: Norway (Oslo Fjord), Sweden (Lake Malaren), Belgium (Zwalm River), and Romania (Arge River). Nested within these case-study basins include multiple, independent stream-site pairs with a forested riparian buffer and unbuffered section located upstream, as well as headwater and downstream sites to show cumulative land-use impacts. CROSSLINK applies existing and bespoke methods to describe habitat conditions, biodiversity, and ecosystem functioning in aquatic and terrestrial habitats. Here, we summarize the approaches used, detail protocols in supplementary materials, and explain how data is applied in an optimization framework to better manage tradeoffs in multifunctional landscapes. We then present results demonstrating the range of riparian conditions present in our case-study basins and how these environmental states influence stream ecological integrity with the commonly used macroinvertebrate Average Score Per Taxon (ASPT) index. We demonstrate that a qualitative index of riparian integrity can be positively associated with stream ecological status. This introduction to the CROSSLINK project shows the potential for our replicated study with its panoply of ecosystem attributes to help guide management decisions regarding the use of forested riparian buffers in human-impacted landscapes. This knowledge is highly relevant in a time of rapid environmental change where freshwater biodiversity is increasingly under pressure from a range of human impacts that include habitat loss, pollution, and climate change.
C1 [Burdon, Francis J.; Ramberg, Ellinor; Sargac, Jasmina; Grandin, Ulf; Johnson, Richard K.; McKie, Brendan G.] Swedish Univ Agr Sci, Dept Aquat Sci & Assessment, S-75007 Uppsala, Sweden.
   [Forio, Marie Anne Eurie; de Saeyer, Nancy; Goethals, Peter] Univ Ghent, Dept Anim Sci & Aquat Ecol, Aquat Ecol Res Unit, B-9000 Ghent, Belgium.
   [Mutinova, Petra Thea; Moe, Therese Fosholt; Kupilas, Benjamin; Friberg, Nikolai] Norwegian Inst Water Res NIVA, N-0349 Oslo, Norway.
   [Mutinova, Petra Thea] Univ Rostock, Inst Biol Sci, D-18059 Rostock, Germany.
   [Pavelescu, Mihaela Oprina; Dinu, Valentin; Cazacu, Constantin; Risnoveanu, Geta] Univ Bucharest, Dept Syst Ecol & Sustainabil, Bucharest 050095, Romania.
   [Witing, Felix; Volk, Martin] UFZ Helmholtz Ctr Environm Res, Dept Computat Landscape Ecol, D-04318 Leipzig, Germany.
   [Kupilas, Benjamin] Univ Munster, Inst Landscape Ecol, D-48149 Munster, Germany.
   [Risnoveanu, Geta] Univ Bucharest, Res Inst, Bucharest 050663, Romania.
   [Friberg, Nikolai] Univ Copenhagen, Freshwater Biol Sect, Dept Biol, DK-2100 Copenhagen, Denmark.
   [Friberg, Nikolai] Univ Leeds, Water Leeds, Leeds LS2 9JT, W Yorkshire, England.
   [Friberg, Nikolai] Univ Leeds, Sch Geog, Leeds LS2 9JT, W Yorkshire, England.
C3 Swedish University of Agricultural Sciences; Ghent University; Norwegian
   Institute for Water Research (NIVA); University of Rostock; University
   of Bucharest; Helmholtz Association; Helmholtz Center for Environmental
   Research (UFZ); University of Munster; University of Bucharest;
   University of Copenhagen; University of Leeds; University of Leeds
RP Burdon, FJ (corresponding author), Swedish Univ Agr Sci, Dept Aquat Sci & Assessment, S-75007 Uppsala, Sweden.
EM francis.burdon@slu.se; ellinor.karin.ramberg@slu.se;
   jasmina.sargac@slu.se; marie.forio@ugent.be; Nancy.DeSaeyer@UGent.be;
   petra.Mutinova@niva.no; therese.fosholt.moe@niva.no;
   mihaela.oprina@g.unibuc.ro; valentindinu23@yahoo.com;
   constantin.cazacu@g.unibuc.ro; felix.witing@ufz.de;
   benjamin.kupilas@niva.no; ulf.grandin@slu.se; martin.volk@ufz.de;
   geta.risnoveanu@g.unibuc.ro; Peter.Goethals@UGent.be;
   Nikolai.Friberg@niva.no; Richard.Johnson@slu.se; Brendan.Mckie@slu.se
RI Grandin, Ulf/HKO-5291-2023; Moe, Therese/AAX-6404-2020; Dinu,
   Valentin/ABD-9154-2020; McKie, Brendan/C-9376-2013; Goethals,
   Peter/A-1116-2008; Oprina-Pavelescu, Mihaela/AAH-5572-2020; Cazacu,
   Constantin/AAD-7419-2019; Forio, Marie/ABU-3758-2022; Burdon,
   Francis/ABC-2827-2020; Volk, Martin/F-1172-2010; Johnson,
   Richard/P-4991-2014; geta, risnoveanu/Q-3790-2019
OI Moe, Therese Fosholt/0000-0002-1004-5961; Sargac,
   Jasmina/0000-0001-7006-8092; Kupilas, Benjamin/0000-0002-4211-1679;
   /0000-0003-1040-1564; McKie, Brendan/0000-0002-1796-9497; Cazacu,
   Constantin/0000-0003-4521-7185; Volk, Martin/0000-0003-0064-8133;
   Grandin, Ulf/0000-0003-0320-0692; Witing, Felix/0000-0002-7314-4908;
   Johnson, Richard/0000-0001-7979-6563; Burdon,
   Francis/0000-0002-5398-4993; Forio, Marie Anne
   Eurie/0000-0001-6675-4751; geta, risnoveanu/0000-0002-5194-5448;
   Oprina-Pavelescu, Mihaela/0000-0002-6526-0546
FU CROSSLINK project through the 2015-2016 BiodivERsA COFUND call for
   research proposals; Swedish Research Council for Sustainable Development
   (FORMAS) [2016-01945]; Swedish Environmental Protection Agency; Research
   Council of Norway (NFR) [264499]; Research Foundation of Flanders (FWO),
   Belgium [G0H6516N]; Romanian National Authority for Scientific Research
   and Innovation (CCCDI-UEFISCDI within PNCDI III)
   [BiodivERsA3-2015-49-CROSSLINK]; Federal Ministry of Education and
   Research (BMBF), Germany [FKZ: 01LC1621A]; Formas [2016-01945] Funding
   Source: Formas
FX This research was conducted as part of the CROSSLINK project funded
   through the 2015-2016 BiodivERsA COFUND call for research proposals.
   National funders: the Swedish Research Council for Sustainable
   Development (FORMAS, project 2016-01945) and the Swedish Environmental
   Protection Agency; The Research Council of Norway (NFR, project 264499);
   The Research Foundation of Flanders (FWO, project G0H6516N), Belgium;
   the Romanian National Authority for Scientific Research and Innovation
   (CCCDI-UEFISCDI, project BiodivERsA3-2015-49-CROSSLINK, within PNCDI
   III); and the Federal Ministry of Education and Research (BMBF, project
   FKZ: 01LC1621A), Germany.
CR Allan JD, 2004, ANNU REV ECOL EVOL S, V35, P257, DOI 10.1146/annurev.ecolsys.35.120202.110122
   [Anonymous], J STAT SOFTW, DOI DOI 10.18637/JSS.V067.I01
   [Anonymous], 2015, Towards an EU research and innovation policy agenda for nature -based solutions & re-naturing cities, DOI DOI 10.2777/479582
   [Anonymous], 2019, VEGAN COMMUNITY ECOL
   [Anonymous], 2006, Watershed Assessment of River Stability and Sediment Supply (WARSSS)
   ARMITAGE PD, 1983, WATER RES, V17, P333, DOI 10.1016/0043-1354(83)90188-4
   Battin J, 2007, P NATL ACAD SCI USA, V104, P6720, DOI 10.1073/pnas.0701685104
   Baxter CV, 2005, FRESHWATER BIOL, V50, P201, DOI 10.1111/j.1365-2427.2004.01328.x
   Bernhardt ES, 2011, ECOL APPL, V21, P1926, DOI 10.1890/10-1574.1
   Birk S, 2006, HYDROBIOLOGIA, V566, P401, DOI 10.1007/s10750-006-0081-8
   Bray JP, 2020, HYDROBIOLOGIA, V847, P177, DOI 10.1007/s10750-019-04080-5
   Briers R., 2016, biotic: Calculation of Freshwater Biotic Indices
   Broadmeadow SB, 2011, RIVER RES APPL, V27, DOI 10.1002/rra.1354
   Burdon FJ, 2008, FRESHWATER BIOL, V53, P330, DOI 10.1111/j.1365-2427.2007.01897.x
   Burdon FJ, 2020, J ANIM ECOL, V89, P730, DOI 10.1111/1365-2656.13142
   Burdon FJ, 2016, ECOL EVOL, V6, P3923, DOI 10.1002/ece3.2165
   Burdon FJ, 2013, ECOL APPL, V23, P1036, DOI 10.1890/12-1190.1
   Burrell TK, 2014, FRESHW SCI, V33, P73, DOI 10.1086/674180
   Carlson PE, 2016, FRESHWATER BIOL, V61, P848, DOI 10.1111/fwb.12745
   CLC, 2018, COR LAND COV CLC INV
   Clews E, 2010, AQUAT CONSERV, V20, pS96, DOI 10.1002/aqc.1096
   Cole LJ, 2020, AGR ECOSYST ENVIRON, V296, DOI 10.1016/j.agee.2020.106891
   Collins KE, 2019, NEW ZEAL J MAR FRESH, V53, P182, DOI 10.1080/00288330.2018.1487454
   Correll DL, 2005, ECOL ENG, V24, P433, DOI 10.1016/j.ecoleng.2005.01.007
   Davy-Bowker J, 2006, HYDROBIOLOGIA, V566, P91, DOI 10.1007/s10750-006-0068-5
   DEATH RG, 1995, ECOLOGY, V76, P1446, DOI 10.2307/1938147
   Dudgeon D, 2019, CURR BIOL, V29, pR960, DOI 10.1016/j.cub.2019.08.002
   Ficetola GF, 2009, CONSERV BIOL, V23, P114, DOI 10.1111/j.1523-1739.2008.01081.x
   Fölster J, 2014, AMBIO, V43, P3, DOI 10.1007/s13280-014-0558-z
   Friberg N, 2016, ADV ECOL RES, V55, P535, DOI 10.1016/bs.aecr.2016.08.010
   Friberg N, 2011, ADV ECOL RES, V44, P1, DOI 10.1016/B978-0-12-374794-5.00001-8
   Friberg N, 2010, FRESHWATER BIOL, V55, P1367, DOI 10.1111/j.1365-2427.2010.02442.x
   Göthe E, 2019, J APPL ECOL, V56, P1687, DOI 10.1111/1365-2664.13413
   Greenwood MJ, 2012, J APPL ECOL, V49, P213, DOI 10.1111/j.1365-2664.2011.02092.x
   GREGORY SV, 1991, BIOSCIENCE, V41, P540, DOI 10.2307/1311607
   Hanna DEL, 2020, CONSERV BIOL, V34, P244, DOI 10.1111/cobi.13348
   Harding J S., 2009, Stream Habitat Assessment Protocols for Wadeable Rivers and Streams of New Zealand
   Harrison I, 2018, SCIENCE, V362, P1369, DOI 10.1126/science.aav9242
   Hauer F. Richard, 2007, P435, DOI 10.1016/B978-012332908-0.50028-0
   Hedges LV, 1999, ECOLOGY, V80, P1150, DOI 10.1890/0012-9658(1999)080[1150:TMAORR]2.0.CO;2
   Honnay O, 2010, J BIOGEOGR, V37, P1730, DOI 10.1111/j.1365-2699.2010.02331.x
   Jacobsen D, 2003, FRESHWATER BIOL, V48, P2025, DOI 10.1046/j.1365-2427.2003.01140.x
   Jacobsen Dean, 1997, P208
   Johnson RK, 2016, FRESHW SCI, V35, P984, DOI 10.1086/687837
   Kristensen PB, 2013, HYDROLOGY EARTH SYST, V10, P6081
   Lajeunesse MJ, 2011, ECOLOGY, V92, P2049, DOI 10.1890/11-0423.1
   Lake Philip S., 2013, Ecological Management & Restoration, V14, P20, DOI 10.1111/emr.12016
   Lennon M, 2015, LOCAL ENVIRON, V20, P957, DOI 10.1080/13549839.2014.880411
   Leroux SJ, 2008, ECOL LETT, V11, P1147, DOI 10.1111/j.1461-0248.2008.01235.x
   Lind L, 2019, J ENVIRON MANAGE, V249, DOI 10.1016/j.jenvman.2019.109391
   LOWRANCE R, 1984, BIOSCIENCE, V34, P374, DOI 10.2307/1309729
   Mander Ü, 2005, ECOL ENG, V24, P421, DOI 10.1016/j.ecoleng.2005.01.015
   Marcarelli AM, 2020, ECOLOGY, V101, DOI 10.1002/ecy.3064
   Naiman RJ, 1997, ANNU REV ECOL SYST, V28, P621, DOI 10.1146/annurev.ecolsys.28.1.621
   NAIMAN RJ, 1993, ECOL APPL, V3, P209, DOI 10.2307/1941822
   Nakagawa S, 2013, METHODS ECOL EVOL, V4, P133, DOI 10.1111/j.2041-210x.2012.00261.x
   Nakano S, 2001, P NATL ACAD SCI USA, V98, P166, DOI 10.1073/pnas.98.1.166
   Niyogi DK, 2007, ENVIRON MANAGE, V39, P213, DOI 10.1007/s00267-005-0310-3
   ODUM EP, 1979, BIOSCIENCE, V29, P349, DOI 10.2307/1307690
   Ossa-Moreno J, 2017, SUSTAIN CITIES SOC, V28, P411, DOI 10.1016/j.scs.2016.10.002
   Palmer MA, 2009, ENVIRON MANAGE, V44, P1053, DOI 10.1007/s00267-009-9329-1
   Parkyn SM, 2003, RESTOR ECOL, V11, P436, DOI 10.1046/j.1526-100X.2003.rec0260.x
   Pfankuch D.J., 1975, Stream reach inventory and channel stability evaluation, P26
   Polis GA, 1997, ANNU REV ECOL SYST, V28, P289, DOI 10.1146/annurev.ecolsys.28.1.289
   Power M.E., 2000, P291
   Quinn JM, 1997, NEW ZEAL J MAR FRESH, V31, P665, DOI 10.1080/00288330.1997.9516797
   R Core Team, 2019, LANG ENV STAT COMP
   Rixen T, 2010, J ENVIRON MANAGE, V91, P1730, DOI 10.1016/j.jenvman.2010.03.009
   Rutherford J.C., 1997, STREAM SHADE RESTORA
   Salo T, 2017, FRESHWATER BIOL, V62, P1831, DOI 10.1111/fwb.12999
   Schwendel AC, 2011, J N AM BENTHOL SOC, V30, P11, DOI 10.1899/09-172.1
   Seppelt R, 2009, ECOL MODEL, V220, P3481, DOI 10.1016/j.ecolmodel.2009.09.009
   Sorensen J., 2018, URBAN PLUVIAL FLOODI
   Sörensen J, 2016, WATER-SUI, V8, DOI 10.3390/w8080332
   Steffen W, 2011, PHILOS T R SOC A, V369, P842, DOI 10.1098/rsta.2010.0327
   Stutter MI, 2012, J ENVIRON QUAL, V41, P297, DOI 10.2134/jeq2011.0439
   Swan DM, 2018, MULTIVAR BEHAV RES, V53, P574, DOI 10.1080/00273171.2018.1466681
   Tagwireyi P, 2016, RIVER RES APPL, V32, P1721, DOI 10.1002/rra.3009
   Thomas SM, 2016, GLOBAL CHANGE BIOL, V22, P310, DOI 10.1111/gcb.13103
   Tilman D, 2017, NATURE, V546, P73, DOI 10.1038/nature22900
   TURNER T, 1995, LANDSCAPE URBAN PLAN, V33, P269, DOI 10.1016/0169-2046(94)02022-8
   Vörösmarty CJ, 2010, NATURE, V467, P555, DOI 10.1038/nature09440
   Wahl CM, 2013, FRESHWATER BIOL, V58, P2310, DOI 10.1111/fwb.12211
   Walsh CJ, 2016, FRESHW SCI, V35, P398, DOI 10.1086/685284
NR 84
TC 42
Z9 48
U1 3
U2 45
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD APR
PY 2020
VL 12
IS 4
AR 1178
DI 10.3390/w12041178
PG 24
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA LX0JR
UT WOS:000539527500255
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Zaginaev, V
   Petrakov, D
   Erokhin, S
   Meleshko, A
   Stoffel, M
   Ballesteros-Cánovas, JA
AF Zaginaev, V.
   Petrakov, D.
   Erokhin, S.
   Meleshko, A.
   Stoffel, M.
   Ballesteros-Canovas, J. A.
TI Geomorphic control on regional glacier lake outburst flood and debris
   flow activity over northern Tien Shan
SO GLOBAL AND PLANETARY CHANGE
LA English
DT Article
DE GLOF; Debris flow; Cryosphere; Tree rings; Dendrogeomorphology; Tien
   Shan; Kyrgyzstan
ID CLIMATE-CHANGE IMPACTS; MASS MOVEMENTS; WOOD ANATOMY; RECONSTRUCTION;
   MOUNTAINS; LANDSLIDE; HAZARDS; RETREAT
AB Glacier lake outburst floods (GLOFs) and related debris flows (DF) are significant natural threats in the Tien Shan Mountains. Their occurrence is favoured by the formation of new glacier lakes and the destabilization of moraines and hillslopes due to climate warming. Understanding the frequency-magnitude of these processes is essential for the implementation of Disaster Risk Reduction strategies. Yet, long-term records of past GLOFs or DF in the region are almost completely missing, which renders rational hazard and risk assessments difficult. Here, we present a unique, multi-century dataset of regional GLOF-DF reconstruction for the Tien Shan based on tree ring analyses from six different torrential fans, and provide insights on regional processes activity. Based on this dataset, we also test whether GLOF-DF activity is related to glacier degradation and changes in geomorphic characteristics at the catchment scale. Results from > 430 disturbed trees growing on six different DF fans suggest frequent GLOF-DF activity since the 19th century, which is consistent with available historical records. We also observe an increase in process activity during the mid-20th century coinciding with phases of glacier stagnation or even slight glacier advances. This means GLOF-DF activity in northern Tien Shan is inversely related to moraine-glacier ratios as well as to glacier area shrinkage rates and fan characteristics (such as slope and depositional area). These findings imply that glaciological and geomorphic features could be used for regional susceptibility assessments in the future. Results presented here are the longest, annually resolved GLOF-DF series in the region, if not worldwide, and constitute a unique dataset to understand process variability. As such, they should be used for further climate change adaptation to mitigate natural hazard and risk in the region.
C1 [Zaginaev, V.; Erokhin, S.; Meleshko, A.] Natl Acad Sci, Inst Water Problems & Hydroenergy, Bishkek, Kyrgyzstan.
   [Petrakov, D.] Lomonosov Moscow State Univ, Fac Geog, Moscow, Russia.
   [Stoffel, M.; Ballesteros-Canovas, J. A.] Univ Geneva, Dept Earth & Environm Sci, Dendrolab Ch, CH-1205 Geneva, Switzerland.
   [Stoffel, M.; Ballesteros-Canovas, J. A.] Univ Geneva, Inst Environm Sci, Climate Change Impacts & Risks Anthropocene C CIA, CH-1227 Carouge, Switzerland.
   [Stoffel, M.] Univ Geneva, Dept FA Forel Aquat & Environm Sci, CH-1205 Geneva, Switzerland.
C3 National Academy of Sciences of the Kyrgyz Republic (NAS KR); Lomonosov
   Moscow State University; University of Geneva; University of Geneva;
   University of Geneva
RP Zaginaev, V (corresponding author), Inst Water Problems & Hydroenergy, 533 Frunze St, Bishkek 720033, Kyrgyzstan.
EM zagivitjob@gmail.com
RI Cánovas, Juan/ABG-7903-2020; Stoffel, Markus/A-1793-2017; Petrakov,
   Dmitry/H-5854-2011
OI Stoffel, Markus/0000-0003-0816-1303; Petrakov,
   Dmitry/0000-0002-0990-495X; Ballesteros Canovas, Juan
   A./0000-0003-4439-397X
FU Swiss National Science Foundation (SNF, Schweizerischer Nationalfonds
   zur Forderung der Wissenschaftlichen Forschung) [152301]
FX This study was funded by the Swiss National Science Foundation (SNF,
   Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen
   Forschung) in the framework of the DEFENCC (no 152301; Future DEbris
   Flows and lake outburst floods in Tien Shan: possible impacts of
   projected Climate Change) project. We also acknowledge the Flood Working
   Group of PAGES (Past Global Changes) for supporting this special issue
   on paleoflood records.
CR Aizen VB, 1988, DATA GLACIOL STUD, V62, P119
   Aizen VB, 2006, ANN GLACIOL-SER, V43, P202, DOI 10.3189/172756406781812465
   Allen SK, 2018, ENVIRON SCI POLICY, V87, P1, DOI 10.1016/j.envsci.2018.05.013
   [Anonymous], DEBRIS FLOWS S E KAZ
   [Anonymous], FIN P INT C FLOODS T
   [Anonymous], 1995, Glaciation of the Tien Shan
   Baimoldaev T, 2007, KAZSELEZASHCHITA OPE, P284
   Ballesteros JA, 2010, TREE PHYSIOL, V30, P773, DOI 10.1093/treephys/tpq031
   Ballesteros JA, 2010, TREE-RING RES, V66, P93, DOI 10.3959/2009-4.1
   Ballesteros-Cánovas JA, 2019, ANN NY ACAD SCI, V1436, P206, DOI 10.1111/nyas.13911
   Ballesteros-Cánovas JA, 2016, GEOMORPHOLOGY, V272, P92, DOI 10.1016/j.geomorph.2015.12.004
   Beniston M, 2018, CRYOSPHERE, V12, P759, DOI 10.5194/tc-12-759-2018
   Benn DI, 2002, QUATERN INT, V97-8, P3, DOI 10.1016/S1040-6182(02)00048-4
   Bodoque JM, 2015, J HYDROL, V529, P449, DOI 10.1016/j.jhydrol.2014.12.004
   Bolch T, 2015, ICE SNOW, P28
   Bollschweiler M, 2008, TREE PHYSIOL, V28, P255, DOI 10.1093/treephys/28.2.255
   Canovas JAB, 2017, J HYDROL, V546, P140, DOI 10.1016/j.jhydrol.2016.12.059
   Chiarle M, 2007, GLOBAL PLANET CHANGE, V56, P123, DOI 10.1016/j.gloplacha.2006.07.003
   Engel Z, 2012, J GLACIOL, V58, P388, DOI 10.3189/2012JoG11J085
   Erokhin S. A, 2003, IZVESTIYA NAS KR, V15, P130
   Erokhin SA, 2018, LANDSLIDES, V15, P83, DOI 10.1007/s10346-017-0862-3
   Farinotti D, 2015, NAT GEOSCI, V8, P716, DOI 10.1038/NGEO2513
   GOMEZ B, 1985, J GLACIOL, V31, P303, DOI 10.3189/S0022143000006638
   Harrison S, 2018, CRYOSPHERE, V12, P1195, DOI 10.5194/tc-12-1195-2018
   Hawkins E, 2016, B AM METEOROL SOC, V97, P963, DOI 10.1175/BAMS-D-14-00154.1
   Hu ZY, 2014, J CLIMATE, V27, P1143, DOI 10.1175/JCLI-D-13-00064.1
   Huggel C, 2004, CAN GEOTECH J, V41, P1068, DOI 10.1139/T04-053
   Huggel C, 2012, EARTH SURF PROC LAND, V37, P77, DOI 10.1002/esp.2223
   Jansky B, 2010, LIMNOLOGICA, V40, P358, DOI 10.1016/j.limno.2009.11.013
   Kogelnig-Mayer B, 2011, ARCT ANTARCT ALP RES, V43, P649, DOI 10.1657/1938-4246-43.4.649
   Lugon R, 2010, GLOBAL PLANET CHANGE, V73, P202, DOI 10.1016/j.gloplacha.2010.06.004
   Marchenko SS, 2007, GLOBAL PLANET CHANGE, V56, P311, DOI 10.1016/j.gloplacha.2006.07.023
   Mayer B, 2010, GEOMORPHOLOGY, V118, P199, DOI 10.1016/j.geomorph.2009.12.019
   Meleshko A, 2017, REMOTE SENSING BASED, P138
   Melton M.A., 1965, Journal of Geology, V73, P1, DOI DOI 10.1086/627044
   Milner AM, 2017, P NATL ACAD SCI USA, V114, P9770, DOI 10.1073/pnas.1619807114
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Narama C, 2018, NAT HAZARD EARTH SYS, V18, P983, DOI 10.5194/nhess-18-983-2018
   Petrakov D, 2016, SCI TOTAL ENVIRON, V562, P364, DOI 10.1016/j.scitotenv.2016.03.162
   Petrov MA, 2017, SCI TOTAL ENVIRON, V592, P228, DOI 10.1016/j.scitotenv.2017.03.068
   Raup B, 2007, GLOBAL PLANET CHANGE, V56, P101, DOI 10.1016/j.gloplacha.2006.07.018
   Rinntech, 2011, LINTAB PRAZISION JAH
   Saez JL, 2012, LANDSLIDES, V9, P189, DOI 10.1007/s10346-011-0284-6
   Schneuwly-Bollschweiler M, 2013, QUAT GEOCHRONOL, V18, P110, DOI 10.1016/j.quageo.2013.05.001
   Schneuwly-Bollschweiler M, 2012, J GEOPHYS RES-EARTH, V117, DOI 10.1029/2011JF002262
   Solomina O.N., 1994, The Holocene, V4, P25
   Solomina ON, 2000, ANN GLACIOL, V31, P26, DOI 10.3189/172756400781820499
   Sorg A, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104018
   Sorg A, 2012, NAT CLIM CHANGE, V2, P725, DOI [10.1038/nclimate1592, 10.1038/NCLIMATE1592]
   Stoffel M, 2008, NAT HAZARD EARTH SYS, V8, P187, DOI 10.5194/nhess-8-187-2008
   Stoffel M, 2014, SCI TOTAL ENVIRON, V493, P1255, DOI 10.1016/j.scitotenv.2014.02.102
   Stoffel M, 2008, DENDROCHRONOLOGIA, V26, P53, DOI 10.1016/j.dendro.2007.06.002
   Stoffel M, 2014, TREE-RING RES, V70, P3, DOI 10.3959/1536-1098-70.1.3
   Stoffel M, 2012, PROG PHYS GEOG, V36, P421, DOI 10.1177/0309133312441010
   Stoffel M, 2012, GEOLOGY, V40, P247, DOI 10.1130/G32751.1
   Stoffel M, 2011, CLIMATIC CHANGE, V105, P263, DOI 10.1007/s10584-011-0036-6
   Stoffel M, 2010, GEOMORPHOLOGY, V116, P67, DOI 10.1016/j.geomorph.2009.10.009
   Usubaliev R, 2007, DATA GLACIOLOGICAL S, V3, P134
   Wang WC, 2015, HYDROL PROCESS, V29, P859, DOI 10.1002/hyp.10199
   Winchester V, 2015, Vulnerability of Land Systems in Asia, P91
   Wu J. S., 1992, Erosion, debris flow and environment in mountain regions: proceedings of the International Symposium held at Chengdu, China, 5-9 July 1992., P355
   Yu  Vinogradov, 1980, SKETCHES OF MUDFLOWS, P144
   Zaginaev V, 2016, GEOMORPHOLOGY, V269, P75, DOI 10.1016/j.geomorph.2016.06.028
   Zaginaev V, 2013, MONITORING FORECASTI, V10, P563
   2010, NAT HAZARDS EARTH SY, V10, P647
   2008, TREE PHYSL, V28, P1713
NR 66
TC 15
Z9 17
U1 4
U2 42
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0921-8181
EI 1872-6364
J9 GLOBAL PLANET CHANGE
JI Glob. Planet. Change
PD MAY
PY 2019
VL 176
BP 50
EP 59
DI 10.1016/j.gloplacha.2019.03.003
PG 10
WC Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Geology
GA HU6BV
UT WOS:000465364600004
DA 2025-01-10
ER

PT J
AU Lega, M
   Casazza, M
   Turconi, L
   Luino, F
   Tropeano, D
   Savio, G
   Ulgiati, S
   Endreny, T
AF Lega, Massimiliano
   Casazza, Marco
   Turconi, Laura
   Luino, Fabio
   Tropeano, Domenico
   Savio, Gabriele
   Ulgiati, Sergio
   Endreny, Theodore
TI Environmental Data Acquisition, Elaboration and Integration: Preliminary
   Application to a Vulnerable Mountain Landscape and Village (Novalesa, NW
   Italy)
SO ENGINEERING
LA English
DT Article
DE Environmental data elaboration; Climate change; Mountain community;
   Italy; Resilience; Socioecological system; Hydrogeological risk
ID CLIMATE-CHANGE ADAPTATION; ECOSYSTEM SERVICES; GLOBAL CHANGE;
   TIME-SERIES; LAND-USE; RESILIENCE; COMMUNITIES; EVENTS; AREAS; CATCHMENT
AB Climate conditions play a crucial role in the survival of mountain communities, whose survival already critically depends on socioeconomic factors. In the case of montane areas that are prone to natural hazards, such as alpine slope failure and debris flows, climatic factors exert a major influence that should be considered when creating appropriate sustainable scenarios. In fact, it has been shown that climate change alters the availability of ecosystem services (ES), thus increasing the risks of declining soil fertility and reduced water availability, as well as the loss of grassland, potential shifts in regulatory services (e.g., protection from natural hazards), and cultural services. This study offers a preliminary discussion on a case study of a region in the Italian Alps that is experiencing increased extreme precipitation and erosion, and where an isolated and historically resilient community directly depends on a natural resource economy. Preliminary results show that economic factors have influenced past population trends of the Novalesa community in the Piemonte Region in northwest Italy. However, the increasing number of rock fall and debris flow events, which are triggered by meteo-climatic factors, may further influence the livelihood and wellbeing of this community, and of other similar communities around the world. Therefore, environmental monitoring and data analysis will be important means of detecting trends in landscape and climate change and choosing appropriate planning options. Such analysis, in turn, would ensure the survival of about 10% of the global population, and would also represent a possibility for future economic development in critical areas prone to poverty conditions. (C) 2018 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.
C1 [Lega, Massimiliano; Casazza, Marco] Parthenope Univ Napoli, Dept Engn, I-80143 Naples, Italy.
   [Turconi, Laura; Luino, Fabio; Tropeano, Domenico; Savio, Gabriele] Natl Res Council CNR IRPI, Inst Hydrogeol Protect Res, I-10135 Turin, Italy.
   [Casazza, Marco; Ulgiati, Sergio] Parthenope Univ Napoli, Dept Sci & Technol, I-80143 Naples, Italy.
   [Endreny, Theodore] SUNY Coll Environm Sci & Forestry, Dept Environm Resources Engn, Syracuse, NY 13210 USA.
C3 Parthenope University Naples; Consiglio Nazionale delle Ricerche (CNR);
   Istituto di Ricerca per la Protezione Idrogeologica (IRPI-CNR);
   Parthenope University Naples; State University of New York (SUNY)
   System; State University of New York (SUNY) College of Environmental
   Science & Forestry
RP Casazza, M (corresponding author), Parthenope Univ Napoli, Dept Engn, I-80143 Naples, Italy.; Casazza, M (corresponding author), Parthenope Univ Napoli, Dept Sci & Technol, I-80143 Naples, Italy.
EM marco.casazza@uniparthenope.it
RI Casazza, Marco/T-6783-2017; Luino, Fabio/AAO-1477-2020; TURCONI,
   LAURA/AAA-6246-2019; Endreny, Theodore/H-4743-2019; Lega,
   Massimiliano/C-8407-2011; Ulgiati, Sergio/ABE-9420-2020; Casazza,
   Marco/D-3133-2013
OI TURCONI, LAURA/0000-0001-5838-4180; Ulgiati, Sergio/0000-0001-6159-4947;
   Casazza, Marco/0000-0002-7579-3231; LUINO, Fabio/0000-0002-4921-4523
FU China 111 Project [B17005]; Parthenope University of Napoli; U.S.-Italy
   Fulbright Commission; Parthenope University through a Fulbright Scholar
   grant
FX This work is supported by the China 111 Project (B17005). Massimiliano
   Lega acknowledges the financial support received by the Parthenope
   University of Napoli under "Bando di sostegno alla ricerca individuale
   per il triennio 2015-2017." Finally, the authors would like to thank the
   Novalesa municipality administration and the monastic community of
   Novalesa Abbey for all the material and spiritual support that was
   provided through the years as we developed our investigation. This
   project was partly supported by the U.S.-Italy Fulbright Commission and
   Parthenope University through a Fulbright Scholar grant to Theodore
   Endreny.
CR [Anonymous], 2010, Adv. Geosci, DOI [10.5194/adgeo-23-47-2010, DOI 10.5194/ADGEO-23-47-2010]
   [Anonymous], 2014, SUSTAINABLE MOUNTAIN
   Archie KM, 2014, MITIG ADAPT STRAT GL, V19, P569, DOI 10.1007/s11027-013-9449-z
   Barros VR, 2014, WORKING GROUP 2 CONT, P688
   Barua A, 2014, REG ENVIRON CHANGE, V14, P267, DOI 10.1007/s10113-013-0471-1
   Bonzanigo L, 2016, J SUSTAIN TOUR, V24, P637, DOI 10.1080/09669582.2015.1122013
   Boschetti M, 2009, INT J REMOTE SENS, V30, P4643, DOI 10.1080/01431160802632249
   Briner S, 2013, ECOL SOC, V18, DOI 10.5751/ES-05576-180335
   Brunetti M, 2006, INT J CLIMATOL, V26, P345, DOI 10.1002/joc.1251
   Brunetti M, 2002, INT J CLIMATOL, V22, P543, DOI 10.1002/joc.751
   Brunner SH, 2016, ENVIRON SCI POLICY, V66, P129, DOI 10.1016/j.envsci.2016.09.003
   Casazza M, 2003, ANN GEOPHYS-ITALY, V46, P235
   Casazza M, 2016, J ENVIRON ACCOUNT MA, V4, P37, DOI 10.5890/JEAM.2016.03.004
   Casazza M, 2017, J ENVIRON ACCOUNT MA, V5, P35, DOI 10.5890/JEAM.2017.03.004
   Casazza M, 2016, J ENVIRON ACCOUNT MA, V4, P399, DOI 10.5890/JEAM.2016.12.004
   Coviello V, 2015, NAT HAZARDS, V78, P2055, DOI 10.1007/s11069-015-1819-2
   Davini P, 2012, ATMOSPHERE-BASEL, V3, P33, DOI 10.3390/atmos3010033
   Errico A, 2015, INT J REMOTE SENS, V36, P3345, DOI 10.1080/01431161.2015.1054960
   Fuhrer J, 2014, SCI TOTAL ENVIRON, V493, P1232, DOI 10.1016/j.scitotenv.2013.06.038
   Gargiulo Francesco, 2013, Algorithms and Architectures for Parallel Processing. 13th International Conference, ICA3PP 2013. Proceedings: LNCS 8286, P201, DOI 10.1007/978-3-319-03889-6_23
   GRILLETTO R, 1986, B MEM SOC ANTHRO PAR, V3, P47, DOI 10.3406/bmsap.1986.1593
   Guzzetti F, 2008, LANDSLIDES, V5, P3, DOI 10.1007/s10346-007-0112-1
   Haida C, 2016, REG ENVIRON CHANGE, V16, P1989, DOI 10.1007/s10113-015-0759-4
   Ingty T, 2017, CLIMATIC CHANGE, V145, P41, DOI 10.1007/s10584-017-2080-3
   Jia Z., 2014, Management and Engineering, V15, P72
   Lega M., 2016, International Journal of Sustainable Development and Planning, V11, P651, DOI 10.2495/SDP-V11-N5-651-662
   Lega M, 2010, WIT TRANS ECOL ENVIR, V140, P123, DOI 10.2495/WM100121
   Lega M, MANAGEMENT ENV 7
   Li H, 2017, J CLEAN PROD, V161, P1064, DOI 10.1016/j.jclepro.2017.05.155
   Ling HB, 2014, QUATERN INT, V336, P158, DOI 10.1016/j.quaint.2013.08.003
   Milan A, 2015, EARTH SYST DYNAM, V6, P375, DOI 10.5194/esd-6-375-2015
   Mina M, 2017, J APPL ECOL, V54, P389, DOI 10.1111/1365-2664.12772
   Mukhopadhyay P, 2014, ECOL SOC, V19, DOI 10.5751/ES-07105-190445
   Nepal S.K., 2013, Nepal Tourism and Development Review, V1, P1, DOI [https://doi.org/10.3126/ntdr.v1i1.7367, DOI 10.3126/NTDR.V1I1.7367]
   Norrant C, 2006, THEOR APPL CLIMATOL, V83, P89, DOI 10.1007/s00704-005-0163-y
   Palomo I, 2017, MT RES DEV, V37, P179, DOI 10.1659/MRD-JOURNAL-D-16-00110.1
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Permanent Secretariat of the Alpine Convention, 2007, TRANSP MOB ALPS REP
   Permanent Secretariat of the Alpine Convention, 2015, DEM CHANG ALPS REP S, V5
   Permanent Secretariat of the Alpine Convention, 2017, ALP AGR
   Porcù F, 2014, ATMOS RES, V150, P21, DOI 10.1016/j.atmosres.2014.07.005
   Prodi F, 2011, ATMOS RES, V99, P162, DOI 10.1016/j.atmosres.2010.09.016
   Rodríguez-Labajos B, 2013, WIRES CLIM CHANGE, V4, P555, DOI 10.1002/wcc.247
   Rosselló-Nadal J, 2014, TOURISM MANAGE, V42, P334, DOI 10.1016/j.tourman.2013.11.006
   Salvati P, 2018, SCI TOTAL ENVIRON, V610, P867, DOI 10.1016/j.scitotenv.2017.08.064
   Schirpke U, 2017, ECOSYST SERV, V26, P79, DOI 10.1016/j.ecoser.2017.06.008
   Schröter D, 2005, SCIENCE, V310, P1333, DOI 10.1126/science.1115233
   Sharma A, 2011, J APPL BEHAV SCI, V47, P168, DOI 10.1177/0021886310381782
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Steffen W, 2011, AMBIO, V40, P739, DOI 10.1007/s13280-011-0185-x
   Tasser E, 2017, LAND USE POLICY, V60, P60, DOI 10.1016/j.landusepol.2016.10.019
   Theule JI, 2018, NAT HAZARD EARTH SYS, V18, P1, DOI 10.5194/nhess-18-1-2018
   Tomczyk AM, 2016, J ENVIRON MANAGE, V166, P156, DOI 10.1016/j.jenvman.2015.10.016
   Tropeano D, 2004, NAT HAZARDS, V31, P663, DOI 10.1023/B:NHAZ.0000024897.71471.f2
   Tropeano D, 1999, EVALUATION DEBRIS PO
   Turconi L., 2008, Wildbach Und Lawinenverbau, V72, P42
   Turconi L, 2015, ENGINEERING GEOLOGY FOR SOCIETY AND TERRITORY, VOL 3: RIVER BASINS, RESERVOIR SEDIMENTATION AND WATER RESOURCES, P85, DOI 10.1007/978-3-319-09054-2_17
   Turconi L, 2010, GEOMORPHOLOGY, V114, P115, DOI 10.1016/j.geomorph.2009.06.012
   Versteegh K, 1990, ARABICA, V37, P359
   Wang H, 2016, ECOL ENG, V87, P224, DOI 10.1016/j.ecoleng.2015.11.027
   [王士远 Wang Shiyuan], 2016, [地理科学进展, Progress in Geography], V35, P1269
NR 61
TC 4
Z9 4
U1 1
U2 14
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 2095-8099
EI 2096-0026
J9 ENGINEERING-PRC
JI Engineering
PD OCT
PY 2018
VL 4
IS 5
BP 635
EP 642
DI 10.1016/j.eng.2018.08.011
PG 8
WC Engineering, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering
GA GZ2OB
UT WOS:000449225100011
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Bourgault, M
   Brand, J
   Tausz-Posch, S
   Armstrong, RD
   O'Leary, GL
   Fitzgerald, GJ
   Tausz, M
AF Bourgault, M.
   Brand, J.
   Tausz-Posch, S.
   Armstrong, R. D.
   O'Leary, G. L.
   Fitzgerald, G. J.
   Tausz, M.
TI Yield, growth and grain nitrogen response to elevated CO<sub>2</sub> in
   six lentil (<i>Lens culinaris</i>) cultivars grown under Free Air
   CO<sub>2</sub> Enrichment (FACE) in a semi-arid environment
SO EUROPEAN JOURNAL OF AGRONOMY
LA English
DT Article
DE Source-sink relationships; Physiological pre-breeding; Climate change
   adaptation; Terminal drought
ID CARBON-DIOXIDE; ATMOSPHERIC CO2; WHEAT CULTIVAR; SEED YIELD; FIELD;
   PHOTOSYNTHESIS; CROP; TRANSPIRATION; ASSIMILATION; FIXATION
AB Atmospheric CO2 concentrations ([CO2]) are predicted to increase from current levels of about 400 ppm to reach 550 ppm by 2050. The direct benefits of elevated [CO2] (e[CO2]) to plant growth appear to be greater under low rainfall conditions, but there are few field (Free Air CO2 Enrichment or FACE) experimental set-ups that directly address semi-arid conditions. The objectives of this study were to investigate the following research questions: 1) What are the effects of e[CO2] on the growth and grain yield of lentil (Lens culinaris) grown under semi-arid conditions under FACE? 2) Does e [CO2] decrease grain nitrogen in lentil? and 3) Is there genotypic variability in the response to e[CO2] in lentil cultivars? Elevated [CO2] increased yields by approximately 0.5 t ha(-1) (relative increase ranging from 18 to 138%) by increasing both biomass accumulation (by 32%) and the harvest index (by up to 60%). However, the relative response of grain yield to e[CO2] was not consistently greater under dry conditions and might depend on water availability post-flowering. Grain nitrogen concentration was significantly reduced by e[CO2] under the conditions of this experiment. No differences were found between the cultivars selected in the response to elevated [CO2] for grain yield or any other parameters observed despite well expressed genotypic variability in many traits of interest. Biomass accumulation from flowering to maturity was considerably increased by elevated [CO2] (a 50% increase) which suggests that the indeterminate growth habit of lentils provides vegetative sinks in addition to reproductive sinks during the grain-filling period.
C1 [Bourgault, M.; Tausz-Posch, S.] Univ Melbourne, Fac Vet & Agr Sci, 4 Water St, Creswick, Vic 3363, Australia.
   [Brand, J.; Armstrong, R. D.; O'Leary, G. L.; Fitzgerald, G. J.] Agr Victoria, Grains Innovat Pk,110 Natimuk Rct, Horsham, Vic 3401, Australia.
   [Tausz, M.] Univ Melbourne, Fac Sci, 4 Water St, Creswick, Vic 3363, Australia.
   [Bourgault, M.] Montana State Univ, Northern Agr Res Ctr, 3710 Assinniboine Rd, Havre, MT 59501 USA.
   [Tausz-Posch, S.] Univ Birmingham, Sch Biosci, Birmingham B15 2TT, W Midlands, England.
   [Tausz, M.] Univ Birmingham, Birmingham Inst Forest Res, Birmingham B15 2TT, W Midlands, England.
C3 University of Melbourne; Agriculture Victoria; University of Melbourne;
   Montana State University System; Montana State University Bozeman;
   Montana State University Northern; University of Birmingham; University
   of Birmingham
RP Bourgault, M (corresponding author), Montana State Univ, Northern Agr Res Ctr, 3710 Assinniboine Rd, Havre, MT 59501 USA.
EM maryse.bourgault@montana.edu
RI Bourgault, Maryse/D-4416-2009; Tausz, Michael/C-1990-2013
OI Tausz-Posch, Sabine/0000-0002-1213-7907; Bourgault,
   Maryse/0000-0001-7756-7353; Tausz, Michael/0000-0001-8205-8561
FU Australian Commonwealth Department of Agriculture and Water Resources
   (DAFWR); Grains Research and Development Corporation (GRDC)
FX Research at the Australian Grains Free Air Carbon dioxide Enrichment
   (AGFACE) facility is jointly run by the Victorian Government and the
   University of Melbourne and receives substantial additional funding from
   the Australian Commonwealth Department of Agriculture and Water
   Resources (DAFWR) and the Grains Research and Development Corporation
   (GRDC). We wish to acknowledge the crucial contributions of Mahabubur
   Mollah (AGFACE research engineer) and Russel Argall (senior technical
   officer) and their team in running and maintaining the AGFACE facility,
   as well as Samuel Henty, Shahnaj Parvin and other team members from the
   University of Melbourne for technical help.
CR Ainsworth EA, 2005, NEW PHYTOL, V165, P351, DOI 10.1111/j.1469-8137.2004.01224.x
   Ainsworth EA, 2004, AGR FOREST METEOROL, V122, P85, DOI 10.1016/j.agrformet.2003.09.002
   Ainsworth EA, 2008, PLANT CELL ENVIRON, V31, P1317, DOI 10.1111/j.1365-3040.2008.01841.x
   [Anonymous], 2012, CROP PASTURE SCI, DOI DOI 10.1071/CP11296
   [Anonymous], CLIM DAT ONL DAT HOR
   [Anonymous], 2015, J INTEGR AGR, DOI DOI 10.1016/S2095-3119(14)60941-2
   Bishop KA, 2015, PLANT CELL ENVIRON, V38, P1765, DOI 10.1111/pce.12443
   Bloom AJ, 2014, NAT CLIM CHANGE, V4, P477, DOI [10.1038/nclimate2183, 10.1038/NCLIMATE2183]
   Bourgault M, 2016, FIELD CROP RES, V196, P1, DOI 10.1016/j.fcr.2016.04.011
   Bunce JA, 2008, AGR ECOSYST ENVIRON, V128, P219, DOI 10.1016/j.agee.2008.06.003
   Butler D., 2007, ASReml-R reference manual
   COLEMAN JS, 1993, OECOLOGIA, V93, P195, DOI 10.1007/BF00317671
   Deryng D, 2016, NAT CLIM CHANGE, V6, P786, DOI [10.1038/nclimate2995, 10.1038/NCLIMATE2995]
   Fitzgerald GJ, 2010, INT J REMOTE SENS, V31, P4335, DOI 10.1080/01431160903258217
   Fitzgerald GJ, 2016, GLOBAL CHANGE BIOL, V22, P2269, DOI 10.1111/gcb.13263
   Food and Agriculture Organization Corporate Statistical Database (FAOSTAT), 2016, FAO UN STAT DIV
   GIFFORD RM, 1979, AUST J PLANT PHYSIOL, V6, P367, DOI 10.1071/PP9790367
   Gilmour AR, 1995, BIOMETRICS, V51, P1440, DOI 10.2307/2533274
   Hao XY, 2012, PHOTOSYNTHETICA, V50, P362, DOI 10.1007/s11099-012-0043-5
   Jablonski LM, 2002, NEW PHYTOL, V156, P9, DOI 10.1046/j.1469-8137.2002.00494.x
   Leakey ADB, 2009, J EXP BOT, V60, P2859, DOI 10.1093/jxb/erp096
   Manderscheid R, 1997, AGR ECOSYST ENVIRON, V64, P65, DOI 10.1016/S0167-8809(97)00020-0
   Manschadi AM, 2006, FUNCT PLANT BIOL, V33, P823, DOI 10.1071/FP06055
   McGrath JM, 2013, PLANT CELL ENVIRON, V36, P697, DOI 10.1111/pce.12007
   Mollah M, 2009, CROP PASTURE SCI, V60, P697, DOI 10.1071/CP08354
   Moore BD, 1999, PLANT CELL ENVIRON, V22, P567, DOI 10.1046/j.1365-3040.1999.00432.x
   Morgan PB, 2005, GLOBAL CHANGE BIOL, V11, P1856, DOI 10.1111/j.1365-2486.2005.001017.x
   Myers SS, 2014, NATURE, V510, P139, DOI 10.1038/nature13179
   Pachauri R.K., 2014, CLIMATE CHANGE 2014
   Perry EM, 2012, INT ARCH PHOTOGRAMM, V39-B8, P317
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Raghuvanshi R. S., 2009, The lentil: botany, production and uses, P408, DOI 10.1079/9781845934873.0408
   Rogers A, 2006, PLANT CELL ENVIRON, V29, P1651, DOI 10.1111/j.1365-3040.2006.01549.x
   Rogers A, 2009, PLANT PHYSIOL, V151, P1009, DOI 10.1104/pp.109.144113
   Serraj R, 1998, PLANT CELL ENVIRON, V21, P491, DOI 10.1046/j.1365-3040.1998.00298.x
   Sicher R, 2010, CAN J PLANT SCI, V90, P257, DOI 10.4141/CJPS09091
   Siddique KHM, 2013, CROP PASTURE SCI, V64, P347, DOI 10.1071/CP13071
   Smith AB, 2007, EUPHYTICA, V157, P253, DOI 10.1007/s10681-007-9418-2
   Taub DR, 2008, J INTEGR PLANT BIOL, V50, P1365, DOI 10.1111/j.1744-7909.2008.00754.x
   Tausz M, 2013, ENVIRON EXP BOT, V88, P71, DOI 10.1016/j.envexpbot.2011.12.005
   Tausz-Posch S, 2015, EUR J AGRON, V64, P21, DOI 10.1016/j.eja.2014.12.009
   Tausz-Posch S, 2013, PHYSIOL PLANTARUM, V148, P232, DOI 10.1111/j.1399-3054.2012.01701.x
   Tausz-Posch S, 2012, FIELD CROP RES, V133, P160, DOI 10.1016/j.fcr.2012.04.007
   Wandtke AA, 2009, URHEBERRECHT, P1, DOI 10.1016/S0065-230X(09)04001-9
   Whitehead SJ, 2000, CROP SCI, V40, P110, DOI 10.2135/cropsci2000.401110x
   Ziska LH, 2012, P ROY SOC B-BIOL SCI, V279, P4097, DOI 10.1098/rspb.2012.1005
   Ziska LH, 2001, CROP SCI, V41, P385, DOI 10.2135/cropsci2001.412385x
NR 47
TC 28
Z9 29
U1 1
U2 64
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1161-0301
EI 1873-7331
J9 EUR J AGRON
JI Eur. J. Agron.
PD JUL
PY 2017
VL 87
BP 50
EP 58
DI 10.1016/j.eja.2017.05.003
PG 9
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA EZ9IJ
UT WOS:000405043200006
OA Bronze, Green Submitted
DA 2025-01-10
ER

PT J
AU Advani, NK
   Kenkel, CD
   Davies, SW
   Parmesan, C
   Singer, MC
   Matz, MV
AF Advani, Nikhil K.
   Kenkel, Carly D.
   Davies, Sarah W.
   Parmesan, Camille
   Singer, Michael C.
   Matz, Mikhail V.
TI Variation in heat shock protein expression at the latitudinal range
   limits of a widely-distributed species, the Glanville fritillary
   butterfly (<i>Melitaea cinxia</i>)
SO PHYSIOLOGICAL ENTOMOLOGY
LA English
DT Article
DE Climate change adaptation; constitutive adjustment hypothesis; Glanville
   fritillary butterfly; glyceraldehyde-3-phosphate dehydrogenase; heat
   shock protein; Hsp20.4; Hsp21.4; Hsp90; latitude; qPCR
ID STRESS RESISTANCE TRAITS; DROSOPHILA-MELANOGASTER; GENETIC-VARIATION;
   HSP70 EXPRESSION; THERMAL ADAPTATION; CLIMATE-CHANGE; PHOSPHOGLUCOSE
   ISOMERASE; ORCHESELLA-CINCTA; METAL TOLERANCE; LYCAENA-TITYRUS
AB Studies of heat shock response show a correlation with local climate, although this is more often across altitudinal than latitudinal gradients. In the present study, differences in constitutive but not inducible components of heat shock response are detected among populations of the Glanville fritillary butterfly Melitaea cinxia L. that exist at the species' latitudinal range limits (Finland and Spain). The study demonstrates that macroclimatic differences between these sites should cause greater exposure of the Spanish population to higher temperatures. Thermal stress treatments are used to estimate differences in the expression of four genes potentially relevant for tolerating these temperatures. For the analysis, three heat-shock proteins and glyceraldehyde-3-phosphate dehydrogenase (G3PDH), a glycolysis enzyme that also modulates cell growth based on metabolic state, are chosen. Two constitutive differences are found between the sites. First, insects from Spain have higher levels of Hsp 21.4 than those from Finland regardless of thermal stress treatment; this protein is not inducible. Second, insects from Finland have higher levels of G3PDH. The two remaining Hsps, Hsp20.4 and Hsp90, show dramatic up-regulation at higher temperatures, although there are no significant differences between insects from the different populations in either constitutive levels or inducibility. In nature, differences between the study populations likely occur in the expression of all four genes that were studied, although these differences would be directly climate-induced in Hsp20.4 and Hsp90 and constitutive in Hsp21.4 and G3PDH. Inducibility may mitigate the need for constitutive variation in traits that adapt insects to local climate.
C1 [Advani, Nikhil K.; Kenkel, Carly D.; Davies, Sarah W.; Matz, Mikhail V.] Univ Texas Austin, Dept Integrat Biol, Austin, TX 78712 USA.
   [Advani, Nikhil K.] World Wildlife Fund, 1250 24th St NW, Washington, DC 20036 USA.
   [Kenkel, Carly D.] Australian Inst Marine Sci, Townsville, Qld, Australia.
   [Davies, Sarah W.] Univ North Carolina Chapel Hill, Dept Marine Sci, Chapel Hill, NC USA.
   [Parmesan, Camille; Singer, Michael C.] Univ Plymouth, Dept Biol Sci, Plymouth, Devon, England.
   [Parmesan, Camille] Univ Texas Austin, Dept Geol Sci, Austin, TX USA.
C3 University of Texas System; University of Texas Austin; World Wildlife
   Fund; Australian Institute of Marine Science; University of North
   Carolina; University of North Carolina Chapel Hill; University of North
   Carolina School of Medicine; University of Plymouth; University of Texas
   System; University of Texas Austin
RP Advani, NK (corresponding author), World Wildlife Fund, 1250 24th St NW, Washington, DC 20036 USA.
EM nkadvani@utexas.edu
RI Singer, Michael/IZE-9090-2023; Parmesan, Camille/GVT-5674-2022; Davies,
   Sarah/ITT-3963-2023; Kenkel, Carly/AGH-5526-2022; Matz,
   Mikhail/K-4392-2017
OI Parmesan, Camille/0000-0002-1515-274X; Matz,
   Mikhail/0000-0001-5453-9819; Advani, Nikhil/0000-0003-2332-1002; Kenkel,
   Carly/0000-0003-1126-4311
FU National Science Foundation [DEB-1054766]
FX We thank Eli Meyer for help with primer selection and design; Galina
   Aglyamova and Wayne Hall for help with the laboratory experiments; James
   Marden and Marjo Saastamoinen for help with obtaining habitat
   temperature data for M. cinxia; and Constanti Stefanescu and Saskya van
   Nouhuys for help with collecting insects from the field. Research was
   supported by National Science Foundation grant DEB-1054766 to M.V.M.
CR Altschul SF, 1997, NUCLEIC ACIDS RES, V25, P3389, DOI 10.1093/nar/25.17.3389
   [Anonymous], 2004, BUTTERFLIES EUROPE
   Atkinson D, 1997, TRENDS ECOL EVOL, V12, P235, DOI 10.1016/S0169-5347(97)01058-6
   Barshis DJ, 2013, P NATL ACAD SCI USA, V110, P1387, DOI 10.1073/pnas.1210224110
   Bennett NL, 2015, OIKOS, V124, P41, DOI 10.1111/oik.01490
   BROWN DC, 1995, MAR ENVIRON RES, V39, P181, DOI 10.1016/0141-1136(94)00014-G
   Curtis RJ, 2015, J INSECT CONSERV, V19, P217, DOI 10.1007/s10841-014-9738-1
   Czechowski T, 2005, PLANT PHYSIOL, V139, P5, DOI 10.1104/pp.105.063743
   Dahlhoff EP, 2000, P NATL ACAD SCI USA, V97, P10056, DOI 10.1073/pnas.160277697
   de Kok JB, 2005, LAB INVEST, V85, P154, DOI 10.1038/labinvest.3700208
   Dutton JM, 2009, J EXP MAR BIOL ECOL, V376, P37, DOI 10.1016/j.jembe.2009.06.001
   Evans TG, 2012, PHILOS T R SOC B, V367, P1733, DOI 10.1098/rstb.2012.0019
   Feder ME, 1999, ANNU REV PHYSIOL, V61, P243, DOI 10.1146/annurev.physiol.61.1.243
   Haag CR, 2005, P ROY SOC B-BIOL SCI, V272, P2449, DOI 10.1098/rspb.2005.3235
   Hanski I, 2006, PLOS BIOL, V4, P719, DOI 10.1371/journal.pbio.0040129
   Hanski IA, 2011, P NATL ACAD SCI USA, V108, P14397, DOI 10.1073/pnas.1110020108
   Hoffmann AA, 2003, J EVOLUTION BIOL, V16, P614, DOI 10.1046/j.1420-9101.2003.00561.x
   HOFFMANN RJ, 1981, BIOCHEM GENET, V19, P129, DOI 10.1007/BF00486143
   Karl I, 2009, J EVOLUTION BIOL, V22, P172, DOI 10.1111/j.1420-9101.2008.01630.x
   Karl I, 2008, OIKOS, V117, P778, DOI 10.1111/j.0030-1299.2008.16522.x
   Kenkel CD, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0026914
   Krebs RA, 1999, CELL STRESS CHAPERON, V4, P243, DOI 10.1379/1466-1268(1999)004<0243:ACOHEA>2.3.CO;2
   Kültz D, 2005, ANNU REV PHYSIOL, V67, P225, DOI 10.1146/annurev.physiol.67.040403.103635
   Kuussaari M, 1996, J ANIM ECOL, V65, P791, DOI 10.2307/5677
   Kuussaari M, 1998, THESIS
   La Sorte FA, 2009, P ROY SOC B-BIOL SCI, V276, P3167, DOI 10.1098/rspb.2009.0162
   Li ZW, 2009, BMC EVOL BIOL, V9, DOI 10.1186/1471-2148-9-215
   LIN JJ, 1995, J EXP BIOL, V198, P551
   Luo SQ, 2015, GENE, V556, P132, DOI 10.1016/j.gene.2014.11.043
   Luo SQ, 2014, J THERM BIOL, V42, P33, DOI 10.1016/j.jtherbio.2014.02.018
   Marden JH, 2013, EVOLUTION, V67, P1105, DOI 10.1111/evo.12004
   Mattila ALK, 2014, J EVOLUTION BIOL, V27, P1733, DOI 10.1111/jeb.12426
   Mattila ALK, 2015, ECOL EVOL, V5, P5539, DOI 10.1002/ece3.1758
   Matz MV, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0071448
   Otsuka Y, 1997, GENES GENET SYST, V72, P19, DOI 10.1266/ggs.72.19
   Pfaffl MW, 2001, NUCLEIC ACIDS RES, V29, DOI 10.1093/nar/29.9.e45
   Pijpe J, 2011, EXP GERONTOL, V46, P426, DOI 10.1016/j.exger.2010.11.033
   PLACE AR, 1978, BIOCHEM GENET, V16, P577, DOI 10.1007/BF00484221
   Ponton F, 2011, J INSECT PHYSIOL, V57, P840, DOI 10.1016/j.jinsphys.2011.03.014
   Roelofs D, 2007, INSECT BIOCHEM MOLEC, V37, P287, DOI 10.1016/j.ibmb.2006.11.013
   Roelofs D, 2010, EVOL ECOL, V24, P527, DOI 10.1007/s10682-009-9345-x
   Roelofs D, 2009, MOL ECOL, V18, P3227, DOI 10.1111/j.1365-294X.2009.04261.x
   Seidler NW, 2013, ADV EXP MED BIOL, V985, P1, DOI 10.1007/978-94-007-4716-6_1
   Shen Y, 2011, J INSECT PHYSIOL, V57, P908, DOI 10.1016/j.jinsphys.2011.03.026
   Sinclair BJ, 2012, PHYSIOL BIOCHEM ZOOL, V85, P594, DOI 10.1086/665388
   Sorensen JG, 2009, FUNCT ECOL, V23, P240, DOI 10.1111/j.1365-2435.2008.01491.x
   Sorensen JG, 2001, FUNCT ECOL, V15, P289, DOI 10.1046/j.1365-2435.2001.00525.x
   Sorensen JG, 2005, J EVOLUTION BIOL, V18, P829, DOI 10.1111/j.1420-9101.2004.00876.x
   Sorte CJB, 2005, MAR BIOL, V146, P985, DOI 10.1007/s00227-004-1508-2
   Stephens Alexandre S, 2011, BMC Res Notes, V4, P410, DOI 10.1186/1756-0500-4-410
   Suggitt AJ, 2012, BIOL LETTERS, V8, P590, DOI 10.1098/rsbl.2012.0112
   Tomanek L, 2002, INTEGR COMP BIOL, V42, P797, DOI 10.1093/icb/42.4.797
   Tomanek L, 2010, J EXP BIOL, V213, P971, DOI 10.1242/jeb.038034
   Van Nouhuys S, 2003, ECOL ENTOMOL, V28, P193, DOI 10.1046/j.1365-2311.2003.00501.x
   Vandesompele J, 2002, GENOME BIOL, V3, DOI 10.1186/gb-2002-3-7-research0034
   Wahlberg N, 2007, EUR J ENTOMOL, V104, P675, DOI 10.14411/eje.2007.085
   Wang GH, 2008, INSECT SCI, V15, P405, DOI 10.1111/j.1744-7917.2008.00227.x
   WATT WB, 1991, FUNCT ECOL, V5, P145, DOI 10.2307/2389252
NR 58
TC 11
Z9 11
U1 1
U2 41
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0307-6962
EI 1365-3032
J9 PHYSIOL ENTOMOL
JI Physiol. Entomol.
PD SEP
PY 2016
VL 41
IS 3
BP 241
EP 248
DI 10.1111/phen.12148
PG 8
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA EA9DE
UT WOS:000386940600008
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Mushtaq, S
   White, N
   Cockfield, G
   Power, B
   Jakeman, G
AF Mushtaq, S.
   White, N.
   Cockfield, G.
   Power, B.
   Jakeman, G.
TI Reconfiguring agriculture through the relocation of production systems
   for water, environment and food security under climate change
SO JOURNAL OF AGRICULTURAL SCIENCE
LA English
DT Article
ID APSIM; MODEL
AB The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations.
   The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.
C1 [Mushtaq, S.; White, N.; Cockfield, G.] Univ So Queensland, Int Ctr Appl Climate Sci, Toowoomba, Qld 4350, Australia.
   [White, N.; Power, B.] Queensland Dept Agr Fisheries & Forestry, Toowoomba, Qld, Australia.
   [Jakeman, G.] ACIL Allen Consulting, Canberra, ACT, Australia.
C3 University of Southern Queensland; Queensland Department of Agriculture
   & Fisheries
RP Mushtaq, S (corresponding author), Univ So Queensland, Int Ctr Appl Climate Sci, Toowoomba, Qld 4350, Australia.
EM Shahbaz.Mushtaq@usq.edu.au
RI White, Neil/C-5782-2008
OI White, Neil/0000-0002-8763-975X; Cockfield, Geoff/0000-0002-0776-3313
FU Department of Agriculture, Fisheries and Forestry (DAFF), Canberra,
   Australia
FX This project was conducted with funding from the Department of
   Agriculture, Fisheries and Forestry (DAFF), Canberra, Australia.
CR [Anonymous], WAT US AUSTR FARMS 2
   Breustedt G, 2007, J AGR ECON, V58, P115, DOI 10.1111/j.1477-9552.2007.00082.x
   Burgess S., 2012, CONSISTENT CLIMATE S
   Camkin J. K., 2007, NO AUSTR IRRIGATION
   Carberry PS, 2011, J AGR SCI-CAMBRIDGE, V149, P77, DOI 10.1017/S0021859610000973
   CSIRO, 2013, FLIND GILB AGR RES A
   CSIRO and Bureau of Meteorology, 2010, TECHNICAL REPORT
   Davidson B., 1966, THE NORTHERN MYTH
   Davison G., 2005, STRUGGLE COUNTRY RUR, P11
   Graham-Taylor S., 1982, LESSONS ORD, P23
   Grundy P., 2009, AUSTR COTTON GROWER, V30, P66
   Grundy P., 2009, AUSTR COTTON GROWER, V30, P18
   Grundy P, 2012, NORpak: Cotton Production and Management Guidelines for the Burdekin and North Queensland Coastal Dry Tropics Region 2012
   Ingram JSI, 2008, AGR ECOSYST ENVIRON, V126, P4, DOI 10.1016/j.agee.2008.01.009
   Jeffrey SJ, 2001, ENVIRON MODELL SOFTW, V16, P309, DOI 10.1016/S1364-8152(01)00008-1
   Keating BA, 2003, EUR J AGRON, V18, P267, DOI 10.1016/S1161-0301(02)00108-9
   MCCOWN RL, 1995, MATH COMPUT SIMULAT, V39, P225, DOI 10.1016/0378-4754(95)00063-2
   McRae D., 2007, CLIMATE CHANGE COTTO
   [Meier Uwe. FBRC Federal Biological Research Center for Agriculture and Forestry FBRC Federal Biological Research Center for Agriculture and Forestry], 2001, Growth stages of mono-and dicotyledonous plants, V2nd, P158
   Murray-Darling Basin Authority, 2010, GUID PROP BAS PLAN
   National Water Commission, 2009, AUSTR WAT REF 2009 2
   Northern Australian Land & Water Taskforce, 2009, SUST DEV NO AUSTR
   Olesen JE, 2002, EUR J AGRON, V16, P239, DOI 10.1016/S1161-0301(02)00004-7
   Potgieter A, 2013, CLIMATIC CHANGE, V117, P163, DOI 10.1007/s10584-012-0543-0
   Power B, 2011, FIELD CROP RES, V124, P171, DOI 10.1016/j.fcr.2011.03.018
   Risbey JS, 2011, REG ENVIRON CHANGE, V11, pS197, DOI 10.1007/s10113-010-0176-7
   Rosenzweig C., 1998, CLIMATE CHANGE GLOBA
   Roth G., 2010, Economic, Environmental and Social Sustainability Indicators of the Australian Cotton Industry
   Shanahan D., 2007, AUSTRALIAN
   Smith I, 2013, CLIMATIC CHANGE, V121, P609, DOI 10.1007/s10584-013-0956-4
   Steffen W, 2011, REG ENVIRON CHANGE, V11, pS205, DOI 10.1007/s10113-010-0178-5
   The Australian, 2012, AUSTRALIAN
   Thiene M, 2013, J AGR ECON, V64, P641, DOI 10.1111/1477-9552.12016
   Watson R. T., 2000, Land use, land-use change and forestry: A special report of the intergovernmental panel on climate change
   Wooding R, 2008, ANZSOG MONOGR, P57
   Zhang Y, 2013, J AGR SCI-CAMBRIDGE, V151, P836, DOI 10.1017/S0021859612000883
   ,, 2007, Climate change 2007: Synthesis Report. Contribution of Working Group I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers
NR 37
TC 3
Z9 3
U1 0
U2 74
PU CAMBRIDGE UNIV PRESS
PI NEW YORK
PA 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA
SN 0021-8596
EI 1469-5146
J9 J AGR SCI-CAMBRIDGE
JI J. Agric. Sci.
PD JUL
PY 2015
VL 153
IS 5
BP 779
EP 797
DI 10.1017/S0021859614001117
PG 19
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA CJ2JX
UT WOS:000355311600002
OA Bronze
DA 2025-01-10
ER

PT J
AU Völker, S
   Baumeister, H
   Classen, T
   Hornberg, C
   Kistemann, T
AF Voelker, Sebastian
   Baumeister, Hendrik
   Classen, Thomas
   Hornberg, Claudia
   Kistemann, Thomas
TI EVIDENCE FOR THE TEMPERATURE-MITIGATING CAPACITY OF URBAN BLUE SPACE - A
   HEALTH GEOGRAPHIC PERSPECTIVE
SO ERDKUNDE
LA English
DT Article
DE Urban blue space; temperature mitigation; climate change adaption; heat
   stress; environmental health; water bodies; urban heat island
ID HEAT-ISLAND; THERMAL ENVIRONMENT; CLIMATE-CHANGE; SEA-BREEZE;
   LAND-COVER; WATER; AREAS; VEGETATION; IMPACTS; COMFORT
AB Climate change is regarded as one of the greatest challenges to cities in the future. Some proposals focus on incorporating urban green space to counter the rise in temperature and ensuing public health hazards. Urban blue spaces, defined as all surface waters within a city, are regarded as a possible factor for temperature mitigation, but effects have not been quantified and so remain underrepresented in research, recommendations for action and planning. A systematic review was conducted of studies quantifying the temperature-mitigating effects of urban blue compared to other urban sites (n=27). The studies included in the review measured air temperatures at various types of urban blue space such as ponds, lakes or rivers and compared them with reference sites at defined distances or to urban reference sites in the same city. The meta-analysis suggested that a cooling effect of 2.5 K (CI 95% 1.9-3.2 K, p<0.01) during the warmest months on northern hemisphere (between May and October) can be attributed to urban blue sites when including remote sensing data. However, research on the air temperature effects of urban blue space remains sparse compared to studies on urban green. The cooling effects clearly attributable to urban blue space are limited by surrounding environmental conditions like microclimate, urban development, wind velocity, wind turbulence, wind direction, temperature and humidity. Future research is needed to help planners use urban blue space efficiently as a temperature-mitigating and health protecting and promoting factor. The temperature-mitigating capacity of urban blue can potentially reduce heat stress in urban areas. To create healthy environments in the cities of the future, a better understanding of health affecting aspects of urban blue is needed to initiate public health action.
C1 [Voelker, Sebastian; Kistemann, Thomas] Univ Bonn, Inst Hyg & Publ Hlth, RG Med Geog & Publ Hlth, D-53105 Bonn, Germany.
   [Baumeister, Hendrik; Classen, Thomas; Hornberg, Claudia] Univ Bielefeld, Sch Publ Hlth, Dept Environm & Hlth 7, D-33615 Bielefeld, Germany.
C3 University of Bonn; University of Bielefeld
RP Völker, S (corresponding author), Univ Bonn, Inst Hyg & Publ Hlth, RG Med Geog & Publ Hlth, Sigmund Freud Str 25, D-53105 Bonn, Germany.
EM sebastian.voelker@ukb.uni-bonn.de; baumeister@uni-bielefeld.de;
   thomas.classen@uni-bielefeld.de; claudia.hornberg@uni-bielefeld.de;
   thomas.kistemann@ukb.uni-bonn.de
RI Classen, Thomas/HDN-4363-2022; Völker, Sebastian/HQZ-3922-2023;
   Kistemann, Thomas/LXA-5389-2024
OI Volker, Sebastian/0000-0002-6187-9253; Kistemann,
   Thomas/0000-0002-3306-7100
FU Fritz and Hildegard Berg Foundation, Essen (Germany)
FX This work is part of the young professionals research group "German
   Healthy Urban Open Spaces". We thank the Fritz and Hildegard Berg
   Foundation, Essen (Germany), for funding.
CR Almendros-Coca M.A., 1992, ESTUDIOS GEOGRAFICOS, V53, P217, DOI 10.3989/egeogr.1992.i207.217
   [Anonymous], 2000, Urban Ecosyst, DOI [10.1023/A:1011355110475, DOI 10.1023/A:1011355110475]
   [Anonymous], GEOGRAPHISCHE RUNDSC
   [Anonymous], 1996, Erdkunde
   [Anonymous], 2008, SYSTEMATIC REV SOCIA
   Arnfield AJ, 2003, INT J CLIMATOL, V23, P1, DOI 10.1002/joc.859
   BOWLER D. E., 2010, SYSTEMATIC REV
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chen XL, 2006, REMOTE SENS ENVIRON, V104, P133, DOI 10.1016/j.rse.2005.11.016
   Chen ZL, 2009, FRONT STRUCT CIV ENG, V3, P462, DOI 10.1007/s11709-009-0066-6
   Comrie A, 2007, GEOGR COMPASS, V1, P325, DOI 10.1111/j.1749-8198.2007.00037.x
   Coutts AM, 2013, PROG PHYS GEOG, V37, P2, DOI 10.1177/0309133312461032
   D'Ippoliti D, 2010, ENVIRON HEALTH-GLOB, V9, DOI 10.1186/1476-069X-9-37
   Deak J, 2011, TOWN PLAN REV, V82, P669, DOI 10.3828/tpr.2011.38
   EEA, 2012, CLIM CHANG IMP VULN, DOI DOI 10.2800/66071
   Fröhlich D, 2013, THEOR APPL CLIMATOL, V111, P547, DOI 10.1007/s00704-012-0678-y
   Ganbo Han, 2011, 2011 International Conference on Multimedia Technology, P4446
   GIVONI B, 1991, ATMOS ENVIRON B-URB, V25, P289, DOI 10.1016/0957-1272(91)90001-U
   Hajat S, 2010, LANCET, V375, P856, DOI 10.1016/S0140-6736(09)61711-6
   Hathway EA, 2012, BUILD ENVIRON, V58, P14, DOI 10.1016/j.buildenv.2012.06.013
   Higgins J., 2008, COCHRANE COLLABORATI
   Hou P, 2013, THEOR APPL CLIMATOL, V111, P109, DOI 10.1007/s00704-012-0629-7
   Huang LM, 2008, THEOR APPL CLIMATOL, V94, P241, DOI 10.1007/s00704-007-0359-4
   Huang LM, 2008, BUILD ENVIRON, V43, P7, DOI 10.1016/j.buildenv.2006.11.025
   IPCC C.W. T., 2007, CLIMATE CHANGE 2007
   ISHII A, 1991, ENERG BUILDINGS, V16, P965, DOI 10.1016/0378-7788(91)90091-G
   JAUREGUI E, 1991, ENERG BUILDINGS, V15, P447
   JENDRITZKY G, 1993, EXPERIENTIA, V49, P733, DOI 10.1007/BF01923541
   KATAYAMA T, 1991, ENERG BUILDINGS, V16, P973, DOI 10.1016/0378-7788(91)90092-H
   Kim YH, 2008, THEOR APPL CLIMATOL, V92, P239, DOI 10.1007/s00704-007-0319-z
   Kjellstrom T, 2010, INT J PUBLIC HEALTH, V55, P97, DOI 10.1007/s00038-009-0090-2
   KOVATS RS, 2008, PUBLIC HLTH, V29, P41, DOI DOI 10.1146/ANNUREV.PUBL-HEALTH.29.020907.090843
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Lopes A, 2011, METEOROL Z, V20, P553, DOI 10.1127/0941-2948/2011/0248
   Mahmoud AHA, 2011, BUILD ENVIRON, V46, P2641, DOI 10.1016/j.buildenv.2011.06.025
   Makhelouf A, 2009, IRAN J ENVIRON HEALT, V6, P35
   Martin J, 2012, J ARID ENVIRON, V84, P9, DOI 10.1016/j.jaridenv.2012.03.019
   Meade M.S., 2005, Medical Geography, V2nd
   Michelozzi P, 2007, ENVIRON HEALTH-GLOB, V6, DOI 10.1186/1476-069X-6-12
   Mohan M, 2013, THEOR APPL CLIMATOL, V112, P647, DOI 10.1007/s00704-012-0758-z
   MUNLV NRW (MINISTERIUM FUR UMWELT UND NATURSCHUTZ LANDWIRTSCHAFT UND VERBRAUCHERSCHUTZ DES LANDES NORDRHEIN-WESTFALEN), 2010, HDB STADTKLIMA MABET
   MURAKAWA S, 1991, ENERG BUILDINGS, V16, P993, DOI 10.1016/0378-7788(91)90094-J
   Nakayama T, 2011, ENVIRON POLLUT, V159, P2164, DOI 10.1016/j.envpol.2010.11.016
   NISHIMURA N., 1998, SOL ENERGY, V64, P197, DOI [10.1016/S0038-092X(98)00116-9, DOI 10.1016/S0038-092X(98)00116-9]
   Oke T. R., 1987, Boundary layer climates, V2nd
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Pauli A., 2010, VERHALTENSTHERAPIE P, V42, P313
   Peng H, 2009, URBAN REMOTE SENSING, P1, DOI [10.1109/URS.2009.5137701, DOI 10.1109/URS.2009.5137701]
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Robine JM, 2008, CR BIOL, V331, P171, DOI 10.1016/j.crvi.2007.12.001
   Robitu M, 2006, SOL ENERGY, V80, P435, DOI 10.1016/j.solener.2005.06.015
   Rydin Y, 2012, LANCET, V379, P2079, DOI 10.1016/S0140-6736(12)60435-8
   Schwarz N, 2012, ECOL INDIC, V18, P693, DOI 10.1016/j.ecolind.2012.01.001
   Shudo H, 1997, ENERG BUILDINGS, V26, P199, DOI 10.1016/S0378-7788(96)01035-3
   Smith C, 2008, ENERG POLICY, V36, P4558, DOI 10.1016/j.enpol.2008.09.011
   Spronken-Smith RA, 2000, INT J CLIMATOL, V20, P1033, DOI 10.1002/1097-0088(200007)20:9<1033::AID-JOC508>3.0.CO;2-U
   Spronken-Smith RA, 1999, BOUND-LAY METEOROL, V93, P287, DOI 10.1023/A:1002001408973
   Sun RH, 2012, ECOL INDIC, V20, P57, DOI 10.1016/j.ecolind.2012.02.006
   Sun RH, 2012, LANDSCAPE URBAN PLAN, V105, P27, DOI 10.1016/j.landurbplan.2011.11.018
   TAHA H, 1988, BUILD ENVIRON, V23, P271, DOI 10.1016/0360-1323(88)90033-9
   Takahashi R, 2010, 7 INT C LYON
   Tuller SE, 1995, INT J CLIMATOL, V15, P1387, DOI 10.1002/joc.3370151206
   Upmanis H, 1998, INT J CLIMATOL, V18, P681, DOI 10.1002/(SICI)1097-0088(199805)18:6<681::AID-JOC289>3.0.CO;2-L
   Völker S, 2013, SOC SCI MED, V78, P113, DOI 10.1016/j.socscimed.2012.09.047
   Völker S, 2011, INT J HYG ENVIR HEAL, V214, P449, DOI 10.1016/j.ijheh.2011.05.001
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Walker C, 2013, URBAN ECOSYST, V16, P313, DOI 10.1007/s11252-012-0256-1
   WHO-EURO (WORLD HEALTH ORGANIZATION), 2008, HEAT HLTH ACT PLANS
   WMO (WORLD METEOROLOGICAL ORGANIZATION), 2010, GUID CLIM PRACT WMO
   WONG N. H., 2011, ICSDC 2011, P81
   World Health Organization World Meteorological Organization, 2012, ATL HLTH CLIM
NR 72
TC 108
Z9 113
U1 14
U2 210
PU BOSS DRUCK MEDIEN GMBH
PI GOCH
PA POSTFACH 10 01 54, GOCH, 47561, GERMANY
SN 0014-0015
J9 ERDKUNDE
JI Erdkunde
PD OCT-DEC
PY 2013
VL 67
IS 4
BP 355
EP 371
DI 10.3112/erdkunde.2013.04.05
PG 17
WC Geography; Geography, Physical
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geography; Physical Geography
GA 283MH
UT WOS:000329249700005
DA 2025-01-10
ER

PT J
AU Zhang, YH
   Zhang, YL
   Wu, Y
   He, XJ
   Zhang, PX
   Ming, YJ
   Yan, JZ
AF Zhang, Yihao
   Zhang, Yili
   Wu, Ya
   He, Xinjun
   Zhang, Puxin
   Ming, Yujia
   Yan, Jianzhong
TI Policy measures mitigate the adoption of crop diversification strategies
   by farmers: insights from the Tibetan Plateau
SO ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
LA English
DT Article; Early Access
DE Policy support; Subsidies; Crop diversification; Climatic adaptation;
   Rural household survey; Interaction effect analysis
ID CLIMATE-CHANGE; ADAPTING AGRICULTURE; DROUGHT ADAPTATION; POVERTY
   REDUCTION; AREA EVIDENCE; IMPACTS; VULNERABILITY; DETERMINANTS;
   VARIABILITY; PERCEPTIONS
AB Crop diversification is a critical adaptation strategy for farmers to cope with climate change, but with the protection of policy measures, farmers might forego pursuing crop diversification. Nevertheless, few studies have focused on the impact of policy measures on crop diversification, especially in regions with severe climate change. This study field surveyed 684 rural households on the Tibetan Plateau to obtain the implementation of policy measures and the level of crop diversification. By using the Tobit regression model, the impact of policy measures on crop diversification was explored. The results indicated that climate change promoted the adoption of crop diversification by farmers; however, the effect reversed when interacting with policy measures such as non-agricultural subsidies, low-interest loans, and agricultural technique training. This finding can help adjust policy measures in other regions severely affected by climate change and establish effective connections between governments and farmers to improve climate adaptation capabilities.
C1 [Zhang, Yihao; Ming, Yujia] Chongqing Univ, Sch Management Sci & Real Estate, Chongqing 400045, Peoples R China.
   [Zhang, Yili] Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
   [Wu, Ya; Yan, Jianzhong] Southwest Univ, Coll Resources & Environm, Chongqing 400715, Peoples R China.
   [He, Xinjun] Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China.
   [Zhang, Puxin] Sichuan Acad Social Sci, Publ Management Res Inst, Chengdu 610071, Peoples R China.
C3 Chongqing University; Chinese Academy of Sciences; Institute of
   Geographic Sciences & Natural Resources Research, CAS; Southwest
   University - China; Chinese Academy of Sciences; Institute of Mountain
   Hazards & Environment, CAS
RP Yan, JZ (corresponding author), Southwest Univ, Coll Resources & Environm, Chongqing 400715, Peoples R China.
EM zhangyhsw@126.com; zhangyl@igsnrr.ac.cn; mswuya@swu.edu.cn;
   hexinjun@imde.ac.cn; zpxswjtu@163.com; 20150659@cqu.edu.cn;
   yanjzswu@126.com
RI He, Xinjun/GXV-2399-2022
FU National Natural Science Foundation of China
FX We appreciate the contributions of anonymous reviewers. Jiyao Yan from
   Bashu International Education Center participates in data analysis.
CR Alam MM, 2012, MITIG ADAPT STRAT GL, V17, P173, DOI 10.1007/s11027-011-9319-5
   Aliabadi V, 2022, WEATHER CLIM SOC, V14, P561, DOI 10.1175/WCAS-D-21-0153.1
   Antwi-Agyei P, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100304
   Anwar MR, 2013, THEOR APPL CLIMATOL, V113, P225, DOI 10.1007/s00704-012-0780-1
   Appiah-Twumasi M, 2024, ENVIRON DEV SUSTAIN, V26, P157, DOI 10.1007/s10668-022-02703-x
   Arbuckle JG Jr, 2015, ENVIRON BEHAV, V47, P205, DOI 10.1177/0013916513503832
   Arunrat N, 2017, J CLEAN PROD, V143, P672, DOI 10.1016/j.jclepro.2016.12.058
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P5045, DOI 10.1007/s10668-019-00414-4
   Cohen AAB, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0229774
   Bhatta GD, 2016, CLIM DEV, V8, P145, DOI 10.1080/17565529.2015.1016883
   Bonzanigo L, 2016, REG ENVIRON CHANGE, V16, P245, DOI 10.1007/s10113-014-0750-5
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Cao SX, 2009, LAND USE POLICY, V26, P1182, DOI 10.1016/j.landusepol.2009.02.006
   Challinor A, 2007, CLIMATIC CHANGE, V83, P381, DOI 10.1007/s10584-007-9249-0
   Chen H, 2014, GLOBAL ENVIRON CHANG, V24, P193, DOI 10.1016/j.gloenvcha.2013.11.010
   Chen S, 2021, J DEV ECON, V148, DOI 10.1016/j.jdeveco.2020.102557
   Chinse E, 2019, LAND DEGRAD DEV, V30, P533, DOI 10.1002/ldr.3190
   Cook BI, 2018, CURR CLIM CHANGE REP, V4, P164, DOI 10.1007/s40641-018-0093-2
   Dessie AB, 2019, ECOL PROCESS, V8, DOI 10.1186/s13717-019-0203-7
   Di Falco S, 2014, J AGR ECON, V65, P485, DOI 10.1111/1477-9552.12053
   Di Falco S, 2010, LAND USE POLICY, V27, P763, DOI 10.1016/j.landusepol.2009.10.007
   Donatti CI, 2019, CLIM DEV, V11, P264, DOI 10.1080/17565529.2018.1442796
   Eshetu G, 2021, CLIM DEV, V13, P318, DOI 10.1080/17565529.2020.1772706
   Fahad S, 2018, LAND USE POLICY, V79, P301, DOI 10.1016/j.landusepol.2018.08.018
   Ge YH, 2023, CLIM RISK MANAG, V39, DOI 10.1016/j.crm.2023.100482
   Goswami S, 2017, INDIAN J ECON DEV, V13, P228, DOI 10.5958/2322-0430.2017.00070.1
   He XJ, 2022, J CLEAN PROD, V381, DOI 10.1016/j.jclepro.2022.135171
   He XJ, 2022, J RURAL STUD, V95, P544, DOI 10.1016/j.jrurstud.2022.10.003
   He XJ, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01752-8
   Heath LC, 2020, ENVIRON RES, V188, DOI 10.1016/j.envres.2020.109636
   Herwehe L, 2018, CLIM DEV, V10, P337, DOI 10.1080/17565529.2017.1301862
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Hufnagel J, 2020, AGRON SUSTAIN DEV, V40, DOI 10.1007/s13593-020-00617-4
   Jamshidi O, 2019, CLIM RISK MANAG, V23, P146, DOI 10.1016/j.crm.2018.06.002
   Karimi V, 2018, J INTEGR AGR, V17, P1, DOI 10.1016/S2095-3119(17)61794-5
   Kemboi E, 2020, COGENT FOOD AGR, V6, DOI 10.1080/23311932.2020.1834669
   Khan I, 2020, LAND USE POLICY, V91, DOI 10.1016/j.landusepol.2019.104395
   Kumar CR, 2022, J PUBLIC AFF, V22, DOI 10.1002/pa.2450
   Sen LTH, 2021, CLIM SERV, V24, DOI 10.1016/j.cliser.2021.100267
   Li CY, 2013, ENVIRON MANAGE, V52, P894, DOI 10.1007/s00267-013-0139-0
   Li MP, 2017, GLOBAL ENVIRON CHANG, V47, P143, DOI 10.1016/j.gloenvcha.2017.10.004
   Li XY, 2018, ECOL INDIC, V87, P285, DOI 10.1016/j.ecolind.2017.12.042
   Li XY, 2017, J GEOGR SCI, V27, P1481, DOI 10.1007/s11442-017-1448-7
   Lin BB, 2011, BIOSCIENCE, V61, P183, DOI 10.1525/bio.2011.61.3.4
   Liu YH, 2016, APPL GEOGR, V73, P62, DOI 10.1016/j.apgeog.2016.06.004
   Lu C, 2020, GROWTH CHANGE, V51, P1804, DOI 10.1111/grow.12431
   Maggio G, 2021, J DEV STUD, V57, P264, DOI 10.1080/00220388.2020.1769072
   Makate C, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2802-4
   Malaiarasan U, 2021, PADDY WATER ENVIRON, V19, P417, DOI 10.1007/s10333-021-00843-w
   Martey E, 2022, ENERG POLICY, V165, DOI 10.1016/j.enpol.2022.112952
   McCord PF, 2015, LAND USE POLICY, V42, P738, DOI 10.1016/j.landusepol.2014.10.012
   Meldrum G, 2018, ENVIRON DEV SUSTAIN, V20, P703, DOI 10.1007/s10668-016-9906-4
   Mersha AA, 2018, WORLD DEV, V107, P87, DOI 10.1016/j.worlddev.2018.03.001
   Min S, 2017, CHINA AGR ECON REV, V9, P188, DOI 10.1108/CAER-07-2016-0097
   Mondal P, 2015, J ENVIRON MANAGE, V148, P21, DOI 10.1016/j.jenvman.2014.02.026
   Mwinjaka O, 2010, CLIM DEV, V2, P346, DOI 10.3763/cdev.2010.0058
   Mzyece A, 2021, J AGR FOOD RES, V5, DOI 10.1016/j.jafr.2021.100162
   Nam Le Phuong, 2022, AgBioForum, V24, P13
   Ndip FE, 2023, LAND USE POLICY, V130, DOI 10.1016/j.landusepol.2023.106663
   Nyima Y, 2014, AREA, V46, P186, DOI 10.1111/area.12099
   Ochieng J, 2020, CLIMATIC CHANGE, V162, P1107, DOI 10.1007/s10584-020-02727-0
   Orlowsky B, 2012, CLIMATIC CHANGE, V110, P669, DOI 10.1007/s10584-011-0122-9
   Osterholz WR, 2018, FIELD CROP RES, V219, P33, DOI 10.1016/j.fcr.2018.01.026
   Panepinto D, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18136767
   Ponce C, 2020, WORLD DEV, V127, DOI 10.1016/j.worlddev.2019.104740
   Pritchard MF, 2013, LAND USE POLICY, V30, P186, DOI 10.1016/j.landusepol.2012.03.012
   Sertse SF, 2021, INT J DISAST RISK RE, V60, DOI 10.1016/j.ijdrr.2021.102255
   Singh S, 2020, ECOL INDIC, V116, DOI 10.1016/j.ecolind.2020.106475
   Smale M, 2003, AGR ECON-BLACKWELL, V28, P13, DOI 10.1111/j.1574-0862.2003.tb00131.x
   Song XQ, 2021, ECOL ECON, V190, DOI 10.1016/j.ecolecon.2021.107184
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Swami D, 2020, CLIMATIC CHANGE, V163, P2175, DOI 10.1007/s10584-020-02935-8
   Udmale P, 2014, INT J DISAST RISK RE, V10, P250, DOI 10.1016/j.ijdrr.2014.09.011
   Waldman KB, 2017, GLOBAL ENVIRON CHANG, V47, P51, DOI 10.1016/j.gloenvcha.2017.09.007
   Wang P, 2019, ECOL INDIC, V101, P1055, DOI 10.1016/j.ecolind.2019.02.007
   Wang T, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12198164
   Wang YT, 2024, ECOL INDIC, V158, DOI 10.1016/j.ecolind.2023.111351
   Wilbanks TJ, 2003, CLIM POLICY, V3, pS147, DOI 10.1016/j.clipol.2003.10.013
   Wilk J, 2013, REG ENVIRON CHANGE, V13, P273, DOI 10.1007/s10113-012-0323-4
   Wu MZ, 2022, INT J CLIM CHANG STR, V14, P20, DOI 10.1108/IJCCSM-03-2021-0031
   Yang SS, 2021, CLIMATIC CHANGE, V164, DOI 10.1007/s10584-021-02992-7
   Yu Y, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116208
   Zhang CH, 2021, J INTEGR AGR, V20, P953, DOI 10.1016/S2095-3119(21)63634-1
   Zhang QQ, 2023, ENERGY REP, V9, P539, DOI 10.1016/j.egyr.2022.12.001
   Zhang YH, 2022, LAND USE POLICY, V113, DOI 10.1016/j.landusepol.2021.105928
   Zhang YH, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18052682
   Zhou H, 2020, LAND USE POLICY, V99, DOI 10.1016/j.landusepol.2020.105088
NR 87
TC 2
Z9 2
U1 19
U2 23
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1387-585X
EI 1573-2975
J9 ENVIRON DEV SUSTAIN
JI Environ. Dev. Sustain.
PD 2024 JUN 9
PY 2024
DI 10.1007/s10668-024-05093-4
EA JUN 2024
PG 30
WC Green & Sustainable Science & Technology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA TO4W7
UT WOS:001242200800001
DA 2025-01-10
ER

PT J
AU Bosma, C
   Hein, L
AF Bosma, Charissa
   Hein, Lars
TI The climate and land use change nexus: Implications for designing
   adaptation and conservation investment strategies in Sub-Saharan Africa
SO SUSTAINABLE DEVELOPMENT
LA English
DT Article
DE adaptation; climate change; DPSIR; investments; land use change;
   Sub-Saharan Africa
ID ECOSYSTEM SERVICES; DPSIR FRAMEWORK; BIODIVERSITY; BALANCE; TRENDS;
   UNCERTAINTIES; DISPLACEMENT; VARIABILITY; POPULATION; MANAGEMENT
AB Climate change and land use change are two global and interacting forces of change that have wide-reaching effects on socio-ecological systems. Despite their interconnectedness, the two are mostly considered separately in investment programs. Therefore, without an integrated systemic approach that considers these interactions, we will fail to achieve the ambitions to deliver on the Sustainable Development Goals. By integrating the Driver-Pressure-State-Impact-Response framework and the System of Environmental-Economic Accounts Ecosystem Accounting, this paper assesses how the interlinkages between climate change and land use change can be jointly considered in the design of climate adaptation and ecosystem conservation investments. The analysis points to the following priorities for interventions in an integrated approach: forest conservation, protection of peatlands, climate-smart agriculture, and restoration of degraded lands. The paper furthermore suggests a set of systemic investment principles that can contribute to capital allocation for climate adaptation and conservation.
C1 [Bosma, Charissa] Netherlands Dev Finance Co, Impact Dept, FMO, The Hague, Netherlands.
   [Bosma, Charissa; Hein, Lars] Wageningen Univ & Res, Dept Environm Sci Environm Syst Anal, Wageningen, Netherlands.
   [Bosma, Charissa] Wageningen Univ & Res, Postbus 47, NL-6700 AA Wageningen, Netherlands.
C3 Wageningen University & Research; Wageningen University & Research
RP Bosma, C (corresponding author), Wageningen Univ & Res, Postbus 47, NL-6700 AA Wageningen, Netherlands.
EM charissa.bosma@wur.nl
CR Aké KMH, 2023, SUSTAIN DEV, V31, P334, DOI 10.1002/sd.2395
   Akinyi DP, 2021, REG SUSTAIN, V2, P130, DOI 10.1016/j.regsus.2021.05.002
   Albrecht S, 2021, J AGRIC FOOD SYST CO, V10, P91, DOI 10.5304/jafscd.2021.103.014
   Alcamo J, 2005, ECOL SOC, V10
   Aleman JC, 2016, GLOBAL CHANGE BIOL, V22, P3013, DOI 10.1111/gcb.13299
   Alexander P, 2015, GLOBAL ENVIRON CHANG, V35, P138, DOI 10.1016/j.gloenvcha.2015.08.011
   Anderegg WRL, 2013, NAT CLIM CHANGE, V3, P30, DOI 10.1038/nclimate1635
   [Anonymous], 2021, NAT CLIM CHANGE, V11, P887, DOI 10.1038/s41558-021-01213-4
   [Anonymous], 1999, Environmental Indicators: Typology and Overview
   [Anonymous], 2019, Global Landscape of Climate Finance 2019
   [Anonymous], 2009, BIOGEOSCIENCES DISCU, DOI [DOI 10.5194/BGD-6-2085-2009, DOI 10.5194/bgd-6-2085-2009]
   [Anonymous], 2021, WMO-No. 1290
   Antwi-Agyei P, 2019, GEOSCIENCES, V9, DOI 10.3390/geosciences9070286
   Arrow K, 2013, SCIENCE, V341, P349, DOI 10.1126/science.1235665
   Austin KG, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-19578-z
   Bajzelj B, 2014, LAND-BASEL, V3, P898, DOI 10.3390/land3030898
   Barbier EB, 2018, SCIENCE, V360, P486, DOI 10.1126/science.aar3454
   Biddulph GE, 2021, BOIS FOR TROP, P3, DOI 10.19182/bft2021.350.a36288
   Bogaart P., 2019, SESSION 7 VALUATION
   Bosma C, 2017, LAND USE POLICY, V60, P181, DOI 10.1016/j.landusepol.2016.10.010
   Bott R., 2014, Igarss, DOI DOI 10.1007/S13398-014-0173-7.2
   Busch J, 2019, NAT CLIM CHANGE, V9, P463, DOI 10.1038/s41558-019-0485-x
   Carlson KM, 2017, NAT CLIM CHANGE, V7, P63, DOI [10.1038/NCLIMATE3158, 10.1038/nclimate3158]
   Ciais P, 2011, PHILOS T R SOC A, V369, P2038, DOI 10.1098/rsta.2010.0328
   Clark R, 2018, LAND USE POLICY, V71, P335, DOI 10.1016/j.landusepol.2017.12.013
   Collier P, 2008, OXFORD REV ECON POL, V24, P337, DOI 10.1093/oxrep/grn019
   Comarazamy DE, 2013, J CLIMATE, V26, P1535, DOI 10.1175/JCLI-D-12-00087.1
   Cook KH, 2012, CLIM DYNAM, V39, P2937, DOI 10.1007/s00382-012-1324-1
   Costanza J K., 2019, Curr. Landscape Ecol. Rep., V4, P1, DOI DOI 10.1007/S40823-019-0035-2
   Costanza R, 2014, GLOBAL ENVIRON CHANG, V26, P152, DOI 10.1016/j.gloenvcha.2014.04.002
   Crezee B, 2022, NAT GEOSCI, V15, P639, DOI 10.1038/s41561-022-00966-7
   Daily G. C., 1997, Nature's services: societal dependence on natural ecosystems., P113
   Dale VH, 1997, ECOL APPL, V7, P753, DOI 10.1890/1051-0761(1997)007[0753:TRBLUC]2.0.CO;2
   Dargie GC, 2017, NATURE, V542, P86, DOI 10.1038/nature21048
   Dinerstein E, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abb2824
   Dinesh D, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10082616
   Diwakar V, 2021, SUSTAIN DEV, V29, P552, DOI 10.1002/sd.2200
   Dixon JA, 2001, FARMING SYSTEMS POVE
   Doherty RM, 2010, GLOBAL CHANGE BIOL, V16, P617, DOI 10.1111/j.1365-2486.2009.01997.x
   Duku C, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abfcfb
   Duku C, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0192642
   Egoh BN, 2012, ECOSYST SERV, V2, P71, DOI 10.1016/j.ecoser.2012.09.004
   Epule TE, 2015, GEOJOURNAL, V80, P79, DOI 10.1007/s10708-014-9528-z
   European Space Agency Climate Change Initiative, 2019, ESA LAND COV CLIM CH
   Fankhauser S., 2016, The economics of climate-resilient development
   Fankhauser S, 2017, ANNU REV RESOUR ECON, V9, P209, DOI 10.1146/annurev-resource-100516-033554
   Fenta AA, 2020, ECOSYST SERV, V45, DOI 10.1016/j.ecoser.2020.101154
   Freeman MC, 2013, ACCOUNT AUDIT ACCOUN, V26, P715, DOI 10.1108/AAAJ-02-2013-1226
   Fu BJ, 2015, J SOIL SEDIMENT, V15, P833, DOI 10.1007/s11368-015-1082-x
   Giller KE, 2021, OUTLOOK AGR, V50, P13, DOI 10.1177/0030727021998063
   Global Commission on Adaptation, 2019, Adapt Now: A Global Call for Leadership on Climate Resilience
   Griscom BW, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0126
   Guo F, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03268-y
   Gupta J, 2020, INT ENVIRON AGREEM-P, V20, P731, DOI 10.1007/s10784-020-09515-2
   Haase D, 2007, LANDSCAPE URBAN PLAN, V80, P1, DOI 10.1016/j.landurbplan.2006.03.011
   Han S, 2023, SUSTAIN DEV, V31, P510, DOI 10.1002/sd.2406
   Harrison PA, 2014, ECOSYST SERV, V9, P191, DOI 10.1016/j.ecoser.2014.05.006
   Hasan SS, 2020, ENVIRON DEV, V34, DOI 10.1016/j.envdev.2020.100527
   Havemann T, 2020, AGR HUM VALUES, V37, P1281, DOI 10.1007/s10460-020-10131-8
   Headey DD, 2014, FOOD POLICY, V48, P18, DOI 10.1016/j.foodpol.2014.05.005
   Hein L, 2020, SCIENCE, V367, P514, DOI 10.1126/science.aaz8901
   Heubes J, 2011, J BIOGEOGR, V38, P2248, DOI 10.1111/j.1365-2699.2011.02560.x
   Hodgson JA, 2011, J APPL ECOL, V48, P148, DOI 10.1111/j.1365-2664.2010.01919.x
   Hoffman Timm, 2008, Rangelands, V30, P12, DOI 10.2111/1551-501X(2008)30[12:CCIOAR]2.0.CO;2
   Holden ST, 2014, FOOD POLICY, V48, P88, DOI 10.1016/j.foodpol.2014.03.005
   Humpenöder F, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abae2a
   Ingram JC, 2022, ECOSYST SERV, V55, DOI 10.1016/j.ecoser.2022.101434
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   International Bank for Reconstruction and Development World Bank, 2020, INV GLOB DIFF TECHN
   International Food Policy Research Institute, 2011, CLIMATE CHANGE IMPAC
   IPBES, 2018, Regional Assessment Report on Biodiversity and Ecosystem Services for Europe and Central Asia
   IPBES, 2019, Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, DOI DOI 10.5281/ZENODO.3553579
   Janetos AC, 2020, CLIMATIC CHANGE, V161, P171, DOI 10.1007/s10584-019-02651-y
   Jin G, 2017, PHYS CHEM EARTH, V101, P70, DOI 10.1016/j.pce.2017.03.003
   Kaushal SS, 2017, WATER-SUI, V9, DOI 10.3390/w9100815
   Keenan RJ, 2015, FOREST ECOL MANAG, V352, P9, DOI 10.1016/j.foreco.2015.06.014
   Keil P, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms9837
   Kemp L., 2022, Proceedings of the National Academy of Sciences (PNAS), V10, DOI DOI 10.1029/2022EF002876
   Kiely L, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-27353-x
   Kogo BK, 2021, ENVIRON DEV SUSTAIN, V23, P23, DOI 10.1007/s10668-020-00589-1
   Komatsuzaki M, 2007, SUSTAIN SCI, V2, P103, DOI 10.1007/s11625-006-0014-5
   Kosanic A, 2020, ECOSYST SERV, V45, DOI 10.1016/j.ecoser.2020.101168
   Kotir Julius H., 2011, Environment Development and Sustainability, V13, P587, DOI 10.1007/s10668-010-9278-0
   Kuyah Shem, 2016, International Journal of Biodiversity Science Ecosystem Services & Management, V12, P255, DOI 10.1080/21513732.2016.1214178
   Lal R, 2018, J SOIL WATER CONSERV, V73, pA145, DOI 10.2489/jswc.73.6.145A
   Lal R, 2018, GLOBAL CHANGE BIOL, V24, P3285, DOI 10.1111/gcb.14054
   Lamb WF, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abee4e
   Lawrence D, 2015, NAT CLIM CHANGE, V5, P27, DOI [10.1038/NCLIMATE2430, 10.1038/nclimate2430]
   Leisher C, 2022, BIODIVERS CONSERV, V31, P1329, DOI 10.1007/s10531-022-02394-w
   Lenton TM, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0123
   Loveland ThomasRezaul Mahmood., 2012, National Climate Assessment Technical Report on the Impacts of Climate and Land Use and Land Cover Change
   Lundberg C, 2005, AMBIO, V34, P433, DOI 10.1639/0044-7447(2005)034[0433:CTBSEA]2.0.CO;2
   Lynch J, 2021, FRONT SUSTAIN FOOD S, V4, DOI 10.3389/fsufs.2020.518039
   Mahmood R, 2014, INT J CLIMATOL, V34, P929, DOI 10.1002/joc.3736
   Maitima J. M., 2009, African Journal of Environmental Science and Technology, V3, P310
   Malhi Y., 2020, Climate Change and Ecosystems: Threats, Opportunities and Solutions, V375, DOI [10.1098/rstb.2019.0104, DOI 10.1098/RSTB.2019.0104]
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Maxim L, 2009, ECOL ECON, V69, P12, DOI 10.1016/j.ecolecon.2009.03.017
   Mayer B, 2016, ASIA PAC J ENVIRON, V19, P79, DOI 10.4337/apjel.2016.01.04
   Mbow C, 2014, NATURE, V508, P192, DOI 10.1038/508192a
   Meadows D.H., 2015, Thinking in Systems, DOI DOI 10.1016/j.jenvman.2017.12.002
   Mendelsohn R, 2009, ANNU REV RESOUR ECON, V1, P309, DOI 10.1146/annurev.resource.050708.144246
   Meyfroidt P, 2013, CURR OPIN ENV SUST, V5, P438, DOI 10.1016/j.cosust.2013.04.003
   Miller MA, 2022, SUSTAIN DEV, V30, P241, DOI 10.1002/sd.2241
   Molotoks A, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0189
   Mori AS, 2017, J APPL ECOL, V54, P12, DOI 10.1111/1365-2664.12669
   Moss ED, 2021, LAND USE POLICY, V105, DOI 10.1016/j.landusepol.2021.105394
   Myhre G, 2003, J CLIMATE, V16, P1511, DOI 10.1175/1520-0442-16.10.1511
   Nerland R, 2023, SUSTAIN DEV, V31, P39, DOI 10.1002/sd.2371
   Netherlands Environmental Assessment Agency, 2020, TRENDS GLOB CO 2 TOT
   Nordhaus W.D., 2006, The Stern Review on the Economics of Climate Change
   Nunez S, 2021, BIODIVERS CONSERV, V30, P3685, DOI 10.1007/s10531-021-02271-y
   Oeba VO, 2017, CLIM CHANG MANAG, P153, DOI 10.1007/978-3-319-49520-0_10
   OECD, 2020, BLEND FIN PRIN GUID
   Ofori IK, 2023, SUSTAIN DEV, V31, P452, DOI 10.1002/sd.2403
   Ofori SA, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.680924
   Oliver TH, 2014, WIRES CLIM CHANGE, V5, P317, DOI 10.1002/wcc.271
   Olorunfemi IE, 2022, ENVIRON DEV SUSTAIN, V24, P40, DOI 10.1007/s10668-021-01484-z
   Patt A., 2007, APPL CLIMATE INF AFR
   Patt A, 2010, GLOBAL ENVIRON CHANG, V20, P153, DOI 10.1016/j.gloenvcha.2009.10.007
   Pereira P, 2020, SCI TOTAL ENVIRON, V702, DOI 10.1016/j.scitotenv.2019.135008
   Pielke RA, 2016, PHYS TODAY, V69, P40, DOI 10.1063/PT.3.3364
   Pimm SL, 2014, SCIENCE, V344, P987, DOI 10.1126/science.1246752
   Potapov P, 2022, NAT FOOD, V3, P19, DOI 10.1038/s43016-021-00429-z
   Power AG, 2010, PHILOS T R SOC B, V365, P2959, DOI 10.1098/rstb.2010.0143
   Reverte C, 2022, SUSTAIN DEV, V30, P1882, DOI 10.1002/sd.2354
   Rhodes CJ, 2017, SCI PROGRESS-UK, V100, P80, DOI 10.3184/003685017X14876775256165
   Gari SR, 2015, OCEAN COAST MANAGE, V103, P63, DOI 10.1016/j.ocecoaman.2014.11.013
   Robinson DA, 2019, GLOBAL CHANGE BIOL, V25, P1895, DOI 10.1111/gcb.14626
   Rockstrom J., 2015, Bounding the Planetary Future: Why We Need a Great Transition
   Rosenstock TS, 2021, NAT CLIM CHANGE, V11, P463, DOI 10.1038/s41558-021-01055-0
   Scharlemann JPW, 2020, SUSTAIN SCI, V15, P1573, DOI 10.1007/s11625-020-00799-6
   Seddon N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0120
   Seidl A, 2020, ECOSYST SERV, V46, DOI 10.1016/j.ecoser.2020.101216
   Serdeczny O, 2017, REG ENVIRON CHANGE, V17, P1585, DOI 10.1007/s10113-015-0910-2
   Sheffield J, 2008, J CLIMATE, V21, P432, DOI 10.1175/2007JCLI1822.1
   Song XP, 2018, NATURE, V560, P639, DOI 10.1038/s41586-018-0411-9
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Thompson H. E., 2010, Sustainability, V2, P2719, DOI 10.3390/su2082719
   Tietjen B., 2019, FINANCE ADAPT MAKING
   Tongwane MI, 2018, AGR SYST, V166, P124, DOI 10.1016/j.agsy.2018.08.011
   Tscherning K, 2012, LAND USE POLICY, V29, P102, DOI 10.1016/j.landusepol.2011.05.009
   Turner MG, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0105
   Turner WR, 2007, BIOSCIENCE, V57, P868, DOI 10.1641/B571009
   Uda SK, 2020, WETL ECOL MANAG, V28, P509, DOI 10.1007/s11273-020-09728-x
   Uda SK, 2017, WETL ECOL MANAG, V25, P683, DOI 10.1007/s11273-017-9544-0
   UN, 2022, World population prospects 2022
   UNEP, 2021, Adaptation Gap Report 2021: The Gathering Storm-Adapting to Climate Change in a Post-Pandemic World
   United Nations, 2021, System of Environmental-Economic Accounting: Ecosystem Accounting: Final Draft
   United Nations, 2015, UNFCCC PAR AGR
   United Nations Statistics Division, 2021, SYST ENV EC ACC EC A
   Valentini R, 2014, BIOGEOSCIENCES, V11, P381, DOI 10.5194/bg-11-381-2014
   van Noordwijk M, 2019, P NATL ACAD SCI USA, V116, P8102, DOI 10.1073/pnas.1903554116
   Verburg P. H., 2004, GeoJournal, V61, P309, DOI 10.1007/s10708-004-4946-y
   Vermeulen SJ, 2012, ANNU REV ENV RESOUR, V37, P195, DOI 10.1146/annurev-environ-020411-130608
   Vrieling A, 2013, REMOTE SENS-BASEL, V5, P982, DOI 10.3390/rs5020982
   Weinzettel J, 2013, GLOBAL ENVIRON CHANG, V23, P433, DOI 10.1016/j.gloenvcha.2012.12.010
   White C, 2020, AM J ECON SOCIOL, V79, P799, DOI 10.1111/ajes.12334
   Winkler K, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22702-2
   World Bank, 2023, World development indicators
   Wu JQ, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-78182-9
   Yan D, 2013, AGR SYST, V119, P10, DOI 10.1016/j.agsy.2013.04.001
   Zabel F, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10775-z
   Zhao F, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su131810153
NR 166
TC 5
Z9 5
U1 4
U2 17
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0968-0802
EI 1099-1719
J9 SUSTAIN DEV
JI Sustain. Dev.
PD OCT
PY 2023
VL 31
IS 5
BP 3811
EP 3830
DI 10.1002/sd.2627
EA JUN 2023
PG 20
WC Development Studies; Green & Sustainable Science & Technology; Regional
   & Urban Planning
WE Social Science Citation Index (SSCI)
SC Development Studies; Science & Technology - Other Topics; Public
   Administration
GA T9KL2
UT WOS:001007071000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Smithers, J
   Blay-Palmer, A
AF Smithers, J
   Blay-Palmer, A
TI Technology innovation as a strategy for climate adaptation in
   agriculture
SO APPLIED GEOGRAPHY
LA English
DT Article
DE adaptation; agricultural research; climate change; soybean cultivation;
   technology innovation
ID VARIABILITY; CANADA; METHODOLOGY; ONTARIO; GROWTH
AB Technological research and development are among the most frequently advocated strategies for adapting agriculture to possible future changes in climate. However, while many statements point to the reliance that is placed on technology, and to the power of induced innovation, the actual process of agricultural research and development has received little explicit consideration in the context of climatic constraints on food production. This paper offers both a descriptive assessment and empirical analysis of the place of technology research and development in climate adaptation research and planning. Insights into the assumed role of technology are developed through a review of the published literature and recent commentary. The role of technological innovation in the handling of climatic risks is then explored empirically in an analysis of innovation research and development in the Ontario soybean industry. This reveals an array of technological innovations that have helped Ontario soybean-growers manage climatic challenges to date, as well as a range of potential constraints on the innovation process itself. (C) 2001 Elsevier Science Ltd. All rights reserved.
C1 Univ Guelph, Dept Geog, Guelph, ON N1G 2W1, Canada.
C3 University of Guelph
RP Smithers, J (corresponding author), Univ Guelph, Dept Geog, Guelph, ON N1G 2W1, Canada.
CR Bazzaz F., 1996, Global Climate Change and Agricultural Production: Direct and Indirect Effects of Changing Hydrological, Pedological and Plant Physiological Processes
   BEVERSDORF WD, 1995, HARVEST GOLD HIST FI
   BLAIN R, 1995, 22 U GUELPH DEP GEOG
   BRKLACICH M, 1992, CLIMATIC CHANGE, V20, P1, DOI 10.1007/BF00144106
   Brklacich M., 1997, Agricultural Restructuring and Sustainability: A geographical perspective, P351
   Bryant CR, 2000, CLIMATIC CHANGE, V45, P181, DOI 10.1023/A:1005653320241
   Burton Ian., 1993, The Environment as Hazard
   [Carter T.R. Intergovernmental Panel on Climate Change (IPCC) Intergovernmental Panel on Climate Change (IPCC)], 1994, IPCC SPECIAL REPORT
   Chiotti Q., 1997, AGR RESTRUCTURING SU, P167
   CHIOTTI QP, 1995, J RURAL STUD, V11, P335, DOI 10.1016/0743-0167(95)00023-G
   *COUNC AGR SCI TEC, 1992, 119 CAST
   CROSSON P, 1983, AGR ECOSYST ENVIRON, V9, P339, DOI 10.1016/0167-8809(83)90020-8
   CROSSON PR, 1989, SCI AM           SEP, P128
   DAMOTA FS, 1978, 160 WMO
   DAY P, 1995, 7 NAT AGR BIOT COUNC, P79
   DUMANSKI J, 1986, J SOIL WATER CONSERV, V41, P204
   Easterling WE, 1996, AGR FOREST METEOROL, V80, P1, DOI 10.1016/0168-1923(95)02315-1
   EASTERLING WE, 1992, AGR FOREST METEOROL, V59, P3, DOI 10.1016/0168-1923(92)90083-G
   EDWARDS CA, 1993, AGR ECOSYST ENVIRON, V46, P99, DOI 10.1016/0167-8809(93)90017-J
   GLANTZ MH, 1991, ENVIRONMENT, V33, P10, DOI 10.1080/00139157.1991.9931393
   GLANTZ MH, 1988, SOC RESPONSES REGION, P113
   GOODMAN RM, 1987, SCIENCE, V236, P48, DOI 10.1126/science.236.4797.48
   Hayami Y., 1985, AGR DEV INT PERSPECT
   Houghton J., 1990, IPCC Scientific Assessment of Climate Change - Report of Working Group I
   JOSEPH A, 1981, CAN GEOGR, V23, P333
   Kaiser H. M., 1993, Agricultural dimensions of global climate change., P136
   KLASSEN S, 1998, CANADIAN WATER RESOU, V24, P61
   LEWANDROWSKI J, 1992, ECONOMIC ISSUES IN GLOBAL CLIMATE CHANGE, P132
   Linstone HA, 1997, TECHNOL FORECAST SOC, V54, P1, DOI 10.1016/S0040-1625(97)87499-9
   MAJOR DJ, 1991, J PROD AGRIC, V4, P606, DOI 10.2134/jpa1991.0606
   Nellis M. D., 1987, Demands on rural lands. Planning for resource use., P71
   *ONT SOYB GROW MAR, 1988, ANN REP
   *ONT SOYB GROW MAR, 1998, SOYB VAR DISTR
   PARRY ML, 1988, IMPACTS CLIMATE VARI, V1
   Reilly JM, 1998, SOIL TILL RES, V47, P275, DOI 10.1016/S0167-1987(98)00116-0
   ROSENBERG NJ, 1993, CLIMATIC CHANGE, V24, P7, DOI 10.1007/BF01091475
   ROSENBERG NJ, 1982, CLIMATIC CHANGE, V4, P239, DOI 10.1007/BF02423399
   ROSENBERG NJ, 1992, CLIMATIC CHANGE, V21, P385, DOI 10.1007/BF00141378
   ROSENBERG NJ, 1991, RESOURCES FUTURE, V103, P17
   ROSENBERG NJ, 1981, CLIMATES IMPACT FOOD, P157
   ROSENZWEIG C, 1994, NATURE, V367, P133, DOI 10.1038/367133a0
   Ruttan VW, 1996, CAN J PLANT PATHOL, V18, P123, DOI 10.1080/07060669609500636
   SCHWEGER C, 1991, ALTERNATIVE FUTURES, P1
   SEDEROFF R, 1995, 7 NAT AGR BIOT COUNC, P71
   Smit B., 1994, ADAPTATION CLIMATIC
   SMIT B, 1999, IN PRESS MITIGATION
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Smith MJ, 1997, BRAIN RES BULL, V42, P1, DOI 10.1016/S0361-9230(96)00224-9
   Smithers J, 1997, GLOBAL ENVIRON CHANG, V7, P129, DOI 10.1016/S0959-3780(97)00003-4
   Smiths J., 1997, Agricultural restructuring and sustainability: a geographical perspective., P167
   SPALING H, 1995, AGR ECOSYST ENVIRON, V53, P279, DOI 10.1016/0167-8809(94)00567-X
   Spedding CRW., 1996, Agriculture and the citizen
   *USDA, 1990, MISCELLANEOUS PUBLIC, V1482
   Warrick R.A., 1980, Climatic Constraints and Human Activities, P93
   WHITE ME, 1994, CORNELL VET, V84, P1
NR 55
TC 70
Z9 86
U1 6
U2 33
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0143-6228
J9 APPL GEOGR
JI Appl. Geogr.
PD APR
PY 2001
VL 21
IS 2
BP 175
EP 197
DI 10.1016/S0143-6228(01)00004-2
PG 23
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA 444FW
UT WOS:000169390300005
DA 2025-01-10
ER

PT J
AU Romanach, L
   Boulaire, F
   Fleming, A
   Capon, T
   Bluhm, S
   Lin, BB
AF Romanach, Lygia
   Boulaire, Fanny
   Fleming, Aysha
   Capon, Tim
   Bluhm, Sonia
   Lin, Brenda B.
TI Australia's National Climate Risk Assessment: Identifying climate risk
   interdependencies within the infrastructure and built environment system
   for effective climate adaptation
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Risk assessment; Climate change; Interdependencies; Systemic risks;
   Infrastructure and built environment
ID RESILIENCE
AB Despite efforts to reduce greenhouse gas emissions, there are unavoidable impacts of climate change that are occurring now and will continue to unfold into the future. As the frequency and intensity of climate disasters increase, improving our understanding of climate risks will be critical for developing effective national climate adaptation actions. In recognition of the need for greater interdisciplinary and cross-sector collaboration to improve our understanding of systemic climate risks, a broad range of decision-makers across government and non-government organisations were engaged to identify Australia's nationally significant risks through Australia's first National Climate Risk Assessment (NCRA). In this paper, we describe the collaborative process developed for Australia's NCRA and highlight the climate risk interdependencies identified for the infrastructure and built environment (I&BE) system. The I&BE system was chosen to illustrate the need to consider climate risk interdependencies, as this system's sectors are heavily interconnected and fundamental to the functioning of critical infrastructure, essential services and supply chains. Using data collected through Australia's NCRA, we illustrate how climate hazards create risks to individual I&BE sectors and how such risks aggregate, compound and/or cascade to form systemic risks. These systemic risks impact not only the I&BE system but also other systems, such as defence and national security, health and social support, and economy, trade and finance. Due to the high interdependencies of climate risks across sectors and systems, cross-sector collaboration is critical to address the interconnectedness of the systems and to develop effective climate adaptation strategies. A systemic approach to address climate risks will allow for response strategies that benefit multiple sectors simultaneously and reduce the likelihood of unforeseen negative compounding and cascading risks and maladaptation.
C1 [Romanach, Lygia; Boulaire, Fanny; Lin, Brenda B.] CSIRO Environm, Dutton Pk, Qld 4102, Australia.
   [Fleming, Aysha] CSIRO, Sandy Bay, Tas 7005, Australia.
   [Capon, Tim] CSIRO Entomol, Canberra, ACT 2601, Australia.
   [Bluhm, Sonia] Scientell, 8 La Trobe St, Melbourne, Vic 3000, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO)
RP Romanach, L (corresponding author), CSIRO Environm, Dutton Pk, Qld 4102, Australia.
EM Lygia.Romanach@csiro.au; Fanny.Boulaire@csiro.au;
   Aysha.Fleming@csiro.au; Tim.Capon@csiro.au; sonia@scientell.com.au;
   Brenda.Lin@csiro.au
RI Fleming, Aysha/E-8753-2011
CR ACMA, 2020, Report for the Minister for Communications, Cyber Safety and the Arts
   AEMO, 2020, 2020 ISP Appendix 8. Resilience and Climate Change
   AghaKouchak A, 2020, ANNU REV EARTH PL SC, V48, P519, DOI 10.1146/annurev-earth-071719-055228
   André K, 2023, FRONT CLIM, V5, DOI 10.3389/fclim.2023.1120421
   [Anonymous], 2020, Royal Commission into National Disaster Arrangements Report
   Australian Government. Department of Home Affairs, 2018, Profiling Australia's Vulnerability: The interconnected causes and cascading effects of systemic disaster risk
   Barquet K, 2024, DISASTERS, V48, DOI 10.1111/disa.12591
   Bebb J., 2003, Potential impacts of climate change on waste management
   Benevolenza MA, 2019, J HUM BEHAV SOC ENVI, V29, P266, DOI 10.1080/10911359.2018.1527739
   Breitenstein M, 2021, J ECON SURV, V35, P512, DOI 10.1111/joes.12411
   Bubeck P, 2019, CLIMATIC CHANGE, V155, P19, DOI 10.1007/s10584-019-02434-5
   Buchtmann M, 2023, DISASTER PREV MANAG, V32, P49, DOI 10.1108/DPM-08-2022-0168
   Chhetri P, 2015, J SPAT SCI, V60, P65, DOI 10.1080/14498596.2014.943311
   Crimmins A.R., 2023, 5 NATL CLIMATE ASSES, DOI [10.7930/NCA5.2023, DOI 10.7930/NCA5.2023]
   CSIRO and Bureau of Meteorology, 2021, ESCI Project Final Report
   Cvitanovic C, 2019, ENVIRON SCI POLICY, V94, P20, DOI 10.1016/j.envsci.2018.12.028
   DCCEEW, 2024, National climate risk assessment
   DeCaro DA, 2017, ECOL SOC, V22, DOI 10.5751/ES-09036-220132
   DELWP, 2022, Guidelines for the Adaptive Management of Wastewater Systems Under Climate Change in Victoria
   Department of Climate Change and Energy Efficiency, 2011, Climate Change Risks to Coastal Buildings and Infrastructure: A Supplement to the First Pass National Assessment
   Department of Transport and Main Roads, 2020, Climate Change Risk and Adaptation Assessment Framework for Infrastructure Projects
   Dingle G, 2023, EUR SPORT MANAG Q, V23, P59, DOI 10.1080/16184742.2022.2092169
   Duck T, 2020, ENVIRON PLAN LAW J, V37, P443
   Ford L., 2020, Our knowledge, our way in caring for country: Indigenous-led approaches to strengthening and sharing our knowledge for land and sea management. Best Practice Guidelines from Australian experiences, P105
   Gillard R, 2016, WIRES CLIM CHANGE, V7, P251, DOI 10.1002/wcc.384
   Harmácková ZV, 2022, CLIM RISK MANAG, V37, DOI 10.1016/j.crm.2022.100452
   Hedlund J., 2023, Npj Climate Action, V1, P48, DOI [10.1038/s44168-023-00078-x, DOI 10.1038/S44168-023-00078-X]
   Hochrainer-Stigler S, 2023, CLIM RISK MANAG, V41, DOI 10.1016/j.crm.2023.100531
   Hughes J, 2021, CLIM RISK MANAG, V31, DOI 10.1016/j.crm.2020.100262
   Hurlimann AC, 2019, BUILD ENVIRON, V153, P128, DOI 10.1016/j.buildenv.2019.02.008
   Ide T, 2023, AUST J INT AFF, V77, P26, DOI 10.1080/10357718.2023.2170978
   Imperiale AJ, 2021, SUSTAIN DEV, V29, P891, DOI 10.1002/sd.2182
   Iozzelli L, 2023, EARTH SYST GOV-NETH, V18, DOI 10.1016/j.esg.2023.100189
   IPCC, 2022, Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
   Izaguirre C, 2020, MARIT POLICY MANAG, V47, P544, DOI 10.1080/03088839.2020.1725673
   Kara ME, 2021, INT J PROD RES, V59, P7317, DOI 10.1080/00207543.2020.1849844
   Karakosta C, 2018, INT J CLIM CHANG STR, V10, P772, DOI 10.1108/IJCCSM-05-2017-0117
   Koks E, 2019, INT J DISAST RISK SC, V10, P421, DOI 10.1007/s13753-019-00236-y
   Kovach Margaret., 2015, RES RESISTANCE REVIS, VSecond, P43
   Lawrence J., 2022, Australasia (Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
   Lawrence J, 2020, CLIM RISK MANAG, V29, DOI 10.1016/j.crm.2020.100234
   Lewison RL, 2019, CONSERV LETT, V12, DOI 10.1111/conl.12628
   Li JB, 2023, WATER RES, V242, DOI 10.1016/j.watres.2023.120282
   Lim-Camacho L, 2017, GLOBAL ENVIRON CHANG, V46, P126, DOI 10.1016/j.gloenvcha.2017.08.011
   Loza ARA, 2021, IMPACT ASSESS PROJ A, V39, P277, DOI 10.1080/14615517.2021.1893928
   Mallon K., 2019, Climate change risk to Australia's built environment: a second pass national assessment
   Marchin RM, 2022, SCI TOTAL ENVIRON, V850, DOI 10.1016/j.scitotenv.2022.157915
   Maskrey A, 2023, DISASTER PREV MANAG, V32, P4, DOI 10.1108/DPM-07-2022-0155
   Mikellidou CV, 2018, SAFETY SCI, V110, P110, DOI 10.1016/j.ssci.2017.12.022
   Morris RL, 2020, REV SYMB LOGIC, V13, P23, DOI 10.1017/S1755020319000583
   Niggli L., 2022, PLoS Clim, V1, DOI [10.1371/journal.pclm.0000057, DOI 10.1371/JOURNAL.PCLM.0000057]
   Norman B., 2022, Urban Planning for Climate Change
   Panteli M, 2017, IEEE SYST J, V11, P1733, DOI 10.1109/JSYST.2015.2389272
   Perera ATD, 2023, RENEW SUST ENERG REV, V173, DOI 10.1016/j.rser.2022.113038
   Pescaroli G, 2016, NAT HAZARDS, V82, P175, DOI 10.1007/s11069-016-2186-3
   Raymond C, 2020, NAT CLIM CHANGE, V10, P611, DOI 10.1038/s41558-020-0790-4
   Renn O, 2022, RISK ANAL, V42, P1902, DOI 10.1111/risa.13657
   Renn O, 2021, J RISK RES, V24, P127, DOI 10.1080/13669877.2020.1779787
   Robertson S, 2021, WIRES CLIM CHANGE, V12, DOI 10.1002/wcc.679
   Rocha JC, 2018, SCIENCE, V362, P1379, DOI 10.1126/science.aat7850
   Savi T, 2015, NEW PHYTOL, V205, P1106, DOI 10.1111/nph.13112
   Shi LD, 2021, SCIENCE, V372, P1408, DOI 10.1126/science.abc8054
   Sonesson TR, 2021, SAFETY SCI, V142, DOI 10.1016/j.ssci.2021.105383
   Steffen W., 2019, Compound costs: how climate change is damaging Australia's economy
   Stern N, 2015, LION ROBB LECT, P1
   Stevens L., 2008, Assessment of Impacts of Climate Change on Australia's Physical Infrastructure
   Subramaniam RC, 2023, REV FISH BIOL FISHER, V33, P1129, DOI 10.1007/s11160-023-09788-1
   Surminski S, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2017.0307
   Terrado M, 2023, CLIM RISK MANAG, V40, DOI 10.1016/j.crm.2023.100513
   Tonmoy FN, 2019, CLIMATIC CHANGE, V153, P539, DOI 10.1007/s10584-019-02367-z
   UNISDR, 2015, SENDAI FRAMEWORK DIS
   Verschuur J, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-32070-0
   Wang T., 2023, Annual Report on Actions to Address Climate Change (2019): Climate Risk Prevention, P79, DOI [10.1007/978- 981-19-7738-1_6, DOI 10.1007/978-981-19-7738-1_6]
   Watts N, 2015, LANCET, V386, P1861, DOI 10.1016/S0140-6736(15)60854-6
   Wilson R, 2023, FIRE-BASEL, V6, DOI 10.3390/fire6020061
   Zhang FS, 2019, J CLEAN PROD, V235, P822, DOI 10.1016/j.jclepro.2019.06.229
   Zhou KH, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15118977
NR 77
TC 0
Z9 0
U1 1
U2 1
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2024
VL 46
AR 100670
DI 10.1016/j.crm.2024.100670
EA NOV 2024
PG 17
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA N5M7W
UT WOS:001364786200001
OA gold
DA 2025-01-10
ER

PT J
AU Armstrong, A
   Cromar, J
   Dorney, C
   Flood, M
   Meyer, MD
AF Armstrong, Amit
   Cromar, James
   Dorney, Chris
   Flood, Mike
   Meyer, Michael D.
TI From Permafrost to Sunny Beaches Lessons Learned from Alaska and
   Southeast Florida Climate Adaptation Studies
SO TRANSPORTATION RESEARCH RECORD
LA English
DT Article
AB This paper examines two climate adaptation assessment studies conducted in significantly different climates Alaska and southeast Florida. The purpose of the studies was to identify areas of commonality between the two studies with respect to the assessment steps, tools used, and the types of strategies and actions recommended. Four topics were identified for the assessment: forecasting future climate conditions, identifying impacts and disruptions, identifying adaptation strategies and options, and considering risks and uncertainties and the implications for engineering design. The paper concludes that the use of surrogate approaches for considered environmental conditions can be a valuable tool for those conducting adaptation assessment studies. Data quality was an important concern in both studies, and adaptation strategies should include both those designed to avoid damage and disruption and those designed to mitigate any potential consequence of an event. A broader concept of loss should be incorporated into the assessment process and into the engineering decisions relating to individual project designs.
C1 [Armstrong, Amit] Fed Highway Adm, Technol Deployment Program, Western Fed Lands Highway Div, Vancouver, WA 98661 USA.
   [Cromar, James] Broward Metropolitan Planning Org, Trade Ctr South, 100 West Cypress Creek Rd,Suite 850, Ft Lauderdale, FL 33309 USA.
   [Dorney, Chris; Flood, Mike] WSP Parsons Brinckerhoff, 100 South Charles St,Tower 1,10th Floor, Baltimore, MD 21201 USA.
   [Meyer, Michael D.] WSP Parsons Brinckerhoff, 3340 Peachtree Rd NE,Tower Pl 100,Suite 2400, Atlanta, GA 30326 USA.
RP Meyer, MD (corresponding author), WSP Parsons Brinckerhoff, 3340 Peachtree Rd NE,Tower Pl 100,Suite 2400, Atlanta, GA 30326 USA.
EM meyer@pbworld.com
CR AASHTO, RES SUST TRANSP SYST
   [Anonymous], EC181 TRANSP RES BOA
   Broward Metropolitan Planning Organization Miami-Dade Metropolitan Planning Organization, 2015, S FLOR CLIM CHANG VU
   FHWA U.S. Department of Transportation, 2013, CLIM CHANG RES PIL
   Meyer M.D., 2014, STRATEGIC ISSUES FAC, V2
   The Gulf Coast Study, 2014, FHWAHEP15004 US DEP
   U.S. Army Corps of Engineers, CLIMATE CHANGE ADAPT
   U.S. Federal Transit Administration, 2014, 0069 FTA
   United States Department of Transportation, TRANSP CLIM CHANG CL
   Watkins T., 2013, DEV GEOGRAPHIC INFOR
NR 10
TC 1
Z9 1
U1 0
U2 2
PU NATL ACAD SCIENCES
PI WASHINGTON
PA 2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA
SN 0361-1981
EI 2169-4052
J9 TRANSPORT RES REC
JI Transp. Res. Record
PY 2016
IS 2571
BP 19
EP 28
DI 10.3141/2571-03
PG 10
WC Engineering, Civil; Transportation; Transportation Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Transportation
GA DQ1UK
UT WOS:000378985700004
DA 2025-01-10
ER

PT J
AU Tan, LL
   Zhang, XL
   Qi, JY
   Sun, DF
   Marek, GW
   Feng, PY
   Li, BG
   Liu, DL
   Li, BG
   Srinivasan, R
   Chen, Y
AF Tan, Lili
   Zhang, Xueliang
   Qi, Junyu
   Sun, Danfeng
   Marek, Gary W.
   Feng, Puyu
   Li, Baogui
   Liu, De Li
   Li, Baoguo
   Srinivasan, Raghavan
   Chen, Yong
TI Assessment of the sustainability of groundwater utilization and crop
   production under optimized irrigation strategies in the North China
   Plain under future climate change
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change adaptation; Limited irrigation; Crop yield; Shallow
   groundwater level; NCP; SWAT-MAD-GW-CO2
ID WATER-USE EFFICIENCY; GREENHOUSE-GAS CONCENTRATIONS; GLOBAL FOOD DEMAND;
   WINTER-WHEAT; CHANGE IMPACT; 3 DECADES; YIELD; RESPONSES; SYSTEMS;
   EVAPOTRANSPIRATION
AB Over-exploitation of groundwater due to intensive irrigation and anticipated climate change pose severe threats to the water and food security worldwide, particularly in the North China Plain (NCP). Limited irrigation has been recognized as an effective way to improve crop water productivity and slow the rapid decline of groundwater levels. Whether optimized limited irrigation strategies could achieve a balance between groundwater pumping and grain production in the NCP under future climate change deserves further study. In this study, an improved Soil and Water Assessment Tool (SWAT) model was used to simulate climate change impacts on shallow groundwater levels and crop production under limited irrigation strategies to suggest optimal irrigation management practices under future climate conditions in the NCP. The simulations of eleven limited irrigation strategies for winter wheat with targeted irrigations at different growth stages and with irrigated or rainfed summer maize were compared with future business-as-usual management. Climate change impacts showed that mean wheat (maize) yield under adequate irrigation was expected to increase by 13.2% (4.9%) during the middle time period (2041-2070) and by 11.2% (4.6%) during the late time period (2071-2100) under three SSPs compared to the historical period (1971-2000). Mean decline rate of shallow groundwater level slowed by approximately 1 m a-1 during the entire future period (2041-2100) under three SSPs with a greater reduction for SSP5-8.5. The average contribution rate of future climate toward the balance of shallow groundwater pumping and replenishment was 62.9%. Based on the simulated crop yields and decline rate of shallow groundwater level under the future climate, the most appropriate limited irrigation was achieved by applying irrigation during the jointing stage of wheat with rainfed maize, which could achieve the groundwater recovery and sustainable food production.
C1 [Tan, Lili; Zhang, Xueliang; Sun, Danfeng; Feng, Puyu; Li, Baogui; Li, Baoguo; Chen, Yong] China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China.
   [Tan, Lili; Zhang, Xueliang; Sun, Danfeng; Li, Baogui; Chen, Yong] China Agr Univ, Res Ctr Land Use & Management, Beijing 100193, Peoples R China.
   [Zhang, Xueliang] Hebei Cangzhou Groundwater & Land Subsidence Natl, Cangzhou 061000, Peoples R China.
   [Qi, Junyu] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA.
   [Marek, Gary W.] USDA ARS Conservat & Prod Res Lab, Bushland, TX 79012 USA.
   [Feng, Puyu; Li, Baoguo; Chen, Yong] Minist Agr & Rural Affairs, Key Lab Arable Land Conservat North China, Beijing 100193, Peoples R China.
   [Liu, De Li] NSW Dept Primary Ind, Wagga Wagga Agr Inst, Wagga Wagga, NSW 2650, Australia.
   [Liu, De Li] Univ New South Wales, Climate Change Res Ctr, Sydney 2052, Australia.
   [Srinivasan, Raghavan] Texas A&M Univ, Dept Ecosyst Sci & Management, College Stn, TX 77843 USA.
C3 China Agricultural University; China Agricultural University; University
   System of Maryland; University of Maryland College Park; Ministry of
   Agriculture & Rural Affairs; Department of Primary Industries & Regional
   Development NSW; University of New South Wales Sydney; Texas A&M
   University System; Texas A&M University College Station
RP Chen, Y (corresponding author), China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China.
EM yongchen@cau.edu.cn
RI Tan, Lili/KBR-1426-2024; Qi, Junyu/Q-3939-2019; Srinivasan,
   Raghavan/AAE-3834-2022
OI Liu, De Li/0000-0003-2574-1908
FU Open Fund of Hebei Cangzhou Groundwater and Land Subsidence National
   Observation and Research Station [CGLOS-2022-01]; National Natural
   Science Foundation of China [42272293]; Chinese Univer-sities Scientific
   Fund [1191-15051002, 1191-15053344]; National Institute of Food and
   Agriculture, U.S. Department of Agriculture [NIFA-2021-67019-33684]
FX Acknowledgements This research was supported by the Open Fund of Hebei
   Cangzhou Groundwater and Land Subsidence National Observation and
   Research Station [grant number CGLOS-2022-01] ; the National Natural
   Science Foundation of China [grant number 42272293] ; the Chinese
   Univer-sities Scientific Fund [grant numbers 1191-15051002 and
   1191-15053344] ; this research was also supported in part by the
   National Institute of Food and Agriculture, U.S. Department of
   Agriculture [grant number NIFA-2021-67019-33684] . We greatly appreciate
   three anony-mous reviewers for their valuable comments and suggestions.
CR Abbaspour KC, 2019, SCI DATA, V6, DOI 10.1038/s41597-019-0282-4
   Ainsworth EA, 2007, PLANT CELL ENVIRON, V30, P258, DOI 10.1111/j.1365-3040.2007.01641.x
   Aliyari F, 2021, SCI TOTAL ENVIRON, V788, DOI 10.1016/j.scitotenv.2021.147717
   Allen DM, 2010, HYDROL PROCESS, V24, P3392, DOI 10.1002/hyp.7757
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Araya A, 2017, AGR SYST, V150, P86, DOI 10.1016/j.agsy.2016.10.007
   Arnold JG, 2012, T ASABE, V55, P1491
   Asseng S, 2019, GLOBAL CHANGE BIOL, V25, P155, DOI 10.1111/gcb.14481
   Bassu S, 2014, GLOBAL CHANGE BIOL, V20, P2301, DOI 10.1111/gcb.12520
   Berg A, 2019, J CLIMATE, V32, P2653, DOI 10.1175/JCLI-D-18-0583.1
   Chen JL, 2016, SURV GEOPHYS, V37, P397, DOI 10.1007/s10712-015-9332-4
   Chen W., 1999, Groundwater in Hebei Province
   Chen Y, 2018, ENVIRON MODELL SOFTW, V99, P25, DOI 10.1016/j.envsoft.2017.09.013
   Chen Y, 2021, AGR WATER MANAGE, V244, DOI 10.1016/j.agwat.2020.106574
   China Geological Survey, 2009, Assessment of sustainable groundwater utilization in the North China Plain
   Chomba IC., 2022, J Hum Earthand Future, V3, P2785, DOI DOI 10.28991/HEF-2022-03-02-09
   Comas LH, 2019, AGR WATER MANAGE, V212, P433, DOI 10.1016/j.agwat.2018.07.015
   Döll P, 2014, WATER RESOUR RES, V50, P5698, DOI 10.1002/2014WR015595
   Elahi E, 2022, APPL ENERG, V309, DOI 10.1016/j.apenergy.2021.118459
   Falloon P, 2010, SCI TOTAL ENVIRON, V408, P5667, DOI 10.1016/j.scitotenv.2009.05.002
   Famiglietti JS, 2014, NAT CLIM CHANGE, V4, P945, DOI 10.1038/nclimate2425
   Grusson Y, 2021, AGR WATER MANAGE, V249, DOI 10.1016/j.agwat.2021.106766
   Gupta HV, 1999, J HYDROL ENG, V4, P135, DOI 10.1061/(ASCE)1084-0699(1999)4:2(135)
   JAMIESON PD, 1991, FIELD CROP RES, V27, P337, DOI 10.1016/0378-4290(91)90040-3
   Kang SZ, 2002, AGR WATER MANAGE, V55, P203, DOI 10.1016/S0378-3774(01)00180-9
   Krysanova V, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa8359
   Legates DR, 1999, WATER RESOUR RES, V35, P233, DOI 10.1029/1998WR900018
   Liu DL, 2012, CLIMATIC CHANGE, V115, P629, DOI 10.1007/s10584-012-0464-y
   Lobell DB, 2020, NAT FOOD, V1, P729, DOI 10.1038/s43016-020-00165-w
   Ma L, 2017, AGR WATER MANAGE, V180, P88, DOI 10.1016/j.agwat.2016.11.007
   Martinsen G, 2022, J HYDROL-REG STUD, V41, DOI 10.1016/j.ejrh.2022.101097
   McGrath JM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/1/014054
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Ministry of Geology and Mineral Resource of China (MGMR), 1992, COMPREHENSIVE HYDRO
   Mo XG, 2017, ADV CLIM CHANG RES, V8, P93, DOI 10.1016/j.accre.2017.05.007
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Neitsch S, 2011, SOIL WATER ASSESSMEN
   Nguyen TG, 2022, CIV ENG J-TEHRAN, V8, P2661, DOI 10.28991/CEJ-2022-08-11-020
   Nyakundi R, 2022, CIV ENG J-TEHRAN, V8, P910, DOI 10.28991/CEJ-2022-08-05-05
   O'Neill BC, 2016, GEOSCI MODEL DEV, V9, P3461, DOI 10.5194/gmd-9-3461-2016
   Pokhrel Y, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00972-w
   Proctor J, 2022, NAT FOOD, V3, P753, DOI 10.1038/s43016-022-00592-x
   Qiu GY, 2008, AGR FOREST METEOROL, V148, P1848, DOI 10.1016/j.agrformet.2008.06.010
   Rashid MA, 2019, AGR WATER MANAGE, V222, P193, DOI 10.1016/j.agwat.2019.06.004
   Razzaq A, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.944156
   Razzaq A, 2019, SCI TOTAL ENVIRON, V666, P849, DOI 10.1016/j.scitotenv.2019.02.266
   Ren L., 2020, Simulation of the variations in shallow groundwater and crop yields under the current situation, limited irrigation schemes, and fallow scheme patterns in the well-irrigated region of the Haihe River basin - a case study of the piedmont plain of Mount Taihang in Hebei Province
   Ren PP, 2022, AGR WATER MANAGE, V263, DOI 10.1016/j.agwat.2022.107468
   Shrestha S, 2016, ENVIRON SCI POLICY, V61, P1, DOI 10.1016/j.envsci.2016.03.010
   Sun HY, 2019, AGR WATER MANAGE, V211, P202, DOI 10.1016/j.agwat.2018.09.046
   Tan LL, 2022, AGR WATER MANAGE, V266, DOI 10.1016/j.agwat.2022.107560
   Tan ML, 2020, ADV WATER RESOUR, V143, DOI 10.1016/j.advwatres.2020.103662
   Taylor RG, 2013, NAT CLIM CHANGE, V3, P322, DOI [10.1038/nclimate1744, 10.1038/NCLIMATE1744]
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   van Dijk M, 2021, NAT FOOD, V2, P494, DOI 10.1038/s43016-021-00322-9
   van Oort PAJ, 2016, AGR WATER MANAGE, V165, P131, DOI 10.1016/j.agwat.2015.11.005
   van Vuuren DP, 2007, CLIMATIC CHANGE, V81, P119, DOI 10.1007/s10584-006-9172-9
   Wang D.C., 1995, Fundamentals of Hydrogeology
   Wang E, 2017, NAT PLANTS, V3, DOI 10.1038/nplants.2017.102
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Willmott CJ., 1981, Phys Geogr, V2, P184, DOI [DOI 10.1080/02723646.1981.10642213, 10.1080/02723646.1981.10642213]
   Wu WY, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-17581-y
   Xiao DP, 2021, AGR WATER MANAGE, V246, DOI 10.1016/j.agwat.2020.106685
   Xiao DP, 2020, AGR WATER MANAGE, V238, DOI 10.1016/j.agwat.2020.106238
   Yan ZZ, 2020, AGR SYST, V178, DOI 10.1016/j.agsy.2019.102745
   [杨会峰 Yang Huifeng], 2021, [中国地质, Geology of China], V48, P1142
   Yang P, 2014, REG ENVIRON CHANGE, V14, P61, DOI 10.1007/s10113-013-0484-9
   Yang YH, 2006, AGR WATER MANAGE, V82, P25, DOI 10.1016/j.agwat.2005.07.020
   Zabel F, 2021, GLOBAL CHANGE BIOL, V27, P3870, DOI 10.1111/gcb.15649
   Zamanirad M, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-018-7585-1
   Zhang C, 2021, J HYDROL, V597, DOI 10.1016/j.jhydrol.2021.126156
   Zhang XY, 2006, AGRON J, V98, P1620, DOI 10.2134/agronj2005.0358
   Zhang XY, 2017, AGR WATER MANAGE, V179, P47, DOI 10.1016/j.agwat.2016.05.004
   Zhang XY, 2013, EUR J AGRON, V50, P52, DOI 10.1016/j.eja.2013.05.005
   Zhang XL, 2022, J HYDROL, V610, DOI 10.1016/j.jhydrol.2022.127799
   Zhang XL, 2018, J HYDROL, V567, P253, DOI 10.1016/j.jhydrol.2018.09.041
   Zhang XL, 2016, J HYDROL, V541, P1221, DOI 10.1016/j.jhydrol.2016.08.030
   Zhang Yingqi, 2022, Journal of Hydrology, DOI 10.1016/j.jhydrol.2022.128544
   Zhang Z., 2009, Atlas of Groundwater Sustainable Utilization in the North China Plain
   Zhang Z.H., 2005, Groundwater Resources of China-Hebei
   Zhao C, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms13530
NR 81
TC 11
Z9 11
U1 23
U2 88
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 15
PY 2023
VL 899
AR 165619
DI 10.1016/j.scitotenv.2023.165619
EA JUL 2023
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA O9JU2
UT WOS:001046917000001
PM 37478948
OA Bronze
DA 2025-01-10
ER

PT J
AU Wei, S
   Cheng, ST
AF Wei, Shuo
   Cheng, Su-Ting
TI Estimating Pruning-Caused Loss on Ecosystem Services of Air Pollution
   Removal and Runoff Avoidance
SO SUSTAINABILITY
LA English
DT Article
DE ecosystem services and values; pruning; street trees; i-Tree Eco; runoff
   avoidance; pollution removal
ID URBAN FOREST; RAINFALL INTERCEPTION; TREE; CALIFORNIA; STREET;
   DEPOSITION; BENEFITS; COSTS; WATER
AB Trees provide multiple ecosystem services (ES) and are generally considered an important natural-based approach for climate change adaptation and mitigation. In urban areas, proper pruning practices can help enhance ES provided by trees, but in areas with issues of typhoons or storms, routinely intensive pruning may reduce ES. Therefore, it is critical to determine proper pruning intensity in balancing the ES provision and life/property protection. With the aim of promoting sustainable urban forestry management, we applied the i-Tree Eco to quantify ES and ES values of air pollution removal and runoff avoidance provided by a total of 87,014 Taipei street trees and developed an analytical method to estimate the potential loss caused by different pruning intensities. Based on the i-Tree Eco estimates, the Taipei street trees on average provide ES values of air pollution removal and runoff avoidance at $2.31 and $1.87 USD/tree/y, respectively. By changing the ratio of crown missing as a surrogate for different pruning intensities, we found that with a less than 25% pruning intensity, the decline ratio of ES values was relatively constant, and the potential loss was estimated at $0.47 USD/tree/y at the 25% pruning intensity. As such, in general maintenance situations, we recommend a less than 25% pruning intensity. However, during typhoon or monsoon seasons, a less than 45% pruning intensity is suggested to balance the ES provision and public safety with an estimated loss at $0.96 USD/tree/y. We also suggest creating visualization maps incorporating the potential ES and the local in situ environmental and tree conditions at a community level to support decision making for a more comprehensive management plan. Based on the framework and method developed in this study, the science-based information can be used to assist maintenance practices and highlight the potential ES values to be enhanced by choosing proper pruning intensity for a more sustainable future.
C1 [Wei, Shuo; Cheng, Su-Ting] Natl Taiwan Univ, Sch Forestry & Resource Conservat, Taipei 10617, Taiwan.
C3 National Taiwan University
RP Cheng, ST (corresponding author), Natl Taiwan Univ, Sch Forestry & Resource Conservat, Taipei 10617, Taiwan.
EM b04605019@ntu.edu.tw; chengsuting@ntu.edu.tw
RI Cheng, Su-Ting/HGU-4213-2022
OI CHENG, SU-TING/0000-0003-1786-6049; Wei, Shuo/0000-0002-9840-8949
FU Belmont Forum, Urban Europe [730254]; Ministry of Science and
   Technology, Taiwan, R.O.C. [MOST 107-2621-M-002-004-MY3, MOST
   108-2621-M-002-010-MY3]; Academia Sinica [AS-SS-108-03-1]
FX This research was funded by Belmont Forum, Urban Europe (Project no.
   730254), the Ministry of Science and Technology, Taiwan, R.O.C. (MOST
   107-2621-M-002-004-MY3 & MOST 108-2621-M-002-010-MY3), and Academia
   Sinica (AS-SS-108-03-1).
CR Alberti Marina, 2004, Urban Ecosystems, V7, P241, DOI 10.1023/B:UECO.0000044038.90173.c6
   Alves PL, 2018, URBAN ECOSYST, V21, P697, DOI 10.1007/s11252-018-0753-y
   American National Standard Institute [ANSI], 2008, A300 ANSI 1
   [Anonymous], 2016, AIR POLLUTANT REMOVA
   [Anonymous], 2012, ARBORIC URBAN FOR, DOI DOI 10.48044/JAUF.2012.026
   BALDOCCHI DD, 1987, ATMOS ENVIRON, V21, P91, DOI 10.1016/0004-6981(87)90274-5
   Baraldi R, 2019, URBAN FOR URBAN GREE, V37, P24, DOI 10.1016/j.ufug.2018.03.002
   Berland A, 2017, LANDSCAPE URBAN PLAN, V162, P167, DOI 10.1016/j.landurbplan.2017.02.017
   Berry BJL, 2008, Urban Ecology: An International Perspective on the Interaction between Humans and Nature, P25
   Clark James R., 2010, Arboriculture & Urban Forestry, V36, P110
   COTTAM G, 1956, ECOLOGY, V37, P451, DOI 10.2307/1930167
   CURTIS JT, 1950, ECOLOGY, V31, P434, DOI 10.2307/1931497
   Fini A, 2015, URBAN FOR URBAN GREE, V14, P664, DOI 10.1016/j.ufug.2015.06.011
   Goulder LH, 2013, CLIM CHANG ECON, V4, DOI 10.1142/S2010007813500103
   Grote R, 2016, FRONT ECOL ENVIRON, V14, P543, DOI 10.1002/fee.1426
   Hirabayashi S., 2013, I TREE ECO PRECIPITA, P21
   Kabisch N, 2017, THEOR PRACT URB SUST, P1, DOI 10.1007/978-3-319-56091-5
   Killus J.P., 1984, EPA600384095A
   Livesley SJ, 2016, J ENVIRON QUAL, V45, P119, DOI 10.2134/jeq2015.11.0567
   Lohbeck M, 2016, ECOLOGY, V97, P2772, DOI 10.1002/ecy.1499
   Masson-Delmotte V., 2021, Climate Change 2021: The Physical Science Basis, P41
   McPherson E.G., 1989, LANDSCAPE J, V8, P13, DOI DOI 10.3368/LJ.8.1.13
   McPherson E.G., 1984, ENERGY CONSERVING SI
   McPherson EG, 2018, URBAN FOR URBAN GREE, V31, P204, DOI 10.1016/j.ufug.2018.03.001
   McPherson EG, 2016, URBAN FOR URBAN GREE, V17, P104, DOI 10.1016/j.ufug.2016.03.013
   McPherson EG, 2013, URBAN FOR URBAN GREE, V12, P134, DOI 10.1016/j.ufug.2013.01.003
   Millward AA, 2011, LANDSCAPE URBAN PLAN, V100, P177, DOI 10.1016/j.landurbplan.2010.11.013
   Nowak D., 2002, Forest Service Gen. Tech. Rep, V290, P107
   Nowak D.J., 1994, Atmospheric carbon dioxide reduction by Chicago's urban forest. Chicago's urban forest ecosystem: results of the Chicago Urban Forest Climate Project, P83
   Nowak D.J., 2000, INTEGRATED TOOLS NAT
   Nowak David J., 2006, Urban Forestry & Urban Greening, V4, P115, DOI 10.1016/j.ufug.2006.01.007
   Nowak David J., 2008, Arboriculture & Urban Forestry, V34, P347
   Nowak David J., 2021, Understanding i-Tree: 2021 Summary of Programs and Methods, P100, DOI [DOI 10.2737/NRS-GTR-200, 10.2737/NRS-GTR-200-2021, DOI 10.2737/NRS-GTR-200-2021]
   Nowak DJ, 1996, FOREST SCI, V42, P504
   Nowak DJ, 1998, NATO CHAL M, V22, P399
   Nytch CJ, 2019, URBAN ECOSYST, V22, P103, DOI 10.1007/s11252-018-0768-4
   Pandey R. K., 2018, Plant Archives, V18, P2687
   PEDERSON JR, 1995, ATMOS ENVIRON, V29, P3115, DOI 10.1016/1352-2310(95)00136-M
   Peper Paula J., 2001, Journal of Arboriculture, V27, P306
   Pickett STA, 2008, BIOSCIENCE, V58, P139, DOI 10.1641/B580208
   Pincetl S, 2013, GEOJOURNAL, V78, P475, DOI 10.1007/s10708-012-9446-x
   Reed J, 2017, FOREST POLICY ECON, V84, P62, DOI 10.1016/j.forpol.2017.01.012
   Roy S, 2012, URBAN FOR URBAN GREE, V11, P351, DOI 10.1016/j.ufug.2012.06.006
   Ryder C. M., 2013, Arboriculture & Urban Forestry, V39, P17
   Santamour F.S., 1990, PROC SEV C METROTREE, P57
   Schomaker M. E., 2007, General Technical Report - Southern Research Station, USDA Forest Service
   Selmi W, 2016, URBAN FOR URBAN GREE, V17, P192, DOI 10.1016/j.ufug.2016.04.010
   Tan XY, 2021, FORESTS, V12, DOI 10.3390/f12030311
   USDA Forest Service, 2016, I TREE EC MAN V6 0, P93
   Vogt Jess, 2015, Arboriculture & Urban Forestry, V41, P293
   Wang J, 2008, J AM WATER RESOUR AS, V44, P75, DOI 10.1111/j.1752-1688.2007.00139.x
   Wang XY, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10030674
NR 52
TC 3
Z9 3
U1 2
U2 16
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JUN
PY 2022
VL 14
IS 11
AR 6637
DI 10.3390/su14116637
PG 12
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 1Z1NN
UT WOS:000808599800001
OA gold
DA 2025-01-10
ER

PT J
AU Staccione, A
   Broccoli, D
   Mazzoli, P
   Bagli, S
   Mysiak, J
AF Staccione, Andrea
   Broccoli, Davide
   Mazzoli, Paolo
   Bagli, Stefano
   Mysiak, Jaroslav
TI Natural water retention ponds for water management in agriculture: A
   potential scenario in Northern Italy
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Green infrastructure network; Nature-based solutions; Water balance;
   Landscape connectivity; Climate change adaptation; Tradable development
   rights
ID TRADABLE DEVELOPMENT RIGHTS; ECOSYSTEM SERVICES; GREEN INFRASTRUCTURE;
   HABITAT PATCHES; FOREST; CONNECTIVITY; BIODIVERSITY; PROTECTION; BASIN;
   EU
AB Climate change is affecting water quantity and quality, with severe impacts on agricultural production. The use of nature-based solutions to address these challenges is increasing. Natural water retention ponds have been identified as viable solutions for water management in agriculture. This paper aims to characterize water retention ponds, and to quantify their effectiveness, direct and indirect benefits, and costs. The paper analyses the case of the Lamone river catchment in Emilia-Romagna Region (Italy), characterized by large seasonal variability of water flow and availability. This is an important agricultural area that relies heavily on irrigation. Here water retention ponds are systematically applied to store water in winter, for use during the dry season. They can play a strategic role in ensuring irrigation water availability, while preserving minimum environmental flow. The paper analyses both the benefits of ponds for the water balance at sub-catchment scale, and the environmental effects produced by ponds having an ecological functionality. We develop an implementation scenario for new ponds, and we appraise the contribution of new ponds whose siting is chosen in order to maximize landscape connectivity. Their hydrological effects are evaluated under present and future climate change scenarios, showing how they may increase water availability for irrigation, while improving the river flow regime. More water for irrigation can favour additional agricultural production, while a more ecologically oriented design of ponds can favour to landscape ecological improvements. The investment costs of ponds are justified in economic terms, and the additional costs of improved design are expected to be balanced by the ecosystem services obtained. The business model required to operate this type of intervention is discussed, together with potential funding channels. We discuss two innovative incentive models based on compensation of land and production lost, and on tradable development rights that can be applied to widely support NBS implementation.
C1 [Staccione, Andrea; Mysiak, Jaroslav] Euro Mediterranean Ctr Climate Change, Edificio Porta DellInnovaz Piano 2,Via Liberta 12, I-30175 Marghera Venice, VE, Italy.
   [Staccione, Andrea; Mysiak, Jaroslav] Ca Foscari Univ Venice, Edificio Porta DellInnovaz Piano 2,Via Liberta 12, I-30175 Marghera Venice, VE, Italy.
   [Broccoli, Davide; Mazzoli, Paolo; Bagli, Stefano] GECOsistema Srl Geog Environm Consulting, R&D Unit Suedtirol Via Maso Pieve Pfarrhofstr 60, I-47923 Rimini, RN, Italy.
C3 Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC); Universita Ca
   Foscari Venezia
RP Staccione, A (corresponding author), Euro Mediterranean Ctr Climate Change, Edificio Porta DellInnovaz Piano 2,Via Liberta 12, I-30175 Marghera Venice, VE, Italy.; Staccione, A (corresponding author), Ca Foscari Univ Venice, Edificio Porta DellInnovaz Piano 2,Via Liberta 12, I-30175 Marghera Venice, VE, Italy.
EM andrea.staccione@cmcc.it
RI Mysiak, Jaroslav/A-8683-2019; Staccione, Andrea/KCL-3533-2024
OI Staccione, Andrea/0000-0002-9251-8952; Broccoli,
   Davide/0000-0003-3129-9618
FU JRC [JRC/IPR/2019/OP/0394]
FX This research was funded by JRC, grant number JRC/IPR/2019/OP/0394 - LOT
   7: Landscape Elements for Water Retention in a Mountainous Environment.
CR AdBPo, 2015, PIAN GEST DISTR IDR
   Aldieri L, 2020, RESOUR POLICY, V69, DOI 10.1016/j.resourpol.2020.101877
   Altamura V., 2014, COSTI PRODUZIONI PRI
   [Anonymous], 2013, FIN GREEN INFR GI EN
   [Anonymous], 2020, FIN COMM COMM EUR PA
   [Anonymous], 2010, CAR STRUTT AZ AGR 6
   [Anonymous], 2018, STAT ESTIMATIVE PROD
   [Anonymous], 2015, AGGIORNAMENTO QUADRO
   [Anonymous], 2016, GEOSCOPIO REGIONE TO
   [Anonymous], 2019, 640 FIN COMM COMM
   [Anonymous], 2020, PROIEZIONI CLIMATICH
   [Anonymous], 2017, GEOPORTALE E ROMAGNA
   [Anonymous], 2012, ROLE ECOSYSTEMS CLIM
   [Anonymous], 2019, GEOPORTALE E ROMAGNA
   Barth NC, 2016, ECOSYST SERV, V21, P39, DOI 10.1016/j.ecoser.2016.07.012
   Bastian O, 2013, ECOL INDIC, V24, P12, DOI 10.1016/j.ecolind.2012.05.016
   Behboudian M, 2021, SCI TOTAL ENVIRON, V751, DOI 10.1016/j.scitotenv.2020.141759
   Bernini L., 2009, ARPA RIV, P2
   Betti L., 2019, ANNATA AGRARIA ROMAG
   Bodin Ö, 2010, ECOL MODEL, V221, P2393, DOI 10.1016/j.ecolmodel.2010.06.017
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Borda-Niño M, 2017, APPL GEOGR, V83, P118, DOI 10.1016/j.apgeog.2017.03.012
   Cassani G., 2009, ACQUA, V2, P45
   Cohen-Sachman E., 2016, NATURE BASED SOLUTIO
   Consorzio di Bonifica Romagna Occidentale, 2019, PROGETTO LAMONE REL
   Consorzio di Bonifica Romagna Occidentale, 2015, UT FOND EUR VAL TERR
   Consorzio di Bonifica Romagna Occidentale, 2018, REL AGR QUADR RIF PR
   Copernicus, 2015, LAND MON SERV RIP Z
   Crea, 2019, BANC DAT RIC
   delle Entrate Agenzia, 2019, BANC DAT QUOT IMM OM
   di Faenza Comune, 2009, PIANO STRUTTURALE CO
   Dobriyal P, 2017, APPL WATER SCI, V7, P2617, DOI 10.1007/s13201-016-0488-y
   EBI: EFSI, 2019, EUR FUNDS STRAT INV
   EC, 2013, EC BEN TS NAT 2000 N
   EC, 2020, COMM COMM EUR PARL C
   EC, 2010, LIFE BUILD EUR GREEN
   EC, 2019, Rural development
   EC, 2012, GUID BEST PRACT LIM, P101
   EC, 2013, SYNTH DOC 1 INTR NAT
   EC, 2019, ENVRIONMENT
   EEA, 2019, USE FRESHW RES
   EEA-European Environment Agency, 2015, EEA TECH REP
   EIB, 2019, INV NAT FIN CONS NAT
   EU, 2015, EU RES INN POL AG NA
   Faivre N, 2017, ENVIRON RES, V159, P509, DOI 10.1016/j.envres.2017.08.032
   Fenu Gianni, 2018, Appl Netw Sci, V3, P22, DOI 10.1007/s41109-018-0085-0
   Gao XP, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9081439
   Greco M., 2014, STAT COMMON LAND NEL
   Harman B, 2011, J ENVIRON PLANN MAN, V54, P617, DOI 10.1080/09640568.2010.526405
   Häyhä T, 2014, ECOL MODEL, V289, P124, DOI 10.1016/j.ecolmodel.2014.07.002
   Hodgson JA, 2016, METHODS ECOL EVOL, V7, P1558, DOI 10.1111/2041-210X.12614
   Huang PJ, 2016, INDIAN J GEO-MAR SCI, V45, P1645
   Hundecha Y, 2016, J HYDROL-REG STUD, V6, P90, DOI 10.1016/j.ejrh.2016.04.002
   Institute for European Environmental Policy (IEEP) and Milieu, 2013, GUID MULT COH POL IN
   Irene L., 2011, GREEN INFRASTRUCTURE
   ISTAT, 2010, CENS AGR 2010 DAT
   IUCN, 2015, DIS CLIM CHAM CHANG
   Janssen-Jansen LB, 2008, LANDSCAPE URBAN PLAN, V87, P192, DOI 10.1016/j.landurbplan.2008.06.002
   Lafortezza Raffaele, 2018, Environ Res, V165, P431, DOI 10.1016/j.envres.2017.11.038
   Lafortezza R, 2013, IFOREST, V6, P102, DOI 10.3832/ifor0723-006
   Liquete C, 2015, ENVIRON SCI POLICY, V54, P268, DOI 10.1016/j.envsci.2015.07.009
   Liu SL, 2017, ECOL MODEL, V353, P129, DOI 10.1016/j.ecolmodel.2016.03.009
   Maes J, 2015, LANDSCAPE ECOL, V30, P517, DOI 10.1007/s10980-014-0083-2
   Magaudda S., 2020, SUSTAIN TIMES, V12, P1
   Masi F, 2017, ECOL ENG, V98, P427, DOI 10.1016/j.ecoleng.2016.03.043
   Mipaf, 2017, PROGR RET RUR NAZ IT
   Mitchell MGE, 2015, TRENDS ECOL EVOL, V30, P190, DOI 10.1016/j.tree.2015.01.011
   Mitchell MGE, 2013, ECOSYSTEMS, V16, P894, DOI 10.1007/s10021-013-9647-2
   Mueller J.E., 2010, 4 WORLD C ENV RESS E, P1
   Niu WJ, 2021, SUSTAIN CITIES SOC, V64, DOI 10.1016/j.scs.2020.102562
   OECD, 2006, COST BENEFIT ANAL EN, DOI [10.1787/9789264010055-en, DOI 10.1787/9789264010055-EN]
   Pascual-Hortal L, 2006, LANDSCAPE ECOL, V21, P959, DOI 10.1007/s10980-006-0013-z
   Realacci E., 2013, LEGISLATIVE PROPOSAL
   Renard V, 2007, TOWN PLAN REV, V78, P41, DOI 10.3828/tpr.78.1.4
   Rinaldi Ceroni F., 2014, COSTI PRODUZONE COLT
   Saura S., 2010, CONEFOR 2 6 USER MAN
   Saura S, 2009, ENVIRON MODELL SOFTW, V24, P135, DOI 10.1016/j.envsoft.2008.05.005
   Saura S, 2011, FOREST ECOL MANAG, V262, P150, DOI 10.1016/j.foreco.2011.03.017
   Saura S, 2010, ECOGRAPHY, V33, P523, DOI 10.1111/j.1600-0587.2009.05760.x
   Trzaska S., 2014, REV DOWNSCALING METH
   Vallecillo S, 2018, LANDSCAPE URBAN PLAN, V174, P41, DOI 10.1016/j.landurbplan.2018.03.001
   Vogt P, 2009, ECOL INDIC, V9, P64, DOI 10.1016/j.ecolind.2008.01.011
   Vogt P, 2017, EUR J REMOTE SENS, V50, P352, DOI 10.1080/22797254.2017.1330650
   Wang H, 2020, J ENVIRON MANAGE, V262, DOI 10.1016/j.jenvman.2020.110331
   Ward P, 2013, LAND USE POLICY, V31, P576, DOI 10.1016/j.landusepol.2012.09.004
NR 85
TC 17
Z9 18
U1 8
U2 57
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD AUG 15
PY 2021
VL 292
AR 112849
DI 10.1016/j.jenvman.2021.112849
EA MAY 2021
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA SP1CX
UT WOS:000659410400006
PM 34051473
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Quansah, JE
   Naliaka, AB
   Fall, S
   Ankumah, R
   El Afandi, G
AF Quansah, Joseph E.
   Naliaka, Amina B.
   Fall, Souleymane
   Ankumah, Ramble
   Afandi, Gamal El
TI Assessing Future Impacts of Climate Change on Streamflow within the
   Alabama River Basin
SO CLIMATE
LA English
DT Article
DE climate change; streamflow; SWAT model; GCM; CNRM-CM5; CESM1-BGC.1;
   HADGEM2-AO.1; Alabama River Basin
ID MODEL; VARIABILITY; CALIFORNIA
AB Global climate change is expected to impact future precipitation and surface temperature trends and could alter local hydrologic systems. This study assessed the likely hydrologic responses and changes in streamflow due to future climate change within the Alabama River Basin (ARB) for the mid-21st century 2045 ("2030-2060") and end-21st century 2075 ("2060-2090"). Using an integrated modeling approach, General Circulation Model (GCM) datasets; the Centre National de Recherches Meteorologiques Climate Model 5 (CNRM-CM5), the Community Earth System Model, version 1-Biogeochemistry (CESM1- BGC.1), and the Hadley Centre Global Environment Model version 2 (HADGEM2-AO.1), under medium Representative Concentration Pathway (RCP) 4.5, and based on World Climate Research Program (WCRP)'s Couple Model Intercomparison Phase 5 (CMIP5), were assimilated into calibrated Soil and Water Assessment Tool (SWAT). Mann-Kendall and Theil Sen's slope were used to assess the trends and magnitude of variability of the historical climate data used for setting up the model. The model calibration showed goodness of fit with minimum Nash-Sutcliffe Efficiency (NSE) coefficient values of 0.83 and Coefficient of Determination (R-2) of 0.88 for the three gages within the ARB. Next, the research assessed changes in streamflow for the years 2045 and 2075 against that of the reference baseline year of 1980. The results indicate situations of likely increase and decrease in mean monthly streamflow discharge and increase in the frequency and variability in peak flows during the periods from the mid to end of the 21st century. Seasonally, monthly streamflow increases between 50% and 250% were found for spring and autumn months with decreases in summer months for 2045. Spring and summer months for 2075 resulted in increased monthly streamflow between 50% and 300%, while autumn and spring months experienced decreased streamflow. While the results are prone to inherent uncertainties in the downscaled GCM data used, the simulated dynamics in streamflow and water availability provide critical information for stakeholders to develop sustainable water management and climate change adaptation options for the ARB.
C1 [Quansah, Joseph E.; Fall, Souleymane; Ankumah, Ramble; Afandi, Gamal El] Tuskegee Univ, Dept Agr & Environm Sci, Tuskegee, AL 36088 USA.
   [Naliaka, Amina B.] Southern Illinois Univ, Sch Earth Syst & Sustainabil, Carbondale, IL 62901 USA.
C3 Tuskegee University; Southern Illinois University System; Southern
   Illinois University
RP Quansah, JE (corresponding author), Tuskegee Univ, Dept Agr & Environm Sci, Tuskegee, AL 36088 USA.
EM jquansah@tuskegee.edu; amina.naliaka@siu.edu; sfall@tuskegee.edu;
   rankumah@tuskegee.edu; gelafandi@tuskegee.edu
RI El Afandi, Gamal/AAZ-4973-2021
OI Fall, Souleymane/0000-0002-0594-8939
FU USDA-NIFA [1001194]; NIFA [1001194, 689305] Funding Source: Federal
   RePORTER
FX This research supported by USDA-NIFA, grant number 1001194.
CR Alexander LV, 2017, WEATHER CLIM EXTREME, V15, P34, DOI 10.1016/j.wace.2017.02.001
   Ali R, 2019, WATER-SUI, V11, DOI 10.3390/w11091855
   Allen M.R., 2018, Framing and context. In: Global Warming of 1.5C. An IPCC special report on the impacts of global warming of 1.5C above preindustrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development
   [Anonymous], 2020, NASA GODDARD I SPACE
   [Anonymous], 2011, IMPACT GLOBAL CHANGE
   Arnold JG, 2012, T ASABE, V55, P1491
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   Aryal Y, 2020, INT J CLIMATOL, V40, P3360, DOI 10.1002/joc.6402
   Bates B.C., 2008, LINKING CLIMATE CHAN
   Bennett JC, 2014, INT J CLIMATOL, V34, P2189, DOI 10.1002/joc.3830
   Field C.B.V., 2012, MANAGING RISKS EXTRE, P14
   Gangrade S, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-59806-6
   Garcia F, 2017, HYDROLOG SCI J, V62, P1149, DOI 10.1080/02626667.2017.1308511
   Gleick P.H., 2000, WATER POTENTIAL CONS, P126
   Hoegh-Guldberg O., 2018, Global warming of 1.5C
   IPCC, IPCC special report on carbon dioxide capture and storage
   Karl T.R., 2009, GLOBAL CLIMATE CHANG, V54
   Kleinschmidt E., 2005, ALABAMA RIVER BASIN
   Koch J, 2016, J HYDROL, V533, P234, DOI 10.1016/j.jhydrol.2015.12.002
   Krause P., 2005, ADV GEOSCIENCES, V5, P89, DOI DOI 10.5194/ADGEO-5-89-2005
   Krysanova V, 2015, HYDROLOG SCI J, V60, P771, DOI 10.1080/02626667.2015.1029482
   Kuriqi A, 2020, ACTA GEOPHYS, V68, P1461, DOI 10.1007/s11600-020-00475-4
   Leta OT, 2016, J HYDROL-REG STUD, V8, P182, DOI 10.1016/j.ejrh.2016.09.006
   Li Z, 2017, HYDROL EARTH SYST SC, V21, P5531, DOI 10.5194/hess-21-5531-2017
   Lins H.F., 2009, USGS Hydro-Climatic Data Network 2009 (HCDN-2009)
   Long MC, 2013, J CLIMATE, V26, P6775, DOI 10.1175/JCLI-D-12-00184.1
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Martin GM, 2011, GEOSCI MODEL DEV, V4, P723, DOI 10.5194/gmd-4-723-2011
   Maurer EP, 2007, CLIMATIC CHANGE, V82, P309, DOI 10.1007/s10584-006-9180-9
   McCuen RH, 2016, J HYDROL ENG, V21, DOI 10.1061/(ASCE)HE.1943-5584.0001340
   Miao CY, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/5/055007
   Mirzabaev A., 2019, CLIMATE CHANGE LAND
   Mohammed IN, 2015, J HYDROL-REG STUD, V3, P160, DOI 10.1016/j.ejrh.2015.01.002
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Murgulet D, 2008, ENVIRON GEOL, V55, P1235, DOI 10.1007/s00254-007-1068-0
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Neitsch S., SOIL WATER ASSESSMEN
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Pathak TB, 2018, AGRONOMY-BASEL, V8, DOI 10.3390/agronomy8030025
   Pitz C.F., 2016, 1603006 STAT WASH DE
   Quansah JE, 2008, T ASABE, V51, P1311, DOI 10.13031/2013.25247
   Randall DA, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P589
   Runkle Jennifer., 2017, NOAA Technical Report NESDIS 149-KY
   Rupp D. E., 2016, U.S. Geological Survey OpenFile Report, V1047, DOI [10.3133/ofr20161047, DOI 10.3133/ofr20161047]
   SEN PK, 1968, J AM STAT ASSOC, V63, P1379
   Seneviratne SI, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P109
   Sinclair W.C., 1982, 8150 USGS
   Su BD, 2017, CLIMATIC CHANGE, V141, P533, DOI 10.1007/s10584-016-1852-5
   Sunde MG, 2017, HYDROL PROCESS, V31, P1790, DOI 10.1002/hyp.11150
   Theil H., 1950, P K NED AKAD WETENSC, V3, P1397
   Thomson AM, 2011, CLIMATIC CHANGE, V109, P77, DOI 10.1007/s10584-011-0151-4
   U.S. Army Corps of Engineers (USACE), 1998, ENV DAT INV STAT AL
   U.S. Environmental Protection Agency (EPA), 2016, 430R16004 EPA, V4th
   U.S. Geological Survey (USGS), 2006, AN DAT NAT WAT INF S
   UN General Assembly, ARES48189 US GEN ASS
   Vincent WF., 2009, Encyclopedia of Inland Waters, V3, P55, DOI DOI 10.1016/B978-012370626-3.00233-7
   Voldoire A, 2013, CLIM DYNAM, V40, P2091, DOI 10.1007/s00382-011-1259-y
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   Weiskopf SR, 2020, SCI TOTAL ENVIRON, V733, DOI 10.1016/j.scitotenv.2020.137782
   Zhao TB, 2015, J CLIMATE, V28, P4490, DOI 10.1175/JCLI-D-14-00363.1
NR 60
TC 18
Z9 18
U1 0
U2 8
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2225-1154
J9 CLIMATE
JI Climate
PD APR
PY 2021
VL 9
IS 4
AR 55
DI 10.3390/cli9040055
PG 19
WC Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Meteorology & Atmospheric Sciences
GA RR2GI
UT WOS:000642923100001
OA gold
DA 2025-01-10
ER

PT J
AU Tcvetkov, P
AF Tcvetkov, Pavel
TI Climate Policy Imbalance in the Energy Sector: Time to Focus on the
   Value of CO<sub>2</sub> Utilization
SO ENERGIES
LA English
DT Article
DE climate policy; carbon tax; CO2 costs; value of CO2 utilization;
   hydrocarbons; energy sector; carbon capture; carbon utilization; carbon
   storage; climate change mitigation; climate change adaptation
ID FEED-IN TARIFF; KUZNETS CURVE HYPOTHESIS; RENEWABLE PORTFOLIO STANDARDS;
   CARBON CAPTURE; SOCIAL COST; ECONOMIC-GROWTH; EMISSION REDUCTION; CHANGE
   ADAPTATION; GREEN PARADOX; STORAGE
AB Global warming is an existential threat to humanity and the rapid energy transition, which is required, will be the defining social, political and technical challenge of the 21st century. Practical experience and research results of recent years have showed that our actions to cover the gap between real situation and aims of climate agreements are not enough and that improvements in climate policy are needed, primarily in the energy sector. It is becoming increasingly clear that hydrocarbon resources, which production volume is increasing annually, will remain a significant part of the global fuel balance in the foreseeable future. Taking this into account, the main problem of the current climate policy is a limited portfolio of technologies, focused on replacement of hydrocarbon resources with renewable energy, without proper attention to an alternative ways of decreasing carbon intensity, such as carbon sequestration options. This study shows the need to review the existing climate policy portfolios through reorientation to CO2 utilization and disposal technologies and in terms of forming an appropriate appreciation for the role of hydrocarbon industries as the basis for the development of CO2-based production chains. In this paper we argue that: (1) focusing climate investments on a limited portfolio of energy technologies may become a trap that keeps us from achieving global emissions goals; (2) accounting for greenhouse gas (GHG) emissions losses, without taking into account the potential social effects of utilization, is a barrier to diversifying climate strategies; (3) with regard to hydrocarbon industries, a transition from destructive to creative measures aimed at implementing environmental projects is needed; (4) there are no cheap climate solutions, but the present cost of reducing CO2 emissions exceeds any estimate of the social cost of carbon.
C1 [Tcvetkov, Pavel] St Petersburg Min Univ, Dept Econ Org & Management, 21 Line,2, St Petersburg 199106, Russia.
C3 Saint Petersburg Mining University
RP Tcvetkov, P (corresponding author), St Petersburg Min Univ, Dept Econ Org & Management, 21 Line,2, St Petersburg 199106, Russia.
EM pscvetkov@yandex.ru
RI Tcvetkov, Pavel/A-3106-2016
OI Tcvetkov, Pavel/0000-0002-3049-7893
FU Russian Science Foundation [18-18-00210]; Saint Petersburg Mining
   University; Russian Science Foundation [18-18-00210] Funding Source:
   Russian Science Foundation
FX The research is carried out with the financial support of the grant of
   the Russian Science Foundation (Project No. 18-18-00210, "Development of
   assessment methodology of public efficiency of projects devoted to
   carbon dioxide sequestration"). YSaint Petersburg Mining University.
CR Agarwal A.S., 2017, HDB CLIMATE CHANGE M, P2487
   Al-Ghussain L, 2019, ENVIRON PROG SUSTAIN, V38, P13, DOI 10.1002/ep.13041
   Alizada K, 2018, ENERGY RES SOC SCI, V44, P346, DOI 10.1016/j.erss.2018.05.033
   [Anonymous], PATHWAYS LOW CARBON
   [Anonymous], 2019, The Circularity Gap Report 2019
   Archer D, 2020, CLIMATIC CHANGE, V162, P2069, DOI 10.1007/s10584-020-02785-4
   Aresta M, 2019, EC BASED CARBON DIOX, DOI [10.1007/978-3-030-15868-2_13, DOI 10.1007/978-3-030-15868-2_13]
   Aslan A, 2018, ENVIRON SCI POLLUT R, V25, P2402, DOI 10.1007/s11356-017-0548-3
   Babacan O, 2020, NAT ENERGY, V5, P720, DOI 10.1038/s41560-020-0646-1
   Bach M, 2019, ENVIRON POLIT, V28, P87, DOI 10.1080/09644016.2019.1521911
   Balezentis T, 2021, ENERGY, V214, DOI 10.1016/j.energy.2020.119081
   Bastien-Olvera BA, 2021, NAT SUSTAIN, V4, P101, DOI 10.1038/s41893-020-00615-0
   Bauer N, 2018, NAT CLIM CHANGE, V8, P130, DOI 10.1038/s41558-017-0053-1
   Behrens A., 2016, CEPS POLICY BRIEF
   Bhadola A., 2020, Technology Scouting - Carbon Capture: from Today's to Novel Technologies
   Biniek K., 2019, WHY COMMERCIAL USE C
   Biniek K, 2020, McKinsey Q
   Bobeck J., 2019, CARBON UTILIZATION V
   Böhringer C, 2017, ENERG ECON, V67, P545, DOI 10.1016/j.eneco.2017.09.001
   Böhringer C, 2015, J REGUL ECON, V48, P74, DOI 10.1007/s11149-015-9279-x
   Böhringer C, 2014, REV ENV ECON POLICY, V8, P1, DOI 10.1093/reep/ret018
   Bovari E, 2018, ECOL ECON, V147, P383, DOI 10.1016/j.ecolecon.2018.01.034
   Bruhn T, 2016, ENVIRON SCI POLICY, V60, P38, DOI 10.1016/j.envsci.2016.03.001
   Buchner B., 2019, GLOBAL LANDSCAPE CLI
   Budinis S, 2018, ENERGY STRATEG REV, V22, P61, DOI 10.1016/j.esr.2018.08.003
   Buonocore E, 2019, ECOL MODEL, V392, P137, DOI 10.1016/j.ecolmodel.2018.11.018
   Callaghan MW, 2020, NAT CLIM CHANGE, V10, P118, DOI 10.1038/s41558-019-0684-5
   Carbon Limits AS and THEMA Consulting Group, 2020, ROL CARB CAPT STOR C
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   Carley S, 2018, NAT ENERGY, V3, P754, DOI 10.1038/s41560-018-0202-4
   Chauvy R, 2020, SUSTAIN PROD CONSUMP, V24, P194, DOI 10.1016/j.spc.2020.07.002
   Cherepovitsyn AK, 2019, J MIN INST, V240, P731, DOI 10.31897/PMI.2019.6.731
   Corno-Gandolphe, 2019, CARBON CAPTURE STORA
   de Lagarde CM, 2018, ENERG POLICY, V117, P263, DOI 10.1016/j.enpol.2018.02.048
   Dolgonosov B.M, 2018, BIOPHYS EC RESOUR QU, V3, DOI [10.1007/s41247-018-0037-4, DOI 10.1007/S41247-018-0037-4]
   Du Y, 2020, IMPACT FEED TARIFF R, V87, P104710
   Durán-Romero G, 2020, TECHNOL FORECAST SOC, V160, DOI 10.1016/j.techfore.2020.120246
   European Commission, 2020, A new Circular Economy Action Plan For a cleaner and more competitive Europe, DOI [10.2779/05068, DOI 10.2779/05068]
   Fais B, 2016, APPL ENERG, V162, P699, DOI 10.1016/j.apenergy.2015.10.112
   Fan JL, 2019, ENERG POLICY, V132, P1229, DOI 10.1016/j.enpol.2019.07.010
   Fan JL, 2018, APPL ENERG, V229, P326, DOI 10.1016/j.apenergy.2018.07.117
   Fasihi M, 2019, J CLEAN PROD, V224, P957, DOI 10.1016/j.jclepro.2019.03.086
   Fawzy S, 2020, ENVIRON CHEM LETT, V18, P2069, DOI 10.1007/s10311-020-01059-w
   Frantzeskaki N, 2019, REG ENVIRON CHANGE, V19, P777, DOI 10.1007/s10113-019-01475-x
   Friedmann Julio., 2020, Levelized Cost of Carbon Abatement: An Improved Cost-Assessment Methodology for a Net-Zero Emissions World
   Fuss S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabf9f
   Gillingham K, 2018, J ECON PERSPECT, V32, P53, DOI 10.1257/jep.32.4.53
   Global CCS Institute, 2019, GLOB STAT STAT REP
   Goodarzi S, 2019, PROD OPER MANAG, V28, P1108, DOI 10.1111/poms.12971
   Greenstone M., 2019, Do Renewable Portfolio Standards Deliver?, DOI DOI 10.2139/SSRN.3374942
   Hashmi R, 2019, J CLEAN PROD, V231, P1100, DOI 10.1016/j.jclepro.2019.05.325
   Hatfield-Dodds S, 2017, J CLEAN PROD, V144, P403, DOI 10.1016/j.jclepro.2016.12.170
   He G, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-16184-x
   Hennessey R, 2017, ENERG POLICY, V111, P214, DOI 10.1016/j.enpol.2017.09.025
   Hepburn C, 2019, NATURE, V575, P87, DOI 10.1038/s41586-019-1681-6
   Hitaj C, 2019, RESOUR ENERGY ECON, V57, P18, DOI 10.1016/j.reseneeco.2018.12.001
   Hoegh-Guldberg O., 2018, Global warming of 1.5C
   Hope C, 2013, CLIMATIC CHANGE, V117, P531, DOI 10.1007/s10584-012-0633-z
   https://dualchallenge.npc.org/downloads.php, 2019, NPC M DUAL CHALL ROA
   IEA, 2019, PUTTING CO 2 USE CRE, P86
   IEA, 2020, CO 2 EM FUEL COMB OV
   IEA, 2020, Special Report on Carbon Capture Utilisation and Storage: CCUS in Clean Energy Transitions
   IEA, 2020, Technical Report
   IEA, 2020, ETP Clean Energy Technology Guide
   IEA, 2020, Methane Tracker 2020
   IEAGHG, 2019, ZER EM CCS POW STAT
   Ilinova AA, 2020, J MIN INST, V244, P493, DOI 10.31897/PMI.2020.4.12
   Jarvis SM, 2018, RENEW SUST ENERG REV, V85, P46, DOI 10.1016/j.rser.2018.01.007
   Jin G, 2020, RENEW SUST ENERG REV, V130, DOI 10.1016/j.rser.2020.109949
   Kätelhön A, 2019, P NATL ACAD SCI USA, V116, P11187, DOI 10.1073/pnas.1821029116
   Kaufman N, 2020, NAT CLIM CHANGE, V10, P1010, DOI 10.1038/s41558-020-0880-3
   Keith DW, 2018, JOULE, V2, P1573, DOI 10.1016/j.joule.2018.05.006
   Kemeny T, 2010, WORLD DEV, V38, P1543, DOI 10.1016/j.worlddev.2010.03.001
   Koçak E, 2019, ENVIRON SCI POLLUT R, V26, P14328, DOI 10.1007/s11356-019-04712-2
   Kolster C, 2017, ENERG ENVIRON SCI, V10, P2594, DOI 10.1039/c7ee02102j
   Kumar S, 2020, J NAT GAS SCI ENG, V81, DOI 10.1016/j.jngse.2020.103437
   Leeson D, 2017, INT J GREENH GAS CON, V61, P71, DOI 10.1016/j.ijggc.2017.03.020
   Li WH, 2018, RSC ADV, V8, P7651, DOI 10.1039/c7ra13546g
   Lin BQ, 2020, HUM SOC SCI COMMUN, V7, DOI 10.1057/s41599-020-00569-w
   Litvinenko VS, 2020, NAT RESOUR RES, V29, P1521, DOI 10.1007/s11053-019-09568-4
   Litvinenko V, 2020, RESOURCES-BASEL, V9, DOI 10.3390/resources9050059
   Liu Z, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18922-7
   Lu YH, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12125078
   Mac Dowell N, 2017, NAT CLIM CHANGE, V7, P243, DOI 10.1038/NCLIMATE3231
   Marcott SA, 2013, SCIENCE, V339, P1198, DOI 10.1126/science.1228026
   Moriarty P, 2019, ENERG POLICY, V131, P229, DOI 10.1016/j.enpol.2019.05.006
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Nagle AJ, 2020, J CLEAN PROD, V277, DOI 10.1016/j.jclepro.2020.123321
   Nordhaus W, 2018, CLIMATIC CHANGE, V148, P623, DOI 10.1007/s10584-018-2218-y
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Oerlemans LAG, 2016, RENEW SUST ENERG REV, V66, P875, DOI 10.1016/j.rser.2016.08.054
   OhAiseadha C, 2020, ENERGIES, V13, DOI 10.3390/en13184839
   Ota T, 2017, PALGR COMMUN, V3, DOI 10.1057/palcomms.2017.69
   Özokcu S, 2017, RENEW SUST ENERG REV, V72, P639, DOI 10.1016/j.rser.2017.01.059
   Pieri T, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5100108
   Pour N., 2019, STATUS BIOENERGY CAR, DOI [10.1016/B978-0-12-816229-3.00005-3, DOI 10.1016/B978-0-12-816229-3.00005-3]
   Quarton CJ, 2020, APPL ENERG, V257, DOI 10.1016/j.apenergy.2019.113936
   Reis AD, 2018, J CLEAN PROD, V200, P269, DOI 10.1016/j.jclepro.2018.07.271
   Ricke K, 2018, NAT CLIM CHANGE, V8, P895, DOI 10.1038/s41558-018-0282-y
   Robinson SA, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.653
   Rochedo PRR, 2016, J CLEAN PROD, V131, P280, DOI 10.1016/j.jclepro.2016.05.033
   Romasheva N, 2019, RESOURCES-BASEL, V8, DOI 10.3390/resources8040181
   Rosendahl, 2019, CESIFO WORKING PAPER
   Royal Society, 2018, GREENH GAS REM
   Rubin ES, 2015, INT J GREENH GAS CON, V40, P378, DOI 10.1016/j.ijggc.2015.05.018
   Saeidi S, 2017, RENEW SUST ENERG REV, V80, P1292, DOI 10.1016/j.rser.2017.05.204
   San-Akca B, 2020, ENERGY RES SOC SCI, V70, DOI 10.1016/j.erss.2020.101690
   Sarkodie SA, 2019, SCI TOTAL ENVIRON, V649, P128, DOI 10.1016/j.scitotenv.2018.08.276
   Siddiqui AS, 2016, EUR J OPER RES, V250, P328, DOI 10.1016/j.ejor.2015.10.063
   Siegenthaler U, 2005, SCIENCE, V310, P1313, DOI 10.1126/science.1120130
   Silvestre BS, 2017, J CLEAN PROD, V142, P360, DOI 10.1016/j.jclepro.2016.07.215
   SINHA A, 2019, DATA SELECTION ENV K, P65
   Sinn HW, 2008, INT TAX PUBLIC FINAN, V15, P360, DOI 10.1007/s10797-008-9082-z
   Skytt T, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105831
   Smol M, 2020, RESOURCES-BASEL, V9, DOI 10.3390/resources9050055
   Solarin SA, 2017, RENEW SUST ENERG REV, V80, P1578, DOI 10.1016/j.rser.2017.07.028
   Song CF, 2018, RENEW SUST ENERG REV, V82, P215, DOI 10.1016/j.rser.2017.09.040
   Spurgeon JM, 2018, ENERG ENVIRON SCI, V11, P1536, DOI 10.1039/c8ee00097b
   Steinkraus A, 2019, GER ECON REV, V20, pE545, DOI 10.1111/geer.12176
   Stern N, 2016, NATURE, V530, P407, DOI 10.1038/530407a
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Stuardi FM, 2019, CURR OPIN GREEN SUST, V16, P71, DOI 10.1016/j.cogsc.2019.02.003
   Tabatabaei SM, 2017, ENERG POLICY, V102, P164, DOI 10.1016/j.enpol.2016.12.028
   Taskforce C.C.C., 2018, DEL CLEAN GROWTH CCU
   Tcvetkov P, 2019, HELIYON, V5, DOI 10.1016/j.heliyon.2019.e02845
   García-Alvarez MT, 2017, RENEW ENERG, V111, P256, DOI 10.1016/j.renene.2017.03.067
   Thisted EV, 2020, ENVIRON POLIT, V29, P804, DOI 10.1080/09644016.2019.1661155
   Thonemann N, 2019, ENERG ENVIRON SCI, V12, P2253, DOI 10.1039/c9ee00914k
   Tol RSJ, 2019, ENERG ECON, V83, P555, DOI 10.1016/j.eneco.2019.07.006
   Tol RSJ, 2018, REV ENV ECON POLICY, V12, P4, DOI 10.1093/reep/rex027
   Tol RichardS.J., 1997, Environmental Modelling and Assessment, V2, P151, DOI [DOI 10.1023/A:1019017529030, 10.1023/A:1019017529030]
   Tsvetkova A., 2018, P 18 INT MULT SCI GE, VVolume 18, P75
   van den Bijgaart I, 2016, J ENVIRON ECON MANAG, V77, P75, DOI 10.1016/j.jeem.2016.01.005
   van der Ploeg F, 2015, REV ENV ECON POLICY, V9, P285, DOI 10.1093/reep/rev008
   VASILEV Y, 2019, 19 INT MULT SCI GEOC, V19, P415, DOI DOI 10.5593/SGEM2019/5.1/S20.052
   Walsh Brian J, 2015, Carbon Balance Manag, V10, P26
   Wang L, 2020, SOIL USE MANAGE, V36, P355, DOI 10.1111/sum.12589
   Wich T, 2020, FRONT ENERGY RES, V7, DOI 10.3389/fenrg.2019.00162
   Xie X, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041109
   Xu Y, 2018, WASTE MANAGE, V75, P450, DOI 10.1016/j.wasman.2018.01.036
   Xydis G, 2019, RESOURCES-BASEL, V8, DOI 10.3390/resources8020106
   Yang L, 2019, APPL ENERG, V255, DOI 10.1016/j.apenergy.2019.113828
   Yu H., 2018, A Comparison of Public Preferences for Different Low-Carbon Energy Technologies: Support for CCS, Nuclear and Wind Energy in the United Kingdom
   Yu XM, 2016, J CLEAN PROD, V133, P18, DOI 10.1016/j.jclepro.2016.05.103
   Zachmann G., 2020, Policy Contribution, Bruegel
   Zhai HB, 2019, ISCIENCE, V13, P440, DOI 10.1016/j.isci.2019.03.006
   Zhang Q, 2018, APPL ENERG, V227, P426, DOI 10.1016/j.apenergy.2017.07.118
   Zhang ZE, 2020, RENEW SUST ENERG REV, V125, DOI 10.1016/j.rser.2020.109799
   Zhiznin SZ, 2020, INT J HYDROGEN ENERG, V45, P31353, DOI 10.1016/j.ijhydene.2020.08.260
   Zuo Y, 2019, J CLEAN PROD, V213, P1274, DOI 10.1016/j.jclepro.2018.12.170
NR 150
TC 47
Z9 47
U1 2
U2 36
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1996-1073
J9 ENERGIES
JI Energies
PD JAN
PY 2021
VL 14
IS 2
AR 411
DI 10.3390/en14020411
PG 22
WC Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Energy & Fuels
GA PX2WI
UT WOS:000611220700001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Qiu, T
   Song, CH
   Clark, JS
   Seyednasrollah, B
   Rathnayaka, N
   Li, JX
AF Qiu, Tong
   Song, Conghe
   Clark, James S.
   Seyednasrollah, Bijan
   Rathnayaka, Nuvan
   Li, Junxiang
TI Understanding the continuous phenological development at daily time step
   with a Bayesian hierarchical space-time model: impacts of climate change
   and extreme weather events
SO REMOTE SENSING OF ENVIRONMENT
LA English
DT Article
DE Land surface phenology; Bayesian hierarchical model; Continuous
   development; Extreme weather events; Climate change; Vegetation index
ID LAND-SURFACE PHENOLOGY; VEGETATION GREEN-UP; NORTHERN-HEMISPHERE; SPRING
   PHENOLOGY; AUTUMN PHENOLOGY; CARBON UPTAKE; SERIES DATA; TEMPERATE;
   RESPONSES; GROWTH
AB The impacts of climate change and extreme weather events (e.g. frost-, heat-, drought-, and heavy rainfall events) on the continuous phenological development over the entire seasonal cycle remained poorly understood. Previous studies mainly focused on modeling key phenological transition dates (e.g. discrete timing of spring bud-break and fall senescence) based on aggregated climate variables (e.g. mean temperature, growing-degree days). We developed and evaluated a Bayesian Hierarchical Space-Time model for Land Surface Phenology (BHST-LSP) to synthesize remotely sensed vegetation greenness with climate covariates at a daily temporal scale from 1981 to 2014 across the entire conterminous United States. The BHST-LSP model incorporated both temporal and spatial information and exhibited high predictive power in simulating daily phenological development with an overall out-of-sample R-2 of 0.80 +/- 0.17 and 0.72 +/- 0.20 for spring and fall phenology, respectively. The overall out-of-sample normalized root mean square errors were 9.3% +/- 6.1% and 9.9% +/- 5.2% between the observed and predicted vegetation greenness for spring and fall phenology, respectively. We found that a fast increase of temperature can accelerate the speed of spring green-up while a slow decrease of temperature can lead to a decelerated fall brown-down. Increasing accumulated precipitation can benefit daily phenological development over an entire growing season, while extreme rainfall events can have the opposite effects. More frequent frost events could slow spring leaf expansion and accelerate fall leaf senescence. Impacts of extreme heat events were complex and depended on water availability. Cropland in the Midwest as well as evergreen needleleaf forest along the coastal regions showed relatively strong resistance to drought events compared to other land cover types. The BHST-LSP model can be used to forecast vegetation phenology given future climate projection, thus providing valuable information for adopting climate change adaptation and mitigation measures.
C1 [Qiu, Tong; Song, Conghe] Univ N Carolina, Dept Geog, Chapel Hill, NC 27599 USA.
   [Qiu, Tong; Clark, James S.] Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA.
   [Clark, James S.] Duke Univ, Dept Stat Sci, Durham, NC 27708 USA.
   [Seyednasrollah, Bijan] No Arizona Univ, Sch Informat Comp & Cyber Syst, Flagstaff, AZ 86011 USA.
   [Seyednasrollah, Bijan] No Arizona Univ, Ctr Ecosyst Sci & Soc, Flagstaff, AZ 86011 USA.
   [Rathnayaka, Nuvan] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA.
   [Li, Junxiang] Shanghai Jiao Tong Univ, Sch Design, Shanghai 200240, Peoples R China.
C3 University of North Carolina; University of North Carolina Chapel Hill;
   Duke University; Duke University; Northern Arizona University; Northern
   Arizona University; University of North Carolina; University of North
   Carolina Chapel Hill; Shanghai Jiao Tong University
RP Qiu, T (corresponding author), Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA.
EM tong.qiu@duke.edu
RI Clark, James/JPK-8317-2023; Qiu, Tong/AFV-7308-2022; Li,
   Junxiang/GSN-5545-2022; Song, Conghe/E-3087-2016; Seyednasrollah,
   Bijan/N-2006-2019; Li, Junxiang/G-6621-2014
OI Qiu, Tong/0000-0003-4499-437X; Li, Junxiang/0000-0001-8452-8029
FU National Aeronautics and Space Administration (NASA) [NNX17AE69G];
   Natural Science Foundation of China [31370482]; University of North
   Carolina at Chapel Hill
FX This research was partially supported by National Aeronautics and Space
   Administration (NASA) with Grant No. NNX17AE69G. T. Qiu also thanks
   University of North Carolina at Chapel Hill for providing the James
   Carlton Ingram summer research fellowship. JX. Li acknolwedge the
   support from Natural Science Foundation of China (Grant No. 31370482).
   We acknowledged NASA's Making Earth System Data Records for Use in
   Research Environments (MEaSUREs) Vegetation Index and Phenology (VIP)
   product for providing the daily EVI2 data, European Space Agency's
   Climate Change Initiative for providing the annual land cover data,
   NASA's Oak Ridge National Laboratory (ORNL) Distributed Active Archive
   Center (DAAC) for providing the Daymet dataset. We thanked Dr. Yulong
   Zhang for providing valuable feedbacks at the early stage of this
   manuscript. We thanked the editor and the reviewers for their insightful
   comments and suggestions. We also thanked Mr. Sandeep Sarangi and Mr.
   Mike Waldron for providing assistant on using UNC Longleaf and Dogwood
   Computing cluster.
CR Alward RD, 1999, SCIENCE, V283, P229, DOI 10.1126/science.283.5399.229
   [Anonymous], GLOB CHANG BIOL
   [Anonymous], 2007, GLOB BIOGEOCHEM CYCL
   [Anonymous], 2016, NASA EOSDIS LAND PRO
   [Anonymous], CLIM CHANG 2013
   Atkinson PM, 2012, REMOTE SENS ENVIRON, V123, P400, DOI 10.1016/j.rse.2012.04.001
   Atzberger C, 2011, INT J DIGIT EARTH, V4, P365, DOI 10.1080/17538947.2010.505664
   Bakar KS, 2015, J STAT SOFTW, V63, P1, DOI 10.18637/jss.v063.i15
   Banerjee S, 2008, J R STAT SOC B, V70, P825, DOI 10.1111/j.1467-9868.2008.00663.x
   Buermann W, 2018, NATURE, V562, P110, DOI 10.1038/s41586-018-0555-7
   Chen J, 2004, REMOTE SENS ENVIRON, V91, P332, DOI 10.1016/j.rse.2004.03.014
   Chuine I, 1999, PLANT CELL ENVIRON, V22, P1, DOI 10.1046/j.1365-3040.1999.00395.x
   Clark JS, 2014, FUNCT ECOL, V28, P1344, DOI 10.1111/1365-2435.12309
   Clark JS, 2014, GLOBAL CHANGE BIOL, V20, P1136, DOI 10.1111/gcb.12420
   Clark JS, 2011, ECOL APPL, V21, P1523, DOI 10.1890/09-1212.1
   Clark JS, 2005, ECOL LETT, V8, P2, DOI 10.1111/j.1461-0248.2004.00702.x
   Clark JS, 2004, ECOLOGY, V85, P3140, DOI 10.1890/03-0520
   Clark JS., 2006, HIERARCHICAL MODELLI
   Cleland EE, 2007, TRENDS ECOL EVOL, V22, P357, DOI 10.1016/j.tree.2007.04.003
   CLEVELAND WS, 1979, J AM STAT ASSOC, V74, P829, DOI 10.2307/2286407
   Cong N, 2013, GLOBAL CHANGE BIOL, V19, P881, DOI 10.1111/gcb.12077
   Cremonese E, 2017, AGR FOREST METEOROL, V247, P320, DOI 10.1016/j.agrformet.2017.08.016
   Dannenberg MP, 2015, REMOTE SENS ENVIRON, V159, P167, DOI 10.1016/j.rse.2014.11.026
   Eilers PHC, 2003, ANAL CHEM, V75, P3631, DOI 10.1021/ac034173t
   Fan Y, 2013, SCIENCE, V339, P940, DOI 10.1126/science.1229881
   Finley AO, 2009, COMPUT STAT DATA AN, V53, P2873, DOI 10.1016/j.csda.2008.09.008
   Friedl MA, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/5/054006
   Fu YSH, 2016, NEW PHYTOL, V212, P590, DOI 10.1111/nph.14073
   Fu YSH, 2015, NATURE, V526, P104, DOI 10.1038/nature15402
   Fu YSH, 2015, GLOBAL CHANGE BIOL, V21, P2687, DOI 10.1111/gcb.12863
   Fu YSH, 2014, GLOBAL CHANGE BIOL, V20, P3743, DOI 10.1111/gcb.12610
   Gallinat AS, 2015, TRENDS ECOL EVOL, V30, P169, DOI 10.1016/j.tree.2015.01.004
   Ganguly S, 2010, REMOTE SENS ENVIRON, V114, P1805, DOI 10.1016/j.rse.2010.04.005
   Garonna I, 2014, GLOBAL CHANGE BIOL, V20, P3457, DOI 10.1111/gcb.12625
   Geweke John, 1991, EVALUATING ACCURACY
   Griffin KL, 2002, GLOBAL CHANGE BIOL, V8, P479, DOI 10.1046/j.1365-2486.2002.00487.x
   Gu L, 2008, BIOSCIENCE, V58, P253, DOI 10.1641/B580311
   Hammond ML, 2018, GEOPHYS RES LETT, V45, P7654, DOI 10.1029/2017GL076928
   Hammond ML, 2017, GLOBAL BIOGEOCHEM CY, V31, P1103, DOI 10.1002/2016GB005600
   HANDCOCK MS, 1994, J AM STAT ASSOC, V89, P368, DOI 10.2307/2290832
   HANDCOCK MS, 1993, TECHNOMETRICS, V35, P403, DOI 10.2307/1270273
   He ZB, 2018, AGR FOREST METEOROL, V260, P31, DOI 10.1016/j.agrformet.2018.05.022
   Hwang T, 2014, GLOBAL CHANGE BIOL, V20, P2580, DOI 10.1111/gcb.12556
   Jentsch A, 2009, GLOBAL CHANGE BIOL, V15, P837, DOI 10.1111/j.1365-2486.2008.01690.x
   Jeong SJ, 2011, GLOBAL CHANGE BIOL, V17, P2385, DOI 10.1111/j.1365-2486.2011.02397.x
   Jia WX, 2018, GLOBAL CHANGE BIOL, V24, P4084, DOI 10.1111/gcb.14317
   Jin HX, 2019, INT J BIOMETEOROL, V63, P763, DOI 10.1007/s00484-019-01690-5
   Jolly WM, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023252
   Jönsson P, 2004, COMPUT GEOSCI-UK, V30, P833, DOI 10.1016/j.cageo.2004.05.006
   Keenan TF, 2014, NAT CLIM CHANGE, V4, P598, DOI [10.1038/nclimate2253, 10.1038/NCLIMATE2253]
   Kim Y, 2012, REMOTE SENS ENVIRON, V121, P472, DOI 10.1016/j.rse.2012.02.014
   Kneib T., 2011, A Space-Time Study on Forest Health
   Kong DD, 2019, ISPRS J PHOTOGRAMM, V155, P13, DOI 10.1016/j.isprsjprs.2019.06.014
   Kreyling J, 2010, ECOLOGY, V91, P1939, DOI 10.1890/09-1160.1
   Liu Q, 2018, GLOBAL CHANGE BIOL, V24, P1342, DOI 10.1111/gcb.13954
   Liu Q, 2016, GLOBAL CHANGE BIOL, V22, P3702, DOI 10.1111/gcb.13311
   Liu RG, 2017, REMOTE SENS ENVIRON, V189, P164, DOI 10.1016/j.rse.2016.11.023
   Ma XL, 2015, J GEOPHYS RES-BIOGEO, V120, P2036, DOI 10.1002/2015JG003144
   Matern B., 2013, Spatial Variation
   Melaas EK, 2018, GEOPHYS RES LETT, V45, P2679, DOI 10.1002/2017GL076933
   Melaas EK, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/5/054020
   Myneni RB, 1997, NATURE, V386, P698, DOI 10.1038/386698a0
   Omernik JM, 2014, ENVIRON MANAGE, V54, P1249, DOI 10.1007/s00267-014-0364-1
   Orsenigo S, 2014, PLANT ECOL, V215, P677, DOI 10.1007/s11258-014-0363-6
   Park H, 2018, REMOTE SENS ENVIRON, V217, P191, DOI 10.1016/j.rse.2018.08.012
   Peng SS, 2013, NATURE, V501, P88, DOI 10.1038/nature12434
   Piao S.L., 2019, GLOB CHANG BIOL
   Piao SL, 2008, NATURE, V451, P49, DOI 10.1038/nature06444
   Piao SL, 2017, NAT CLIM CHANGE, V7, P359, DOI [10.1038/nclimate3277, 10.1038/NCLIMATE3277]
   Piao SL, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms7911
   Piao SL, 2006, GLOBAL CHANGE BIOL, V12, P672, DOI 10.1111/j.1365-2486.2006.01123.x
   Qiu T, 2020, REMOTE SENS ENVIRON, V236, DOI 10.1016/j.rse.2019.111477
   Reichstein M, 2007, GLOBAL CHANGE BIOL, V13, P634, DOI 10.1111/j.1365-2486.2006.01224.x
   Richardson AD, 2006, GLOBAL CHANGE BIOL, V12, P1174, DOI 10.1111/j.1365-2486.2006.01164.x
   Richardson AD, 2018, NATURE, V560, P368, DOI 10.1038/s41586-018-0399-1
   Richardson AD, 2013, AGR FOREST METEOROL, V169, P156, DOI 10.1016/j.agrformet.2012.09.012
   Richardson AD, 2010, PHILOS T R SOC B, V365, P3227, DOI 10.1098/rstb.2010.0102
   Sahu SK, 2012, APPL STOCH MODEL BUS, V28, P395, DOI 10.1002/asmb.1951
   Senf C, 2017, REMOTE SENS ENVIRON, V194, P155, DOI 10.1016/j.rse.2017.03.020
   Seyednasrollah B, 2018, REMOTE SENS ENVIRON, V209, P446, DOI 10.1016/j.rse.2018.02.059
   Shen MG, 2015, GLOBAL CHANGE BIOL, V21, P3647, DOI 10.1111/gcb.12961
   Sulla-Menashe D, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa9b88
   THORNTON P., 2017, Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version3
   Thornton PE, 1997, J HYDROL, V190, P214, DOI 10.1016/S0022-1694(96)03128-9
   Wan SQ, 2009, ECOLOGY, V90, P2700, DOI 10.1890/08-2026.1
   Wang JM, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6ad9
   Wang LH, 2018, GLOBAL CHANGE BIOL, V24, P5484, DOI 10.1111/gcb.14369
   White MA, 2009, GLOBAL CHANGE BIOL, V15, P2335, DOI 10.1111/j.1365-2486.2009.01910.x
   Wielgolaski FE, 2001, INT J BIOMETEOROL, V45, P196, DOI 10.1007/s004840100100
   Wolf AA, 2017, P NATL ACAD SCI USA, V114, P3463, DOI 10.1073/pnas.1608357114
   Wu CY, 2018, NAT CLIM CHANGE, V8, P1092, DOI 10.1038/s41558-018-0346-z
   Xie YY, 2015, P NATL ACAD SCI USA, V112, P13585, DOI 10.1073/pnas.1509991112
   Yang YT, 2015, GLOBAL CHANGE BIOL, V21, P652, DOI 10.1111/gcb.12778
   Yu R, 2016, INT J BIOMETEOROL, V60, P335, DOI 10.1007/s00484-015-1031-9
   Zhang C, 2007, PROCEEDINGS OF 2007 INTERNATIONAL WORKSHOP ON SIGNAL DESIGN AND ITS APPLICATIONS IN COMMUNICATIONS, P34
   Zhang XY, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab04d2
   Zhang XY, 2018, REMOTE SENS ENVIRON, V216, P212, DOI 10.1016/j.rse.2018.06.047
   Zhang XY, 2015, REMOTE SENS ENVIRON, V156, P457, DOI 10.1016/j.rse.2014.10.012
   Zhang XY, 2003, REMOTE SENS ENVIRON, V84, P471, DOI 10.1016/S0034-4257(02)00135-9
   Zhao SQ, 2016, P NATL ACAD SCI USA, V113, P6313, DOI 10.1073/pnas.1602312113
NR 100
TC 26
Z9 30
U1 6
U2 95
PU ELSEVIER SCIENCE INC
PI NEW YORK
PA STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA
SN 0034-4257
EI 1879-0704
J9 REMOTE SENS ENVIRON
JI Remote Sens. Environ.
PD SEP 15
PY 2020
VL 247
AR 111956
DI 10.1016/j.rse.2020.111956
PG 23
WC Environmental Sciences; Remote Sensing; Imaging Science & Photographic
   Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Remote Sensing; Imaging Science &
   Photographic Technology
GA ML0TJ
UT WOS:000549189200053
OA Bronze
DA 2025-01-10
ER

PT J
AU Aubin, I
   Boisvert-Marsh, L
   Kebli, H
   McKenney, D
   Pedlar, J
   Lawrence, K
   Hogg, EH
   Boulanger, Y
   Gauthier, S
   Ste-Marie, C
AF Aubin, I.
   Boisvert-Marsh, L.
   Kebli, H.
   McKenney, D.
   Pedlar, J.
   Lawrence, K.
   Hogg, E. H.
   Boulanger, Y.
   Gauthier, S.
   Ste-Marie, C.
TI Tree vulnerability to climate change: improving exposure-based
   assessments using traits as indicators of sensitivity
SO ECOSPHERE
LA English
DT Article
DE adaptation strategies; boreal forest; climate change; drought
   sensitivity; migration capacity; temperate forest; vulnerability
   assessment
ID FUNCTIONAL TRAITS; ADAPTIVE CAPACITY; INTRASPECIFIC VARIABILITY; SPECIES
   VULNERABILITY; DISTRIBUTION MODELS; SOIL PROPERTIES; CANADA FORESTS;
   SEVERE DROUGHT; BOREAL FOREST; NORTH-AMERICA
AB Projected changes in climate conditions vary widely across Canada's 350 M ha of forests, and so does the capacity of forest species to cope with these changes (sensitivity). Development and prioritization of adaptation strategies for sustainable forest management will depend on integrated assessments of relative stand vulnerability. We developed species-specific indices of sensitivity to (1) drought-induced mortality and (2) migration failure, based on traits for 22 of the most abundant tree species in Canada. By combining this information with stand composition data and spatially explicit climate change projections, we were able to map Canadian forest vulnerability to drought and migration failure. Our maps show forest vulnerability changing rapidly under a high carbon emission scenario (RCP 8.5) between short( 2011-2040), medium-(2041-2070), and long-term projections (2071-2100). Several zones of special concern emerged based on the biomass involved, stand sensitivity, and vulnerability trends across time. Boreal forests in the central regions of Alberta and Saskatchewan appeared most vulnerable to drought-induced mortality in the mid to long term. In the short term, distance to suitable habitat is projected to shift quickly along latitudinal gradients, particularly in Central Canada, while zones of vulnerability to migration failure appeared across the Rockies region in the long term as suitable conditions disappear from mountainous areas. This spatial assessment of vulnerability, which integrates species-specific sensitivity, highlights important regional contrasts between vulnerability to drought (from high exposure, high proportion of sensitive species, or both) and to migration failure. By affecting either species' ability to persist in place or to migrate, different climate change impacts can yield distinct biotic responses, with important implications for regional climate change adaptation strategies. Multi-faceted vulnerability assessments, integrating both exposure and sensitivity indices specific to expected impacts of climate change, have the potential to provide crucial information to managers. We discuss some of these implications, explore the current limitations of our approach, and suggest a path forward.
C1 [Aubin, I.; Boisvert-Marsh, L.; Kebli, H.; McKenney, D.; Pedlar, J.; Lawrence, K.] Nat Resources Canada, Canadian Forest Serv, Great Lakes Forestry Ctr, Sault Ste Marie, ON P6A 2E5, Canada.
   [Hogg, E. H.] Nat Resources Canada, Canadian Forest Serv, Northern Forestry Ctr, Edmonton, AB T6H 3S5, Canada.
   [Boulanger, Y.; Gauthier, S.] Nat Resources Canada, Canadian Forest Serv, Laurentian Forestry Ctr, Quebec City, PQ G1V 4C7, Canada.
   [Ste-Marie, C.] Nat Resources Canada, Geol Survey Canada, Ottawa, ON K1A 0E8, Canada.
C3 Natural Resources Canada; Canadian Forest Service; Great Lakes Forestry
   Centre; Natural Resources Canada; Canadian Forest Service; Natural
   Resources Canada; Canadian Forest Service; Natural Resources Canada;
   Lands & Minerals Sector - Natural Resources Canada; Geological Survey of
   Canada
RP Aubin, I (corresponding author), Nat Resources Canada, Canadian Forest Serv, Great Lakes Forestry Ctr, Sault Ste Marie, ON P6A 2E5, Canada.
EM isabelle.aubin@canada.ca
RI Gauthier, Sylvie/J-3923-2019
OI Gauthier, Sylvie/0000-0001-6720-0195; Ste-Marie,
   Catherine/0000-0003-3885-7416; Boisvert-Marsh, Laura/0000-0002-0939-8196
FU Forest Change Initiative (Canadian Forest Service, Natural Resources
   Canada)
FX The authors would like to thank Kevin Good, Sandrine Gautier-Ethier,
   Margot Downey, and Kellina Higgins for assistance in surveying the
   literature and to Francoise Cardou for visual and editorial support. We
   are grateful to Andre Beaudoin, Pierre Bernier, and David Price for
   providing access to the base datasets and for giving advice on their
   utilization. We also thank Ken Baldwin for his expertise on Canadian
   tree species distributions. This work was nourished by the stimulating
   discussions of the Tree Traits and Climate Change workshop held in Mont
   St-Hilaire in April 2013, organized by Isabelle Aubin and Alison D.
   Munson. This work was supported by the Forest Change Initiative
   (Canadian Forest Service, Natural Resources Canada). The authors declare
   no conflict of interest.
CR Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Anderegg WRL, 2016, P NATL ACAD SCI USA, V113, P5024, DOI 10.1073/pnas.1525678113
   Angert AL, 2011, ECOL LETT, V14, P677, DOI 10.1111/j.1461-0248.2011.01620.x
   [Anonymous], 1990, SILVICS N AM
   [Anonymous], 2011, SCANNING CONSERVATIO
   Arora VK, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL046270
   Arora VK, 2005, J GEOPHYS RES-BIOGEO, V110, DOI 10.1029/2005JG000042
   Aubin I, 2016, ENVIRON REV, V24, P164, DOI 10.1139/er-2015-0072
   Aubin I., 2012, TOPIC-Traits of Plants in Canada
   Bansal S, 2015, GLOBAL CHANGE BIOL, V21, P947, DOI 10.1111/gcb.12719
   Beaudoin A, 2014, CAN J FOREST RES, V44, P521, DOI 10.1139/cjfr-2013-0401
   Beguin J, 2017, GEODERMA, V306, P195, DOI 10.1016/j.geoderma.2017.06.016
   Boisvert-Marsh L, 2014, ECOSPHERE, V5, DOI 10.1890/ES14-00111.1
   Boulanger Y, 2017, LANDSCAPE ECOL, V32, P1415, DOI 10.1007/s10980-016-0421-7
   Brandt JP, 2009, ENVIRON REV, V17, P101, DOI 10.1139/A09-004
   Bréda N, 2006, ANN FOREST SCI, V63, P625, DOI 10.1051/forest:2006042
   Bussotti F, 2015, ENVIRON EXP BOT, V111, P91, DOI 10.1016/j.envexpbot.2014.11.006
   Canadian National Vegetation Classification, 2015, VEG ZON CAN IN PRESS
   Case MJ, 2016, CLIMATIC CHANGE, V136, P367, DOI 10.1007/s10584-016-1608-2
   Case MJ, 2015, BIOL CONSERV, V187, P127, DOI 10.1016/j.biocon.2015.04.013
   Chmura DJ, 2011, FOREST ECOL MANAG, V261, P1121, DOI 10.1016/j.foreco.2010.12.040
   Clark JS, 2016, GLOBAL CHANGE BIOL, V22, P2329, DOI 10.1111/gcb.13160
   Coops NC, 2011, ECOL MODEL, V222, P2119, DOI 10.1016/j.ecolmodel.2011.03.033
   Corlett RT, 2013, TRENDS ECOL EVOL, V28, P482, DOI 10.1016/j.tree.2013.04.003
   Dukes JS, 2009, CAN J FOREST RES, V39, P231, DOI 10.1139/X08-171
   Edwards J.E., 2015, CLIMATE CHANGE SUSTA
   Environment Canada, 2016, ENV CLIM CHANG CAN S
   Farrar J.L., 1995, TREES CANADA
   Flannigan MD, 2009, INT J WILDLAND FIRE, V18, P483, DOI 10.1071/WF08187
   Foden WB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0065427
   Franks SJ, 2014, EVOL APPL, V7, P123, DOI 10.1111/eva.12112
   Gallien L, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0152867
   Gallien L, 2010, DIVERS DISTRIB, V16, P331, DOI 10.1111/j.1472-4642.2010.00652.x
   Garcia RA, 2014, J BIOGEOGR, V41, P724, DOI 10.1111/jbi.12257
   Gauthier S, 2015, SCIENCE, V349, P819, DOI 10.1126/science.aaa9092
   Gauthier S, 2014, ENVIRON REV, V22, P256, DOI 10.1139/er-2013-0064
   Gillis MD, 2005, FOREST CHRON, V81, P214, DOI 10.5558/tfc81214-2
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Guisan A, 2013, ECOL LETT, V16, P1424, DOI 10.1111/ele.12189
   Hamann A, 2015, GLOBAL CHANGE BIOL, V21, P997, DOI 10.1111/gcb.12736
   Hof C, 2011, GLOBAL CHANGE BIOL, V17, P2987, DOI 10.1111/j.1365-2486.2011.02418.x
   Hogg EH, 2013, AGR FOREST METEOROL, V178, P173, DOI 10.1016/j.agrformet.2013.04.025
   Hogg EH, 2008, CAN J FOREST RES, V38, P1373, DOI 10.1139/X08-001
   Hogg EH, 1997, AGR FOREST METEOROL, V84, P115, DOI 10.1016/S0168-1923(96)02380-5
   HOGG EH, 1994, CAN J FOREST RES, V24, P1835, DOI 10.1139/x94-237
   Iverson LR, 2008, FOREST ECOL MANAG, V254, P390, DOI 10.1016/j.foreco.2007.07.023
   Iverson LR, 1998, ECOL MONOGR, V68, P465, DOI 10.1890/0012-9615(1998)068[0465:PAOTSF]2.0.CO;2
   Janowiak MK, 2014, J FOREST, V112, P424, DOI 10.5849/jof.13-094
   Jump AS, 2009, TRENDS ECOL EVOL, V24, P694, DOI 10.1016/j.tree.2009.06.007
   Landhäusser SM, 2002, J ECOL, V90, P658, DOI 10.1046/j.1365-2745.2002.00699.x
   Lindner M, 2010, FOREST ECOL MANAG, V259, P698, DOI 10.1016/j.foreco.2009.09.023
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Maherali H, 2004, ECOLOGY, V85, P2184, DOI 10.1890/02-0538
   Mansuy N, 2014, GEODERMA, V235, P59, DOI 10.1016/j.geoderma.2014.06.032
   Markewitz D, 2010, NEW PHYTOL, V187, P592, DOI 10.1111/j.1469-8137.2010.03391.x
   Marris E., 2007, NATURE REPORTS, V1, P94, DOI [10.1038/climate.2007.70, DOI 10.1038/CLIMATE.2007.70]
   McKenney D, 2009, FOREST CHRON, V85, P258, DOI 10.5558/tfc85258-2
   McKenney D, 2013, FOREST CHRON, V89, P659, DOI 10.5558/tfc2013-118
   Mckenney DW, 2007, BIOSCIENCE, V57, P939, DOI 10.1641/B571106
   McKenney DW, 2011, B AM METEOROL SOC, V92, P1611, DOI 10.1175/2011BAMS3132.1
   McKenney DW, 2011, GLOBAL CHANGE BIOL, V17, P2720, DOI 10.1111/j.1365-2486.2011.02413.x
   Michaelian M, 2011, GLOBAL CHANGE BIOL, V17, P2084, DOI 10.1111/j.1365-2486.2010.02357.x
   Michalak JL, 2017, FRONT ECOL ENVIRON, V15, P367, DOI 10.1002/fee.1516
   Munier A, 2010, PLANT ECOL, V210, P19, DOI 10.1007/s11258-010-9724-y
   Nadeau CP, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00069.1
   Nadeau S, 2015, AM J BOT, V102, P1342, DOI 10.3732/ajb.1500160
   Nagel LM, 2017, J FOREST, V115, P167, DOI 10.5849/jof.16-039
   National Forest Inventory, 2006, CAN NAT FOR INV
   Pacifici M, 2015, NAT CLIM CHANGE, V5, P215, DOI 10.1038/NCLIMATE2448
   Pannell JR, 1998, EVOLUTION, V52, P657, DOI [10.2307/2411261, 10.1111/j.1558-5646.1998.tb03691.x]
   Pedlar JH, 2017, SCI REP-UK, V7, DOI 10.1038/srep43881
   Pedlar JH, 2012, BIOSCIENCE, V62, P835, DOI 10.1525/bio.2012.62.9.10
   Pérez-Harguindeguy N, 2013, AUST J BOT, V61, P167, DOI 10.1071/BT12225
   Perie C, 2014, MEMOIRE RECHERCHE FO
   Perie C., 2009, ATLAS INTERACTIF CHA
   Périé C, 2016, PEERJ, V4, DOI 10.7717/peerj.2218
   Portier J, 2016, FORESTS, V7, DOI 10.3390/f7100211
   Potter KM, 2017, NEW FOREST, V48, P275, DOI 10.1007/s11056-017-9569-5
   Prieto I, 2017, AM J BOT, V104, P62, DOI 10.3732/ajb.1600354
   Rehfeldt GE, 2001, CLIMATIC CHANGE, V50, P355, DOI 10.1023/A:1010614216256
   Rogers BM, 2017, GLOBAL CHANGE BIOL, V23, P3302, DOI 10.1111/gcb.13585
   Sanchez-Salguero R, 2017, GLOBAL CHANGE BIOL, V23, P2705, DOI 10.1111/gcb.13541
   Sanford T, 2014, NAT CLIM CHANGE, V4, P164, DOI 10.1038/nclimate2148
   Schaberg PG, 2011, FOREST ECOL MANAG, V262, P2142, DOI 10.1016/j.foreco.2011.08.004
   Scheller RM, 2007, ECOL MODEL, V201, P409, DOI 10.1016/j.ecolmodel.2006.10.009
   Sgrò CM, 2011, EVOL APPL, V4, P326, DOI 10.1111/j.1752-4571.2010.00157.x
   Sides CB, 2014, AM J BOT, V101, P56, DOI 10.3732/ajb.1300284
   Sittaro F, 2017, GLOBAL CHANGE BIOL, V23, P3292, DOI 10.1111/gcb.13622
   Stahl U, 2014, P NATL ACAD SCI USA, V111, P13739, DOI 10.1073/pnas.1300673111
   Stevens-Rumann CS, 2018, ECOL LETT, V21, P243, DOI 10.1111/ele.12889
   Talluto MV, 2016, GLOBAL ECOL BIOGEOGR, V25, P238, DOI 10.1111/geb.12395
   Urban MC, 2016, SCIENCE, V353, P1113, DOI 10.1126/science.aad8466
   van Mantgem PJ, 2009, SCIENCE, V323, P521, DOI 10.1126/science.1165000
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P95, DOI 10.1007/s10584-011-0152-3
   Violle C, 2007, OIKOS, V116, P882, DOI 10.1111/j.2007.0030-1299.15559.x
   Violle C, 2014, P NATL ACAD SCI USA, V111, P13690, DOI 10.1073/pnas.1415442111
   Violle C, 2012, TRENDS ECOL EVOL, V27, P244, DOI 10.1016/j.tree.2011.11.014
   Vittoz P, 2007, BOT HELV, V117, P109, DOI 10.1007/s00035-007-0797-8
   Wang TL, 2016, FOREST ECOL MANAG, V360, P357, DOI 10.1016/j.foreco.2015.08.004
   Webster MS, 2017, TRENDS ECOL EVOL, V32, P167, DOI 10.1016/j.tree.2016.12.007
   Willis SG, 2015, BIOL CONSERV, V190, P167, DOI 10.1016/j.biocon.2015.05.001
   Wright JP, 2016, PHILOS T R SOC B, V371, DOI 10.1098/rstb.2015.0272
   Zolkos SG, 2015, ECOSYSTEMS, V18, P202, DOI 10.1007/s10021-014-9822-0
NR 105
TC 66
Z9 67
U1 6
U2 47
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2150-8925
J9 ECOSPHERE
JI Ecosphere
PD FEB
PY 2018
VL 9
IS 2
AR e02108
DI 10.1002/ecs2.2108
PG 24
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA FY8CT
UT WOS:000427091200007
OA gold
DA 2025-01-10
ER

PT J
AU Kelkar, U
   Narula, KK
   Sharma, VP
   Chandna, U
AF Kelkar, Ulka
   Narula, Kapil Kumar
   Sharma, Ved Prakash
   Chandna, Usha
TI Vulnerability and adaptation to climate variability and water stress in
   Uttarakhand State, India
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article; Proceedings Paper
CT Conference on Local Evidence on Vulnerabilities and Adaptations to
   Global Environmental Change
CY MAY 03-21, 2004
CL IIASA, Laxenburg, AUSTRIA
SP START, IHDP
HO IIASA
DE Climate change; Water stress; Agriculture
AB This paper presents a participatory approach to investigate vulnerability and adaptive capacity to climate variability and water stress in the Lakhwar watershed in Uttarakhand State, India. Highly water stressed microwatersheds were identified by modelling surface runoff, soil moisture development, lateral runoff, and groundwater recharge. The modelling results were shared with communities in two villages, and timeline exercises were carried out to allow them to trace past developments that have impacted their lives and livelihoods, and stimulate discussion about future changes and possible adaptation interventions. (C) 2008 Elsevier Ltd. All rights reserved.
C1 [Kelkar, Ulka] TERI, Bangalore 560071, Karnataka, India.
   [Narula, Kapil Kumar; Sharma, Ved Prakash; Chandna, Usha] TERI, India Habitat Ctr, New Delhi 110003, India.
RP Kelkar, U (corresponding author), TERI, 4th Main,2nd Cross,Domlur 2nd Stage, Bangalore 560071, Karnataka, India.
EM ulkak@teri.res.in
CR AGRAWAL R, 2002, 17 S INT FARM SYST A
   [Anonymous], 1999, Development as Freedom
   [Anonymous], 1992, CROPS WEATHER
   [Anonymous], 2003, P NATL ACAD SCI
   [Anonymous], 2007, CLIM CHANG IMP AD VU
   [Anonymous], 2005, WAT DAT BOOK
   BASU S, 1993, NAT WORKSH STAT TRIB
   BOHLE HG, 1994, GLOBAL ENVIRON CHANG, V4, P37, DOI 10.1016/0959-3780(94)90020-5
   CHOPRA R, 2002, ARE EMPTY THALIS UTT
   Dangwal D. D., 2005, CONSERV SOC, V3, P110
   Evans K., 2006, Field guide to the Future: Four Ways for Communities to Think Ahead
   *FSI, 2008, STAT FOR REP 2005
   *GOV UTT, 2004, DRAFT WAT POL UTT
   Kasemir B., 2003, PUBLIC PARTICIPATION
   Ligia Noronha Ligia Noronha, 2003, Environmental threats, vulnerability and adaptation: case studies from India, P31
   MAJUMDAR DN, 1962, HIMALAYAN POLYANDRY, P389
   McDonald MG, 1988, US GEOLOGICAL SURVEY, V6, P586
   Narain V., 2003, Institutions, Technology and Water Control: Water users associations and irrigation management reform in two large scale systems in India
   NARULA K, 2003, TERI, P55
   Neitsch S., 2002, Soil and Water Assessment Tool (SWAT)
   OBRIEN K, 2004, GLOBAL ENVIRON CHANG, V10, P221
   *PSI, 2003, SURV LESS HIM JAL SA
   Sati VishwambharPrasad., 2005, Journal of Mountain Science, V2, P76, DOI [10.1007/s11629-005-0076-3, DOI 10.1007/S11629-005-0076-3]
   Schroter D., 2005, Mitigation and Adaptation Strategies for Global Change, V10, P573, DOI 10.1007/s11027-005-6135-9
   Sen A.K., 1981, POVERTY FAMINES
   Tyler Stephen., 2006, COMMUNITIES LIVELIHO
   *WAT MAN DIR UTT, 2004, SUCC STOR
NR 27
TC 84
Z9 94
U1 1
U2 31
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD OCT
PY 2008
VL 18
IS 4
BP 564
EP 574
DI 10.1016/j.gloenvcha.2008.09.003
PG 11
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Environmental Sciences & Ecology; Geography
GA 387ZF
UT WOS:000261989400004
DA 2025-01-10
ER

PT J
AU Anisimov, OA
   Zhil'tsova, EL
   Shapovalova, KO
   Ershova, AA
AF Anisimov, O. A.
   Zhil'tsova, E. L.
   Shapovalova, K. O.
   Ershova, A. A.
TI Analysis of Climate Change Indicators. Part 1. Eastern Siberia
SO RUSSIAN METEOROLOGY AND HYDROLOGY
LA English
DT Article
DE Climate change; Eastern Siberia; climate indicators; public perception;
   adaptation
AB Data on modern climate and environmental changes in Eastern Siberia are compared with the public perception of such changes through cognitive indicators. Observations reveal positive air temperature trends for all seasons, shortening of the cold period, decrease in wintertime daily temperature variations, deeper seasonal thawing of permafrost, and lengthening of the vegetation period. The public perception acknowledges these changes only partly, although they already affect many types of human's activity. The gap between observational data and the cognitive indicators of climate change complicates the development and implementation of climate adaptation strategies.
C1 [Anisimov, O. A.; Zhil'tsova, E. L.; Shapovalova, K. O.; Ershova, A. A.] State Hydrol Inst, Vtoraya Liniya 23, St Petersburg 199053, Russia.
RP Anisimov, OA (corresponding author), State Hydrol Inst, Vtoraya Liniya 23, St Petersburg 199053, Russia.
EM oleg@oa7661.spb.edu
RI Zh., Elena/ABC-6540-2021; Anisimov, Oleg/D-8052-2017; Ershova,
   Alexandra/E-4198-2014
OI Anisimov, Oleg/0000-0002-9515-4576; Ershova,
   Anastasia/0009-0006-6545-3635; Zh., Elena L./0000-0003-4587-6703;
   Ershova, Alexandra/0000-0003-3634-7009
FU Russian Foundation for Basic Research [18-05-60005]
FX The research was supported by the Russian Foundation for Basic Research
   (grant 18-05-60005).
CR Anisimov O A, 2017, KRIOSFERA ZEMLI
   Anisimov O. A., 2015, ISSLEDOVANIYA ZEMLI
   Anisimov O A, 2017, GEOGRAPH REV
   Anisimov O. A., 2017, LED SNEG
   Anisimov O, 2019, AMBIO, V48, P661, DOI 10.1007/s13280-018-1096-x
   [Anonymous], 2013, CLIM CHANG 2013 PHYS
   [Anonymous], 2019, REPORT CLIMATE FEATU
   [Anonymous], 2014, The Second Roshydromet Assessment Report on the Climate Change and Its Consequences in the Russian Federation
   Kokorev V. A., PERMAFROST WEB PORTA
   Revich B A, 2018, GIGIENA SANITARIYA
   Zhil'tsova E L, 2015, ARKTIKA 21 VEK
NR 11
TC 3
Z9 3
U1 0
U2 12
PU PLEIADES PUBLISHING INC
PI MOSCOW
PA PLEIADES PUBLISHING INC, MOSCOW, 00000, RUSSIA
SN 1068-3739
EI 1934-8096
J9 RUSS METEOROL HYDRO+
JI Russ. Meteorol. Hydrol.
PD DEC
PY 2019
VL 44
IS 12
BP 810
EP 817
DI 10.3103/S1068373919120033
PG 8
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA KI9RI
UT WOS:000511694800003
DA 2025-01-10
ER

PT J
AU Pérez-Fargallo, A
   Rubio-Bellido, C
   Pulido-Arcas, JA
   Gallego-Maya, I
   Guevara-García, FJ
AF Perez-Fargallo, Alexis
   Rubio-Bellido, Carlos
   Pulido-Arcas, Jesus A.
   Gallego-Maya, Inmaculada
   Javier Guevara-Garcia, Fco.
TI Influence of Adaptive Comfort Models on Energy Improvement for Housing
   in Cold Areas
SO SUSTAINABILITY
LA English
DT Article
DE climate adaptation; social housing; thermal comfort; adaptive comfort
ID THERMAL COMFORT; RESIDENTIAL BUILDINGS; CLIMATE; POVERTY; ZERO
AB The evaluation of construction standards using adaptive thermal comfort models has a great impact on energy consumption. The analysis of a user's climate adaptation must be one of the first steps in the search for nearly/net Zero Energy Buildings (nZEB). The goal of this work is to analyze the standards recommended by the Chile's Construction with Sustainability Criteria for the building of housing, applying the ASHRAE 55-2017 and EN 15251: 2007 adaptive comfort models in social housing. The study produces concrete recommendations associated with construction strategies, to increase the number of hours the user finds themselves with acceptable thermal comfort levels, without repercussions for energy consumption. Sixteen parametric series were evaluated with a dynamic simulation of the most common prototype of social housing in the Bio-Bio Region. The study shows that thermal comfort conditions can be increased through a combination of improvement measures compared to the ECCS standard (Construction Standards with Sustainability Criteria): 27.52% in the case of applying EN 15251: 2007 and 24.04% in the case of ASHRAE 55-2017.
C1 [Perez-Fargallo, Alexis; Pulido-Arcas, Jesus A.] Univ Bio Bio, Dept Bldg Sci, Concepcion 4030000, Chile.
   [Rubio-Bellido, Carlos; Gallego-Maya, Inmaculada; Javier Guevara-Garcia, Fco.] Univ Seville, Dept Bldg Construct 2, E-41012 Seville, Spain.
C3 Universidad del Bio-Bio; University of Sevilla
RP Rubio-Bellido, C (corresponding author), Univ Seville, Dept Bldg Construct 2, E-41012 Seville, Spain.
EM aperezf@ubiobio.cl; carlosrubio@us.es; jpulido@ubiobio.cl;
   gallego_inma@hotmail.com; guevara@us.es
RI GUEVARA GARCIA, FRANCISCO JAVIER/M-3942-2014; Pulido Arcas, Jesus
   Alberto/T-2129-2017; Rubio-Bellido, Carlos/K-1861-2014; Perez Fargallo,
   Alexis/K-1975-2014
OI GUEVARA GARCIA, FRANCISCO JAVIER/0000-0001-7062-1257; Gallego Maya,
   Inmaculada/0000-0002-4374-9447; Pulido Arcas, Jesus
   Alberto/0000-0002-7956-2203; Rubio-Bellido, Carlos/0000-0001-6719-8793;
   Perez Fargallo, Alexis/0000-0001-7071-7523
FU FONDECYT [3160806]; National Science and Technology Research Commission
   (CONICYT); VI PPIT-US
FX This work forms part of the FONDECYT 3160806 research project, "Study of
   the viable energy improvement standard for social housing in a situation
   of energy poverty via the evaluation of post-occupational adaptive
   comfort and its progressive implementation", financed by the National
   Science and Technology Research Commission (CONICYT). The authors Alexis
   Perez-Fargallo and Carlos Rubio-Bellido would like to acknowledge the VI
   PPIT-US for support this research and internationalization.
CR [Anonymous], WORLD EN OUTL 2013
   [Anonymous], 2013, ASHRAE
   Attia S, 2015, ENERG BUILDINGS, V102, P117, DOI 10.1016/j.enbuild.2015.05.017
   Burattini C, 2015, SUSTAINABILITY-BASEL, V7, P10428, DOI 10.3390/su70810428
   Bustamante W., 2009, Camino al Bicentenario - Propuestas para Chile, P253, DOI [10.1007/s13398-014-0173-7.2, DOI 10.1007/S13398-014-0173-7.2]
   Citec U.B.B., 2012, MANUAL HERMETICIDAD
   Comite Europeen de Normalisation (CEN), 2007, 152172007 EN CEN
   Comite Europeen de Normalisation (CEN), 2008, 156032008 EN CEN
   Comite Europeen de Normalisation (CEN), 2007, 152512007 EN CEN
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Figueroa R., 2013, P PLEA2013 29 C SUST, P6
   Humphreys MA, 2013, BUILD ENVIRON, V63, P40, DOI 10.1016/j.buildenv.2013.01.024
   Kunkel S., 2015, INDOOR AIR QUALITY T
   Ministry of Housing and Urbanism of Chile (MINVU), COD CONSTR SUST
   Ministry of Housing and Urbanism of Chile (MINVU), 2011, VIV MOD CONSTR SIT P
   Ministry of Housing and Urbanism of Chile (MINVU), EST HIST
   Ministry of Housing and Urbanism of Chile (MINVU), 2011, 01 DS MINVU
   Ministry of Housing and Urbanism of Chile (MINVU), 2011, 49 DS MINVU
   Nicol F, 2007, ENERG BUILDINGS, V39, P737, DOI 10.1016/j.enbuild.2007.02.001
   Nicol JF, 2002, ENERG BUILDINGS, V34, P563, DOI 10.1016/S0378-7788(02)00006-3
   Oropeza-Perez I, 2017, ENERG BUILDINGS, V145, P251, DOI 10.1016/j.enbuild.2017.04.031
   Peacock AD, 2010, ENERG POLICY, V38, P3277, DOI 10.1016/j.enpol.2010.01.021
   Fargallo AP, 2016, INF CONSTR, V68, DOI 10.3989/ic.15.048
   Programa de Estudios e Investigaciones en Energia (PRIEN), EST POT AH EN MED ME
   Salata F, 2017, ENERG CONVERS MANAGE, V138, P61, DOI 10.1016/j.enconman.2017.01.062
   Santamouris M, 2016, SOL ENERGY, V128, P61, DOI 10.1016/j.solener.2016.01.021
   Thomson H, 2013, ENERG POLICY, V52, P563, DOI 10.1016/j.enpol.2012.10.009
   UNEP, 2012, BUILD DES CONSTR FOR
   Ureta-Gragera, 2015, HABITAT SUST, V5, P33
   US Department of Energy, 2010, EN PLUS ENG REF REF
   van Hooff T, 2015, BUILD ENVIRON, V83, P142, DOI 10.1016/j.buildenv.2014.10.006
NR 31
TC 9
Z9 10
U1 1
U2 24
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD MAR
PY 2018
VL 10
IS 3
AR 859
DI 10.3390/su10030859
PG 15
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA GA8DA
UT WOS:000428567100286
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Preston, BL
   Dow, K
   Berkhout, F
AF Preston, Benjamin L.
   Dow, Kirstin
   Berkhout, Frans
TI The Climate Adaptation Frontier
SO SUSTAINABILITY
LA English
DT Article
DE climate change; adaptation; limits; sustainability; adaptive capacity;
   resilience
ID SAFE OPERATING SPACE; ADAPTIVE GOVERNANCE; CHANGE IMPACTS;
   VULNERABILITY; THRESHOLDS; RESILIENCE; CAPACITY; WORKING; TIME;
   MANAGEMENT
AB Climate adaptation has emerged as a mainstream risk management strategy for assisting in maintaining socio-ecological systems within the boundaries of a safe operating space. Yet, there are limits to the ability of systems to adapt. Here, we introduce the concept of an. adaptation frontier., which is defined as a socio-ecological system's transitional adaptive operating space between safe and unsafe domains. A number of driving forces are responsible for determining the sustainability of systems on the frontier. These include path dependence, adaptation/development deficits, values conflicts and discounting of future loss and damage. The cumulative implications of these driving forces are highly uncertain. Nevertheless, the fact that a broad range of systems already persist at the edge of their frontiers suggests a high likelihood that some limits will eventually be exceeded. The resulting system transformation is likely to manifest as anticipatory modification of management objectives or loss and damage. These outcomes vary significantly with respect to their ethical implications. Successful navigation of the adaptation frontier will necessitate new paradigms of risk governance to elicit knowledge that encourages reflexive reevaluation of societal values that enable or constrain sustainability.
C1 [Preston, Benjamin L.] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA.
   [Preston, Benjamin L.] Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37831 USA.
   [Dow, Kirstin] Univ S Carolina, Dept Geog, Columbia, SC 29208 USA.
   [Berkhout, Frans] Vrije Univ Amsterdam, Inst Environm Studies, NL-1081 HV Amsterdam, Netherlands.
C3 United States Department of Energy (DOE); Oak Ridge National Laboratory;
   United States Department of Energy (DOE); Oak Ridge National Laboratory;
   University of South Carolina System; University of South Carolina
   Columbia; Vrije Universiteit Amsterdam
RP Preston, BL (corresponding author), Oak Ridge Natl Lab, Div Environm Sci, POB 2008,MS 6301, Oak Ridge, TN 37831 USA.
EM prestonbl@ornl.gov; kdow@sc.edu; frans.berkhout@vu.nl
RI Preston, Benjamin/B-9001-2012; Berkhout, Frans/N-4196-2013
OI Preston, Benjamin/0000-0002-7966-2386; Berkhout,
   Frans/0000-0001-8668-0470
FU Oak Ridge National Laboratory's (ORNL) Laboratory Directed Research and
   Development Program; US Department of Energy [DE-AC05-00OR22725]
FX The lead author's contributions to this research were sponsored through
   Oak Ridge National Laboratory's (ORNL) Laboratory Directed Research and
   Development Program. ORNL is managed by UT-Battelle, LLC, for the US
   Department of Energy under contract DE-AC05-00OR22725. The author
   acknowledges the assistance of Megan Maloney in the analysis of some of
   the data sources reported in this paper, as well as conversations with
   Mozaharul Alam, Richard Klein, Guy Midgley and Rebecca Shaw that
   informed this paper's discussion of limits to adaptation.
CR Adaptation Fund Board, 2012, AFBEFC87
   Adger W.N., 2006, CLIMATE CHANGE 2007, P717
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   AINSLIE G, 1975, PSYCHOL BULL, V82, P463, DOI 10.1037/h0076860
   Ainslie G., 2001, BREAKDOWN WILL
   Akçakaya HR, 2006, GLOBAL CHANGE BIOL, V12, P2037, DOI 10.1111/j.1365-2486.2006.01253.x
   [Anonymous], INFR 2011 STRAT PRIO
   [Anonymous], 2005, Journal of Environmental Policy Planning, DOI DOI 10.1080/15239080500251908
   [Anonymous], 2012, Inclusive Wealth Report 2012: Measuring progress toward sustainability
   [Anonymous], 2008, 13 YAL SCH FOR ENV S
   [Anonymous], 2009, ASSESSING COSTS ADAP
   [Anonymous], 2006, EC CLIMATE CHANGE ST, DOI DOI 10.1378/CHEST.128.5
   [Anonymous], 2005, MILL DEV GOALS REP
   [Anonymous], 2008, ADAPTATION LEGAL DUT
   [Anonymous], 1948, United Nations General Assembly Resolution 194
   [Anonymous], 2007, Climate Change 2007: A Synthesis Report, P22
   [Anonymous], 2012, LOSS DAMAGE DUE CLIM
   [Anonymous], 2008, Risk Governance. Coping with Uncertainty in a Complex World
   [Anonymous], MILL DEV GOALS 2012
   [Anonymous], RES DICT
   [Anonymous], CLIMATE CHANGE SOCIA
   [Anonymous], 2005, POLICY OPTIONS
   [Anonymous], 1992, CONV BIOL DIV
   Armour KC, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL045850
   Bardsley DK, 2010, POPUL ENVIRON, V32, P238, DOI 10.1007/s11111-010-0126-9
   Barnett J, 2007, POLIT GEOGR, V26, P639, DOI 10.1016/j.polgeo.2007.03.003
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bierwagen BG, 2010, P NATL ACAD SCI USA, V107, P20887, DOI 10.1073/pnas.1002096107
   BODEN TA, 2010, GLOBAL CO2 EMISSIONS
   Bouwer L.M., 2011, B AM METEOROL SOC, V92, P46
   Brandt JP, 2009, ENVIRON REV, V17, P101, DOI 10.1139/A09-004
   Briske DD, 2010, ECOL SOC, V15
   Brunner R., 2010, ADAPTIVE GOVERNANCE, P404
   Brunner R. D., 2005, ADAPTIVE GOVERNANCE
   Burton I, 2004, IDS BULL-I DEV STUD, V35, P31, DOI 10.1111/j.1759-5436.2004.tb00131.x
   Burton I., 2004, 1 MET SERV CAN AD IM
   Burton I., 2009, Earthscan Reader on Adaptation to Climate Change, eds, P89
   Burton P., 2013, URBAN POL R IN PRESS
   Campbell-Lendrum D, 2007, B WORLD HEALTH ORGAN, V85, P235, DOI 10.2471/BLT.06.039503
   CARTER T, 2007, FUTURE CLIMATIC WIND
   Chameides B., 2012, SCI AM
   Changnon S.A., 2001, NAT HAZARDS REV, V2, P113, DOI [10.1061/(asce)1527-6988(2001)2:3(113), DOI 10.1061/(ASCE)1527-6988(2001)2:3(113).]
   Changnon SA, 2000, SCIENCE, V289, P2053, DOI 10.1126/science.289.5487.2053
   Changnon SA, 2003, NAT HAZARDS, V29, P273, DOI 10.1023/A:1023642131794
   Changnon SA, 1998, NAT HAZARDS, V18, P287, DOI 10.1023/A:1026475006301
   Chhetri NB, 2010, ANN ASSOC AM GEOGR, V100, P894, DOI 10.1080/00045608.2010.500547
   Christensen L, 2012, ECOL SOC, V17, DOI 10.5751/ES-04499-170105
   Clark T.W., 2002, POLICY PROCESS PRACT, P215
   Cutter S.L., 2005, EOS, Transaction, American Geophysical Union, V86, P381, DOI [DOI 10.1029/2005EO410001, 10.1029/2005EO410001]
   Cutter S.L., 2005, EOS, Transaction, American Geophysical Union, V86, P388, DOI [10.1029/2005EO410001, DOI 10.1029/2005EO410001]
   Dedekorkut A, 2010, AUST PLAN, V47, P203, DOI 10.1080/07293682.2010.508206
   Dessai S, 2004, CLIM POLICY, V4, P107
   Di Baldassarre G, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL045467
   Diffenbaugh NS, 2007, P NATL ACAD SCI USA, V104, P20195, DOI 10.1073/pnas.0706680105
   Dow K., 2013, NATURE CLIM IN PRESS
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Folke C., 2002, Navigating Social-Ecological Systems: Building Resilience for Complexity and Change
   Fordham DA, 2012, GLOBAL CHANGE BIOL, V18, P1357, DOI 10.1111/j.1365-2486.2011.02614.x
   Foster P, 2001, EARTH-SCI REV, V55, P73, DOI 10.1016/S0012-8252(01)00056-3
   Frederick S, 2002, J ECON LIT, V40, P351, DOI 10.1257/002205102320161311
   Friedlingstein P, 2005, P NATL ACAD SCI USA, V102, P10832, DOI 10.1073/pnas.0504755102
   Friedlingstein P, 2010, NAT GEOSCI, V3, P811, DOI 10.1038/ngeo1022
   Fung F, 2011, PHILOS T R SOC A, V369, P99, DOI 10.1098/rsta.2010.0293
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Grasso M, 2010, GLOBAL ENVIRON CHANG, V20, P74, DOI 10.1016/j.gloenvcha.2009.10.006
   Haddad BM, 2005, GLOBAL ENVIRON CHANG, V15, P165, DOI 10.1016/j.gloenvcha.2004.10.002
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Hare B, 2006, CLIMATIC CHANGE, V75, P111, DOI 10.1007/s10584-005-9027-9
   Heal G, 2009, CLIMATIC CHANGE, V96, P275, DOI 10.1007/s10584-009-9641-z
   Hegerl GC, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P663
   Helmer M, 2006, DISASTERS, V30, P1, DOI 10.1111/j.1467-9523.2006.00302.x
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   Hoegh-Guldberg O, 2007, SCIENCE, V318, P1737, DOI 10.1126/science.1152509
   Howden S.M., 2005, P GREENH 2005 C MELB
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Keeling CD, 2005, ECOL STU AN, V177, P83
   Leary N, 2009, CLIM RES, V40, P121, DOI 10.3354/cr00832
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Libecap G.D., 2010, I PATH DEPENDENCE CL, P1
   Lobell DB, 2006, AGR FOREST METEOROL, V141, P208, DOI 10.1016/j.agrformet.2006.10.006
   Loewenstein G, 2008, ANNU REV PSYCHOL, V59, P647, DOI 10.1146/annurev.psych.59.103006.093710
   Lynch AH, 2008, B AM METEOROL SOC, V89, P169, DOI 10.1175/BAMS-89-2-169
   Mastrandrea MD, 2004, SCIENCE, V304, P571, DOI 10.1126/science.1094147
   McClure SM, 2007, J NEUROSCI, V27, P5796, DOI 10.1523/JNEUROSCI.4246-06.2007
   McClure SM, 2004, SCIENCE, V306, P503, DOI 10.1126/science.1100907
   McGray H., 2007, Weathering the Storm: Options for Framing Adaptation and Development
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Meinshausen M, 2009, NATURE, V458, P1158, DOI 10.1038/nature08017
   Meze-Hausken E, 2008, CLIMATIC CHANGE, V89, P299, DOI 10.1007/s10584-007-9392-7
   Morgan M.G., 1999, CLIMATIC CHANGE, V41, P1573
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Munich R, 2011, Natural catastrophes 2010: analyses, assessments, positions
   Nakicenovic N., 2000, Special report on emissions scenarios. a 149 special report of working group III of the intergovernmental panel on climate change, P599
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Nelson R, 2008, ENVIRON SCI POLICY, V11, P588, DOI 10.1016/j.envsci.2008.06.005
   New South Wales, 2012, COAST PROT AM BILL 2
   Newell RG, 2004, ENERG POLICY, V32, P519, DOI 10.1016/S0301-4215(03)00153-8
   Nidumolu UB, 2012, CLIM RES, V51, P249, DOI 10.3354/cr01075
   NOAA (National Oceanographic and Atmospheric Administration), SPAT TRENDS COAST SO
   O'Brien KL, 2010, WIRES CLIM CHANGE, V1, P232, DOI 10.1002/wcc.30
   O'Brien KL, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P164
   O'Neill SJ, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014018
   Office of Management and Budget (OMB), 1994, A94 WHIT HOUS OFF MA
   Park SE, 2012, GLOBAL ENVIRON CHANG, V22, P115, DOI 10.1016/j.gloenvcha.2011.10.003
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P20
   Peng SB, 2004, P NATL ACAD SCI USA, V101, P9971, DOI 10.1073/pnas.0403720101
   Petherick A, 2012, NAT CLIM CHANGE, V2, P228, DOI 10.1038/nclimate1472
   Pielke R. A., 2008, Nat. hazards Rev, V9, P29, DOI [10.1061/(asce)1527-6988(2008)9:1(29), DOI 10.1061/(ASCE)1527-6988(2008)9:1(29), 10.1061/(ASCE)1527-6988(2008)9:1(29)]
   Pielke RA, 2007, PHILOS T R SOC A, V365, P2717, DOI 10.1098/rsta.2007.2086
   Pielke R, 2007, NATURE, V445, P597, DOI 10.1038/445597a
   Preston B., 2010, Managing climate change: papers from the GREENHOUSE 2009 Conference, P185
   Preston B.L., 2013, GLOBAL ENV IN PRESS
   Productivity Commission, 2011, 55 PROD COMM
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Ragen TJ, 2008, ECOL APPL, V18, pS166, DOI 10.1890/06-0734.1
   Renn O., 2012, RISK SOCIAL THEORY E, P59
   Riegl BM, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0024802
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Saavedra C, 2009, HABITAT INT, V33, P246, DOI 10.1016/j.habitatint.2008.10.004
   Schilling E.G., 2009, Acceptance sampling in quality control (2009), V2nd, P1
   Sheehan P, 2008, GLOBAL ENVIRON CHANG, V18, P380, DOI 10.1016/j.gloenvcha.2008.04.008
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Smith MS, 2011, PHILOS T R SOC A, V369, P196, DOI 10.1098/rsta.2010.0277
   Spash CL, 2007, ECOL ECON, V63, P706, DOI 10.1016/j.ecolecon.2007.05.017
   Thomsen DC, 2012, ECOL SOC, V17, DOI 10.5751/ES-04953-170320
   Thornton PK, 2011, PHILOS T R SOC A, V369, P117, DOI 10.1098/rsta.2010.0246
   Tompkins EL, 2012, GLOBAL ENVIRON CHANG, V22, P3, DOI 10.1016/j.gloenvcha.2011.09.010
   Trenberth KE, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P235
   UNEP (United Nations Environment Programme), 2011, PRACT FRAM PLANN PRO, P143
   van Vliet J, 2012, CLIMATIC CHANGE, V113, P551, DOI 10.1007/s10584-012-0458-9
   Wetherald RT, 2001, GEOPHYS RES LETT, V28, P1535, DOI 10.1029/2000GL011786
   Wheaton E., 1999, Mitigation and Adaptation Strategies for Global Change, V4, P215, DOI DOI 10.1023/A:1009660700150
   Wigley TML, 2005, SCIENCE, V307, P1766, DOI 10.1126/science.1103934
   Wittmann M, 2007, EXP BRAIN RES, V179, P643, DOI 10.1007/s00221-006-0822-y
   Xu LJ, 2009, BRAIN RES, V1261, P65, DOI 10.1016/j.brainres.2008.12.061
   Yohe G, 2002, GLOBAL ENVIRON CHANG, V12, P25, DOI 10.1016/S0959-3780(01)00026-7
   Yohe GW, 2003, CLIMATIC CHANGE, V56, P235, DOI 10.1023/A:1021723530541
   Yuen E, 2013, MITIG ADAPT STRAT GL, V18, P567, DOI 10.1007/s11027-012-9376-4
NR 139
TC 62
Z9 67
U1 1
U2 57
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD MAR
PY 2013
VL 5
IS 3
BP 1011
EP 1035
DI 10.3390/su5031011
PG 25
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 213HW
UT WOS:000324047700011
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Burt, Z
   Leal, S
   Workman, J
   McElroy, M
   Bouhia, H
AF Burt, Zachary
   Leal, Susan
   Workman, James
   McElroy, Michael
   Bouhia, Hynd
TI The design of climate-adaptive water subsidies: financial incentives for
   urban water conservation in Morocco
SO JOURNAL OF WATER SANITATION AND HYGIENE FOR DEVELOPMENT
LA English
DT Article
DE climate adaptation; conservation-oriented pricing; demand management;
   MENA; subsidized water services; utility policy
AB In a 500-household pilot, we tested an innovative approach to water demand management, implemented in collaboration with a water utility in a large city in the Middle East and North Africa (MENA) region. We provided a novel intervention, called a Water Savings Credit (WSC), which granted participants volumetric rebates on their water bills for their reductions in water consumption. WSCs were effective at encouraging conservation in our pilot in Marrakech. Our approach has the benefits of a price incentive, without the political risk of a tariff increase. For urban water utilities that provide highly subsidized services, this approach could ultimately pay for itself, or potentially result in net financial savings. Our approach may be especially effective in the countries of the MENA region, as the region has a high rate of subsidization for water services, and because it is facing increasing water scarcity from economic growth, urbanization, and climate change.
C1 [Burt, Zachary] Athena Infon, Chennai, India.
   [Leal, Susan; McElroy, Michael] Harvard Univ, Sch Engn & Appl Sci, Cambridge, MA USA.
   [Workman, James] Aquashares, Mill Valley, CA USA.
   [Bouhia, Hynd] BAL Method, London, England.
C3 Harvard University
RP Burt, Z (corresponding author), Athena Infon, Chennai, India.
EM zzburt@gmail.com
FU Middle East Initiative at Harvard University; T32 NIH training grant
   during this project, through the Mailman School of Public Health at
   Columbia University
FX This project was initiated and originally managed by Professor Peter
   Rogers of Harvard University School of Engineering and Applied Science.
   Management was transferred to Professor Michael McElroy after the demise
   of Professor Rogers. This paper is dedicated to his memory. We would
   also like to acknowledge the contributions of Monty Simus and Hynd
   Bouhia, as collaborators on this project, and Mourad Hati for his ground
   efforts in Marrakech. This research was funded by a grant from the
   Middle East Initiative at Harvard University. Z.B. was supported by a
   T32 NIH training grant during this project, through the Mailman School
   of Public Health at Columbia University.
CR AfDB, 2006, 9 DRINK WAT SAN PROJ, P103
   Andres Luis., 2019, Doing More with Less: Smarter Subsidies for Water Supply and Sanitation
   Baker JE, 2021, J ASSOC ENVIRON RESO, V8, P475, DOI 10.1086/712429
   Borgomeo E., 2018, WATER ENERGY FOOD NE, V51
   Dalhuisen JM, 2003, LAND ECON, V79, P292, DOI 10.2307/3146872
   Flörke M, 2018, NAT SUSTAIN, V1, P51, DOI 10.1038/s41893-017-0006-8
   Fuente D., 2017, WATER RESOUR RES
   Fuente D, 2016, WATER RESOUR RES, V52, P4845, DOI 10.1002/2015WR018375
   Gassert F., 2013, AQUEDUCT COUNTRY RIV, P28
   Gleick P. H., 1998, Water Policy, V1, P487, DOI DOI 10.1016/S1366-7017(99)00008-2
   Grafton RQ, 2011, REV ENV ECON POLICY, V5, P219, DOI 10.1093/reep/rer002
   Hall DC, 2009, CONTEMP ECON POLICY, V27, P555, DOI 10.1111/j.1465-7287.2009.00163.x
   Howard G., 2003, Domestic water quantity, service, level and health
   Kochhar M.K., 2015, Staff Discuss. Notes, V15, P1, DOI [10.5089/9781484391198.006, DOI 10.5089/9781484391198.006]
   Lahlou M, 2000, J AM WATER RESOUR AS, V36, P1003, DOI 10.1111/j.1752-1688.2000.tb05705.x
   Mekonnen MM, 2016, SCI ADV, V2, DOI 10.1126/sciadv.1500323
   Moumen Z., 2019, WATER RESOUR DEV MAN, V1, P18
   Olmstead SM, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR007227
   Rogers Peter., 2010, Running Out of Water: The Looming Crisis and Solutions to Conserve Our Most Precious Resource
   Siddiqi A, 2011, ENERG POLICY, V39, P4529, DOI 10.1016/j.enpol.2011.04.023
   Tull C., 2016, KDD WORKSH DAT SCI F
   Verner D, 2012, MENA DEV REP, P1, DOI 10.1596/978-0-8213-9458-8
   Workman J., 2017, EVOLUTION INNOVATION
   World-Bank, 2017, MENA DEV SERIES WORL
NR 24
TC 1
Z9 1
U1 1
U2 5
PU IWA PUBLISHING
PI LONDON
PA REPUBLIC-EXPORT BLDG, UNITS 1 04 & 1 05, 1 CLOVE CRESCENT, LONDON,
   ENGLAND
SN 2043-9083
EI 2408-9362
J9 J WATER SANIT HYG DE
JI J. Wate Sanit. Hyg. Dev.
PD JUN
PY 2023
VL 13
IS 6
BP 424
EP 432
DI 10.2166/washdev.2023.236
EA APR 2023
PG 9
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA K0NM9
UT WOS:000974274900001
OA gold
DA 2025-01-10
ER

PT J
AU Liu, CT
   Ou, SJ
   Mao, BG
   Tang, JY
   Wang, W
   Wang, HR
   Cao, SY
   Schläppi, MR
   Zhao, BR
   Xiao, GY
   Wang, XP
   Chu, CC
AF Liu, Citao
   Ou, Shujun
   Mao, Bigang
   Tang, Jiuyou
   Wang, Wei
   Wang, Hongru
   Cao, Shouyun
   Schlappi, Michael R.
   Zhao, Bingran
   Xiao, Guoying
   Wang, Xiping
   Chu, Chengcai
TI Early selection of <i>bZIP73</i> facilitated adaptation of
   <i>japonica</i> rice to cold climates
SO NATURE COMMUNICATIONS
LA English
DT Article
ID TRANSCRIPTION FACTOR; DROUGHT-RESISTANCE; STRESS TOLERANCE; CULTIVATED
   RICE; REVEALS; ASSOCIATION; GENE; ABA; DOMESTICATIONS; IDENTIFICATION
AB Cold stress is a major factor limiting production and geographic distribution of rice (Oryza sativa). Although the growth range of japonica subspecies has expanded northward compared to modern wild rice (O. rufipogon), the molecular basis of the adaptation remains unclear. Here we report bZIP73, a bZIP transcription factor-coding gene with only one functional polymorphism (+511G>A) between the two subspecies japonica and indica, may have facilitated japonica adaptation to cold climates. We show the japonica version of bZIP73 (bZIP73(Jap)) interacts with bZIP71 and modulates ABA levels and ROS homeostasis. Evolutionary and population genetic analyses suggest bZIP73 has undergone balancing selection; the bZIP73(Jap) allele has firstly selected from standing variations in wild rice and likely facilitated cold climate adaptation during initial japonica domestication, while the indica allele bZIP73(Ind) was subsequently selected for reasons that remain unclear. Our findings reveal early selection of bZIP73(Jap) may have facilitated climate adaptation of primitive rice germplasms.
C1 [Liu, Citao; Ou, Shujun; Tang, Jiuyou; Wang, Wei; Wang, Hongru; Cao, Shouyun; Chu, Chengcai] Chinese Acad Sci, Inst Genet & Dev Biol, State Key Lab Plant Genom, Beijing 100101, Peoples R China.
   [Liu, Citao; Ou, Shujun; Tang, Jiuyou; Wang, Wei; Wang, Hongru; Cao, Shouyun; Chu, Chengcai] Chinese Acad Sci, Inst Genet & Dev Biol, Natl Ctr Plant Gene Res Beijing, Beijing 100101, Peoples R China.
   [Ou, Shujun] Michigan State Univ, Dept Hort, E Lansing, MI 48824 USA.
   [Mao, Bigang; Zhao, Bingran] China Natl Hybrid Rice Res & Dev Ctr, State Key Lab Hybrid Rice, Changsha 410125, Hunan, Peoples R China.
   [Schlappi, Michael R.] Marquette Univ, Dept Biol Sci, Milwaukee, WI 53233 USA.
   [Xiao, Guoying] Chinese Acad Sci, Inst Subtrop Agr, Changsha 410125, Hunan, Peoples R China.
   [Wang, Xiping] Beijing Normal Univ, Beijing 100875, Peoples R China.
   [Chu, Chengcai] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Genetics & Developmental
   Biology, CAS; Chinese Academy of Sciences; Institute of Genetics &
   Developmental Biology, CAS; Michigan State University; Marquette
   University; Chinese Academy of Sciences; Institute of Subtropical
   Agriculture, CAS; Beijing Normal University; Chinese Academy of
   Sciences; University of Chinese Academy of Sciences, CAS
RP Chu, CC (corresponding author), Chinese Acad Sci, Inst Genet & Dev Biol, State Key Lab Plant Genom, Beijing 100101, Peoples R China.; Chu, CC (corresponding author), Chinese Acad Sci, Inst Genet & Dev Biol, Natl Ctr Plant Gene Res Beijing, Beijing 100101, Peoples R China.; Wang, XP (corresponding author), Beijing Normal Univ, Beijing 100875, Peoples R China.; Chu, CC (corresponding author), Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
EM xipingwang@hotmail.com; ccchu@genetics.ac.cn
RI Wang, He/JCO-3900-2023; Ou, Shujun/N-5263-2019; Tang,
   Jiuyou/J-7224-2015; Chu, Chengcai/AAF-6083-2019
OI Wang, Hongru/0000-0001-8305-5231; Ou, Shujun/0000-0001-5938-7180; Chu,
   Chengcai/0000-0001-8097-6115
FU National Natural Science Foundation of China [31271680, 31501283]; State
   Key Laboratory of Plant Genomics
FX We thank Mr. Gupo Li for plant management in the field, and Y. Liao for
   providing bZIP73 orthologous sequences from the Oryza genus. We also
   thank Drs. Jun Fang, Shaopei Gao, Bo Xu, Changhui Sun, Linchuan Liu,
   Chengzhen Liang, and Zhimin Jiang in the Chu lab for their help with
   biochemistry experiments and for fruitful discussions during the article
   preparation. The work was supported by grants from the National Natural
   Science Foundation of China (#31271680 and #31501283) and the State Key
   Laboratory of Plant Genomics. ArcGIS (R) and ArcAtlas (TM) are the
   intellectual property of Esri and are used herein under license.
   Copyright (c) Esri. All rights reserved. For more information about Esri
   (R) software, please visit www.esri.com.
CR Agrama HA, 2009, CROP SCI, V49, P1336, DOI 10.2135/cropsci2008.06.0551
   Alachiotis N, 2012, BIOINFORMATICS, V28, P2274, DOI 10.1093/bioinformatics/bts419
   Bart R, 2006, PLANT METHODS, V2, DOI 10.1186/1746-4811-2-13
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Chen LP, 2018, NEW PHYTOL, V218, P219, DOI 10.1111/nph.14977
   Chernukhin I, 2011, ANAL BIOCHEM, V412, P183, DOI 10.1016/j.ab.2011.01.036
   Choi JY, 2017, MOL BIOL EVOL, V34, P969, DOI 10.1093/molbev/msx049
   Civán P, 2018, BMC EVOL BIOL, V18, DOI 10.1186/s12862-018-1180-7
   Civán P, 2015, NAT PLANTS, V1, DOI [10.1038/NPLANTS.2015.164, 10.1038/nplants.2015.164]
   Cui LG, 2015, PLOS GENET, V11, DOI 10.1371/journal.pgen.1005617
   Du H, 2013, PLANT MOL BIOL, V83, P475, DOI 10.1007/s11103-013-0103-7
   Excoffier L, 2010, MOL ECOL RESOUR, V10, P564, DOI 10.1111/j.1755-0998.2010.02847.x
   Fairhurst T. H., 2002, Better Crops International, V16, P3
   Fu JH, 2012, ANAL SCI, V28, P1081, DOI 10.2116/analsci.28.1081
   Fuller DQ, 2010, ARCHAEOL ANTHROP SCI, V2, P115, DOI 10.1007/s12520-010-0035-y
   Garris AJ, 2005, GENETICS, V169, P1631, DOI 10.1534/genetics.104.035642
   Gross BL, 2014, P NATL ACAD SCI USA, V111, P6190, DOI 10.1073/pnas.1308942110
   Corrêa LGG, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002944
   Hellens RP, 2005, PLANT METHODS, V1, DOI 10.1186/1746-4811-1-13
   Hiraga S, 2001, PLANT CELL PHYSIOL, V42, P462, DOI 10.1093/pcp/pce061
   Hu B, 2015, NAT GENET, V47, P834, DOI 10.1038/ng.3337
   Huang GT, 2012, MOL BIOL REP, V39, P969, DOI 10.1007/s11033-011-0823-1
   Huang L, 2016, BMC PLANT BIOL, V16, DOI 10.1186/s12870-016-0897-y
   Huang XH, 2012, NATURE, V490, P497, DOI 10.1038/nature11532
   Jakoby M, 2002, TRENDS PLANT SCI, V7, P106, DOI 10.1016/S1360-1385(01)02223-3
   Jena KK, 2012, CROP SCI, V52, P517, DOI 10.2135/cropsci2010.12.0733
   Joo J, 2014, PLANT BIOTECHNOL REP, V8, P431, DOI 10.1007/s11816-014-0335-2
   Kawahara Y, 2013, RICE, V6, DOI 10.1186/1939-8433-6-4
   Kim SI, 2011, BIOCHEM J, V435, P373, DOI 10.1042/BJ20101610
   Liu Citao, 2018, Yichuan, V40, P171, DOI 10.16288/j.yczz.18-007
   Liu CT, 2014, PLANT MOL BIOL, V84, P19, DOI 10.1007/s11103-013-0115-3
   Liu CT, 2012, PLANTA, V235, P1157, DOI 10.1007/s00425-011-1564-z
   Liu LL, 2013, J INTEGR BIOINFORMAT, V10, DOI 10.2390/biecoll-jib-2013-223
   Londo JP, 2006, P NATL ACAD SCI USA, V103, P9578, DOI 10.1073/pnas.0603152103
   Lu GW, 2014, PLANT J, V78, P468, DOI 10.1111/tpj.12487
   Luo AD, 2005, J INTEGR PLANT BIOL, V47, P745, DOI 10.1111/j.1744-7909.2005.00071.x
   Lv Y, 2016, PLANT CELL ENVIRON, V39, P556, DOI 10.1111/pce.12635
   Ma Y, 2015, CELL, V160, P1209, DOI 10.1016/j.cell.2015.01.046
   Mega R, 2015, SCI REP-UK, V5, DOI 10.1038/srep13819
   Mittler R, 2015, PLANT CELL, V27, P64, DOI 10.1105/tpc.114.133090
   Nijhawan A, 2008, PLANT PHYSIOL, V146, P333, DOI 10.1104/pp.107.112821
   Ning J, 2010, PLANT PHYSIOL, V152, P876, DOI 10.1104/pp.109.149856
   Oleksyk TK, 2010, PHILOS T R SOC B, V365, P185, DOI 10.1098/rstb.2009.0219
   Pérez-Rodríguez P, 2010, NUCLEIC ACIDS RES, V38, pD822, DOI 10.1093/nar/gkp805
   Saito K, 2010, PLANT SCI, V179, P97, DOI 10.1016/j.plantsci.2010.04.004
   Scheres B, 2017, NATURE, V543, P337, DOI 10.1038/nature22010
   Schläppi MR, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00957
   Shakiba E, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0172133
   Shimizu H, 2005, PLANT CELL PHYSIOL, V46, P1623, DOI 10.1093/pcp/pci178
   Sornaraj P, 2016, BBA-GEN SUBJECTS, V1860, P46, DOI 10.1016/j.bbagen.2015.10.014
   Tamura K, 2011, MOL BIOL EVOL, V28, P2731, DOI 10.1093/molbev/msr121
   TAYLOR MFJ, 1995, SCIENCE, V270, P1497, DOI 10.1126/science.270.5241.1497
   Teacher AGF, 2011, MOL ECOL RESOUR, V11, P151, DOI 10.1111/j.1755-0998.2010.02890.x
   Vitte C, 2004, MOL GENET GENOMICS, V272, P504, DOI 10.1007/s00438-004-1069-6
   Waadt R, 2008, PLANT J, V56, P505, DOI 10.1111/j.1365-313X.2008.03612.x
   Wang D, 2016, RICE, V9, DOI 10.1186/s12284-016-0133-2
   Wang HR, 2017, GENOME RES, V27, P1029, DOI 10.1101/gr.204800.116
   Wang HR, 2016, MOL PLANT, V9, P975, DOI 10.1016/j.molp.2016.04.018
   Wang WS, 2018, NATURE, V557, P43, DOI 10.1038/s41586-018-0063-9
   Wu WX, 2013, P NATL ACAD SCI USA, V110, P2775, DOI 10.1073/pnas.1213962110
   Xie GS, 2012, BIOCHEM J, V443, P95, DOI 10.1042/BJ20111792
   Xu X, 2012, NAT BIOTECHNOL, V30, P105, DOI 10.1038/nbt.2050
   Yamaguchi-Shinozaki K, 2006, ANNU REV PLANT BIOL, V57, P781, DOI 10.1146/annurev.arplant.57.032905.105444
   Zhang Q, 2014, RICE, V7, DOI 10.1186/s12284-014-0024-3
   Zhang X, 2011, PLANT MOL BIOL, V75, P365, DOI 10.1007/s11103-011-9732-x
   Zhang Y, 2011, PLANT METHODS, V7, DOI 10.1186/1746-4811-7-30
   Zhang Y, 2008, GENOME BIOL, V9, DOI 10.1186/gb-2008-9-9-r137
   Zhang ZY, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14788
   Zong W, 2016, PLANT PHYSIOL, V171, P2810, DOI 10.1104/pp.16.00469
NR 69
TC 154
Z9 186
U1 18
U2 190
PU NATURE RESEARCH
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2041-1723
J9 NAT COMMUN
JI Nat. Commun.
PD AUG 17
PY 2018
VL 9
AR 3302
DI 10.1038/s41467-018-05753-w
PG 12
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA GQ6VP
UT WOS:000441865600007
PM 30120236
OA gold, Green Published
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Williams, MK
   Green, A
   Kim, E
AF Williams, Mark K.
   Green, Alex
   Kim, Ella
TI Municipal Leadership of Climate Adaptation Negotiations: Effective Tools
   and Strategies in Houston and Fort Lauderdale
SO NEGOTIATION JOURNAL
LA English
DT Article
DE negotiation; public dispute resolution; multiparty negotiation;
   adaptation; cities; climate change; climate negotiation; municipal
   leadership; public policy implementation; environmental policy
ID BARRIERS; POLICY
AB Negotiation analysis of climate change-related issues has largely focused on public dispute resolution mechanisms that are typically applied in the face of specific environmental crises, or on multiparty diplomacy relating to international climate agreements. Mayors and other municipal leaders, however, are increasingly taking steps to negotiate urban planning efforts with stakeholders to implement policies for managing the intensifying impact of climate change. In this article, we analyze negotiations in Houston, Texas, and Fort Lauderdale, Florida, to identify which methods municipal leaders employed to conduct negotiations to implement climate adaptation policies and also consider whether those methods were effective. The two cities present two differing city management structures: Houston has a strong mayor-driven system, while Fort Lauderdale uses a city commission and city manager system. In this article, we examine the barriers that leaders must overcome and consider their options for negotiating lasting agreements.
C1 [Williams, Mark K.] Harvard Law Sch, Program Negotiat, Cambridge, MA 02138 USA.
   [Green, Alex] Harvard Sch Business, Boston, MA USA.
   [Kim, Ella] MIT, Dept Urban Studies & Planning, Cambridge, MA 02139 USA.
C3 Harvard University; Harvard University; Massachusetts Institute of
   Technology (MIT)
RP Williams, MK (corresponding author), Harvard Law Sch, Program Negotiat, Cambridge, MA 02138 USA.
EM ismwilliams@law.harvard.edu
CR Anguelovski I, 2011, CURR OPIN ENV SUST, V3, P169, DOI 10.1016/j.cosust.2010.12.017
   [Anonymous], 1999, The consensus building handbook : A comprehensive guide to reaching agreement, DOI DOI 10.4135/9781452231389
   [Anonymous], MULTIPARTY NEGOTIATI
   [Anonymous], USITC PUBL
   [Anonymous], HARVARD BUSINESS REV
   [Anonymous], 2014, WORLD URB PROSP 2014, DOI 10.18356/527e5125-en
   Aylett A., 2014, Progress and Challenges in the Urban Governance of Climate Change Results of a Global Survey
   Bagley K., 2016, RISING SEAS PULL FOR
   Bazerman MH, 2008, NEGOTIATION J, V24, P113, DOI 10.1111/j.1571-9979.2007.00170.x
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Carmin J., 2013, OECD Regional Development Working Papers
   City of Fort Lauderdale, 2016, PLANNING ZONING BOAR
   City of Fort Lauderdale, 2016, FORUM PROPOSED SEAWA
   City of Fort Lauderdale, 2013, WE AR READ WE AR RES
   Council of Fort Lauderdale Civic Associations, 2016, AB THE COUNC
   Davis J. H., 2016, NY TIMES
   Dutta-Koehler M.C., 2013, THESIS MIT CAMBRIDGE
   Feldman L. R, 2016, SEAWALL PROCESS MEMO
   Gassman N, 2016, COMMUNICATION
   Goodell J., 2013, Rolling Stone
   Harris County Flood Control District, 2016, FLOOD ED MAPP TOOL H
   Hartford Institute for Religion Research, 2015, DAT MEG US
   Hughes S, 2015, URBAN CLIM, V14, P17, DOI 10.1016/j.uclim.2015.06.003
   Institute of Politics, 2016, FELL A PARK
   IPCC (Intergovernmental Panel on Climate Change), 2014, Climate Change 2014: Mitigation of Climate Change, DOI DOI 10.1017/CB09781107415416
   Jones S, 2013, REG STUD, V47, P974, DOI 10.1080/00343404.2011.585150
   Kahan DM, 2011, J RISK RES, V14, P147, DOI 10.1080/13669877.2010.511246
   Kervin D., 2011, HOUSTON CITY COUNCIL
   Lanza M., 2016, Houston's Tax Day flooding put into historical perspective
   Lax D.A., 2006, 3-D Negotiation: Powerful tools to change the game in your most important deals
   Lee K, 2011, TEXAS WATCHDOG  0617
   Lindner J., 2016, STORM FLOOD INFORM A
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Miller S., 2010, RENEW HOUSTON LEADER
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   National Aeronautics and Space Administration, 2016, 2016 CLIM TRENDS CON
   Olson B., 2016, HOUSTON CHRONICLE
   Parker A., 2016, COMMUNICATION
   ReBuild Houston, 2016, WHAT IS REBUILD HOUS
   ReBuild Houston, 2016, LOOK BACK LOOK FORW
   ReBuild Houston, 2016, PAY US YOU GO FUND
   Renn O, 2011, WIRES CLIM CHANGE, V2, P154, DOI 10.1002/wcc.99
   Sanchez R., 2016, CABLE NEWS NETW 0421
   Sebenius JamesK., 1984, NEGOTIATING LAW SEA
   Seiler J. P., 2016, COMMUNICATION
   Shi LD, 2015, J AM PLANN ASSOC, V81, P191, DOI 10.1080/01944363.2015.1074526
   Sjostedt Gunnar, 2013, CLIMATE CHANGE NEGOT
   Smith J.B., 2010, ADAPTING CLIMATE CHA
   Susskind L, 2006, NEGOTIATION J, V22, P351, DOI 10.1111/j.1571-9979.2006.00106.x
   Susskind L., 2015, Managing climate risks in coastal communities: Strategies for engagement, readiness and adaptation
   Susskind L.E., 1987, Breaking the impasse: Consensual approaches to resolving public disputes
   Susskind L, 2010, TOWN PLAN REV, V81, P217, DOI 10.3828/tpr.2010.5
   Susskind LE, 2015, NEGOTIATION J, V31, P223, DOI 10.1111/nejo.12092
   Texas A&M University Real Estate Center, 2016, POP DAT HOUST WOODL
   The World Bank Group, 2011, Guide to Climate Change Adaptation in Cities
   Thompson L., 2012, The mind and heart of the negotiator, V5th
   United States Census Bureau, 2016, QUICK FACTS HOUST CI
NR 57
TC 2
Z9 3
U1 2
U2 21
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0748-4526
EI 1571-9979
J9 NEGOTIATION J
JI Negot. J.
PD JAN
PY 2017
VL 33
IS 1
BP 5
EP 23
DI 10.1111/nejo.12171
PG 19
WC Management; Social Sciences, Interdisciplinary
WE Social Science Citation Index (SSCI)
SC Business & Economics; Social Sciences - Other Topics
GA EK1HB
UT WOS:000393675300002
DA 2025-01-10
ER

PT J
AU Manos, E
   Witharana, C
   Perera, AS
   Liljedahl, AK
AF Manos, Elias
   Witharana, Chandi
   Perera, Amal S.
   Liljedahl, Anna K.
TI A multi-objective comparison of CNN architectures in Arctic human-built
   infrastructure mapping from sub-meter resolution satellite imagery
SO INTERNATIONAL JOURNAL OF REMOTE SENSING
LA English
DT Article
DE Segmentation; neural networks; buildings; Arctic; deep learning; very
   high spatial resolution
ID ALASKA PUBLIC INFRASTRUCTURE; CLIMATE-CHANGE; STATISTICAL COMPARISONS;
   ECONOMIC-ASSESSMENT; BUILDING DETECTION; CLASSIFICATION; LANDSCAPES;
   CLASSIFIERS; ALGORITHMS; TESTS
AB Risk assessment of infrastructure exposed to ice-rich permafrost hazards is essential for climate change adaptation in the Arctic. As this process requires up-to-date, comprehensive, high-resolution maps of human-built infrastructure, gaps in such geospatial information and knowledge of the applications required to produce it must be addressed. Therefore, this study highlights the ongoing development of a deep learning approach to efficiently map the Arctic built environment by detecting nine different types of structures (detached houses, row houses, multi-story blocks, non-residential buildings, roads, runways, gravel pads, pipelines, and storage tanks) from recently-acquired Maxar commercial satellite imagery (<1 m resolution). We conducted a multi-objective comparison, focusing on generalization performance and computational cost, of nine different semantic segmentation architectures. K-fold cross validation was used to estimate the average F1-score of each architecture and the Friedman Aligned Ranks test with the Bergmann-Hommel post-hoc procedure was applied to test for significant differences in generalization performance. ResNet-50-UNet++ performs significantly better than five out of the other eight candidate architectures; no significant difference was found in the pairwise comparisons of ResNet-50-UNet++ to ResNet-50-MANet, ResNet-101-MANet, and ResNet-101-UNet++. We then conducted a high-performance computing scaling experiment to compare the number of service units and runtime required for model inferencing on a hypothetical pan-Arctic scale dataset. We found that the ResNet-50-UNet++ model could save up to similar to 54% on service unit expenditure, or similar to 18% on runtime, when considering operational deployment of our mapping approach. Our results suggest that ResNet-50-UNet++ could be the most suitable architecture (out of the nine that were examined) for deep learning-enabled Arctic infrastructure mapping efforts. Overall, our findings regarding the differences between the examined CNN architectures and our methodological framework for multi-objective architecture comparison can provide a foundation that may propel future pan-Arctic GeoAI mapping efforts of infrastructure.
C1 [Manos, Elias; Witharana, Chandi; Perera, Amal S.] Univ Connecticut, Dept Nat Resources & Environm, Storrs, CT USA.
   [Witharana, Chandi] Univ Connecticut, Eversource Energy Ctr, Storrs, CT USA.
   [Liljedahl, Anna K.] Woodwell Climate Res Ctr, Falmouth, MA USA.
   [Manos, Elias] Univ Connecticut, Dept Nat Resources & Environm, 1376 Storrs Rd,Unit 4087, Storrs, CT 06269 USA.
C3 University of Connecticut; University of Connecticut; University of
   Connecticut
RP Manos, E (corresponding author), Univ Connecticut, Dept Nat Resources & Environm, 1376 Storrs Rd,Unit 4087, Storrs, CT 06269 USA.
EM elias.manos@uconn.edu
RI witharana, chandi/C-9074-2015
OI Liljedahl, Anna/0000-0001-7114-6443; Manos, Elias/0000-0002-7350-0116
FU U.S. National Science Foundation's Office of Polar Programs (NSF-OPP)
   [1927723, 1927872, 2052107]; National Science Foundation [2138259,
   2138286, 2138307, 2137603, 2138296]
FX This work is funded by the U.S. National Science Foundation's Office of
   Polar Programs (NSF-OPP) (grant No. 1927723, 1927872, and 2052107).
   Furthermore, this work used the Delta supercomputer at the National
   Center for Supercomputing Applications at the University of Illinois
   Urbana- Champaign through allocation #EES220055 from the Advanced
   Cyberin frastructure Coordination Ecosystem: Services & Support (ACCESS)
   program, which is supported by National Science Foundation grants
   #2138259, #2138286, #2138307, #2137603, and #2138296.
CR [Anonymous], 2022, National Snow and Ice Data Center
   [Anonymous], 2023, CGS Planning & Lands - GIS Data (ESRI Shapefile)
   [Anonymous], 2023, Delta User Guide - Delta Supercomputer - NCSA Wiki
   [Anonymous], 2023, OpenDataTemplate
   [Anonymous], 2022, NSB GIS Public
   [Anonymous], 2022, Alaska Geobotany Center - Organizations - Alaska Arctic Geoecological Atlas
   Ardelean F, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12233999
   Aytekin O, 2012, INT J REMOTE SENS, V33, P2152, DOI 10.1080/01431161.2011.606852
   Ba J., 2015, ARXIV, P1
   Badina SV., 2020, Stud. Russ. Econ. Devel., V31, P396, DOI [https://doi.org/10.1134/S1075700720040036, 10.1134/S1075700720040036]
   Bartsch A, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac3176
   Bartsch A, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12152368
   Bergmann B., 1988, Multiple Hypotheses Testing, P100, DOI [DOI 10.1007/978-3-642-52307-6_8, DOI 10.1007/978-3-642-52307-68]
   Biskaborn BK, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-018-08240-4
   Blaschke T, 2010, ISPRS J PHOTOGRAMM, V65, P2, DOI 10.1016/j.isprsjprs.2009.06.004
   Blaschke T, 2014, ISPRS J PHOTOGRAMM, V87, P180, DOI 10.1016/j.isprsjprs.2013.09.014
   Blunden J., 2016, Bull. Am. Meterol. Soc, V98, DOI [10.1175/2017BAMSStateoftheClimate.1, DOI 10.1175/2017BAMSSTATEOFTHECLIMATE.1]
   Calvo B, 2016, R J, V8, P248
   Chaurasia A, 2017, 2017 IEEE VISUAL COMMUNICATIONS AND IMAGE PROCESSING (VCIP)
   Chen LC, 2018, Arxiv, DOI [arXiv:1802.02611, 10.48550/arXiv.1802.02611]
   Comiso JC, 2014, WIRES CLIM CHANGE, V5, P389, DOI 10.1002/wcc.277
   Demsar J, 2006, J MACH LEARN RES, V7, P1
   Deng J, 2009, PROC CVPR IEEE, P248, DOI 10.1109/CVPRW.2009.5206848
   Dobinski W, 2011, EARTH-SCI REV, V108, P158, DOI 10.1016/j.earscirev.2011.06.007
   Dore M. H., 2001, Canadian Climate Change Action Fund. St. Catherines
   Duro DC, 2012, REMOTE SENS ENVIRON, V118, P259, DOI 10.1016/j.rse.2011.11.020
   Fan TL, 2020, IEEE ACCESS, V8, P179656, DOI 10.1109/ACCESS.2020.3025372
   Friedman M, 1937, J AM STAT ASSOC, V32, P675, DOI 10.2307/2279372
   Friedman M, 1940, ANN MATH STAT, V11, P86, DOI 10.1214/aoms/1177731944
   Gadal S, 2019, ISPRS INT J GEO-INF, V8, DOI 10.3390/ijgi8030129
   García S, 2010, INFORM SCIENCES, V180, P2044, DOI 10.1016/j.ins.2009.12.010
   García S, 2008, J MACH LEARN RES, V9, P2677
   Gautier DL, 2009, SCIENCE, V324, P1175, DOI 10.1126/science.1169467
   Hassol SusanJoy., 2004, IMPACTS WARMING ARCT
   He KM, 2015, Arxiv, DOI [arXiv:1512.03385, DOI 10.48550/ARXIV.1512.03385]
   Hjort J, 2022, NAT REV EARTH ENV, V3, P24, DOI 10.1038/s43017-021-00247-8
   HODGES JL, 1962, ANN MATH STAT, V33, P482, DOI 10.1214/aoms/1177704575
   Hossain K., 2017, Current Developments in Arctic Law
   Huang G, 2018, Arxiv, DOI [arXiv:1608.06993, DOI 10.48550/ARXIV.1608.06993]
   Iakubovskii P., 2023, Python
   Instanes A., 2016, P 9 INT C PERMAFROST, P779
   Japkowicz Nathalie, 2011, Evaluating Learning Algorithms: A Classification Perspective
   Khrustalev L., 2011, RELIABILITY NO INFRA
   Kohavi R., 1995, P IJCAI 95 14 INT JO, VVolume 14, P1137
   Kumpula T, 2010, ARCTIC, V63, P165
   Kumpula T., 2006, Nordia Geographical Publications, V35, P17
   Kumpula T, 2012, REMOTE SENS-BASEL, V4, P1046, DOI 10.3390/rs4041046
   Kumpula T, 2011, GLOBAL ENVIRON CHANG, V21, P550, DOI 10.1016/j.gloenvcha.2010.12.010
   Larsen JoanNymand., 2015, The New Arctic, P159, DOI [10.1007/978-3-319-17602-4_12, DOI 10.1007/978-3-319-17602-4_12]
   Larsen PH, 2008, GLOBAL ENVIRON CHANG, V18, P442, DOI 10.1016/j.gloenvcha.2008.03.005
   Lehner A, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11020173
   Li JY, 2022, GISCI REMOTE SENS, V59, P1199, DOI 10.1080/15481603.2022.2101727
   Li MC, 2016, INT J APPL EARTH OBS, V49, P87, DOI 10.1016/j.jag.2016.01.011
   Lin TY, 2018, Arxiv, DOI [arXiv:1708.02002, 10.48550/arXiv.1708.02002]
   López-Serrano PM, 2016, CAN J REMOTE SENS, V42, P690, DOI 10.1080/07038992.2016.1217485
   Manos E, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14112719
   Melnikov VP, 2022, NAT HAZARDS, V112, P231, DOI 10.1007/s11069-021-05179-6
   Melvin AM, 2017, P NATL ACAD SCI USA, V114, pE122, DOI 10.1073/pnas.1611056113
   Molinaro AM, 2005, BIOINFORMATICS, V21, P3301, DOI 10.1093/bioinformatics/bti499
   Nelson FE, 2001, NATURE, V410, P889, DOI 10.1038/35073746
   Nymand Larsen J., 2014, TemaNord, V2014
   Ourng C, 2019, JOINT URB REMOTE SEN, DOI 10.1109/jurse.2019.8809013
   Paszke A, 2019, ADV NEUR IN, V32
   Peña JM, 2014, REMOTE SENS-BASEL, V6, P5019, DOI 10.3390/rs6065019
   Pizarro J, 2002, NEUROCOMPUTING, V48, P155, DOI 10.1016/S0925-2312(01)00653-1
   Porfiriev BN, 2021, HER RUSS ACAD SCI+, V91, P677, DOI 10.1134/S1019331621060113
   Porfiriev BN, 2021, HER RUSS ACAD SCI+, V91, P17, DOI 10.1134/S1019331621010068
   Porfiriev BN, 2019, HER RUSS ACAD SCI+, V89, P567, DOI 10.1134/S1019331619060121
   Programme (AMAP) Arctic Monitoring and Assessment, 2017, Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017
   Ramage J, 2021, POPUL ENVIRON, V43, P22, DOI 10.1007/s11111-020-00370-6
   Ramm F., 2020, OpenStreetMap Data in Layered GIS Format (Geofabrik)
   Raschka S, 2020, Arxiv, DOI [arXiv:1811.12808, DOI 10.48550/ARXIV.1811.12808]
   Raynolds MK, 2014, GLOBAL CHANGE BIOL, V20, P1211, DOI 10.1111/gcb.12500
   Santafe G, 2015, ARTIF INTELL REV, V44, P467, DOI 10.1007/s10462-015-9433-y
   Simonyan K, 2015, Arxiv, DOI arXiv:1409.1556
   Streletskiy DA, 2023, ENVIRON RES LETT, V18, DOI 10.1088/1748-9326/acab18
   Streletskiy DA, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/aaf5e6
   Streletskiy DA, 2017, PERMAFROST PERIGLAC, V28, P566, DOI 10.1002/ppp.1918
   Streletskiy DA, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/12/125005
   Suter L, 2019, POLAR GEOGR, V42, P267, DOI 10.1080/1088937X.2019.1686082
   Tan MX, 2020, Arxiv, DOI arXiv:1905.11946
   Udawalpola M., 2021, Int. Arch. Photogramm., Remote Sens. Spatial Inf. Sci., P175, DOI [https://doi.org/10.5194/isprs-archives-XLIV-M-3-2021-175-2021, DOI 10.5194/ISPRS-ARCHIVES-XLIV-M-3-2021-175-2021]
   Udawalpola MR, 2022, PHOTOGRAMM ENG REM S, V88, P181, DOI 10.14358/PERS.21-00059R2
   Vazquez E. G., 2001, Bio-Inspired Applications of Connectionism. 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001. Proceedings, Part II. (Lecture Notes in Computer Science Vol.2085), P88
   Nhu VH, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17144933
   Witharana C., 2020, ISPRS - International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, VXLIV-M-2-2020, pXLIV, DOI [https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-111-2020, DOI 10.5194/ISPRS-ARCHIVES-XLIV-M-2-2020-111-2020]
   Witharana C., 2023, Ice-Wedge Polygon Detection in Satellite Imagery from Pan-Arctic Regions, Permafrost Discovery Gateway, 2001-2021, DOI [https://doi.org/10.18739/A2KW57K57, DOI 10.18739/A2KW57K57]
   Witharana C, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14174132
   Zar J.H., 1999, Biostatistical Analysis
   Zhou ZW, 2018, Arxiv, DOI arXiv:1807.10165
NR 90
TC 1
Z9 1
U1 3
U2 6
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 0143-1161
EI 1366-5901
J9 INT J REMOTE SENS
JI Int. J. Remote Sens.
PD DEC 17
PY 2023
VL 44
IS 24
BP 7670
EP 7705
DI 10.1080/01431161.2023.2287563
PG 36
WC Remote Sensing; Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Remote Sensing; Imaging Science & Photographic Technology
GA CK4Y2
UT WOS:001125145200001
DA 2025-01-10
ER

PT J
AU Kessler, KA
AF Kessler, Kim Andreas
TI What do remote outer island populations in the Pacific think about
   foreign aid? Insights from Mauke, Cook Islands
SO DEVELOPMENT POLICY REVIEW
LA English
DT Article
DE aid; community development; Cook Islands; do no harm; local;
   perspectives; outer islands; Pacific; remoteness; social cohesion;
   spatial development
ID CLIMATE-CHANGE ADAPTATION; CAPACITY
AB Motivation: Pacific aid research has largely focused on national issues and social justice, rather than spatial justice and the development of remote outer islands. In particular, the perspectives of remote outer island populations on aid have not previously been assessed.
   Purpose: This study explores the experiences and views of the population of a remote Pacific outer island, Mauke in the Cook Islands, on the foreign aid they receive. By listening to and learning from local people living with aid on a remote outer island, this article seeks to address spatially insensitive Pacific aid research and policy. Based on these insights, the article derives policy implications for aid and development actors working on Mauke and other remote outer islands in the Pacific.
   Methods and approach: Employing a mixed-methods approach, this article draws on field research conducted on Mauke, involving in-depth semi-structured interviews and a quantitative survey.
   Findings: The people of Mauke are divided about whether the island should receive more or less aid. Those calling for more aid tend to be younger; they stress the need for infrastructure development. Those advocating for less aid tend to be older; they argue that aid has harmed Mauke by decreasing endogenous initiatives and creating social tensions, both of which reduce social cohesion among the remote island population.
   Policy implications: Rather than investing in "community-based/led development"-doing development with the community, aid to remote Pacific outer islands should focus more on "community development"-with the aim of enhancing social cohesion among peripheral islands. Donors, governments, and development partners must carefully reflect on the degree to which their interventions may harm social cohesion and the endogenous development potential of remote outer island populations. These implications matter given the persistence of uncritical (mis) representations and (mis)conceptions of remote Pacific outer island populations as harmonious and mutually supportive.
C1 [Kessler, Kim Andreas] Univ Otago, Sch Geog, Dunedin, New Zealand.
   [Kessler, Kim Andreas] Univ South Pacific, Sch Agr Geog Environm Ocean & Nat Sci, Suva, Fiji.
C3 University of Otago; University of the South Pacific
RP Kessler, KA (corresponding author), Univ Otago, Sch Geog, Dunedin, New Zealand.; Kessler, KA (corresponding author), Univ South Pacific, Sch Agr Geog Environm Ocean & Nat Sci, Suva, Fiji.
EM kim.kessler@postgrad.otago.ac.nz
RI Kessler, Kim/JRZ-1254-2023
OI Kessler, Kim Andreas/0000-0002-3385-6927
FU University of the South Pacific (USP)
FX This research was partially funded by the University of the South
   Pacific (USP). Open access publishing facilitated by University of
   Otago, as part of the Wiley - University of Otago agreement via the
   Council of Australian University Librarians.
CR Aipira C, 2017, CLIM CHANG MANAG, P225, DOI 10.1007/978-3-319-50094-2_13
   Anderson MaryB., 1999, DO NO HARM AID CAN S
   [Anonymous], 1993, NEW OCEANIA REDISCOV
   [Anonymous], 2013, Radio New ZealandOctober 28
   Armstrong A., 2020, Oxford research encyclopedia of education, DOI [10.1093/acrefore/9780190264093.013.1200, DOI 10.1093/ACREFORE/9780190264093.013.1200]
   Assa Jacob., 2021, MULTIDIMENSIONAL VUL
   Baldacchino G, 2004, TIJDSCHR ECON SOC GE, V95, P272, DOI 10.1111/j.1467-9663.2004.00307.x
   Baldacchino G., 2005, The Round Table, V94, P31
   Baldacchino Godfrey., 2006, ISL STUD J, V1, P3
   Barnett J, 2010, EARTHSCAN CLIM, P1
   Barnett J., 2005, Journal of International Affairs, V59, P203
   Barnett J., 2016, The Palgrave handbook of international development, P731, DOI DOI 10.1057/978-1-137-42724-3-40
   Barnett J, 2008, POLIT SCI, V60, P31, DOI 10.1177/003231870806000104
   Bertram G, 2018, J PAC HIST, V53, P44, DOI 10.1080/00223344.2018.1435966
   Bertram Geoffrey., 1986, Pacific Viewpoint, V27, P47, DOI DOI 10.1111/APV.271003
   Bertram I. G  ..., 1985, Pacific Viewpoint, V26, P497, DOI DOI 10.1111/APV.263002
   Brown Oli., 2005, Aiding or Abetting? Dilemmas of Foreign Aid and political instability in the Melanesian Pacific
   Cambers G, 2017, CLIM CHANG MANAG, P3, DOI 10.1007/978-3-319-50094-2_1
   Connell J, 2010, SINGAPORE J TROP GEO, V31, P115, DOI 10.1111/j.1467-9493.2010.00387.x
   Cook Islands Statistics Office, 2022, Census of population and dwellings 2021
   Cook Islands Statistics Office, 2012, Cook Islands 2011 census of population and dwellings: Main report
   Cope M., 2003, Key Methods in Geography, P440
   Diedrich A, 2019, AMBIO, V48, P385, DOI 10.1007/s13280-018-1081-4
   Dornan M, 2017, ASIA PAC POLICY STUD, V4, P386, DOI 10.1002/app5.185
   Dumaru P, 2010, WIRES CLIM CHANGE, V1, P751, DOI 10.1002/wcc.65
   Duncan R., 2019, Pacific Economic Bulletin, V9, P21
   Embassy of Japan in New Zealand, 2020, Grant contract signing for the project for the establishment of water tanks in Mauke Island under Grant Assistance for Grassroots Human Security Projects (GGP) at Wellington
   Gaventa J., 2019, Power, Empowerment and Social Change
   Haak E, 2021, NEW ZEAL GEOGR, V77, P32, DOI 10.1111/nzg.12284
   Hooper A., 2005, Culture and sustainable development in the Pacific, P1
   Hughes H, 2010, PAC ECON BULL, V25, P232
   Johnston I, 2014, DISASTER PREV MANAG, V23, P123, DOI 10.1108/DPM-06-2013-0096
   Keen M, 2019, URBAN POLICY RES, V37, P324, DOI 10.1080/08111146.2019.1626710
   Kelly C., 1985, Master's thesis
   Kessler K. A., 2018, Unpublished Master's thesis
   Lowy Institute, PACIFIC AID MAP
   Lowy Institute, Pacific aid map: Cook Islands
   Malherbe W, 2020, OCEAN COAST MANAGE, V191, DOI 10.1016/j.ocecoaman.2020.105186
   McKinnon K, 2016, GENDER PLACE CULT, V23, P1376, DOI 10.1080/0966369X.2016.1160036
   Mountfort H., 2013, Master's thesis
   Murray WE, 2011, ASIA PAC VIEWP, V52, P272, DOI 10.1111/j.1467-8373.2011.01468.x
   Nunn PD, 2009, CLIM RES, V40, P211, DOI 10.3354/cr00806
   Organisation for Economic Cooperation and Development, 2023, History of DAC Lists of aid recipient countries
   Overton J., 2019, Aid, ownership and development: The inverse sovereignty effect in the Pacific Islands, DOI [10.4324/9780429444814, DOI 10.4324/9780429444814]
   Overton J, 2013, GEOGR COMPASS, V7, P116, DOI 10.1111/gec3.12026
   Petzold J, 2015, OCEAN COAST MANAGE, V112, P36, DOI 10.1016/j.ocecoaman.2015.05.003
   Pirnia P., 2016, Doctoral dissertation
   Poirine B, 1998, CONTEMP PACIFIC, V10, P65
   Robinson SA, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.653
   Sachs J., 2021, DECADE ACTION SMALL
   Thomas FR, 2007, ROUTL PAC RIM GEOGR, V6, P38
   Titz A, 2018, SOCIETIES, V8, DOI 10.3390/soc8030071
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   United Nations Department of Economic and Social Affairs, Multidimensional vulnerability index for SIDS
   United Nations Development Programme, 2015, Leave no one behind: Advancing social, economic, cultural and political inclusion of LGBTI people in Asia and the Pacific - Summary
   United Nations Office of the High Representative for the Least Developed Countries Landlocked Developing Countries and Small Island Developing States, About Small Island Developing States
   United Nations Office of the High Representative for the Least Developed Countries Landlocked Developing Countries and Small Island Developing States, 2023, OUTC DOC INT PREP M
   United Nations Statistics Division, 2023, Country profile
   Weir T., 2013, Climate - smart technologies: Integrating renewable energy and energy efficiency in mitigation and adaptation responses, DOI [10.1007/978-3-642-37753-2_4, DOI 10.1007/978-3-642-37753-2_4]
   Wood T, 2022, DEV POLICY REV, V40, DOI 10.1111/dpr.12573
   Wrighton N., 2010, Participation, power and practice in development: A case study of theoretical doctrines and international agency practice in Tuvalu
NR 61
TC 1
Z9 2
U1 0
U2 5
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0950-6764
EI 1467-7679
J9 DEV POLICY REV
JI Dev. Policy Rev.
PD DEC
PY 2023
VL 41
SU 2
SI SI
DI 10.1111/dpr.12759
EA DEC 2023
PG 12
WC Development Studies
WE Social Science Citation Index (SSCI)
SC Development Studies
GA JZ8H9
UT WOS:001117740200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Muhl, EK
   Armitage, D
   Anderson, K
   Boyko, C
   Busilacchi, S
   Butler, J
   Cvitanovic, C
   Faulkner, LA
   Hall, JA
   Martynuik, G
   Paul-Burke, K
   Swerdfager, T
   Thorpe, H
   van Putten, IE
AF Muhl, Ella-Kari
   Armitage, Derek
   Anderson, Kevin
   Boyko, Cindy
   Busilacchi, Sara
   Butler, James
   Cvitanovic, Christopher
   Faulkner, Linda A.
   Hall, Julie A.
   Martynuik, Geoffrey
   Paul-Burke, Kura
   Swerdfager, Trevor
   Thorpe, Hilary
   van Putten, Ingrid E.
TI Transitioning toward "deep" knowledge co-production in coastal and
   marine systems: examining the interplay among governance, power, and
   knowledge
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE Key Words: conservation; governance; knowledge; ocean; power;
   sustainability
ID SETTLER COLONIALISM; SCIENCE; RESOURCE; EXCHANGE; POLICY; COD;
   NEWFOUNDLAND; STRATEGIES; INTERFACE; COLLAPSE
AB Knowledge co-production (KCP) is presented as an effective strategy to inform responses to complex coastal and marine social-ecological challenges. Co-production processes are further posited to improve research and decision outcomes in a wide range of problem contexts (e.g., biodiversity conservation, climate change adaptation), for example, by facilitating social learning among diverse actors. As such, KCP processes are increasingly centered in global environment initiatives such as the United Nations Decade of Ocean Science for Sustainable Development. However, KCP is not a panacea, and much uncertainty remains about its emergence and implementation, in particular, the manner in which broader governance contexts determine the interplay of knowledge, power, and decision-making. Three objectives guide our analysis: (1) to interrogate more fully the interplay among social relations of power, knowledge production practices, and the (colonial) governance contexts in which they are embedded; (2) to consider the challenges and limitations of KCP in particular places by drawing attention to key governance themes and their implications for achieving better outcomes; and (3) to work toward a fuller understanding of "deep KCP" that cautions against a tendency to view knowledge processes in coastal and marine governance settings as an instrumental or techno-managerial problem. A qualitative and reflective approach was used to examine multiple dimensions of the interplay of KCP, governance, and power in several marine and coastal contexts, including Canada, New Zealand, and Papua New Guinea. In particular, our analysis highlights the importance of: (1) recognizing diverse motivations that frame co-production processes; (2) the manner in which identities, positionality, and values influence and are influenced by governance contexts; (3) highlighting governance capacity with respect to spatial and temporal constraints; (4) institutional reforms necessary for KCP and the links to governance; and (5) the relationship between knowledge sharing, data sovereignty, and governance. We seek to encourage those involved in or considering co-production initiatives to engage carefully and critically in these processes and make co-production more than a box to tick.
C1 [Muhl, Ella-Kari; Armitage, Derek; Swerdfager, Trevor] Univ Waterloo, Sch Environm Resources & Sustainabil, Waterloo, ON, Canada.
   [Armitage, Derek] Univ Waterloo, Environm Change & Governance Grp, Waterloo, ON, Canada.
   [Anderson, Kevin] Mem Univ Newfoundland, Fisheries & Marine Inst, St John, NF, Canada.
   [Boyko, Cindy] Council Haida Nation, Gwaii Haanas Archipelago Management Board, Haida Gwaii, BC, Canada.
   [Butler, James] Cawthron Inst, Nelson, New Zealand.
   [Cvitanovic, Christopher] Univ New South Wales, Sch Business, Canberra, ACT, Australia.
   [Faulkner, Linda A.; Hall, Julie A.] Natl Inst Water & Atmospher Res NIWA, Sustainable Seas Natl Sci Challenge, Wellington, New Zealand.
   [Martynuik, Geoffrey] Gwaii Haanas Field Unit, Parks Canada, BC, Canada.
   [Paul-Burke, Kura] Univ Waikato, Fac Maori & Indigenous Studies, Sch Sci & Pua Wananga Ki Te Ao, Te Aka Matuatua, Tauranga, New Zealand.
   [Thorpe, Hilary] Protected Areas Estab, Parks Canada, BC, Canada.
   [van Putten, Ingrid E.] CSIRO Environm, Hobart, Tas, Australia.
   [van Putten, Ingrid E.] Univ Tasmania, Ctr Marine Socioecol, Hobart, Tas, Australia.
C3 University of Waterloo; University of Waterloo; Memorial University
   Newfoundland; Cawthron Institute; University of New South Wales Sydney;
   National Institute of Water & Atmospheric Research (NIWA) - New Zealand;
   Parks Canada; University of Waikato; Parks Canada; Commonwealth
   Scientific & Industrial Research Organisation (CSIRO); University of
   Tasmania
RP Muhl, EK (corresponding author), Univ Waterloo, Sch Environm Resources & Sustainabil, Waterloo, ON, Canada.
EM emuhl@uwaterloo.ca; derek.armitage@uwaterloo.ca;
   kevin.anderson@mi.mun.ca; cindylouboyko@gmail.com;
   sara_busilacchi@hotmail.com; james.butler@cawthron.org.nz;
   c.cvitanovic@unsw.edu.au; linda@tutaiao.co.nz; julie.hall@niwa.co.nz;
   geoffrey.martynuik@canada.ca; kura@waikato.ac.nz;
   trevor.swerdfager@uwaterloo.ca; hilary.thorpe@pc.gc.ca;
   Ingrid.vanputten@csiro.au
RI Butler, James/D-7446-2011; Muhl, Ella-Kari/HNR-8983-2023
OI Butler, James/0000-0001-8333-947X
FU Social Science and Humanities Research Council of Canada (SSHRC)
FX Acknowledgments: We acknowledge the financial support of the Social
   Science and Humanities Research Council of Canada (SSHRC) .
CR Agrawal A, 2001, INT J MANAG REV, V3, P285, DOI 10.1111/1468-2370.00069
   Alfred T, 2005, GOV OPPOS, V40, P597, DOI 10.1111/j.1477-7053.2005.00166.x
   [Anonymous], 2003, The theory and practice of knowledge brokering in Canada's health system
   Armitage D, 2011, GLOBAL ENVIRON CHANG, V21, P995, DOI 10.1016/j.gloenvcha.2011.04.006
   Armitage DR, 2019, BIOSCIENCE, V69, P523, DOI 10.1093/biosci/biz059
   Artelle KA, 2019, BIOL CONSERV, V240, DOI 10.1016/j.biocon.2019.108284
   Bednarek AT, 2018, SUSTAIN SCI, V13, P1175, DOI 10.1007/s11625-018-0550-9
   Berkes F., 2003, RCSD INT C POL COMM
   Bhandar B, 2018, Global Insurgent Leg, P1
   Bremer S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.482
   Buckley S, 2011, PROCEEDINGS OF THE 3RD EUROPEAN CONFERENCE ON INTELLECTUAL CAPITAL, P103
   Cash DW, 2006, ECOL SOC, V11
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Chambers JM, 2022, GLOBAL ENVIRON CHANG, V72, DOI 10.1016/j.gloenvcha.2021.102422
   Chambers JM, 2021, NAT SUSTAIN, V4, P983, DOI 10.1038/s41893-021-00755-x
   Ciuk S., 2018, SAGE HDB QUALITATIVE, P270, DOI [DOI 10.4135/9781526430212.N17, 10.4135/9781526430212, DOI 10.4135/9781526430212]
   Clark WC, 2003, P NATL ACAD SCI USA, V100, P8059, DOI 10.1073/pnas.1231333100
   Coulthard Glen., 2010, AFFINITIES J RADICAL, V4, P79
   Creswell J. W., 2018, Research design: qualitative, quantitative, and mixed methods approaches
   Cvitanovic C, 2021, ENVIRON SCI POLICY, V123, P179, DOI 10.1016/j.envsci.2021.05.020
   Cvitanovic C, 2019, ENVIRON SCI POLICY, V94, P20, DOI 10.1016/j.envsci.2018.12.028
   Daniel R., 2019, Eos, V100
   Derickson KD, 2022, ANN AM ASSOC GEOGR, V112, P838, DOI 10.1080/24694452.2021.1996219
   Djenontin INS, 2018, ENVIRON MANAGE, V61, P885, DOI 10.1007/s00267-018-1028-3
   Dorries H, 2022, ENVIRON PLANN D, V40, P306, DOI 10.1177/02637758211068505
   Fazey I, 2018, ENERGY RES SOC SCI, V40, P54, DOI 10.1016/j.erss.2017.11.026
   Forsyth T., 2003, CRITICAL POLITICAL E
   Goldman MJ, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.526
   Graham ID, 2006, J CONTIN EDUC HEALTH, V26, P13, DOI 10.1002/chp.47
   Greenhalgh T, 2004, MILBANK Q, V82, P581, DOI 10.1111/j.0887-378X.2004.00325.x
   Harris C, 2004, ANN ASSOC AM GEOGR, V94, P165, DOI 10.1111/j.1467-8306.2004.09401009.x
   Harris D. C., 2008, Landing native fisheries: Indian Reserves and fishing rights in British Columbia, 1849-1925, DOI [10.59962/9780774856102, DOI 10.59962/9780774856102]
   Harris DouglasC., 2010, ARCTIC REV. LAW POL, V1, P82
   Hill R, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102161
   HUTCHINGS JA, 1994, CAN J FISH AQUAT SCI, V51, P2126, DOI 10.1139/f94-214
   Jasanoff S, 1996, SOC STUD SCI, V26, P393, DOI 10.1177/030631296026002008
   Jasanoff S., 2004, STATES KNOWLEDGE KNO
   Jessen TD, 2022, FRONT ECOL ENVIRON, V20, P93, DOI 10.1002/fee.2435
   Karcher DB, 2022, OCEAN COAST MANAGE, V225, DOI 10.1016/j.ocecoaman.2022.106194
   Karcher DB, 2022, J ENVIRON MANAGE, V314, DOI 10.1016/j.jenvman.2022.114994
   Lemos MC, 2018, NAT SUSTAIN, V1, P722, DOI 10.1038/s41893-018-0191-0
   Lemos MC, 2005, GLOBAL ENVIRON CHANG, V15, P57, DOI 10.1016/j.gloenvcha.2004.09.004
   Levesque P, 2007, J CAN ACAD CHILD ADO, V16, P51
   Levin B., 2008, request of the Canadian Council on Learning and the Social Sciences and Humanities Research Council
   Liboiron M, 2021, POLLUTION IS COLONIALISM, P1
   Lin YC, 2006, AUTOMAT CONSTR, V15, P693, DOI 10.1016/j.autcon.2005.09.006
   Littlechild DB, 2021, FACETS, V6, P665, DOI 10.1139/facets-2020-0076
   Mahajan SL, 2023, ICES J MAR SCI, V80, P390, DOI 10.1093/icesjms/fsac115
   Meyer M, 2010, SCI COMMUN, V32, P118, DOI 10.1177/1075547009359797
   Milich L, 1999, SOC NATUR RESOUR, V12, P625, DOI 10.1080/089419299279353
   Miller CA, 2020, ENVIRON SCI POLICY, V113, P88, DOI 10.1016/j.envsci.2018.01.016
   Mills KE, 2023, ICES J MAR SCI, V80, P358, DOI 10.1093/icesjms/fsac110
   Moola F, 2019, ENVIRON REV, V27, P200, DOI 10.1139/er-2018-0091
   Muhl EK, 2022, ENVIRON MANAGE, V70, P448, DOI 10.1007/s00267-022-01670-3
   Nadasdy P, 1999, ARCTIC ANTHROPOL, V36, P1
   No'kmaq M, 2021, FACETS, V6, P839, DOI 10.1139/facets-2020-0083
   Norstrom AV, 2020, NAT SUSTAIN, V3, P182, DOI 10.1038/s41893-019-0448-2
   Ostrom E, 1996, WORLD DEV, V24, P1073, DOI 10.1016/0305-750X(96)00023-X
   Parsons M., 2021, Decolonising blue spaces in the Anthropocene: freshwater management in Aotearoa New Zealand, DOI [10.1007/978-3-030-61071-5_2, DOI 10.1007/978-3-030-61071-5]
   Paul-Burke K., 2020, N. Z. Sci. Rev., V76, P32, DOI [10.26686/nzsr.v76i1-2.7831, DOI 10.26686/NZSR.V76I1-2.7831]
   Reid AJ, 2021, FISH FISH, V22, P243, DOI 10.1111/faf.12516
   Robards MD, 2018, DEEP-SEA RES PT II, V152, P203, DOI 10.1016/j.dsr2.2018.02.008
   Root-Bernstein M, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15031831
   Salomon AK, 2023, PHILOS T R SOC B, V378, DOI 10.1098/rstb.2022.0196
   Schneider F, 2021, CURR OPIN ENV SUST, V49, P127, DOI 10.1016/j.cosust.2021.04.007
   Schwermer H, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132112229
   Scott James C., 1998, Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed
   Silver JJ, 2022, AM NAT, V200, P168, DOI 10.1086/720152
   Silver JJ, 2013, J RURAL STUD, V32, P430, DOI 10.1016/j.jrurstud.2013.10.003
   Starman A.B., 2013, Journal of Contemporary Educational Studies - Sodobna Pedagogika, V64
   Steger C, 2020, ECOL SOC, V25, DOI 10.5751/ES-11325-250202
   Straus SE, 2009, CAN MED ASSOC J, V181, P165, DOI 10.1503/cmaj.081229
   Tengö M, 2014, AMBIO, V43, P579, DOI 10.1007/s13280-014-0501-3
   Todd Z, 2018, DECOLONIZATION, V7, P60
   Todd Z, 2016, J HIST SOCIOL, V29, P4, DOI 10.1111/johs.12124
   Turnhout E, 2020, CURR OPIN ENV SUST, V42, P15, DOI 10.1016/j.cosust.2019.11.009
   Vincent K, 2020, NAT CLIM CHANGE, V10, P877, DOI 10.1038/s41558-020-00910-w
   Whyte K, 2018, ENVIRON SOC, V9, P125, DOI 10.3167/ares.2018.090109
   Winter KB, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103554
   Wolfe P, 2006, J GENOCIDE RES, V8, P387, DOI 10.1080/14623520601056240
   Wyborn C, 2019, ANNU REV ENV RESOUR, V44, P319, DOI [10.1146/annurev-environ-101718-033103, 10.1146/annurev-environ-101718033103]
   Yanow D, 2012, J ORGAN ETHNOGR, V1, P31, DOI 10.1108/202466741211220633
   Ybema S., 2009, ORG ETHNOGRAPHY STUD, P101, DOI DOI 10.4135/9781446278925
   Yin R. K., 2013, Case study research: Design and methods, V5, DOI DOI 10.1097/FCH.0B013E31822DDA9E
   Zurba M, 2022, SUSTAIN SCI, V17, P449, DOI 10.1007/s11625-021-00996-x
NR 85
TC 16
Z9 16
U1 6
U2 20
PU Resilience Alliance
PI Dedham
PA 231 Bussey St., Beckwith and Brown, Dedham, Massachusetts, UNITED STATES
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PD OCT
PY 2023
VL 28
IS 4
AR 17
DI 10.5751/ES-14443-280417
PG 24
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA Y9TL8
UT WOS:001108611800002
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Grady, K
   Markus, M
   Wu, S
   Wang, FY
   Koric, S
AF Grady, Kevin
   Markus, Momcilo
   Wu, Shu
   Wang, Fuyao
   Koric, Seid
TI Assessment of the benefits of climate model weights for ensemble
   analysis in three urban precipitation frequency studies
SO JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
LA English
DT Article
DE climate change adaptation; climate models; precipitation frequency;
   projected frequency; urban adaptation; urban hydrology; weighted
   ensemble
ID PROJECTIONS; PROBABILITY; RAINFALL
AB In hydrology, projected climate change impact assessment studies typically rely on ensembles of downscaled climate model outputs. Due to large modeling uncertainties, the ensembles are often averaged to provide a basis for studying the effects of climate change. A key issue when analyzing averages of a climate model ensemble is whether to weight all models in the ensemble equally, often referred to as the equal-weights or unweighted approach, or to use a weighted approach, where, in general, each model would have a different weight. Many studies have advocated for the latter, based on the assumption that models that are better at simulating the past, that is, the models with higher hindcast accuracy, will give more accurate forecasts for the future and thus should receive higher weights. To examine this issue, observed and modeled daily precipitation frequency (PF) estimates for three urban areas in the United States, namely Boston, Massachusetts; Houston, Texas; and Chicago, Illinois, were analyzed. The comparison used the raw output of 24 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. The PFs from these models were compared with the observed PFs for a specific historical training period to determine model weights for each area. The unweighted and weighted averaged model PFs from a more recent testing period were then compared with their corresponding observed PFs to determine if weights improved the estimates. These comparisons indeed showed that the weighted averages were closer to the observed values than the unweighted averages in nearly all cases. The study also demonstrated how weights can help reduce model spread in future climate projections by comparing the unweighted and weighted ensemble standard deviations in these projections. In all studied scenarios, the weights actually reduced the standard deviations compared to the equal-weights approach. Finally, an analysis of the results' sensitivity to the areal reduction factor used to allow comparisons between point station measurements and grid-box averages is provided.
C1 [Grady, Kevin; Markus, Momcilo] Univ Illinois, Prairie Res Inst, Champaign, IL 61820 USA.
   [Wu, Shu; Wang, Fuyao] Univ Wisconsin, Nelson Inst Environm Studies, Madison, WI USA.
   [Koric, Seid] Univ Illinois, Natl Ctr Supercomp Applicat, Champaign, IL USA.
C3 University of Illinois System; University of Illinois Urbana-Champaign;
   University of Wisconsin System; University of Wisconsin Madison;
   University of Illinois System; University of Illinois Urbana-Champaign
RP Markus, M (corresponding author), Univ Illinois, Prairie Res Inst, Champaign, IL 61820 USA.
EM mmarkus@illinois.edu
RI Wang, Fuyao/H-1715-2013
FU National Oceanic and Atmospheric Administration [SUBAWD000255]; National
   Science Foundation [OCI-0725070, ACI-1238993]
FX National Oceanic and Atmospheric Administration, Grant/Award Number:
   SUBAWD000255; National Science Foundation, Grant/Award Number:
   OCI-0725070 and ACI-1238993
CR Allen RJ, 2005, J HYDROL ENG, V10, P327, DOI 10.1061/(ASCE)1084-0699(2005)10:4(327)
   [Anonymous], 2019, PRECIPITATION FREQUE
   Christensen JH, 2010, CLIM RES, V44, P179, DOI 10.3354/cr00916
   cli-MATE, 2019, MIDWESTERN REGIONAL
   Douglas EM, 2011, J HYDROL ENG, V16, P203, DOI 10.1061/(ASCE)HE.1943-5584.0000303
   Emanuel K, 2017, P NATL ACAD SCI USA, V114, P12681, DOI 10.1073/pnas.1716222114
   Hagedorn R, 2005, TELLUS A, V57, P219, DOI 10.1111/j.1600-0870.2005.00103.x
   Hershfield D.M., 1961, RAINFALL FREQUENCY A, P65
   Hosking J.R.M., 1997, Regional Frequency Analysis: An Approach Based on L-Moments, DOI [10.1017/CBO9780511529443, DOI 10.1017/CBO9780511529443]
   Knutti R, 2017, GEOPHYS RES LETT, V44, P1909, DOI 10.1002/2016GL072012
   Knutti R, 2010, CLIMATIC CHANGE, V102, P395, DOI 10.1007/s10584-010-9800-2
   Knutti R, 2010, J CLIMATE, V23, P2739, DOI 10.1175/2009JCLI3361.1
   LANGBEIN W. B., 1949, TRANS AMER GEOPHYS UNION, V30, P879
   Li ZY, 2019, ANTHROPOCENE, V25, DOI 10.1016/j.ancene.2019.100193
   Markus M, 2018, J HYDROL ENG, V23, DOI 10.1061/(ASCE)HE.1943-5584.0001614
   Markus M, 2012, CLIMATIC CHANGE, V111, P879, DOI 10.1007/s10584-011-0172-z
   Masson D, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL046864
   Notaro M, 2014, J CLIMATE, V27, P6526, DOI 10.1175/JCLI-D-13-00520.1
   Pavlovic S, 2016, J HYDROL, V537, P419, DOI 10.1016/j.jhydrol.2016.03.027
   Perica S., 2018, Precipitation-Frequency Atlas of the United States, Texas
   Räisänen J, 2012, CLIM DYNAM, V39, P1981, DOI 10.1007/s00382-011-1217-8
   Reidmiller D. R., 2018, Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, VII, DOI [DOI 10.7930/NCA4.2018, 10.7930/NCA4.2018]
   Rimoldini L, 2014, ASTRON COMPUT, V5, P1, DOI 10.1016/j.ascom.2014.02.001
   Sánchez E, 2009, ATMOS SCI LETT, V10, P241, DOI 10.1002/asl.230
   Sanderson B., 2017, Climate Science Special Report: Fourth National Climate Assessment: Volume, VI, P436, DOI DOI 10.7930/J06T0JS3
   Sanderson BM, 2015, J CLIMATE, V28, P5171, DOI 10.1175/JCLI-D-14-00362.1
   Shortridge JE, 2018, CLIMATIC CHANGE, V151, P525, DOI 10.1007/s10584-018-2324-x
   Sivapalan M, 1998, J HYDROL, V204, P150, DOI 10.1016/S0022-1694(97)00117-0
   Steinschneider S, 2015, GEOPHYS RES LETT, V42, P5014, DOI 10.1002/2015GL064529
   Tukey J. W., 1977, EXPLORATORY DATA ANA, V2, P131, DOI [10.1002/bimj.4710230408, DOI 10.1007/978-1-4419-7976-6]
   Um MJ, 2018, WATER RESOUR MANAG, V32, P913, DOI 10.1007/s11269-017-1846-8
   Um MJ, 2017, J HYDROL, V552, P396, DOI 10.1016/j.jhydrol.2017.07.007
   US Weather Bureau, 1957, 29 US DEP COMM
   Wang K., 2017, IMPACTS POTENTIAL FU
   Weigel AP, 2010, J CLIMATE, V23, P4175, DOI 10.1175/2010JCLI3594.1
   Wu S, 2019, WATER-SUI, V11, DOI 10.3390/w11061279
   Wuebbles D.J., 2017, CLIMATE SCI SPECIAL, VI, P12, DOI [DOI 10.7930/J0DJ5CTG, 10.7930/ j0dj5ctg]
   Wuebbles D.J., 2017, CLIMATE SCI SPECIAL, P470, DOI [DOI 10.7930/J0J964J6, 10.7930/j0j964j6]
   Zhang W, 2018, NATURE, V563, P384, DOI 10.1038/s41586-018-0676-z
NR 39
TC 0
Z9 0
U1 4
U2 5
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1093-474X
EI 1752-1688
J9 J AM WATER RESOUR AS
JI J. Am. Water Resour. Assoc.
PD JUN
PY 2023
VL 59
IS 3
BP 498
EP 509
DI 10.1111/1752-1688.13065
EA OCT 2022
PG 12
WC Engineering, Environmental; Geosciences, Multidisciplinary; Water
   Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA I6DJ3
UT WOS:000867586800001
OA Bronze, Green Submitted
DA 2025-01-10
ER

PT J
AU Markanday, A
   Galarraga, I
AF Markanday, Ambika
   Galarraga, Ibon
TI The cognitive and experiential effects of flood risk framings and
   experience, and their influence on adaptation investment behaviour
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Climate change adaptation; Flood risk; Risk communication; Lab
   experiment
ID GLOBAL CLIMATE-CHANGE; PSYCHOLOGICAL DISTANCE; PUBLIC ENGAGEMENT; PLACE
   ATTACHMENT; POLICY PREFERENCES; NATURAL HAZARDS; PERCEPTIONS;
   COMMUNICATION; MITIGATION; RESPONSES
AB This study explores how decision makers invest in adaptation to protect against flood risks in response to a) different framings of flood risk information, and b) after experiencing losses from a hypothetical flood event. An incentivised economic lab experiment is conducted on a sample of students in Bilbao (Basque Country, Spain). A 2 x 2 between-subject design is used to measure investment behaviour with and without exposure to a flood risk map and after exposure to impacts framed as economic losses versus number of persons affected. Experience is measured through a 2-period repeated game within-subject design. Flood risk maps and impacts framed as number of persons affected were conducive to more experiential forms of decision-making, while decisions based on impacts framed as economic losses were more cognitive in nature. Those that saw text-only framings used a combination of cognitive and experiential factors for making decisions. While exposure to maps evoked more affect-driven responses, they were associated with lower ratings of positive affect and self-efficacy, and resulted in lower investments in protection compared to text-only framings. Greater experiential processing was found for impact framings based on persons affected, but they were not especially effective at increasing personal relevance of the issue or in driving investments. Individuals who experienced losses from a hypothetical flood event had greater ratings of negative affect, and made subsequent decisions that were more affect-driven in nature. In contrast, individuals who did not experience losses had greater ratings of positive affect, and made subsequent decisions based on primarily cognitive factors. Investments in protection reduced for those who did not experience losses, and remained the same for those who did experience losses. Results suggest that changes in adaptation investments between decision points may be dependent on both the experience (or lack thereof) of losses, as well as the extent to which individuals were risk-averse or risk-taking in previous investment decisions.
C1 [Markanday, Ambika; Galarraga, Ibon] Basque Ctr Climate Change BC3, Parque Cient UPV EHU, Leioa, Spain.
   [Galarraga, Ibon] Univ Basque Country, Dept Fundamentos Anal Econ, Bilbao, Spain.
C3 Basque Centre for Climate Change (BC3); University of Basque Country
RP Markanday, A (corresponding author), BC3, Edificio Sede 1,Planta 1,Parque Cient UPV EHU, Leioa 48940, Spain.
EM Ambika.markanday@bc3research.org; ibon.galarraga@bc3research.org
RI GALARRAGA, IBON/M-7130-2013
OI Galarraga, Ibon/0000-0002-2683-9360
FU Horizon 2020 COACCH Project [776479]; Basque Government through the
   BERC; Spanish Ministry of Economy and Competitiveness MINECO through the
   BC3 Maria de Maetzu [MDM-2017-0714]
FX This research was supported by the Horizon 2020 COACCH Project (grant
   agreement no. 776479). Additionally, it was also supported by the Basque
   Government through the BERC 2018-2021 program and by the Spanish
   Ministry of Economy and Competitiveness MINECO through the BC3 Maria de
   Maetzu excellence accreditation MDM-2017-0714.
CR Basque Government, 2007, MET VAL COST IMP CAM
   Bell H. M., 2007, Environmental Hazards, V7, P302, DOI 10.1016/j.envhaz.2007.08.004
   Bonaiuto M, 2016, J ENVIRON PSYCHOL, V48, P33, DOI 10.1016/j.jenvp.2016.07.007
   Brody SD, 2008, ENVIRON BEHAV, V40, P72, DOI 10.1177/0013916506298800
   Bubeck P, 2018, RISK ANAL, V38, P1239, DOI 10.1111/risa.12938
   Burningham K, 2008, DISASTERS, V32, P216, DOI 10.1111/j.1467-7717.2007.01036.x
   Chen S, 1999, DUAL-PROCESS THEORIES IN SOCIAL PSYCHOLOGY, P73
   Chust G, 2011, CLIM RES, V48, P307, DOI 10.3354/cr00914
   Cooper KE, 2016, SCI COMMUN, V38, P626, DOI 10.1177/1075547016666843
   De Dominicis S, 2015, J ENVIRON PSYCHOL, V43, P66, DOI 10.1016/j.jenvp.2015.05.010
   DeGolia AH, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0220320
   Demeritt D, 2014, ENVIRON HAZARDS-UK, V13, P313, DOI 10.1080/17477891.2014.924897
   Dottori F, 2018, NAT CLIM CHANGE, V8, P781, DOI 10.1038/s41558-018-0257-z
   Druckman JN, 2008, POLIT BEHAV, V30, P297, DOI 10.1007/s11109-008-9056-y
   EPSTEIN S, 1994, AM PSYCHOL, V49, P709, DOI 10.1037/0003-066X.49.8.709
   Falk A., 2016, IZA DISCUSSION PAPER
   Forzieri G, 2016, CLIMATIC CHANGE, V137, P105, DOI 10.1007/s10584-016-1661-x
   Foudi S, 2017, WATER RESOUR RES, V53, P5831, DOI 10.1002/2017WR020435
   Fox-Rogers L, 2016, J HYDROL, V543, P330, DOI 10.1016/j.jhydrol.2016.10.009
   Galarraga I, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa513
   Gifford R, 2011, AM PSYCHOL, V66, P290, DOI 10.1037/a0023566
   Gifford R, 2009, J ENVIRON PSYCHOL, V29, P1, DOI 10.1016/j.jenvp.2008.06.001
   Gigerenzer G, 2005, RISK ANAL, V25, P623, DOI 10.1111/j.1539-6924.2005.00608.x
   Graham T, 2017, GLOBAL ENVIRON CHANG, V44, P98, DOI 10.1016/j.gloenvcha.2017.03.004
   Hart PS, 2016, SCI COMMUN, V38, P415, DOI 10.1177/1075547016655357
   Hart PS, 2013, PUBLIC UNDERST SCI, V22, P785, DOI 10.1177/0963662513482268
   Hartmann P, 2014, INT J ADVERT, V33, P741, DOI 10.2501/IJA-33-4-741-765
   Harvatt J, 2011, J RISK RES, V14, P63, DOI 10.1080/13669877.2010.503935
   Hidalgo M.C., 2010, Psyecology, V1, P105, DOI [10.1174/217119710790709595, DOI 10.1174/217119710790709595]
   Highfield WE, 2013, RISK ANAL, V33, P186, DOI 10.1111/j.1539-6924.2012.01840.x
   Jones C, 2017, RISK ANAL, V37, P331, DOI 10.1111/risa.12601
   Kahneman D., 2011, Thinking, fast and slow
   Kellens W, 2013, RISK ANAL, V33, P24, DOI 10.1111/j.1539-6924.2012.01844.x
   Kellens W, 2011, RISK ANAL, V31, P1055, DOI 10.1111/j.1539-6924.2010.01571.x
   Kellstedt PM, 2008, RISK ANAL, V28, P113, DOI 10.1111/j.1539-6924.2008.01010.x
   KUNDA Z, 1990, PSYCHOL BULL, V108, P480, DOI 10.1037/0033-2909.108.3.480
   Kunz M, 2011, NAT HAZARDS, V59, P1735, DOI 10.1007/s11069-011-9864-y
   Lawrence J, 2014, NAT HAZARDS, V74, P1773, DOI 10.1007/s11069-014-1288-z
   Leiserowitz A., 2013, Climate change in the American mind: A focus on California, Colorado, Ohio, and Texas
   Leiserowitz A, 2007, CREATING A CLIMATE FOR CHANGE: COMMUNICATING CLIMATE CHANGE AND FACILITATING SOCIAL CHANGE, P44, DOI 10.1017/CBO9780511535871.005
   Leiserowitz A, 2006, CLIMATIC CHANGE, V77, P45, DOI 10.1007/s10584-006-9059-9
   Lindman HR., 1974, Analysis of Variance in Complex Experimental Designs
   Loewenstein GF, 2001, PSYCHOL BULL, V127, P267, DOI 10.1037//0033-2909.127.2.267
   Lorenzoni I, 2007, GLOBAL ENVIRON CHANG, V17, P445, DOI 10.1016/j.gloenvcha.2007.01.004
   Maibach EW, 2010, BMC PUBLIC HEALTH, V10, DOI 10.1186/1471-2458-10-299
   Markanday A., 2020, BC3 WORKING PAPER SE, V202002
   Marx SM, 2007, GLOBAL ENVIRON CHANG, V17, P47, DOI 10.1016/j.gloenvcha.2006.10.004
   Meyer V, 2012, NAT HAZARDS, V62, P301, DOI 10.1007/s11069-011-9997-z
   Miceli R, 2008, J ENVIRON PSYCHOL, V28, P164, DOI 10.1016/j.jenvp.2007.10.006
   Mishra S, 2010, J ENVIRON PSYCHOL, V30, P187, DOI 10.1016/j.jenvp.2009.11.005
   Morton TA, 2011, GLOBAL ENVIRON CHANG, V21, P103, DOI 10.1016/j.gloenvcha.2010.09.013
   Moser SC, 2014, WIRES CLIM CHANGE, V5, P337, DOI 10.1002/wcc.276
   Mossler MV, 2017, GLOBAL ENVIRON CHANG, V45, P63, DOI 10.1016/j.gloenvcha.2017.04.002
   Myers TA, 2012, CLIMATIC CHANGE, V113, P1105, DOI 10.1007/s10584-012-0513-6
   Newman CL, 2012, INT J ADVERT, V31, P511, DOI 10.2501/IJA-31-3-511-527
   Nicholson-Cole S. A., 2005, Computers, Environment and Urban Systems, V29, P255, DOI 10.1016/j.compenvurbsys.2004.05.002
   O'Neill SJ, 2014, WIRES CLIM CHANGE, V5, P73, DOI 10.1002/wcc.249
   O'Neill SJ, 2013, GLOBAL ENVIRON CHANG, V23, P413, DOI 10.1016/j.gloenvcha.2012.11.006
   Oakley M, 2020, WATER-SUI, V12, DOI 10.3390/w12071848
   Otieno C, 2014, ENVIRON EDUC RES, V20, P612, DOI 10.1080/13504622.2013.833589
   Petrovic N, 2014, CLIMATIC CHANGE, V126, P245, DOI 10.1007/s10584-014-1192-2
   Retchless DP, 2018, ENVIRON BEHAV, V50, P483, DOI 10.1177/0013916517709043
   Roeser S, 2012, RISK ANAL, V32, P1033, DOI 10.1111/j.1539-6924.2012.01812.x
   Roeser S, 2010, J RISK RES, V13, P175, DOI 10.1080/13669870903126275
   Roth RE, 2009, CARTOGR GEOGR INF SC, V36, P29, DOI 10.1559/152304009787340160
   Scannell L, 2013, ENVIRON BEHAV, V45, P60, DOI 10.1177/0013916511421196
   Schultz PW, 2014, ENVIRON BEHAV, V46, P267, DOI 10.1177/0013916512458579
   Semenza JC, 2011, ENVIRON HEALTH-GLOB, V10, DOI 10.1186/1476-069X-10-46
   Sheppard SRJ, 2005, ENVIRON SCI POLICY, V8, P637, DOI 10.1016/j.envsci.2005.08.002
   Siegrist M, 2008, RISK ANAL, V28, P771, DOI 10.1111/j.1539-6924.2008.01049.x
   Siegrist M, 2006, RISK ANAL, V26, P971, DOI 10.1111/j.1539-6924.2006.00792.x
   Singh AS, 2017, ENVIRON SCI POLICY, V73, P93, DOI 10.1016/j.envsci.2017.04.011
   Sloman SA, 1996, PSYCHOL BULL, V119, P3, DOI 10.1037/0033-2909.119.1.3
   Slovic P, 2004, RISK ANAL, V24, P311, DOI 10.1111/j.0272-4332.2004.00433.x
   Slovic P, 2007, EUR J OPER RES, V177, P1333, DOI 10.1016/j.ejor.2005.04.006
   Smith N, 2014, RISK ANAL, V34, P937, DOI 10.1111/risa.12140
   Smith N, 2012, RISK ANAL, V32, P1021, DOI 10.1111/j.1539-6924.2012.01801.x
   Soane E, 2010, ENVIRON PLANN A, V42, P3023, DOI 10.1068/a43238
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   Spence A, 2012, RISK ANAL, V32, P957, DOI 10.1111/j.1539-6924.2011.01695.x
   Spence A, 2010, GLOBAL ENVIRON CHANG, V20, P656, DOI 10.1016/j.gloenvcha.2010.07.002
   Spiegelhalter D, 2011, SCIENCE, V333, P1393, DOI 10.1126/science.1191181
   Stevenson KT, 2014, CLIMATIC CHANGE, V126, P293, DOI 10.1007/s10584-014-1228-7
   Sunstein CR, 2007, COLUMBIA LAW REV, V107, P501
   Takao K, 2004, J RISK RES, V7, P775, DOI 10.1080/1366987031000075996
   Terpstra T, 2011, RISK ANAL, V31, P1658, DOI 10.1111/j.1539-6924.2011.01616.x
   Uzzell DL, 2000, J ENVIRON PSYCHOL, V20, P307, DOI 10.1006/jevp.2000.0175
   van Alphen J, 2009, J FLOOD RISK MANAG, V2, P285, DOI 10.1111/j.1753-318X.2009.01045.x
   van der Linden S, 2014, EUR J SOC PSYCHOL, V44, P430, DOI 10.1002/ejsp.2008
   van der Linden SL, 2014, CLIMATIC CHANGE, V126, P255, DOI 10.1007/s10584-014-1190-4
   Vasco G., 2015, ESTRATEGIA CAMBIO CL
   Walker BJA, 2018, ENVIRON BEHAV, V50, P781, DOI 10.1177/0013916517713299
   Wang S, 2019, FRONT PSYCHOL, V10, DOI 10.3389/fpsyg.2019.00230
   WATSON D, 1988, J PERS SOC PSYCHOL, V54, P1063, DOI 10.1037/0022-3514.54.6.1063
   Weber EU, 2011, AM PSYCHOL, V66, P315, DOI 10.1037/a0023253
   Whitmarsh L, 2008, J RISK RES, V11, P351, DOI 10.1080/13669870701552235
   Wiest SL, 2015, GLOBAL ENVIRON CHANG, V31, P187, DOI 10.1016/j.gloenvcha.2014.12.006
   Winsemius HC, 2016, NAT CLIM CHANGE, V6, P381, DOI [10.1038/nclimate2893, 10.1038/NCLIMATE2893]
   Zaalberg R, 2009, RISK ANAL, V29, P1759, DOI 10.1111/j.1539-6924.2009.01316.x
NR 99
TC 2
Z9 2
U1 1
U2 13
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2021
VL 34
AR 100359
DI 10.1016/j.crm.2021.100359
EA SEP 2021
PG 17
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA WD5LI
UT WOS:000704981500002
PM 34956829
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Lopes, HS
   Remoaldo, PC
   Ribeiro, V
   Martín-Vide, J
AF Silva Lopes, Helder
   Remoaldo, Paula C.
   Ribeiro, Vitor
   Martin-Vide, Javier
TI Perceptions of human thermal comfort in an urban tourism destination - A
   case study of Porto (Portugal)
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Tourism; Urban areas; Perceptions; Thermal comfort; City of Porto
ID MEAN RADIANT TEMPERATURE; PUBLIC SPACE DESIGN; PERSONAL FACTORS;
   HEAT-STRESS; OUTDOOR; CLIMATE; ADAPTATION; LISBON; ENVIRONMENTS;
   SENSATION
AB Tourism is one of the fastest growing economic sectors on an international scale. Based on this growth, it became necessary to consider climatic-meteorological conditions as determinants for boosting tourism in some geographical areas. The main objective of this paper is to characterize the perception of bioclimatic comfort of tourists who visited the city of Porto in the summer seasons of 2019 and 2020 (in the on-going pandemic). Primary data were obtained from a questionnaire on perceptions of bioclimatic comfort and microclimatic measurements applied to 207 tourists in the summer of 2019, 146 in the winter of 2019-2020 and 210 in the summer of 2020. It took place in one of the main places of passage for tourists visiting the city of Porto. Based on statistical analysis, responses were parameterized according to the environmental and sociodemographic characteristics of the tourists. In addition, summary indicators (Physiological Equivalent Temperature - PET, Thermal Sensation Vote - TSV, Thermal Preference Vote - TPV) were used to characterize the profile of visiting tourists. The influence of microclimate conditions on the thermal comfort of tourists was evident, showing, however, that they still felt comfortable regardless of the situation. The results demonstrated a good effort to reduce thermal discomfort through adapted behavior. Air temperature and relative humidity seem to be more directly related to mean thermal sensation votes in the summer of 2019 (r(2) = 0.86 and r(2) = 0.68, respectively). In the winters of 2019-2020 and summer of 2020, these indicators do not show such a strong correlation. Anyway, it is verified that there is a greater tolerance for higher and lower temperatures than those that are verified for the residents, when compared to previous studies. The consideration of average thresholds for thermal comfort in tourism is crucial. In future studies and planning proposals, it will be necessary to consider the optimal climatic conditions of local climate change adaptation and mitigation policies.
C1 [Silva Lopes, Helder; Remoaldo, Paula C.; Martin-Vide, Javier] Univ Minho, Lab2PT Landscape Heritage & Terr Lab, Dept Geog, ICS, Guimaraes, Portugal.
   [Silva Lopes, Helder; Remoaldo, Paula C.] Univ Barcelona, IdRA Climatol Grp, Dept Geog, FGH, Barcelona, Spain.
   [Ribeiro, Vitor] Univ Minho, Lab2PT Landscape Heritage & Terr Lab, Dept Geog, CIPAF,ICS, Guimaraes, Portugal.
   [Ribeiro, Vitor] ESE Paula Frassinetti, Porto, Portugal.
C3 Universidade do Minho; University of Barcelona; Universidade do Minho
RP Lopes, HS (corresponding author), Univ Minho, Lab2PT Landscape Heritage & Terr Lab, Dept Geog, ICS, Guimaraes, Portugal.; Lopes, HS (corresponding author), Univ Barcelona, IdRA Climatol Grp, Dept Geog, FGH, Barcelona, Spain.
EM htsltiago@hotmail.com; premoaldo@geografia.uminho.pt;
   vitor.geografia@gmail.com; jmartinvide@ub.edu
RI Lopes, Hélder/ADP-8422-2022; Ribeiro, Vitor/AAC-5667-2022; Remoaldo,
   Paula/M-2800-2017; RIBEIRO, Vitor/M-7663-2013
OI Remoaldo, Paula/0000-0002-9445-5465; Lopes, Helder/0000-0002-2931-5175;
   RIBEIRO, Vitor/0000-0002-5993-3492
FU FCT Portugal [SFRH/BD/129153/2017]; Lab2PT - Landscapes, Heritage and
   Territory Laboratory [AUR/04509]; FCT [POCI 01 0145 FEDER 007528];
   Fundação para a Ciência e a Tecnologia [SFRH/BD/129153/2017] Funding
   Source: FCT
FX This research was funded by FCT Portugal, grant number
   SFRH/BD/129153/2017 and Lab2PT - Landscapes, Heritage and Territory
   Laboratory - AUR/04509 and FCT through national funds and when
   appli-cable of the FEDER cofinancing, in the aim/under the scope of the
   new-partnership agreement PT2020 and COMPETE2020- POCI 01 0145 FEDER
   007528.
CR Alcoforado MJ, 2009, LANDSCAPE URBAN PLAN, V90, P56, DOI 10.1016/j.landurbplan.2008.10.006
   Alcoforado MJ, 2006, THEOR APPL CLIMATOL, V84, P151, DOI 10.1007/s00704-005-0152-1
   Andrade H, 2008, THEOR APPL CLIMATOL, V92, P225, DOI 10.1007/s00704-007-0321-5
   Andrade H, 2011, INT J BIOMETEOROL, V55, P665, DOI 10.1007/s00484-010-0379-0
   [Anonymous], 1998, ISO 7726 ERGONOMICS, DOI DOI 10.1111/INA.12748
   [Anonymous], 2009, ASHRAE Handbook|Fundamentals
   ASHRAE, 2013, 552013 ASHRAE, P30329
   ASHRAE, 2017, THERM COMF, P28
   Ashworth G.J., 2000, TOURIST HIST CITY
   BALLANTYNE ER, 1977, INT J BIOMETEOROL, V21, P29, DOI 10.1007/BF01552964
   Baruti MM, 2020, SUSTAIN CITIES SOC, V62, DOI 10.1016/j.scs.2020.102380
   Bedford T., 1936, WARMTH FACTOR COMF W
   Binarti F, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100531
   Brager GS, 1998, ENERG BUILDINGS, V27, P83, DOI 10.1016/S0378-7788(97)00053-4
   Butler R. W., 1990, Tourism Recreation Research, V15, P46
   Carvalho D, 2017, URBAN CLIM, V19, P1, DOI 10.1016/j.uclim.2016.11.005
   Chen YC, 2014, THEOR APPL CLIMATOL, V118, P535, DOI 10.1007/s00704-013-1081-z
   Cheung PK, 2019, BUILD ENVIRON, V151, P303, DOI 10.1016/j.buildenv.2019.01.057
   Coccolo S, 2016, URBAN CLIM, V18, P33, DOI 10.1016/j.uclim.2016.08.004
   Cooper D.R., 1998, Business Research Methods, V6th
   Costa JP, 2014, URBAN DES INT, V19, P77, DOI 10.1057/udi.2013.15
   Costa J, 2014, WORLDW HOSP TOUR THE, V6, P413, DOI 10.1108/WHATT-09-2014-0027
   Crank PJ, 2020, SCI TOTAL ENVIRON, V749, DOI 10.1016/j.scitotenv.2020.141392
   Lopes HD, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116399
   de Brum Ferreira D., 1990, FINISTERRA, V25
   de Freitas IV, 2019, PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON TOURISM RESEARCH (ICTR 2019), P345
   DEFREITAS CR, 1990, INT J CLIMATOL, V10, P89
   Dubois G., 2009, Climat, meteorology et frequentation touristique - Rapport final
   EC, 2021, EC PERF FOR
   Elnabawi MH, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11010051
   Emmanuel R., 2016, Urban Climate Challenges in the Tropics: Rethinking Planning and Design Opportunities, P31
   Eugenio-Martin JL, 2010, TOURISM MANAGE, V31, P744, DOI 10.1016/j.tourman.2009.07.015
   Fang ZS, 2019, SUSTAIN CITIES SOC, V44, P676, DOI 10.1016/j.scs.2018.10.022
   Fountain ME, 1996, ASHRAE J, V38, P39
   Gebremedhin T.G., 1994, Research Methods and Communication in the Social Sciences
   Gomes A., 2020, GEOGR PORTO, P14
   Gomez Martin B. G, 2017, RETOS TURISMO ESPANO
   Gomez-Martin M.B., 2005, Boletin de la Asociacion espanola de Geografia, V40, P111
   Gómez-Martín MB, 2006, CLIM RES, V32, P75, DOI 10.3354/cr032075
   Gusman I, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11205701
   Havenith G, 2002, ENERG BUILDINGS, V34, P581, DOI 10.1016/S0378-7788(02)00008-7
   Hwang R-L., 2007, ARCHIT SCI REV, V50, P357, DOI [10.3763/asre.2007.5043, DOI 10.3763/ASRE.2007.5043]
   ISO 8996, 2004, 8996 ISO
   ISO 9920, 2007, 9920 ISO
   Johansson E, 2018, INT J BIOMETEOROL, V62, P387, DOI 10.1007/s00484-017-1329-x
   Johansson E, 2014, URBAN CLIM, V10, P346, DOI 10.1016/j.uclim.2013.12.002
   Kántor N, 2012, INT J BIOMETEOROL, V56, P1075, DOI 10.1007/s00484-012-0523-0
   Knez I, 2006, INT J BIOMETEOROL, V50, P258, DOI 10.1007/s00484-006-0024-0
   Kotler P., 1999, MARK MANAG, V9th
   Kovács A, 2016, THEOR APPL CLIMATOL, V125, P113, DOI 10.1007/s00704-015-1488-9
   Lam CKC, 2018, URBAN CLIM, V23, P204, DOI 10.1016/j.uclim.2016.08.006
   Li KM, 2016, ENERG BUILDINGS, V133, P498, DOI 10.1016/j.enbuild.2016.10.013
   Lin TP, 2013, BUILD ENVIRON, V59, P599, DOI 10.1016/j.buildenv.2012.10.005
   Lin TP, 2011, TOURISM MANAGE, V32, P492, DOI 10.1016/j.tourman.2010.03.017
   Lin TP, 2010, BUILD ENVIRON, V45, P213, DOI 10.1016/j.buildenv.2009.06.002
   Lindner-Cendrowska K, 2018, INT J BIOMETEOROL, V62, P113, DOI 10.1007/s00484-016-1220-1
   Lindner-Cendrowska K, 2013, GEOGR POL, V86, P55, DOI 10.7163/GPol.2013.7
   Lopes HD, 2019, BULL GEOGR SOCIO-ECO, V46, P119, DOI 10.2478/bog-2019-0038
   M. da Economia, 2017, ESTR TUR 2027 LID TU
   Machete R, 2014, FINISTERRA, V49, P153
   Mansfeld Y., 2004, Proceedings NATO Advanced Research Workshop on Climate Change and Tourism, P116
   Martin BG, 2005, ANN TOURISM RES, V32, P571, DOI 10.1016/j.annals.2004.08.004
   MARTIN HDV, 1974, ERGONOMICS, V17, P221, DOI 10.1080/00140137408931341
   Matzarakis A., 2014, Sustainble Environmental Research, V24, P273
   Matzarakis A., 2010, Proceedings of the 7th Conference on Biometeorology, P392
   Matzarakis A, 2007, INT J BIOMETEOROL, V51, P323, DOI 10.1007/s00484-009-0261-0
   McKercher B, 2015, J TRAVEL RES, V54, P442, DOI 10.1177/0047287514522880
   Monteiro A, 2014, ERDE, V145, P80
   Monteiro A, 2013, INT J BIOMETEOROL, V57, P155, DOI 10.1007/s00484-012-0543-9
   Mora R, 2018, ASHRAE TRAN, V124, P11
   Morabito M, 2020, SCI TOTAL ENVIRON, V738, DOI 10.1016/j.scitotenv.2020.140347
   Morris Nathan B, 2020, Temperature (Austin), V8, P160, DOI 10.1080/23328940.2020.1826840
   Naboni E, 2017, ENRGY PROCED, V122, P1112, DOI 10.1016/j.egypro.2017.07.471
   Ndetto EL, 2015, AIR QUAL ATMOS HLTH, V8, P175, DOI 10.1007/s11869-014-0261-z
   Ndetto EL, 2013, ADV METEOROL, V2013, DOI 10.1155/2013/549096
   NIELSEN R, 1987, ERGONOMICS, V30, P1689, DOI 10.1080/00140138708966058
   Nikolopoulou M, 2001, SOL ENERGY, V70, P227, DOI 10.1016/S0038-092X(00)00093-1
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Oliveira S, 2007, INT J BIOMETEOROL, V52, P69, DOI 10.1007/s00484-007-0100-0
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Ramires A, 2018, J DESTIN MARK MANAGE, V8, P49, DOI 10.1016/j.jdmm.2016.12.001
   Ribeiro J., 2014, Noroeste Global
   Rutty M, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11040412
   Rutty M, 2015, INT J BIOMETEOROL, V59, P37, DOI 10.1007/s00484-014-0820-x
   Rutty M, 2014, TOURISM GEOGR, V16, P346, DOI 10.1080/14616688.2014.932833
   Rutty M, 2010, TOUR PLAN DEV, V7, P267, DOI 10.1080/1479053X.2010.502386
   Nouri AS, 2018, SUSTAIN CITIES SOC, V37, P7, DOI 10.1016/j.scs.2017.10.031
   Nouri AS, 2017, BUILD ENVIRON, V118, P67, DOI 10.1016/j.buildenv.2017.03.027
   Scott D, 2008, CLIM RES, V38, P61, DOI 10.3354/cr00774
   Silva Lopes H., 2016, TURISMO COMO ALAVANC
   Soares L., 2020, LANDSCAPES LANDFORMS, P281
   Spagnolo J, 2003, BUILD ENVIRON, V38, P721, DOI 10.1016/S0360-1323(02)00209-3
   Turismo de Portugal, 2015, TUR 2020 CINC PRINC
   UNWTO, 2020, WORST YEAR TOUR HIST
   UNWTO, 2021, INT TOUR HIGHL, V2019
   Xi TY, 2020, BUILD ENVIRON, V173, DOI 10.1016/j.buildenv.2020.106757
   Yasmeen R., 2019, Top 100 city destinations: 2019 edition
   Zhen M, 2021, J ASIAN ARCHIT BUILD, V20, P222, DOI 10.1080/13467581.2020.1782210
   Zikmund WG., 2003, Business Research Methods, V7
NR 99
TC 31
Z9 32
U1 6
U2 36
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-1323
EI 1873-684X
J9 BUILD ENVIRON
JI Build. Environ.
PD NOV
PY 2021
VL 205
AR 108246
DI 10.1016/j.buildenv.2021.108246
EA AUG 2021
PG 21
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Construction & Building Technology; Engineering
GA WC3MM
UT WOS:000704164100002
DA 2025-01-10
ER

PT J
AU Khadim, FK
   Dokou, Z
   Lazin, R
   Moges, S
   Bagtzoglou, AC
   Anagnostou, E
AF Khadim, Fahad Khan
   Dokou, Zoi
   Lazin, Rehenuma
   Moges, Semu
   Bagtzoglou, Amvrossios C.
   Anagnostou, Emmanouil
TI Groundwater modeling in data scarce aquifers: The case of Gilgel-Abay,
   Upper Blue Nile, Ethiopia
SO JOURNAL OF HYDROLOGY
LA English
DT Article
DE Groundwater model; MODFLOW-NWT; Gilgel-Abay; Upper Blue Nile; Lake Tana;
   Citizen science
ID LAKE TANA BASIN; ROCK UNDERGROUND EXCAVATIONS; RECHARGE RATE ESTIMATION;
   PERCHED WATER BODIES; HYDROLOGIC CONSTRAINTS; ARID ENVIRONMENTS;
   RIVER-BASIN; BALANCE; FLOW; CLIMATE
AB Groundwater (GW) is the main source of domestic water supply in Ethiopia (85%), however, despite widespread acknowledgement of its potential for resource-based development and climate change adaptation, the sector is still quite under-investigated. This is mainly due to the scarcity of in situ data, which are essential to building robust impact models. To address this, we developed a fine-resolution (500 m) GW model using MODFLOW-NWT, focusing on the Gilgel-Abay Catchment located in the Upper Blue Nile basin, fed with daily distributed input forcings of recharge and streamflow simulated by the Coupled Routing and Excess Storage (CREST) hydrological model. The model was calibrated against instantaneous observation records of GW table for 38 historical wells, and validated at selected sites using time series data collected from the Citizen Science Initiative (PIRE CSI), and the Innovation Lab for Small Scale Irrigation (ILSSI) project. An RMSE of 14.4 m (1.8% of range) was achieved for calibration and same for validation was 18.21 m and 15.76 mat the PIRE CSI and ILSSI sites, respectively. The findings of this research indicate substantial physical GW resource availability in the Gilgel-Abay region. Moreover, we expect the model to have multiscale future applications. These include obtaining dynamically downscaled boundary conditions for a local-scale GW model, to be developed in the next phase of our research. Further, an upscaled version of this model to encompass the entire Tana Basin would be developed to simulate lake-aquifer interactions. Finally, the approach of this research combining different types of datasets (e.g., reanalysis products, satellite data, citizen science data, etc.) is adaptable to other global data-scarce regions. Moreover, the method overcomes specific challenges associated to in situ data scarcity, limited knowledge on GW resources availability in the area, interaction with complex boundary conditions, and sensitivity under meteorological boundary forcings.
C1 [Khadim, Fahad Khan; Lazin, Rehenuma; Moges, Semu; Bagtzoglou, Amvrossios C.; Anagnostou, Emmanouil] Univ Connecticut, Dept Civil & Environm Engn, Storrs, CT 06269 USA.
   [Dokou, Zoi] Calif State Univ Sacramento, Dept Civil Engn, 6000 J St, Sacramento, CA 95819 USA.
C3 University of Connecticut; California State University System;
   California State University Sacramento
RP Dokou, Z (corresponding author), Calif State Univ Sacramento, Dept Civil Engn, 6000 J St, Sacramento, CA 95819 USA.
EM zoi.dokou@csus.edu
RI Lazin, Rehenuma/GPK-6157-2022; Bagtzoglou, Amvrossios/AAG-6598-2019
OI Lazin, Rehenuma/0000-0002-9838-2160; Khadim, Fahad
   Khan/0000-0002-0899-3540; Dokou, Zoi/0000-0003-0879-3423
FU National Science Foundation [1545874]; Abay Basin Authority (ABA)
   -Ethiopia; Bahir Dar University (BU) -Ethiopia; Ministry of Water,
   Irrigation, and Energy-Ethiopia
FX This research is based upon work supported by the National Science
   Foundation under Grant No. 1545874. The authors would like to thank all
   the supporting agencies, e.g. Abay Basin Authority (ABA) -Ethiopia,
   Bahir Dar University (BU) -Ethiopia, and the Ministry of Water,
   Irrigation, and Energy-Ethiopia for their continuous support during the
   completion of this research. In particular, we would like to thank Dr.
   Seifu Tilahun and Dr. Mamaru Moges of BU for coordinating the citizen
   science project and data collection. We would also like to acknowledge
   the Innovation Lab for Small Scale Irrigation (ILSSI) project for
   providing us in-situ information on GW well depths, which was used to
   validate our model. Finally, the authors would like to thank Kristi
   Arsenault (NASA/GSFC) for kindly sharing the results of the models
   developed under the Forecasting for Africa and the Middle East (FAME)
   project, which were used to compare our regional groundwater model
   estimations.
CR Abiy AZ, 2016, SPRING GEOGR, P463, DOI 10.1007/978-3-319-18787-7_22
   Arsenault KR, 2020, B AM METEOROL SOC, V101, pE1007, DOI 10.1175/BAMS-D-18-0264.1
   Asfaw B., 2003, REGIONAL HYDROGEOLOG
   Asrie NA, 2016, J AGRIC ENVIRON INT, V110, P5, DOI 10.12895/jaeid.20161.380
   AWULACHEW S.B., 2008, A review of hydrology, sediment and water resource use in the Blue Nile Basin, Iwmi
   Aydin A, 2000, MAR PETROL GEOL, V17, P797, DOI 10.1016/S0264-8172(00)00020-9
   Ayenew T., 2001, SINET: Ethiop. J. Sci., V24, P167, DOI [10.4314/sinet.v24i2.18184, DOI 10.4314/SINET.V24I2.18184]
   Ayenew T, 2008, J AFR EARTH SCI, V52, P97, DOI 10.1016/j.jafrearsci.2008.06.006
   Bagtzoglou AC, 2003, ENVIRON FORENSICS, V4, P47, DOI 10.1080/15275920303491
   Bagtzoglou AC, 2003, ENVIRON FORENSICS, V4, P39, DOI 10.1080/15275920303488
   Bagtzoglou AC, 2007, ENVIRON GEOL, V51, P1285, DOI 10.1007/s00254-006-0422-y
   Bagtzoglou AC, 2007, ENVIRON GEOL, V51, P1295, DOI 10.1007/s00254-006-0423-x
   Bakker M., 2016, SCRIPTING MODFLOW MO
   BCEOM, 1999, AB RIV BAS INT MAST
   Bhuiyan M.A.E., 2019, HYDROL EARTH SYST SC
   Bhuiyan MAE, 2018, HYDROL EARTH SYST SC, V22, P1371, DOI 10.5194/hess-22-1371-2018
   Buytaert W, 2014, FRONT EARTH SC-SWITZ, V2, DOI 10.3389/feart.2014.00026
   Caine JS, 1996, GEOLOGY, V24, P1025, DOI 10.1130/0091-7613(1996)024<1025:FZAAPS>2.3.CO;2
   Candela L, 2014, HYDROL PROCESS, V28, P3714, DOI 10.1002/hyp.9901
   Chebud YA, 2009, HYDROL PROCESS, V23, P3694, DOI 10.1002/hyp.7516
   Colchester FE, 2017, ENVIRON MODELL SOFTW, V91, P241, DOI 10.1016/j.envsoft.2017.01.026
   Conway D, 1997, HYDROLOG SCI J, V42, P265, DOI 10.1080/02626669709492024
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Döll P, 2014, WATER RESOUR RES, V50, P5698, DOI 10.1002/2014WR015595
   Dokou Z., 2018, AGU FALL M
   Domenico P., 1998, PHYS CHEM HYDROGEOLO, V2nd
   Enku T, 2017, LAND DEGRAD DEV, V28, P1831, DOI 10.1002/ldr.2650
   Fan Y, 2013, SCIENCE, V339, P940, DOI 10.1126/science.1229881
   Franke O.L., 1987, Techniques of Water-Resources Investigations of the U.S. Geological Survey
   Gamvroudis C, 2017, ENVIRON EARTH SCI, V76, DOI 10.1007/s12665-017-6721-7
   Giordano M, 2009, ANNU REV ENV RESOUR, V34, P153, DOI 10.1146/annurev.environ.030308.100251
   Gorelick SM, 2015, WATER RESOUR RES, V51, P3031, DOI 10.1002/2014WR016825
   Guariso G., 1987, INT J WATER RESOUR D, V3, P105, DOI DOI 10.1080/07900628708722338
   Guzman JA, 2015, ENVIRON MODELL SOFTW, V73, P103, DOI 10.1016/j.envsoft.2015.08.011
   Haile AT, 2009, J APPL METEOROL CLIM, V48, P1696, DOI 10.1175/2009JAMC2092.1
   Haile G. G., 2015, Academia Journal of Agricultural Research, V3, P264
   Harbaugh A.W., 2005, FLOW PROCESS
   Hautot S, 2006, J AFR EARTH SCI, V44, P331, DOI 10.1016/j.jafrearsci.2005.11.027
   Huffman G.J., 2019, INTEGRATED MULTISATE
   Ochoa-González GH, 2015, GEOFIS INT, V54, P199, DOI 10.1016/j.gi.2015.04.016
   Ireson A, 2006, WATER RESOUR MANAG, V20, P567, DOI 10.1007/s11269-006-3085-2
   JOHNSON PA, 1994, J IRRIG DRAIN ENG, V120, P573, DOI 10.1061/(ASCE)0733-9437(1994)120:3(573)
   JONES MJ, 1985, Q J ENG GEOL, V18, P35, DOI 10.1144/GSL.QJEG.1985.018.01.06
   Kebede S, 2006, J HYDROL, V316, P233, DOI 10.1016/j.jhydrol.2005.05.011
   Kebede S, 2005, APPL GEOCHEM, V20, P1658, DOI 10.1016/j.apgeochem.2005.04.016
   Kebede S., 2012, GROUNDWATER ETHIOPIA
   Kleist DT, 2009, MON WEATHER REV, V137, P1046, DOI 10.1175/2008MWR2623.1
   Lazin R, 2020, J HYDROL, V590, DOI 10.1016/j.jhydrol.2020.125231
   Legesse D, 2004, HYDROL PROCESS, V18, P487, DOI 10.1002/hyp.1334
   Li JD, 2016, J HYDROL ENG, V21, DOI 10.1061/(ASCE)HE.1943-5584.0001353
   Lijalem G.A., 2018, IRRIGATION PERFORMAN
   Llamas M.R., 2005, J WATER RESOUR PLAN, P131
   MacDonald AM, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/2/024009
   Massuel S, 2017, HYDROGEOL J, V25, P1565, DOI 10.1007/s10040-017-1573-5
   Maxwell RM, 2015, GEOSCI MODEL DEV, V8, P923, DOI 10.5194/gmd-8-923-2015
   Maxwell RM, 2005, J HYDROMETEOROL, V6, P233, DOI 10.1175/JHM422.1
   McCartney MP, 2012, WATER INT, V37, P362, DOI 10.1080/02508060.2012.706384
   McNally A, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.12
   Mechal A, 2015, J HYDROL-REG STUD, V4, P644, DOI 10.1016/j.ejrh.2015.09.001
   Mengistu H.A., 2019, HYDROGEOL J, P1
   Mengistu S.W.Y, 2010, NUMERICAL GROUNDWATE
   Näschen K, 2018, WATER-SUI, V10, DOI 10.3390/w10050599
   Nelson RL, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010927
   Nigate F, 2016, J AFR EARTH SCI, V121, P154, DOI 10.1016/j.jafrearsci.2016.05.015
   Niswonger R.G., 2005, GEOLOGICAL SURVEY TE, P50
   Oliver M. A., 1990, International Journal of Geographical Information Systems, V4, P313, DOI 10.1080/02693799008941549
   Pande S, 2012, WATER RESOUR MANAG, V26, P909, DOI 10.1007/s11269-011-9816-z
   Papadopoulou MP, 2010, ENVIRON MODEL ASSESS, V15, P319, DOI 10.1007/s10666-009-9207-5
   Reilly T.E., 2004, GUIDELINES EVALUATIN
   Setegn SG, 2010, HYDROL PROCESS, V24, P357, DOI 10.1002/hyp.7457
   Shah T., 2010, TAMING ANARCHY GROUN, DOI DOI 10.4324/9781936331598
   Shen XY, 2017, J HYDROL, V552, P1, DOI 10.1016/j.jhydrol.2017.05.048
   Shukla S, 2020, NAT HAZARD EARTH SYS, V20, P1187, DOI 10.5194/nhess-20-1187-2020
   SMEC, 2007, Technical report
   Sutanudjaja EH, 2011, HYDROL EARTH SYST SC, V15, P2913, DOI 10.5194/hess-15-2913-2011
   SUTCLIFFE JV, 1987, HYDROLOG SCI J, V32, P143, DOI 10.1080/02626668709491174
   Tegegne G, 2017, J HYDROL-REG STUD, V14, P49, DOI 10.1016/j.ejrh.2017.10.002
   Tilahun SA, 2020, HYDROL PROCESS, V34, P1741, DOI 10.1002/hyp.13659
   Tindimugaya C.B, 2012, HYDROGEOL J, P1
   Trichakis I, 2017, ENVIRON PROCESS, V4, pS81, DOI 10.1007/s40710-017-0216-0
   Walker D, 2019, HYDROLOGY-BASEL, V6, DOI 10.3390/hydrology6020043
   Walker D, 2016, J HYDROL, V538, P713, DOI 10.1016/j.jhydrol.2016.04.062
   Walraevens K, 2015, LAND DEGRAD DEV, V26, P725, DOI 10.1002/ldr.2377
   Walraevens K, 2009, HYDROLOG SCI J, V54, P739, DOI 10.1623/hysj.54.4.739
   Winston R.B., 2017, USGS OPEN-FILE REP
   WOOD RB, 1988, HYDROBIOLOGIA, V158, P29, DOI 10.1007/BF00026266
   Yamazaki D, 2017, GEOPHYS RES LETT, V44, P5844, DOI 10.1002/2017GL072874
NR 87
TC 29
Z9 29
U1 0
U2 14
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0022-1694
EI 1879-2707
J9 J HYDROL
JI J. Hydrol.
PD NOV
PY 2020
VL 590
AR 125214
DI 10.1016/j.jhydrol.2020.125214
PG 16
WC Engineering, Civil; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA PG5DE
UT WOS:000599754500018
DA 2025-01-10
ER

PT J
AU Wang, J
   Zhang, XY
   Su, L
   Li, HY
   Zhang, L
   Wei, JG
AF Wang, Jing
   Zhang, Xiaoyu
   Su, Long
   Li, Hongying
   Zhang, Lei
   Wei, Jianguo
TI Global warming effects on climate zones for wine grape in Ningxia
   region, China
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
AB Against the background of global warming, the climatic suitability for growing usual crops has been changing in certain regions. In this study, we focused on the Ningxia Plain in China, an important wine grape (Vitis vinifera L.) growing region. Based on the daily average air temperature data from 1981 to 2017, we investigated changes in the planting boundaries of different climate zones for wine grape before and after 1997 (when an abrupt change in regional air temperature occurred). The goal of this study is to provide scientific evidence for local agricultural authorities to make long-term climate change adaptation plans. We used the effective accumulated temperature as an indicator to evaluate the inter-decadal changes in the climate zones for wine grape. We concluded as follows: (1) since the abrupt change in regional air temperature in 1997, the subtotal area of climate zone I for wine grape was reduced by 31%, while the subtotal area of climate zone II (moved southward) and III (part of climate zone II in the northern part of the region turned into climate zone III) for wine grape was expanded by 7% and 24%, respectively; (2) during the 1990s, climate zone III for wine grape emerged in the study region; during the 2000s, the planting boundaries of climate zone II and III moved southward; during the period of 2011-2017, climate zone I (suitable) for wine grape mostly vanished in the Ningxia Plain; and (3) since the abrupt change in regional air temperature in 1997, most of the area in the Eastern Foothills of the Helan Mountains turned from climate zone II to climate zone III for wine grape, with the exceptions of Hongsipu district and the relatively high altitude area. During the 37 study years, most of the area in the study region remained as climate zone II for wine grape with a probability of 80%. Overall, the climate zones for wine grape in Ningxia, China have changed against the background of global warming. In particular, the wine grape varieties and wine types are expected to be changed in the Helan Mountains area in order to adapt to the ongoing climate change.
C1 [Wang, Jing; Zhang, Xiaoyu; Li, Hongying; Zhang, Lei; Wei, Jianguo] China Meteorol Adm, Key Lab Meteorol Disaster Monitoring & Early Warn, Yinchuan 750002, Ningxia, Peoples R China.
   [Wang, Jing; Zhang, Xiaoyu; Li, Hongying; Zhang, Lei; Wei, Jianguo] Ningxia Key Lab Meteorol Disaster Prevent & Reduc, Yinchuan 750002, Ningxia, Peoples R China.
   [Wang, Jing; Zhang, Xiaoyu; Li, Hongying; Zhang, Lei] Ningxia Meteorol Sci Inst, Yinchuan 750002, Ningxia, Peoples R China.
   [Su, Long] Domaine Chandon Ningxia Moet Hennessy Co Ltd, Yongning 750100, Peoples R China.
   [Wei, Jianguo] Ningxia Meteorol Informat Ctr, Yinchuan 750002, Ningxia, Peoples R China.
C3 China Meteorological Administration
RP Zhang, XY (corresponding author), China Meteorol Adm, Key Lab Meteorol Disaster Monitoring & Early Warn, Yinchuan 750002, Ningxia, Peoples R China.; Zhang, XY (corresponding author), Ningxia Key Lab Meteorol Disaster Prevent & Reduc, Yinchuan 750002, Ningxia, Peoples R China.; Zhang, XY (corresponding author), Ningxia Meteorol Sci Inst, Yinchuan 750002, Ningxia, Peoples R China.
EM zhang_xynet@163.com
RI Jiang, Wei/AAD-4758-2020; zhang, xiaoyu/HJI-4374-2023
FU National Natural Science Foundation of China [41675114]; Climate Change
   Special Fund of China Meteorological Administration [CCSF201511]; Key
   Research and Development Program of Ningxia Hui autonomous region [2018
   BFH03012]; Natural Science Foundation of Ningxia [NZ16202]
FX This study is funded by National Natural Science Foundation of China
   (Grant no. 41675114), Climate Change Special Fund of China
   Meteorological Administration (Grant no. CCSF201511), Key Research and
   Development Program of Ningxia Hui autonomous region (Grant no. 2018
   BFH03012), and Natural Science Foundation of Ningxia (Grant no.
   NZ16202).
CR Amerine M. A., 1944, HILGARDIA, V15, P493
   [Anonymous], 2013, WORK GROUP CONTR IPC
   Butterfield RE, 2000, CLIMATE CHANGE CLIMA, P265
   de Orduña RM, 2010, FOOD RES INT, V43, P1844, DOI 10.1016/j.foodres.2010.05.001
   [方锋 FANG Feng], 2007, [高原气象, Plateau Meteorology], V26, P579
   Foster G, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/4/044022
   Hall A, 2016, INT J BIOMETEOROL, V60, P1405, DOI 10.1007/s00484-016-1133-z
   Han S., 2018, ANN REV CONTROL ROBO, V1, P1, DOI DOI 10.1007/S00704-018-2461-1
   IPCC, 2013, WARM CLIM SYST UN RE
   Jones GV, 2005, ACTA HORTIC, P41, DOI 10.17660/ActaHortic.2005.689.2
   Jones GV, 2005, CLIMATIC CHANGE, V73, P319, DOI 10.1007/s10584-005-4704-2
   Jones GV, 2006, CLIMATE TERRROIR IMP
   Li Q, 2004, THEOR APPL CLIMATOL, V79, P165, DOI 10.1007/s00704-004-0065-4
   [梁珑腾 Liang Longteng], 2018, [自然资源学报, Journal of Natural Resources], V33, P2149
   Mozell M. R., 2014, Wine Economics and Policy, V3, P81, DOI 10.1016/j.wep.2014.08.001
   Ollat N, 2017, OENO ONE, V51, P59, DOI 10.20870/oeno-one.2016.0.0.1872
   Pan C, 2018, NEUROCOMPUTING, V275, P2512, DOI 10.1016/j.neucom.2017.11.035
   Qu ML, 1991, AGRO CLIMATIC INTERN
   [商沙沙 Shang Shasha], 2018, [干旱区研究, Arid Zone Research], V35, P68
   Tate A. B., 2001, Journal of Wine Research, V12, P95, DOI 10.1080/09571260120095012
   van Leeuwen C, 2004, AM J ENOL VITICULT, V55, P207
   van Leeuwen C, 2016, J WINE ECON, V11, P150, DOI 10.1017/jwe.2015.21
   [王素艳 Wang Suyan], 2017, [生态学报, Acta Ecologica Sinica], V37, P3776
   White MA, 2006, P NATL ACAD SCI USA, V103, P11217, DOI 10.1073/pnas.0603230103
   Winkler A.J., 1974, GEN VITICULTURE, P58
   Yang Xiao-guang, 2011, Yingyong Shengtai Xuebao, V22, P3177
   Yang XG, 2015, AGR FOREST METEOROL, V208, P76, DOI 10.1016/j.agrformet.2015.04.024
   Ye Q, 2015, AGR WATER MANAGE, V159, P35, DOI 10.1016/j.agwat.2015.05.022
   [尹云鹤 YIN Yun-he], 2009, [自然资源学报, Journal of Natural Resources], V24, P2147
   Zhang Xiao-yu, 2014, Shengtaixue Zazhi, V33, P3112
NR 30
TC 20
Z9 22
U1 7
U2 86
PU SPRINGER WIEN
PI WIEN
PA SACHSENPLATZ 4-6, PO BOX 89, A-1201 WIEN, AUSTRIA
SN 0177-798X
EI 1434-4483
J9 THEOR APPL CLIMATOL
JI Theor. Appl. Climatol.
PD MAY
PY 2020
VL 140
IS 3-4
BP 1527
EP 1536
DI 10.1007/s00704-020-03170-y
EA MAR 2020
PG 10
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA LJ1HE
UT WOS:000520806500002
DA 2025-01-10
ER

PT J
AU Zander, KK
   Richerzhagen, C
   Garnett, ST
AF Zander, Kerstin K.
   Richerzhagen, Carmen
   Garnett, Stephen T.
TI Human mobility intentions in response to heat in urban South East Asia
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate change adaptation; Indonesia; Malaysia; Migration intentions;
   Protection motivation theory; Philippines
ID PROTECTION MOTIVATION THEORY; CLIMATE-CHANGE; HUMAN MIGRATION;
   OUT-MIGRATION; FEAR APPEALS; ADAPTATION; IMPACT; RISK; TEMPERATURE;
   VARIABILITY
AB Climate change and associated weather extremes and natural hazards have large impacts on the urban population of the Global South where population growth will rapidly increase the already large number of people who will be affected. Using Protection Motivation Theory (PMT), we investigate how hot temperatures, manifested as heat stress, is affecting the intentions of moving among the urban population in three Asian countries (Indonesia, Malaysia, Philippines). We conducted an online survey with 2219 respondents. Almost all respondents (98%) had experienced heat stress, albeit at different levels. When asked whether respondents would be likely to move away from their current locations because of heat, nearly a quarter (23%) reported that they were very likely to do so, and 50% that they probably would. Stronger moving intentions because of heat were associated with women and older people. Concerns about increases from damage from heat (threat appraisal) were more strongly associated with moving intentions than an understanding of the costs and benefits (coping appraisal). Among the threat appraisal, heat stress levels and risk perception were the strongest predictors of moving intentions because of heat. The results contrast with the findings of migration studies in response to sudden onset hazards and underpin the differences in adaptation behaviour in response to different climate change impacts. Moving away to cooler places as an adaptation strategy to heat may be challenging to foresee in terms of timing, capabilities, destination and potential costs because it may not happen soon. We strongly recommend further research on climate change migration of the urban population, including within urban and urban-to-urban movements. While many people move back after sudden onset disasters, heat potentially leads to permanent movements given it is likely to be better planned, and as the habitability of some places is increasingly compromised. Overall the effects of slow onset environmental hazards such as pollution and heat on migration warrant more research attention given the rapidity of urban population growth, particularly in the global south.
C1 [Zander, Kerstin K.] Charles Darwin Univ, Northern Inst, Darwin, NT, Australia.
   [Zander, Kerstin K.; Richerzhagen, Carmen] German Dev Inst, Bonn, Germany.
   [Garnett, Stephen T.] Charles Darwin Univ, Res Inst Environm & Livelihoods, Darwin, NT, Australia.
C3 Charles Darwin University; Deutsches Institut Entwicklungspolitik (DIE);
   Charles Darwin University
RP Zander, KK (corresponding author), Charles Darwin Univ, Northern Inst, Darwin, NT, Australia.
EM kerstin.zander@cdu.edu.au
RI Garnett, Stephen/M-3877-2013; Zander, Kerstin/M-2888-2013
OI Zander, Kerstin/0000-0002-2237-1801
FU Faculty of Law, Education, Business and Arts (LEBA) at Charles Darwin
   University - Alexander von Humboldt Foundation
FX We are grateful for the financial support from the Faculty of Law,
   Education, Business and Arts (LEBA) at Charles Darwin University who
   sponsored this research through its small grant scheme. The lead author
   is funded by the Alexander von Humboldt Foundation.
CR Abrahamson V, 2009, J PUBLIC HEALTH-UK, V31, P119, DOI 10.1093/pubmed/fdn102
   Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Ajzen I., 2010, PREDICTING CHANGING
   Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   [Anonymous], 2018, GLOB COMP SAF ORD RE
   [Anonymous], PROGR HUMAN GEOGRAPH
   [Anonymous], 2017, EXTREME HEAT MIGRATI
   [Anonymous], REVERSE MIGRATION PO
   [Anonymous], 2015, ANN REV SOCIOL
   [Anonymous], TAL 3 CIT HEAT ACT P
   [Anonymous], 48 SESS IPCC
   [Anonymous], OCCUP ENV MED
   [Anonymous], 2003, The Vulnerability of Cities: Natural Disasters and Social Resilience
   [Anonymous], 2014, DEMOGR RES
   Bakhsh K, 2018, SUSTAIN CITIES SOC, V41, P95, DOI 10.1016/j.scs.2018.05.021
   Bardsley DK, 2010, POPUL ENVIRON, V32, P238, DOI 10.1007/s11111-010-0126-9
   Beattie James, 2012, Health History, V14, P100
   Black R, 2011, NATURE, V478, P447, DOI 10.1038/478477a
   Black R, 2011, ENVIRON PLANN A, V43, P431, DOI 10.1068/a43154
   Bohra-Mishra P, 2017, POPUL ENVIRON, V38, P286, DOI 10.1007/s11111-016-0263-x
   Bohra-Mishra P, 2014, P NATL ACAD SCI USA, V111, P9780, DOI 10.1073/pnas.1317166111
   Bubeck P, 2013, GLOBAL ENVIRON CHANG, V23, P1327, DOI 10.1016/j.gloenvcha.2013.05.009
   Cattaneo C, 2016, J DEV ECON, V122, P127, DOI 10.1016/j.jdeveco.2016.05.004
   Chen S., 2017, NBER WORKING PAPER S
   Choi N, 2016, URBAN STUD, V53, P577, DOI 10.1177/0042098014543032
   Crone DL, 2017, AUST J PSYCHOL, V69, P39, DOI 10.1111/ajpy.12110
   de Munck C, 2013, INT J CLIMATOL, V33, P210, DOI 10.1002/joc.3415
   Elliott JR, 2006, SOC SCI RES, V35, P295, DOI 10.1016/j.ssresearch.2006.02.003
   Estoque RC, 2016, LANDSCAPE ECOL, V31, P1481, DOI 10.1007/s10980-016-0341-6
   Falco C, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10051405
   Floyd DL, 2000, J APPL SOC PSYCHOL, V30, P407, DOI 10.1111/j.1559-1816.2000.tb02323.x
   Goldbach C, 2017, CESIFO ECON STUD, V63, P529, DOI 10.1093/cesifo/ifx007
   Goodman JK, 2013, J BEHAV DECIS MAKING, V26, P213, DOI 10.1002/bdm.1753
   Gosling SN, 2009, CLIMATIC CHANGE, V92, P299, DOI [10.1007/s10584-008-9441-x, 10.1007/S10584-008-9441-X]
   Gray C, 2016, CLIMATIC CHANGE, V135, P555, DOI 10.1007/s10584-015-1592-y
   Gray CL, 2012, P NATL ACAD SCI USA, V109, P6000, DOI 10.1073/pnas.1115944109
   Green W., 2000, Econometric Analysis, Vfifth
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Grothmann T, 2006, NAT HAZARDS, V38, P101, DOI 10.1007/s11069-005-8604-6
   Hajat S, 2010, LANCET, V375, P856, DOI 10.1016/S0140-6736(09)61711-6
   Henry S, 2004, POPUL ENVIRON, V25, P423, DOI 10.1023/B:POEN.0000036928.17696.e8
   Hugo G, 2011, GLOBAL ENVIRON CHANG, V21, pS21, DOI 10.1016/j.gloenvcha.2011.09.008
   Hunter LM, 2014, POPUL SPACE PLACE, V20, P402, DOI 10.1002/psp.1776
   López-Sánchez JI, 2018, INT J HYPERTHER, V34, P423, DOI 10.1080/02656736.2017.1345013
   International Energy Agency, 2018, The Future of Cooling: Opportunities for Energy-Efficient Air-Conditioning
   Jamero ML, 2017, NAT CLIM CHANGE, V7, P581, DOI [10.1038/nclimate3344, 10.1038/NCLIMATE3344]
   Jha CK, 2018, INT J CLIM CHANG STR, V10, P121, DOI 10.1108/IJCCSM-03-2017-0059
   Jylhä M, 2009, SOC SCI MED, V69, P307, DOI 10.1016/j.socscimed.2009.05.013
   Keshavarz M, 2016, J ARID ENVIRON, V127, P128, DOI 10.1016/j.jaridenv.2015.11.010
   Kniveton D, 2017, NAT CLIM CHANGE, V7, P548, DOI 10.1038/nclimate3346
   Koerth J, 2013, REG ENVIRON CHANGE, V13, P897, DOI 10.1007/s10113-012-0399-x
   Koubi V, 2016, CLIMATIC CHANGE, V138, P439, DOI 10.1007/s10584-016-1767-1
   Krellenberg K, 2017, PROG HUM GEOG, V41, P408, DOI 10.1177/0309132516645959
   Lundgren-Kownacki K, 2018, INT J BIOMETEOROL, V62, P401, DOI 10.1007/s00484-017-1493-z
   Ma WJ, 2011, SCI TOTAL ENVIRON, V409, P3634, DOI 10.1016/j.scitotenv.2011.06.042
   MADDUX JE, 1983, J EXP SOC PSYCHOL, V19, P469, DOI 10.1016/0022-1031(83)90023-9
   Martin IM, 2007, RISK ANAL, V27, P887, DOI 10.1111/j.1539-6924.2007.00930.x
   Matthews TKR, 2017, P NATL ACAD SCI USA, V114, P3861, DOI 10.1073/pnas.1617526114
   McLeman R, 2018, POPUL ENVIRON, V39, P319, DOI 10.1007/s11111-017-0290-2
   Mendelsohn R, 2014, J INTEGR AGR, V13, P660, DOI 10.1016/S2095-3119(13)60701-7
   Mertens K, 2018, LAND USE POLICY, V75, P77, DOI 10.1016/j.landusepol.2018.01.028
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Mueller V, 2014, NAT CLIM CHANGE, V4, P182, DOI [10.1038/nclimate2103, 10.1038/NCLIMATE2103]
   Nawrotzki RJ, 2017, POPUL SPACE PLACE, V23, DOI 10.1002/psp.2033
   Nawrotzki RJ, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/11/114023
   Nawrotzki RJ, 2014, SOC NATUR RESOUR, V27, P215, DOI 10.1080/08941920.2013.842275
   Nielsen JS, 2011, RESOUR ENERGY ECON, V33, P119, DOI 10.1016/j.reseneeco.2010.01.006
   Nitschke M, 2011, ENVIRON HEALTH-GLOB, V10, DOI 10.1186/1476-069X-10-42
   Ohira T, 2013, CIRC J, V77, P1646, DOI 10.1253/circj.CJ-13-0702
   Parsons L, 2019, PROG HUM GEOG, V43, P670, DOI 10.1177/0309132518781011
   Perkins SE, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL053361
   Piguet E, 2018, POPUL ENVIRON, V39, P357, DOI 10.1007/s11111-018-0296-4
   Raftery AE, 2017, NAT CLIM CHANGE, V7, P637, DOI [10.1038/nclimate3352, 10.1038/NCLIMATE3352]
   Ramachandran A, 2012, WORLD J DIABETES, V3, P110, DOI 10.4239/wjd.v3.i6.110
   Rise J, 2003, SCAND J PSYCHOL, V44, P87, DOI 10.1111/1467-9450.00325
   Rogers R. W., 1983, Social psychophysiology: A source book, P153
   ROGERS RW, 1975, J PSYCHOL, V91, P93, DOI 10.1080/00223980.1975.9915803
   Rossi F, 2015, APPL ENERG, V145, P8, DOI 10.1016/j.apenergy.2015.01.129
   Ruiter RAC, 2014, INT J PSYCHOL, V49, P63, DOI 10.1002/ijop.12042
   Santamouris M, 2015, ENERG BUILDINGS, V98, P119, DOI 10.1016/j.enbuild.2014.09.052
   Schuster C, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5f35
   Speelman LH, 2017, SUSTAIN SCI, V12, P433, DOI 10.1007/s11625-016-0410-4
   Stewart N, 2017, TRENDS COGN SCI, V21, P736, DOI 10.1016/j.tics.2017.06.007
   Stockdale A, 2014, POPUL SPACE PLACE, V20, P83, DOI 10.1002/psp.1758
   Stojanov R, 2017, GEOGR J, V183, P370, DOI 10.1111/geoj.12177
   Sulser F., 2014, PROC INT ACM WORKSHO, P63, DOI DOI 10.1145/2660114
   Sultan B, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104006
   Thiede BC, 2017, POPUL ENVIRON, V39, P147, DOI 10.1007/s11111-016-0265-8
   van Dalen HP, 2012, POPUL SPACE PLACE, V18, P31, DOI 10.1002/psp.642
   Warner K, 2014, CLIM DEV, V6, P1, DOI 10.1080/17565529.2013.835707
   Wilhelmi OV, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014021
   Windle J, 2011, ECON ANAL POLICY, V41, P83, DOI 10.1016/S0313-5926(11)50006-2
   Witvorapong N, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0130862
   Wolch JR, 2014, LANDSCAPE URBAN PLAN, V125, P234, DOI 10.1016/j.landurbplan.2014.01.017
   Wouters H, 2017, GEOPHYS RES LETT, V44, P8997, DOI 10.1002/2017GL074889
   Xiao H, 2014, PLOS NEGLECT TROP D, V8, DOI 10.1371/journal.pntd.0003246
   Zander KK, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aad2e5
   Zander KK, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15030401
   Zander KK, 2016, CLIMATIC CHANGE, V138, P297, DOI 10.1007/s10584-016-1727-9
   Zander KK, 2015, NAT CLIM CHANGE, V5, P647, DOI [10.1038/NCLIMATE2623, 10.1038/nclimate2623]
   Zhao Y, 2016, P NATL ACAD SCI USA, V113, P4640, DOI 10.1073/pnas.1521828113
NR 102
TC 49
Z9 51
U1 2
U2 52
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD MAY
PY 2019
VL 56
BP 18
EP 28
DI 10.1016/j.gloenvcha.2019.03.004
PG 11
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA IB1VN
UT WOS:000470053200003
DA 2025-01-10
ER

PT J
AU Mahmood, S
   Khan, AU
   Mayo, SM
AF Mahmood, Shakeel
   Khan, Amin-ul-Haq
   Mayo, Shaker Mahmood
TI Exploring underlying causes and assessing damages of 2010 flash flood in
   the upper zone of Panjkora River
SO NATURAL HAZARDS
LA English
DT Article
DE Flash flood; Underlying causes; GIS; GPS; Damages
ID RISK-MANAGEMENT; IMPACT; VULNERABILITY; PAKISTAN; SYSTEM; SCALE; BASIN
AB The paper assesses the damage caused by 2010 flash flood and its underlying causes in the upper zone of Panjkora River within district Dir Upper, Khyber Pakhtunkhwa (KP) Province in Pakistan. Floods in general and flash floods in particular are very common in the area, and the phenomenon has intensified in the wake of observed climatic changes in the region. Anticipating an increase in the multiplicity of causes and a rise in the human, livelihood, and property losses attributed to flash floods calls for a detailed study of affected communities in the region. Within the study area of District Dir Upper-within the band of 200 m on both sides of Panjkora River, three most affected communities, namely Barikot, Kalkot, and Sharingal, were picked on random basis to have detailed analysis of underlying causes and the quantification of damage assessment in the area. Questionnaire-based household survey and structured interviews were conducted to investigate physical and economic damages in the sample sites. Global positioning system (GPS) survey is also conducted to acquire absolute location of damages, and geographic information system is used to visualize land use, land cover, physical features, and GPS data. Monsoon winds interacted with the westerlies abnormally caused unprecedented high intensity rainfall in the valley. The steep topography of the area caused rainwater to accumulate rapidly in the Panjkora River channel, overpowering the withholding capacity of the river. The flash flood inflected heavy losses to life and properties of the local population. The infrastructure such as houses, roads, retaining walls, bridges, water supply schemes, and irrigation channels were destroyed severely in the whole area particularly in Kalkot. Three explored underlying causes of flash floods and the degree of damage due to 2010 flash floods in the region call for an enhanced realization for climatic change adaptability, flood risk management, and mitigation measures, better flood response through early warning systems, and improved rehabilitation and recovery efforts within flood prone areas such as district Dir Upper, KP, Pakistan.
C1 [Mahmood, Shakeel] Govt Coll Univ, Dept Geog, Lahore, Pakistan.
   [Khan, Amin-ul-Haq] Govt Coll Univ, Sustainable Dev Study Ctr, Lahore, Pakistan.
   [Mayo, Shaker Mahmood] UET, Dept City & Reg Planning, Lahore, Pakistan.
C3 Government College University Lahore; Government College University
   Lahore
RP Mahmood, S (corresponding author), Govt Coll Univ, Dept Geog, Lahore, Pakistan.
EM shakeelmahmood@gcu.edu.pk
RI Mahmood, Shakeel/GQH-3340-2022
OI Mahmood, Shakeel/0000-0001-6909-0735
CR Ahmad I, 2015, ADV METEOROL, V2015, DOI 10.1155/2015/431860
   Alderman K, 2012, ENVIRON INT, V47, P37, DOI 10.1016/j.envint.2012.06.003
   [Anonymous], 1965, FOREST TYPES PAKISTA
   Anwar Sajjad Anwar Sajjad, 2015, American Journal of Plant Sciences, V6, P1501
   Asgharpour SE, 2011, PROCD SOC BEHV, V19, P556, DOI 10.1016/j.sbspro.2011.05.169
   Atta-ur R, 2011, NAT HAZARDS, V59, P1239, DOI DOI 10.1007/S11069-0011-9830-8
   Atta-ur-Rahman, 2013, NAT HAZARDS, V66, P887, DOI 10.1007/s11069-012-0528-3
   Beniston M., 2011, IMPACT CLIMATE CHANG
   Borga M, 2011, ENVIRON SCI POLICY, V14, P834, DOI 10.1016/j.envsci.2011.05.017
   Borga M, 2007, J HYDROMETEOROL, V8, P1049, DOI 10.1175/JHM593.1
   Choudhury NY, 2004, APPL GEOGR, V24, P241, DOI 10.1016/j.apgeog.2004.04.001
   Fendler R, 2008, NAT HAZARDS, V46, P257, DOI 10.1007/s11069-007-9209-z
   Forte F, 2006, ENVIRON GEOL, V50, P581, DOI 10.1007/s00254-006-0234-0
   Fuller IC, 2008, GEOMORPHOLOGY, V98, P84, DOI 10.1016/j.geomorph.2007.02.026
   Gaurav K, 2011, NAT HAZARDS, V59, P1815, DOI 10.1007/s11069-011-9869-6
   Government of Khyber Pakhtunkhwa (GoKP), 2009, ENV PROF KHYB PAKHT
   Government of KP (GoKP), 2011, FLOOD REP 2010
   Government of Pakistan (GoP), 2012, POP CENS ORG PAK
   Government of Pakistan (GoP), 1999, DISTR CENS REP DIR 1
   Groisman PY, 2004, J HYDROMETEOROL, V5, P64, DOI 10.1175/1525-7541(2004)005<0064:CCOTHC>2.0.CO;2
   Jonkman SN, 2005, NAT HAZARDS, V34, P151, DOI 10.1007/s11069-004-8891-3
   Krausmann E, 2008, NAT HAZARDS, V46, P179, DOI 10.1007/s11069-007-9203-5
   Lehner B, 2006, CLIMATIC CHANGE, V75, P273, DOI 10.1007/s10584-006-6338-4
   Mahmood S, 2016, INT J DISAST RISK RE, V16, P215, DOI 10.1016/j.ijdrr.2016.02.009
   Ibarra EM, 2012, APPL GEOGR, V32, P490, DOI 10.1016/j.apgeog.2011.06.003
   Mazzorana B, 2009, NAT HAZARD EARTH SYS, V9, P145, DOI 10.5194/nhess-9-145-2009
   Montz B. E., 2002, Environmental Hazards, V4, P15
   Nathan F, 2008, DISASTERS, V32, P337, DOI 10.1111/j.1467-7717.2008.01043.x
   Pande RK, 2010, DISASTER PREV MANAG, V19, P565, DOI 10.1108/09653561011091896
   Rossa AM, 2010, J HYDROL, V394, P230, DOI 10.1016/j.jhydrol.2010.08.035
   Syvitski J.P. M., 2013, GSA Today, V23, P4, DOI DOI 10.1130/GSATG165A.1
   Tariq MAUR, 2012, PHYS CHEM EARTH, V47-48, P11, DOI 10.1016/j.pce.2011.08.014
   Teng WH, 2006, NAT HAZARDS, V37, P191, DOI 10.1007/s11069-005-4667-7
   Vinet F, 2008, APPL GEOGR, V28, P323, DOI 10.1016/j.apgeog.2008.02.007
   Zhang JiQun Zhang JiQun, 2002, Environmental Hazards, V4, P33, DOI 10.1016/S1464-2867(03)00002-0
   Zhang Q, 2008, J HYDROL, V353, P215, DOI 10.1016/j.jhydrol.2007.11.023
   Zielinski T, 2003, GEOMORPHOLOGY, V54, P293, DOI 10.1016/S0169-555X(02)00362-8
NR 37
TC 32
Z9 33
U1 1
U2 26
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 0921-030X
EI 1573-0840
J9 NAT HAZARDS
JI Nat. Hazards
PD SEP
PY 2016
VL 83
IS 2
BP 1213
EP 1227
DI 10.1007/s11069-016-2386-x
PG 15
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA DS5AZ
UT WOS:000380794200021
DA 2025-01-10
ER

PT J
AU Pauw, WP
AF Pauw, W. P.
TI Not a panacea: private-sector engagement in adaptation and adaptation
   finance in developing countries
SO CLIMATE POLICY
LA English
DT Article
DE adaptation; adaptation finance; agriculture; climate finance; private
   sector; Zambia
ID CLIMATE-CHANGE; AFRICA
AB The role of the private sector in climate finance is increasingly emphasized in international political debates. Knowledge of private engagement in mitigating climate change and in more advanced economies is growing, but the evidence base for private-sector engagement in climate change adaptation in developing countries remains weak. Starting from the premise that the private sector's role in adaptation is often inevitable and potentially significant, this article first analyses the potential of private-sector engagement in adaptation and adaptation financing in developing countries by conceptualizing the private sector's roles and motivation therein. For further inquiry, and for a discussion based on a developing-country context, interviews were conducted with key stakeholders for adaptation of Zambia's agricultural sector, including on ways in which the government can incentivize private-sector engagement in adaptation.How much private-sector adaptation and adaptation finance can be identified depends on the interpretation of the concept of adaptation. Under a broad interpretation, the domestic private sector in particular can contribute substantially to adaptation, both directly and indirectly, through its investments and activities. However, the international private sector's role in financing adaptation should be analysed under a strict interpretation of adaptation and appears limited.Policy relevanceInternational political debates increasingly stress the importance of private climate finance, yet are constrained by vagueness around the private sector's role in adaptation finance. This article conceptualizes and scrutinizes private-sector engagement in adaptation and adaptation finance in developing countries. It concludes that the domestic private sector in particular can contribute substantially to adaptation in direct and indirect ways, and that domestic policies incentivize such contributions. However, international private financing of adaptation is more limited and its analysis requires a stricter interpretation of adaptation. Private-sector engagement in adaptation and adaptation finance can supplement, but not substitute for, public investments in adaptation. These limitations are particularly important when discussing private adaptation finance as part of the developed countries' pledge to mobilize US$100 billion of climate finance per annum from 2020 onwards.
C1 [Pauw, W. P.] German Dev Inst DIE, Deutsch Inst Entwicklungspolit, D-53113 Bonn, Germany.
   [Pauw, W. P.] Inst Environm Studies, NL-1081 HV Amsterdam, Netherlands.
C3 Deutsches Institut Entwicklungspolitik (DIE); Vrije Universiteit
   Amsterdam
RP Pauw, WP (corresponding author), German Dev Inst DIE, Deutsch Inst Entwicklungspolit, Tulpenfeld 6, D-53113 Bonn, Germany.
EM w.p.pauw@gmail.com
OI Pauw, Pieter/0000-0002-9323-2577
FU German Federal Ministry for Economic Cooperation and Development (BMZ)
FX The research is part of the Climate Change and Development beacon
   project funded by the German Federal Ministry for Economic Cooperation
   and Development (BMZ). I am indebted to all those who generously gave
   their time to be interviewed and engaged in this research, both in
   Zambia and afterwards during various UNFCCC conferences and workshops. I
   would also like to thank Shikha Bhasin, Frank Biermann, Clara Brandi,
   Alejandro Guarin, and Pier Vellinga for proof-reading and commenting on
   earlier versions of this article, and thank three anonymous reviewers
   for their invaluable comments and suggestions for improvements. All
   remaining errors are the fault of the author.
CR Agrawala S., 2011, PRIVATE SECTOR ENGAG
   [Anonymous], 131 ECDPM
   [Anonymous], 137 ICRAF WORLD AGR
   [Anonymous], NAT AGR POL
   [Anonymous], ADV ONTW DOOR DUURZ
   [Anonymous], 2013, MAKING ADAPTATION PR
   [Anonymous], INN CLIM FIN EX UNEP
   [Anonymous], STRAT PROGR CLIM RES
   [Anonymous], 1966, 1 NAT DEV PLAN 1 NDP
   [Anonymous], 2009, CLOS GAPS DIS RISK R
   [Anonymous], NAT AGR POL 2004 201
   [Anonymous], WORKING PAPER SERIES
   [Anonymous], 2008, CREAT EN ENV PRIV SE
   [Anonymous], 2011, C PART ITS 16 SESS H
   [Anonymous], 2010, MIND PRET MEER AMB O
   [Anonymous], 2010, NAT CLIM CHANG RESP
   [Anonymous], PRIV INV INCL GREEN
   [Anonymous], 2007, SYNTHESIS REPORT CON
   [Anonymous], AD GREEN EC CO COMM
   [Anonymous], 35 AFR DEP BANK
   [Anonymous], 2011, LANDSCAPE CLIMATE FI
   [Anonymous], OPP PRIV SECT ENG UR
   [Anonymous], CAN CORPORATE SOCIAL
   [Anonymous], EC CLIM CHANG ZAMB
   [Anonymous], 2011, GREEN CLIMATE FUND O
   [Anonymous], 2013, Global Landscape of Climate Finance 2015
   [Anonymous], REP SECR GEN HIGH LE
   [Anonymous], 20110538 STOCKH ENV
   [Anonymous], MITIGATION ADAPTATIO
   [Anonymous], MAT CLIM CHANG FIN C
   [Anonymous], OECD CCXG GLOB FOR T
   [Anonymous], RES REPORT
   [Anonymous], UNDERSTANDING CLIMAT
   [Anonymous], BUS LEAD CLIM CHANG
   [Anonymous], ZAMBIA UNDP CLIMATE
   [Anonymous], NEW AD MARK CLIM CHA
   [Anonymous], STUD PRIV SECT DEV Z
   [Anonymous], PRIV SECT IN DAT ACT
   [Anonymous], ASTI IFPRI FARA C AC
   [Anonymous], PPCRSC133REV1 CIF WO
   [Anonymous], CLIMATE DEV
   [Anonymous], 2013, INT CLIMATE FINANCE
   Ayers J, 2011, GLOBAL ENVIRON POLIT, V11, P62, DOI 10.1162/GLEP_a_00043
   Begum RA, 2015, MITIG ADAPT STRAT GL, V20, P361, DOI 10.1007/s11027-013-9495-6
   Berkhout F, 2006, CLIMATIC CHANGE, V78, P135, DOI 10.1007/s10584-006-9089-3
   Bouwer LM, 2006, DISASTERS, V30, P49, DOI 10.1111/j.1467-9523.2006.00306.x
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Christiansen L., 2012, ACCESSING INT FUNDIN
   Denton F, 2010, CLIM POLICY, V10, P655, DOI 10.3763/cpol.2010.0149
   Edwards M, 2009, WRR VERKENN, P237
   Gschwend T, 2007, RESEARCH DESIGN IN POLITICAL SCIENCE: HOW TO PRACTICE WHAT THEY PREACH, P1
   Hayashi D, 2013, CLIM POLICY, V13, P191, DOI 10.1080/14693062.2013.745114
   Huq S, 2004, IDS BULL-I DEV STUD, V35, P15, DOI 10.1111/j.1759-5436.2004.tb00129.x
   Ireland Philip, 2012, International Journal of Development Issues, V11, P92, DOI 10.1108/14468951211241100
   Kato T., 2014, SCALING REPLICATING
   Klein R. J. T., 2008, Financing adaptation to climate change
   Pauw P, 2013, INT J CLIM CHANG STR, V5, P267, DOI 10.1108/IJCCSM-03-2012-0014
   Pegels Anna., 2014, Green Industrial Policy in Emerging Countries
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Surminski S, 2013, NAT CLIM CHANGE, V3, P943, DOI 10.1038/nclimate2040
   UNFCCC, 2009, INV FIN FLOWS ADDR C
   World Bank, 2013, WORLD BANK GROUP IMPACT EVALUATIONS: RELEVANCE AND EFFECTIVENESS, P1, DOI 10.1596/978-0-8213-9717-6
   World Bank, 2010, EC AD CLIM CHANG
NR 63
TC 46
Z9 50
U1 5
U2 57
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PD SEP 3
PY 2015
VL 15
IS 5
BP 583
EP 603
DI 10.1080/14693062.2014.953906
PG 21
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA CO7OW
UT WOS:000359350700003
OA Green Published
DA 2025-01-10
ER

PT J
AU Chelleri, L
   Schuetze, T
   Salvati, L
AF Chelleri, L.
   Schuetze, T.
   Salvati, L.
TI Integrating resilience with urban sustainability in neglected
   neighborhoods: Challenges and opportunities of transitioning to
   decentralized water management in Mexico City
SO HABITAT INTERNATIONAL
LA English
DT Article
DE Urban resilience; Urban sustainability; Climate change adaptation;
   Neglected neighborhoods; Decentralized water management; Mexico City
   Green Plan
ID PERIURBAN AREAS; RAINWATER; ADAPTATION; SYSTEMS; VULNERABILITY;
   ENVIRONMENT; QUALITY
AB The impacts of climate change and decreasing local resources are increasingly threatening the resilience and sustainable management of urban areas and infrastructures worldwide. To cope with such threads and vulnerabilities, urban sustainability and resilience oriented plans have been developed. Accordingly, policy makers need to learn how to properly integrate urban sustainability with urban resilience principles and practices in the re-shaping of urban agendas. In order to highlight the future potential of integrating transformative resilience principles into the general sustainability approach, this paper provides a critical review of a recent and successful urban regeneration and development plan, the "Mexico City Green Plan". This paper also discusses a feasibility study for urban redevelopment and transition towards resilience in Mexico City, in order to illustrate the necessity and potential of urban resilience for the improvement of the life prospects of disadvantaged inhabitant groups. The Valle del Chalco neighborhood in Mexico City is presented as an example, whereby resilient and sustainable urban transformation was achieved through an integrated and sustainable decentralized water management and infrastructure plan. In practice, the terms 'Sustainability' and 'Resilience' can be exploited to justify conventional, non-sustainable urban development practices. The results discussed in this paper demonstrate the necessity of the integration of transformative resilience principles within sustainable urban redevelopment and regeneration. The main findings are i) Policy makers underestimate the potential of urban resilience in shaping more sustainable urban futures, since they only understand resilience as the flipside of specific vulnerabilities, ii) The building of urban resilience within sustainable urban transitions and redevelopment can effectively foster people empowerment, particularly in combination with the decentralization of resources management systems, and iii) The main challenge for the implementation and execution of transitions processes towards urban resilience and sustainability is the elimination of political barriers. (c) 2015 Elsevier Ltd. All rights reserved.
C1 [Chelleri, L.] GSSI Cities, Gran Sasso Sci Inst, I-67100 Laquila, Italy.
   [Schuetze, T.] Sungkyunkwan Univ, Dept Architecture, Suwon 440746, South Korea.
   [Salvati, L.] Council Res Agr, Unit Climatol & Meteorol Appl Agr CRA CMA, I-00186 Rome, Italy.
C3 Gran Sasso Science Institute (GSSI); Sungkyunkwan University (SKKU)
RP Chelleri, L (corresponding author), GSSI Cities, Gran Sasso Sci Inst, Viale F Crispi 7, I-67100 Laquila, Italy.
EM Lorenzo.chelleri@gmail.com
RI Schuetze, Thorsten/ABA-5119-2021; Salvati, Luca/AAS-6179-2021
OI Chelleri, Lorenzo/0000-0003-0229-5028; Schuetze,
   Thorsten/0000-0001-7849-2330
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Amin MT, 2013, INT J ENVIRON SCI TE, V10, P27, DOI 10.1007/s13762-012-0096-9
   [Anonymous], 2012, WORLD URB PROSP 2011
   Baker JL, 2012, URB DEV SER, P1, DOI 10.1596/978-0-8213-8845-7
   BOERS TM, 1982, AGR WATER MANAGE, V5, P145, DOI 10.1016/0378-3774(82)90003-8
   Carmin J, 2012, J PLAN EDUC RES, V32, P18, DOI 10.1177/0739456X11430951
   Cerón-Palma I, 2013, HABITAT INT, V38, P47, DOI 10.1016/j.habitatint.2012.09.008
   Chelleri L., 2012, Multidisciplinary perspectives on urban resilience: a workshop report
   Chelleri L, 2015, ENVIRON URBAN, V27, P181, DOI 10.1177/0956247814550780
   Collier MJ, 2013, CITIES, V32, pS21, DOI 10.1016/j.cities.2013.03.010
   Domènech L, 2012, WATER ENVIRON J, V26, P465, DOI 10.1111/j.1747-6593.2011.00305.x
   Martinez SE, 2011, WATER RESOUR MANAG, V25, P239, DOI 10.1007/s11269-010-9697-6
   Elmqvist Thomas., 2014, SOLUTIONS, V5, P26, DOI DOI 10.1016/j.ecolind.2011.06.017
   Folke C, 2010, ECOL SOC, V15
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Garrido S, 2011, WATER SCI TECHNOL, V63, P2395, DOI 10.2166/wst.2011.199
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Kyessi AG, 2005, HABITAT INT, V29, P1, DOI 10.1016/S0197-3975(03)00059-6
   Lankao PR, 2011, CURR OPIN ENV SUST, V3, P142, DOI 10.1016/j.cosust.2010.12.016
   Lizarralde G, 2015, SUSTAIN CITIES SOC, V15, P96, DOI 10.1016/j.scs.2014.12.004
   Lopez A., 2011, TECHNOLOGY SUSTAINAB
   Lye DJ, 2009, SCI TOTAL ENVIRON, V407, P5429, DOI 10.1016/j.scitotenv.2009.07.011
   Massoud MA, 2009, J ENVIRON MANAGE, V90, P652, DOI 10.1016/j.jenvman.2008.07.001
   Meera V, 2006, J WATER SUPPLY RES T, V55, P257, DOI 10.2166/aqua.2006.0010
   Miller F, 2010, ECOL SOC, V15
   Morales Novelo J. A., 2011, WATER RESOURCES MEXI, P395
   Morales-Pinzón T, 2012, WATER ENVIRON J, V26, P550, DOI 10.1111/j.1747-6593.2012.00316.x
   Nanninga TA, 2012, WATER-SUI, V4, P739, DOI 10.3390/w4030739
   Spring UO, 2011, CURR OPIN ENV SUST, V3, P497, DOI 10.1016/j.cosust.2011.11.002
   Otterpohl R, 1997, WATER SCI TECHNOL, V35, P121, DOI 10.1016/S0273-1223(97)00190-X
   Parkinson J, 2003, ENVIRON URBAN, V15, P75, DOI 10.1177/095624780301500119
   Pearson L., 2014, RESILIENT SUSTAINABL
   Pizzo B, 2015, CITIES, V43, P133, DOI 10.1016/j.cities.2014.11.015
   Redman CL, 2014, ECOL SOC, V19, DOI 10.5751/ES-06390-190237
   Romero-Lankao P, 2014, HABITAT INT, V42, P224, DOI 10.1016/j.habitatint.2013.12.008
   Sample DJ, 2006, J WATER RES PLAN MAN, V132, P362, DOI 10.1061/(ASCE)0733-9496(2006)132:5(362)
   Schewenius M, 2014, AMBIO, V43, P434, DOI 10.1007/s13280-014-0505-z
   Secretaria del Medio Ambiente, 2012, PROGR ACC CLIM CIUD, P197
   Secretaria del Medio Ambiente, 2012, CINC AN AV PLAN VERD, P218
   Secretaria del Medio Ambiente, 2007, PLAN VERD CIUD MEX
   Secretaria del Medio Ambiente, 2008, PROGR ACC CLIM CIUD, P171
   Sen Z, 2013, ARAB J GEOSCI, V6, P287, DOI 10.1007/s12517-011-0354-z
   Spring, 2012, WATER RESOURCES MEXI, P3, DOI [10.1007/978-3-642-05432-7_1, DOI 10.1007/978-3-642-05432-7_1]
   Suriyachan C, 2012, HABITAT INT, V36, P85, DOI 10.1016/j.habitatint.2011.06.001
   Tortajada C, 2006, INT J WATER RESOUR D, V22, P353, DOI 10.1080/07900620600671367
   Tsur Y., 1997, DECENTRALIZATION COO
   Turner BL, 2010, GLOBAL ENVIRON CHANG, V20, P570, DOI 10.1016/j.gloenvcha.2010.07.003
   Vale LJ, 2014, BUILD RES INF, V42, P191, DOI 10.1080/09613218.2014.850602
   Wilder M, 2006, WORLD DEV, V34, P1977, DOI 10.1016/j.worlddev.2005.11.026
   Wilderer P.A., 2001, Decentralised Sabitation and Reuse: Concepts, Systems and Implementation, P39
   Zhang DQ, 2009, URBAN WATER J, V6, P375, DOI 10.1080/15730620902934827
NR 51
TC 118
Z9 126
U1 11
U2 179
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0197-3975
EI 1873-5428
J9 HABITAT INT
JI Habitat Int.
PD AUG
PY 2015
VL 48
BP 122
EP 130
DI 10.1016/j.habitatint.2015.03.016
PG 9
WC Development Studies; Environmental Studies; Regional & Urban Planning;
   Urban Studies
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology; Public
   Administration; Urban Studies
GA CK3JU
UT WOS:000356113200014
DA 2025-01-10
ER

PT J
AU Tompkins, EL
   Adger, WN
AF Tompkins, EL
   Adger, WN
TI Defining response capacity to enhance climate change policy
SO ENVIRONMENTAL SCIENCE & POLICY
LA English
DT Article; Proceedings Paper
CT Workshop on Mitigation and Adaptation Strategies for Climate Change
CY 2003
CL Essen, GERMANY
SP GKSS, Karlsruhe Res Ctr, inst Technol Assessment & Syst Anal, Ctr Adv Study Humanities
DE adaptation; mitigation; climate change policy; risk; technology; social
   change; response capacity
ID COASTAL MANAGEMENT; ADAPTATION; KNOWLEDGE; FRAMEWORK
AB Climate change adaptation and mitigation decisions made by governments are usually taken in different policy domains. At the individual level however, adaptation and mitigation activities are undertaken together as part of the management of risk and resources. We propose that a useful starting point to develop a national climate policy is to understand what societal response might mean in practice. First we frame the set of responses at the national policy level as a trade off between investment in the development and diffusion of new technology, and investment in encouraging and enabling society to change its behaviour and or adopt the new technology. We argue that these are the pertinent trade-offs, rather than those usually posited between climate change mitigation and adaptation. The preference for a policy response that focuses more on technological innovation rather than one that focuses on changing social behaviour will be influenced by the capacity of different societies to change their greenhouse gas emissions; by perceived vulnerability to climate impacts; and by capacity to modify social behaviour and physical environment. Starting with this complete vision of response options should enable policy makers to re-evaluate the risk environment and the set of response options available to them. From here, policy makers should consider who is responsible for making climate response decisions and when actions should be taken. Institutional arrangements dictate social and political acceptability of different policies, they structure worldviews, and they determine the provision of resources for investment in technological innovation and social change. The importance of focussing on the timing of the response is emphasised to maximise the potential for adjustments through social learning and institutional change at different policy scales. We argue that the ability to respond to climate change is both enabled and constrained by social and technological conditions. The ability of society to respond to climate change and the need for technological change for both decarbonisation and for dealing with surprise in general, are central to concepts of sustainable development. (c) 2005 Elsevier Ltd. All rights reserved.
C1 Univ E Anglia, Sch Environm Sci, Tyndall Ctr Climate Change Res, Norwich NR4 7TJ, Norfolk, England.
   Univ Southampton, Dept Geog, Southampton, Hants, England.
C3 University of East Anglia; University of Southampton
RP Univ E Anglia, Sch Environm Sci, Tyndall Ctr Climate Change Res, Norwich NR4 7TJ, Norfolk, England.
EM e.tompkins@uea.ac.uk
RI Tompkins, Emma/B-6863-2016; Adger, William Neil/F-7676-2010
OI Tompkins, Emma/0000-0002-4825-9797; Adger, William
   Neil/0000-0003-4244-2854
CR Adger WN, 2003, ECON GEOGR, V79, P387
   Allanson P, 1999, EUR REV AGRIC ECON, V26, P1, DOI 10.1093/erae/26.1.1
   Allen W, 2001, ENVIRON MANAGE, V27, P215, DOI 10.1007/s002670010144
   [Anonymous], 1993, An inquiry into well-being and destitution
   [Anonymous], 1993, Decisions with Multiple Objectives
   [Anonymous], EC IMPACT CLIMATE CH
   [Anonymous], 2002, CLIMATE CHANGE SCENA
   [Anonymous], 1998, FACILITATING SUSTAIN
   [Anonymous], POT UK AD STRAT CLIM
   Bakker KJ, 2003, GEOFORUM, V34, P359, DOI 10.1016/S0016-7185(02)00092-1
   Barker T, 2003, GLOBAL ENVIRON CHANG, V13, P1, DOI 10.1016/S0959-3780(02)00085-7
   Barnett J, 2002, CLIM POLICY, V2, P231, DOI 10.1016/S1469-3062(02)00023-2
   Blaikie P., 1994, Natural Hazards, Peoples Vulnerability and Disater
   Clarke S., 2002, LONDONS WARMING IMPA
   Cordes JJ, 1998, LAND ECON, V74, P128, DOI 10.2307/3147218
   Dessai S, 2004, CLIMATIC CHANGE, V64, P11, DOI 10.1023/B:CLIM.0000024781.48904.45
   DESSAI S, 2005, GLOBAL ENV CHANGE, V15
   EPPEI S, 2002, ENERGY SAVING TRUST
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   Gezon L, 1997, HUM ORGAN, V56, P462, DOI 10.17730/humo.56.4.x7378n322466748q
   Hale Lynne Zeitlin, 1994, P68
   Hall PeterA. David W. Soskice., 2003, Varieties of Capitalism: The Institutional Foundations of Comparative Advantage, DOI DOI 10.2307/30040740
   JAGER J, 2001, LEARNING MANAGE GLOB, V2, P165
   JORDAN A, 1995, 9520141 CSERGE GEC
   Kane S, 2000, CLIMATIC CHANGE, V45, P1, DOI 10.1023/A:1005699828901
   Kates RW, 2000, CLIMATIC CHANGE, V45, P5, DOI 10.1023/A:1005672413880
   Keeney RL, 2001, RISK ANAL, V21, P989, DOI 10.1111/0272-4332.216168
   KING IC, SMALL ISLANDS 3 MILL
   Lawson T, 2003, J ECON ISSUES, V37, P175, DOI 10.1080/00213624.2003.11506562
   Lee MW, 1999, ADV OCCUP ERGO SAF, V3, P3
   Mastrandrea MD, 2004, SCIENCE, V304, P571, DOI 10.1126/science.1094147
   Michaelowa A, 2000, J WORLD TRADE, V34, P157, DOI 10.1023/A:1009015120210
   Nordhaus WD, 1994, EC CLIMATE CHANGE
   O'Riordan T, 1999, GLOBAL ENVIRON CHANG, V9, P81, DOI 10.1016/S0959-3780(98)00030-2
   Olsen S, 1997, OCEAN COAST MANAGE, V37, P155, DOI 10.1016/S0964-5691(98)80036-7
   OLSEN SB, 1993, OCEAN COAST MANAGE, V21, P201, DOI 10.1016/0964-5691(93)90027-V
   Olsen SB, 1998, AMBIO, V27, P611
   Olsson P, 2001, ECOSYSTEMS, V4, P85, DOI 10.1007/s100210000061
   ORIORDAN T, 1998, HUMAN CHOICE CLIMATE, V1
   Parsons E., 1995, Barriers and bridges to the renewal of ecosystems and institutions, P428
   PETERS P, 1987, QUESTION COMMONS CUL, P400
   RAYNER S, SOCIETAL FRAMEWORK, V1, P1
   *REG COORD UNDP GE, 2002, VULN MAGHR REG CLIM
   Scheraga JD, 1998, CLIMATE RES, V11, P85, DOI 10.3354/cr011085
   Schneider SH, 2004, GLOBAL ENVIRON CHANG, V14, P245, DOI 10.1016/j.gloenvcha.2004.04.008
   Schneider SH, 2002, CLIMATIC CHANGE, V52, P441, DOI 10.1023/A:1014221225434
   Sorensen J, 1997, COAST MANAGE, V25, P3, DOI 10.1080/08920759709362308
   Sorrell S, 2003, ENERG POLICY, V31, P865, DOI 10.1016/S0301-4215(02)00130-1
   Stevenson R, 2002, J ECON ISSUES, V36, P263, DOI 10.1080/00213624.2002.11506469
   Tol RSJ, 2003, CLIMATIC CHANGE, V56, P265, DOI 10.1023/A:1021753906949
   Tompkins E, 2002, ENVIRON PLANN A, V34, P1095, DOI 10.1068/a34213
   Tompkins EL, 2004, ECOL SOC, V9
   TOMPKINS EL, 2005, NATL LEVEL RESPONSES
   Tonn B., 2000, J ENVIRON PLANN MAN, V43, P163, DOI [DOI 10.1080/09640560010658, 10.1080/09640560010658]
   TURNPENNY J, 2003, 31 U E ANGL TYND CTR
   *UKCIP, 2003, IMP CLIM CHANG BUILT
   Walters C.J., 2001, Adaptive management of renewable resources
   WALTERS CJ, 1997, CHALLENGES ADAPTIVE
   Watson R.T., 2001, CLIMATE CHANGE 2001, P398
   White A.T., 1994, Collaborative and Community-Based Management of Coral Reefs
   Wilbanks TJ, 2003, ENVIRONMENT, V45, P28, DOI 10.1080/00139150309604547
   *WORLD BANK, 1997, 15916 UNEP WORLD BAN
   Yohe G, 2004, SCIENCE, V306, P416, DOI 10.1126/science.1101170
NR 63
TC 204
Z9 243
U1 3
U2 89
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 1462-9011
EI 1873-6416
J9 ENVIRON SCI POLICY
JI Environ. Sci. Policy
PY 2005
VL 8
IS 6
BP 562
EP 571
DI 10.1016/j.envsci.2005.06.012
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Environmental Sciences & Ecology
GA 991MD
UT WOS:000233817200004
DA 2025-01-10
ER

PT J
AU Khan, NA
   Qiao, JM
   Abid, M
   Gao, QJ
AF Khan, Nasir Abbas
   Qiao, Jiamei
   Abid, Muhammad
   Gao, Qijie
TI Understanding farm-level cognition of and autonomous adaptation to
   climate variability and associated factors: Evidence from the
   rice-growing zone of Pakistan
SO LAND USE POLICY
LA English
DT Article
DE Climate variability; Perception; Adaptation; Farmer; Pakistan;
   Agriculture; socio-economic analysis
ID AGRICULTURAL ADAPTATION; SMALLHOLDER FARMERS; PERCEPTIONS; STRATEGIES;
   POLICY; RISK; VULNERABILITY; INFORMATION; RESPONSES; BARRIERS
AB This study was conducted in the rice-growing zone of Punjab province, where rice production is affected by climate variabilities. The study aimed to assess farmers? perception of and adaptation to climate variability and its associated factors. Cross-sectional data of 480 rice growers was collected from the four rice-growing districts in Punjab using a multi-stage sampling approach. A multivariate probit model is used to analyze the determinants of farmers? adaptation decisions, and an ordered probit model is employed to estimate the factors affecting adaptation intensity. We find that farmers perceived significant changes in local climate, i.e., increase in summer temperature, decrease in summer rainfall, and changing pattern of rainfall and winter cropping season. Rice growers applied supplementary irrigation, changed rice cultivation dates, considered fertilizer management and crop diversification, and changed crop varieties as adaptation strategies to cope with climatic variability. The results of the multivariate probit model indicate farmers? age, farm size, availability of water resources, livestock ownership, off-farm income, and access to farm advisory services, credit, and climate information as significant determinants of adaptation strategies. The ordered probit model shows a positive and significant effect of farmers? education level and availability of irrigation water, farm labor, credit, farm advisory services, and climate information on adaptation intensity. The findings identify lack of water resources, financial constraints, and limited advisory services as key barriers to adaptation. This study suggests that the government should adopt a proactive approach to support farming communities to adapt to climate variability through improved access to water resources, advisory services, and credit services.
C1 [Khan, Nasir Abbas] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Sch Management Sci & Engn, Nanjing 210044, Peoples R China.
   [Khan, Nasir Abbas; Qiao, Jiamei; Gao, Qijie] China Agr Univ, Coll Humanities & Dev Studies COHD, 17 Qing Hua Dong Lu, Beijing 100083, Peoples R China.
   [Abid, Muhammad] COMSATS Univ Islamabad, Ctr Climate Res & Dev, Islamabad 45550, Pakistan.
   [Abid, Muhammad] Deutsch Gesell Int Zusammenarbeit GIZ, Level 2, Islamabad 45550, Pakistan.
C3 Nanjing University of Information Science & Technology; China
   Agricultural University; COMSATS University Islamabad (CUI)
RP Gao, QJ (corresponding author), China Agr Univ, Coll Humanities & Dev Studies COHD, 17 Qing Hua Dong Lu, Beijing 100083, Peoples R China.
EM nasirkhanpk@cau.edu.cn; qiaojiamei@cau.edu.cn;
   muhammad.abid@comsats.edu.pk; gaocau@126.com
RI Abid, Muhammad/ITW-0166-2023; Khan, Nasir Abbas/Z-3608-2019
OI Khan, Nasir Abbas/0000-0002-6079-715X
CR Abid M, 2020, CLIM RISK MANAG, V27, DOI 10.1016/j.crm.2019.100200
   Abid M, 2019, ENVIRON MANAGE, V63, P110, DOI 10.1007/s00267-018-1113-7
   Abid M, 2017, CLIMATE, V5, DOI 10.3390/cli5040085
   Abid M, 2016, SCI TOTAL ENVIRON, V547, P447, DOI 10.1016/j.scitotenv.2015.11.125
   Aggarwal PK, 2011, CLIMATE CHANGE AND FOOD SECURITY IN SOUTH ASIA, P253, DOI 10.1007/978-90-481-9516-9_16
   Ahmad A., 2015, Handbook of Climate Change and Agroecosystems: The Agricultural Model Inter-comparison and Improvement Project Integrated Crop and Economic Assessments, Part 2, P219
   Akhtar S, 2018, J INTEGR AGR, V17, P1454, DOI 10.1016/S2095-3119(17)61796-9
   Alauddin M, 2014, ECOL ECON, V106, P204, DOI 10.1016/j.ecolecon.2014.07.025
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Amare ZY., 2018, AGR FOOD SECUR, V7, P1, DOI [10.1186/s40066-018-0188-y, DOI 10.1186/S40066-018-0188-Y]
   Amusa TA., 2017, TRENDS AGR EC, V10, P1
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Bell AR, 2014, WATER RESOUR RES, V50, P6679, DOI 10.1002/2014WR015704
   Board of Statistics (BOS) Punjab, 2018, DIR AGR EC MARK PUNJ
   Bonzanigo L, 2016, REG ENVIRON CHANGE, V16, P245, DOI 10.1007/s10113-014-0750-5
   BOS, 2017, FIN EST MAJ KHAR CRO
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Christoplos I., 2009, The Human Dimension of Climate Adaptation: The Importance of Local and Institutional Issues
   Cooper PJM, 2008, AGR ECOSYST ENVIRON, V126, P24, DOI 10.1016/j.agee.2008.01.007
   Eckstein D., 2020, GLOBAL CLIMATE RISK
   Eisenack K, 2009, 17 ANN C EUR ASS ENV
   Fosu-Mensah B. Y., 2012, Environment Development and Sustainability, V14, P495, DOI 10.1007/s10668-012-9339-7
   *GOP, 2019, STAT POCK BOOK PUNJ
   Kassie M, 2013, TECHNOL FORECAST SOC, V80, P525, DOI 10.1016/j.techfore.2012.08.007
   Kelkar U, 2008, GLOBAL ENVIRON CHANG, V18, P564, DOI 10.1016/j.gloenvcha.2008.09.003
   Khan N.A., 2020, ENVIRON SCI POLLUT R
   Khan NA, 2022, ELECTRON COMMER RES, V22, P1107, DOI 10.1007/s10660-020-09442-z
   Khan NA, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-71011-z
   Khan NA, 2020, ENVIRON SCI POLLUT R, V27, P20292, DOI 10.1007/s11356-020-08341-y
   Khan NA, 2019, CIENC RURAL, V49, DOI 10.1590/0103-8478cr20181016
   Khan NA, 2020, INFORM DEV, V36, P390, DOI 10.1177/0266666919864126
   Khatri-Chhetri A, 2017, AGR SYST, V151, P184, DOI 10.1016/j.agsy.2016.10.005
   Khattak M.S., 2015, Journal of Himalayan Earth Sciences, V48
   Knox J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034032
   Lal M, 2011, REG ENVIRON CHANGE, V11, pS79, DOI 10.1007/s10113-010-0166-9
   Li S, 2017, J ENVIRON MANAGE, V185, P21, DOI 10.1016/j.jenvman.2016.10.051
   Mahmood N, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12041650
   Masud MM, 2017, J CLEAN PROD, V156, P698, DOI 10.1016/j.jclepro.2017.04.060
   Mersha AA, 2018, WORLD DEV, V107, P87, DOI 10.1016/j.worlddev.2018.03.001
   Mertz O, 2009, ENVIRON MANAGE, V43, P804, DOI 10.1007/s00267-008-9197-0
   Mittal S, 2016, J AGRIC EDUC EXT, V22, P199, DOI 10.1080/1389224X.2014.997255
   Mulwa C, 2017, CLIM RISK MANAG, V16, P208, DOI 10.1016/j.crm.2017.01.002
   *PDMA, 2014, PROV DIS MAN AUTH
   PMD, 2017, LAND US STAT
   Rahman HMT, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00002
   Sarker MAR, 2014, ECON ANAL POLICY, V44, P405, DOI 10.1016/j.eap.2014.11.004
   Shaffril HAM, 2018, SCI TOTAL ENVIRON, V644, P683, DOI 10.1016/j.scitotenv.2018.06.349
   Shah AA, 2018, INT NGO J, V13, P7, DOI [10.5897/INGOJ2016.0301, DOI 10.5897/INGOJ2016.0301]
   Simelton E, 2013, CLIM DEV, V5, P123, DOI 10.1080/17565529.2012.751893
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Somda J., 2017, Evaluating Climate Change Action for Sustainable Development, P255, DOI DOI 10.1007/978-3-319-43702-6_14
   Stuart D, 2014, LAND USE POLICY, V36, P210, DOI 10.1016/j.landusepol.2013.08.011
   Teddlie C, 2007, J MIX METHOD RES, V1, P77, DOI 10.1177/2345678906292430
   Teklewold H, 2019, CLIM DEV, V11, P180, DOI 10.1080/17565529.2018.1442801
   Thorn J, 2015, GLOBAL ENVIRON CHANG, V31, P121, DOI 10.1016/j.gloenvcha.2014.12.009
   Ullah R, 2015, INT J DISAST RISK RE, V12, P268, DOI 10.1016/j.ijdrr.2015.02.001
   Zamasiya B, 2017, J ENVIRON MANAGE, V198, P233, DOI 10.1016/j.jenvman.2017.04.073
   Zhai SY, 2018, J INTEGR AGR, V17, P949, DOI 10.1016/S2095-3119(17)61753-2
   Zhang WeiJian Zhang WeiJian, 2012, Scientia Agricultura Sinica, V45, P1265
NR 59
TC 33
Z9 34
U1 1
U2 21
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0264-8377
EI 1873-5754
J9 LAND USE POLICY
JI Land Use Pol.
PD JUN
PY 2021
VL 105
AR 105427
DI 10.1016/j.landusepol.2021.105427
PG 12
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA RP2UD
UT WOS:000641588100006
DA 2025-01-10
ER

PT J
AU Dingkuhn, M
   Pasco, R
   Pasuquin, JM
   Damo, J
   Soulié, JC
   Raboin, LM
   Dusserre, J
   Sow, A
   Manneh, B
   Shrestha, S
   Balde, A
   Kretzschmar, T
AF Dingkuhn, Michael
   Pasco, Richard
   Pasuquin, Julie M.
   Damo, Jean
   Soulie, Jean-Christophe
   Raboin, Louis-Marie
   Dusserre, Julie
   Sow, Abdoulaye
   Manneh, Baboucarr
   Shrestha, Suchit
   Balde, Alpha
   Kretzschmar, Tobias
TI Crop-model assisted phenomics and genome-wide association study for
   climate adaptation of indica rice. 1. Phenology
SO JOURNAL OF EXPERIMENTAL BOTANY
LA English
DT Article
DE Candidate genes; cold tolerance; flowering; HD3a florigen; heuristics;
   Oryza sativa L.; photoperiod sensitivity; RIDEV crop model
ID TRANSCRIPTION FACTORS; TRANSGENIC RICE; ORYZA-SATIVA; QTL ANALYSIS;
   STRESS; DETERMINANTS; ENVIRONMENTS; TEMPERATURE; PERFORMANCE; EXPRESSION
AB Phenology and time of flowering are crucial determinants of rice adaptation to climate variation. A previous study characterized flowering responses of 203 diverse indica rices (the ORYTAGE panel) to ten environments in Senegal (six sowing dates) and Madagascar (two years and two altitudes) under irrigation in the field. This study used the physiological phenology model RIDEV V2 to heuristically estimate component traits of flowering such as cardinal temperatures (base temperature (Tbase) and optimum temperature), basic vegetative phase, photoperiod sensitivity and cold acclimation, and to conduct a genome-wide association study for these traits using 16 232 anonymous single-nucleotide polymorphism (SNP) markers. The RIDEV model after genotypic parameter optimization explained 96% of variation in time to flowering for Senegal alone and 91% for Senegal and Madagascar combined. The latter was improved to 94% by including an acclimation parameter reducing Tbase when the crop experienced low temperatures during early vegetative development. Eighteen significant (P< 1.0 x 10(-5)) quantitative trait loci (QTLs) were identified, namely ten for RIDEV parameters and eight for climatic index variables (difference in time to flowering between key environments). Co-localization of QTLs for different traits were rare. RIDEV parameters gave QTLs that were mostly more significant and distinct from QTLs for index variables. Candidate genes were investigated within the estimated 50% linkage disequilibrium regions of 39 kB. In addition to several known flowering network genes, they included genes related to thermal stress adaptation and epigenetic control mechanisms. The peak SNP for a QTL for the crop parameter Tbase (P= 2.0 x 10(-7)) was located within HD3a, a florigen that was recently identified as implicated in flowering under cool conditions.
C1 [Dingkuhn, Michael; Soulie, Jean-Christophe; Raboin, Louis-Marie; Dusserre, Julie] Cirad, Umr AGAP, Dept BIOS, F-34398 Montpellier, France.
   [Dingkuhn, Michael; Soulie, Jean-Christophe; Raboin, Louis-Marie; Dusserre, Julie] Cirad, Upr AIDA, Dept ES, F-34398 Montpellier, France.
   [Pasco, Richard; Pasuquin, Julie M.; Damo, Jean; Shrestha, Suchit; Kretzschmar, Tobias] IRRI, CESD Div, DAPO Box 7777, Manila, Philippines.
   [Sow, Abdoulaye; Manneh, Baboucarr; Balde, Alpha] Africa Rice Ctr, Sahel Stn, PB 96, St Louis, Senegal.
C3 Universite de Montpellier; CIRAD; CIRAD; CGIAR; International Rice
   Research Institute (IRRI); CGIAR; Africa Rice Center
RP Dingkuhn, M (corresponding author), Cirad, Umr AGAP, Dept BIOS, F-34398 Montpellier, France.; Dingkuhn, M (corresponding author), Cirad, Upr AIDA, Dept ES, F-34398 Montpellier, France.
EM michael.dingkuhn@cirad.fr
RI kretzschmar, tobias/AAH-3739-2021; Shrestha, Suchit/ABG-1637-2021
OI Damo, Jean Louise/0000-0002-9996-930X; Soulie,
   Jean-Christophe/0000-0003-2904-9548; kretzschmar,
   tobias/0000-0002-8227-0746
CR Arora R, 2007, BMC GENOMICS, V8, DOI 10.1186/1471-2164-8-242
   Bai B, 2015, INT J MOL SCI, V16, P11398, DOI 10.3390/ijms160511398
   Baldoni E, 2015, INT J MOL SCI, V16, P15811, DOI 10.3390/ijms160715811
   Bradbury PJ, 2007, BIOINFORMATICS, V23, P2633, DOI 10.1093/bioinformatics/btm308
   Browning SR, 2007, AM J HUM GENET, V81, P1084, DOI 10.1086/521987
   Chinnusamy V, 2009, CURR OPIN PLANT BIOL, V12, P133, DOI 10.1016/j.pbi.2008.12.006
   Courtois B, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0078037
   De Datta S.K., 1981, Principle and Practices of rice production, P618
   DINGKUHN M, 1995, AGR SYST, V48, P435, DOI 10.1016/0308-521X(94)00029-K
   DINGKUHN M, 1995, AGR SYST, V48, P411, DOI 10.1016/0308-521X(94)00028-J
   DINGKUHN M, 1995, AGR SYST, V48, P385, DOI 10.1016/0308-521X(94)00027-I
   Dingkuhn M, 1997, IRRIGATED RICE SAHEL, P343
   DINGKUHN M, 2015, PLANT PHENOLOGICAL T, V183, P342
   Dingkuhn M, 2008, EUR J AGRON, V28, P74, DOI 10.1016/j.eja.2007.05.005
   Dingkuhn M, 2015, FIELD CROP RES, V183, P282, DOI 10.1016/j.fcr.2015.07.024
   Fang YJ, 2008, MOL GENET GENOMICS, V280, P547, DOI 10.1007/s00438-008-0386-6
   Fujimori DG, 2013, CURR OPIN CHEM BIOL, V17, P597, DOI 10.1016/j.cbpa.2013.05.032
   Fukai S, 1999, FIELD CROP RES, V64, P51, DOI 10.1016/S0378-4290(99)00050-7
   Gómez-Ariza J, 2015, J EXP BOT, V66, P2027, DOI 10.1093/jxb/erv004
   Hammer GL, 2002, EUR J AGRON, V18, P15, DOI 10.1016/S1161-0301(02)00093-X
   Hu SK, 2013, RICE, V6, DOI 10.1186/1939-8433-6-24
   Ito Y, 2006, PLANT CELL PHYSIOL, V47, P141, DOI 10.1093/pcp/pci230
   Jeong JS, 2013, PLANT BIOTECHNOL J, V11, P101, DOI 10.1111/pbi.12011
   Julia C, 2013, EUR J AGRON, V49, P50, DOI 10.1016/j.eja.2013.03.006
   Julia C, 2012, EUR J AGRON, V43, P166, DOI 10.1016/j.eja.2012.06.007
   Kapazoglou A, 2012, BMC PLANT BIOL, V12, DOI 10.1186/1471-2229-12-166
   Kawahara Y, 2013, RICE, V6, DOI 10.1186/1939-8433-6-4
   Koumoto T, 2014, MEMORY GENERATIONS C
   Kulik A, 2011, OMICS, V15, P859, DOI 10.1089/omi.2011.0091
   Liu Q, 2009, FEBS LETT, V583, P723, DOI 10.1016/j.febslet.2009.01.020
   Mao DH, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0047275
   Mellacheruvu S, 2016, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.01167
   Nakagawa H, 2005, THEOR APPL GENET, V110, P778, DOI 10.1007/s00122-004-1905-4
   Nuruzzaman M, 2013, FRONT MICROBIOL, V4, DOI 10.3389/fmicb.2013.00248
   Park MR, 2010, PLANT CELL ENVIRON, V33, P2209, DOI 10.1111/j.1365-3040.2010.02221.x
   Rebolledo MC, 2015, J EXP BOT, V66, P5555, DOI 10.1093/jxb/erv258
   REICOSKY DC, 1989, AGR FOREST METEOROL, V46, P193, DOI 10.1016/0168-1923(89)90064-6
   Shi J, 2015, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00803
   Shimono H, 2011, CROP SCI, V51, P290, DOI 10.2135/cropsci2010.05.0300
   Shrestha R, 2014, ANN BOT-LONDON, V114, P1445, DOI 10.1093/aob/mcu032
   Shrestha S, 2013, ENVIRON EXP BOT, V89, P1, DOI 10.1016/j.envexpbot.2012.12.007
   Smita S, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.01157
   Song YL, 2012, SCI CHINA LIFE SCI, V55, P241, DOI 10.1007/s11427-012-4300-4
   Suzaki T, 2006, PLANT CELL PHYSIOL, V47, P1591, DOI 10.1093/pcp/pcl025
   SVED J A, 1971, Theoretical Population Biology, V2, P125
   Takasaki H, 2010, MOL GENET GENOMICS, V284, P173, DOI 10.1007/s00438-010-0557-0
   Wahl V, 2013, SCIENCE, V339, P704, DOI 10.1126/science.1230406
   Wopereis M. C. S., 2003, Decision support tools for smallholder agriculture in Sub-Saharan Africa: a practical guide, P114
   Xiong HY, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0092913
   Yin XY, 2005, J EXP BOT, V56, P967, DOI 10.1093/jxb/eri090
   Zhang S, 2013, EUR J AGRON, V45, P165, DOI 10.1016/j.eja.2012.10.005
   Zhang TY, 2008, AGR FOREST METEOROL, V148, P1412, DOI 10.1016/j.agrformet.2008.04.007
NR 52
TC 16
Z9 20
U1 3
U2 38
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0022-0957
EI 1460-2431
J9 J EXP BOT
JI J. Exp. Bot.
PD JUL 10
PY 2017
VL 68
IS 15
BP 4369
EP 4388
DI 10.1093/jxb/erx249
PG 20
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA FG4PH
UT WOS:000410245700029
PM 28922774
OA Bronze, Green Published
DA 2025-01-10
ER

PT J
AU Bremer, S
   Stiller-Reeve, M
   Mamnun, N
   Lazrus, H
AF Bremer, Scott
   Stiller-Reeve, Mathew
   Mamnun, Nabir
   Lazrus, Heather
TI Co-producing representations of summer rainfall in Bangladesh
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Climate adaptation; Co-production; Culture; Institutions; Seasonality;
   Symbols
ID CLIMATE-CHANGE; TRADITIONAL KNOWLEDGE; CULTURAL THEORY; ADAPTATION;
   COMMUNITIES; RISK
AB Climate adaptation governance increasingly investigates the cultural capacities of communities to cope with climate variability and change. This paper reports on research of the symbolic representations of summer rainfall in the cultural repertoires guiding diverse institutionalised fields of activity in Sylhet Division. The research conducted interviews and co-created 'cognitive maps' with communities, to critically reflect on their changing seasonal symbols. The study revealed a common stock of summer symbols in Sylhet communities, which individuals reconfigure for strategizing and justifying particular practices. Symbols are stable but not static. As people's uses of knowledge systems change-moving toward scientific representations-so too does their use of symbols. Moreover, environmental and climatic changes, such as a drying summer, are undermining long-held semiotic templates. Many local and traditional signs no longer hold, leaving communities without cultural templates for timely seasonal action. This work highlights the importance of cultural frameworks for organising communities' seasonal adaptation, and the imperative for critically revisiting frameworks in rapid flux.
C1 [Bremer, Scott] Univ Bergen, Ctr Study Sci & Humanities, Postboks 7805, N-5020 Bergen, Norway.
   [Stiller-Reeve, Mathew] Univ Bergen, Bjerknes Ctr Climate Res, NORCE Climate, Bergen, Norway.
   [Stiller-Reeve, Mathew] Univ Bergen, Ctr Climate & Energy Transformat, Bergen, Norway.
   [Mamnun, Nabir] Bangladesh Ctr Adv Studies, Dhaka, Bangladesh.
   [Mamnun, Nabir] Alfred Wegener Inst, Bremerhaven, Germany.
   [Lazrus, Heather] Natl Ctr Atmospher Res, Boulder, CO USA.
C3 University of Bergen; Norwegian Research Centre (NORCE); University of
   Bergen; Bjerknes Centre for Climate Research; University of Bergen;
   Helmholtz Association; Alfred Wegener Institute, Helmholtz Centre for
   Polar & Marine Research; National Center Atmospheric Research (NCAR) -
   USA
RP Bremer, S (corresponding author), Univ Bergen, Ctr Study Sci & Humanities, Postboks 7805, N-5020 Bergen, Norway.
EM scott.bremer@uib.no; mathew@stillerreeve.no; nabir.mamnun@gmail.com;
   hlazrus@ucar.edu
RI Mamnun, Nabir/I-7903-2019; Bremer, Scott/Q-6524-2017
OI Mamnun, Nabir/0000-0002-6650-8857
CR Abul Basher M, 2018, THEOR APPL CLIMATOL, V134, P441, DOI 10.1007/s00704-017-2285-4
   Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   [Anonymous], 2013, GLOBAL CHANGE ENERGY, DOI DOI 10.1007/978-94-007-6661-7
   [Anonymous], 2004, STATES KNOWLEDGE COP
   [Anonymous], 2017, The Daily Star
   [Anonymous], 1990, The Condition of Postmodernity: An Enquiry into the Origins of Cultural Change
   Bastian Michelle., 2012, Environmental Philosophy, V9, P23, DOI DOI 10.5840/ENVIROPHIL2012913
   Blanchard A, 2015, KNOW YOUR FOOD FOOD, P387, DOI [10.3920/978-90-8686-813-1, DOI 10.3920/978-90-8686-813-1]
   Bourdieu Pierre., 1977, CAMBRIDGE STUDIES SO, DOI [10.1017/CBO9780511812507, DOI 10.1017/CBO9780511812507]
   Bremer S, 2019, ENVIRON SCI POLICY, V94, P245, DOI 10.1016/j.envsci.2018.12.029
   Bremer S, 2018, WEATHER CLIM SOC, V10, P259, DOI 10.1175/WCAS-D-17-0033.1
   Bremer S, 2021, WIRES CLIM CHANGE, V12, DOI 10.1002/wcc.739
   Bremer S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.482
   Bremer S, 2017, WEATHER CLIM SOC, V9, P669, DOI 10.1175/WCAS-D-17-0007.1
   Crane D., 1994, SOCIOLOGY CULTURE, P1
   Deb AK, 2017, INT J CLIM CHANG STR, V9, P446, DOI [10.1108/ijccsm-06-2016-0078, 10.1108/IJCCSM-06-2016-0078]
   DiMaggio P.J., 1991, NEW IN SITU TIONALIS, P1
   Douglas M., 1986, How Institutions Think
   Dovers SR, 2010, WIRES CLIM CHANGE, V1, P212, DOI 10.1002/wcc.29
   Feola G, 2019, CLIMATE CULTURE MULT, DOI [10.1017/9781108505284, DOI 10.1017/9781108505284.010]
   Findlater K, 2021, NAT CLIM CHANGE, V11, P731, DOI 10.1038/s41558-021-01125-3
   Fischer L, 2021, SEASONS PHILOS LIT E
   FUNTOWICZ SO, 1993, FUTURES, V25, P739, DOI 10.1016/0016-3287(93)90022-L
   Garschagen M, 2013, NAT HAZARDS, V67, P25, DOI 10.1007/s11069-011-9753-4
   Geoghegan H, 2012, CLIMATIC CHANGE, V113, P55, DOI 10.1007/s10584-012-0417-5
   Haque MM, 2017, CLIM RISK MANAG, V16, P43, DOI 10.1016/j.crm.2016.12.002
   Hasan MK, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135384
   Hasan MK, 2019, J ENVIRON MANAGE, V237, P54, DOI 10.1016/j.jenvman.2019.02.028
   Hastrup K, 2016, ANTHROPOLOGY AND CLIMATE CHANGE: FROM ACTIONS TO TRANSFORMATIONS, 2ND EDITION, P35
   Hatfield SC, 2018, ECOL PROCESS, V7, DOI 10.1186/s13717-018-0136-6
   Hulme M., 2016, WEATHERED CULTURES C, DOI [10.4135/9781473957749, DOI 10.4135/9781473957749]
   Isaac ME, 2009, ENVIRON MANAGE, V43, P1321, DOI 10.1007/s00267-008-9201-8
   Jasanoff S, 2010, THEOR CULT SOC, V27, P233, DOI 10.1177/0263276409361497
   Kwiecien O, 2022, EARTH-SCI REV, V225, DOI 10.1016/j.earscirev.2021.103843
   Lazrus H, 2015, HUM ORGAN, V74, P52, DOI 10.17730/humo.74.1.q0667716284749m8
   Leonard S, 2013, GLOBAL ENVIRON CHANG, V23, P623, DOI 10.1016/j.gloenvcha.2013.02.012
   Levi-Strauss Claude., 1962, SAVAGE MIND
   López S, 2017, ANTHROPOCENE, V17, P30, DOI 10.1016/j.ancene.2017.01.001
   Mamun MAA, 2013, BBC MEDIA ACTION UK
   Mayer M, 2012, INT POLIT SOCIOL, V6, P165, DOI 10.1111/j.1749-5687.2012.00157.x
   McKemey M, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12030995
   McNeeley SM, 2014, WEATHER CLIM SOC, V6, P506, DOI 10.1175/WCAS-D-13-00027.1
   Meisch SP, 2022, FUTURES, V135, DOI 10.1016/j.futures.2021.102868
   Miller C., 2004, STATES OF KNOWLEDGE
   Orlove BenjaminS., 2003, Weather, climate, culture, DOI DOI 10.5040/9781474215947.CH-007
   Papageorgiou EI, 2013, IEEE T FUZZY SYST, V21, P66, DOI 10.1109/TFUZZ.2012.2201727
   Parkes-Nield S, 2022, NEW YORK TIMES BK R, P1, DOI [10.1080/14688417.2021.2023029, DOI 10.1080/14688417.2021.2023029]
   Penn HJF, 2016, WEATHER CLIM SOC, V8, P435, DOI 10.1175/WCAS-D-15-0061.1
   Rayner Steve., 2003, WEATHER CLIMATE CULT, P277
   Roncoli C., 2003, WEATHER CLIMATE CULT, P277
   Schmidt A, 2013, GLOBAL ENVIRON CHANG, V23, P1233, DOI 10.1016/j.gloenvcha.2013.07.020
   Scott WR, 2014, MANAGEMENT, V17, P136, DOI 10.3917/mana.172.0136
   SEWELL WH, 1992, AM J SOCIOL, V98, P1, DOI 10.1086/229967
   Sewell WH., 2004, PRACTICING HIST NEW, P76
   Shahvi S, 2021, SCI TOTAL ENVIRON, V750, DOI 10.1016/j.scitotenv.2020.142193
   Sheridan MJ, 2012, J EAST AFR STUD, V6, P230, DOI 10.1080/17531055.2012.669572
   Stiller-Reeve MA, 2016, WEATHER CLIM SOC, V8, P493, DOI 10.1175/WCAS-D-15-0054.1
   Stiller-Reeve MA, 2015, B AM METEOROL SOC, V96, P49, DOI 10.1175/BAMS-D-13-00144.1
   Strauss S, 2016, ANTHROPOLOGY AND CLIMATE CHANGE: FROM ACTIONS TO TRANSFORMATIONS, 2ND EDITION, P162
   Strauss S, 2012, WIRES CLIM CHANGE, V3, P371, DOI 10.1002/wcc.181
   SWIDLER A, 1986, AM SOCIOL REV, V51, P273, DOI 10.2307/2095521
   Totin E, 2018, NJAS-WAGEN J LIFE SC, V84, P27, DOI 10.1016/j.njas.2017.07.002
   Vaisey S, 2009, AM J SOCIOL, V114, P1675, DOI 10.1086/597179
NR 63
TC 4
Z9 4
U1 0
U2 1
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD JUN
PY 2023
VL 23
IS 2
AR 60
DI 10.1007/s10113-023-02057-8
PG 17
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA C7LL1
UT WOS:000963688300002
OA hybrid
DA 2025-01-10
ER

PT J
AU Habib, B
AF Habib, Benjamin
TI Climate Change and Regime Perpetuation in North Korea
SO ASIAN SURVEY
LA English
DT Article
DE North Korea; climate change; regime change; Kim Jong-il; adaptive
   capacity
AB Climate change is a new variable that may weaken the Kim Jong-il regime by disrupting North Korea's agricultural sector, leading to greater food insecurity and erosion of the state's institutions. North Korea has limited capacity to adapt to climate hazards, which could exacerbate existing stresses and push the regime into terminal decay.
C1 La Trobe Univ, Sch Social Sci, Albury, NSW, Australia.
C3 La Trobe University
RP Habib, B (corresponding author), La Trobe Univ, Sch Social Sci, Albury, NSW, Australia.
EM b.habib@latrobe.edu.au
RI Habib, Benjamin/J-3502-2019
OI Habib, Benjamin/0000-0003-3087-4828
CR [Anonymous], DPRK EN EXP WORK GRO
   ASHER D, 2005, NAUTILUS I SECURITY
   Bates R., 2003, POLITICAL INSTABILIT, P9
   BECK P, 2008, COMMUNICATION   0722
   BECK P, 2005, N KOREA CAN IRON FIS, P4
   BUZAN B, 1991, PEOPLE STATES FEAR A, P90
   CAMPBELL K, 2008, CLIMATIC CATACLYSM F, P14
   Chestnut S, 2007, INT SECURITY, V32, P80, DOI 10.1162/isec.2007.32.1.80
   Chung YS, 2004, CLIMATIC CHANGE, V66, P151, DOI 10.1023/B:CLIM.0000043141.54763.f8
   CRUZ RV, 2007, CLIMATE CHANGE 2007, P483
   Dupont A, 2008, SURVIVAL, V50, P29, DOI 10.1080/00396330802173107
   Eberstadt N, 1997, FOREIGN AFF, V76, P77, DOI 10.2307/20047938
   Friedrich Carl, 1966, TOTALITARIAN DICTATO, P21
   Füssel HM, 2007, GLOBAL ENVIRON CHANG, V17, P155, DOI 10.1016/j.gloenvcha.2006.05.002
   GOODKIND D, 2001, POPUL DEV REV, V27, P199
   HAGGARD S, 2007, FAMINE N KOREA MARKE, P21
   HAGGARD S, 2007, N KOREAS EXTERNAL EC, P14
   Hansen J.E., 2007, ENV RESARCH LETT, V2, P1
   HANSEN JM, 2008, ARXIV08041126V2PHYSI, P12
   HOMERDIXON T, 2006, UPSIDE DOWN CATASTRO, P41
   HULTMAN N, 2006, J INT AFF, V59, P26
   INHO P, 2008, COMMUNICATION   0728
   KIM IP, 2006, N KOREA POLITICS REG, P64
   KIM SC, 2002, DEV SOC, V31, P95
   KYUNGWON K, 1996, HARVARD INT REV, V18, P71
   KYUNGWON K, 2005, HARVARD INT REV, P58
   KYUNGWON K, 1996, HARVARD INT REV, V18, P22
   LANKOV A, 2007, N DMZ ESSAYS DAILY L, P66
   MANSOUROV A, 2007, DISASTER MANAGEMENT, P4
   McLeman R, 2006, CLIMATIC CHANGE, V76, P31, DOI 10.1007/s10584-005-9000-7
   MUNASINGHE M, 2005, PRIMER CLIMATE CHANG, P187
   Noland M, 1997, FOREIGN AFF, V76, P105, DOI 10.2307/20048125
   NOLAND M, 2006, PETERSON I INT  0425
   PARK H, 2002, N KOREA POLITICS UNC, P20
   PINISTON D, 2003, NONPROLIFERATION REV, V10, P9
   Scobell Andrew, 2006, KIM JON IL N KOREA L, P34
   SMITH D, 2007, CLIMATE CONFLICT LIN, P21
   SMITH H, 2000, PROMOTING INT SCI TE, P205
   SPRATT D, 2008, CLIMATE CODE RED CAS, P17
   Tainter Joseph A., 1988, COLLAPSE COMPLEX SOC, P23
   Warren Rachel, 2006, UNDERSTANDING REGION, P35
   WOO MJE, 2005, ASIAN SURV, V46, P54
   2008, DAILY NK        0728
   2007, WORLD REPORT 2007, P297
NR 44
TC 11
Z9 11
U1 0
U2 8
PU UNIV CALIFORNIA PRESS
PI OAKLAND
PA 155 GRAND AVE, SUITE 400, OAKLAND, CA 94612-3758 USA
SN 0004-4687
EI 1533-838X
J9 ASIAN SURV
JI Asian Surv.
PD MAR-APR
PY 2010
VL 50
IS 2
BP 378
EP 401
DI 10.1525/as.2010.50.2.378
PG 24
WC Area Studies
WE Social Science Citation Index (SSCI)
SC Area Studies
GA 601ZY
UT WOS:000278109100006
DA 2025-01-10
ER

PT J
AU Zhu, HS
   Qi, FF
   Wang, XY
   Zhang, YH
   Chen, FJW
   Cai, ZK
   Chen, YY
   Chen, KZ
   Chen, HB
   Xie, ZH
   Chen, GM
   Zhu, YY
   Zhang, XY
   Han, X
   Wu, SG
   Chen, S
   Fu, YY
   He, F
   Weng, YW
   Ou, JM
AF Zhu, Hansong
   Qi, Feifei
   Wang, Xiaoying
   Zhang, Yanhua
   Chen, Fangjingwei
   Cai, Zhikun
   Chen, Yuyan
   Chen, Kaizhi
   Chen, Hongbin
   Xie, Zhonghang
   Chen, Guangmin
   Zhu, Yiyang
   Zhang, Xiaoyuan
   Han, Xu
   Wu, Shenggen
   Chen, Si
   Fu, Yuying
   He, Fei
   Weng, Yuwei
   Ou, Jianming
TI Study of the driving factors of the abnormal influenza A (H3N2) epidemic
   in 2022 and early predictions in Xiamen, China
SO BMC INFECTIOUS DISEASES
LA English
DT Article
DE Influenza; Meteorological factors; Air quality; Phylogenetic analysis;
   LSTM; Random forest (RF)
ID HUMIDITY; TEMPERATURE; PERIOD
AB Background Influenza outbreaks have occurred frequently these years, especially in the summer of 2022 when the number of influenza cases in southern provinces of China increased abnormally. However, the exact evidence of the driving factors involved in the prodrome period is unclear, posing great difficulties for early and accurate prediction in practical work. Methods In order to avoid the serious interference of strict prevention and control measures on the analysis of influenza influencing factors during the COVID-19 epidemic period, only the impact of meteorological and air quality factors on influenza A (H3N2) in Xiamen during the non coronavirus disease 2019 (COVID-19) period (2013/01/01-202/01/24) was analyzed using the distribution lag non-linear model. Phylogenetic analysis of influenza A (H3N2) during 2013-2022 was also performed. Influenza A (H3N2) was predicted through a random forest and long short-term memory (RF-LSTM) model via actual and forecasted meteorological and influenza A (H3N2) values. Results Twenty nine thousand four hundred thirty five influenza cases were reported in 2022, accounting for 58.54% of the total cases during 2013-2022. A (H3N2) dominated the 2022 summer epidemic season, accounting for 95.60%. The influenza cases in the summer of 2022 accounted for 83.72% of the year and 49.02% of all influenza reported from 2013 to 2022. Among them, the A (H3N2) cases in the summer of 2022 accounted for 83.90% of all A (H3N2) reported from 2013 to 2022. Daily precipitation(20-50 mm), relative humidity (70-78%), low (<= 3 h) and high (>= 7 h) sunshine duration, air temperature (<= 21 degrees C) and O-3 concentration (<= 30 mu g/m(3), > 85 mu g/m(3)) had significant cumulative effects on influenza A (H3N2) during the non-COVID-19 period. The daily values of PRE, RHU, SSD, and TEM in the prodrome period of the abnormal influenza A (H3N2) epidemic (19-22 weeks) in the summer of 2022 were significantly different from the average values of the same period from 2013 to 2019 (P < 0.05). The minimum RHU value was 70.5%, the lowest TEM value was 16.0 degrees C, and there was no sunlight exposure for 9 consecutive days. The highest O-3 concentration reached 164 <mu>g/m(3). The range of these factors were consistent with the risk factor range of A (H3N2). The common influenza A (H3N2) variant genotype in 2022 was 3 C.2a1b.2a.1a. It was more accurate to predict influenza A (H3N2) with meteorological forecast values than with actual values only. Conclusion The extreme weather conditions of sustained low temperature and wet rain may have been important driving factors for the abnormal influenza A (H3N2) epidemic. A low vaccination rate, new mutated strains, and insufficient immune barriers formed by natural infections may have exacerbated this epidemic. Meteorological forecast values can aid in the early prediction of influenza outbreaks. This study can help relevant departments prepare for influenza outbreaks during extreme weather, provide a scientific basis for prevention strategies and risk warnings, better adapt to climate change, and improve public health.
C1 [Zhu, Hansong; Zhang, Yanhua; Cai, Zhikun; Chen, Hongbin; Xie, Zhonghang; Chen, Guangmin; Wu, Shenggen; Weng, Yuwei; Ou, Jianming] Fujian Prov Ctr Dis Control & Prevent, Fuzhou 350012, Fujian, Peoples R China.
   [Zhu, Hansong; Xie, Zhonghang; Chen, Guangmin; Wu, Shenggen; He, Fei; Weng, Yuwei; Ou, Jianming] Fujian Med Univ, Sch Publ Hlth, Fuzhou 350011, Fujian, Peoples R China.
   [Qi, Feifei] Xi An Jiao Tong Univ, Sch Publ Hlth, Xian 710061, Shanxi, Peoples R China.
   [Wang, Xiaoying] Xiamen Univ, Sch Publ Hlth, Xiamen 361100, Fujian, Peoples R China.
   [Chen, Fangjingwei] Fujian Normal Univ, Sch Geog Sci Sch Carbon Neutral Future Technol, Sch Carbon Neutral Future Technol, Fuzhou 350117, Fujian, Peoples R China.
   [Chen, Yuyan] Fujian Prov Judicial Drug Rehabil Hosp, Fuzhou 350007, Fujian, Peoples R China.
   [Chen, Kaizhi] Fuzhou Univ, Fuzhou 350108, Fujian, Peoples R China.
   [Zhu, Yiyang] Fuzhou Huayuan Primary Sch, Fuzhou 350001, Fujian, Peoples R China.
   [Zhang, Xiaoyuan; Han, Xu] Fujian Univ Tradit Chinese Med, Fuzhou 350108, Fujian, Peoples R China.
   [Chen, Si] Fujian Inst Meteorol Sci, Fuzhou 350001, Fujian, Peoples R China.
   [Chen, Si] Fujian Prov Key Lab Disaster Weather, Fuzhou 350007, Fujian, Peoples R China.
   [Chen, Si] China Meteorol Adm, Key Open Lab Straits Disaster Weather, Fuzhou 350007, Fujian, Peoples R China.
   [Fu, Yuying] Fujian Chuanzheng Commun Coll, Fuzhou 350007, Peoples R China.
   [Qi, Feifei] Xi An Jiao Tong Univ, Key Lab Environm & Genes Related Dis, Minist Educ, Xian 710061, Peoples R China.
C3 Fujian Medical University; Xi'an Jiaotong University; Xiamen University;
   Fujian Normal University; Fuzhou University; Fujian University of
   Traditional Chinese Medicine; China Meteorological Administration;
   Fujian Chuanzheng Communications College; Xi'an Jiaotong University
RP Zhu, HS; Wu, SG; Weng, YW; Ou, JM (corresponding author), Fujian Prov Ctr Dis Control & Prevent, Fuzhou 350012, Fujian, Peoples R China.; Zhu, HS; Wu, SG; He, F; Weng, YW; Ou, JM (corresponding author), Fujian Med Univ, Sch Publ Hlth, Fuzhou 350011, Fujian, Peoples R China.; Chen, S (corresponding author), Fujian Inst Meteorol Sci, Fuzhou 350001, Fujian, Peoples R China.; Chen, S (corresponding author), Fujian Prov Key Lab Disaster Weather, Fuzhou 350007, Fujian, Peoples R China.; Chen, S (corresponding author), China Meteorol Adm, Key Open Lab Straits Disaster Weather, Fuzhou 350007, Fujian, Peoples R China.; Fu, YY (corresponding author), Fujian Chuanzheng Commun Coll, Fuzhou 350007, Peoples R China.
EM hszhu33@126.com; lxbywstj@126.com; chensifuzhou@126.com;
   2021003@fjcpc.edu.cn; i.fei.he@fjmu.edu.cn; wengywfjcdc@aliyun.com;
   ojmfj@vip.sina.com
RI Hansong Zhu, 祝寒松/IAN-2892-2023; Fu, Yuying/Z-5839-2019; He,
   Fei/IZQ-3336-2023
FU Natural Science Foundation of Fujian Province; Standard Map Service
   Network; Xiamen medical and health institutions and Xiamen Municipal
   Bureau of Statistics
FX We would like to thank the Standard Map Service Network, the air quality
   data network of the China National Environmental Monitoring Centre,
   Xiamen medical and health institutions and Xiamen Municipal Bureau of
   Statistics.
CR Ali ST, 2018, EUR RESPIR J, V51, DOI 10.1183/13993003.00369-2018
   [Anonymous], Health industry standard of the People's Republic of China (Diagnostic criteria for influenza) (WS285-2008)
   [Anonymous], Summary of notifiable infectious diseases in China
   [Anonymous], 2022, Xiamen Climate Annual Report
   [Anonymous], Chinese Weekly Influenza Surveillance Report(Week 38)
   Behr A, 2019, APPL ECON, V51, P5345, DOI 10.1080/00036846.2019.1613499
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Caini S, 2018, ENVIRON RES, V167, P307, DOI 10.1016/j.envres.2018.07.035
   Chen Y, 2023, BMC PUBLIC HEALTH, V23, DOI 10.1186/s12889-023-16712-6
   Chicco D, 2021, PEERJ COMPUT SCI, DOI 10.7717/peerj-cs.623
   Dangi T, 2014, INDIAN J MED RES, V139, P418
   Du MX, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0277045
   Ebi KL, 2021, ANNU REV PUBL HEALTH, V42, P293, DOI 10.1146/annurev-publhealth-012420-105026
   Gasparrini A, 2010, STAT MED, V29, P2224, DOI 10.1002/sim.3940
   [胡衍坤 Hu Yankun], 2021, [小型微型计算机系统, Journal of Chinese Computer Systems], V42, P1569
   Im U, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.954045
   Iuliano AD, 2018, LANCET, V391, P1285, DOI 10.1016/S0140-6736(17)33293-2
   Jaramillo L, 2024, CULT ORGAN, V30, P291, DOI 10.1080/14759551.2023.2206132
   Lam EKS, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-16545-6
   Lau SYF, 2021, INFLUENZA OTHER RESP, V15, P513, DOI 10.1111/irv.12829
   Li JL, 2023, VIRUSES-BASEL, V15, DOI 10.3390/v15010116
   Liu XX, 2019, INT J BIOMETEOROL, V63, P51, DOI 10.1007/s00484-018-1633-0
   Lowen AC, 2014, J VIROL, V88, P7692, DOI 10.1128/JVI.03544-13
   Lu JY, 2021, SCI TOTAL ENVIRON, V776, DOI 10.1016/j.scitotenv.2021.145967
   Nuvolone D, 2018, ENVIRON SCI POLLUT R, V25, P8074, DOI 10.1007/s11356-017-9239-3
   Park JE, 2020, INFLUENZA OTHER RESP, V14, P11, DOI 10.1111/irv.12682
   Paynter S, 2015, EPIDEMIOL INFECT, V143, P1110, DOI 10.1017/S0950268814002702
   Petrova VN, 2018, NAT REV MICROBIOL, V16, P60, DOI [10.1038/nrmicro.2017.118, 10.1038/nrmicro.2017.146]
   Pluth TB, 2021, WATER ENVIRON RES, DOI 10.1002/wer.1668
   Shin HH, 2022, SCI TOTAL ENVIRON, V806, DOI 10.1016/j.scitotenv.2021.150515
   Sitati A, 2021, DISCOV SUSTAIN, V2, DOI 10.1007/s43621-021-00052-9
   Sooryanarain H, 2015, ANNU REV ANIM BIOSCI, V3, P347, DOI 10.1146/annurev-animal-022114-111017
   Troeger CE, 2019, LANCET RESP MED, V7, P69, DOI [10.1016/S2213-2600(18)30496-X, 10.1016/s2213-2600(18)30496-x]
   Uyeki TM, 2022, LANCET, V400, P693, DOI 10.1016/S0140-6736(22)00982-5
   Wang DA, 2023, VIRUSES-BASEL, V15, DOI 10.3390/v15030594
   Wang J Y, 2018, Zhonghua Yu Fang Yi Xue Za Zhi, V52, P842, DOI 10.3760/cma.j.issn.0253-9624.2018.08.013
   Wang JY, 2022, FRONT PUBLIC HEALTH, V10, DOI 10.3389/fpubh.2022.833710
   Yang J, 2023, BMC INFECT DIS, V23, DOI 10.1186/s12879-023-08769-w
   Yang J, 2023, EBIOMEDICINE, V87, DOI 10.1016/j.ebiom.2022.104421
   Yin P, 2020, LANCET PLANET HEALTH, V4, pE386, DOI 10.1016/S2542-5196(20)30161-3
   Zhang B, 2022, SCI TOTAL ENVIRON, V852, DOI 10.1016/j.scitotenv.2022.158525
   Zhang R, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18116174
   Zhang Y Q, 2016, Zhonghua Yu Fang Yi Xue Za Zhi, V50, P634, DOI 10.3760/cma.j.issn.0253-9624.2016.07.014
   Zheng YL, 2021, ENVIRON SCI POLLUT R, V28, P473, DOI 10.1007/s11356-020-10523-7
   Zhou LL, 2022, EPIDEMICS-NETH, V41, DOI 10.1016/j.epidem.2022.100650
   Zhu HS, 2024, BMC INFECT DIS, V24, DOI 10.1186/s12879-024-09750-x
   Zhu HS, 2022, BMC PUBLIC HEALTH, V22, DOI 10.1186/s12889-022-14299-y
NR 47
TC 1
Z9 1
U1 2
U2 2
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
EI 1471-2334
J9 BMC INFECT DIS
JI BMC Infect. Dis.
PD OCT 2
PY 2024
VL 24
IS 1
AR 1093
DI 10.1186/s12879-024-09996-5
PG 21
WC Infectious Diseases
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Infectious Diseases
GA I0C0W
UT WOS:001327011600004
PM 39358703
OA gold
DA 2025-01-10
ER

PT J
AU Richards, D
   Allen, K
   Graham, S
   Harcourt, N
   Kirk, N
   Lavorel, S
   Mcnally, S
   Polyakov, M
   Whitehead, D
AF Richards, Daniel
   Allen, Kara
   Graham, Scott
   Harcourt, Nikki
   Kirk, Nick
   Lavorel, Sandra
   Mcnally, Sam
   Polyakov, Maksym
   Whitehead, David
TI Carbon stocks and sequestration from small tree patches in grassland
   landscapes in Aotearoa-New Zealand
SO CLIMATE POLICY
LA English
DT Article; Early Access
DE Emissions trading scheme; climate change adaptation; climate change
   mitigation; carbon policy
ID SCATTERED TREES; BIODIVERSITY; MANAGEMENT; FUTURE; AREA; REFORESTATION;
   CONSERVATION; CATCHMENTS; GRADIENTS; LIVESTOCK
AB Small patches of trees add structural heterogeneity to grassland landscapes, support biodiversity, and provide essential ecosystem services including carbon stocks and sequestration, erosion control, and shade provision. In Aotearoa-New Zealand (A-NZ) small patches of trees have further cultural significance within Te Ao M & amacr;ori - the worldview of the indigenous M & amacr;ori people. However, economic pressures have driven the management of grasslands either towards removing tree cover to enhance agricultural productivity, or large-scale conversion of grassland to production forests. Protecting existing small patches of trees, and encouraging their establishment across grassland landscapes, is challenging since the current extent and benefits of these patches is not known. This study demonstrates the critical contributions of small tree patches (those less than one hectare in area) in A-NZ grassland landscapes. Using a high-resolution tree cover dataset, we mapped 1,639,015 small tree patches in grasslands across A-NZ, with grassland small tree patches covering a total land area of between 185,589 ha and 187,928 ha. We used a probabilistic simulation approach to estimate carbon stocks and annual sequestration, revealing a potential aboveground carbon stock between 11.6 and 29.3 million tonnes (Mt) of carbon and an annual biomass sequestration of 0.3 Mt to 0.8 Mt. Despite their current exclusion from the national carbon emissions market, economic valuation suggests a liability of between $NZ 86.9 million and $NZ 8.6 billion (<euro>47.9 million to <euro>4.7. billion) if the small tree patches were felled, and a market value of between $NZ 2.0 million and $NZ 237.6 million (<euro>1.1 and 130.9 million) annually for sequestration. Existing policies, including afforestation incentives, do not encourage protection or establishment of small patches of trees. Significant policy adjustments are required to recognize, protect, and incentivize the conservation and establishment of small patches of trees within grassland landscapes.
C1 [Richards, Daniel; Allen, Kara; Graham, Scott; Kirk, Nick; Lavorel, Sandra; Mcnally, Sam; Whitehead, David] Manaaki Whenua Landcare Res, 76 Gerald St, Lincoln, New Zealand.
   [Harcourt, Nikki] Manaaki Whenua Landcare Res, Hamilton, New Zealand.
   [Lavorel, Sandra] Univ Grenoble Alpes, Univ Savoie Mt Blanc, CNRS, Grenoble, France.
   [Polyakov, Maksym] Manaaki Whenua Landcare Res, Auckland, New Zealand.
C3 Landcare Research - New Zealand; Landcare Research - New Zealand;
   Communaute Universite Grenoble Alpes; Universite Grenoble Alpes (UGA);
   Centre National de la Recherche Scientifique (CNRS); Universite Savoie
   Mont Blanc; Landcare Research - New Zealand
RP Richards, D (corresponding author), Manaaki Whenua Landcare Res, 76 Gerald St, Lincoln, New Zealand.
EM richardsd@landcareresearch.co.nz
RI Polyakov, Maksym/G-1523-2010
FU Ministry of Business, Innovation and Employment Endeavour Fund
   [C09X2209]
FX Funding for this work was provided to Manaaki Whenua - Landcare Research
   from the Ministry of Business, Innovation and Employment Endeavour Fund,
   contract number C09X2209.
CR Abbott M, 2019, J LANDSC ARCHIT, V14, P6, DOI 10.1080/18626033.2019.1673562
   Accatino F, 2019, AGR SYST, V168, P58, DOI 10.1016/j.agsy.2018.08.002
   Adams T, 2012, FOREST POLICY ECON, V15, P78, DOI 10.1016/j.forpol.2011.09.010
   [Anonymous], 2022, Climate Change (Forestry) Regulations 2022, Schedule 4
   Barbera G., 2016, Biocultural Diversity in Europe, Environmental History, V5, P21
   Bardgett RD, 2021, NAT REV EARTH ENV, V2, P720, DOI 10.1038/s43017-021-00207-2
   Basher LR, 2013, ECOSYSTEM SERVICES IN NEW ZEALAND: CONDITIONS AND TRENDS, P363
   Bastin JF, 2019, SCIENCE, V365, P76, DOI 10.1126/science.aax0848
   Bateman IJ, 2023, PEOPLE NAT, V5, P271, DOI 10.1002/pan3.10331
   Bell DM, 2017, ECOL APPL, V27, P1666, DOI 10.1002/eap.1560
   Bergin DO, 2000, NEW ZEAL J BOT, V38, P343
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Brooking T., 2002, Environmental Histories of New Zealand
   Carswell F., 2014, Tools to predict carbon sequestration in regenerating shrublands
   Case B, 2020, ANAL CARBON STOCKS N
   Centeri C., 2016, Biocultural diversity in Europe. Environmental history, V5, P75, DOI [10.1007/978-3-319-26315-1_4, DOI 10.1007/978-3-319-26315-14]
   CHEN JQ, 1995, ECOL APPL, V5, P74, DOI 10.2307/1942053
   Connor H, 2021, GENEALOGY-BASEL, V5, DOI 10.3390/genealogy5020029
   Cubbage F, 2012, AGROFOREST SYST, V86, P303, DOI 10.1007/s10457-012-9482-z
   Deniz M, 2023, INT J BIOMETEOROL, V67, P409, DOI 10.1007/s00484-023-02431-5
   Du ZR, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01260-2
   Easdale T., 2021, MPI Technical Paper No: 2021/21
   Efron B., 1986, Statistical Science, V1, P54
   England JR, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135345
   Ewers RM, 2006, BIOL CONSERV, V133, P312, DOI 10.1016/j.biocon.2006.06.018
   Garvey SM, 2022, GLOBAL CHANGE BIOL, V28, P3094, DOI 10.1111/gcb.16099
   Gehlhausen SM, 2000, PLANT ECOL, V147, P21, DOI 10.1023/A:1009846507652
   Gibbons P, 2008, CONSERV BIOL, V22, P1309, DOI 10.1111/j.1523-1739.2008.00997.x
   Gibbons Philip, 2002, Ecological Management & Restoration, V3, P205, DOI 10.1046/j.1442-8903.2002.00114.x
   Gillson L, 2024, TRENDS ECOL EVOL, V39, P359, DOI 10.1016/j.tree.2023.11.008
   Goulter C., 2010, SFF Project L09/023 Report
   Government of South Australia, 2023, A comparison of participating in the Emissions Reduction Fund under the plantation forestry method versus the farm forestry method
   Gregory NG, 1995, NEW ZEAL J AGR RES, V38, P423, DOI 10.1080/00288233.1995.9513146
   Gril E, 2023, REMOTE SENS ENVIRON, V298, DOI 10.1016/j.rse.2023.113820
   Harcourt N, 2022, AUSTRALAS J WAT RESO, V26, P116, DOI 10.1080/13241583.2022.2031571
   Hawke M. F., 2003, NZGA: Research and Practice Series, V72th
   HAWLEY JG, 1988, J SOIL WATER CONSERV, V43, P495
   Hijmans R. J., 2014, GEOSPHERE SPHERICAL
   Jobbágy EG, 2000, ECOL APPL, V10, P423, DOI 10.2307/2641104
   Jonas H. D., 2017, PARKS, V23, P63, DOI [DOI 10.2305/IUCN.CH.2017.PARKS-23-2HDJ.EN, 10.2305/iucn.ch.2017.parks-232hdj.en, 10.2305/IUCN.CH.2017.PARKS-23-2HDJ.en]
   Jönsson MT, 2007, FOREST ECOL MANAG, V242, P306, DOI 10.1016/j.foreco.2007.01.048
   Keller ED, 2014, GEOSCI MODEL DEV, V7, P2359, DOI 10.5194/gmd-7-2359-2014
   Kremen C, 2018, SCIENCE, V362, DOI 10.1126/science.aau6020
   Leining C, 2020, CLIM POLICY, V20, P246, DOI 10.1080/14693062.2019.1699773
   Liu SY, 2023, SCI ADV, V9, DOI 10.1126/sciadv.adh4097
   Loreau M, 2021, BIOL REV, V96, P2333, DOI 10.1111/brv.12756
   Mackay-Smith TH, 2024, NEW ZEAL J AGR RES, DOI 10.1080/00288233.2023.2298922
   Manaaki Whenua-Landcare Research, 2021, LCDB v5.0-Land Cover Database version 5.0
   Marden M., 1993, New Zealand Journal of Forestry Science, V23, P255
   Marden M, 2012, NEW ZEAL GEOGR, V68, P24, DOI 10.1111/j.1745-7939.2012.01218.x
   Mark AF, 2005, NEW ZEAL J BOT, V43, P245, DOI 10.1080/0028825X.2005.9512953
   McCarthy JK, 2021, NEW ZEAL J ECOL, V45, DOI 10.20422/nzjecol.45.31
   McGowan R., 2011, Rongoa Maori: A practical guide to traditional maori medicine
   Meeussen C, 2021, SCI TOTAL ENVIRON, V759, DOI 10.1016/j.scitotenv.2020.143497
   Meurk CD, 2000, LANDSCAPE URBAN PLAN, V50, P129, DOI 10.1016/S0169-2046(00)00085-2
   Ministry for the Environment, 2023, New Zealand's Greenhouse Gas Inventory 1990-2021
   Ministry for the Environment, 2022, Aotearoa New Zealand's First Emissions Reduction Plan. No.978-1-99-102526-5).
   Ministry for the Environment, 2021, Te hau marohi ki anamata: Transitioning to a low-emissions and climate-resilient future
   Ministry for the Environment, 2020, Net emissions and removals from vegetation and soils on sheep and beef farmland
   Moller H, 2008, NEW ZEAL J AGR RES, V51, P253, DOI 10.1080/00288230809510453
   Morgenroth J, 2022, URBAN FOR URBAN GREE, V68, DOI 10.1016/j.ufug.2022.127468
   Morreale LL, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-27373-7
   Morrisey D., 2007, Auckland Regional Council Technical Publication, VTP325
   New Zealand Ministry for Primary Industries, 2023, How forest land is defined in the ETS
   Norton DA, 2020, NEW ZEAL J ECOL, V44, DOI 10.20417/nzjecol.44.15
   Olofsson P, 2014, REMOTE SENS ENVIRON, V148, P42, DOI 10.1016/j.rse.2014.02.015
   Olofsson P, 2013, REMOTE SENS ENVIRON, V129, P122, DOI 10.1016/j.rse.2012.10.031
   Orefice J, 2017, AGROFOREST SYST, V91, P149, DOI 10.1007/s10457-016-9916-0
   Orme P., 2022, Report produced for Beef + Lamb NZ
   Ozolins Amanda, 2001, Pacific Conservation Biology, V7, P195
   Pannell JL, 2021, NEW ZEAL J ECOL, V45, DOI 10.20417/nzjecol.45.11
   Paul KI, 2016, LAND USE POLICY, V51, P135, DOI 10.1016/j.landusepol.2015.10.027
   Paul T., 2021, MPI Technical Paper No: 2022/12
   Polyakov M., 2022, Landcare Research Contract Report Number LC4108 produced for the Climate Change Commission
   Portner H.-O., 2021, IPBES, DOI [10.5281/zenodo.4782538, DOI 10.5281/ZENODO.4782538]
   Prevedello JA, 2018, J APPL ECOL, V55, P205, DOI 10.1111/1365-2664.12943
   Quinn JM, 2002, NEW ZEAL J MAR FRESH, V36, P409, DOI 10.1080/00288330.2002.9517097
   R Core Team, 2017, R LANG ENV STAT COMP
   Reinmann AB, 2017, P NATL ACAD SCI USA, V114, P107, DOI 10.1073/pnas.1612369114
   Remy E, 2016, FOREST ECOL MANAG, V376, P45, DOI 10.1016/j.foreco.2016.05.040
   Richards D, 2023, ECOSYST PEOPLE, V19, DOI 10.1080/26395916.2023.2225647
   Richards DR, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18118-z
   Robson-Williams M, 2023, GAIA, V32, P126, DOI 10.14512/gaia.32.1.9
   Sales-Baptista E, 2021, AGROFOREST SYST, V95, P1, DOI 10.1007/s10457-020-00581-8
   Schipper LA, 2017, NEW ZEAL J AGR RES, V60, P93, DOI 10.1080/00288233.2017.1284134
   Schons S., 2024, CNRE-177P
   Seddon N, 2021, GLOBAL CHANGE BIOL, V27, P1518, DOI 10.1111/gcb.15513
   Smallfield P. W., 1970, The grassland revolution in New Zealand
   Smith IA, 2018, FRONT ECOL ENVIRON, V16, P213, DOI 10.1002/fee.1793
   Smith P, 2022, GLOBAL CHANGE BIOL, V28, P2555, DOI 10.1111/gcb.16056
   Spiekermann RI, 2022, GEOMORPHOLOGY, V396, DOI 10.1016/j.geomorph.2021.107993
   Spiekermann RI, 2021, J ENVIRON MANAGE, V286, DOI 10.1016/j.jenvman.2021.112194
   Streck C, 2023, CLIM POLICY, DOI 10.1080/14693062.2023.2230940
   Suyadi, 2020, ESTUAR COAST, V43, P1456, DOI 10.1007/s12237-020-00736-x
   Theecanmole, 2016, Zenodo, DOI 10.5281/zenodo.221328
   Torralba M, 2016, AGR ECOSYST ENVIRON, V230, P150, DOI 10.1016/j.agee.2016.06.002
   Tozer K, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.550334
   Veldman JW, 2015, BIOSCIENCE, V65, P1011, DOI 10.1093/biosci/biv118
   West TAP, 2020, ECOSYST SERV, V46, DOI 10.1016/j.ecoser.2020.101212
   Whitehead D, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01837-4
   Whitehead D, 2020, FRONT SUSTAIN FOOD S, V4, DOI 10.3389/fsufs.2020.585913
   Whitehead D, 2018, AGR ECOSYST ENVIRON, V265, P432, DOI 10.1016/j.agee.2018.06.022
   Woodland Carbon Code, 2024, Eligible activities-Soil types and landuse
   Zanaga Daniele, 2021, Zenodo, DOI 10.5281/ZENODO.5571935
   Zhang JJ, 2021, ECOL INDIC, V129, DOI 10.1016/j.ecolind.2021.107962
   Zhao YY, 2020, LANDSCAPE ECOL, V35, P793, DOI 10.1007/s10980-020-00980-3
NR 106
TC 0
Z9 0
U1 0
U2 0
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PD 2024 NOV 23
PY 2024
DI 10.1080/14693062.2024.2427710
EA NOV 2024
PG 19
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA N0A2U
UT WOS:001361056600001
DA 2025-01-10
ER

PT J
AU Martinez, V
   Mantas, J
   Hulke, J
   Gituku, B
   Ndiema, N
   Elkouby, M
   Thompson, A
   Cantoadams, J
   Yeh, SRA
   Vanleeuwen, A
   Young, H
   Titcomb, G
AF Martinez, Viviana
   Mantas, John
   Hulke, Jenna
   Gituku, Benard
   Ndiema, Nickson
   Elkouby, Malik
   Thompson, Asher
   Cantoadams, Joelle
   Yeh, Serena
   Vanleeuwen, Adam
   Young, Hillary
   Titcomb, Georgia
TI Interacting effects of surface water and temperature on wild and
   domestic large herbivore aggregations and contact rates
SO JOURNAL OF APPLIED ECOLOGY
LA English
DT Article
DE camera trap; climate change adaptation; ecological hotspot;
   interspecific disease transmission; temporal niche partitioning;
   waterhole; wildlife-livestock interface
ID AFRICAN; HOTSPOTS; CATTLE
AB Earth's climate is rapidly changing, bringing forth questions of how domestic and wild animals will alter their behaviour in response to increasing temperatures and dryland expansion. Dwindling water availability will likely impact animal behaviour and water foraging, potentially increasing animal aggregations and interspecific contacts. These interspecific contacts are especially important for competition, predation and disease transmission among wildlife and domestic animals. In this study, we analysed interspecific wildlife and cattle contacts using two years of camera trap data at an experimental water manipulation site at a conservancy in central Kenya. We found that on average, the hourly probability of any interspecific contact was approximately 3.4 times higher at water sources versus drained water sources and 18 times higher than surrounding matrix areas, and that this relationship was amplified by dry and hot conditions. Species-specific analyses revealed variation in the magnitude of responses across wildlife and domestic cattle, although all animals had approximately 2-3 times higher interspecific contact probability with other species at water in hot conditions versus other conditions. Notably, we observed the largest behavioural changes for relatively water-independent species, such as giraffe, which had 3.6 times higher interspecific contact probability at water sources in hot versus other conditions. Synthesis and applications. These findings show how elevated temperatures that will become increasingly common with future climate changes can increase interspecific contacts around critical water resources. In mixed wildlife-livestock systems, maintaining wildlife-only water sources may be a practical management tool to mitigate human-wildlife conflict and disease transmission at this interface, especially during dry and hot conditions.
   These findings show how elevated temperatures that will become increasingly common with future climate changes can increase interspecific contacts around critical water resources. In mixed wildlife-livestock systems, maintaining wildlife-only water sources may be a practical management tool to mitigate human-wildlife conflict and disease transmission at this interface, especially during dry and hot conditions.image
C1 [Martinez, Viviana; Elkouby, Malik; Cantoadams, Joelle; Yeh, Serena; Vanleeuwen, Adam; Young, Hillary; Titcomb, Georgia] Univ Calif Santa Barbara, Dept Ecol Evolut & Marine Biol, Santa Barbara, CA 93106 USA.
   [Mantas, John] Mpala Res Ctr, Nanyuki, Kenya.
   [Hulke, Jenna] Texas A&M Univ, Dept Biol, College Stn, TX USA.
   [Gituku, Benard; Ndiema, Nickson] Ol Pejeta Conservancy, Nanyuki, Kenya.
   [Thompson, Asher] Univ Calif Berkeley, Berkeley, CA USA.
   [Titcomb, Georgia] Colorado State Univ, Warner Coll Nat Resources, Dept Fish Wildlife & Conservat Biol, Ft Collins, CO 80523 USA.
C3 University of California System; University of California Santa Barbara;
   Texas A&M University System; Texas A&M University College Station;
   University of California System; University of California Berkeley;
   Colorado State University
RP Titcomb, G (corresponding author), Univ Calif Santa Barbara, Dept Ecol Evolut & Marine Biol, Santa Barbara, CA 93106 USA.; Titcomb, G (corresponding author), Colorado State Univ, Warner Coll Nat Resources, Dept Fish Wildlife & Conservat Biol, Ft Collins, CO 80523 USA.
EM georgia.titcomb@colostate.edu
RI Titcomb, Georgia/ABF-6335-2021
OI Hulke, Jenna/0000-0001-9820-1641
FU National Science Foundation [1650114]; Division of Environmental Biology
   [1556786]; National Geographic Society [EC-33R-18]
FX National Science Foundation, Grant/Award Number: 1650114; Division of
   Environmental Biology, Grant/Award Number: 1556786; National Geographic
   Society, Grant/Award Number: EC-33R-18
CR Amulyoto M., 2020, AWARENESS PRACTICES
   AYENI J S O, 1975, East African Wildlife Journal, V13, P305
   Bennitt E, 2022, BIOL CONSERV, V268, DOI 10.1016/j.biocon.2022.109502
   Bhola N, 2012, J ANIM ECOL, V81, P1268, DOI 10.1111/j.1365-2656.2012.02000.x
   Brooks ME, 2017, R J, V9, P378, DOI 10.32614/RJ-2017-066
   Caravaggi A, 2020, CONSERV SCI PRACT, V2, DOI 10.1111/csp2.239
   Ceballos G, 2006, P NATL ACAD SCI USA, V103, P19374, DOI 10.1073/pnas.0609334103
   Chamaillé-Jammes S, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0059164
   Csardi G., 2006, The igraph software package for complex network research
   de Leeuw J, 2001, BIOL CONSERV, V100, P297, DOI 10.1016/S0006-3207(01)00034-9
   Donchyts G, 2016, NAT CLIM CHANGE, V6, P810, DOI 10.1038/nclimate3111
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   FRYXELL JM, 1988, TRENDS ECOL EVOL, V3, P237, DOI 10.1016/0169-5347(88)90166-8
   Funk C, 2008, P NATL ACAD SCI USA, V105, P11081, DOI 10.1073/pnas.0708196105
   Hayward MW, 2012, S AFR J WILDL RES, V42, P117, DOI 10.3957/056.042.0209
   Hempson GP, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-17348-4
   Hofmeester TR, 2020, REMOTE SENS ECOL CON, V6, P129, DOI 10.1002/rse2.136
   Huang JP, 2016, NAT CLIM CHANGE, V6, P166, DOI [10.1038/NCLIMATE2837, 10.1038/nclimate2837]
   Kihwele ES, 2020, ECOL MONOGR, V90, DOI 10.1002/ecm.1404
   Kock R, 2014, ECOLOGY, EVOLUTION AND BEHAVIOUR OF WILD CATTLE: IMPLICATIONS FOR CONSERVATION, P431
   Makindi S. M., 2014, INT J SCI RES, V3
   McIntyre T, 2020, WILDLIFE RES, V47, P177, DOI 10.1071/WR19040
   Meek PD, 2014, BIODIVERS CONSERV, V23, P2321, DOI 10.1007/s10531-014-0712-8
   Mutiga JK, 2010, WATER RESOUR MANAG, V24, P3939, DOI 10.1007/s11269-010-9641-9
   Ndlovu M, 2018, BIOL LETTERS, V14, DOI 10.1098/rsbl.2018.0360
   Odadi WO, 2007, RANGELAND ECOL MANAG, V60, P179, DOI 10.2111/05-044R3.1
   Odadi WO, 2009, APPL ANIM BEHAV SCI, V116, P120, DOI 10.1016/j.applanim.2008.08.010
   Ogada DL, 2012, CONSERV BIOL, V26, P453, DOI 10.1111/j.1523-1739.2012.01827.x
   Ogutu JO, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0163249
   Owen-Smith N, 2020, MAMMAL REV, V50, P252, DOI 10.1111/mam.12193
   Pedersen AB, 2007, CONSERV BIOL, V21, P1269, DOI 10.1111/j.1523-1739.2007.00776.x
   Sitters J, 2009, BIOL CONSERV, V142, P738, DOI 10.1016/j.biocon.2008.12.001
   Smit IPJ, 2007, BIOL CONSERV, V136, P85, DOI 10.1016/j.biocon.2006.11.009
   Titcomb G., 2024, DATA INTERACTING EFF, DOI [10.5061/dryad.02v6wwqc5, DOI 10.5061/DRYAD.02V6WWQC5]
   Titcomb G, 2023, P ROY SOC B-BIOL SCI, V290, DOI 10.1098/rspb.2023.2239
   Titcomb G, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-27352-y
   Titcomb GC, 2021, ECOL APPL, V31, DOI 10.1002/eap.2422
   Valeix M, 2007, OECOLOGIA, V153, P739, DOI 10.1007/s00442-007-0764-5
   Valeix M, 2011, J TROP ECOL, V27, P163, DOI 10.1017/S0266467410000647
   Valls-Fox H, 2018, ANIM CONSERV, V21, P365, DOI 10.1111/acv.12403
   WESTERN D, 1975, East African Wildlife Journal, V13, P265
   World Bank Group, 2024, CLIMATE DATA PROJECT
   Zvidzai M., 2013, INT J DEV SUSTAINABI, V2, P455
NR 43
TC 0
Z9 0
U1 7
U2 7
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0021-8901
EI 1365-2664
J9 J APPL ECOL
JI J. Appl. Ecol.
PD SEP
PY 2024
VL 61
IS 9
BP 2219
EP 2230
DI 10.1111/1365-2664.14728
EA JUL 2024
PG 12
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA P9Y3L
UT WOS:001270665600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Hordofa, AT
   Leta, OT
   Alamirew, T
   Chukalla, AD
AF Hordofa, Aster Tesfaye
   Leta, Olkeba Tolessa
   Alamirew, Tena
   Chukalla, Abebe Demissie
TI Response of Winter Wheat Production to Climate Change in Ziway Lake
   Basin
SO SUSTAINABILITY
LA English
DT Article
DE AquaCrop; irrigation water productivity; rainfall categories; RCP4; 5
   and 8; 5; Rift Valley Lake Basin
ID CROP WATER PRODUCTIVITY; SIMULATE YIELD RESPONSE; MAIN ETHIOPIAN RIFT;
   NORTH CHINA PLAIN; CHANGE IMPACTS; RIVER-BASIN; IRRIGATION; MODEL; DRY;
   MANAGEMENT
AB The crop production and limited freshwater resources in the Central Rift Valley (CRV) Lake Basin of Ethiopia have been facing pressure from warmer and drier climates. Thus, irrigation with the goal of increasing water use efficiency and the productivity of rainfed agriculture is vital to address climate effects, water scarcity, and food security. This study is aimed at assessing the sustainability of winter wheat production under climate change, and irrigation as an adaptation measure to improve yield, crop water productivity (CWP), and irrigation water productivity (IWP) in the CRV of Ethiopia. AquaCrop is applied to evaluate the effects of climate change and simulate irrigation as an adaptation measure. The analysis covers the baseline (1981-2020) and future (2026-2095) periods with each period categorized into three rainfall years (wet, normal, and dry). The future period is described using two representatives' concentration pathways (RCP4.5 and PCP8.5) scenarios. The results under rainfed and future climate conditions show that the winter wheat yield and CWP are projected to be lowered as compared to the baseline period. Most importantly, a significant reduction in wheat yield and CWP is noticed during the dry years (-60% and -80%) compared to the wet years (-30% and -51%) and normal years (-18% and -30%), respectively. As compared to rainfed agriculture, irrigation significantly reduces the risk of wheat yield decline and improves the CWP. Irrigation is also able to improve the CWP of rainfed wheat production ranging from 0.98-1.4 kg/m(3) to 1.48-1.56 kg/m(3). A projected CWP improvement of 1.1-1.32 kg/m(3) under irrigation is possible from 0.87-1.1 kg/m(3) under rainfed conditions. The study concludes that optimizing irrigation as a climate-change-adapting strategy in the CRV has a more pronounced positive impact to the rainfed production system, especially for the dry and normal years.
C1 [Hordofa, Aster Tesfaye] Addis Ababa Univ, Africa Ctr Excellence Water Management, Addis Ababa 1176, Ethiopia.
   [Leta, Olkeba Tolessa] St Johns River Water Management Dist, Bur Watershed Management & Modeling, 4049 Reid St, Palatka, FL 32177 USA.
   [Alamirew, Tena] Addis Ababa Univ, Ethiopian Inst Water Resources, Addis Ababa 1176, Ethiopia.
   [Chukalla, Abebe Demissie] IHE Delft Inst Water Educ, Dept Land & Water Management, NL-2611 Delft, Netherlands.
C3 Addis Ababa University; Addis Ababa University; IHE Delft Institute for
   Water Education
RP Hordofa, AT (corresponding author), Addis Ababa Univ, Africa Ctr Excellence Water Management, Addis Ababa 1176, Ethiopia.
EM aster.tesfaye@aau.edu.et
RI Agumassie, Tena/AAL-3707-2021; Hordofa, Aster Tesfaye/ABH-1509-2020;
   Leta, Olkeba Tolessa/O-6265-2017
OI Alamirew, Tena/0000-0001-7491-4401; Hordofa, Aster
   Tesfaye/0000-0003-0979-3169; Leta, Olkeba Tolessa/0000-0003-3479-901X
FU Africa Center of Excellence for Water Management, Addis Ababa University
FX This work was financially supported by the Africa Center of Excellence
   for Water Management, Addis Ababa University.
CR Abdalhi MAM, 2018, ITAL J AGRON, V13, P267, DOI 10.4081/ija.2018.1288
   Abebe G., 2016, INT J WASTE RESOUR, V6, P1000223, DOI [10.4172/2252-5211.1000223, DOI 10.4172/2252-5211.1000223]
   Abraham T., 2018, EARTH SCI CLIM CHANG, V9, P474, DOI [10.4172/2157-7617.1000474, DOI 10.4172/2157-7617.1000474]
   Akinsulu A. A., 2019, Journal of Marketing and Consumer Research, V52, P10, DOI [https://doi.org/10.7176/JMCR, DOI 10.7176/JMCR]
   Alhamshry A, 2020, WATER-SUI, V12, DOI 10.3390/w12010055
   Amouzou KA, 2019, FIELD CROP RES, V235, P104, DOI 10.1016/j.fcr.2019.02.021
   Araya A, 2020, SCI TOTAL ENVIRON, V731, DOI 10.1016/j.scitotenv.2020.139094
   Ayenew T, 2003, J RADIOANAL NUCL CH, V257, P11, DOI 10.1023/A:1024772621428
   Biazin B, 2021, FRONT WATER, V3, DOI 10.3389/frwa.2021.664127
   Borena Fikadu Robi, 2021, African Journal of Agricultural Research, V17, P1221, DOI 10.5897/AJAR2021.15653
   Challinor AJ, 2008, AGR FOREST METEOROL, V148, P343, DOI 10.1016/j.agrformet.2007.09.015
   Chukalla AD, 2015, HYDROL EARTH SYST SC, V19, P4877, DOI 10.5194/hess-19-4877-2015
   Debonne N, 2021, AGR SYST, V186, DOI 10.1016/j.agsy.2020.102943
   Desta H, 2017, LIMNOLOGICA, V65, P61, DOI 10.1016/j.limno.2017.07.005
   Ding ZL, 2021, AGR WATER MANAGE, V244, DOI 10.1016/j.agwat.2020.106626
   Diro S. B., 2009, Journal of Applied Horticulture (Lucknow), V11, P103
   Ezenne GI, 2019, AGR WATER MANAGE, V218, P158, DOI 10.1016/j.agwat.2019.03.034
   Faramarzi M, 2010, AGR WATER MANAGE, V97, P1861, DOI 10.1016/j.agwat.2010.07.002
   Fujihara Y, 2008, J HYDROL, V353, P33, DOI 10.1016/j.jhydrol.2008.01.024
   Gado TA, 2017, J HYDROL, V554, P646, DOI 10.1016/j.jhydrol.2017.09.043
   Gammans M, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6b0c
   Ge TD, 2012, ACTA PHYSIOL PLANT, V34, P1043, DOI 10.1007/s11738-011-0901-y
   Gerber A., 2008, OXFORD HDB POLITICAL
   Gohari A, 2013, SCI TOTAL ENVIRON, V442, P405, DOI 10.1016/j.scitotenv.2012.10.029
   Goshime Demelash Wondimagegnehu, 2019, WIT Transactions on Ecology and the Environment, V239, P67, DOI 10.2495/WS190071
   Goshime DW, 2019, HYDROLOGY-BASEL, V6, DOI 10.3390/hydrology6030068
   He WT, 2018, AGR SYST, V159, P187, DOI 10.1016/j.agsy.2017.01.025
   Hernandez-Ochoa IM, 2019, EUR J AGRON, V109, DOI 10.1016/j.eja.2019.125915
   Hordofa AT, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9010002
   Hordofa AT, 2021, CLIMATE, V9, DOI 10.3390/cli9070113
   Hsiao TC, 2009, AGRON J, V101, P448, DOI 10.2134/agronj2008.0218s
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Iqbal MA, 2014, AGR WATER MANAGE, V135, P61, DOI 10.1016/j.agwat.2013.12.012
   Irmak S, 2016, IRRIGATION SCI, V34, P271, DOI 10.1007/s00271-016-0502-z
   Jiang YW, 2016, AGR WATER MANAGE, V177, P37, DOI 10.1016/j.agwat.2016.06.014
   Joshi N., 2011, Journal of Contemporary India Studies: Space and Society, V1, P19, DOI [10.1007/978-4-431-54343-5_9, DOI 10.1007/978-4-431-54343-5_9]
   Kawo Nafyad Serre, 2021, Arabian Journal of Geosciences, V14, DOI 10.1007/s12517-021-06599-1
   Kelly TD, 2021, AGR WATER MANAGE, V254, DOI 10.1016/j.agwat.2021.106976
   Kheir AMS, 2021, AGR WATER MANAGE, V256, DOI 10.1016/j.agwat.2021.107122
   Kloss S, 2012, WATER RESOUR MANAG, V26, P997, DOI 10.1007/s11269-011-9906-y
   Kristensen K, 2011, J AGR SCI-CAMBRIDGE, V149, P33, DOI 10.1017/S0021859610000675
   Larsen JN, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1567
   Le Turdu C, 1999, PALAEOGEOGR PALAEOCL, V150, P135, DOI 10.1016/S0031-0182(98)00220-X
   Legesse D, 2006, QUATERN INT, V148, P8, DOI 10.1016/j.quaint.2005.11.003
   Li HM, 2005, AGR WATER MANAGE, V76, P8, DOI 10.1016/j.agwat.2005.01.006
   Marin FR, 2019, THEOR APPL CLIMATOL, V138, P1785, DOI 10.1007/s00704-019-02940-7
   Mo XG, 2009, AGR ECOSYST ENVIRON, V134, P67, DOI 10.1016/j.agee.2009.05.017
   Mohammed Y, 2021, GEOENVIRONMENTAL DIS, V8, DOI 10.1186/s40677-021-00183-1
   Mostafa SM, 2021, AQUA-UK, V70, P1066, DOI 10.2166/aqua.2021.019
   Muluneh A, 2017, J AGR SCI-CAMBRIDGE, V155, P703, DOI 10.1017/S0021859616000897
   Musie M, 2020, WATER-SUI, V12, DOI 10.3390/w12010164
   Niu G, 2016, AGR WATER MANAGE, V166, P53, DOI 10.1016/j.agwat.2015.12.011
   Özdogan M, 2011, AGR ECOSYST ENVIRON, V141, P1, DOI 10.1016/j.agee.2011.02.001
   Pascual-Ferrer J, 2014, INT J WATER RESOUR D, V30, P572, DOI 10.1080/07900627.2013.843410
   Patil RH, 2010, J AGR SCI-CAMBRIDGE, V148, P553, DOI 10.1017/S0021859610000419
   Paul M, 2020, CLIMATE, V8, DOI 10.3390/cli8120139
   Raes D., 2018, AquaCrop version 6.0-6.1 Reference manual FAO crop-water productivity model to simulate yield response to water
   Raes D, 2009, AGRON J, V101, P438, DOI 10.2134/agronj2008.0140s
   Reddy VR, 2000, ENVIRON MODELL SOFTW, V15, P79, DOI 10.1016/S1364-8152(99)00011-0
   Redi M., 2019, International Journal of Research Studies in Agricultural Sciences, V5, DOI [10.20431/2454-6224.0504005, DOI 10.20431/2454-6224.0504005]
   Rodriguez AVC, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9070378
   Díaz JAR, 2007, REG ENVIRON CHANGE, V7, P149, DOI 10.1007/s10113-007-0035-3
   Steduto P., 2009, Concepts and applications of AquaCrop: the FAO crop water productivity model, P175
   Steduto P, 2009, AGRON J, V101, P426, DOI 10.2134/agronj2008.0139s
   Sullivan RC, 2019, J HYDROMETEOROL, V20, P1619, DOI 10.1175/JHM-D-18-0259.1
   Sundström J, 2014, FOOD SECUR, V6, P201, DOI 10.1007/s12571-014-0331-y
   Taffesse A.S., 2011, ESSP II Working Paper 16, P53, DOI [10.9783/9780812208610.53, DOI 10.9783/9780812208610.53]
   Tao FL, 2010, EUR J AGRON, V33, P103, DOI 10.1016/j.eja.2010.04.002
   Ulsido Mihret Dananto, 2014, Environmental Research, Engineering and Management, V67, P5, DOI 10.5755/j01.erem.67.1.6240
   Vaghefi SA, 2017, WATER-SUI, V9, DOI 10.3390/w9030157
   Vanuytrecht E, 2014, ENVIRON MODELL SOFTW, V62, P351, DOI 10.1016/j.envsoft.2014.08.005
   Xiao DP, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041277
   Xiao GJ, 2008, AGR ECOSYST ENVIRON, V127, P37, DOI 10.1016/j.agee.2008.02.007
   Yang J, 2003, PLANT SOIL, V250, P175, DOI 10.1023/A:1022801322245
   Yemane Gebreselassie Yemane Gebreselassie, 2015, African Journal of Agricultural Research, V10, P269
   You LZ, 2009, AGR FOREST METEOROL, V149, P1009, DOI 10.1016/j.agrformet.2008.12.004
   Zeleke K, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11020337
   Zhao J, 2020, AGR WATER MANAGE, V240, DOI 10.1016/j.agwat.2020.106298
NR 78
TC 4
Z9 4
U1 0
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD OCT
PY 2022
VL 14
IS 20
AR 13666
DI 10.3390/su142013666
PG 17
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 5P7YG
UT WOS:000873361300001
OA gold
DA 2025-01-10
ER

PT J
AU Rodríguez-Cruz, LA
   Moore, M
   Niles, MT
AF Rodriguez-Cruz, Luis Alexis
   Moore, Maya
   Niles, Meredith T.
TI Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation
   Strategies After Hurricane Maria: A Mixed-Methods Approach to
   Understanding Adaptive Capacity
SO FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
LA English
DT Article
DE climate change; islands and archipelagos; food systems; farmers'
   decision-making; disaster and climate risk reduction
ID CLIMATE-CHANGE ADAPTATION; CONSERVATION PRACTICES; FOOD SECURITY;
   VULNERABILITY; PERCEPTIONS; ADOPTION; IMPACTS; COMMUNITIES; MANAGEMENT;
   INTENSIFICATION
AB Farmers across the globe are experiencing compounding shocks that make evident the need to better understand potential drivers and barriers to strengthen adaptive capacity. This is especially true in the context of a disaster, where a disruption in the natural and built environment hinders livelihood strategies and exposes the underlying dynamics that perpetuate vulnerability to natural hazards. As such, the interconnections of structural and individual attributes must be considered when evaluating adaptive capacity. This paper uses a convergent mixed-methods approach to assess Puerto Rican farmers' actual and intended adoption of adaptation practices, in light of the obstacles they faced toward recovery after 2017's category four Hurricane Maria, to contribute to better understanding adaptive capacity. This study uses data from 405 farmers across Puerto Rico (87% response rate), surveyed 8 months after Maria by agricultural agents of the Extension Service of the University of Puerto Rico at Mayaguez. Quantitative data was assessed through negative binomial regressions (actual adoption) and generalized linear models (intended adoption), while qualitative data (reported obstacles) were analyzed through thematic analysis. This study found that almost half of farmers adopted an adaptation practice after Maria, and that in many cases, broader structures, such as systems of governance, farmers' social networks, and infrastructure, affect adaptive capacity more than individual perceptions of capacity. Future adaptation strategies and interventions, especially in the context of disaster, should consider the extent to which structural factors hinder individuals' ability to prepare for, respond, and recover from the impacts of these shocks. Our results show that there might be opportunity to enact new systems in light of catastrophic events, but this does not solely depend on individual actions. The mixed-methods approach used can inform future studies in better assessing adaptive capacity from a standpoint that incorporates individual and structural components.
C1 [Rodriguez-Cruz, Luis Alexis; Moore, Maya; Niles, Meredith T.] Univ Vermont, Food Syst & Aduate Program, Burlington, VT 05405 USA.
   [Rodriguez-Cruz, Luis Alexis; Moore, Maya; Niles, Meredith T.] Univ Vermont, Gund Inst Environm, Burlington, VT 05405 USA.
   [Niles, Meredith T.] Univ Vermont, Dept Nutr & Food Sci, Burlington, VT USA.
C3 University of Vermont; University of Vermont; University of Vermont
RP Rodríguez-Cruz, LA (corresponding author), Univ Vermont, Food Syst & Aduate Program, Burlington, VT 05405 USA.; Rodríguez-Cruz, LA (corresponding author), Univ Vermont, Gund Inst Environm, Burlington, VT 05405 USA.
EM lrodrig2@uvm.edu
RI Moore, Maya/AHE-8863-2022
OI Moore, Maya/0000-0002-0251-1539; Rodriguez-Cruz, Luis
   Alexis/0000-0002-2229-8448
FU College of Agriculture and Life Sciences and Food Systems Graduate
   program of the University of Vermont; MTN
FX This research was internally funded through the College of Agriculture
   and Life Sciences and Food Systems Graduate program of the University of
   Vermont. MTN allocated funding.
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Alvarez-Berríos NL, 2018, RENEW AGR FOOD SYST, V33, P279, DOI 10.1017/S174217051800011X
   Alvarez-Febles N., 2020, Climate Justice and Community Renewal, P131, DOI 10.4324/9780429277146-9
   Anderzén J, 2020, J RURAL STUD, V77, P33, DOI 10.1016/j.jrurstud.2020.04.001
   [Anonymous], 2014, FOOD SECURITY NUTR S
   [Anonymous], IPCCS 5 ASS REP WHAT
   Bagagnan AR, 2019, CLIMATE, V7, DOI 10.3390/cli7010013
   Bang H.N., 2019, American Journal of Climate Change, V08, P454, DOI [10.4236/ajcc.2019.84025, DOI 10.4236/AJCC.2019.84025]
   Barnes ML, 2020, NAT CLIM CHANGE, V10, P823, DOI 10.1038/s41558-020-0871-4
   Bonilla Y, 2020, POLIT GEOGR, V78, DOI 10.1016/j.polgeo.2020.102181
   Borges-Mendez R., 2019, J EXTREME EVENTS, V6, P1940001, DOI [DOI 10.1142/S2345737619400013, https://doi.org/10.1142/S2345737619400013]
   Brooks N., 2005, ADAPTATION POLICY FR, P165
   Bueno R., 2017, Puerto Rico, Climatic Extremes, and the Economics of Resilience No, P10
   Carro-Figueroa V., 2002, Caribbean Studies, V30, P77
   Castro Rivera A., 2018, CARTILLA CICLONES
   Caswell M., 2016, ASSESSING RESILIENCE
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   Claassen R, 2017, AM J AGR ECON, V99, P592, DOI 10.1093/ajae/aaw075
   Clay LA, 2018, RISK HAZARDS CRISIS, V9, P303, DOI 10.1002/rhc3.12137
   Comas-Pagan M., 2014, Plan de sguridad alimentaria p, P40
   Creswell J. W., 2020, 30 Essential Skills for the Qualitative Researcher
   Creswell JW., 2017, DESIGNING CONDUCTING
   Creswell W., 2009, Research design: Qualitative, quantitative, and mixed methods approaches, V3rd
   Diaz E.L., 2018, CHAPTER 20 US CARIBB
   Diaz Rolon A., 2019, ASPIRA QUE HAYA MAS
   Doran EMB, 2020, J ENVIRON MANAGE, V276, DOI 10.1016/j.jenvman.2020.111304
   Felix G, 2017, HURRICANE MARIA AGRO
   Fernandez M, 2019, AGROECOL SUST FOOD, V43, P579, DOI 10.1080/21683565.2018.1530326
   Foguesatto CR, 2020, SCI TOTAL ENVIRON, V729, DOI 10.1016/j.scitotenv.2020.138831
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Gould W.A., 2015, Caribbean Regional Climate Sub Hub Assessment of Climate Change Vulnerability and Adaptation and Mitigation Strategies
   Gould WA, 2017, FORESTS, V8, DOI 10.3390/f8070242
   Graham B., 2012, Profile of the Small-Scale Farming in the Caribbean p, P62
   Haden V, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0052882
   Harvey C. A., 2018, Agriculture & Food Security, V7, P57, DOI 10.1186/s40066-018-0209-x
   Holt-Giménez E, 2002, AGR ECOSYST ENVIRON, V93, P87, DOI 10.1016/S0167-8809(02)00006-3
   Irizarry-Ruiz C., 2016, DESAFIOS AGR PUERTO
   Jezeer RE, 2019, J ENVIRON MANAGE, V242, P496, DOI 10.1016/j.jenvman.2019.04.101
   Kassie M, 2015, LAND USE POLICY, V42, P400, DOI 10.1016/j.landusepol.2014.08.016
   Kim K, 2019, INT J DISAST RISK RE, V39, DOI 10.1016/j.ijdrr.2019.101244
   Kuder GF, 1937, PSYCHOMETRIKA, V2, P151, DOI 10.1007/BF02288391
   Lavrakas P., 2008, ENCY SURVEY RES METH, V1
   Le Dang H, 2018, CLIM DEV, V10, P509, DOI 10.1080/17565529.2017.1304885
   Lopez-Marrero T., 2018, ACTIVIDAD CICLONICA
   Lopez-Marrero T., 2012, CARIBBEAN STUD, P129, DOI [10.1353/crb.2012.0034, DOI 10.1353/CRB.2012.0034]
   López-Marrero T, 2019, NAT HAZARDS, V98, P809, DOI 10.1007/s11069-019-03716-y
   López-Marrero T, 2010, GEOGR J, V176, P150, DOI 10.1111/j.1475-4959.2010.00353.x
   López-Marrero T, 2010, NAT HAZARDS, V52, P277, DOI 10.1007/s11069-009-9370-7
   Lowitt K, 2015, REG ENVIRON CHANGE, V15, P1367, DOI 10.1007/s10113-015-0805-2
   Mase AS, 2017, CLIM RISK MANAG, V15, P8, DOI 10.1016/j.crm.2016.11.004
   Masters P., 2017, AM BIGGEST BLACKOUT
   Rosset PM, 2011, J PEASANT STUD, V38, P161, DOI 10.1080/03066150.2010.538584
   Moulton AA., 2019, J EXTREME EVENTS, V6, P1940003, DOI [10.1142/S2345737619400037, DOI 10.1142/S2345737619400037]
   Nichols A., 2007, UK STAT US GROUP M U
   Niles MT, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0192928
   Niles MT, 2016, GLOBAL ENVIRON CHANG, V39, P133, DOI 10.1016/j.gloenvcha.2016.05.002
   Niles MT, 2016, CLIMATIC CHANGE, V135, P277, DOI 10.1007/s10584-015-1558-0
   Niles MT, 2015, AGR ECOSYST ENVIRON, V200, P178, DOI 10.1016/j.agee.2014.11.010
   Nunnally J.C., 1978, PSYCHOMETRIC THEORY, V2nd
   O'Connor C, 2020, INT J QUAL METH, V19, DOI 10.1177/1609406919899220
   Paul J, 2017, J CLEAN PROD, V142, P1387, DOI 10.1016/j.jclepro.2016.11.168
   Payne PR, 2021, ECOL SOC, V26, DOI 10.5751/ES-12026-260102
   Perfecto I, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51416-1
   Phillips CA, 2020, NAT CLIM CHANGE, V10, P586, DOI 10.1038/s41558-020-0804-2
   Prokopy LS, 2019, J SOIL WATER CONSERV, V74, P520, DOI 10.2489/jswc.74.5.520
   QSR, 2019, NVIV 12
   Quarantelli E. L., 1992, IMPORTANCE THINKING
   Ranjan P, 2019, SOC NATUR RESOUR, V32, P1171, DOI 10.1080/08941920.2019.1648710
   Raza MH, 2019, J CLEAN PROD, V227, P613, DOI 10.1016/j.jclepro.2019.04.244
   Reed MS, 2013, ECOL ECON, V94, P66, DOI 10.1016/j.ecolecon.2013.07.007
   Reyes J, 2020, AGR WATER MANAGE, V232, DOI 10.1016/j.agwat.2020.106000
   Ribot J, 2014, J PEASANT STUD, V41, P667, DOI 10.1080/03066150.2014.894911
   Rodriguez-Cruz L.A., 2020, **DATA OBJECT**, DOI 10.7910/DVN/JZFWZZ
   Rodríguez-Cruz LA, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0244512
   Saint Ville AS, 2016, FOOD SECUR, V8, P535, DOI 10.1007/s12571-016-0581-y
   Salerno J, 2019, CLIMATIC CHANGE, V153, P123, DOI 10.1007/s10584-019-02370-4
   Santos-Burgoa C., 2018, Acertainment of the Estimated Excess Mortality from Hurricane Maria in Puerto Rico
   Scobie M, 2018, ENVIRON DEV SUSTAIN, V20, P769, DOI 10.1007/s10668-017-9909-9
   Shah SH, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00001
   Shinbrot XA, 2019, ENVIRON MANAGE, V63, P583, DOI 10.1007/s00267-019-01152-z
   Singh AS, 2017, ENVIRON SCI POLICY, V73, P93, DOI 10.1016/j.envsci.2017.04.011
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   Luu TA, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11102993
   U.S. Census Bureau, 2020, US CENS BUR QUICKFAC
   USDA ERS, 2020, USDA ERS FARM HOUS I
   USDA NASS, 2020, 2017 CENS AGR PUERT, P117
   Wang YD, 2019, J ENVIRON MANAGE, V237, P15, DOI 10.1016/j.jenvman.2019.02.070
   Weis T, 2007, RACE CLASS, V49, P112, DOI 10.1177/03063968070490020607
   White A., 2018, Report of the 2017-2018 New England Adaptation Survey for Vegetable and Fruit Growers
   Wilson RS, 2020, NAT CLIM CHANGE, V10, P200, DOI 10.1038/s41558-020-0691-6
   Wisner B., 2004, AT RISK, V2nd
   Wisner Ben., 2012, ROUTLEDGE HDB HAZARD, DOI DOI 10.4324/9780203844236
   Zhang JA, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2019GL086206
   Zurovec O, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11216079
NR 97
TC 11
Z9 13
U1 2
U2 15
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2571-581X
J9 FRONT SUSTAIN FOOD S
JI Front. Sustain. Food Syst.
PD JUL 5
PY 2021
VL 5
AR 662918
DI 10.3389/fsufs.2021.662918
PG 16
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA TK6NH
UT WOS:000674272300001
OA gold
DA 2025-01-10
ER

PT J
AU Coletta, VR
   Pagano, A
   Pluchinotta, I
   Fratino, U
   Scrieciu, A
   Nanu, F
   Giordano, R
AF Coletta, Virginia Rosa
   Pagano, Alessandro
   Pluchinotta, Irene
   Fratino, Umberto
   Scrieciu, Albert
   Nanu, Florentina
   Giordano, Raffaele
TI Causal Loop Diagrams for supporting Nature Based Solutions participatory
   design and performance assessment
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Nature Based Solutions co-design; Water-related risks; Co-benefits
   assessment; Participatory modelling; System thinking
AB The contribution of Nature Based Solutions (NBSs) for supporting climate change adaptation and water-related risks reduction is becoming increasingly relevant for policy and decision-makers, compared to 'grey infrastructures', thanks to their capability to jointly deal with a multiplicity of societal and environmental challenges, producing several co-benefits besides limiting the impacts of water-related risks. Nevertheless, their mainstreaming is still limited by several barriers, which are often related to socio-institutional (e.g. limited cooperation and stakeholders' involvement, limited awareness about NBSs impacts) rather than to technical aspects. In this context, innovative tools for NBSs planning, design, implementation and assessment are required, along with effective processes capable of supporting stakeholders' participation. The present research aims to propose a shift in the approach to NBSs design, based on the early stakeholders' involvement in the identification, modelling and performance assessment in terms of benefits and, particularly, co-benefits production. A multi-step methodology was implemented for the purpose, combining both individual and participatory activities. Reference is made to one of the case studies of the NAIAD project, namely the Balta Potelu Pond Area (Lower Danube, Romania). Causal Loop Diagrams (CLDs) were used to describe the system in terms of causal connections and mutual influences, incorporating stakeholders' views and ideas. Inputs from both institutional (e.g. ministries and municipalities) and non-institutional stakeholders (e.g. NGOs and members of the local communities) were integrated. This allowed a comparative assessment of multiple NBSs, based on the analysis of benefits and co-benefits produced, as well as the identification of trade-offs among different stakeholders (e.g. the increase of agricultural production versus biodiversity conservation) and potential side effects. CLDs were then coupled with a Performance Matrix (a basic feature of Multi-Criteria Decision Analysis) and fuzzy logic to help decision-makers identify the most suitable NBSs for the area. The whole process was aimed at facilitating the process of NBSs selection and analysis, while considering the multiple impacts associated with their implementation.
C1 [Coletta, Virginia Rosa; Fratino, Umberto] Politecn Bari, DICATECh, Bari, Italy.
   [Coletta, Virginia Rosa; Pagano, Alessandro; Giordano, Raffaele] Natl Res Council IRSA CNR, Water Res Inst, Bari, Italy.
   [Pluchinotta, Irene] UCL, Bartlett Fac Built Environm, Inst Environm Design & Engn, London, England.
   [Scrieciu, Albert] Natl Inst Marine Geol & Geoecol GeoEcoMar, Bucharest, Romania.
   [Nanu, Florentina] Business Dev Grp BDG, Bucharest, Romania.
C3 Politecnico di Bari; Consiglio Nazionale delle Ricerche (CNR); Istituto
   di Ricerca sulle Acque (IRSA-CNR); University of London; University
   College London; National Institute of Marine Geology & Geoecology of
   Romania (GeoEcoMar)
RP Coletta, VR (corresponding author), Politecn Bari, DICATECh, Bari, Italy.
EM virginiarosa.coletta@poliba.it
RI Fratino, Umberto/F-3149-2012; Albert, Scrieciu/AAD-8193-2021; GIORDANO,
   RAFFAELE/AAX-7089-2020; Coletta, Virginia/AAM-8887-2021; Pagano,
   Alessandro/P-1544-2018
OI Coletta, Virginia Rosa/0000-0002-3724-9139; Pagano,
   Alessandro/0000-0002-2511-9396; Scrieciu, Albert/0000-0001-6297-8635
FU H2020 NAIAD project [730497]
FX The research activities described in this work were supported by the
   H2020 NAIAD project (Grant Agreement No 730497). We would like to thank
   the project team for the many stimulant discussions and kind
   cooperation. Furthermore, a big thank you goes to the institutional and
   non-institutional stakeholders who provided their knowledge and
   expertise, the basis of this work.
CR Ackermann F, 2016, INT J PROJ MANAG, V34, P891, DOI 10.1016/j.ijproman.2016.04.001
   Albert C, 2019, LANDSCAPE URBAN PLAN, V182, P12, DOI 10.1016/j.landurbplan.2018.10.003
   Alves A, 2019, J ENVIRON MANAGE, V239, P244, DOI 10.1016/j.jenvman.2019.03.036
   Alves A, 2018, WATER RESOUR MANAG, V32, P2505, DOI 10.1007/s11269-018-1943-3
   [Anonymous], 2000, SYSTEMS THINKING MOD
   [Anonymous], 2015, Towards an EU research and innovation policy agenda for nature-based solutions and re-naturing cities: final report of the Horizon 2020 expert group on 'Nature-based solutions and re-naturing cities, DOI DOI 10.2777/765301
   Bain PG, 2016, NAT CLIM CHANGE, V6, P154, DOI [10.1038/NCLIMATE2814, 10.1038/nclimate2814]
   Belton V., 2002, MULIPLE CRITERIA DEC
   Calliari E, 2019, SCI TOTAL ENVIRON, V656, P691, DOI 10.1016/j.scitotenv.2018.11.341
   Connop S, 2016, ENVIRON SCI POLICY, V62, P99, DOI 10.1016/j.envsci.2016.01.013
   de Vito R, 2017, ADV WATER RESOUR, V110, P423, DOI 10.1016/j.advwatres.2017.10.027
   Debele SE, 2019, ENVIRON RES, V179, DOI 10.1016/j.envres.2019.108799
   EDEN C, 1992, J MANAGE STUD, V29, P261, DOI 10.1111/j.1467-6486.1992.tb00664.x
   Faivre N, 2017, ENVIRON RES, V159, P509, DOI 10.1016/j.envres.2017.08.032
   Ferretti V, 2019, CITIES, V95, DOI 10.1016/j.cities.2019.06.017
   Fritz M, 2017, THEOR PRACT URB SUST, P65, DOI 10.1007/978-3-319-56091-5_5
   Giordano R, 2020, SCI TOTAL ENVIRON, V713, DOI 10.1016/j.scitotenv.2020.136552
   Giordano R, 2012, ENVIRON MODELL SOFTW, V36, P49, DOI 10.1016/j.envsoft.2011.09.004
   Giordano R, 2017, GROUP DECIS NEGOT, V26, P911, DOI 10.1007/s10726-016-9519-1
   Giordano R, 2017, ENVIRON MODELL SOFTW, V95, P180, DOI 10.1016/j.envsoft.2017.06.026
   Inam A, 2015, J ENVIRON MANAGE, V152, P251, DOI 10.1016/j.jenvman.2015.01.052
   Jacobs S, 2016, ECOSYST SERV, V22, P213, DOI 10.1016/j.ecoser.2016.11.007
   Jeong H, 2016, AGR WATER MANAGE, V171, P89, DOI 10.1016/j.agwat.2016.03.019
   Kabisch N, 2017, ENVIRON RES, V159, P362, DOI 10.1016/j.envres.2017.08.004
   Lanzas M, 2019, SCI TOTAL ENVIRON, V651, P541, DOI 10.1016/j.scitotenv.2018.09.164
   Larson EK, 2013, LANDSCAPE URBAN PLAN, V109, P45, DOI 10.1016/j.landurbplan.2012.10.008
   Maes J, 2017, CONSERV LETT, V10, P121, DOI 10.1111/conl.12216
   McVittie A, 2018, INT J DISAST RISK RE, V32, P42, DOI 10.1016/j.ijdrr.2017.12.014
   Mehryar S, 2019, J ENVIRON MANAGE, V250, DOI 10.1016/j.jenvman.2019.109482
   Mihailovici J.M., 2006, HIDROTEHNICA, V51, P9
   Mirchi A, 2012, WATER RESOUR MANAG, V26, P2421, DOI 10.1007/s11269-012-0024-2
   Murti R, 2019, INT J DISAST RISK RE, V33, P433, DOI 10.1016/j.ijdrr.2018.09.018
   Narayan S, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-09269-z
   Nichersu I., 2015, J ENV SCI ENG B, V4, P434, DOI [10.17265/2162-5263/2015.08.004, DOI 10.17265/2162-5263/2015.08.004]
   Pagano A, 2019, SCI TOTAL ENVIRON, V690, P543, DOI 10.1016/j.scitotenv.2019.07.059
   Perrone A, 2020, J HYDROL, V580, DOI 10.1016/j.jhydrol.2019.124354
   Pluchinotta I, 2019, SUSTAIN CITIES SOC, V46, DOI 10.1016/j.scs.2018.12.030
   Rajaram T, 2010, EXPERT SYST APPL, V37, P1734, DOI 10.1016/j.eswa.2009.07.035
   Raymond CM, 2017, ENVIRON SCI POLICY, V77, P15, DOI 10.1016/j.envsci.2017.07.008
   Ruangpan L, 2020, NAT HAZARD EARTH SYS, V20, P243, DOI 10.5194/nhess-20-243-2020
   Santoro S, 2019, SCI TOTAL ENVIRON, V655, P188, DOI 10.1016/j.scitotenv.2018.11.116
   Shrestha S, 2019, J ENVIRON MANAGE, V235, P535, DOI 10.1016/j.jenvman.2019.01.035
   Small N, 2017, GLOBAL ENVIRON CHANG, V44, P57, DOI 10.1016/j.gloenvcha.2017.03.005
   Tetelea, 2017, INV NATURE UNISDR 20
   Uricchio VF, 2004, J ENVIRON MANAGE, V73, P189, DOI 10.1016/j.jenvman.2004.06.011
   Wihlborg M, 2019, J ENVIRON MANAGE, V233, P706, DOI 10.1016/j.jenvman.2018.12.018
   WWF Germany, 2009, LOW DAN GREEN CORR A
   ZADEH LA, 1975, INFORM SCIENCES, V8, P199, DOI [10.1016/0020-0255(75)90036-5, 10.1016/0020-0255(75)90046-8]
   Zimmermann HJ, 1991, Fuzzy Sets Theory and its Applications
   Zomorodian M, 2018, J ENVIRON MANAGE, V227, P294, DOI 10.1016/j.jenvman.2018.08.097
NR 50
TC 42
Z9 44
U1 5
U2 41
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD FEB 15
PY 2021
VL 280
AR 111668
DI 10.1016/j.jenvman.2020.111668
EA JAN 2021
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA QA6QY
UT WOS:000613569300001
PM 33248814
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Jacobsen, CD
   Brown, DJ
   Flint, WD
   Pauley, TK
   Buhlmann, KA
   Mitchell, JC
AF Jacobsen, Carl D.
   Brown, Donald J.
   Flint, William D.
   Pauley, Thomas K.
   Buhlmann, Kurt A.
   Mitchell, Joseph C.
TI Vulnerability of high-elevation endemic salamanders to climate change: A
   case study with the Cow Knob Salamander (<i>Plethodon punctatus</i>)
SO GLOBAL ECOLOGY AND CONSERVATION
LA English
DT Article
DE Amphibian; Appalachia; Climate change; George Washington National
   Forest; Habitat suitability model; MaxLike
ID DISTRIBUTION MODELS; HABITAT; CONNECTIVITY; BIODIVERSITY; POPULATIONS;
   EVOLUTION; ECOLOGY; ABSENCE; MAXENT; FUTURE
AB Rapid contemporary climate change is a potential threat to long-term persistence of montane wildlife species because they often have narrow thermal tolerances and have limited potential to shift their distributions. The Appalachian Mountain region in the eastern United States is a global biodiversity hotspot for woodland salamanders (genus Plethodon), many of which are high-elevation endemic species. Robust assessments of the vulnerability of high-elevation endemic salamanders to climate change, including delineation of future potential climate refugia, are needed to guide climate change adaptations strategies. The Cow Knob Salamander (Plethodon punctatus) is a species of conservation concern found at high elevations in the Valley and Ridge Province of western Virginia and eastern West Virginia. We used habitat suitability models to examine relationships between landscape characteristics, climate variables, and P. punctatus occurrence, and estimated effects of future climate scenarios on the species' climatic niche. We found that elevation, slope, aspect, and hillshade were influential landscape predictors of species occurrence, and that mean annual temperature was the most influential climate variable. Future climate projections indicated this species will likely lose most of its climatic niche by mid-century, and that amount of suitable habitat will continue to decline through 2100. We identified several pockets of habitat that may represent climate change refugia for P. punctatus due to cooler microclimates from greater hillshade and aspects that receive less direct solar radiation; however, we found these refugia exist in small, isolated habitat patches. Our study provides quantitative estimates that support the general concern that high-elevation endemic salamanders are particularly vulnerable to climate change. Our models can be used by natural resource managers to guide current P. punctatus monitoring and habitat conservation efforts, as well as to identify focal areas that will likely serve as refugia for the species as the climate continues to change over this century. (C) 2019 The Authors. Published by Elsevier B.V.
C1 [Jacobsen, Carl D.; Brown, Donald J.] West Virginia Univ, Sch Nat Resources, 322 Percival Hall, Morgantown, WV 26506 USA.
   [Brown, Donald J.] US Forest Serv, Northern Res Stn, POB 404, Parsons, WV 26287 USA.
   [Flint, William D.] James Madison Univ, Dept Biol, MSC 7801, Harrisonburg, VA 22807 USA.
   [Pauley, Thomas K.] Marshall Univ, Dept Biol Sci, 400 Hal Greer Blvd, Huntington, WV 25755 USA.
   [Buhlmann, Kurt A.] Univ Georgia, Savannah River Ecol Lab, Aiken, SC 29802 USA.
   [Mitchell, Joseph C.] Mitchell Ecol Res Serv LLC, 1015 SW Mapleton St, Ft White, FL 32038 USA.
C3 West Virginia University; United States Department of Agriculture
   (USDA); United States Forest Service; James Madison University; Marshall
   University; United States Department of Energy (DOE); Savannah River
   Ecology Laboratory; University System of Georgia; University of Georgia
RP Jacobsen, CD (corresponding author), West Virginia Univ, 1145 Evansdale Dr,322 Percival Hall, Morgantown, WV 26506 USA.
EM jacobsencarl89@gmail.com; donald.brown1@mail.wvu.edu; flintwd@jmu.edu;
   pauley@marshall.edu; buhlmann@uga.edu
FU USDA Forest Service Northern Research Station; USDA National Institute
   of Food and Agriculture, McIntire Stennis project [WVA00122]
FX This work was supported by a research grant from the USDA Forest Service
   Northern Research Station. Donald Brownwas supported by the USDA
   National Institute of Food and Agriculture, McIntire Stennis project
   WVA00122, and theWest Virginia Agricultural and Forestry Experiment
   Station. We mourn the recent loss of our colleague, Joe Mitchell who
   demonstrated conservation vision, effort, and concern for P. punctatus.
   We thank all of the individuals who have contributed knowledge and data
   on the ecology and distribution of P. punctatus, particularly R.
   Highton, D. Fraser, and R. Tucker. We thank C. Rota and M. Strager for
   modeling assistance. J. Schuler, an anonymous reviewer, and the
   associate editor provided suggestions that enhanced the quality of this
   manuscript. We acknowledge the World Climate Research Programme's
   Working Group on Coupled Modelling, which is responsible for CMIP, and
   we thank the climate modeling groups for producing and making available
   their model output. Any use of trade, product, or firm names is for
   descriptive purposes only and does not imply endorsement by the U.S.
   Government.
CR Anderson DR, 2002, J WILDLIFE MANAGE, V66, P912, DOI 10.2307/3803155
   Baldwin RA, 2009, ENTROPY, V11, P854, DOI 10.3390/e11040854
   Bernardo J, 2006, BIOL LETTERS, V2, P135, DOI 10.1098/rsbl.2005.0417
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Blois JL, 2013, SCIENCE, V341, P499, DOI 10.1126/science.1237184
   Boyce MS, 1999, TRENDS ECOL EVOL, V14, P268, DOI 10.1016/S0169-5347(99)01593-1
   Brotons L, 2004, ECOGRAPHY, V27, P437, DOI 10.1111/j.0906-7590.2004.03764.x
   Buhlmann Kurt A., 1988, U S Forest Service General Technical Report RM, V166, P38
   Caruso NM, 2014, GLOBAL CHANGE BIOL, V20, P1751, DOI 10.1111/gcb.12550
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Clay TA, 2016, ETHOLOGY, V122, P127, DOI 10.1111/eth.12453
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   Downer H.R., 2009, THESIS
   Dullinger S, 2012, NAT CLIM CHANGE, V2, P619, DOI 10.1038/NCLIMATE1514
   Elsen PR, 2015, NAT CLIM CHANGE, V5, P772, DOI [10.1038/NCLIMATE2656, 10.1038/nclimate2656]
   FEDER ME, 1983, HERPETOLOGICA, V39, P291
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fischman RL, 2014, BIOSCIENCE, V64, P993, DOI 10.1093/biosci/biu160
   Fitzpatrick MC, 2013, ECOSPHERE, V4, DOI 10.1890/ES13-00066.1
   Flint WD, 2005, J HERPETOL, V39, P578, DOI 10.1670/255-04A.1
   Gibbs JP, 1998, LANDSCAPE ECOL, V13, P263, DOI 10.1023/A:1008056424692
   Gifford ME, 2012, ECOGRAPHY, V35, P193, DOI 10.1111/j.1600-0587.2011.06866.x
   Grant EHC, 2018, ECOL EVOL, V8, P7553, DOI 10.1002/ece3.4198
   Gu WD, 2004, BIOL CONSERV, V116, P195, DOI 10.1016/S0006-3207(03)00190-3
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Gustafson EJ, 2013, LANDSCAPE ECOL, V28, P1429, DOI 10.1007/s10980-013-9927-4
   Hayhoe K, 2007, CLIM DYNAM, V28, P381, DOI 10.1007/s00382-006-0187-8
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hirzel AH, 2002, ECOLOGY, V83, P2027, DOI 10.1890/0012-9658(2002)083[2027:ENFAHT]2.0.CO;2
   Hirzel AH, 2008, J APPL ECOL, V45, P1372, DOI 10.1111/j.1365-2664.2008.01524.x
   Hoffacker ML, 2018, OECOLOGIA, V188, P623, DOI 10.1007/s00442-018-4228-x
   IPCC, 2010, IPCC EXP M ASS COMB
   Jacobsen C.D., 2019, ARBOREAL BEHAV HERPE, V50, P110
   Jacobsen C.D., 2019, THESIS
   Kozak KH, 2010, AM NAT, V176, P40, DOI 10.1086/653031
   Kuussaari M, 2009, TRENDS ECOL EVOL, V24, P564, DOI 10.1016/j.tree.2009.04.011
   La Sorte Frank A, 2010, Proc Biol Sci, V277, P3401, DOI 10.1098/rspb.2010.0612
   Lafon CW, 2007, PHYS GEOGR, V28, P1, DOI 10.2747/0272-3646.28.1.1
   Lembrechts JJ, 2019, ECOGRAPHY, V42, P1267, DOI 10.1111/ecog.03947
   Luoto M, 2005, GLOBAL ECOL BIOGEOGR, V14, P575, DOI 10.1111/j.1466-822x.2005.00186.x
   MacKenzie DI, 2006, J WILDLIFE MANAGE, V70, P367, DOI 10.2193/0022-541X(2006)70[367:MTPORU]2.0.CO;2
   Mammola S, 2018, ECOGRAPHY, V41, P1194, DOI 10.1111/ecog.03464
   Markle TM, 2018, ECOL EVOL, V8, P4644, DOI 10.1002/ece3.4006
   McCune B, 2002, J VEG SCI, V13, P603, DOI 10.1111/j.1654-1103.2002.tb02087.x
   McEntire KD, 2019, FRONT ECOL EVOL, V7, DOI 10.3389/fevo.2019.00022
   Mcrae BH, 2008, ECOLOGY, V89, P2712, DOI 10.1890/07-1861.1
   Merow C, 2014, METHODS ECOL EVOL, V5, P215, DOI 10.1111/2041-210X.12152
   Milanovich JR, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0012189
   Mitchell J.C., 1994, Conservation agreement for the Cow Knob Salamander
   Moskwik M, 2014, J BIOGEOGR, V41, P1957, DOI 10.1111/jbi.12352
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Nuñez TA, 2013, CONSERV BIOL, V27, P407, DOI 10.1111/cobi.12014
   Peterman WE, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0062184
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Quintero I, 2013, ECOL LETT, V16, P1095, DOI 10.1111/ele.12144
   Riddell EA, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aar5471
   Riddell L, 2019, NORTH SCOTL, V10, P1, DOI 10.3366/nor.2019.0166
   Rissler LJ, 2010, MOL ECOL, V19, P5404, DOI 10.1111/j.1365-294X.2010.04879.x
   Royle JA, 2012, METHODS ECOL EVOL, V3, P545, DOI 10.1111/j.2041-210X.2011.00182.x
   Sutton WB, 2015, FORESTS, V6, P1, DOI 10.3390/f6010001
   Tebaldi C, 2014, CLIMATIC CHANGE, V122, P459, DOI 10.1007/s10584-013-1032-9
   Title PO, 2018, ECOGRAPHY, V41, P291, DOI 10.1111/ecog.02880
   U.S. Forest Service, 2014, US FOREST SERVICE MA, P374
   Yackulic CB, 2013, METHODS ECOL EVOL, V4, P236, DOI 10.1111/2041-210x.12004
   Zuckerberg B, 2009, GLOBAL CHANGE BIOL, V15, P1866, DOI 10.1111/j.1365-2486.2009.01878.x
NR 66
TC 8
Z9 9
U1 6
U2 37
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
EI 2351-9894
J9 GLOB ECOL CONSERV
JI Glob. Ecol. Conserv.
PD MAR
PY 2020
VL 21
AR e00883
DI 10.1016/j.gecco.2019.e00883
PG 12
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA KR7RT
UT WOS:000517814100088
OA gold
DA 2025-01-10
ER

PT J
AU Howe-Kerr, LI
   Bachelot, B
   Wright, RM
   Kenkel, CD
   Bay, LK
   Correa, AMS
AF Howe-Kerr, Lauren I.
   Bachelot, Benedicte
   Wright, Rachel M.
   Kenkel, Carly D.
   Bay, Line K.
   Correa, Adrienne M. S.
TI Symbiont community diversity is more variable in corals that respond
   poorly to stress
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE Acropora millepora; alpha diversity; beta diversity; climate change;
   coral; generalized joint attribute model (GJAM); Symbiodiniaceae; Vibrio
   owensii
ID SYMBIODINIUM SPP.; MULTIPLE PARTNERS; ALGAL SYMBIONTS; REEF CORALS;
   BIODIVERSITY; GROWTH; SUSCEPTIBILITY; FLEXIBILITY; TOLERANCE; MUTUALISM
AB Coral reefs are declining globally as climate change and local water quality press environmental conditions beyond the physiological tolerances of holobionts-the collective of the host and its microbial symbionts. To assess the relationship between symbiont composition and holobiont stress tolerance, community diversity metrics were quantified for dinoflagellate endosymbionts (Family: Symbiodiniaceae) from eight Acropora millepora genets that thrived under or responded poorly to various stressors. These eight selected genets represent the upper and lower tails of the response distribution of 40 coral genets that were exposed to four stress treatments (and control conditions) in a 10-day experiment. Specifically, four 'best performer' coral genets were analyzed at the end of the experiment because they survived high temperature, high pCO(2), bacterial exposure, or combined stressors, whereas four 'worst performer' genets were characterized because they experienced substantial mortality under these stressors. At the end of the experiment, seven of eight coral genets mainly hosted Cladocopium symbionts, whereas the eighth genet was dominated by both Cladocopium and Durusdinium symbionts. Symbiodiniaceae alpha and beta diversity were higher in worst performing genets than in best performing genets. Symbiont communities in worst performers also differed more after stress exposure relative to their controls (based on normalized proportional differences in beta diversity), than did best performers. A generalized joint attribute model estimated the influence of host genet and treatment on Symbiodiniaceae community composition and identified strong associations among particular symbionts and host genet performance, as well as weaker associations with treatment. Although dominant symbiont physiology and function contribute to host performance, these findings emphasize the importance of symbiont community diversity and stochasticity as components of host performance. Our findings also suggest that symbiont community diversity metrics may function as indicators of resilience and have potential applications in diverse disciplines from climate change adaptation to agriculture and medicine.
C1 [Howe-Kerr, Lauren I.; Bachelot, Benedicte; Correa, Adrienne M. S.] Rice Univ, BioSci Rice, 6100 Main St,MS-140, Houston, TX 77005 USA.
   [Wright, Rachel M.] Smith Coll, Biol Sci, Northampton, MA 01063 USA.
   [Kenkel, Carly D.] Univ Southern Calif, Dept Biol Sci, Los Angeles, CA 90007 USA.
   [Bay, Line K.] Australian Inst Marine Sci, Townsville, Qld, Australia.
C3 Rice University; Smith College; University of Southern California;
   Australian Institute of Marine Science
RP Howe-Kerr, LI (corresponding author), Rice Univ, BioSci Rice, 6100 Main St,MS-140, Houston, TX 77005 USA.
EM lih2@rice.edu
RI Bay, Line/D-4037-2009; Kenkel, Carly/AGH-5526-2022
OI Correa, Adrienne/0000-0003-0137-5042; Howe-Kerr, Lauren
   I./0000-0002-8086-5869; Bay, Line/0000-0002-9760-2977; Wright,
   Rachel/0000-0002-5867-1224
FU Sigma Xi [G2016100191023671]; Australian Institute of Marine Science
   [G11/34671.1, G14/37318.1]; US National Science Foundation [1635798,
   1800914, 1928609, 1401165]; National Academies of Sciences, Engineering,
   and Medicine [2000009651]; Division Of Ocean Sciences; Directorate For
   Geosciences [1928609, 1635798] Funding Source: National Science
   Foundation; Division Of Ocean Sciences; Directorate For Geosciences
   [1800914] Funding Source: National Science Foundation; Div Of Biological
   Infrastructure; Direct For Biological Sciences [1401165] Funding Source:
   National Science Foundation
FX Sigma Xi Grant-in-Aid of Research, Grant/Award Number:
   G2016100191023671; Australian Institute of Marine Science, Grant/Award
   Number: G11/34671.1 and G14/37318.1; US National Science Foundation,
   Grant/Award Number: 1635798, 1800914, 1928609 and 1401165; National
   Academies of Sciences, Engineering, and Medicine, Grant/Award Number:
   2000009651
CR Anderson MJ, 2013, ECOL MONOGR, V83, P557, DOI 10.1890/12-2010.1
   [Anonymous], 2019, A Research Review of Interventions to Increase the Persistence and Resilience of Coral Reefs, DOI [10.17226/25279, DOI 10.17226/25279]
   [Anonymous], 2019, VEGAN COMMUNITY ECOL
   Anslan S, 2018, MYCOKEYS, P29, DOI 10.3897/mycokeys.39.28109
   Baker AC, 2001, NATURE, V411, P765, DOI 10.1038/35081151
   Baker AC, 2004, NATURE, V430, P741, DOI 10.1038/430741a
   Barshis DJ, 2014, MOL BIOL EVOL, V31, P1343, DOI 10.1093/molbev/msu107
   Baumgarten S, 2013, BMC GENOMICS, V14, DOI 10.1186/1471-2164-14-704
   Bay LK, 2016, ROY SOC OPEN SCI, V3, DOI 10.1098/rsos.160322
   Berkelmans R, 2006, P ROY SOC B-BIOL SCI, V273, P2305, DOI 10.1098/rspb.2006.3567
   Bongaerts P, 2011, MAR ECOL PROG SER, V439, P117, DOI 10.3354/meps09315
   Brading P, 2011, LIMNOL OCEANOGR, V56, P927, DOI 10.4319/lo.2011.56.3.0927
   Brener-Raffalli K, 2018, MICROBIOME, V6, DOI 10.1186/s40168-018-0423-6
   Callahan BJ, 2016, NAT METHODS, V13, P581, DOI [10.1038/NMETH.3869, 10.1038/nmeth.3869]
   Cantin NE, 2009, CORAL REEFS, V28, P405, DOI 10.1007/s00338-009-0478-8
   Chen YF, 2015, J GASTROEN HEPATOL, V30, P1429, DOI 10.1111/jgh.12932
   Clark JS, 2017, ECOL MONOGR, V87, P34, DOI 10.1002/ecm.1241
   Correa AMS, 2009, CORAL REEFS, V28, P81, DOI 10.1007/s00338-008-0456-6
   Cunning R, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2014.1725
   Cunning R, 2017, PEERJ, V5, DOI 10.7717/peerj.3472
   Cunning R, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0145099
   Cunning R, 2013, NAT CLIM CHANGE, V3, P259, DOI [10.1038/nclimate1711, 10.1038/NCLIMATE1711]
   Fox JW, 2005, ECOL LETT, V8, P846, DOI 10.1111/j.1461-0248.2005.00795.x
   Froslev TG, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01312-x
   Green EA, 2014, PEERJ, V2, DOI 10.7717/peerj.386
   Halfvarson J, 2017, NAT MICROBIOL, V2, DOI 10.1038/nmicrobiol.2017.4
   Hauff B, 2014, DIS AQUAT ORGAN, V112, P149, DOI 10.3354/dao02802
   Hoadley KD, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-46412-4
   Howells EJ, 2013, ECOLOGY, V94, P1078, DOI 10.1890/12-1257.1
   Hughes TP, 2018, NATURE, V556, P492, DOI 10.1038/s41586-018-0041-2
   Hughes TP, 2017, NATURE, V543, P373, DOI 10.1038/nature21707
   Hume BCC, 2018, PEERJ, V6, DOI 10.7717/peerj.4816
   Jones AM, 2008, P ROY SOC B-BIOL SCI, V275, P1359, DOI 10.1098/rspb.2008.0069
   Jones A, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0010437
   Jones RJ, 2008, MAR BIOL, V154, P65, DOI 10.1007/s00227-007-0900-0
   Kaniewska P, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0034659
   Kenkel CD, 2018, PEERJ, V6, DOI 10.7717/peerj.6047
   LaJeunesse TC, 2004, MAR ECOL PROG SER, V284, P147, DOI 10.3354/meps284147
   LaJeunesse TC, 2018, CURR BIOL, V28, P2570, DOI 10.1016/j.cub.2018.07.008
   LaJeunesse TC, 2009, P ROY SOC B-BIOL SCI, V276, P4139, DOI 10.1098/rspb.2009.1405
   Lee MJ, 2016, MICROB ECOL, V71, P771, DOI 10.1007/s00248-015-0724-2
   Leggat W, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0026687
   Little AF, 2004, SCIENCE, V304, P1492, DOI 10.1126/science.1095733
   Loreau M, 1998, P NATL ACAD SCI USA, V95, P5632, DOI 10.1073/pnas.95.10.5632
   Loreau M, 2001, SCIENCE, V294, P804, DOI 10.1126/science.1064088
   Love MI, 2014, GENOME BIOL, V15, DOI 10.1186/s13059-014-0550-8
   Ludka J, 2015, ECOL ENTOMOL, V40, P437, DOI 10.1111/een.12206
   Lundgren P, 2013, BMC GENET, V14, DOI 10.1186/1471-2156-14-9
   Manzello DP, 2019, GLOBAL CHANGE BIOL, V25, P1016, DOI 10.1111/gcb.14545
   Maynard J, 2015, NAT CLIM CHANGE, V5, P688, DOI 10.1038/nclimate2625
   McIlroy SE, 2019, ECOL EVOL, V9, P12767, DOI 10.1002/ece3.5749
   McMurdie PJ, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0061217
   Mieog JC, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0006364
   Miller TEX, 2007, OIKOS, V116, P500, DOI 10.1111/j.2007.0030-1299.15317.x
   Moeller AH, 2013, CELL HOST MICROBE, V14, P340, DOI 10.1016/j.chom.2013.08.005
   Moeller HV, 2016, PEERJ, V4, DOI 10.7717/peerj.2270
   Morikawa MK, 2019, P NATL ACAD SCI USA, V116, P10586, DOI 10.1073/pnas.1721415116
   Palmer CV, 2018, COMMUN BIOL, V1, DOI 10.1038/s42003-018-0097-4
   Palmer TM, 2010, P NATL ACAD SCI USA, V107, P17234, DOI 10.1073/pnas.1006872107
   Poland DM, 2019, MAR ECOL PROG SER, V612, P87, DOI 10.3354/meps12876
   Putnam HM, 2013, MAR BIOL, V160, P2157, DOI 10.1007/s00227-012-2129-9
   Putnam HM, 2012, P ROY SOC B-BIOL SCI, V279, P4352, DOI 10.1098/rspb.2012.1454
   Quigley KM, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-50045-y
   Quigley KM, 2018, HEREDITY, V121, P524, DOI 10.1038/s41437-018-0059-0
   Quigley KM, 2017, FRONT MAR SCI, V4, DOI 10.3389/fmars.2017.00401
   Quigley KM, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-08179-4
   Quigley KM, 2016, ROY SOC OPEN SCI, V3, DOI 10.1098/rsos.160471
   Quigley KM, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0094297
   Ratzka Carolin, 2012, Insects, V3, P553, DOI 10.3390/insects3020553
   Rouzé H, 2016, ECOL EVOL, V6, P560, DOI 10.1002/ece3.1895
   Silverstein RN, 2017, J EXP BIOL, V220, P1192, DOI 10.1242/jeb.148239
   Silverstein RN, 2015, GLOBAL CHANGE BIOL, V21, P236, DOI 10.1111/gcb.12706
   Smith RT, 2009, J PHYCOL, V45, P1030, DOI 10.1111/j.1529-8817.2009.00730.x
   Stanton ML, 2003, AM NAT, V162, pS10, DOI 10.1086/378646
   Stat M, 2012, ADV MAR BIOL, V63, P1, DOI 10.1016/B978-0-12-394282-1.00001-6
   Stat M, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0015854
   Tilman D, 1997, SCIENCE, V278, P1866
   van Oppen MJH, 2018, MOL ECOL, V27, P2956, DOI 10.1111/mec.14763
   Wang S, 2012, NAT METHODS, V9, P808, DOI [10.1038/NMETH.2023, 10.1038/nmeth.2023]
   Witman JD, 2004, P NATL ACAD SCI USA, V101, P15664, DOI 10.1073/pnas.0404300101
   Wright RM, 2019, GLOBAL CHANGE BIOL, V25, P3294, DOI 10.1111/gcb.14764
   Wu J, 2016, ISME J, V10, P2435, DOI 10.1038/ismej.2016.37
   Zaneveld JR, 2017, NAT MICROBIOL, V2, DOI 10.1038/nmicrobiol.2017.121
   Zaneveld JR, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11833
   Ziegler M, 2018, J PHYCOL, V54, P447, DOI 10.1111/jpy.12749
   Ziegler M, 2018, ISME J, V12, P161, DOI 10.1038/ismej.2017.151
   Ziegler M, 2017, J BIOGEOGR, V44, P674, DOI 10.1111/jbi.12913
NR 87
TC 34
Z9 40
U1 1
U2 36
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD APR
PY 2020
VL 26
IS 4
BP 2220
EP 2234
DI 10.1111/gcb.14999
EA FEB 2020
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA NG8TI
UT WOS:000512729000001
PM 32048447
OA Bronze, Green Submitted
DA 2025-01-10
ER

PT J
AU Hao, L
   Pan, C
   Fang, D
   Zhang, XY
   Zhou, DC
   Liu, PL
   Liu, YQ
   Sun, G
AF Hao, Lu
   Pan, Cen
   Fang, Di
   Zhang, Xiaoyu
   Zhou, Decheng
   Liu, Peilong
   Liu, Yongqiang
   Sun, Ge
TI Quantifying the effects of overgrazing on mountainous watershed
   vegetation dynamics under a changing climate
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Vegetation dynamics; Leaf area index; Grazing pressure; Climate change
   detection; Mountainous watershed management
ID LEAF-AREA INDEX; INNER-MONGOLIA; GRASSLAND ECOSYSTEM; HEIHE RIVER;
   TYPICAL STEPPE; SOIL; COVER; SERVICES; MODEL; EVAPOTRANSPIRATION
AB Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km x 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural management that aims at meeting multiple demands of watershed ecosystem services in arid and semiarid rangelands. (C) 2018 Elsevier B.V. All rights reserved.
C1 [Hao, Lu; Pan, Cen; Fang, Di; Zhou, Decheng; Liu, Peilong] Nanjing Univ Informat Sci & Technol, Joint Int Res Lab Climate & Environm Change ILCEC, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Jiangsu Key Lab Agr Meteorol,Minist Educ KLME, Nanjing 210044, Jiangsu, Peoples R China.
   [Zhang, Xiaoyu] CMA, Key Lab Meteorol Disaster Monitoring & Early Warn, Yinchuan 750002, Peoples R China.
   [Liu, Yongqiang] US Forest Serv, Ctr Forest Disturbance Sci, Southern Res Stn, USDA, Athens, GA 30602 USA.
   [Sun, Ge] US Forest Serv, Eastern Forest Environm Threat Assessment Ctr, Southern Res Stn, USDA, Raleigh, NC 27606 USA.
C3 Nanjing University of Information Science & Technology; China
   Meteorological Administration; United States Department of Agriculture
   (USDA); United States Forest Service; United States Department of
   Agriculture (USDA); United States Forest Service
RP Hao, L (corresponding author), Nanjing Univ Informat Sci & Technol, Joint Int Res Lab Climate & Environm Change ILCEC, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Jiangsu Key Lab Agr Meteorol,Minist Educ KLME, Nanjing 210044, Jiangsu, Peoples R China.
EM haolu@nuist.edu.cn
RI Liu, Yongqiang/J-2027-2012; Sun, Ge/ABF-6673-2020; Zhang,
   xiaoyu/GXA-3206-2022; Zhou, Decheng/H-5583-2019
OI Zhou, Decheng/0000-0003-0947-0853; Sun, Ge/0000-0002-0159-1370
FU Natural Science Foundation of China [91425301, 41571026]; Chinese
   Special Fund for Meteorological-Scientific Research in the Public
   Interest [GYHY201506001-23]; Southern Research Station, United States
   Department of Agriculture Forest Service
FX This work was supported by the Natural Science Foundation of China
   (grant numbers 91425301, 41571026) and the Chinese Special Fund for
   Meteorological-Scientific Research in the Public Interest (grant number
   GYHY201506001-23). We thank the two anonymous reviewers and editors for
   their constructive comments and suggestions. We acknowledge the China
   Meteorological Data Service Center (http://data.cma.cn/en) for providing
   weather observation data, Beijing Normal University
   (http://www.bnu-datacenter.coml) for the LAI datasets, and the Cold and
   Arid Regions Science Data Center (http://westdc.westgis.ac.cn/) for
   sharing the climate and vegetation data. Partial support was also
   received from the Southern Research Station, United States Department of
   Agriculture Forest Service.
CR Andrew ME, 2014, PROG PHYS GEOG, V38, P328, DOI 10.1177/0309133314528942
   [Anonymous], 2011, Qinghai Prataculture
   [Anonymous], 2005, ECOSYSTEMS HUMAN WEL
   Ao-Jan Su, 2010, Proceedings 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT), P50, DOI 10.1109/WI-IAT.2010.195
   Archer ERM, 2004, J ARID ENVIRON, V57, P381, DOI 10.1016/S0140-1963(03)00107-1
   Baranova Alina, 2016, Hacquetia, V15, P21, DOI 10.1515/hacq-2016-0014
   Bastin G, 2012, REMOTE SENS ENVIRON, V121, P443, DOI 10.1016/j.rse.2012.02.021
   Blanco LJ, 2009, RANGELAND ECOL MANAG, V62, P445, DOI 10.2111/08-213.1
   BNU Center for Global Change, 2016, DAT PROC AN
   Bréda NJJ, 2003, J EXP BOT, V54, P2403, DOI 10.1093/jxb/erg263
   Bresloff CJ, 2013, J ENVIRON MANAGE, V114, P92, DOI 10.1016/j.jenvman.2012.09.026
   BUDYKO M.I., 1974, Climate and Life, P508
   Bürgi M, 2015, LANDSCAPE ECOL, V30, P11, DOI 10.1007/s10980-014-0102-3
   Chen JQ, 2015, BIOSCIENCE, V65, P559, DOI 10.1093/biosci/biv050
   Chen Y, 2005, PHYS CHEM EARTH, V30, P408, DOI 10.1016/j.pce.2005.06.019
   Cheng GD, 2014, NATL SCI REV, V1, P413, DOI 10.1093/nsr/nwu017
   Christensen L, 2004, CLIMATIC CHANGE, V63, P351, DOI 10.1023/B:CLIM.0000018513.60904.fe
   Darvishzadeh R, 2008, INT J APPL EARTH OBS, V10, P358, DOI 10.1016/j.jag.2008.02.005
   DAUGHTRY CST, 1992, REMOTE SENS ENVIRON, V39, P141, DOI 10.1016/0034-4257(92)90132-4
   Deng SF, 2013, J MT SCI-ENGL, V10, P1050, DOI 10.1007/s11629-013-2558-z
   Díaz S, 2007, GLOBAL CHANGE BIOL, V13, P313, DOI 10.1111/j.1365-2486.2006.01288.x
   Feng XM, 2011, ECOL INDIC, V11, P175, DOI 10.1016/j.ecolind.2009.07.002
   Ganguly S, 2008, REMOTE SENS ENVIRON, V112, P4333, DOI 10.1016/j.rse.2008.07.014
   Gao JM, 2017, INT J DISAST RISK RE, V25, P60, DOI 10.1016/j.ijdrr.2017.07.012
   Gao JM, 2016, INT J DISAST RISK RE, V19, P334, DOI 10.1016/j.ijdrr.2016.09.007
   [郭铌 Guo Ni], 2003, [应用气象学报, Journal of Applied Meteorolgical Science], V14, P700
   Hamon W. R., 1964, Publ. Int. Ass. sci. Hydrol. Symp. gen. Assembly Berkeley, V63, P52
   Han F., 1993, ACTA PHYTOECOLOGICA, V17, P331
   Han JJ, 2015, PLANT ECOL, V216, P599, DOI 10.1007/s11258-015-0462-z
   Han QF, 2014, ECOL COMPLEX, V17, P149, DOI 10.1016/j.ecocom.2013.12.002
   Hao L, 2016, T ASABE, V59, P577
   Hao L, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8121032
   Hao L, 2014, LANDSCAPE ECOL, V29, P1657, DOI 10.1007/s10980-014-0092-1
   Ji XB, 2007, AGR WATER MANAGE, V87, P337, DOI 10.1016/j.agwat.2006.08.011
   Kawamura K, 2005, AGR ECOSYST ENVIRON, V107, P83, DOI 10.1016/j.agee.2004.09.008
   Kendall M., 1975, Rank Correlation Methods, V4th
   Lamarque P, 2011, REG ENVIRON CHANGE, V11, P791, DOI 10.1007/s10113-011-0214-0
   Li A, 2012, LANDSCAPE ECOL, V27, P969, DOI 10.1007/s10980-012-9751-2
   Li D., 2011, THESIS, DOI [10.7666/d.Y2039004, DOI 10.7666/D.Y2039004]
   Li RH, 2014, ECOL INDIC, V41, P155, DOI 10.1016/j.ecolind.2014.01.043
   Li X, 2013, B AM METEOROL SOC, V94, P1145, DOI 10.1175/BAMS-D-12-00154.1
   Liang SL, 2013, INT J DIGIT EARTH, V6, P5, DOI 10.1080/17538947.2013.805262
   Liu PL, 2017, SCI TOTAL ENVIRON, V589, P73, DOI 10.1016/j.scitotenv.2017.02.210
   [刘兴元 LIU Xing-yuan], 2010, [中国草地学报, Chinese Journal of Grassland], V32, P99
   Liu YB, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094010
   Ludwig J. A., 1997, LAND SCAPE ECOLOGY F
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Musau J., 2016, Hydrol. Earth Syst. Sci. Discuss., DOI DOI 10.5194/HESS-2016-502
   Ning B.Y., 2006, ECON GEOL, V26, P128
   Pickup G., 1989, Australian Rangeland Journal, V11, P74
   Sa W. J., 2012, THESIS
   Schirpke U, 2017, ECOSYST SERV, V26, P79, DOI 10.1016/j.ecoser.2017.06.008
   Schröter D, 2005, SCIENCE, V310, P1333, DOI 10.1126/science.1115233
   Sha Z, 2014, REMOTE SENS LETT, V5, P912, DOI 10.1080/2150704X.2014.976882
   Shang Z., 2007, Front. Agric. China, V1, P197, DOI [DOI 10.1007/S11703-007-0034-7, 10.1007/s11703-007-0034-7]
   Snow Leopard Network (SLN), 2014, SNOW LEOPARD SURVIVA
   Steinfeld H, 2007, ANNU REV ENV RESOUR, V32, P271, DOI 10.1146/annurev.energy.32.041806.143508
   Sun G., 2013, Landscape Influences on Climate and Water Resources at the Landscape to Regional Scale, P309, DOI [DOI 10.1007/978-94-007-6350-6_15, 10.1007/978-94-007-6350-6_15]
   Sun G, 2013, DRYLAND E ASIA LAND, P153
   Sun G, 2017, ECOL PROCESS, V6, DOI 10.1186/s13717-017-0104-6
   Sun G, 2011, J GEOPHYS RES-BIOGEO, V116, DOI 10.1029/2010JG001573
   Sun G, 2011, ECOHYDROLOGY, V4, P245, DOI 10.1002/eco.194
   SUN L, 2017, SUSTAINABILITY-BASEL, V9, DOI DOI 10.3390/SU9020281
   Wang H., 2008, J. Xi'an Univ. Sci. Technol, V28, P6
   Wang JY, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8030168
   Wang NL, 2009, CHINESE SCI BULL, V54, P2751, DOI 10.1007/s11434-009-0505-8
   [王巧玲 Wang Qiaoling], 2014, [甘肃农业大学学报, Journal of Gansu Agricultural University], V49, P127
   Wang X. F., 2005, J GANSU FORESTRY SCI, V30, P32
   Wang YuPing Wang YuPing, 2012, Scientia Silvae Sinicae, V48, P23
   Washington-Allen RA, 2006, RANGELAND ECOL MANAG, V59, P19, DOI 10.2111/04-116R2.1
   Wessels KJ, 2007, J ARID ENVIRON, V68, P271, DOI 10.1016/j.jaridenv.2006.05.015
   Wint W., 2007, Gridded Livestock of the World, P131
   Xiao ZQ, 2016, IEEE T GEOSCI REMOTE, V54, P5301, DOI 10.1109/TGRS.2016.2560522
   Xiao ZQ, 2014, IEEE T GEOSCI REMOTE, V52, P209, DOI 10.1109/TGRS.2013.2237780
   [颜东海 Yan Donghai], 2012, [干旱区研究, Arid Zone Research], V29, P245
   Yan Min, 2016, Chinese Journal of Plant Ecology, V40, P1, DOI 10.17521/cjpe.2015.0253
   Yang DW, 2015, SCI CHINA EARTH SCI, V58, P36, DOI 10.1007/s11430-014-5029-7
   [杨嘉 YANGJia], 2008, [高原气象, Plateau Meteorology], V27, P896
   Yu L, 2010, PEDOSPHERE, V20, P342, DOI 10.1016/S1002-0160(10)60023-9
   Yu X., 1983, CHIN J GRASSL, V1, P9
   Zarate-Valdez JL, 2012, COMPUT ELECTRON AGR, V85, P24, DOI 10.1016/j.compag.2012.03.009
   Zhang X, 2016, CLIN MASS SPECTROM, V2, P1, DOI 10.1016/j.clinms.2016.11.002
   Zhang Z., 1992, RANGELAND RESOURCES, P15
NR 83
TC 57
Z9 59
U1 5
U2 165
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD OCT 15
PY 2018
VL 639
BP 1408
EP 1420
DI 10.1016/j.scitotenv.2018.05.224
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA GL0UG
UT WOS:000436806200134
PM 29929304
DA 2025-01-10
ER

PT J
AU Nizic, MK
   Grdic, ZS
AF Nizic, Marinela Krstinic
   Grdic, Zvonimira Sverko
TI Winter Tourism in Croatia: Is It Possible?
SO SUSTAINABILITY
LA English
DT Article
DE climate change; winter tourism; extending the tourism season; Croatia
ID CLIMATE-CHANGE ADAPTATION; WEATHER; DEMAND; PERCEPTIONS; IMPACTS
AB Tourism in Croatia primarily relies on the "sun and sea" product as the main asset of its offering. The current lack of adequate infrastructure, an underdeveloped winter tourism offering and the lack of stakeholders' interest in developing winter tourism products are only some of the problems facing winter tourism development in Croatia. Winter tourism development does not include only snow-related activities but all outdoor activities, where weather and climate play a significant role. This paper analyzes the relationship between average monthly climate indicators in summer and winter periods and the number of overnight stays in Croatia from 1977 to 2014. In the regression analysis, we used a multivariate model with first difference specification and ordinary least square (OLS) estimation, in which past period of the dependent variable was also included. Seasonality was controlled by using quarterly dummy variable. The analyses for coastal and continental Croatia were made separately. Using regression and correlation analyses, we prove that Croatian tourism in the coastal part is strongly related to climate parameters while that influence in the continental part is less significant. The main hypothesis of the paper is that, with the increase in temperature, the tourism season will be prolonged in both the coastal and continental part of the Republic of Croatia. However, other interventions in tourism (such as raising the quality, expanding the offering etc.) can also increase tourism results since climate parameters do not have the same effect on the continental and coastal part of the Republic of Croatia. The impending climate change will cause climate indicators to change, thus unlocking the potential for winter tourism development in areas not related to the sea, but also requiring the development of various forms of special-interest tourism. Winter tourism in Croatia represents a big potential not only because climate change will potentially make winters in Croatia milder but also because, with the right policies, there is a huge potential to develop the undeveloped region of continental Croatia with products that would diversify the Croatian tourism offerings.
C1 [Nizic, Marinela Krstinic; Grdic, Zvonimira Sverko] Univ Rijeka, Fac Tourism & Hospitality Management, Primorska 42, Opatija 51410, Croatia.
C3 University of Rijeka
RP Grdic, ZS (corresponding author), Univ Rijeka, Fac Tourism & Hospitality Management, Primorska 42, Opatija 51410, Croatia.
EM marikn@fthm.hr; zgrdic@fthm.hr
RI ; Sverko Grdic, Zvonimira/T-4012-2018
OI Krstinic Nizic, Marinela/0000-0002-0042-7608; Sverko Grdic,
   Zvonimira/0000-0002-9029-6487
FU University of Rijeka [ZP UNIRI 4/16]
FX This paper has been financially supported by the University of Rijeka,
   for the scientific project ZP UNIRI 4/16.
CR Amelung B., 2007, Journal of Travel Research, V45, P285, DOI 10.1177/0047287506295937
   [Anonymous], TURISTICKA GEOGRAFIJ
   [Anonymous], GROSS DOM PROD 2000
   [Anonymous], TURIZAM SPORT RAZVOJ
   [Anonymous], 2012, TOURISM DESTINATION
   [Anonymous], POP CENS REP CROAT
   [Anonymous], KLIMATOLOGIJA GEOGRA
   [Anonymous], 7 I TOUR
   [Anonymous], 2007, TOUR HOSP MANAG
   [Anonymous], 2015, J. Environ. Manag. Tour
   [Anonymous], 2003, P FRST INT C CLIMATE
   [Anonymous], KLIMATSKE PROMJENE T
   [Anonymous], 2004, TOUR HOSP MANAG
   Bar On R., 1976, Journal of Travel Research, V14, P25, DOI DOI 10.1177/004728757601400470
   Becken S, 2013, J TRAVEL RES, V52, P156, DOI 10.1177/0047287512461569
   Beniston M, 2006, HYDROBIOLOGIA, V562, P3, DOI 10.1007/s10750-005-1802-0
   Bonzanigo L, 2016, J SUSTAIN TOUR, V24, P637, DOI 10.1080/09669582.2015.1122013
   Buckley R, 2011, ANNU REV ENV RESOUR, V36, P397, DOI 10.1146/annurev-environ-041210-132637
   Bujosa A, 2013, CLIMATIC CHANGE, V117, P363, DOI 10.1007/s10584-012-0554-x
   Dawson J, 2013, TOURISM MANAGE, V35, P244, DOI 10.1016/j.tourman.2012.07.009
   Dawson J, 2007, ANN LEIS RES, V10, P550, DOI 10.1080/11745398.2007.9686781
   Dulal H. B., 2009, Sustainability, V1, P363
   Hall CM, 2015, TOURISM MANAGE, V47, P352, DOI 10.1016/j.tourman.2014.08.009
   Hamilton JM, 2007, REG ENVIRON CHANGE, V7, P161, DOI 10.1007/s10113-007-0036-2
   Han JH, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8070644
   Hindley A, 2017, CURR ISSUES TOUR, V20, P1684, DOI 10.1080/13683500.2014.946477
   Hoogendoorn G, 2016, BULL GEOGR SOCIO-ECO, V31, P59, DOI 10.1515/bog-2016-0005
   Hopkins D, 2014, TOURISM GEOGR, V16, P400, DOI 10.1080/14616688.2013.823457
   Jopp R, 2015, TOUR PLAN DEV, V12, P300, DOI 10.1080/21568316.2014.988879
   Jopp R, 2013, ASIA PAC J TOUR RES, V18, P144, DOI 10.1080/10941665.2012.688515
   Kaenzig R, 2016, TOURISM GEOGR, V18, P111, DOI 10.1080/14616688.2016.1144642
   Köberl J, 2016, SCI TOTAL ENVIRON, V543, P1039, DOI 10.1016/j.scitotenv.2015.03.099
   Koenig-Lewis N., 2005, International Journal of Tourism Research, V7, P201, DOI 10.1002/jtr.531
   Kozak N, 2008, TOURISM GEOGR, V10, P81, DOI 10.1080/14616680701825230
   Li HY, 2018, J TRAVEL RES, V57, P178, DOI 10.1177/0047287516687409
   Li HY, 2017, J TRAVEL RES, V56, P158, DOI 10.1177/0047287515626304
   Martin BG, 2005, ANN TOURISM RES, V32, P571, DOI 10.1016/j.annals.2004.08.004
   McKercher B, 2015, J TRAVEL RES, V54, P442, DOI 10.1177/0047287514522880
   Michailidou AV, 2016, TOURISM MANAGE, V55, P1, DOI 10.1016/j.tourman.2016.01.010
   Müller H, 2008, TOUR REV, V63, P57, DOI 10.1108/16605370810901580
   Nizic MK, 2014, TOUR HOSP MANAG-CROA, V20, P29
   Ridderstaat J, 2014, TOURISM MANAGE, V41, P245, DOI 10.1016/j.tourman.2013.09.005
   Schliephack J, 2017, TOURISM MANAGE, V59, P182, DOI 10.1016/j.tourman.2016.08.004
   Scott D, 2010, PROCEDIA ENVIRON SCI, V1, P146, DOI 10.1016/j.proenv.2010.09.011
   Scott D, 2007, TOURISM MANAGE, V28, P570, DOI 10.1016/j.tourman.2006.04.020
   Scott D, 2010, J SUSTAIN TOUR, V18, P283, DOI 10.1080/09669581003668540
   Solomon S., 2007, Contibution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, V50, P75
   Steiger R, 2013, TOURISM GEOGR, V15, P577, DOI 10.1080/14616688.2012.762539
   Wong E, 2013, ASIA PAC J TOUR RES, V18, P52, DOI 10.1080/10941665.2012.688511
   Wyss R, 2015, LOCAL ENVIRON, V20, P908, DOI 10.1080/13549839.2013.879289
NR 50
TC 3
Z9 3
U1 1
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD OCT
PY 2018
VL 10
IS 10
AR 3563
DI 10.3390/su10103563
PG 14
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA GY4UB
UT WOS:000448559400205
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Stephens, SA
   Bell, RG
   Lawrence, J
AF Stephens, Scott A.
   Bell, Robert G.
   Lawrence, Judy
TI Developing signals to trigger adaptation to sea-level rise
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE sea-level rise; storm-tide; coastal adaptation; dynamic adaptive policy
   pathways; flooding; inundation
ID DEEP UNCERTAINTY; TIPPING POINTS; STORM-SURGE; EXTREME; CLIMATE; IMPACT;
   PROJECTIONS; GUIDANCE
AB Dynamic adaptive policy pathways (DAPP) is emerging as a 'fit-for-purpose' method for climate-change adaptation planning to address widening future uncertainty and long planning timeframes. A key component of DAPP is to monitor indicators of change such as flooding and storm events, which can trigger timely adaptive actions (change pathway/behavior) ahead of thresholds. Signals and triggers are needed to support DAPP-the signal provides early warning of the emergence of the trigger (decision-point), and the trigger initiates the process to change pathway before a harmful adaptation-threshold is reached. We demonstrate a new approach to designing signals and triggers using the case of increased flooding as sea level continues to rise. The flooding frequency is framed in terms of probable timing of several events reaching a specific height threshold within a set monitoring period. This framing is well suited to adaptive planning for different hazards, because it allows the period over which threshold exceedances are monitored to be specified, and thus allows action before adaptation-thresholds are reached, while accounting for the potential range of timing and providing a probability of premature warning, or of triggering adaptation too late. For our New Zealand sea level case study, we expect early signals to be observed in 10 year monitoring periods beginning 2021. Some urgency is therefore required to begin the assessment, planning and community engagement required to develop adaptive plans and associated signals and triggers for monitoring. Worldwide, greater urgency is required at tide-dominated sites than those adapted to large storm-surges. Triggers can be designed with confidence that a change in behavior pathway (e.g. relocating communities) will be triggered before an adaptation-threshold occurs. However, it is difficult to avoid the potential for premature adaptation. Therefore, political, social, economic, or cultural signals are also needed to complement the signals and triggers based on coastal-hazard considerations alone.
C1 [Stephens, Scott A.; Bell, Robert G.] Natl Inst Water & Atmospher Res, POB 11115, Hamilton 3251, New Zealand.
   [Lawrence, Judy] Victoria Univ Wellington, New Zealand Climate Change Res Inst, Sch Geog Environm & Earth Sci, Cotton Bldg,Rooms 125-133,POB 600, Wellington, New Zealand.
C3 National Institute of Water & Atmospheric Research (NIWA) - New Zealand;
   Victoria University Wellington
RP Stephens, SA (corresponding author), Natl Inst Water & Atmospher Res, POB 11115, Hamilton 3251, New Zealand.
EM scott.stephens@niwa.co.nz
RI Lawrence, Judy/W-9823-2019
OI Stephens, Scott/0000-0002-6573-8757; Bell, Robert/0000-0002-8490-8942
FU Supporting Decision Making in a Changing Climate: Tools and measures
   project within the NZ Deep South National Science Challenge; NZ Ministry
   of Business, Innovation and Employment under Strategic Science
   Investment Fund-National Institute of Water and Atmospheric Research
   [CAVA1804]; Resilience Science Challenge Living at the Edge project
FX The authors were funded primarily by the Supporting Decision Making in a
   Changing Climate: Tools and measures project within the NZ Deep South
   National Science Challenge. SAS and RGB were partially funded by the NZ
   Ministry of Business, Innovation and Employment under Strategic Science
   Investment Fund (Project CAVA1804)-National Institute of Water and
   Atmospheric Research. RGB and JL also received funding from the
   Resilience Science Challenge Living at the Edge project which has
   enabled further testing for development of signals and triggers to
   support DAPP. Benjamin Robinson processed sealevel data. Thanks to Karin
   Bryan, Paula Blackett and two anonymous reviewers, whose reviews helped
   to improve the manuscript. Sea-level data were obtained from various
   port companies in NZ, and the University of Hawaii Sea Level Centre.
CR [Anonymous], SILVERMAND2011 INTER
   [Anonymous], CLIMATE CHANGE 2014
   Barnett J, 2014, NAT CLIM CHANGE, V4, P1103, DOI 10.1038/NCLIMATE2383
   Beavan R., 2012, Vertical Land Movement Around the New Zealand Coastline: Implications for Sea-Level Rise
   Buchanan MK, 2016, CLIMATIC CHANGE, V137, P347, DOI 10.1007/s10584-016-1664-7
   Ceres RL, 2017, CLIMATIC CHANGE, V145, P221, DOI 10.1007/s10584-017-2075-0
   Church JA, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1137
   Devlin AT, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-17056-z
   Frame B, 2018, CLIM RISK MANAG, V21, P39, DOI 10.1016/j.crm.2018.05.001
   Gouldby B, 2014, COAST ENG, V88, P15, DOI 10.1016/j.coastaleng.2014.01.012
   Haasnoot M, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/10/105008
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Haasnoot M, 2012, CLIMATIC CHANGE, V115, P795, DOI 10.1007/s10584-012-0444-2
   Hannah J, 2012, J GEOPHYS RES-OCEANS, V117, DOI 10.1029/2011JC007591
   Hermans LM, 2017, ENVIRON SCI POLICY, V69, P29, DOI 10.1016/j.envsci.2016.12.005
   Hinkel J, 2014, P NATL ACAD SCI USA, V111, P3292, DOI 10.1073/pnas.1222469111
   Hunter JR, 2013, OCEAN ENG, V71, P17, DOI 10.1016/j.oceaneng.2012.12.041
   Hunter J, 2012, CLIMATIC CHANGE, V113, P239, DOI 10.1007/s10584-011-0332-1
   Hunter J, 2010, CLIMATIC CHANGE, V99, P331, DOI 10.1007/s10584-009-9671-6
   Jeuken A, 2015, J WATER CLIM CHANGE, V6, P711, DOI 10.2166/wcc.2014.141
   Jordà G, 2014, J GEOPHYS RES-OCEANS, V119, P7164, DOI 10.1002/2014JC010005
   Kopp RE, 2017, EARTHS FUTURE, V5, P1217, DOI 10.1002/2017EF000663
   Kopp RE, 2014, EARTHS FUTURE, V2, P383, DOI 10.1002/2014EF000239
   Kwadijk JCJ, 2010, WIRES CLIM CHANGE, V1, P729, DOI 10.1002/wcc.64
   Kwakkel JH, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000626
   Lawrence J, 2018, ENVIRON SCI POLICY, V82, P100, DOI 10.1016/j.envsci.2018.01.012
   Lawrence J, 2017, ENVIRON SCI POLICY, V68, P47, DOI 10.1016/j.envsci.2016.12.003
   Le Cozannet G, 2015, ENVIRON MODELL SOFTW, V73, P44, DOI 10.1016/j.envsoft.2015.07.021
   Mastrandrea MD, 2011, CLIMATIC CHANGE, V108, P675, DOI 10.1007/s10584-011-0178-6
   Mazas F, 2014, COAST ENG, V91, P140, DOI 10.1016/j.coastaleng.2014.05.006
   Merrifield MA, 2013, J GEOPHYS RES-OCEANS, V118, P2535, DOI 10.1002/jgrc.20173
   Moftakhari HR, 2017, P NATL ACAD SCI USA, V114, P9785, DOI 10.1073/pnas.1620325114
   Nicholls RJ, 2011, PHILOS T R SOC A, V369, P161, DOI [10.1098/rsta.2010.0291, 10.1098/rsta.2010.029]
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Oddo PC, 2020, RISK ANAL, V40, P153, DOI 10.1111/risa.12888
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Ranger N, 2013, EURO J DECIS PROCESS, V1, P233, DOI 10.1007/s40070-013-0014-5
   Ray RD, 2016, EARTHS FUTURE, V4, P578, DOI 10.1002/2016EF000423
   Rueda A, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-05090-w
   Salas JD, 2014, J HYDROL ENG, V19, P554, DOI 10.1061/(ASCE)HE.1943-5584.0000820
   Slangen ABA, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5020021
   Solari S, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011475
   Stephens SA, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5030040
   Sweet WV, 2014, EARTHS FUTURE, V2, P579, DOI 10.1002/2014EF000272
   Tebaldi C, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014032
   van Buuren A, 2014, REG ENVIRON CHANGE, V14, P1021, DOI 10.1007/s10113-013-0448-0
   Wahl T, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms16075
   Wahl T, 2011, NAT HAZARD EARTH SYS, V11, P2925, DOI 10.5194/nhess-11-2925-2011
   Wahl T, 2015, NAT CLIM CHANGE, V5, P1093, DOI [10.1038/nclimate2736, 10.1038/NCLIMATE2736]
   Walker WE, 2013, SUSTAINABILITY-BASEL, V5, P955, DOI 10.3390/su5030955
   Werners SE, 2013, CURR OPIN ENV SUST, V5, P334, DOI 10.1016/j.cosust.2013.06.005
   Wong TE, 2017, EARTHS FUTURE, V5, P1015, DOI 10.1002/2017EF000607
NR 52
TC 59
Z9 62
U1 1
U2 19
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 1748-9326
J9 ENVIRON RES LETT
JI Environ. Res. Lett.
PD OCT
PY 2018
VL 13
IS 10
AR 104004
DI 10.1088/1748-9326/aadf96
PG 11
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA GV2PM
UT WOS:000445933400002
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Akumaga, U
   Tarhule, A
   Piani, C
   Traore, B
   Yusuf, AA
AF Akumaga, Uvirkaa
   Tarhule, Aondover
   Piani, Claudio
   Traore, Bouba
   Yusuf, Ado A.
TI Utilizing Process-Based Modeling to Assess the Impact of Climate Change
   on Crop Yields and Adaptation Options in the Niger River Basin, West
   Africa
SO AGRONOMY-BASEL
LA English
DT Article
DE climate change; agriculture; crop yield; adaptation; Niger Basin;
   AquaCrop
ID FAO AQUACROP MODEL; MAIZE; PRECIPITATION; AGRICULTURE; SIMULATIONS; MALI
AB Climate change is estimated to substantially reduce crop yields in Sub-Saharan West Africa by 2050. Yet, a limited number of studies also suggest that several adaptation measures may mitigate the effects of climate change induced yield loss. In this paper, we used AquaCrop, a process-based model developed by the FAO (The Food and Agriculture Organization, Rome, Italy), to quantify the risk of climate change on several key cereal crops in the Niger Basin. The crops analyzed include maize, millet, and sorghum under rain fed cultivation systems in various agro-ecological zones within the Niger Basin. We also investigated several adaptation strategies, including changes in the sowing dates, soil nutrient status, and cultivar. Future climate change is estimated using nine ensemble bias-corrected climate model projection results under RCP4.5 and RCP8.5 (RCP-Representative Concentration Pathway) emissions scenario at mid future time period, 2021/25-2050. The results show that on average, temperature had a larger effect on crop yields so that the increase in precipitation could still be a net loss of crop yield. Our simulated results showed that climate change effects on maize and sorghum yield would be mostly positive (2% to 6% increase) in the Southern Guinea savanna zone while at the Northern Guinea savanna zone it is mostly negative (2% to 20% decrease). The results show that at the Sahelian zone the projected changes in temperature and precipitation have little to no impact on millet yield for the future time period, 2021/25-2050. In all agro-ecological zones, increasing soil fertility from poor fertility to moderate, near optimal and optimal level significantly reversed the negative yield change respectively by over 20%, 70% and 180% for moderate fertility, near optimal fertility, and optimal fertility. Thus, management or adaptation factors, such as soil fertility, had a much larger effect on crop yield than the climatic change factors. These results provide actionable guidance on effective climate change adaptation strategies for rain fed agriculture in the region.
C1 [Akumaga, Uvirkaa] Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA.
   [Tarhule, Aondover] SUNY Binghamton, Grad Sch, Binghamton, NY 13902 USA.
   [Piani, Claudio] Amer Univ Paris, Dept Comp Math & Environm Sci, F-75007 Paris, France.
   [Traore, Bouba] ICRISAT Mali, BP 320, Bamako, Mali.
   [Yusuf, Ado A.] Ahmadu Bello Univ, Inst Agr Res, Fac Agr, Dept Soil Sci, Zaria 1044, Pmb, Nigeria.
C3 University of Oklahoma System; University of Oklahoma - Norman; State
   University of New York (SUNY) System; Binghamton University, SUNY; The
   American University of Paris; Ahmadu Bello University; Institute for
   Agricultural Research, Samaru, Zaria
RP Akumaga, U (corresponding author), Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA.
EM uvirkaa.akumaga-1@ou.edu; atarhule@binghamton.edu; cpiani@aup.edu;
   bouabasiditraore@yahoo.fr; adamu_99@yahoo.co.uk
RI Akumaga, Uvirkaa/U-7812-2019
OI Yusuf, Ado/0000-0003-2869-4625
CR Adejuwon JO, 2006, CLIM RES, V32, P229, DOI 10.3354/cr032229
   Akumaga U, 2017, AGR FOREST METEOROL, V232, P225, DOI 10.1016/j.agrformet.2016.08.011
   Andersen I, 2005, DIR DEV, P1, DOI 10.1596/978-0-8213-6203-7
   [Anonymous], ESAPWP228 UN DEP EC
   [Anonymous], WEST AFRICAN AGRICUL
   [Anonymous], 2009, Climate change. Impact on Agriculture and costs of adaptation, P1
   [Anonymous], 2004, ISWS CR 2004-08
   [Anonymous], 2017, FAO-Statistics
   Araya A, 2010, FIELD CROP RES, V116, P196, DOI 10.1016/j.fcr.2009.12.010
   Blanc E., 2012, AM J CLIMATE CHANGE, V1, P1, DOI DOI 10.4236/AJCC.2012.11001
   Butt TA, 2005, CLIMATIC CHANGE, V68, P355, DOI 10.1007/s10584-005-6014-0
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   *FAO, 2006, STAT FOOD INS WORLD, P4
   FAO, 2012, ETO CALC REF MAN VER
   Gbobaniyi E, 2014, INT J CLIMATOL, V34, P2241, DOI 10.1002/joc.3834
   Haerter JO, 2015, GEOPHYS RES LETT, V42, P1919, DOI 10.1002/2015GL063188
   Heng LK, 2009, AGRON J, V101, P488, DOI 10.2134/agronj2008.0029xs
   Hsiao TC, 2009, AGRON J, V101, P448, DOI 10.2134/agronj2008.0218s
   JAMIESON PD, 1991, FIELD CROP RES, V27, P337, DOI 10.1016/0378-4290(91)90040-3
   Jones PG, 2003, GLOBAL ENVIRON CHANG, V13, P51, DOI 10.1016/S0959-3780(02)00090-0
   Knox J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034032
   Lahmar R, 2012, FIELD CROP RES, V132, P158, DOI 10.1016/j.fcr.2011.09.013
   Muller C., 2010, Climate change impacts on agricultural yields: Background note to the World Development Report 2010
   Nikulin G, 2012, J CLIMATE, V25, P6057, DOI 10.1175/JCLI-D-11-00375.1
   Pachauri R.K., 2014, CLIMATE CHANGE 2014
   Piani C, 2010, J HYDROL, V395, P199, DOI 10.1016/j.jhydrol.2010.10.024
   Raes D, 2009, AGRON J, V101, P438, DOI 10.2134/agronj2008.0140s
   Rockstrom J., 2007, Water for Food, Water for Life, P315
   Rockström J, 2015, NATURE, V519, P283, DOI 10.1038/519283a
   Rosenzweig C, 2014, P NATL ACAD SCI USA, V111, P3268, DOI 10.1073/pnas.1222463110
   Roudier P, 2011, GLOBAL ENVIRON CHANG, V21, P1073, DOI 10.1016/j.gloenvcha.2011.04.007
   Sánchez PA, 2010, NAT GEOSCI, V3, P299, DOI 10.1038/ngeo853
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   Steduto P, 2009, AGRON J, V101, P426, DOI 10.2134/agronj2008.0139s
   Sultan B, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104006
   Tarhule A., 2011, CLIMATE VARIABILTY S
   Tarhule A, 2015, INT J CLIMATOL, V35, P520, DOI 10.1002/joc.3999
   Tarhule A, 2009, B AM METEOROL SOC, V90, P1607, DOI 10.1175/2009BAMS2697.1
   Thornton PK, 2011, PHILOS T R SOC A, V369, P117, DOI 10.1098/rsta.2010.0246
   Tingem M, 2009, MITIG ADAPT STRAT GL, V14, P153, DOI 10.1007/s11027-008-9156-3
   Traore B, 2017, FIELD CROP RES, V201, P133, DOI 10.1016/j.fcr.2016.11.002
   Van Gaelen H, 2015, J AGR SCI-CAMBRIDGE, V153, P1218, DOI 10.1017/S0021859614000872
   Washington R., 2012, CLIMATE CHANGE W AFR, V303
   WILLMOTT CJ, 1982, B AM METEOROL SOC, V63, P1309, DOI 10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2
   Willmott CJ., 1981, Phys Geogr, V2, P184, DOI [DOI 10.1080/02723646.1981.10642213, 10.1080/02723646.1981.10642213]
NR 45
TC 15
Z9 17
U1 1
U2 25
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 2073-4395
J9 AGRONOMY-BASEL
JI Agronomy-Basel
PD FEB
PY 2018
VL 8
IS 2
AR 1 1
DI 10.3390/agronomy8020011
PG 19
WC Agronomy; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences
GA FZ3QV
UT WOS:000427505900003
OA Green Accepted, Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Arshad, M
   Kächele, H
   Krupnik, TJ
   Amjath-Babu, TS
   Aravindakshan, S
   Abbas, A
   Mehmood, Y
   Müller, K
AF Arshad, Muhammad
   Kaechele, Harald
   Krupnik, Timothy J.
   Amjath-Babu, T. S.
   Aravindakshan, Sreejith
   Abbas, Azhar
   Mehmood, Yasir
   Mueller, Klaus
TI Climate variability, farmland value, and farmers' perceptions of climate
   change: implications for adaptation in rural Pakistan
SO INTERNATIONAL JOURNAL OF SUSTAINABLE DEVELOPMENT AND WORLD ECOLOGY
LA English
DT Article
DE Climate change; land valuation; land use; adaptation; rural development;
   South Asia; Ricardian analysis
ID FOOD SECURITY; WHEAT YIELD; AGRICULTURE; BANGLADESH; OPTIONS; WATER;
   IRRIGATION; IMPACTS; ENERGY; US
AB Many studies have examined the impact of climatic variability on agricultural productivity, although an understanding of these effects on farmland values and their relationship to farmers' decisions to adapt and modify their land-use practices remains nascent in developing nations. We estimated the impacts of the deviation in our study year's (2012) temperature and precipitation patterns from medium-term (1980-2011) climatic patterns on farmland values in Pakistan. This was accomplished by employing a modified form of a Ricardian regression model. We also examined farmers' perceptions of climate change during this period, as well as their perceptions of climate change impacts on farm productivity, in addition to past and anticipated farm adaptation strategies. Our results indicate that positive temperature deviation from the medium-term mean - indicative of climatic change - affects farmland values in Pakistan. Deviation in annual cumulative precipitation conversely appears to have no significant impact. Estimates of the marginal impact of temperature deviation suggested a slight but negative linear relationship with farmland values. The location of farms in areas where farmers can avail financial or extension services conversely had a positive impact on farmland values, as did the availability of irrigation facilities. Our analysis of farmers' perceptions of climate change and their consequent adaptation behavior indicated a relatively high degree of awareness of climatic variability that influenced a number of proactive and future anticipated farm adaptation strategies. Examples included increased use of irrigation and farm enterprise diversification, as well as land-use change, including shifting from agriculture into alternative land uses. National policy in Pakistan underscores the importance of maintaining a productive rural agricultural sector. Our findings consequently highlight the importance of appropriate adaptation strategies to maintain both farm productivity and farmland values in much of Pakistan. The implications of increased extension and financial services to enhance farmers' potential for climate change adaptation are discussed.
C1 [Arshad, Muhammad; Kaechele, Harald; Amjath-Babu, T. S.; Abbas, Azhar; Mueller, Klaus] Leibniz Ctr Agr Landscape Res ZALF, Inst Socioecon, Muncheberg, Germany.
   [Kaechele, Harald] Eberswalde Univ Sustainable Dev, Dept Landscape Management & Nat Conservat, Eberswalde, Germany.
   [Krupnik, Timothy J.; Aravindakshan, Sreejith] Int Maize & Wheat Improvement Ctr CIMMYT, Sustainable Intensificat Program, Dhaka, Bangladesh.
   [Aravindakshan, Sreejith] Wageningen Univ, Farming Syst Ecol FSE, Wageningen, Netherlands.
   [Abbas, Azhar] Univ Agr Faisalabad, Inst Agr & Resource Econ, Faisalabad, Pakistan.
   [Mehmood, Yasir] Northwest Agr & Forestry Univ, Coll Econ & Management, Yangling, Peoples R China.
   [Mueller, Klaus] Humboldt Univ, Econ & Polit Rural Areas, Fac Life Sci, Berlin, Germany.
C3 Leibniz Association; Leibniz Zentrum fur Agrarlandschaftsforschung
   (ZALF); Eberswalde University for Sustainable Development; CGIAR;
   International Maize & Wheat Improvement Center (CIMMYT); Wageningen
   University & Research; University of Agriculture Faisalabad; Northwest
   A&F University - China; Humboldt University of Berlin
RP Arshad, M (corresponding author), Leibniz Ctr Agr Landscape Res ZALF, Inst Socioecon, Muncheberg, Germany.
EM Muhammad.Arshad@zalf.de
RI Abid, Muhammad/J-8581-2017; Abbas, Dr Azhar/H-9311-2019; Krupnik,
   Timothy/J-6363-2019; Aravindakshan, Sreejith/L-4282-2016
OI Mehmood, Yasir/0000-0003-2389-6324; Aravindakshan,
   Sreejith/0000-0003-3801-3221; Abbas, Dr. Azhar/0000-0003-2045-2971;
   Amjath-Babu, T.S/0000-0001-9902-7104; Arshad,
   Muhammad/0000-0002-6948-7094; Krupnik, Timothy
   Joseph/0000-0001-6973-0106
FU German Academic Exchange Service (DAAD); Higher Education Commission,
   Pakistan (HEC); Stiftung Fiat Panis, Germany; ZALF, Germany
FX This study is financed by German Academic Exchange Service (DAAD) and
   Higher Education Commission, Pakistan (HEC). Initial data collection was
   funded by Stiftung Fiat Panis, Germany, while follow-up data collection
   was financed by ZALF, Germany.
CR Abbas A, 2016, INT J SUST DEV WORLD, V23, P98, DOI 10.1080/13504509.2015.1111954
   Amjath-Babu TS, 2016, ECOL INDIC, V67, P830, DOI 10.1016/j.ecolind.2016.03.030
   [Anonymous], POP GROWTH ANN
   [Anonymous], CLIM CHANGE
   [Anonymous], 2007, COMPREHENSIVE ASSESS
   [Anonymous], EC APLIC
   [Anonymous], 2009, PMD222009
   [Anonymous], GEOGRAFIA
   [Anonymous], ANN FLOOD REP
   [Anonymous], PAK DEV REV
   [Anonymous], J WATER RESOUR DEV
   [Anonymous], GLOB PLANET CHANGE
   [Anonymous], SCI
   [Anonymous], 82 FOND E ENR MATT
   [Anonymous], 2015, EC SURVEY PAKISTAN
   [Anonymous], CLIM CHANGE
   [Anonymous], GLOB ENV CHANGE
   [Anonymous], P NATI ACAD SCI
   [Anonymous], 2014, IMPACTS ADAPTATION V
   [Anonymous], J AGR RES
   [Anonymous], 2009, GLOBAL ENVIRON CHANG, DOI DOI 10.1016/j.gloenvcha.2009.01.002
   [Anonymous], ENVIRON MANAGE
   [Anonymous], 2015, WORLD DEV IND 2015 E
   [Anonymous], 2009, UNDERSTANDING FARMER
   [Anonymous], CLIM CHANGE EC
   [Anonymous], J NAT RESOUR POL RES
   [Anonymous], WATER POL
   [Anonymous], AGR ECOSYST ENV
   Aravindakshan S, 2015, ENERGY, V90, P483, DOI 10.1016/j.energy.2015.07.088
   Arshad M, 2017, PADDY WATER ENVIRON, V15, P249, DOI 10.1007/s10333-016-0544-0
   Arshad M, 2016, CLIM DEV, V8, P234, DOI 10.1080/17565529.2015.1034232
   Ashutosh Tripathi Ashutosh Tripathi, 2016, Agriculture, Ecosystems & Environment, V216, P356, DOI 10.1016/j.agee.2015.09.034
   Battisti DS, 2009, SCIENCE, V323, P240, DOI 10.1126/science.1164363
   Biemans H, 2013, SCI TOTAL ENVIRON, V468, pS117, DOI 10.1016/j.scitotenv.2013.05.092
   Calzadilla A, 2013, CLIMATIC CHANGE, V120, P357, DOI 10.1007/s10584-013-0822-4
   Dell M, 2012, AM ECON J-MACROECON, V4, P66, DOI 10.1257/mac.4.3.66
   Descheemaeker K, 2019, EXP AGR, V55, P169, DOI 10.1017/S001447971600048X
   Di Falco S, 2011, AM J AGR ECON, V93, P825, DOI 10.1093/ajae/aar006
   Duffy M, 2009, J HUNGER ENVIRON NUT, V4, P375, DOI 10.1080/19320240903321292
   Ellis F., 1996, AGR POLICIES DEV COU
   Esham M, 2013, MITIG ADAPT STRAT GL, V18, P535, DOI 10.1007/s11027-012-9374-6
   Hisali E, 2011, GLOBAL ENVIRON CHANG, V21, P1245, DOI 10.1016/j.gloenvcha.2011.07.005
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Jain M, 2015, GLOBAL ENVIRON CHANG, V31, P98, DOI 10.1016/j.gloenvcha.2014.12.008
   Krupnik TJ, 2017, LAND USE POLICY, V60, P206, DOI 10.1016/j.landusepol.2016.10.001
   Krupnik TJ, 2015, AGR SYST, V139, P166, DOI 10.1016/j.agsy.2015.05.007
   Krupnik TJ, 2015, FIELD CROP RES, V170, P7, DOI 10.1016/j.fcr.2014.09.019
   Lippert C, 2009, CLIMATIC CHANGE, V97, P593, DOI 10.1007/s10584-009-9652-9
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Maddison D, 2000, EUR REV AGRIC ECON, V27, P519, DOI 10.1093/erae/27.4.519
   Massetti E, 2011, CLIM CHANG ECON, V2, P301, DOI 10.1142/S2010007811000322
   Mendelsohn R, 2006, ENVIRON DEV ECON, V11, P159, DOI 10.1017/S1355770X05002755
   MENDELSOHN R, 1994, AM ECON REV, V84, P753
   Nelson GC, 2014, P NATL ACAD SCI USA, V111, P3274, DOI 10.1073/pnas.1222465110
   Piya L, 2013, REG ENVIRON CHANGE, V13, P437, DOI 10.1007/s10113-012-0359-5
   Power AG, 2010, PHILOS T R SOC B, V365, P2959, DOI 10.1098/rstb.2010.0143
   Reinsborough MJ, 2003, CAN J ECON, V36, P21, DOI 10.1111/1540-5982.00002
   Ricardo D., 1817, On the Principles of Political Economy and Taxation
   Ruamsuke K, 2015, ENERGY, V81, P446, DOI 10.1016/j.energy.2014.12.057
   Salik KM, 2015, OCEAN COAST MANAGE, V112, P61, DOI 10.1016/j.ocecoaman.2015.05.006
   Schlenker W, 2005, AM ECON REV, V95, P395, DOI 10.1257/0002828053828455
   Sheikh A. D., 2007, Pakistan Journal of Agricultural Sciences, V44, P341
   Siddiqui R., 2012, Pakistan Development Review, V4, DOI [10.30541/v51i4iipp.261-276, DOI 10.30541/V51I4IIPP.261-276]
   Sietz D, 2011, ENVIRON SCI POLICY, V14, P493, DOI 10.1016/j.envsci.2011.01.001
   Silvestri S, 2012, REG ENVIRON CHANGE, V12, P791, DOI 10.1007/s10113-012-0293-6
   Sterrett C., 2011, Review of climate change adaptation practices in South Asia, Oxfam Research Report
   Tambo JA, 2012, MITIG ADAPT STRAT GL, V17, P277, DOI 10.1007/s11027-011-9325-7
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Waqar Akram Waqar Akram, 2011, Pakistan Economic and Social Review, V49, P231
   Wood SA, 2014, GLOBAL ENVIRON CHANG, V25, P163, DOI 10.1016/j.gloenvcha.2013.12.011
   Zhu TJ, 2013, WATER INT, V38, P651, DOI 10.1080/02508060.2013.830682
NR 71
TC 23
Z9 25
U1 0
U2 4
PU TAYLOR & FRANCIS INC
PI PHILADELPHIA
PA 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA
SN 1350-4509
EI 1745-2627
J9 INT J SUST DEV WORLD
JI Int. J. Sustain. Dev. World Ecol.
PY 2017
VL 24
IS 6
BP 532
EP 544
DI 10.1080/13504509.2016.1254689
PG 13
WC Green & Sustainable Science & Technology; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA FH1QD
UT WOS:000410913600007
DA 2025-01-10
ER

PT J
AU Arbuckle, JG Jr
   Hobbs, J
   Loy, A
   Morton, LW
   Prokopy, LS
   Tyndall, J
AF Arbuckle, J. G., Jr.
   Hobbs, J.
   Loy, A.
   Morton, L. W.
   Prokopy, L. S.
   Tyndall, J.
TI Understanding Corn Belt farmer perspectives on climate change to inform
   engagement strategies for adaptation and mitigation
SO JOURNAL OF SOIL AND WATER CONSERVATION
LA English
DT Article
DE adaptation; agriculture; climate change; communication; extension;
   latent class analysis
ID PERCEPTIONS; AGRICULTURE; SCIENCE; VULNERABILITY; WILLINGNESS;
   CHALLENGES; INTERFACE; ATTITUDES; EFFICACY; BELIEFS
AB Development of extension and outreach that effectively engage farmers in climate change adaptation and/or mitigation activities can be informed by an improved understanding of farmers' perspectives on climate change and related impacts. This research employed latent class analysis (LCA) to analyze data from a survey of 4,778 farmers from 11 US Corn Belt states. The research focused on two related research questions: (1) to what degree do farmers differ on key measures of beliefs about climate change, experience with extreme weather, perceived risks to agriculture, efficacy, and level of support for public and private adaptive and mitigative action; and (2) are there potential areas of common ground among farmers? Results indicate that farmers have highly heterogeneous perspectives, and six distinct classes of farmers are identified. We label these as the following: the concerned (14%), the uneasy (25%), the uncertain (25%), the unconcerned (13%), the confident (18%), and the detached (5%). These groups of farmers differ primarily in terms of beliefs about climate change, the degree to which they had experienced extreme weather, and risk perceptions. Despite substantial differences on these variables, areas of similarity were discerned on variables measuring farmers' (1) confidence that they will be able to deal with increases in weather variability and (2) support for public and private efforts to help farmers adapt to increased weather variability. These results can inform segmented approaches to outreach that target subpopulations of farmers as well as broader engagement strategies that would reach wider populations. Further, findings suggest that strategies with specific reference to climate change might be most effective in engaging the subpopulations of farmers who believe that climate change is occurring and a threat, but that use of less charged terms such as weather variability would likely be more effective with a broader range of farmers. Outreach efforts that (1) appeal to farmers' problem solving capacity and (2) employ terms such as "weather variability" instead of more charged terms such as "climate change" are more likely to be effective with a wider farmer audience.
C1 [Arbuckle, J. G., Jr.; Morton, L. W.] Iowa State Univ, Ames, IA 50011 USA.
   [Hobbs, J.] CALTECH, Jet Prop Lab, Pasadena, CA USA.
   [Loy, A.] Lawrence Univ, Appleton, WI 54912 USA.
   [Prokopy, L. S.] Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA.
   [Tyndall, J.] Iowa State Univ, Dept Nat Resources Ecol & Management, Ames, IA USA.
C3 Iowa State University; California Institute of Technology; National
   Aeronautics & Space Administration (NASA); NASA Jet Propulsion
   Laboratory (JPL); Lawrence University; Purdue University System; Purdue
   University; Iowa State University
RP Arbuckle, JG Jr (corresponding author), Iowa State Univ, Ames, IA 50011 USA.
RI Arbuckle, J/P-2151-2016; Tyndall, John/AAR-6189-2021
OI Kling, Catherine L/0000-0002-4785-7154; Loy, Adam/0000-0002-5780-4611
CR Ajzen I, 2002, J APPL SOC PSYCHOL, V32, P665, DOI 10.1111/j.1559-1816.2002.tb00236.x
   Akerlof K, 2013, GLOBAL ENVIRON CHANG, V23, P81, DOI 10.1016/j.gloenvcha.2012.07.006
   Anderegg WRL, 2010, P NATL ACAD SCI USA, V107, P12107, DOI 10.1073/pnas.1003187107
   [Anonymous], CLIMAGE CHANGE IMPAC
   [Anonymous], 2005, Perspective
   [Anonymous], 2009, 2007 Census of Agriculture
   [Anonymous], HDB ENV SOCIOLOGY
   [Anonymous], US GLOB WARM VIEWS S
   [Anonymous], 1994, AGR HDB
   [Anonymous], CLIMATIC CHANGE
   [Anonymous], 2009, Eos (Washington DC), DOI DOI 10.1029/2009EO030002
   [Anonymous], 2008, Handbook of Data Visualization, DOI DOI 10.1007/978-3-540-33037-07
   [Anonymous], 2007, SYNTHESIS REPORT CON
   [Anonymous], CROP PROD 2010 SUMM
   [Anonymous], PROD SUPPL DISTR ONL
   [Anonymous], AGR FOR CHANG CLIM A
   [Anonymous], POS STAT CLIM CHANG
   [Anonymous], 2012, FARMER BEHAV AGR MAN, DOI DOI 10.1787/9789264167650-EN
   [Anonymous], 2010, AD IMP CLIM CHANG AM
   Arbuckle JG, 2013, CLIMATIC CHANGE, V117, P943, DOI 10.1007/s10584-013-0707-6
   BANDURA A, 1991, ORGAN BEHAV HUM DEC, V50, P248, DOI 10.1016/0749-5978(91)90022-L
   Berry PM, 2006, ENVIRON SCI POLICY, V9, P189, DOI 10.1016/j.envsci.2005.11.004
   Brody SD, 2008, ENVIRON BEHAV, V40, P72, DOI 10.1177/0013916506298800
   Brossard D, 2010, NEW AGENDAS COMMUN, P11
   Comito J, 2011, PATHWAYS FOR GETTING TO BETTER WATER QUALITY: THE CITIZEN EFFECT, P67, DOI 10.1007/978-1-4419-7282-8_6
   Ding D, 2011, NAT CLIM CHANGE, V1, P462, DOI 10.1038/NCLIMATE1295
   Dunlap RE, 2013, AM BEHAV SCI, V57, P691, DOI 10.1177/0002764213477097
   Groffman PM, 2010, FRONT ECOL ENVIRON, V8, P284, DOI 10.1890/090160
   Hatfield JL, 2011, AGRON J, V103, P351, DOI 10.2134/agronj2010.0303
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Hulme M, 2009, WHY WE DISAGREE ABOUT CLIMATE CHANGE: UNDERSTANDING CONTROVERSY, INACTION AND OPPORTUNITY, P1
   Kahan DM, 2011, J RISK RES, V14, P147, DOI 10.1080/13669877.2010.511246
   Kellstedt PM, 2008, RISK ANAL, V28, P113, DOI 10.1111/j.1539-6924.2008.01010.x
   Lal R, 2011, J SOIL WATER CONSERV, V66, P276, DOI 10.2489/jswc.66.4.276
   Leiserowitz A., 2013, EXTREME WEATHER CLIM
   Linzer DA, 2011, J STAT SOFTW, V42, P1, DOI 10.18637/jss.v042.i10
   Loy A., 2013, Farmer Perspectives on Agriculture and Weather Variability in the Corn Belt: A Statistical Atlas
   Magidson J., 2004, SAGE HDB QUANTITATIV
   Magidson J., 2002, Canadian journal of marketing research, V20, P36
   Maibach E.W., 2011, Global Warming's Six Americas screening tools: Survey instruments; instructions for coding and data treatment; and statistical program scripts
   Maibach EW, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017571
   McCarl BA, 2010, CLIMATIC CHANGE, V100, P119, DOI 10.1007/s10584-010-9833-6
   McCright AM, 2010, THEOR CULT SOC, V27, P100, DOI 10.1177/0263276409356001
   Morton LW, 2011, PATHWAYS FOR GETTING TO BETTER WATER QUALITY: THE CITIZEN EFFECT, P1
   Moser SC, 2010, WIRES CLIM CHANGE, V1, P31, DOI 10.1002/wcc.11
   Myers TA, 2013, NAT CLIM CHANGE, V3, P343, DOI [10.1038/NCLIMATE1754, 10.1038/nclimate1754]
   Nelson G. C, 2010, FOOD SECURITY FARMIN
   Nisbet MC, 2007, PUBLIC OPIN QUART, V71, P444, DOI 10.1093/poq/nfm031
   Nowak P, 2013, J SOIL WATER CONSERV, V68, p50A, DOI 10.2489/jswc.68.2.50A
   O'Connor RE, 2005, RISK ANAL, V25, P1265, DOI 10.1111/j.1539-6924.2005.00675.x
   O'Connor RE, 1999, RISK ANAL, V19, P461, DOI 10.1023/A:1007004813446
   Osmond DL, 2010, FRONT ECOL ENVIRON, V8, P306, DOI 10.1890/090145
   *PEW RES CTR, 2012, MOR SAY THER IS SOL
   R Core Team, 2012, R: A Language and Environment for Statistical Computing
   Rogers EM, 2003, Diffusion of Innovations, VXXI
   Ruttan VW, 1996, SOCIOL RURALIS, V36, P51, DOI 10.1111/j.1467-9523.1996.tb00004.x
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   SWCS, 2011, POS STAT CLIM CHANG
   Walthall C., 2012, USDA Technical Bulletin
   Weber EU, 2010, WIRES CLIM CHANGE, V1, P332, DOI 10.1002/wcc.41
   Weber EU, 2011, AM PSYCHOL, V66, P315, DOI 10.1037/a0023253
   WEGMAN EJ, 1990, J AM STAT ASSOC, V85, P664, DOI 10.2307/2290001
NR 62
TC 67
Z9 81
U1 1
U2 57
PU SOIL WATER CONSERVATION SOC
PI ANKENY
PA 945 SW ANKENY RD, ANKENY, IA 50023-9723 USA
SN 0022-4561
EI 1941-3300
J9 J SOIL WATER CONSERV
JI J. Soil Water Conserv.
PD NOV-DEC
PY 2014
VL 69
IS 6
BP 505
EP 516
DI 10.2489/jswc.69.6.505
PG 12
WC Ecology; Soil Science; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Agriculture; Water Resources
GA AT6BY
UT WOS:000345025000014
OA Bronze
DA 2025-01-10
ER

PT J
AU Nieuwenhuis, E
   Cuppen, E
   Langeveld, J
AF Nieuwenhuis, Eva
   Cuppen, Eefje
   Langeveld, Jeroen
TI The role of integration for future urban water systems: Identifying
   Dutch urban water practitioners' perspectives using Q methodology
SO CITIES
LA English
DT Article
DE Future-proofing; Integrated urban water management; Perspectives; Q
   methodology; Systems integration; Water governance
ID OF-THE-ART; STAKEHOLDER PERSPECTIVES; STORMWATER MANAGEMENT;
   CLIMATE-CHANGE; INFRASTRUCTURE; INSTITUTIONS; GOVERNANCE; RESILIENT;
   LESSONS
AB Urban water systems are under increased pressure from ongoing developments like climate change, population growth and urbanization. While it is clear that current urban water challenges need a more integrated approach, practitioners disagree on what such an integrated approach means exactly. Integration could therefore be described as a wicked problem, with practitioners having different understandings of integration, as well as the opportunities and challenges they should focus on; e.g., climate adaptation, resource recovery or collective replacement. This lack of consensus challenges decision-making, and thus the implementation of integration. To foster urban water systems integration, this study uses Q methodology to explore the different perspectives that Dutch urban water practitioners have on integration for future urban water systems. Our analysis reveals four salient perspectives: perspective 1 sees coordination as a means to make the system future-proof, perspective 2 focuses on climate adaptation, perspective 3 aims for recovery, and perspective 4 is all about efficiency and being in control. While all perspectives acknowledge that traditional urban water practices need to change, they differ on which sustainability challenges are considered most important and what means should be used. Practitioners need to understand these differences to deal effectively with the wicked nature of integration.
C1 [Nieuwenhuis, Eva; Langeveld, Jeroen] Delft Univ Technol, Fac Civil Engn, Delft, Netherlands.
   [Nieuwenhuis, Eva] Delft Univ Technol, Fac Technol Policy & Management, Delft, Netherlands.
   [Cuppen, Eefje] Leiden Univ, Fac Governance & Global Affairs, Leiden, Netherlands.
   [Langeveld, Jeroen] Partners4UrbanWater, Nijmegen, Netherlands.
C3 Delft University of Technology; Delft University of Technology; Leiden
   University - Excl LUMC; Leiden University
RP Nieuwenhuis, E (corresponding author), Delft Univ Technol, Fac Civil Engn, Delft, Netherlands.; Nieuwenhuis, E (corresponding author), Delft Univ Technol, Fac Technol Policy & Management, Delft, Netherlands.
EM e.m.nieuwenhuis@tudelft.nl
RI langeveld, jeroen/AAG-9594-2020; Cuppen, Eefje/M-1775-2015
FU Dutch "Kennisprogramma Urban Drainage" (Urban Drainage Knowledge
   Programme)
FX This work was supported by the Dutch "Kennisprogramma Urban Drainage"
   (Urban Drainage Knowledge Programme). The parties involved are: ARCADIS,
   Deltares, Evides, the cities of Almere, Arnhem, Breda, The Hague,
   Rotterdam, and Utrecht, GMB Rioleringstechnieken, KWR Watercycle
   Research Institute, Royal HaskoningDHV, the RIONED Foundation, STOWA,
   Sweco, Tauw, vandervalk+degroot, Waternet, De Dommel Water Board, and
   Witteveen+Bos.
CR [Anonymous], 1980, POLITICAL SUBJECTIVITY: APPLICATIONS OF Q METHODOLOGY IN POLITICAL SCIENCE
   [Anonymous], 2013, RIOL BEELD BENCHM RI
   Ashley RM, 2005, WATER SCI TECHNOL, V52, P265, DOI 10.2166/wst.2005.0142
   Banasick S, 2020, KEN Q ANAL VERSION 1
   Brown RR, 2009, WATER SCI TECHNOL, V59, P847, DOI 10.2166/wst.2009.029
   Brown RR, 2009, WATER SCI TECHNOL, V59, P839, DOI 10.2166/wst.2009.028
   Butler D, 2017, GLOB CHALL, V1, P63, DOI 10.1002/gch2.1010
   Chocat B, 2007, INDOOR BUILT ENVIRON, V16, P273, DOI 10.1177/1420326X07078854
   Chrobak K, 2020, Przestrzen i Forma, V42, P147
   Cousins JJ, 2017, CITIES, V66, P44, DOI 10.1016/j.cities.2017.03.005
   Cuppen E, 2012, POLICY SCI, V45, P23, DOI 10.1007/s11077-011-9141-7
   CUPPEN EHW, 2010, PUTTING PERSPECTIVES
   de Bruijn H, 2010, PROCESS MANAGEMENT: WHY PROJECT MANAGEMENT FAILS IN COMPLEX DECISION MAKING PROCESS, SECOND EDITION, P165, DOI 10.1007/978-3-642-13941-3_9
   de Graaf R, 2010, TECHNOL FORECAST SOC, V77, P1282, DOI 10.1016/j.techfore.2010.03.011
   Deletic A, 2020, BLUE-GREEN SYST, V2, P186, DOI 10.2166/bgs.2020.002
   Dunn G, 2017, URBAN WATER J, V14, P758, DOI 10.1080/1573062X.2016.1241284
   Exel VJ., 2005, Q METHODOLOGY SNEAK
   Ferguson BC, 2013, GLOBAL ENVIRON CHANG, V23, P264, DOI 10.1016/j.gloenvcha.2012.07.008
   Fletcher TD, 2015, URBAN WATER J, V12, P525, DOI 10.1080/1573062X.2014.916314
   Fratini CF, 2012, URBAN WATER J, V9, P317, DOI 10.1080/1573062X.2012.668913
   Fuenfschilling L, 2016, TECHNOL FORECAST SOC, V103, P298, DOI 10.1016/j.techfore.2015.11.023
   Harman H.H., 1976, Modern Factor Analysis
   Hisschemoller Matthijs., 1995, Knowledge and Policy, V8, P40, DOI 10.1007/BF02832229
   Hooimeijer F.L., 2018, J URBAN INT RES PLAC, V11, P303, DOI [10.1080/17549175.2017.1422532, DOI 10.1080/17549175.2017.1422532]
   Hunt DVL, 2014, TUNN UNDERGR SP TECH, V39, P15, DOI 10.1016/j.tust.2012.02.001
   Jiang Y, 2018, ENVIRON SCI POLICY, V80, P132, DOI 10.1016/j.envsci.2017.11.016
   Kiparsky M, 2013, ENVIRON ENG SCI, V30, P395, DOI 10.1089/ees.2012.0427
   Majamaa K, 2010, DESALIN WATER TREAT, V18, P17, DOI 10.5004/dwt.2010.1284
   Marlow DR, 2013, WATER RES, V47, P7150, DOI 10.1016/j.watres.2013.07.046
   McKeown B.Thomas., 2013, Q METHODOLOGY, V2nd
   Mitchell VG, 2006, ENVIRON MANAGE, V37, P589, DOI 10.1007/s00267-004-0252-1
   Mo WW, 2013, J ENVIRON MANAGE, V127, P255, DOI 10.1016/j.jenvman.2013.05.007
   Molenveld A., 2020, HDB RES METHODS APPL, P333, DOI [10.4337/9781788111195, DOI 10.4337/9781788111195]
   Molenveld A, 2020, CLIMATIC CHANGE, V162, P233, DOI 10.1007/s10584-020-02683-9
   Nieuwenhuis E, 2021, J CLEAN PROD, V280, DOI 10.1016/j.jclepro.2020.124977
   Pahl-Wostl C, 2011, WATER RESOUR MANAG, V25, P837, DOI 10.1007/s11269-010-9729-2
   PBL, 2010, RECT FORM FLOOD RISK
   Raadgever GT, 2008, HYDROL EARTH SYST SC, V12, P1097, DOI 10.5194/hess-12-1097-2008
   Rainproof Amsterdam, 2018, AMST RAINPR
   Rijke J, 2013, ENVIRON SCI POLICY, V25, P62, DOI 10.1016/j.envsci.2012.09.012
   Riley B, 2017, BUILD ENVIRON, V114, P219, DOI 10.1016/j.buildenv.2016.12.016
   RITTEL HWJ, 1973, POLICY SCI, V4, P155, DOI 10.1007/BF01405730
   Roy AH, 2008, ENVIRON MANAGE, V42, P344, DOI 10.1007/s00267-008-9119-1
   Stephenson W, 1936, B J PSYCHOL-GEN SECT, V26, P344, DOI 10.1111/j.2044-8295.1936.tb00803.x
   Tscheikner-Gratl F, 2019, URBAN WATER J, V16, P662, DOI 10.1080/1573062X.2020.1713382
   Tscheikner-Gratl F, 2016, URBAN WATER J, V13, P28, DOI 10.1080/1573062X.2015.1057174
   von der Tann L, 2020, UNDERGR SPACE, V5, P144, DOI 10.1016/j.undsp.2019.03.003
   Watts S., 2012, Doing Q methodological research
   Webler T, 2006, POLICY STUD J, V34, P699, DOI 10.1111/j.1541-0072.2006.00198.x
   Wong THF, 2009, WATER SCI TECHNOL, V60, P673, DOI 10.2166/wst.2009.436
NR 50
TC 10
Z9 10
U1 1
U2 31
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0264-2751
EI 1873-6084
J9 CITIES
JI Cities
PD JUL
PY 2022
VL 126
AR 103659
DI 10.1016/j.cities.2022.103659
EA MAR 2022
PG 14
WC Urban Studies
WE Social Science Citation Index (SSCI)
SC Urban Studies
GA 0P0YL
UT WOS:000783948900005
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Zandersen, M
   Oddershede, JS
   Pedersen, AB
   Nielsen, HO
   Termansen, M
AF Zandersen, Marianne
   Oddershede, Jakob Stoktoft
   Pedersen, Anders Branth
   Nielsen, Helle Orsted
   Termansen, Mette
TI Nature Based Solutions for Climate Adaptation - Paying Farmers for Flood
   Control
SO ECOLOGICAL ECONOMICS
LA English
DT Article
ID AGGLOMERATION BONUS; CHOICE EXPERIMENTS; MUDDY FLOODS; PAYMENTS;
   SCHEMES; DESIGN; POLICY; CONSERVATION; INSTRUMENTS; ENVIRONMENT
AB Climate change is expected to lead to more frequent and severe fluvial flood events in Northern Europe. Nature Based Solutions are increasingly recognised as a natural insurance against flood risks in vulnerable areas. This requires collaboration at landscape scale between providers and beneficiaries of flood control. In particular, mechanisms to incentivise owners of land could potentially offer cost-effective ways to reduce damage to urban infrastructure. We conduct a choice experiment among farmers located in the vicinity of a river to assess their willingness to accept a contract that would allow a local Danish municipality to periodically flood farmland to reduce urban flood risks. Results indicate that farmers on average are hesitant about entering into abatement contracts, especially if they have prior experience of crop losses due to extreme weather events. If they were to agree on a contract they would prefer a separate compensation for lost crops; a collective negotiation and higher rather than lower yearly payments. Surprisingly, data did not show a significant preference for or against a requirement to grow flood resistant crops. The results suggest that a contract with a separate damage compensation and based on individual negotiation would on average require an annual payment of 290Euro/ha for farmers with no prior experience of crop losses and 469Euro/ha for farmers who have experienced crop losses. The paper discusses the potentials and limitations of landscape scale Nature Based Solutions for climate adaptation.
C1 [Zandersen, Marianne; Pedersen, Anders Branth; Nielsen, Helle Orsted] Aarhus Univ, Dept Environm Sci, Aarhus, Denmark.
   [Zandersen, Marianne; Pedersen, Anders Branth; Nielsen, Helle Orsted] Aarhus Univ, iClimate, Interdisciplinary Ctr Climat, Aarhus, Denmark.
   [Oddershede, Jakob Stoktoft] Aarhus Univ, Dept Econ & Business Econ, Aarhus, Denmark.
   [Termansen, Mette] Univ Copenhagen, Dept Food & Resource Econ, Copenhagen, Denmark.
C3 Aarhus University; Aarhus University; Aarhus University; University of
   Copenhagen
RP Zandersen, M (corresponding author), Aarhus Univ, Dept Environm Sci, Aarhus, Denmark.; Zandersen, M (corresponding author), Aarhus Univ, iClimate, Interdisciplinary Ctr Climat, Aarhus, Denmark.
EM mz@envs.au.dk; jakoboddershede@gmail.com; abp@envs.au.dk;
   hon@envs.au.dk; mt@ifro.ku.dk
RI Pedersen, Anders Branth/IWM-0095-2023; Zandersen, Marianne/AAF-1323-2020
OI Pedersen, Anders Branth/0000-0002-4163-5649; Termansen,
   Mette/0000-0003-4875-2810; Zandersen, Marianne/0000-0002-3827-3990;
   Nielsen, Helle Orsted/0000-0003-0486-9662
FU EU FP7-project BASE [308337]; EFFECT-project [817903]; North Sea Region
   Programme
FX This work was supported by EU FP7-project BASE (Grant Agreement No.
   308337). Furthermore, the EFFECT-project (Grant Agreement No. 817903)
   has supported the completion of the manuscript. The Aquarius project,
   funded by the North Sea Region Programme developed the technical
   solutions and potential business model for 'farmers as water managers',
   upon which this research is based. We thank four anonymous farmers for
   commenting on the survey, the agricultural extension service Heden &
   Fjorden for distributing the survey to its members and Irene Wiborg,
   SEGES, for useful discussions on the financial incentives for entering
   into a performance contract. We are grateful for colleagues at
   Department for Environmental Science and two anonymous reviewers for
   providing valuable and helpful comments and inputs on earlier versions.
CR Adamowicz W, 1998, AM J AGR ECON, V80, P64, DOI 10.2307/3180269
   [Anonymous], 2005, Applied Choice Analysis: a Primer
   [Anonymous], 2015, Towards an EU research and innovation policy agenda for nature-based solutions and re-naturing cities: final report of the Horizon 2020 expert group on 'Nature-based solutions and re-naturing cities, DOI DOI 10.2777/765301
   Banerjee S, 2012, ECOL ECON, V84, P142, DOI 10.1016/j.ecolecon.2012.09.005
   Beharry-Borg N, 2013, REG ENVIRON CHANGE, V13, P633, DOI 10.1007/s10113-012-0282-9
   BEN-AKIVA M. E., 1985, Discrete Choice Analysis: Theory and Application to Travel Demand
   Broch SW, 2012, ENVIRON RESOUR ECON, V51, P561, DOI 10.1007/s10640-011-9512-8
   Bromley D. W., 1990, European Review of Agricultural Economics, V17, P197, DOI 10.1093/erae/17.2.197
   Brouwer R, 2009, ENVIRON DEV ECON, V14, P397, DOI 10.1017/S1355770X08004828
   Bubeck P, 2012, RISK ANAL, V32, P1481, DOI 10.1111/j.1539-6924.2011.01783.x
   Christensen T, 2011, ECOL ECON, V70, P1558, DOI 10.1016/j.ecolecon.2011.03.021
   Collentine D, 2018, J FLOOD RISK MANAG, V11, P76, DOI 10.1111/jfr3.12269
   Dury J, 2013, EUR J AGRON, V50, P1, DOI 10.1016/j.eja.2013.04.008
   Eckel CC, 2009, J ECON BEHAV ORGAN, V69, P110, DOI 10.1016/j.jebo.2007.08.012
   EEA, 2012, CLIM CHANG IMP VULN, DOI DOI 10.2800/66071
   Engel S, 2008, ECOL ECON, V65, P663, DOI 10.1016/j.ecolecon.2008.03.011
   Erdlenbruch K, 2009, J ENVIRON MANAGE, V91, P363, DOI 10.1016/j.jenvman.2009.09.002
   Espinosa-Goded M, 2010, J AGR ECON, V61, P259, DOI 10.1111/j.1477-9552.2010.00244.x
   European Environment Agency, 2018, WHY SHOULD WE CAR FL
   Evrard O, 2007, CATENA, V70, P443, DOI 10.1016/j.catena.2006.11.011
   Gómez-Baggethun E, 2015, ECOL ECON, V117, P217, DOI 10.1016/j.ecolecon.2015.03.016
   Greiner R, 2016, AUST J AGR RESOUR EC, V60, P1, DOI 10.1111/1467-8489.12098
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Hanley N, 1998, ENVIRON RESOUR ECON, V11, P413, DOI 10.1023/A:1008287310583
   Dang HL, 2014, ENVIRON MANAGE, V54, P331, DOI 10.1007/s00267-014-0299-6
   Holstebro Kommune, 2014, KLIMATILPASNINGSPLAN
   Holstebro Kommune, 2017, TILLAEG NR 6 KOMMUNE
   Horne P, 2006, SILVA FENN, V40, P169, DOI 10.14214/sf.359
   Jorgensen SL, 2020, ECOL ECON, V169, DOI 10.1016/j.ecolecon.2019.106489
   Kaczan D, 2013, ECOL ECON, V95, P20, DOI 10.1016/j.ecolecon.2013.07.011
   KAHNEMAN D, 1984, AM PSYCHOL, V39, P341, DOI 10.1037/0003-066X.39.4.341
   KAHNEMAN D, 1979, ECONOMETRICA, V47, P263, DOI 10.2307/1914185
   Kuhfuss L., 2019, AGR POLICY ENV ENV P, P1
   Kuhfuss L, 2016, EUR REV AGRIC ECON, V43, P609, DOI 10.1093/erae/jbv031
   Liu ZY, 2019, ENVIRON RESOUR ECON, V73, P843, DOI 10.1007/s10640-019-00330-1
   Louviere Jordan J., 2001, Stated choice methods: Analysis and application
   Manale A, 2000, J SOIL WATER CONSERV, V55, P285
   McFadden D., 1974, Journal of Public Economics, V3, P303, DOI [10.1016/0047-2727(74)90003-6, DOI 10.1016/0047-2727(74)90003-6]
   Morris J, 2016, J FLOOD RISK MANAG, V9, P50, DOI 10.1111/jfr3.12110
   Mullan D, 2016, GEOMORPHOLOGY, V270, P102, DOI 10.1016/j.geomorph.2016.07.012
   Nielsen HelleOrsted., 2010, Bounded rationality in decision-making: How cognitive shortcuts and professional values may interfere with market-based regulation
   O'Connell E, 2007, HYDROL EARTH SYST SC, V11, P96, DOI 10.5194/hess-11-96-2007
   Parkhurst GM, 2002, ECOL ECON, V41, P305, DOI 10.1016/S0921-8009(02)00036-8
   Parkhurst GM, 2007, ECOL ECON, V64, P344, DOI 10.1016/j.ecolecon.2007.07.009
   Pedersen A. B., 2011, BARRIERER LANDMAENDE, V134
   Pedersen A.B., 2014, BEKAEMPELSESMIDDELFO
   Pedersen AB, 2012, J ENVIRON PLANN MAN, V55, P1094, DOI 10.1080/09640568.2011.636568
   Reynaud A, 2016, ENVIRON MODEL ASSESS, V21, P603, DOI 10.1007/s10666-016-9500-z
   Rojas R, 2013, GLOBAL ENVIRON CHANG, V23, P1737, DOI 10.1016/j.gloenvcha.2013.08.006
   Ruto E, 2009, J ENVIRON PLANN MAN, V52, P631, DOI 10.1080/09640560902958172
   Salzman J, 2018, NAT SUSTAIN, V1, P136, DOI 10.1038/s41893-018-0033-0
   Simon V.M., 1998, PSYCHOL SPAIN, V2, P100
   Statistics Denmark, 2019, STATBANK DENM BUS SE
   Thurstone LL, 1927, PSYCHOL REV, V34, P273, DOI 10.1037/h0070288
   Vatn A, 2015, ECOL ECON, V117, P225, DOI 10.1016/j.ecolecon.2014.07.017
   Wätzold F, 2014, RESOUR ENERGY ECON, V37, P85, DOI 10.1016/j.reseneeco.2013.11.011
   Weikard HP, 2017, LAND USE POLICY, V65, P128, DOI 10.1016/j.landusepol.2017.04.006
   Wiborg I., 2014, TECHNICAL REPORT DCE, P1
   Wynn G, 2001, J AGR ECON, V52, P65, DOI 10.1111/j.1477-9552.2001.tb00910.x
   Zandersen M, 2016, ECOL ECON, V123, P14, DOI 10.1016/j.ecolecon.2015.12.002
   ,, 2017, EEA Report
NR 61
TC 22
Z9 22
U1 11
U2 108
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-8009
EI 1873-6106
J9 ECOL ECON
JI Ecol. Econ.
PD JAN
PY 2021
VL 179
AR 106705
DI 10.1016/j.ecolecon.2020.106705
PG 10
WC Ecology; Economics; Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Business & Economics
GA OH7WO
UT WOS:000582804400001
OA Green Accepted, Green Submitted
DA 2025-01-10
ER

PT J
AU Nawiyantoa
   Husain, SB
   Wisnu
   Nai'm, M
AF Nawiyantoa
   Husain, Sarkawi B.
   Wisnu
   Nai'm, Mohamad
TI Controlling the Brantas river: construction and impact of
   Japan-supported irrigation infrastructure on the agricultural economy
   and the environment in East Java
SO COGENT ARTS & HUMANITIES
LA English
DT Article
DE Irrigation infrastructure; Japan's aid; Brantas river; rice production;
   flood control; environmental impacts; Samuel Adu-Gyamfi, History and
   Political Studies, Kwame Nkrumah University of Science and Technology,
   Kumasi, Ghana; Landscape; Landscape History; Building and Construction;
   Rural Development; Environment and the Developing World; Human
   Geography; History
ID HOKKAIDO; POVERTY; DAMS
AB This article examines the crucial role played by Japan in the development of irrigation infrastructure in Indonesia from the 1960s to the 1990s. While the assistance provided by Japan in irrigation infrastructure significantly enhanced the prominence of the Brantas river valleys as a major rice granary during the green revolution, it has been largely overlooked in Indonesian historiography. Despite the historical influence of the Dutch, this article aims to elucidate the reasons behind Japan's involvement in the modernization of irrigation systems along the Brantas river in East Java, as well as the resultant effects on food production and the environment. Employing a historical approach and drawing on both primary and secondary sources, this study argues that Japan's role in Indonesia's irrigation development during the independence period originated from the war compensation fund paid by the Japanese government. This fund subsequently paved the way for greater involvement of Japanese agencies in mutual cooperation in developing irrigation infrastructure. The expansion of irrigated lands and increased rice productivity, facilitated by Japan-supported irrigation infrastructure, mitigated the risks of harvest failure due to droughts and floods. The infrastructure has also played a significant role in flood control during rainy seasons and in securing irrigation water, especially during dry seasons. Additionally, while acknowledging sacrifices incurred during the construction process and the environmental consequences of their operations, it is evident that the Japan-supported irrigation infrastructure effectively tamed the ferocity of the river and optimized its benefits, significantly improving the livelihoods of many people. To ensure the long-term sustainability of Japanese-funded infrastructure along the Brantas River, comprehensive strategies encompassing regular maintenance, technological updates, community engagement, integrated water resource management, agriculture diversification, and climate change adaptation are essential.
C1 [Nawiyantoa] Univ Jember, Fac Humanities, Dept Hist, Jember, East Java, Indonesia.
   [Husain, Sarkawi B.] Univ Airlangga, Fac Humanities, Dept Hist, Surabaya, Indonesia.
   [Wisnu] Univ Negeri Surabaya, Fac Social Sci & Law, Dept Hist Educ, Surabaya, Indonesia.
   [Nai'm, Mohamad] Univ Jember, Fac Educ & Teacher Training, Dept Hist Educ, Jember, Indonesia.
C3 Universitas Jember; Airlangga University; Universitas Negeri Surabaya;
   Universitas Jember
RP Nawiyantoa (corresponding author), Univ Jember, Fac Humanities, Dept Hist, Jember, East Java, Indonesia.
EM nawiyanto.sastra@unej.ac.id
RI Husain, Sarkawi/AEK-8438-2022; suki, wisnu/AAN-4743-2021
OI Nawiyanto, Nawiyanto/0000-0003-2612-1911; B. Husain,
   Sarkawi/0000-0002-9572-9050
FU Sumitomo Foundation; Sumitomo Foundation
FX The research activities were carried out between April 2021 and
   September 2022. The authors extend their sincere gratitude to the
   President of the Sumitomo Foundation and its staff for their generous
   support.
CR Abdullah T., 1978, Manusia dalam Kemelut Sejarah
   Album Foto 4, 1980, Pembangunan Bendung Lengkong Baru
   Amin M. H. F., 2019, Ecology, Environment Conservation, V25, P1
   Angoedi Abdullah., 1984, Sejarah irigasi di Indonesia
   [Anonymous], 1970, Direktorat Djenderal Pengairan Departemen Pekerdjaan Umum dan Tenaga Listrik
   [Anonymous], 1980, Badan Pelaksanaan Proyek Induk Pengembangan Wilayah Sungai Kali Brantas
   [Anonymous], 1972, Amanat Presiden Republik Indonesia: Pidato pada Upatjara Dalam Rangka Selesainja Bendungan Serbaguna Karangkates Djawa Timur Pada Tanggal 2 Mei 1972. Laporan, Sambutan & Amanat pada Atjara Peresmian Bendungan Serbaguna Karangkates tanggal 2 Mei 1972
   [Anonymous], 1952, Treaty of Peace with Japan
   [Anonymous], Pembikinan Pengairan Sampejan Baru, P2
   [Anonymous], 1992, Dampak Bendungan Serba Guna Karangkates terhadap Sosial Ekonomi di Malang
   ANRI, 2020, Inventaris Arsip Perusahaan Umum (Perum) Jasa Tirta I (1927) 1962-1997
   Badan Pelaksana Proyek Induk Pengembangan Wilayah Sungai Kali Brantas, 1987, Project Completion Report Proyek Wlingi Tahap I
   Badan Pelaksanaan Proyek, 1979, Laporan Akhir (Completion Report) Proyek Dam Lengkong Baru: Main report
   Badan Pelaksanaan Proyek Induk Pengembangan Wilayah Sungai Kali Brantas, 1980, Laporan Akhir Proyek Dam Lengkong Baru, main report
   BAPERSIP, 2002, Inventaris Arsip Perum Jasa Tirta Malang
   Boelee E, 2013, COMPR ASSESS WAT MAN, V10, P1, DOI 10.1079/9781780640884.0000
   Booth A., 1977, Bulletin of Indonesian Economic Studies, V13, P45, DOI 10.1080/00074917712331333114
   Booth A., 1977, Bulletin of Indonesian Economic Studies, V13, P33, DOI 10.1080/00074917712331333034
   Booth A., 1988, AGR DEV INDONESIA
   BPS Jawa Timur, 1983, Jawa Timur Dalam Angka Tahun 1983
   BPS Kabupaten Blitar, 1979, Kabupaten Blitar Dalam Angka
   BPS Kabupaten Blitar, 1991, Kabupaten Blitar Dalam Angka
   Bravo-Ureta BE, 2020, WORLD DEV, V135, DOI 10.1016/j.worlddev.2020.105073
   Bupati Sidoarjo, 2019, Peraturan Bupati Sidoarjo Nomor 86 Tahun 2019 Tentang Rencana Induk Sistem Penyediaan Air Minum Kabupaten Sidoarjo Tahun 2018-2037
   Department of Public Works and Energy, 1975, Estimate of construction cost for Wlingi Dam and Power Station Project
   Dhawan B.D., 1988, IRRIGATION INDIAS AG
   Dick HowardW., 2002, EMERGENCE NATL EC EC
   Direktorat Jenderal Pengairan, 1976, Project completion report (PCR) Proyek Wlingi I
   Direktorat Jenderal Pengairan, 1987, Proyek Pengembangan Wilayah Kali Widas
   Direktorat Jenderal Pengairan, 1976, Feasibility report on the Widas Irrigation Project
   Direktorat Jenderal Sumber Daya Air Satker Direktorat Bina Operasi dan Pemeliharaan, 2012, Penyusunan Rencana Tindak Darurat/RTD Bendungan Wlingi Jawa Timur.
   Direktorat Jenderal Sumber Daya Air Wilayah Tengah, 2002, Penilaian dan Evaluasi Tim Kerja Panitia Persiapan Penyerahan Proyek Selesai Pada Proyek Pembangunan Waduk Wonorejo
   Dwipayana G., 1991, Jejak Langkah Pak Harto 28 Maret 1968-23 Maret 1973
   Ertsen M. W., 2005, Prescribing perfection: Emergence of an engineering irrigation design approach in the Netherlands East Indies and its legacy 1830-1990
   Evenson RE, 2003, SCIENCE, V300, P758, DOI 10.1126/science.1078710
   Falkenmark M., 2007, Water for Food, Water for Life-A Comprehensive Assessment of Water Management in Agriculture, P233
   Feith H., 1995, Soekarno-Militer Dalam Demokrasi Terpimpin
   Fox J. J., 1997, Pembangunan Yang Berimbang: Jawa Timur dalam Era Orde Baru, P167
   Fukushima M, 2007, FRESHWATER BIOL, V52, P1511, DOI 10.1111/j.1365-2427.2007.01783.x
   Gammelsrod T., 1996, Effect of Zambezi river management on the prawn fishery of the Sofala Banj in water management and wetlands in Sub-Saharan Africa
   Gebregziabher G., 2011, Journal of Development and Agricultural Economics, V3, P514
   Geertz C., 1963, Agricultural Involution: The Process of Ecological Change in Indonesia
   Gunawan R., 2008, Sungai sebagai Pusat Peradaban: Prosiding Seminar Perubahan DAS Brantas dalam Perspektif Sejarah, P191
   HARRISS J, 1995, WORLD DEV, V23, P117, DOI 10.1016/0305-750X(94)00109-C
   Hatano K., 2005, ANN DISASTER PREVENT, V48B, P919
   Hazell Peter.B.R., 1982, Instability in Indian Foodgrains Production
   Hearman V., 2015, Global Food History, V1, P81, DOI 10.1080/20549547.2015.11435413
   Higgins BenjaminH., 1957, INDONESIAS EC STABIL
   Hill Hal., 2000, INDONESIAN EC
   Hirakawa H., 2011, SGRA Report No. 58
   Huang QQ, 2005, AUST J AGR RESOUR EC, V49, P159, DOI 10.1111/j.1467-8489.2005.00281.x
   Husain S. B., 2020, Banjir di Kota Surabaya Paruh Kedua Abad ke-20
   Hussain I, 2004, IRRIG DRAIN, V53, P1, DOI 10.1002/ird.114
   Itsukushima R, 2023, RIVER RES APPL, V39, P1136, DOI 10.1002/rra.4129
   Itsukushima R, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01820-z
   JICA, 1986, Development of The Brantas River Basin
   Kantor Sensus dan Statistik, 1972, Jawa Timur Dalam Angka Tahun 1971
   Kantor Statistik, 1997, Jawa Timur Dalam Angka 1996
   Kantor Statistik, 1983, Jawa Timur Dalam Angka Tahun 1981
   Karunakaran K. R., 1998, Indian Economic Review, V33, P207
   Kholidulazhhar, 2019, Keanekaragaman Ikan di Waduk Ir. Sutami Karangkates, Malang-Jawa Timur
   KINOSHITA T, 1986, B INDONES ECON STUD, V22, P34, DOI 10.1080/00074918612331334754
   Kompas.com, 2011, Puluhan Jenis Ikan di Sungai Brantas Menghilang
   Kop J. H., 2015, Irrigation revisited: An anthology of Indonesian-Dutch Cooperation 1965-2014
   Kurasawa A, 2019, Sisi Gelap Perang Asia: Problem Repatriasi dan Pampasan Perang Jepang Berdasarkan Arsip Yang Belum Pernah Terungkap
   Kurasawa Aika., 1993, Mobilisasi dan Kontrol: Studi Tentang Perubahan Sosial di Pedesaan Jawa, 1942-1945
   Kurasawa Aiko, 2015, Peristiwa 1965: Persepsi dan Sikap Jepang The 1965 incident: The perceptions and attitude of Japan
   Leirissa R. Z., 1996, Sejarah Perekonomian Indonesia
   Lembaga Pengabdian Kepada Masyarakat, 2003, Proyek Pembangunan Waduk Wonorejo di Propinsi Jawa Timur
   Mardiyah R., 2016, Pembangunan Waduk Wonorejo Kabupaten Tulungagung Tahun 1982-2002
   Margana S., 2010, Sejarah Pangan di Indonesia: Strategi dan Politik Pangan Dari Masa Kolonial Sampai Masa Reformasi
   Maryono A., 2003, Pembangunan Sungai, Dampak dan Restorasi Sungai
   Mehra S., 1981, Instability in Indian agriculture in the context of the new technology, V25
   Meynell P. J., 1995, Parks: The International Journal of Protected Areas and Conservation, V5, P15
   Moore A. S., 2020, Interrogating 'comprehensive development': The colonial wartime background to Japan's development cooperation. Background Paper No 10 Japan development cooperation: A historical perspective
   Mori Seiichi, 1999, Ecology and Civil Engineering, V2, P165
   Mustopo H., 1969, Laporan Diskripsi Data Penelitian Sosial di Blitar Selatan
   Nagasawa Toru, 2009, Japanese Journal of Ichthyology, V56, P31
   Nawiyanto, 2007, Environmental change in a frontier region of Java: Besuki 1870-1970
   Nawiyanto, 2022, Membangun Sungai Untuk Kehidupan
   Nawiyanto, 2005, The rising sun in a Javanese rice granary: Change and impact of Japanese occupation on the agricultural economy of Besuki Residency
   Nippon Koei Co. Ltd, 1982, Wlingi 2nd Stage Project Lodoyo Power Station Quantity Calculations
   Nippon Koei Co. Ltd, 1976, Wlingi multi-purpose project supplemental detailed design report on The Wlingi Power Station Substructure Part II Design Calculations
   Nippon Koei Co. Ltd, 1985, Wlingi Dam, and Power Station Project meteorological and hydrological analysis
   Nishihara M, 1993, Sukarno, Ratna Sari Dewi Pampasan Perang: Hubungan Indonesia Jepang 1951-1966
   Parwanto W, 2008, Sungai Sebagai Pusat Peradaban, P173
   Penvenne LJ, 1996, AM SCI, V84, P438
   Perusahaan Umum Listrik Negara, 1976, Agency of Ministry of Mines and Energy Government of the Republic of Indonesia, Wlingi Multi-purpose Project for Gates, Penstock and Accessories Contract No. PJ.021/PST/76 Final Operation and Maintenance Instructions
   PINSTRUP-ANDERSEN P, 1985, Food Reviews International, V1, P1
   Prabowo A. D., 2020, Handep: Jurnal Sejarah Dan Budaya, V4, P19, DOI [DOI 10.33652/HANDEP.V4I1.118, https://doi.org/10.33652/handep.v4i1.118]
   Projek Induk Serbaguna Kali Brantas, 1980, Pertumbuhan Ikan di Waduk Karangkates
   Projek Induk Serbaguna Kali Brantas0, 1972, Uraian Singkat Mengenai Projek Bendungan Serbaguna Karangkates
   Purwanto B., 2002, Indonesian economic development and Japanese technology, P1
   Ravestein W., 2005, Icon, V11, P197
   Ravestein W., 2018, Engineering the Dutch Empire: Irrigation, the colonial state and ideology in Java 1832-1942
   Reid A., 1986, JAPANESE EXPERIENCE
   Restanti N. A. D., 2021, Pembangunan Bendung Lengkong san Dampaknya Terhadap Ekologi di Sidoarjo Selatan
   Ricklefs M. C., 2008, Sejarah Indoensia Modern 1200-2008
   Roejito, 1980, Laporan Pelaksanaan Bantuan Luar Negeri Bulan Januari 1980 kepada Direktur Jenderal Pengairan 3 Maret
   Saith A., 1992, Longitudinal analysis of structural change in a north Indian village, 1970-1987: Some preliminary findings
   Saleh R. H. A., 2000, "horizontal ellipsis Mari Bung Rebut Kembali!"
   Santoso A., 1986, Public policy implementation: Rice policy at the regional level in Indonesia
   Santoso A., 1997, Pembangunan Yang Berimbang: Jawa Timur dalam Era Orde Baru, P301
   Santoso A, 2020, Inventaris Perusahaan Umum (Perum) Jasa Tirta I (1927) 1962-1997
   Sato Shigeru., 1994, WAR NATIONALISM PEAS
   Setiyono A. P., 2002, Bachelor thesis
   Shiamah N. L., 2019, Bachelor thesis
   Sinarno D., 2007, Menyimak Bendungan di Indonesia 1910-2006
   Staf Proyek Brantas, 1980, Laporan Pelaksanaan Bantuan Luar Negeri Dalam Rangka Project Aid Proyek Induk Pengembangan Sungai Brantas Direktorat Jenderal Pengairan Bulan Januari 1980
   Suharman, 2018, Akademika, V17, P75
   Sutami, 1972, Projek Induk Serbaguna Kali Brantas, Laporan, Sambutan Amanat pada Atjara Peresmian Bendungan Serbaguna Karangkates tanggal 2 Mei 1972
   Sutedjo E, 2006, Kedaulatan Rakyat
   Takahasi Y, 2004, INT J WATER RESOUR D, V20, P35, DOI 10.1080/07900620310001635593
   Team Penyusun, 1985, Pola Sistem Drainase Surabaya
   Tridaya PT Anggun, 1970, The Brantas River Rehabilitation Project: Final report
   van der Eng P., 1996, Agricultural Growth in Indonesia: Productivity Change and Policy Impact since 1880
   van der Meulen W. A., 1939, Bulletin of the Colonial Institute of Amsterdam, V3,
   Van Zanden J. L., 2012, Ekonomi Indonesia 1800-2010: Antara Drama dan Keajaiban Pertumbuhan
   Wasista D., 2013, Mendamaikan industri dan Lingkungan: Perubahan Lingkungan di Sidoarjo 1970-2006
   Wie T. K., 2005, Pelaku Berkisah: Ekonomi Indonesia 1950-an sampai 1990-an
   Wie T. K., 1994, The transfer of science and technology between Europe and Asia, 1780-1880, P39
   WIE TK, 1984, B INDONES ECON STUD, V20, P90, DOI 10.1080/00074918412331334622
   Yoshimura C, 2005, RIVER RES APPL, V21, P93, DOI 10.1002/rra.835
NR 123
TC 0
Z9 0
U1 1
U2 2
PU TAYLOR & FRANCIS AS
PI OSLO
PA KARL JOHANS GATE 5, NO-0154 OSLO, NORWAY
SN 2331-1983
J9 COGENT ARTS HUMANITE
JI Cogent Art Humanities
PD DEC 31
PY 2024
VL 11
IS 1
AR 2335756
DI 10.1080/23311983.2024.2335756
PG 22
WC Humanities, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Arts & Humanities - Other Topics
GA NG4V9
UT WOS:001199295700001
OA gold
DA 2025-01-10
ER

PT J
AU Sanz-Mas, M
   Continente, X
   Brugueras, S
   Marí-Dell'Olmo, M
   Oliveras, L
   López, MJ
AF Sanz-Mas, Marta
   Continente, Xavier
   Brugueras, Silvia
   Mari-Dell'Olmo, Marc
   Oliveras, Laura
   Lopez, Maria Jose
TI Evaluating the effect of passive cooling strategies in school buildings
   on children's well-being in Barcelona: A quasi-experimental, mixed
   methods study
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change adaptation; Passive cooling strategies; Children; School;
   Thermal comfort; Mixed methods
ID INDOOR ENVIRONMENTAL-QUALITY; THERMAL COMFORT; EDUCATIONAL BUILDINGS;
   SBS SYMPTOMS; AIR-QUALITY; CLASSROOMS; TEMPERATURE; VENTILATION;
   HUMIDITY; OFFICE
AB Passive cooling strategies were implemented in 11 school buildings in Barcelona within a pilot project to improve thermal conditions. The present study aimed to evaluate the intervention's impact on students' comfort and wellbeing at school. A quasi-experimental pre-post study based on mixed methods was conducted. Quantitative data were collected through self-reported questionnaires administrated to sixth-grade students in 21 schools (11 in an intervention group, IG, and 10 in a comparison group, CG). The authors measured changes in satisfaction with indoor temperature and indoor air quality (IAQ), the presence of bothering factors (temperature too high, temperature too low, unpleasant odours, and lighting problems), and students' well-being and performance. Difference-in-difference analysis was conducted to evaluate differences between the IG and CG in pre-post changes. Qualitative data were collected through photovoice-based sessions (59 sixth grade students) and interviews (7 teachers) in the IG. A thematic content analysis identified three main categories: changes in perceptions of indoor environmental conditions, indoor environment-related health and well-being, and indoor environment and their reported impact on learning. Quantitative findings show positive changes among the IG in perceived indoor temperature, air quality, and well-being at school, while suggest no significant changes in perceptions of temperature too low, lighting problems, and students' performance, in relation to the CG. Compared to the CG, students in the IG perceiving temperature too high significantly decreased among girls, while unpleasant odours decreased only among boys. In the qualitative assessment, participants reported that school transformations improved their indoor thermal and visual comfort, IAQ, and unpleasant odours. Participants also reported a reduction of fatigue, stress, irritability, and stifling sensation, as well as enhanced concentration. This study highlights the benefits of school passive design for student's comfort and well-being in Mediterranean climates and suggests the need to extend these interventions to other school buildings in similar contexts.
C1 [Sanz-Mas, Marta; Continente, Xavier; Brugueras, Silvia; Mari-Dell'Olmo, Marc; Oliveras, Laura; Lopez, Maria Jose] Agencia Salut Publ Barcelona ASPB, Pl Lesseps 1, Barcelona 08023, Spain.
   [Sanz-Mas, Marta; Lopez, Maria Jose] Univ Pompeu Fabra, Dept Ciencies Expt & Salut DCEXS, Doctor Aiguader 88, Barcelona 08003, Spain.
   [Continente, Xavier; Mari-Dell'Olmo, Marc; Lopez, Maria Jose] Consorcio Invest Biomed Red Epidemiol & Salud Publ, Av Monforte Lemos 3-5,Pabellon 11,Planta 0, Madrid 28029, Spain.
   [Continente, Xavier; Brugueras, Silvia; Mari-Dell'Olmo, Marc; Oliveras, Laura; Lopez, Maria Jose] Inst Recerca St Pau IR PAU, St Quinti 77-79, Barcelona 08041, Spain.
C3 Public Health Agency of Barcelona; Pompeu Fabra University
RP Continente, X (corresponding author), Agencia Salut Publ Barcelona ASPB, Serv Avaluacio & Metodes Intervencio SAMI, Pl Lesseps 1, Barcelona 08023, Spain.
EM ext_msanz@aspb.cat; xcontine@aspb.cat; sbruguer@aspb.cat;
   mmari@aspb.cat; lolivera@aspb.cat; mjlopez@aspb.cat
RI Oliveras, Laura/IWU-7660-2023; Lopez, Maria/HHC-3659-2022
OI Sanz-Mas, Marta/0009-0007-4078-2501
FU European Regional Development Fund [GBG_AS2C]; Ministry of Universities
   and Research, Government of Catalonia [2021SGR00977]
FX Funding This work was supported by European Regional Development Fund
   within the framework of the Urban Innovative Action 3rd call [GBG_AS2C,
   M.J.L.] ; and the Ministry of Universities and Research, Government of
   Catalonia [grant 2021SGR00977, M.J.L.] .
CR Ahmed T, 2021, RENEW SUST ENERG REV, V138, DOI 10.1016/j.rser.2020.110669
   Ajuntament de Barcelona, 2017, Distribucio territorial de la renda familiar disponible per capita a Barcelona
   Ajuntament de Barcelona, 2020, Barcelona converteix 11 escoles en refugis climatics i es compromet a dedicar el 25% de la inversio municipal en reformes escolars a la lluita contra l'emergencia climatica
   Alegría-Sala A, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192316039
   Almeida RMSF, 2014, ENERG BUILDINGS, V81, P127, DOI 10.1016/j.enbuild.2014.06.020
   Andersson K, 1998, INDOOR AIR, P32
   [Anonymous], RENEWSCHOOL Project
   [Anonymous], School of the Future-Towards Zero Emission With High Performance Indoor Environment
   Baba FM, 2023, ENERG BUILDINGS, V279, DOI 10.1016/j.enbuild.2022.112710
   Bakó-Biró Z, 2012, BUILD ENVIRON, V48, P215, DOI 10.1016/j.buildenv.2011.08.018
   Balador Z., 2017, PLEA C, P1
   Berardi U, 2017, ENRGY PROCED, V140, P141, DOI 10.1016/j.egypro.2017.11.130
   Bidassey-Manilal S, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13060566
   Bluyssen PM, 2017, INDOOR BUILT ENVIRON, V26, P1040, DOI 10.1177/1420326X16661866
   Bryman A., 2016, Qualitative Research, V6, P97, DOI [DOI 10.1177/1468794106058877, 10.1177/1468794106058877]
   Creswell JW., 2017, DESIGNING CONDUCTING
   Currie C., 2014, Health Behaviour in School-Aged Children (HBSC) Study Protocol: Background, Methodology, and Mandatory Items for the 2013/2014 Survey
   De Giuli V, 2012, BUILD ENVIRON, V56, P335, DOI 10.1016/j.buildenv.2012.03.024
   Deng ZP, 2024, INDOOR AIR, V2024, DOI 10.1155/2024/5584960
   Desideri U, 2012, APPL ENERG, V97, P384, DOI 10.1016/j.apenergy.2012.02.009
   Diaz-Lopez C, 2022, BUILD ENVIRON, V221, DOI 10.1016/j.buildenv.2022.109297
   Díaz-López C, 2022, J BUILD ENG, V45, DOI 10.1016/j.jobe.2021.103598
   Domínguez-Amarillo S, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12145772
   Fang L, 2004, INDOOR AIR, V14, P74, DOI 10.1111/j.1600-0668.2004.00276.x
   Fang YH, 2023, J BUILD ENG, V65, DOI 10.1016/j.jobe.2022.105430
   Gaitani N, 2015, ENRGY PROCED, V78, P3348, DOI 10.1016/j.egypro.2015.11.749
   Sánchez-Torija JG, 2022, INF CONSTR, V74, DOI 10.3989/ic.87607
   Gil-Baez M, 2019, ENERGY, V167, P144, DOI 10.1016/j.energy.2018.10.094
   Gil-Baez M, 2017, ENERGY, V137, P1186, DOI 10.1016/j.energy.2017.05.188
   Grassie D, 2022, BUILD CITIES, V3, P204, DOI 10.5334/bc.159
   Haselsteiner E., 2021, Rethinking Sustainability towards a Regenerative Economy, P169, DOI [10.1007/978-3-030-71819-09, DOI 10.1007/978-3-030-71819-09]
   Heracleous C, 2021, J BUILD ENG, V44, DOI 10.1016/j.jobe.2021.103358
   Heracleous C, 2018, ENERGY, V165, P1228, DOI 10.1016/j.energy.2018.10.051
   Honey-Roses J., 2023, Protegim Les Escoles: Avaluaciodels Entorns Pacificats del Programa Protegim Les Escoles 2021 de la Ciutat de Barcelona
   Jia LR, 2021, BUILDINGS-BASEL, V11, DOI 10.3390/buildings11120591
   Karjalainen S, 2012, INDOOR AIR, V22, P96, DOI 10.1111/j.1600-0668.2011.00747.x
   Lang XY, 2024, BUILD ENVIRON, V252, DOI 10.1016/j.buildenv.2024.111248
   Liu C, 2020, IOP C SER EARTH ENV, V531, DOI 10.1088/1755-1315/531/1/012034
   Mazon J, 2014, INT J BIOMETEOROL, V58, P717, DOI 10.1007/s00484-013-0652-0
   Moreno C., 2019, ADOLESCENCIA ESPANA
   Nico MA, 2015, APPL ERGON, V48, P111, DOI 10.1016/j.apergo.2014.11.013
   Nikolaou G.I., 2021, IOP Conf. Ser. Earth Environ. Sci., V899, DOI [10.1088/1755-1315/899/1/012036, DOI 10.1088/1755-1315/899/1/012036]
   Norbäck D, 2008, INT ARCH OCC ENV HEA, V82, P21, DOI 10.1007/s00420-008-0301-9
   Plazas FL, 2023, J CLEAN PROD, V432, DOI 10.1016/j.jclepro.2023.139588
   Rius A., 2022, 3cat
   Rivas I, 2014, ENVIRON INT, V69, P200, DOI 10.1016/j.envint.2014.04.009
   Roulet CA, 2006, BUILD RES INF, V34, P467, DOI 10.1080/09613210600822279
   Sadrizadeh S, 2022, J BUILD ENG, V57, DOI 10.1016/j.jobe.2022.104908
   Sanz-Mas M, 2024, J URBAN HEALTH, V101, P141, DOI 10.1007/s11524-023-00814-y
   Savelieva K, 2019, ENVIRON HEALTH-GLOB, V18, DOI 10.1186/s12940-019-0555-6
   School Vent Cool, Ventilation, cooling and strategies for high performance school renovations
   Seppänen O, 2002, INDOOR AIR, V12, P98, DOI 10.1034/j.1600-0668.2002.01111.x
   Strack Robert W, 2004, Health Promot Pract, V5, P49, DOI 10.1177/1524839903258015
   Torsheim T, 2016, CHILD INDIC RES, V9, P771, DOI 10.1007/s12187-015-9339-x
   Vilceková S, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-12147-z
   Wang C, 1997, HEALTH EDUC BEHAV, V24, P369, DOI 10.1177/109019819702400309
   Wang J, 2022, SCI TOTAL ENVIRON, V802, DOI 10.1016/j.scitotenv.2021.149804
   Wang Z, 2018, BUILD ENVIRON, V138, P181, DOI 10.1016/j.buildenv.2018.04.040
   Wargocki P, 2013, BUILD ENVIRON, V59, P581, DOI 10.1016/j.buildenv.2012.10.007
   Williams R, 2012, STATA J, V12, P308, DOI 10.1177/1536867X1201200209
   Zahiri S., 2016, Frontiers in built environment, V2, P3, DOI [10.3389/fbuil.2016.00003, DOI 10.3389/FBUIL.2016.00003]
   Zinzi M, 2021, ENERGIES, V14, DOI 10.3390/en14102799
   Zomorodian ZS, 2016, RENEW SUST ENERG REV, V59, P895, DOI 10.1016/j.rser.2016.01.033
NR 63
TC 0
Z9 0
U1 6
U2 6
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 1
PY 2024
VL 949
AR 175104
DI 10.1016/j.scitotenv.2024.175104
EA AUG 2024
PG 9
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA C2M0K
UT WOS:001287736600001
PM 39079644
OA hybrid
DA 2025-01-10
ER

PT J
AU Schröder, LS
   Bhalerao, AK
   Kabir, KH
   Scheffran, J
   Schneider, UA
AF Schroeder, Lea S.
   Bhalerao, Amol K.
   Kabir, Khondokar H.
   Scheffran, Juergen
   Schneider, Uwe A.
TI Managing uphill cultivation under climate change - An assessment of
   adaptation decisions among tribal farmers in Nagaland state of India
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Upland agriculture; Tribal farmers; Soil and water conservation;
   Adaptation decisions; Climate change; Northeast India
ID SMALLHOLDER FARMERS; ADAPTIVE CAPACITY; DETERMINANTS; PERCEPTIONS;
   AGRICULTURE; STRATEGIES; VULNERABILITY; VARIABILITY; AWARENESS; DISTRICT
AB Tribal farmers in the Himalayas are vulnerable to climatic changes, as their rain-fed cultivation systems, practiced on steep, sloping terrain, are susceptible to changes in rainfall while at the same time being the primary means of livelihood. Soil and water conservation practices (SWCP) can improve the resilience of these cultivation systems to adverse climatic conditions. However, little is known about adaptation within these tribal farming communities. This is the first empirical study on the adaptation decisions of tribal farmers in the Himalayan uplands of Northeast India. Starting from the analysis of future climate risks, we surveyed 372 tribal farmers in Nagaland state to analyze perceived climate and environmental changes in relation to socio-demographic factors. We estimate current adoption rates of SWCP together with farmers' goals and values and employ a binary logit model (BLM) to quantify the influence of diverse factors on adaptation decisions. Our results show that increases in temperatures and crop diseases were the most perceived changes by tribal farmers. Climate projections indicate that precipitation amount and intensity, along with temperatures, will increase towards the end of the century, underlining the importance of SWCP. However, all considered SWCP were employed by less than half of the tribal farmers. Adoption probabilities for all practices were significantly increased when farmers participated in agricultural training. After that, participation in a civil society organization, livestock ownership, high-altitude locations, and perceived increases in droughts were found to increase adoption probabilities significantly, while socio-demographic factors were of only minor importance. If the most effective factor was employed to all farmers, average adoption rates of SWCP could at least double. Adoption decisions were mainly motivated by improving livelihoods, sustaining natural resources, reducing workload, and preserving cultural aspects of cultivation. This research contributes to understanding adaptation decisions of tribal farmers and quantifies the untapped potential for climate change adaptation of marginalized and climate-vulnerable farming communities in mountain regions.
C1 [Schroeder, Lea S.; Kabir, Khondokar H.; Schneider, Uwe A.] Univ Hamburg, Ctr Earth Syst Res & Sustainabil CEN, Res Unit Sustainabil & Climate Risks, Grindelberg 5, D-20144 Hamburg, Germany.
   [Bhalerao, Amol K.] Indian Council Agr Res, Indian Vet Res Inst, Training & Educ Ctr, Pune 411005, Maharashtra, India.
   [Kabir, Khondokar H.] Univ Guelph, Sch Environm Design & Rural Dev, 50 Stone Rd East, Guelph, ON N1G 2W1, Canada.
   [Scheffran, Juergen] Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur, Grindelberg 5-7, D-20144 Hamburg, Germany.
   [Kabir, Khondokar H.] Bangladesh Agr Univ, Dept Agr Extens Educ, Mymensingh 2202, Bangladesh.
C3 University of Hamburg; Indian Council of Agricultural Research (ICAR);
   ICAR - Indian Veterinary Research Institute; University of Guelph;
   University of Hamburg; Bangladesh Agricultural University (BAU)
RP Schröder, LS (corresponding author), Univ Hamburg, Ctr Earth Syst Res & Sustainabil CEN, Res Unit Sustainabil & Climate Risks, Grindelberg 5, D-20144 Hamburg, Germany.
EM lea.sophia.schroeder@uni-hamburg.de
RI Scheffran, Jurgen/M-6876-2019; Kabir, Khondokar Humayun/W-9026-2018;
   Schneider, Uwe/M-7342-2016
OI Scheffran, Jurgen/0000-0002-7171-3062; Schroder, Lea
   Sophia/0000-0001-5891-7290; Kabir, Khondokar
   Humayun/0000-0001-9219-2529; Schneider, Uwe/0000-0002-6833-9292
FU Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
   [BGD-1214857-IKS]; Alexander von Humboldt Foundation;  [390683824]
FX This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German
   Research Foundation) under Germany's Excellence Strategy-EXC 2037 '
   CLICCS-Climate, Climatic Change, and Society'-Project Number: 390683824,
   contribution to the Center for Earth System Research and Sustainability
   (CEN) of Universitat Hamburg. We would like to thank the Alexander von
   Humboldt Foundation for financial contribution under grant
   BGD-1214857-IKS. We would also like to thank the local extension
   functionaries and farmers of Nagaland for their support during the data
   collection phase, and the anonymous reviewers for their comments and
   suggestions, which have considerably improved this work.
CR Abid M, 2015, EARTH SYST DYNAM, V6, P225, DOI 10.5194/esd-6-225-2015
   Abid M, 2016, SCI TOTAL ENVIRON, V547, P447, DOI 10.1016/j.scitotenv.2015.11.125
   Adeagbo OA, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e06231
   Adego T, 2022, CLIM DEV, V14, P487, DOI 10.1080/17565529.2021.1943296
   Adhikari S, 2022, ADV AGR, V2022, DOI 10.1155/2022/1556407
   Ahmed Z, 2021, LAND USE POLICY, V103, DOI 10.1016/j.landusepol.2021.105295
   Ali MF, 2021, ENVIRON SCI POLLUT R, V28, P14844, DOI 10.1007/s11356-020-11472-x
   Amir S, 2020, ARAB J GEOSCI, V13, DOI 10.1007/s12517-020-06019-w
   [Anonymous], 2015, Global Forest Resources Assessment 2015. How Are the World's Forests Changing?, V2nd
   [Anonymous], 2013, Shuttle Radar Topography Mission Global 1 arc second. In: Center, DOI DOI 10.5069/G9445JDFACCESSED:2021-03-12
   Asfaw A, 2019, ENVIRON DEV SUSTAIN, V21, P2535, DOI 10.1007/s10668-018-0150-y
   Bhalerao AK, 2022, INT J SUST DEV WORLD, V29, P291, DOI 10.1080/13504509.2021.1986750
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Datta P, 2022, ENVIRON MANAGE, V70, P911, DOI 10.1007/s00267-022-01724-6
   Datta P, 2022, GEOJOURNAL, V87, P3621, DOI 10.1007/s10708-021-10450-1
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Dhakal B., 2020, J. Climatol. Weather Forecast., V8
   Eshetu G, 2021, CLIM DEV, V13, P318, DOI 10.1080/17565529.2020.1772706
   Frieler K, 2017, GEOSCI MODEL DEV, V10, P4321, DOI 10.5194/gmd-10-4321-2017
   Ghosh-Jerath S, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.667297
   Government of India N.E.C.S., 2015, Basic Statistics of North Eastern Region 2015
   Government of Nagaland D.o.E.S., 2019, Statistical Handbook of Nagaland
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Hasan MK, 2020, CLIMATIC CHANGE, V161, P617, DOI 10.1007/s10584-020-02708-3
   Hasan MK, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135384
   Hasan MK, 2019, J ENVIRON MANAGE, V237, P54, DOI 10.1016/j.jenvman.2019.02.028
   Dang HL, 2019, CLIM DEV, V11, P765, DOI 10.1080/17565529.2018.1562866
   Dang HL, 2014, NAT HAZARDS, V71, P385, DOI 10.1007/s11069-013-0931-4
   Vo HH, 2021, ASIA-PAC J REG SCI, V5, P327, DOI 10.1007/s41685-020-00181-5
   ICIMOD, 2010, Synthesis Report of Climate Change Impact and Vulnerability in the Eastern Himalayas
   Jayahari K.M., 2015, Socio-Economic and Ecological Impact Study of Sustainable Land and Ecosystem Management in Shifting Cultivation Areas of Nagaland
   Jha CK, 2021, ENVIRON SUSTAIN IND, V10, DOI 10.1016/j.indic.2021.100112
   Jin JJ, 2016, NAT HAZARDS, V82, P1609, DOI 10.1007/s11069-016-2260-x
   Jin JJ, 2015, SCI TOTAL ENVIRON, V538, P942, DOI 10.1016/j.scitotenv.2015.07.027
   Kaye JP, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-016-0410-x
   Khan I, 2020, LAND USE POLICY, V91, DOI 10.1016/j.landusepol.2019.104395
   Khanal U, 2018, ECOL ECON, V144, P139, DOI 10.1016/j.ecolecon.2017.08.006
   Koç G, 2022, ENVIRON DEV SUSTAIN, V24, P9907, DOI 10.1007/s10668-021-01850-x
   Lange S, 2019, GEOSCI MODEL DEV, V12, P3055, DOI 10.5194/gmd-12-3055-2019
   Lange Stefan, 2019, GFZ
   Lange Stefan., 2021, Isimip3b bias adjustment fact sheet
   Lone FA, 2022, GEOJOURNAL, V87, P1743, DOI 10.1007/s10708-020-10330-0
   Marie M, 2020, HELIYON, V6, DOI 10.1016/j.heliyon.2020.e03867
   Menard S., 2002, APPL LOGISTIC REGRES, DOI DOI 10.4135/9781412983433
   Mwinkom FXK, 2021, SN APPL SCI, V3, DOI 10.1007/s42452-021-04503-w
   Ngangom B, 2020, INT SOIL WATER CONSE, V8, P308, DOI 10.1016/j.iswcr.2020.07.001
   Huong NTL, 2017, INT J CLIM CHANG STR, V9, P555, DOI [10.1108/IJCCSM-02-2017-0032, 10.1108/ijccsm-02-2017-0032]
   Pandey DK, 2020, FOREST POLICY ECON, V111, DOI 10.1016/j.forpol.2019.102046
   Panta B, 2020, SN APPL SCI, V2, DOI 10.1007/s42452-020-03747-2
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Rai CK, 2019, INDIAN J DAIRY SCI, V72, P668, DOI 10.33785/IJDS.2019.v72i06.013
   Ramos MC, 2006, J ENVIRON MANAGE, V78, P97, DOI 10.1016/j.jenvman.2005.04.010
   Rana RS, 2021, MT RES DEV, V41, pR50, DOI 10.1659/MRD-JOURNAL-D-20-00056.1
   Rogers R. W., 1983, Social psychophysiology: A source book, P153
   Rymbai D, 2018, INT J BIOMETEOROL, V62, P1833, DOI 10.1007/s00484-018-1586-3
   Schröder LS, 2024, LAND DEGRAD DEV, V35, P670, DOI 10.1002/ldr.4944
   Sertse SF, 2021, INT J DISAST RISK RE, V60, DOI 10.1016/j.ijdrr.2021.102255
   Sharma A, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-020-08512-x
   Sharma NK, 2017, AGR ECOSYST ENVIRON, V247, P43, DOI 10.1016/j.agee.2017.06.026
   Shrestha AB, 2017, INT J CLIMATOL, V37, P1066, DOI 10.1002/joc.4761
   Shukla G, 2016, ENVIRON DEV SUSTAIN, V18, P1167, DOI 10.1007/s10668-015-9694-2
   Singh RK, 2017, APPL GEOGR, V86, P41, DOI 10.1016/j.apgeog.2017.06.018
   Stern PC, 2000, J SOC ISSUES, V56, P407, DOI 10.1111/0022-4537.00175
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Thoai TQ, 2018, LAND USE POLICY, V70, P224, DOI 10.1016/j.landusepol.2017.10.023
   Truong DD, 2022, FRONT SUSTAIN FOOD S, V6, DOI 10.3389/fsufs.2022.790089
   van Vliet N, 2012, GLOBAL ENVIRON CHANG, V22, P418, DOI 10.1016/j.gloenvcha.2011.10.009
   Warner BP, 2016, AGR HUM VALUES, V33, P785, DOI 10.1007/s10460-015-9661-4
   Tran XM, 2017, AEBMR ADV ECON, V32, P351
   Zamasiya B, 2017, J ENVIRON MANAGE, V198, P233, DOI 10.1016/j.jenvman.2017.04.073
   Zobeidi T., 2022, Sci. Rep., V12
NR 72
TC 5
Z9 5
U1 20
U2 32
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD JAN 1
PY 2024
VL 349
AR 119473
DI 10.1016/j.jenvman.2023.119473
EA NOV 2023
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA Z0WB3
UT WOS:001109360400001
PM 37939473
OA hybrid
DA 2025-01-10
ER

PT J
AU Li, JB
   Zhai, ZH
   Ding, YF
   Li, HY
   Deng, Y
   Chen, SH
   Ye, LF
AF Li, Jiangbo
   Zhai, Zhihong
   Ding, Yunfei
   Li, Haiyan
   Deng, Yan
   Chen, Sihao
   Ye, Lifei
TI Effect of optimal allocation of urban trees on the outdoor thermal
   environment in hot and humid areas: A case study of a university campus
   in Guangzhou, China
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Urban microclimate; Urban greenery; Tree species; Spatial configuration
ID CLIMATE-CHANGE ADAPTATION; HEAT-ISLAND; ENVI-MET; MICROCLIMATE MODEL;
   ECOSYSTEM SERVICES; COMFORT; ENERGY; AIR; TEMPERATURE; SURFACE
AB The process of urbanization in developing countries has had an ecological impact, destroying the outdoor thermal environment, especially in hot and humid areas where high summer temperatures are a nuisance for human outdoor activities. The role of urban greening in improving the regional microclimate has been confirmed by many studies. To improve the outdoor thermal environment, taking a university campus in Guangzhou as an example, the tree species and tree geometric parameters were analyzed, the ENVI-met model was established, and a simulation platform was calibrated based on the measured data, which improved the accuracy of the simulation platform. In this simulation platform, the maximum root mean square errors of air temperature and humidity were as low as 1.49 degrees C and 5.63 %, respectively. To reveal the influence of the physical morphology of tree species and their community characteristics on the outdoor thermal environment, six typical greening tree species and 37 green space configurations were established, and the influence of each tree species and their spatial configurations on the cooling effect of the outdoor environment was simulated. The results showed that the leaf area index, crown width, and tree height had a great influence on the ground temperature and sensible heat flux under the tree canopy, and the cooling effect of the tree group was improved when the height of the trees exceeded 10 m, with an ideal canopy coverage of 30 %. Optimizing the green space configuration reduced the temperature at pedestrian height (1.5 m) in the study area by up to 1.5 degrees C, and a reduction of 0.5 degrees C was observed over approximately 50 % of the green area during the peak summer temperatures (14:00-16:00), mitigating the microclimate heat environment. This study can enable urban planners to determine the type, quantity, and spatial allocation of green vegetation to improve the urban thermal environment.
C1 [Li, Jiangbo; Ding, Yunfei; Deng, Yan; Ye, Lifei] Guangzhou Univ, Sch Civil Engn, Guangzhou 510006, Peoples R China.
   [Zhai, Zhihong; Li, Haiyan] Guangzhou Climate & Agrometeorol Ctr, Guangzhou 511430, Peoples R China.
   [Chen, Sihao] Guangdong Ocean Univ, Coll Ocean Engn & Energy, Zhanjiang 524088, Peoples R China.
C3 Guangzhou University; Guangdong Ocean University
RP Ding, YF (corresponding author), Guangzhou Univ, Sch Civil Engn, Guangzhou 510006, Peoples R China.
EM dingyf@126.com
RI deng, yan/KCK-8563-2024; Li, Haiyan/AAP-9200-2021; Ye,
   Lifei/LUZ-3553-2024
OI Ye, lifei/0000-0001-5947-4815; yunfei, Ding/0000-0002-1848-0845
FU Guangzhou Science and technology Program key project [202206010132]
FX The work was financially supported by Guangzhou Science and technology
   Program key project (No.202206010132) .
CR Akbari H, 2002, ENVIRON POLLUT, V116, pS119, DOI 10.1016/S0269-7491(01)00264-0
   Akbari H, 2016, J CIV ENG MANAG, V22, P1, DOI 10.3846/13923730.2015.1111934
   Akbari H, 2009, CLIMATIC CHANGE, V94, P275, DOI 10.1007/s10584-008-9515-9
   Armson D, 2012, URBAN FOR URBAN GREE, V11, P245, DOI 10.1016/j.ufug.2012.05.002
   Ballinas M, 2016, URBAN FOR URBAN GREE, V20, P152, DOI 10.1016/j.ufug.2016.08.004
   Barrass T.R., 1974, Phys. Bull., DOI [10.1088/0031-9112/25/2/025, DOI 10.1088/0031-9112/25/2/025]
   Bruse M, 1998, ENVIRON MODELL SOFTW, V13, P373, DOI 10.1016/S1364-8152(98)00042-5
   Brysse K, 2013, GLOBAL ENVIRON CHANG, V23, P327, DOI 10.1016/j.gloenvcha.2012.10.008
   Ca VT, 1998, ENERG BUILDINGS, V29, P83, DOI 10.1016/S0378-7788(98)00032-2
   Chow WTL, 2011, THEOR APPL CLIMATOL, V103, P197, DOI 10.1007/s00704-010-0293-8
   Dan M.K., 1994, Energy Environ. Div., DOI [10.2172/10180633, DOI 10.2172/10180633]
   Dimoudi A, 2003, ENERG BUILDINGS, V35, P69, DOI 10.1016/S0378-7788(02)00081-6
   Fahmy M, 2010, BUILD ENVIRON, V45, P345, DOI 10.1016/j.buildenv.2009.06.014
   Gatto E, 2020, FORESTS, V11, DOI 10.3390/f11020228
   Ge JJ, 2023, BUILD ENVIRON, V232, DOI 10.1016/j.buildenv.2023.110054
   Hsieh CM, 2018, ENERG BUILDINGS, V159, P382, DOI 10.1016/j.enbuild.2017.10.045
   Jiang YF, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph182111404
   Kim H, 2019, LAND USE POLICY, V86, P328, DOI 10.1016/j.landusepol.2019.05.016
   Lafortezza R, 2009, URBAN FOR URBAN GREE, V8, P97, DOI 10.1016/j.ufug.2009.02.003
   Lalic B, 2004, J APPL METEOROL, V43, P641, DOI 10.1175/1520-0450(2004)043<0641:AERDLD>2.0.CO;2
   Le Tran Y, 2017, URBAN FOR URBAN GREE, V22, P84, DOI 10.1016/j.ufug.2017.02.003
   Li JF, 2021, BUILD ENVIRON, V199, DOI 10.1016/j.buildenv.2021.107935
   Liu ZX, 2020, URBAN FOR URBAN GREE, V50, DOI 10.1016/j.ufug.2020.126646
   Luo YW, 2021, J BUILD ENG, V43, DOI 10.1016/j.jobe.2021.102473
   McPherson E. G., 1997, Urban Ecosystems, V1, P49, DOI 10.1023/A:1014350822458
   Meng WG, 2011, J TROP METEOROL, V17, P257, DOI 10.3969/j.issn.1006-8775.2011.03.007
   Monteith L., 1974, Physics Today, DOI DOI 10.1063/1.3128494
   Morakinyo TE, 2018, BUILD ENVIRON, V137, P157, DOI 10.1016/j.buildenv.2018.04.012
   Morakinyo TE, 2017, BUILD ENVIRON, V115, P1, DOI 10.1016/j.buildenv.2017.01.005
   Morakinyo TE, 2016, BUILD ENVIRON, V103, P262, DOI 10.1016/j.buildenv.2016.04.025
   Moser A, 2015, URBAN FOR URBAN GREE, V14, P1110, DOI 10.1016/j.ufug.2015.10.005
   Müller N, 2014, THEOR APPL CLIMATOL, V115, P243, DOI 10.1007/s00704-013-0890-4
   Ng E, 2012, BUILD ENVIRON, V47, P256, DOI 10.1016/j.buildenv.2011.07.014
   O'Malley C, 2015, SUSTAIN CITIES SOC, V19, P222, DOI 10.1016/j.scs.2015.05.009
   Ohashi Y, 2007, J APPL METEOROL CLIM, V46, P66, DOI 10.1175/JAM2441.1
   OKE TR, 1989, PHILOS T ROY SOC B, V324, P335, DOI 10.1098/rstb.1989.0051
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Rui LY, 2019, BUILD SIMUL-CHINA, V12, P183, DOI 10.1007/s12273-018-0498-9
   Sailor DJ, 2008, ENERG BUILDINGS, V40, P1246, DOI 10.1016/j.enbuild.2007.11.004
   Salata F, 2017, SUSTAIN CITIES SOC, V30, P79, DOI 10.1016/j.scs.2017.01.006
   Shashua-Bar L, 2011, INT J CLIMATOL, V31, P1498, DOI 10.1002/joc.2177
   Simon H, 2018, LANDSCAPE URBAN PLAN, V174, P33, DOI 10.1016/j.landurbplan.2018.03.003
   Skelhorn C, 2014, LANDSCAPE URBAN PLAN, V121, P129, DOI 10.1016/j.landurbplan.2013.09.012
   Stone B, 2013, ENVIRON SCI TECHNOL, V47, P7780, DOI 10.1021/es304352e
   Strohbach MW, 2013, LANDSCAPE URBAN PLAN, V114, P69, DOI 10.1016/j.landurbplan.2013.02.007
   Tam BY, 2015, URBAN CLIM, V12, P1, DOI 10.1016/j.uclim.2014.12.004
   Tan Z, 2017, BUILD ENVIRON, V120, P93, DOI 10.1016/j.buildenv.2017.05.017
   Thorsson S, 2007, INT J CLIMATOL, V27, P1983, DOI 10.1002/joc.1537
   Tsoka S, 2018, SUSTAIN CITIES SOC, V43, P55, DOI 10.1016/j.scs.2018.08.009
   Wang D, 2019, SCI TOTAL ENVIRON, V690, P923, DOI 10.1016/j.scitotenv.2019.07.039
   [汪军能 Wang Junneng], 2022, [气候变化研究进展, Progressus Inquisitiones de Mutatione Climatis], V18, P433
   Wang WJ, 2018, IOP CONF SER-MAT SCI, V324, DOI 10.1088/1757-899X/324/1/012049
   Wang YF, 2014, BUILD ENVIRON, V77, P88, DOI 10.1016/j.buildenv.2014.03.021
   Yang XS, 2013, BUILD ENVIRON, V60, P93, DOI 10.1016/j.buildenv.2012.11.008
   Yang YJ, 2018, SUSTAIN CITIES SOC, V37, P563, DOI 10.1016/j.scs.2017.09.033
   Zhang L, 2018, BUILD ENVIRON, V130, P27, DOI 10.1016/j.buildenv.2017.12.014
   Zhang TL, 2022, ENERG BUILDINGS, V273, DOI 10.1016/j.enbuild.2022.112359
   Zhang TL, 2022, BUILD SIMUL-CHINA, V15, P1367, DOI 10.1007/s12273-021-0829-0
   Zinzi M, 2012, ENERG BUILDINGS, V55, P66, DOI 10.1016/j.enbuild.2011.09.024
NR 59
TC 8
Z9 8
U1 22
U2 88
PU ELSEVIER SCIENCE SA
PI LAUSANNE
PA PO BOX 564, 1001 LAUSANNE, SWITZERLAND
SN 0378-7788
EI 1872-6178
J9 ENERG BUILDINGS
JI Energy Build.
PD DEC 1
PY 2023
VL 300
AR 113640
DI 10.1016/j.enbuild.2023.113640
EA OCT 2023
PG 17
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA W9OS0
UT WOS:001094855500001
DA 2025-01-10
ER

PT J
AU Meza, F
   Darbyshire, R
   Farrell, A
   Lakso, A
   Lawson, J
   Meinke, H
   Nelson, G
   Stockle, C
AF Meza, Francisco
   Darbyshire, Rebecca
   Farrell, Aidan
   Lakso, Alan
   Lawson, James
   Meinke, Holger
   Nelson, Gerald
   Stockle, Claudio
TI Assessing temperature-based adaptation limits to climate change of
   temperate perennial fruit crops
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE chilling requirements; climate change adaptation; growing degree days;
   limits to adaptation; temperate Fruit trees
ID HEAT REQUIREMENTS; SPRING PHENOLOGY; CARBON BALANCE; CHANGE IMPACTS;
   WINTER CHILL; FLOWER BUDS; APPLE; ALMOND; GROWTH; TREES
AB Temperate perennial fruit and nut trees play varying roles in world food diversity-providing edible oils and micronutrient, energy, and protein dense foods. In addition, perennials reuse significant amounts of biomass each year providing a unique resilience. But they also have a unique sensitivity to seasonal temperatures, requiring a period of dormancy for successful growing season production. This paper takes a global view of five temperate tree fruit crops-apples, cherries, almonds, olives, and grapes-and assesses the effects of future temperature changes on thermal suitability. It uses climate data from five earth system models for two CMIP6 climate scenarios and temperature-related indices of stress to indicate potential future areas where crops cannot be grown and highlight potential new suitable regions. The loss of currently suitable areas and new additions in new locations varies by scenario. In the southern hemisphere (SH), end-century (2081-2100) suitable areas under the SSP 5-8.5 scenario decline by more than 40% compared to a recent historical period (1991-2010). In the northern hemisphere (NH) suitability increases by 20% to almost 60%. With SSP1-2.6, however, the changes are much smaller with SH area declining by about 25% and NH increasing by about 10%. The results suggest substantial restructuring of global production for these crops. Essentially, climate change shifts temperature-suitable locations toward higher latitudes. In the SH, most of the historically suitable areas were already at the southern end of the landmass limiting opportunities for adaptation. If breeding efforts can bring chilling requirements for the major cultivars closer to that currently seen in some cultivars, suitable areas at the end of the century are greater, but higher summer temperatures offset the extent. The high value of fruit crops provides adaptation opportunities such as cultivar selection, canopy cooling using sprinklers, shade netting, and precision irrigation.
C1 [Meza, Francisco] Pontificia Univ Catolica Chile, Ctr Interdisciplinario Cambio Global, Santiago, Chile.
   [Darbyshire, Rebecca] CSIRO Agr & Food, Canberra, ACT, Australia.
   [Farrell, Aidan] Dept Life Sci, St Augustine, Trinidad Tobago.
   [Lakso, Alan] Cornell Univ, Sch Integrat Plant Sci, Geneva, NY USA.
   [Lawson, James] Cent Coast Primary Ind Ctr, New South Wales Dept Primary Ind, Ourimbah, NSW, Australia.
   [Meinke, Holger] Univ Tasmania, Hobart, Tas, Australia.
   [Nelson, Gerald] Univ Illinois, Champaign, IL USA.
   [Stockle, Claudio] Washington State Univ, Dept Biol Syst Engn, Pullman, WA USA.
C3 Pontificia Universidad Catolica de Chile; Commonwealth Scientific &
   Industrial Research Organisation (CSIRO); Agriculture & Food; Cornell
   University; Department of Primary Industries & Regional Development NSW;
   University of Tasmania; University of Illinois System; University of
   Illinois Urbana-Champaign; Washington State University
RP Meza, F (corresponding author), Pontificia Univ Catolica Chile, Ctr Interdisciplinario Cambio Global, Santiago, Chile.
EM fmeza@uc.cl
RI Nelson, Gerald/L-5903-2019; Darbyshire, Rebecca/AAI-3945-2021; Meinke,
   Holger/C-7215-2013
OI Nelson, Gerald/0000-0003-3626-1221; Darbyshire,
   Rebecca/0000-0003-4712-8514; Lawson, James/0000-0001-7983-4443; Meinke,
   Holger/0000-0003-2657-3264
FU FONDECYT [1210526]
FX This work has been carried out with partial support from FONDECYT Grant
   1210526 to Francisco Meza.
CR Alae-Carew C, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab5cc0
   Almond Board of Australia, 2008, ALL ALM FACT SHEET 0
   Alonso JM, 2005, J AM SOC HORTIC SCI, V130, P308, DOI 10.21273/JASHS.130.3.308
   Araújo M, 2019, PLANTA, V249, P1583, DOI 10.1007/s00425-019-03109-2
   Arquero Octavio., 2013, Manual Del Almendro, V1st
   Atkinson CJ, 2013, ENVIRON EXP BOT, V91, P48, DOI 10.1016/j.envexpbot.2013.02.004
   Badescu A., 2017, Acta Horticulturae, P299
   Bartomeus I, 2013, ECOL LETT, V16, P1331, DOI 10.1111/ele.12170
   Benmoussa H, 2017, AGR FOREST METEOROL, V239, P34, DOI 10.1016/j.agrformet.2017.02.030
   Beppu K, 2001, SCI HORTIC-AMSTERDAM, V87, P77, DOI 10.1016/S0304-4238(00)00173-4
   Bonada M, 2015, AUST J GRAPE WINE R, V21, P240, DOI 10.1111/ajgw.12142
   Campoy JA, 2019, INT J BIOMETEOROL, V63, P183, DOI 10.1007/s00484-018-1649-5
   Caprio JM, 2006, CAN J PLANT SCI, V86, P259, DOI 10.4141/P05-032
   Chmielewski FM, 2018, INT J BIOMETEOROL, V62, P217, DOI 10.1007/s00484-017-1443-9
   Cogato A, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11101940
   CRASSWELLER RM, 1981, J AM SOC HORTIC SCI, V106, P53
   Darbyshire R, 2011, AGR FOREST METEOROL, V151, P1074, DOI 10.1016/j.agrformet.2011.03.010
   De Melo-Abreu JP, 2004, AGR FOREST METEOROL, V125, P117, DOI 10.1016/j.agrformet.2004.02.009
   Decourtye A, 2019, CURR OPIN INSECT SCI, V35, P123, DOI 10.1016/j.cois.2019.07.008
   El Yaacoubi A, 2016, INT J BIOMETEOROL, V60, P1695, DOI 10.1007/s00484-016-1160-9
   EREZ A, 1990, ACTA HORTIC, V276, P165, DOI 10.17660/ActaHortic.1990.276.18
   Erez A, 2000, TEMPERATE FRUIT CROPS IN WARM CLIMATES, P17
   Evans KJ, 2020, PLANT DIS, V104, P3097, DOI 10.1094/PDIS-04-20-0812-FE
   Feng Y, 2018, SCI HORTIC-AMSTERDAM, V238, P318, DOI 10.1016/j.scienta.2018.05.002
   Ferrise R., 2013, Regional Assessment of Climate Change in the Mediterranean: Volume 2: Agriculture, Forests and Ecosystem Services and People,, P49
   FISHMAN S, 1987, J THEOR BIOL, V124, P473, DOI 10.1016/S0022-5193(87)80221-7
   Flore J.A., 2018, HDB ENV PHYSL FRUIT, P233
   Franke JA, 2022, GLOBAL CHANGE BIOL, V28, P167, DOI 10.1111/gcb.15868
   Gabaldón-Leal C, 2017, INT J CLIMATOL, V37, P940, DOI 10.1002/joc.5048
   Glenn DM, 2013, HORTICUL RE, V41, P47, DOI 10.1002/9781118707418.ch02
   GOODE JE, 1979, J HORTIC SCI BIOTECH, V54, P1
   Greer DH, 2010, FUNCT PLANT BIOL, V37, P206, DOI 10.1071/FP09209
   Gutiérrez-Gamboa G, 2021, J SCI FOOD AGR, V101, P1261, DOI 10.1002/jsfa.10813
   Hasegawa T, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01150-7
   Houston L, 2018, CLIMATIC CHANGE, V146, P159, DOI 10.1007/s10584-017-1951-y
   Jackson J.E., 1983, Acta Hort, V139, P75, DOI DOI 10.17660/ACTAHORTIC.1983.139.10
   Kuden A. B., 2020, Acta Horticulturae, P145, DOI 10.17660/ActaHortic.2020.1280.20
   Lakso AN, 2017, BURL DODDS AGR SCI, V18, P103, DOI 10.19103/AS.2016.0017.05
   Lakso AN, 2015, ACTA HORTIC, V1068, P235, DOI 10.17660/ActaHortic.2015.1068.29
   Lakso AN, 2011, ACTA HORTIC, V903, P733
   Lakso A. N., 1987, Agrometeorology. 2nd International Cesena Agricultura Conference, Cesena, 8-9 October 1987., P287
   Lakso A.N., 1994, Handbook of environmental physiology of fruit crops Volume I, VI, P3
   Luedeling E, 2012, SCI HORTIC-AMSTERDAM, V144, P218, DOI 10.1016/j.scienta.2012.07.011
   Luedeling E, 2011, INT J BIOMETEOROL, V55, P411, DOI 10.1007/s00484-010-0352-y
   Luedeling E, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0006166
   Markou M, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11050483
   Martínez-Lüscher J, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.579192
   Measham PF, 2017, SCI HORTIC-AMSTERDAM, V216, P134, DOI 10.1016/j.scienta.2017.01.006
   Miserere A, 2018, ACTA HORTIC, V1199, P523, DOI 10.17660/ActaHortic.2018.1199.83
   Monteverde C, 2020, ADV CLIM CHANG RES, V11, P279, DOI 10.1016/j.accre.2020.08.002
   Morales A, 2016, EUR J AGRON, V74, P93, DOI 10.1016/j.eja.2015.12.006
   Mupambi G, 2018, SCI HORTIC-AMSTERDAM, V236, P60, DOI 10.1016/j.scienta.2018.03.014
   Neilsen D, 2017, ACTA HORTIC, V1160, P207, DOI [10.17660/actahortic.2017.1160.30, 10.17660/ActaHortic.2017.1160.30]
   Nissim Y, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0231956
   Orlandi F, 2014, THEOR APPL CLIMATOL, V115, P207, DOI 10.1007/s00704-013-0892-2
   Oukabli A, 2003, J HORTIC SCI BIOTECH, V78, P580, DOI 10.1080/14620316.2003.11511667
   Palmer John W., 2003, P217, DOI 10.1079/9780851995922.0217
   Parker LE, 2017, INT J BIOMETEOROL, V61, P1593, DOI 10.1007/s00484-017-1338-9
   Pfleiderer P, 2019, CLIMATIC CHANGE, V157, P515, DOI 10.1007/s10584-019-02570-y
   Pope KS, 2014, AGR FOREST METEOROL, V198, P15, DOI 10.1016/j.agrformet.2014.07.009
   Pope KS, 2013, GLOBAL CHANGE BIOL, V19, P1518, DOI 10.1111/gcb.12130
   Prudencio AS, 2018, SCI HORTIC-AMSTERDAM, V235, P39, DOI 10.1016/j.scienta.2018.02.073
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Racsko J, 2012, CRIT REV PLANT SCI, V31, P455, DOI 10.1080/07352689.2012.696453
   RAMANKUTTY N, 2008, GLOBAL BIOGEOCHEM CY, V0022
   Ramirez L., 2010, Acta Horticulturae, P107
   Ramrez F., 2015, Responses of Fruit Trees to Global Climate Change, P3, DOI [10.1007/978-3-319-14200-5, DOI 10.1007/978-3-319-14200-5]
   Reginato G, 2019, EUR J HORTIC SCI, V84, P124, DOI 10.17660/eJHS.2019/84.3.2
   Rodrigo J, 2000, SCI HORTIC-AMSTERDAM, V85, P155, DOI 10.1016/S0304-4238(99)00150-8
   Rosati A, 2007, ANN BOT-LONDON, V99, P255, DOI 10.1093/aob/mcl252
   Rowland L. J., 2011, GENETICS GENOMICS BR, P232
   Sahu N, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0235041
   Saure M. C., 1985, Horticultural Reviews, V7, P239, DOI 10.1002/9781118060735.ch6
   Schrader L, 2003, ACTA HORTIC, P397, DOI 10.17660/ActaHortic.2003.618.47
   Slavin JL, 2012, ADV NUTR, V3, P506, DOI 10.3945/an.112.002154
   Sorkheh K, 2018, SCI HORTIC-AMSTERDAM, V227, P162, DOI 10.1016/j.scienta.2017.09.037
   Thomas D S., 2012, Understanding and managing the risks and opportunities from climate change on Cherry production
   Valverde P, 2015, AGR WATER MANAGE, V152, P17, DOI 10.1016/j.agwat.2014.12.012
   van Leeuwen C, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9090514
   van Leeuwen C, 2016, J WINE ECON, V11, P150, DOI 10.1017/jwe.2015.21
   Voller C. F. P., 1986, Deciduous Fruit Grower, V36, P302
   Westwood M. N., 1993, Temperate-zone pomology: physiology and culture.
   White JW, 2011, FIELD CROP RES, V124, P357, DOI 10.1016/j.fcr.2011.07.001
   Wolfe DW, 2008, MITIG ADAPT STRAT GL, V13, P555, DOI 10.1007/s11027-007-9125-2
   Zabel F, 2021, GLOBAL CHANGE BIOL, V27, P3870, DOI 10.1111/gcb.15649
NR 85
TC 7
Z9 7
U1 13
U2 73
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD MAY
PY 2023
VL 29
IS 9
BP 2557
EP 2571
DI 10.1111/gcb.16601
EA FEB 2023
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA C1KV0
UT WOS:000939101800001
PM 36652298
DA 2025-01-10
ER

PT J
AU Rahut, DB
   Aryal, JP
   Marenya, P
AF Rahut, Dil Bahadur
   Aryal, Jeetendra Prakash
   Marenya, Paswel
TI Understanding climate-risk coping strategies among farm households:
   Evidence from five countries in Eastern and Southern Africa
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate shock; Farm household; Ex-post risk coping; Sub-Saharan Africa
ID SUB-SAHARAN AFRICA; CHANGE ADAPTATION; CONSERVATION AGRICULTURE; SMART
   AGRICULTURE; FOOD SECURITY; POVERTY; VULNERABILITY; VARIABILITY;
   ETHIOPIA; ADOPTION
AB Climate change is having a catastrophic impact on the livelihoods of farm households in Eastern and Southern Africa (ESA). This study employs comprehensive data obtained in 2018 from 4351 farm households in five countries to appraise the key climate hazards experienced by farmers, the risk coping methods adopted, and factor influencing the use of these methods. Although droughts, floods, hailstorms, and crop pests/diseases are major climate-induced risks in ESA. droughts are predominant in all these countries. Farm households in ESA have adopted various strategies to address climate risk, which includes changing farming practices, reducing consumption, using savings and borrowing, and seeking new employment. Farming families headed by a female, married, or an elderly member opt to change farming methods and decrease consumption, whereas they are less inclined to look for alternate livelihood options. Farming families with higher livestock endowments commonly use savings or borrow and are unlikely to change farming methods, decrease consumption, and search for alternate employment. Better-off families tend to change farming methods but are unlikely to adopt other risk coping options. Farming families with non-farm livelihood options are unlikely to change farming methods, use savings/borrowings, or decrease consumption, whereas they tend to search for alternate employment.Training on agriculture and economic status are crucial for climate change adaptation in these regions. Findings exhibit substantial differences among the study countries regarding the adoption of coping strategies. Compared to farmers in Kenya, farmers in other countries change agricultural methods to cope with climate shocks. Ethiopian farmers, compared to their Kenyan counterparts, decrease consumption to deal with climate risks, whereas, farmers in Tanzania, Malawi, and Mozambique are less likely to use this option. Similarly, the likelihood of seeking alternative employment as a risk coping strategy is lower among Ethiopian farmers, while it is higher among the farmers in other countries. (C) 2021 Elsevier B.V. All rights reserved.
C1 [Rahut, Dil Bahadur] Asian Dev Bank Inst ADBI, Tokyo, Japan.
   [Rahut, Dil Bahadur; Aryal, Jeetendra Prakash] Int Maize & Wheat Improvement Ctr CIMMYT, Texcoco, Mexico.
   [Marenya, Paswel] Int Maize & Wheat Improvement Ctr CIMMYT, Nairobi, Kenya.
C3 CGIAR; International Maize & Wheat Improvement Center (CIMMYT); CGIAR;
   International Maize & Wheat Improvement Center (CIMMYT)
RP Rahut, DB (corresponding author), Kasumigaseki Bldg,Level 8, Chiyoda City, Tokyo 1006008, Japan.
EM drahut@adbi.org; jeetenaryal@gmail.com; p.marenya@cgiar.org
RI Rahut, Dil Bahadur/AAD-8370-2022; Rahut, Dil Bahadur/AES-0258-2022
OI Marenya, Paswel/0000-0003-2496-2303; Aryal,
   Jeetendra/0000-0002-9128-5739; Rahut, Dil Bahadur/0000-0002-7505-5271
CR Abegunde VO, 2019, CLIMATE, V7, DOI 10.3390/cli7110132
   Abid M, 2020, CLIM RISK MANAG, V27, DOI 10.1016/j.crm.2019.100200
   Abraham T, 2018, FINANC INNOV, V4, DOI 10.1186/s40854-018-0094-0
   Adam HN, 2015, CLIM DEV, V7, P142, DOI 10.1080/17565529.2014.934772
   Adenle AA, 2017, ECOL ECON, V141, P190, DOI 10.1016/j.ecolecon.2017.06.004
   Adhikari U, 2015, FOOD ENERGY SECUR, V4, P110, DOI 10.1002/fes3.61
   Ahmed SA, 2011, GLOBAL ENVIRON CHANG, V21, P46, DOI 10.1016/j.gloenvcha.2010.10.003
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Ali MP, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0091678
   Amare A., 2017, Agric. Food Secur, V6, P64, DOI DOI 10.1186/S40066-017-0144-2
   Amare A, 2018, ECOL PROCESS, V7, DOI 10.1186/s13717-018-0124-x
   Ampaire EL, 2020, CLIMATIC CHANGE, V158, P43, DOI 10.1007/s10584-019-02447-0
   Anande Doreen M., 2019, Atmospheric and Climate Sciences, V9, P421, DOI 10.4236/acs.2019.93029
   Andersson JA, 2014, AGR ECOSYST ENVIRON, V187, P116, DOI 10.1016/j.agee.2013.08.008
   [Anonymous], 2010, Hydro-economic modeling of climate change impacts in Ethiopia
   [Anonymous], 2013, Q B DROUGHT TOLERANT
   [Anonymous], 2018, Mozambique Country Climate Risk Assessment Report. p, P44
   Appiah DO, 2020, GEOJOURNAL, V85, P579, DOI 10.1007/s10708-019-09976-2
   Aragon M., 1998, MED GLOBAL SURVIVAL, V5, P42
   Arndt C, 2014, J AFR ECON, V23, P83, DOI 10.1093/jae/eju013
   Artur L, 2012, GLOBAL ENVIRON CHANG, V22, P529, DOI 10.1016/j.gloenvcha.2011.11.013
   Aryal JP, 2020, REV DEV ECON, V24, P973, DOI 10.1111/rode.12670
   Aryal JP, 2020, ENVIRON MANAGE, V66, P105, DOI 10.1007/s00267-020-01291-8
   Aryal JP, 2020, INT J INNOV SUSTAIN, V14, P219, DOI 10.1504/IJISD.2020.106243
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P3267, DOI 10.1007/s10668-019-00345-0
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P5045, DOI 10.1007/s10668-019-00414-4
   Aryal JP, 2018, NAT RESOUR FORUM, V42, P141, DOI 10.1111/1477-8947.12152
   Asseng S, 2015, NAT CLIM CHANGE, V5, P143, DOI [10.1038/nclimate2470, 10.1038/NCLIMATE2470]
   Baez Javier E., 2020, Economics of Disasters and Climate Change, V4, P103, DOI 10.1007/s41885-019-00049-9
   Barros V.R., CLIMATE CHANGE 2014, P688
   Beegle K., 2019, ACCELERATING POVERTY
   Belcore E, 2020, GEOGR J, V186, P156, DOI 10.1111/geoj.12321
   Benson C., DROUGHT SUBSAHARAN A
   Bewket W., 2015, AGR ADAPTATION I RES
   Bowen A, 2012, CLIMATIC CHANGE, V113, P95, DOI 10.1007/s10584-011-0346-8
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Burn DH, 2008, J HYDROL, V352, P225, DOI 10.1016/j.jhydrol.2008.01.019
   Buvinic M, 1997, ECON DEV CULT CHANGE, V45, P259, DOI 10.1086/452273
   Carabine E., 2014, INTERGOVERNMENTAL PA
   Carnes BA, 2014, J GERONTOL A-BIOL, V69, P1087, DOI 10.1093/gerona/glt159
   Carter TR, 2016, REG ENVIRON CHANGE, V16, P43, DOI 10.1007/s10113-014-0688-7
   Changa L. B., 2017, Spatial and Temporal Analysis of Rainfall and Temperature Extreme Indices in Tanzania
   Cholo TC, 2020, CLIM DEV, V12, P323, DOI 10.1080/17565529.2019.1618234
   Connolly-Boutin L, 2016, REG ENVIRON CHANGE, V16, P385, DOI 10.1007/s10113-015-0761-x
   Conway D, 2011, GLOBAL ENVIRON CHANG, V21, P227, DOI 10.1016/j.gloenvcha.2010.07.013
   Davis-Reddy C L., 2017, Climate risk and vulnerability: A handbook for Southern Africa, V2nd
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Deressa TT, 2011, J AGR SCI-CAMBRIDGE, V149, P23, DOI 10.1017/S0021859610000687
   Deutsch CA, 2018, SCIENCE, V361, P916, DOI 10.1126/science.aat3466
   Di Falco S, 2013, LAND ECON, V89, P743, DOI 10.3368/le.89.4.743
   Earth Institute, KEN NAT DIS PROF
   England MI, 2018, REG ENVIRON CHANGE, V18, P2059, DOI 10.1007/s10113-018-1283-0
   Ensor J, 2015, WIRES CLIM CHANGE, V6, P509, DOI 10.1002/wcc.348
   Faiyetole AA, 2017, INT J CLIM CHANG STR, V9, P730, DOI 10.1108/IJCCSM-02-2017-0033
   Field C.B, 2014, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI DOI 10.1017/CBO9781107415379
   Fischer HW, 2020, CLIM DEV, V12, P689, DOI 10.1080/17565529.2019.1676690
   Fjelde H, 2012, POLIT GEOGR, V31, P444, DOI 10.1016/j.polgeo.2012.08.004
   Ford JD, 2015, REG ENVIRON CHANGE, V15, P801, DOI 10.1007/s10113-014-0648-2
   Gachene CKK, 2015, Sustainable Intensification to Advance Food Security and Enhance Climate Resilience in Africa, P165, DOI [DOI 10.1007/978-3-319-09360-4_8, 10.1007/978-3-319-09360-4_8]
   Gebrehiwot T, 2013, J EAST AFR STUD, V7, P607, DOI 10.1080/17531055.2013.817162
   Golrokhian A., 2016, World Dev Perspect, V1, P53, DOI DOI 10.1016/J.WDP.2016.05.005
   Government of Malawi, 2015, FLOODS POSTDISASTER
   Government of Malawi, MAL DROUGHT POSTD NE
   Graham C, 2020, GEOFORUM, V117, P300, DOI 10.1016/j.geoforum.2020.07.004
   Greene W. H., 2003, Econometric Analysis
   Gulland A., 2019, The Telegraph
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Hallegatte S, 2018, ENVIRON DEV ECON, V23, P217, DOI 10.1017/S1355770X18000141
   Harper S, 2019, J POPUL AGEING, V12, P401, DOI 10.1007/s12062-019-09255-5
   Headache classification Committee of the International Headache Society (IHS), 2018, Cephalalgia, V38, P1, DOI [10.1177/0333102417738202, DOI 10.1177/0333102417738202, DOI 10.2833/9937]
   Hertel TW, 2010, APPL ECON PERSPECT P, V32, P355, DOI 10.1093/aepp/ppq016
   JERNECK A, 2018, CLIMATE CHANGE 2014, V13, P403
   KANGALAWE RY, 2017, SUSTAIN SCI, V9, P202
   KATENGEZA SP, 2019, CLIM DEV, V156, P134
   KIJAZI AL, 2009, ECOL ECON, V38, P209
   KIJAZI AL, 2009, CLIM RES, V29, P955
   Lobell DB, 2007, ENVIRON RES LETT, V2, DOI 10.1088/1748-9326/2/1/014002
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   LOCKWOOD M, 2013, SCIENCE, V31, P647
   MERSHA AA, 2016, DEV POLICY REV, V16, P1701
   MOHAN D, 2016, REG ENVIRON CHANGE, V8, P312
   MSOWOYA K, 2016, CLIM DEV, V30, P5299
   MUCHURU S, 2019, WATER RESOUR MANAG, P1
   MUGINGENGA EW, 2016, CLIM DEV, V43, P49
   MULWA C, 2017, J RURAL STUD, V16, P208
   Nelson GC, 2009, Climate change: Impact on Agriculture and costs of Adaptation, V21, DOI DOI 10.2499/0896295354
   Ngana, 2010, J GEOGR REG PLAN, V3
   NGIGI MW, 2017, CLIM RISK MANAG, V138, P99
   Niang I., 2014, AFRICA B
   Nyangena W, 2013, WIDER WORKING PAPER
   OCHIENG J, 2016, ECOL ECON, V77, P71
   Omambia A.N., 2017, HDB CLIMATE CHANGE M, P749, DOI DOI 10.1007/978-3-319-14409-2_17
   Onyutha C, 2019, FOOD ENERGY SECUR, V8, DOI 10.1002/fes3.160
   Orindi VA, 2005, IDS BULL-I DEV STUD, V36, P87, DOI 10.1111/j.1759-5436.2005.tb00236.x
   OSBAHR H, 2008, FOOD ENERGY SECUR, V39, P1951
   Pande P., 2009, Adaptation of small scale farmers to climatic risks in India
   Pardoe J, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01693-8
   Parry J., 2012, Climate risks, vulnerability and governance in Kenya: a review. Commissioned by: climate risk management technical assistance support project (CRM TASP), joint initiative of bureau for crisis prevention and recovery and bureau for development policy of UNDP.
   PARRY M, 2005, GEOFORUM, V360, P2125
   Parry M.L., 2007, IPCC Climate Change 2007: Impacts, Adaptation and Vulnerability
   Partey ST, 2020, CLIMATIC CHANGE, V158, P61, DOI 10.1007/s10584-018-2239-6
   Pasquini L, 2020, SCI TOTAL ENVIRON, V747, DOI 10.1016/j.scitotenv.2020.141355
   Pauw K.J. Thurlow., 2010, Droughts and floods in Malawi: Assessing the economywide effects
   PHUONG LTH, 2017, GEOFORUM, V82, P1
   Aryal JP, 2020, INT J CLIM CHANG STR, V12, P128, DOI 10.1108/IJCCSM-09-2018-0065
   Aryal JP, 2019, REV DEV ECON, V23, P782, DOI 10.1111/rode.12566
   Quinn CF, 2018, CLIM POLICY, V18, P146, DOI 10.1080/14693062.2016.1258631
   RAO N, 2019, PHILOS T R SOC B, V11, P14
   Recha CW, 2017, GEOSCI LETT, V4, DOI 10.1186/s40562-017-0088-1
   Roos P. B., 2015, International Journal of Climate Change: Impacts and Responses, V7, P13
   Sapkota TB, 2015, J INTEGR AGR, V14, P1524, DOI 10.1016/S2095-3119(15)61093-0
   Saptutyningsih E, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2019.104189
   Schaeffer M., 2015, AFRICAS ADAPTATION G
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   SEAMAN JA, 2014, ENVIRON RES LETT, V4, P59
   SERDECZNY O, 2017, CLIM RISK MANAG, V17, P1585
   SHIFERAW B, 2014, REG ENVIRON CHANGE, V44, P272
   SMALE M, 1995, WORLD DEV, V23, P819, DOI 10.1016/0305-750X(95)00013-3
   SMUCKER TA, 2015, WORLD DEV, V59, P39
   Thomas TS, 2013, INT FOOD POLICY RES
   THORNTON PK, 2014, NJAS-WAGEN J LIFE SC, V20, P3313
   von Grebmer Klaus., 2019, Global Hunger Index: The Challenge of Hunger and Climate Change, Deutsche Welthungerhilfe
   WANG SW, 2017, GLOBAL CHANGE BIOL, V9, P517
   WARNATZSCH EA, 2019, INT J CLIM CHANG STR, V654, P378
   Zougmoré RB, 2018, CAH AGRIC, V27, DOI 10.1051/cagri/2018019
NR 126
TC 24
Z9 26
U1 5
U2 40
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD MAY 15
PY 2021
VL 769
AR 145236
DI 10.1016/j.scitotenv.2021.145236
EA JAN 2021
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA QT5HI
UT WOS:000626618100131
PM 33736234
DA 2025-01-10
ER

PT J
AU Hanh, TTT
   Huong, LTT
   Huong, NTL
   Linh, TNQ
   Quyen, NH
   Nhung, NTT
   Ebi, K
   Cuong, ND
   Nhu, HV
   Kien, TM
   Hales, S
   Cuong, M
   Tho, NTT
   Toan, LQ
   Bich, NN
   Minh, HV
AF Tran Thi Tuyet Hanh
   Le Thi Thanh Huong
   Nguyen Thi Lien Huong
   Tran Nu Quy Linh
   Nguyen Huu Quyen
   Nguyen Thi Trang Nhung
   Ebi, Kristie
   Nguyen Dinh Cuong
   Ha Van Nhu
   Tran Mai Kien
   Hales, Simon
   Manh Cuong
   Nguyen Thi Thi Tho
   Luu Quoc Toan
   Nguyen Ngoc Bich
   Hoang Van Minh
TI Vietnam Climate Change and Health Vulnerability and Adaptation
   Assessment, 2018
SO ENVIRONMENTAL HEALTH INSIGHTS
LA English
DT Article
DE Climate change; health impacts; vulnerability and adaptation assessment;
   Vietnam
ID DIARRHEA; IMPACT; FEVER
AB BACKGROUND: The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030.
   METHODS: The assessment followed the first 4 steps outlined in the World Health Organization's Guidelines in conducting "Vulnerability and Adaptation Assessments." A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events. (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5.
   RESULTS: The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017. the level of "exposure" to climate change-related hazards of the health sector was "high' to "very high,' with an average score from 3.5 to 4.4 (out of 5.0). For "health sensitivity," the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as "high." For 'adaptive capacity," the scores were from 4.0 to 4.1, which meant adaptive capacity was "very low." The overall V&A rating in 2013 was "very high risk" (score 4.1) and "high risk" with scores of 3.8 in 2014 and 3.7 in 2015 to 2017.
   CONCLUSIONS: Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.
C1 [Tran Thi Tuyet Hanh; Le Thi Thanh Huong; Ha Van Nhu; Luu Quoc Toan; Nguyen Ngoc Bich] Hanoi Univ Publ Hlth, Fac Environm & Occupat Hlth, Hanoi, Vietnam.
   [Nguyen Thi Lien Huong; Manh Cuong] Vietnam Hlth Environm Management Agcy, Hanoi, Vietnam.
   [Tran Nu Quy Linh] Griffith Univ, Ctr Environm & Populat Hlth, Sch Med, Brisbane, Qld, Australia.
   [Nguyen Huu Quyen] Inst Hydrol & Meteorol Sci & Climate Change, Climate Res & Climate Forecasting Div, Hanoi, Vietnam.
   [Nguyen Thi Trang Nhung] Hanoi Univ Publ Hlth, Dept Biostat, Hanoi, Vietnam.
   [Ebi, Kristie] Univ Washington, Ctr Hlth & Global Environm, Seattle, WA 98195 USA.
   [Nguyen Dinh Cuong] ADB TA Project, Hanoi, Vietnam.
   [Tran Mai Kien] Inst Hydrol & Meteorol Sci & Climate Change, Climate Change Res Ctr, Hanoi, Vietnam.
   [Hales, Simon] Univ Otago, Publ Hlth Dept, Otago, New Zealand.
   [Nguyen Thi Thi Tho] Natl Inst Hyg & Epidemiol, Dept Noncommunicable Dis Prevent & Control, Hanoi, Vietnam.
   [Hoang Van Minh] Hanoi Univ Publ Hlth, 1A Duc Thang Rd, Hanoi 100000, Vietnam.
C3 Hanoi University of Public Health; Griffith University; Hanoi University
   of Public Health; University of Washington; University of Washington
   Seattle; University of Otago; National Institute of Hygiene &
   Epidemiology (NIHE); Hanoi University of Public Health
RP Huong, LTT (corresponding author), Hanoi Univ Publ Hlth, 1A Duc Thang Rd, Hanoi 100000, Vietnam.
EM lth@huph.edu.vn
RI Hoang, Minh/AET-0962-2022; Nguyen, Truong/JXN-9786-2024; hales,
   simon/E-5768-2010; Nhung, Nguyen/ADR-1738-2022; Tran,
   Linh/AAU-7091-2020; Ebi, Kristie/AFK-6769-2022
OI Tran Thi, Tuyet-Hanh/0000-0002-9191-577X; Tran, Nu Quy
   Linh/0000-0002-2807-8323; Hoang Van, Minh/0000-0002-4749-5536; Nguyen,
   Thi Trang Nhung/0000-0002-1248-1070; Le, Huong/0000-0002-3844-8041;
   Hales, Simon/0000-0002-4529-7595
FU Asian Development Bank [TA-8898 REG]
FX The author(s) disclosed receipt of the following financial support for
   the research, authorship, and/or publication of this article: The
   assessment received technical and financial support from Asian
   Development Bank under the project titled "TA-8898 REG: Regional
   Capacity Development for Strengthening Resilience to Climate Change in
   the Health Sector in the Greater Mekong Sub-region."
CR Älgå A, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15122689
   [Anonymous], 2015, VIRULENCE, DOI DOI 10.1080/21505594.2015.1023985
   [Anonymous], ENV HLTH PERSPECT
   AUSTIN S, 2016, MICROMACHINES-BASEL, V13, P889, DOI DOI 10.3390/IJERPH13090889
   Birkmann J, 2012, ENVIRON SCI ENG, P245, DOI 10.1007/978-94-007-3962-8_10
   CARE, 2010, COMM BAS AD TOOK
   Choi Y, 2016, BMC PUBLIC HEALTH, V16, DOI 10.1186/s12889-016-2923-2
   Ebi K.L., 2013, PROTECTING HLTH CLIM
   Eckstein D., 2021, Who Suffers Most from Extreme Weather Events, 2000-2019
   Foreman KJ, 2018, LANCET, V392, P2052, DOI [10.1016/S0140-6736(18)31694-5, 10.1016/s0140-6736(18)31694-5]
   Gilfillan D, 2017, ECOL SOC, V22, DOI 10.5751/ES-09235-220314
   Lam HM, 2018, INFLUENZA OTHER RESP, V12, P742, DOI 10.1111/irv.12595
   Hii Yien Ling, 2016, Curr Environ Health Rep, V3, P81, DOI 10.1007/s40572-016-0078-z
   Lee HS, 2017, BMC INFECT DIS, V17, DOI 10.1186/s12879-017-2326-8
   Huang CR, 2011, AM J PREV MED, V40, P183, DOI 10.1016/j.amepre.2010.10.025
   Le TDP, 2016, AIMS PUBLIC HEALTH, V3, P769, DOI 10.3934/publichealth.2016.4.769
   Levison MM, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15102237
   Nguyen YT, 2013, VACCINE, V31, P4368, DOI 10.1016/j.vaccine.2013.07.018
   Pham HV, 2011, BMC INFECT DIS, V11, DOI 10.1186/1471-2334-11-172
   Phung D, 2015, INT J BIOMETEOROL, V59, P1321, DOI 10.1007/s00484-014-0942-1
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Rakotoarison N, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15122643
   Thompson CN, 2015, HEALTH PLACE, V35, P147, DOI 10.1016/j.healthplace.2015.08.001
   Thuc T., 2016, Climate change and sea level rise scenarios for vietnam
   Toai N. P., 2016, Environment Asia, V9, P55
   Wangdi K, 2018, MALARIA J, V17, DOI 10.1186/s12936-018-2478-z
   Watts N, 2017, LANCET, V389, P1151, DOI 10.1016/S0140-6736(16)32124-9
   World Health Organization, 2014, QUANT RISK ASS EFF C
   World Health Organization, UPD DENG SIT W PAC R
   World Health Organization, 2013, PROT HLHT CLIM CHANG
   Wu Xiaoxu, 2016, Environ Int, V86, P14, DOI 10.1016/j.envint.2015.09.007
   [No title captured]
NR 32
TC 13
Z9 13
U1 2
U2 23
PU SAGE PUBLICATIONS LTD
PI LONDON
PA 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
SN 1178-6302
J9 ENVIRON HEALTH INSIG
JI Environ. Health Insights
PD JUN
PY 2020
VL 14
AR 1178630220924658
DI 10.1177/1178630220924658
PG 11
WC Public, Environmental & Occupational Health
WE Emerging Sources Citation Index (ESCI)
SC Public, Environmental & Occupational Health
GA ME5ZV
UT WOS:000544734600001
PM 32612364
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Milheiras, SG
   Sallu, SM
   Marshall, AR
   Shirima, DD
   Kioko, EN
   Loveridge, R
   Moore, E
   Olivier, P
   Teh, YA
   Rushton, S
   Pfeifer, M
AF Milheiras, Sergio G.
   Sallu, Susannah M.
   Marshall, Andrew R.
   Shirima, Deo D.
   Kioko, Esther N.
   Loveridge, Robin
   Moore, Eleanor
   Olivier, Pieter
   Teh, Yit Arn
   Rushton, Stephen
   Pfeifer, Marion
TI A Framework to Assess Forest-Agricultural Landscape Management for
   Socioecological Well-Being Outcomes
SO FRONTIERS IN FORESTS AND GLOBAL CHANGE
LA English
DT Article
DE biodiversity; ecosystem restoration; sustainable livelihoods; Africa;
   rural development; multifunctionality
ID ECOSYSTEM SERVICES; LAND-USE; CLIMATE-CHANGE; TRADE-OFFS; SUSTAINABLE
   INTENSIFICATION; ECOLOGICAL INTENSIFICATION; ENVIRONMENTAL COSTS;
   KILOMBERO VALLEY; BIODIVERSITY; AGROFORESTRY
AB Global demand for agricultural products continues to grow. However, efforts to boost productivity exacerbate existing pressures on nature, both on farms and in the wider landscape. There is widespread appreciation of the critical need to achieve balance between biodiversity and human well-being in rural tropical crop production landscapes, that are essential for livelihoods and food security. There is limited empirical evidence of the interrelationships between natural capital, the benefits and costs of nature and its management, and food security in agricultural landscapes. Agroforestry practices are frequently framed as win-win solutions to reconcile the provision of ecosystem services important to farmers (i.e., maintaining soil quality, supporting pollinator, and pest control species) with nature conservation. Yet, underlying trade-offs (including ecosystem disservices linked to pest species or human-wildlife conflicts) and synergies (e.g., impact of ecosystem service provision on human well-being) are seldom analysed together at the landscape scale. Here, we propose a systems model framework to analyse the complex pathways, with which natural capital on and around farms interacts with human well-being, in a spatially explicit manner. To illustrate the potential application of the framework, we apply it to a biodiversity and well-being priority landscape in the Southern Agricultural Growth Corridor of Tanzania, a public-private partnership for increasing production of cash and food crops. Our framework integrates three main dimensions: biodiversity (using tree cover and wildlife as key indicators), food security through crop yield and crop health, and climate change adaptation through microclimate buffering of trees. The system model can be applied to analyse forest-agricultural landscapes as socio-ecological systems that retain the capacity to adapt in the face of change in ways that continue to support human well-being. It is based on metrics and pathways that can be quantified and parameterised, providing a tool for monitoring multiple outcomes from management of forest-agricultural landscapes. This bottom-up approach shifts emphasis from global prioritisation and optimisation modelling frameworks, based on biophysical properties, to local socio-economic contexts relevant in biodiversity-food production interactions across large parts of the rural tropics.
C1 [Milheiras, Sergio G.; Moore, Eleanor; Teh, Yit Arn; Rushton, Stephen; Pfeifer, Marion] Newcastle Univ, Fac Sci Agr & Engn, Sch Nat & Environm Sci, Newcastle Upon Tyne, Northumberland, England.
   [Sallu, Susannah M.] Univ Leeds, Fac Environm, Sch Earth & Environm, Leeds, England.
   [Marshall, Andrew R.; Loveridge, Robin] Univ York, Dept Environm & Geog, York, North Yorkshire, England.
   [Marshall, Andrew R.] Univ Sunshine Coast, Trop Forests & People Res Ctr, Sippy Downs, Qld, Australia.
   [Shirima, Deo D.] Sokoine Univ Agr, Dept Ecosyst & Conservat, Morogoro, Tanzania.
   [Kioko, Esther N.] Natl Museums Kenya, Zool Dept, Invertebrate Zool Sect, Nairobi, Kenya.
   [Loveridge, Robin] Biodivers Consultancy, Cambridge, Cambridgeshire, England.
   [Olivier, Pieter] MAP Sci Serv, Pretoria, South Africa.
   [Olivier, Pieter] Univ Pretoria, Dept Zool & Entomol, Pretoria, South Africa.
C3 Newcastle University - UK; University of Leeds; University of York - UK;
   University of the Sunshine Coast; Sokoine University of Agriculture;
   University of Pretoria
RP Milheiras, SG (corresponding author), Newcastle Univ, Fac Sci Agr & Engn, Sch Nat & Environm Sci, Newcastle Upon Tyne, Northumberland, England.
EM smilheiras@gmail.com
RI Sallu, Susannah/T-9318-2019
OI Sallu, Susannah/0000-0002-1471-2485; Durrant,
   Eleanor/0000-0003-3396-6912; G. Milheiras, Sergio/0000-0003-4166-8333
FU BBSRC Global Challenges Research Fund [BB/S014586/1]; Tanzania
   Commission for Science and Technology [2019-578-NA-2019-243,
   2019-577-NA-2019-243]; BBSRC [BB/S014586/1] Funding Source: UKRI
FX Agrisys Tanzania project was funded through BBSRC Global Challenges
   Research Fund under reference BB/S014586/1. This research was registered
   in the Tanzania Commission for Science and Technology under references
   2019-578-NA-2019-243 and 2019-577-NA-2019-243.
CR Aizen MA, 2009, ANN BOT-LONDON, V103, P1579, DOI 10.1093/aob/mcp076
   Alhafedh Y., 2018, IPBES REGIONAL ASSES
   Ango TG, 2017, ORYX, V51, P527, DOI [10.1017/s0030605316000028, 10.1017/S0030605316000028]
   [Anonymous], 2019, GLOBAL ASSESSMENT RE
   Balmford A, 2018, NAT SUSTAIN, V1, P477, DOI 10.1038/s41893-018-0138-5
   Bastin JF, 2019, SCIENCE, V365, P76, DOI 10.1126/science.aax0848
   Bateman IJ, 2020, NAT SUSTAIN, V3, P776, DOI 10.1038/s41893-020-0552-3
   Bennett NJ, 2017, BIOL CONSERV, V205, P93, DOI 10.1016/j.biocon.2016.10.006
   Bergius M, 2018, J PEASANT STUD, V45, P825, DOI 10.1080/03066150.2016.1260554
   Bianchi FJJA, 2006, P ROY SOC B-BIOL SCI, V273, P1715, DOI 10.1098/rspb.2006.3530
   Boetzl FA, 2020, J APPL ECOL, V57, P1482, DOI 10.1111/1365-2664.13653
   Bommarco R, 2013, TRENDS ECOL EVOL, V28, P230, DOI 10.1016/j.tree.2012.10.012
   Borrelli P, 2020, P NATL ACAD SCI USA, V117, P21994, DOI 10.1073/pnas.2001403117
   Borrelli P, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-02142-7
   Brosi BJ, 2008, J APPL ECOL, V45, P773, DOI 10.1111/j.1365-2664.2007.01412.x
   Brown SE, 2018, ENVIRON EVID, V7, DOI 10.1186/s13750-018-0136-0
   Brueckner-Irwin I, 2019, ECOL SOC, V24, DOI 10.5751/ES-10995-240307
   Carvalheiro LG, 2010, J APPL ECOL, V47, P810, DOI 10.1111/j.1365-2664.2010.01829.x
   Chambers JM, 2021, NAT SUSTAIN, V4, P983, DOI 10.1038/s41893-021-00755-x
   Chaudhary A, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10082764
   Chavarría JYD, 2018, AGR ECOSYST ENVIRON, V263, P41, DOI 10.1016/j.agee.2018.04.020
   Chazdon RL, 2008, SCIENCE, V320, P1458, DOI 10.1126/science.1155365
   Collins M, 2019, IPCC special report on the Ocean and cryosphere in a changing climate, DOI [DOI 10.1017/978100957964.008, DOI 10.1017/9781009157964.008]
   Crist E, 2017, SCIENCE, V356, P260, DOI 10.1126/science.aal2011
   Dainese M, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax0121
   Dasgupta P, 2021, The economics of biodiversity: The Dasgupta review
   Daw TM, 2016, ECOL SOC, V21, DOI 10.5751/ES-08173-210211
   Daw TM, 2015, P NATL ACAD SCI USA, V112, P6949, DOI 10.1073/pnas.1414900112
   Doggart N, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab6b35
   Dollinger J, 2018, AGROFOREST SYST, V92, P213, DOI 10.1007/s10457-018-0223-9
   Dudley N, 2017, BIOL CONSERV, V209, P449, DOI 10.1016/j.biocon.2017.03.012
   Enns C, 2018, GEOFORUM, V88, P105, DOI 10.1016/j.geoforum.2017.11.017
   European Space Agency [ESA], 2017, CLIM CHANG IN LAND C
   Ewers RM, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0058093
   FAO, 2017, FUTURE FOOD AGR TREN, DOI DOI 10.2307/4356839
   Fischer J, 2014, CONSERV LETT, V7, P149, DOI 10.1111/conl.12084
   Fleischman F, 2020, BIOSCIENCE, V70, P947, DOI 10.1093/biosci/biaa094
   Folke C, 2016, ECOL SOC, V21, DOI 10.5751/ES-08748-210341
   Frund HC, 2011, SOIL BIOL, V24, P261, DOI 10.1007/978-3-642-14636-7_16
   Fry BP, 2017, ORYX, V51, P68, DOI 10.1017/S003060531500112X
   Funk CC, 2009, FOOD SECUR, V1, P271, DOI 10.1007/s12571-009-0026-y
   Gagic V, 2019, J APPL ECOL, V56, P2528, DOI 10.1111/1365-2664.13482
   Garibaldi LA, 2019, TRENDS ECOL EVOL, V34, P282, DOI 10.1016/j.tree.2019.01.003
   Gough I, 2007, WELLBEING IN DEVELOPING COUNTRIES: FROM THEORY TO RESEARCH, P3, DOI 10.1017/CBO9780511488986.002
   Grass I, 2019, PEOPLE NAT, V1, P262, DOI 10.1002/pan3.21
   Gunderson L.H., 2012, FDN ECOLOGICAL RESIL
   Gurr GM, 2016, NAT PLANTS, V2, DOI 10.1038/nplants.2016.14
   Horlings LG, 2011, GLOBAL ENVIRON CHANG, V21, P441, DOI 10.1016/j.gloenvcha.2011.01.004
   Howe C, 2014, GLOBAL ENVIRON CHANG, V28, P263, DOI 10.1016/j.gloenvcha.2014.07.005
   IFAD (International Fund for Agricultural Development), 2021, STRUGGL STRENGTH WIS
   Isbell F, 2017, J ECOL, V105, P871, DOI 10.1111/1365-2745.12789
   Isman MB, 2008, PEST MANAG SCI, V64, P8, DOI 10.1002/ps.1470
   Jayne TS, 2010, WORLD DEV, V38, P1384, DOI 10.1016/j.worlddev.2010.06.002
   Jenkins RKB, 2003, BIODIVERS CONSERV, V12, P787, DOI 10.1023/A:1022426026881
   Jones T, 2012, TROP CONSERV SCI, V5, P463, DOI 10.1177/194008291200500405
   Jonsson K, 1999, EXP AGR, V35, P39, DOI 10.1017/S0014479799001039
   Kangalawe RYM, 2005, PHYS CHEM EARTH, V30, P968, DOI 10.1016/j.pce.2005.08.044
   Kennedy CM, 2013, ECOL LETT, V16, P584, DOI 10.1111/ele.12082
   Khan ZR, 2008, FIELD CROP RES, V106, P224, DOI 10.1016/j.fcr.2007.12.002
   King MF, 2014, SOC INDIC RES, V116, P681, DOI 10.1007/s11205-013-0320-0
   Kornov L., 2000, Impact Assessment and Project Appraisal, V18, P191, DOI DOI 10.3152/147154600781767402
   Kravchenko AN, 2017, P NATL ACAD SCI USA, V114, P926, DOI 10.1073/pnas.1612311114
   Kremen C, 2015, ANN NY ACAD SCI, V1355, P52, DOI 10.1111/nyas.12845
   Lasco RD, 2014, CURR OPIN ENV SUST, V6, P83, DOI 10.1016/j.cosust.2013.11.013
   Laurance WF, 2015, CURR BIOL, V25, P3202, DOI 10.1016/j.cub.2015.10.046
   Lehmann P, 2020, FRONT ECOL ENVIRON, V18, P141, DOI 10.1002/fee.2160
   Li M, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-48747-4
   Lin BB, 2008, BIOSCIENCE, V58, P847, DOI 10.1641/B580911
   Lobell DB, 2011, NAT CLIM CHANGE, V1, P42, DOI [10.1038/NCLIMATE1043, 10.1038/nclimate1043]
   Loveridge R, 2020, ENVIRON SCI POLICY, V114, P461, DOI 10.1016/j.envsci.2020.09.002
   Malézieux E, 2009, AGRON SUSTAIN DEV, V29, P43, DOI 10.1051/agro:2007057
   Marsden C, 2020, PLANT SOIL, V453, P29, DOI 10.1007/s11104-019-04322-4
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P61, DOI 10.1016/j.cosust.2013.10.014
   McGregor JA, 2018, WELLBEING POL POL, P197, DOI 10.1007/978-3-319-58394-5_9
   McKinnon MC, 2016, ENVIRON EVID, V5, DOI 10.1186/s13750-016-0058-7
   McShane TO, 2011, BIOL CONSERV, V144, P966, DOI 10.1016/j.biocon.2010.04.038
   Milner-Gulland EJ, 2014, CONSERV BIOL, V28, P1160, DOI 10.1111/cobi.12277
   Mukeka JM, 2019, GLOB ECOL CONSERV, V18, DOI 10.1016/j.gecco.2019.e00620
   Munishi S, 2019, PHYS CHEM EARTH, V112, P216, DOI 10.1016/j.pce.2019.03.008
   Nagendra Harini., 2016, NATURE CITY BENGALUR, DOI [10.1093/acprof:oso/9780199465927.001.0001, DOI 10.1093/ACPROF:OSO/9780199465927.001.0001]
   Ndoli A, 2017, FIELD CROP RES, V213, P1, DOI 10.1016/j.fcr.2017.07.020
   Newbold T, 2015, NATURE, V520, P45, DOI 10.1038/nature14324
   Nyhus PJ, 2016, ANNU REV ENV RESOUR, V41, P143, DOI 10.1146/annurev-environ-110615-085634
   Ojedokun C. A., 2020, Journal of Applied Sciences & Environmental Management, V24, P1363, DOI 10.4314/jasem.v24i8.9
   Oldfield EE, 2019, SOIL-GERMANY, V5, P15, DOI 10.5194/soil-5-15-2019
   OpenStreetMap Contributors, 2019, OP STREET MAP ROAD D
   Paavola J, 2008, ENVIRON SCI POLICY, V11, P642, DOI 10.1016/j.envsci.2008.06.002
   Pellegrini P, 2018, P NATL ACAD SCI USA, V115, P2335, DOI 10.1073/pnas.1717072115
   Peng SS, 2014, P NATL ACAD SCI USA, V111, P2915, DOI 10.1073/pnas.1315126111
   Pfeifer M, 2017, NATURE, V551, P187, DOI 10.1038/nature24457
   Power AG, 2010, PHILOS T R SOC B, V365, P2959, DOI 10.1098/rstb.2010.0143
   Pretty J, 2015, INSECTS, V6, P152, DOI 10.3390/insects6010152
   Ramankutty N, 2018, ANNU REV PLANT BIOL, V69, P789, DOI 10.1146/annurev-arplant-042817-040256
   Rasmussen LV, 2018, NAT SUSTAIN, V1, P275, DOI 10.1038/s41893-018-0070-8
   Rendón OR, 2019, PEOPLE NAT, V1, P486, DOI 10.1002/pan3.10050
   Reyes-García V, 2016, J HAPPINESS STUD, V17, P773, DOI 10.1007/s10902-014-9608-2
   Robards MD, 2011, GLOBAL ENVIRON CHANG, V21, P522, DOI 10.1016/j.gloenvcha.2010.12.004
   Rosenstock TS, 2014, CURR OPIN ENV SUST, V6, P15, DOI 10.1016/j.cosust.2013.09.001
   SAGCOT, 2011, Southern Agricultural Growth Corridor of Tanzania: Investment Blueprint
   Sánchez-Romero R, 2021, FOREST ECOL MANAG, V479, DOI 10.1016/j.foreco.2020.118506
   Schrama M, 2018, AGR ECOSYST ENVIRON, V256, P123, DOI 10.1016/j.agee.2017.12.023
   Shaffer LJ, 2019, FRONT ECOL EVOL, V6, DOI 10.3389/fevo.2018.00235
   Sida TS, 2018, AGR FOREST METEOROL, V248, P339, DOI 10.1016/j.agrformet.2017.10.013
   Sinclair FL, 1999, AGROFOREST SYST, V46, P161, DOI 10.1023/A:1006278928088
   Sirami C, 2019, P NATL ACAD SCI USA, V116, P16442, DOI 10.1073/pnas.1906419116
   Smith HE, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101976
   Strassburg BBN, 2020, NATURE, V586, P724, DOI 10.1038/s41586-020-2784-9
   Suich H, 2015, ECOSYST SERV, V12, P137, DOI 10.1016/j.ecoser.2015.02.005
   Teixeira FZ, 2019, LANDSCAPE ECOL, V34, P1583, DOI 10.1007/s10980-019-00778-y
   Tilman D, 2002, NATURE, V418, P671, DOI 10.1038/nature01014
   Torralba M, 2016, AGR ECOSYST ENVIRON, V230, P150, DOI 10.1016/j.agee.2016.06.002
   Trimmer JT, 2017, TROP CONSERV SCI, V10, DOI 10.1177/1940082917720666
   Tscharntke T, 2005, ECOL LETT, V8, P857, DOI 10.1111/j.1461-0248.2005.00782.x
   Tscharntke T, 2012, BIOL REV, V87, P661, DOI 10.1111/j.1469-185X.2011.00216.x
   Tscharntke T, 2011, J APPL ECOL, V48, P619, DOI 10.1111/j.1365-2664.2010.01939.x
   UNEP-WCMC IUCN, 2021, PROT PLAN WORLD DAT
   van Groenigen JW, 2014, SCI REP-UK, V4, DOI 10.1038/srep06365
   van Ittersum MK, 2016, P NATL ACAD SCI USA, V113, P14964, DOI 10.1073/pnas.1610359113
   Vialatte A, 2019, LANDSCAPE ECOL, V34, P1653, DOI 10.1007/s10980-019-00829-4
   Webb NP, 2017, FRONT ECOL ENVIRON, V15, P450, DOI 10.1002/fee.1530
   Williams A, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-26896-2
   Winfree R, 2018, SCIENCE, V359, P791, DOI 10.1126/science.aao2117
   Woodhouse E, 2015, PHILOS T R SOC B, V370, DOI 10.1098/rstb.2015.0103
   Zhang W, 2007, ECOL ECON, V64, P253, DOI 10.1016/j.ecolecon.2007.02.024
NR 124
TC 5
Z9 5
U1 9
U2 73
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-893X
J9 FRONT FOR GLOB CHANG
JI Front. For. Glob. Change
PD MAY 26
PY 2022
VL 5
AR 709971
DI 10.3389/ffgc.2022.709971
PG 13
WC Ecology; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Forestry
GA 2D4JZ
UT WOS:000811516700001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Joubert, C
   Young, PR
   Eyéghé-Bickong, HA
   Vivier, MA
AF Joubert, Chandre
   Young, Philip R.
   Eyeghe-Bickong, Hans A.
   Vivier, Melane A.
TI Field-Grown Grapevine Berries Use Carotenoids and the Associated
   Xanthophyll Cycles to Acclimate to UV Exposure Differentially in High
   and Low Light (Shade) Conditions
SO FRONTIERS IN PLANT SCIENCE
LA English
DT Article
DE UVB radiation; solar radiation; climate change adaptation; acclimation;
   berry development
ID B-INDUCED PHOTOMORPHOGENESIS; SOLAR ULTRAVIOLET-RADIATION;
   PHOTOOXIDATIVE STRESS; SUNLIGHT EXPOSURE; LEAF REMOVAL; LEAVES;
   ANTHOCYANIN; FRUIT; FLAVONOL; IMPACT
AB Light quantity and quality modulate grapevine development and influence berry metabolic processes. Here we studied light as an information signal for developing and ripening grape berries. A Vitis vinifera Sauvignon Blanc field experiment was used to identify the impacts of UVB on core metabolic processes in the berries under both high light (HL) and low light (LL) microclimates. The primary objective was therefore to identify UVB-specific responses on berry processes and metabolites and distinguish them from those responses elicited by variations in light incidence. Canopy manipulation at the bunch zone via early leaf removal, combined with UVB-excluding acrylic sheets installed over the bunch zones resulted in four bunch microclimates: (1) HL (control); (2) LL (control); (3) HL with UVB attenuation and (4) LL with UVB attenuation. Metabolite profiles of three berry developmental stages showed predictable changes to known UV-responsive compound classes in a typical UV acclimation (versus UV damage) response. Interestingly, the berries employed carotenoids and the associated xanthophyll cycles to acclimate to UV exposure and the berry responses differed between HL and LL conditions, particularly in the developmental stages where berries are still photosynthetically active. The developmental stage of the berries was an important factor to consider in interpreting the data. The green berries responded to the different exposure and/or UVB attenuation signals with metabolites that indicate that the berries actively managed its metabolism in relation to the exposure levels, displaying metabolic plasticity in the photosynthesis-related metabolites. Core processes such as photosynthesis, photo-inhibition and acclimation were maintained by differentially modulating metabolites under the four treatments. Ripe berries also responded metabolically to the light quality and quantity, but mostly formed compounds (volatiles and polyphenols) that have direct antioxidant and/or "sunscreening" abilities. The data presented for the green berries and those for the ripe berries conform to what is known for UVB and/or light stress in young, active leaves and older, senescing tissues respectively and provide scope for further evaluation of the sink/source status of fruits in relation to photosignalling and/or stress management.
C1 [Joubert, Chandre; Young, Philip R.; Eyeghe-Bickong, Hans A.; Vivier, Melane A.] Univ Stellenbosch, Dept Viticulture & Oenol, ZA-7600 Stellenbosch, South Africa.
   [Young, Philip R.; Eyeghe-Bickong, Hans A.; Vivier, Melane A.] Univ Stellenbosch, Inst Wine Biotechnol, ZA-7600 Stellenbosch, South Africa.
   [Eyeghe-Bickong, Hans A.] Univ Stellenbosch, Inst Grape & Wine Sci, ZA-7600 Stellenbosch, South Africa.
C3 Stellenbosch University; Stellenbosch University; Stellenbosch
   University
RP Vivier, MA (corresponding author), Univ Stellenbosch, Dept Viticulture & Oenol, ZA-7600 Stellenbosch, South Africa.; Vivier, MA (corresponding author), Univ Stellenbosch, Inst Wine Biotechnol, ZA-7600 Stellenbosch, South Africa.
EM mav@sun.ac.za
RI Young, Philip/ABA-6871-2021; Eyeghe Bickong, Hans Andre/ABC-2712-2021
OI Eyeghe-Bickong, Hans Andre/0000-0002-6822-9157; Young,
   Philip/0000-0002-6488-4859
FU Wine Industry Network for Expertise and Technology (Winetech);
   Department of Science and Technology (DST); National Research Foundation
   (NRF); Technology and Human Resources for Industry Programme (THRIP)
FX The authors would like to recognize the following people for their
   contributions toward this study: Ms Zelmari Coetzec for her assistance
   with the viticultural treatments, logger installation and sampling; Dr.
   Katja Suklje and Prof Alain Deloire for useful discussions during the
   planning stages of the study; Ms Varsha Premsagar for her assistance
   with sample processing; Mrs Anke Berry and Ms Louise Dautrey for their
   assistance with sampling processing and analysis; Mr Lucky Mokwena for
   his assistance with the implementation of the GC-MS method for volatile
   aroma compound analysis; Dr Albert Strever for his help with the
   statistical analysis. The study was financially supported with grants
   from Wine Industry Network for Expertise and Technology (Winetech),
   Department of Science and Technology (DST), the National Research
   Foundation (NRF) and the Technology and Human Resources for Industry
   Programme (THRIP).
CR Alexandersson E, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00286
   ALLEN MS, 1991, AM J ENOL VITICULT, V42, P109
   ARAKAWA O, 1985, PHYSIOL PLANTARUM, V64, P323, DOI 10.1111/j.1399-3054.1985.tb03347.x
   Azuma A, 2012, PLANTA, V236, P1067, DOI 10.1007/s00425-012-1650-x
   Barros EP, 2012, TALANTA, V101, P177, DOI 10.1016/j.talanta.2012.08.028
   BLANKE MM, 1989, PLANT CELL ENVIRON, V12, P31, DOI 10.1111/j.1365-3040.1989.tb01914.x
   Bureau SM, 2000, J SCI FOOD AGR, V80, P2012, DOI 10.1002/1097-0010(200011)80:14<2012::AID-JSFA738>3.0.CO;2-X
   Calvenzani V, 2010, PLANTA, V231, P755, DOI 10.1007/s00425-009-1082-4
   Carbonell-Bejerano P, 2014, BMC PLANT BIOL, V14, DOI 10.1186/1471-2229-14-183
   Carvalho LC, 2015, PLANT CELL ENVIRON, V38, P777, DOI 10.1111/pce.12445
   Cramer GR, 2011, BMC PLANT BIOL, V11, DOI 10.1186/1471-2229-11-163
   Dal Santo S, 2013, GENOME BIOL, V14, DOI 10.1186/gb-2013-14-6-r54
   Demmig-Adams B, 2006, NEW PHYTOL, V172, P11, DOI 10.1111/j.1469-8137.2006.01835.x
   DemmigAdams B, 1996, TRENDS PLANT SCI, V1, P21, DOI 10.1016/S1360-1385(96)80019-7
   Diago MP, 2012, AM J ENOL VITICULT, V63, P367, DOI 10.5344/ajev.2012.11116
   Downey MO, 2004, AUST J GRAPE WINE R, V10, P55, DOI 10.1111/j.1755-0238.2004.tb00008.x
   EICHHORN K W, 1977, Nachrichtenblatt des Deutschen Pflanzenschutzdienstes (Stuttgart), V29, P119
   Eyéghé-Bickong HA, 2012, J CHROMATOGR B, V885, P43, DOI 10.1016/j.jchromb.2011.12.011
   Fariña L, 2005, J AGR FOOD CHEM, V53, P1633, DOI 10.1021/jf040332d
   Favory JJ, 2009, EMBO J, V28, P591, DOI 10.1038/emboj.2009.4
   García-Plazaola JI, 2007, FUNCT PLANT BIOL, V34, P759, DOI 10.1071/FP07095
   Gil M, 2013, PHYTOCHEMISTRY, V96, P148, DOI 10.1016/j.phytochem.2013.08.011
   Gregan SM, 2012, AUST J GRAPE WINE R, V18, P227, DOI 10.1111/j.1755-0238.2012.00192.x
   Hassenberg K, 2012, J APPL BOT FOOD QUAL, V85, P174
   Hideg É, 2013, TRENDS PLANT SCI, V18, P107, DOI 10.1016/j.tplants.2012.09.003
   Johnson MP, 2007, J BIOL CHEM, V282, DOI 10.1074/jbc.M702831200
   Joshi P., 2013, Plastid development in leaves during growth and senescence, P641, DOI [10.1007/978-94-007-5724-0_28, DOI 10.1007/978-94-007-5724-0_28]
   Juvany M, 2013, J EXP BOT, V64, P3087, DOI 10.1093/jxb/ert174
   Kolb CA, 2003, FUNCT PLANT BIOL, V30, P1177, DOI 10.1071/FP03076
   Lashbrooke JG, 2010, AUST J GRAPE WINE R, V16, P349, DOI 10.1111/j.1755-0238.2010.00097.x
   Li JG, 2013, PROTEIN CELL, V4, P485, DOI 10.1007/s13238-013-3036-7
   Liu LL, 2015, PLANT CELL ENVIRON, V38, P905, DOI 10.1111/pce.12349
   Loreto F, 2004, TREE PHYSIOL, V24, P361, DOI 10.1093/treephys/24.4.361
   Loreto F, 2001, PLANT PHYSIOL, V127, P1781, DOI 10.1104/pp.010497
   Loreto F, 2010, TRENDS PLANT SCI, V15, P154, DOI 10.1016/j.tplants.2009.12.006
   Lund CM, 2009, AM J ENOL VITICULT, V60, P1
   Martínez-Lüscher J, 2013, PLANT SCI, V213, P114, DOI 10.1016/j.plantsci.2013.08.010
   Pontin MA, 2010, BMC PLANT BIOL, V10, DOI 10.1186/1471-2229-10-224
   Possell M., 2013, BIOL CONTROLS MODELS, P209
   Ramel F, 2012, P NATL ACAD SCI USA, V109, P5535, DOI 10.1073/pnas.1115982109
   Schultz HR, 1998, VITIS, V37, P191
   Song JQ, 2015, FOOD CHEM, V173, P424, DOI 10.1016/j.foodchem.2014.09.150
   Steel CC, 2000, BIOCHEM SOC T, V28, P883, DOI 10.1042/BST0280883
   Tardaguila J, 2010, AM J ENOL VITICULT, V61, P372
   THAYER SS, 1990, PHOTOSYNTH RES, V23, P331, DOI 10.1007/BF00034864
   Matus JT, 2009, J EXP BOT, V60, P853, DOI 10.1093/jxb/ern336
   Tian B, 2015, AUST J GRAPE WINE R, V21, P417, DOI 10.1111/ajgw.12135
   Tilbrook Kimberley, 2013, Arabidopsis Book, V11, pe0164, DOI 10.1199/tab.0164
   Ubi BE, 2006, PLANT SCI, V170, P571, DOI 10.1016/j.plantsci.2005.10.009
   Vogelmann TC, 2014, ADV PHOTOSYNTH RESP, V39, P363, DOI 10.1007/978-94-017-8742-0_19
   WALTERS RG, 1994, PLANTA, V195, P248, DOI 10.1007/BF00199685
   Young PR, 2016, PLANT PHYSIOL, V170, P1235, DOI 10.1104/pp.15.01775
   Zhang HH, 2014, FOOD CHEM, V164, P242, DOI 10.1016/j.foodchem.2014.05.012
NR 53
TC 48
Z9 53
U1 3
U2 62
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 1664-462X
J9 FRONT PLANT SCI
JI Front. Plant Sci.
PD JUN 10
PY 2016
VL 7
AR 786
DI 10.3389/fpls.2016.00786
PG 17
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA DO0UN
UT WOS:000377493900001
PM 27375645
OA gold, Green Published
DA 2025-01-10
ER

PT C
AU Evans, JP
   Olson, R
   Fita, L
   Argüeso, D
   Di Luca, A
AF Evans, J. P.
   Olson, R.
   Fita, L.
   Argueso, D.
   Di Luca, A.
BE Weber, T
   McPhee, MJ
   Anderssen, RS
TI NARCliM model performance including teleconnections with climate modes
SO 21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015)
LA English
DT Proceedings Paper
CT 21st International Congress on Modelling and Simulation (MODSIM) held
   jointly with the 23rd National Conference of the
   Australian-Society-for-Operations-Research / DSTO led Defence Operations
   Research Symposium (DORS
CY NOV 29-DEC 04, 2015
CL Gold Coast, AUSTRALIA
SP BMT WBM, CSIRO, UNSW Australia Canberra, Griffith Univ, Deltares, Modelling & Simulat Soc Australia & New Zealand, Australian Soc Operat Res, DSTO, Gold Coast Tourism Corp
DE Regional Climate Model; Future Climate Projections; south-east
   Australia; precipitation; temperature; WRF
ID MIDDLE-EAST; PRECIPITATION; VARIABILITY; PROJECTIONS; SIMULATION;
   RESOLUTION
AB NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modelling project for the Australian area. It provides a dynamically downscaled climate dataset for the CORDEX-AustralAsia region at 50km, and South-East Australia at a resolution of 10km. NARCliM data is being used by the NSW and ACT governments to design their climate change adaptation plans. Data is available through the AdaptNSW website (http://climatechange. environment. nsw.gov.au/).
   NARCliM uses version 3.3 of the Weather Research and Forecasting (WRF) regional climate model (RCM) to perform an ensemble of simulations for the present and the projected future climate. WRF is run in three different model configurations (different combinations of physical parametrizations) that have been shown to perform well in the South-East Australia and were chosen based on performance and independence. These three RCMs are used to simulate three different periods: 1990-2009, 2020-2039 and 2060-2079. Four different Global Climate Models (GCMs: MIROC-medres 3.2, ECHAM5, CCCMA 3.1 and CSIRO mk3.0) from CMIP3 are used as initial and boundary conditions for the WRF simulations. These GCMs were chosen through a process that considered model performance, independence and projected future changes. Thus a RCM ensemble of 12 simulations for each period is obtained. Additionally to the GCM-driven simulations, 3 control run simulations driven by the NCEP/NCAR reanalysis for the entire period of 1950-2009 are also performed in order to evaluate the RCMs performance in the area.
   The NARCliM ensemble is found to have a consistent cold bias throughout the year with many areas showing the ensemble members significantly agreeing on the bias. This bias is significant over most of southeast Australia in winter and summer. The ensemble also displays a consistent wet bias with most of southeast Australia showing significant agreement amongst ensemble members on this bias in summer and autumn. A dry bias is present on the southeast coast in winter
   The regional models are found to do a reasonably good job at capturing the teleconnections with large scale climate modes such as El Nino - Southern Oscillation (ENSO), when compared to the driving global data. Each regional model displays differing strengths and weaknesses in this respect.
C1 [Evans, J. P.; Olson, R.; Argueso, D.; Di Luca, A.] Univ New South Wales, Climate Change Res Ctr, Sydney, NSW, Australia.
   [Evans, J. P.; Olson, R.; Argueso, D.; Di Luca, A.] Univ New South Wales, ARC Ctr Excellence Climate Syst Sci, Sydney, NSW, Australia.
   [Fita, L.] Univ Paris 06, CNR, Lab Meteorol Dynam, Paris, France.
C3 University of New South Wales Sydney; University of New South Wales
   Sydney; ARC Centre of Excellence for Climate System Science; Sorbonne
   Universite; Institut Polytechnique de Paris; Ecole Polytechnique
RP Evans, JP (corresponding author), Univ New South Wales, Climate Change Res Ctr, Sydney, NSW, Australia.
EM jason.evans@unsw.edu.au
RI Di Luca, Alejandro/Y-4908-2019; Evans, Jason/F-3716-2011; Argüeso,
   Daniel/G-1970-2012
OI Di Luca, Alejandro/0000-0002-1481-2961
FU NSW Office of Environment and Heritage; Australian Government
FX The NARCliM project is funded and managed by the NSW Office of
   Environment and Heritage. This research was undertaken with the
   assistance of resources provided at the NCI National Facility systems at
   the Australian National University through the National Computational
   Merit Allocation Scheme supported by the Australian Government.
CR [Anonymous], 2009, Eos, Transactions American Geophysical Union, DOI [DOI 10.1029/2009EO360002, 10.1175/BAMS-D-11-00223.1]
   [Anonymous], THEORETICAL APPL CLI
   Argueso D, 2012, J CLIMATE, V25, P4883, DOI 10.1175/JCLI-D-11-00276.1
   Christensen JH, 2007, CLIMATIC CHANGE, V81, P1, DOI 10.1007/s10584-006-9211-6
   Déqué M, 2005, CLIM DYNAM, V25, P653, DOI 10.1007/s00382-005-0052-1
   Evans JP, 2014, GEOSCI MODEL DEV, V7, P621, DOI 10.5194/gmd-7-621-2014
   Evans JP, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2010JD013816
   Evans JP, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/044050
   Evans JP, 2013, CLIM RES, V56, P131, DOI 10.3354/cr01151
   Evans JP, 2012, J CLIMATE, V25, P7232, DOI 10.1175/JCLI-D-11-00616.1
   Evans JP, 2012, CLIM DYNAM, V39, P1241, DOI 10.1007/s00382-011-1244-5
   Evans JP, 2011, INT J CLIMATOL, V31, P1758, DOI 10.1002/joc.2206
   Evans JP, 2010, THEOR APPL CLIMATOL, V99, P389, DOI 10.1007/s00704-009-0151-8
   Evans JP, 2009, CLIMATIC CHANGE, V92, P417, DOI 10.1007/s10584-008-9438-5
   Evans JP, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2004JD005046
   Evans JP, 2004, INT J CLIMATOL, V24, P1671, DOI 10.1002/joc.1084
   Foley AM, 2010, PROG PHYS GEOG, V34, P647, DOI 10.1177/0309133310375654
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1547, DOI 10.1002/joc.1556
   Ji F, 2014, THEOR APPL CLIMATOL, V115, P297, DOI 10.1007/s00704-013-0904-2
   Jones DA, 2009, AUST METEOROL OCEAN, V58, P233, DOI 10.22499/2.5804.003
   Kalnay E, 1996, B AM METEOROL SOC, V77, P437, DOI 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
   Kendon EJ, 2010, J CLIMATE, V23, P6485, DOI 10.1175/2010JCLI3502.1
   Kostopoulou E, 2009, TELLUS A, V61, P357, DOI 10.1111/j.1600-0870.2009.00389.x
   Mariotti A, 2008, ENVIRON RES LETT, V3, DOI 10.1088/1748-9326/3/4/044001
   Meehl GA, 2007, B AM METEOROL SOC, V88, P1383, DOI 10.1175/BAMS-88-9-1383
   Solomon D., 2007, Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the IPCC
   van der Linden P, 2009, SUMMARY RES RESULTS
   Vavrus S, 2009, CLIM DYNAM, V33, P1099, DOI 10.1007/s00382-008-0475-6
   Zaitchik BF, 2007, J CLIMATE, V20, P3924, DOI 10.1175/JCLI4223.1
   Zaitchik BF, 2007, J CLIMATE, V20, P4133, DOI 10.1175/JCLI4248.1
NR 30
TC 0
Z9 0
U1 0
U2 0
PU MODELLING & SIMULATION SOC AUSTRALIA & NEW ZEALAND INC
PI CHRISTCHURCH
PA MSSANZ, CHRISTCHURCH, 00000, NEW ZEALAND
BN 978-0-9872143-5-5
PY 2015
BP 1531
EP 1536
PG 6
WC Computer Science, Interdisciplinary Applications; Operations Research &
   Management Science; Mathematics, Applied
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science; Operations Research & Management Science; Mathematics
GA BI2XC
UT WOS:000410535400219
DA 2025-01-10
ER

PT J
AU Zhang, YS
   Balzter, H
   Wu, XC
AF Zhang, Youshui
   Balzter, Heiko
   Wu, Xiongchang
TI Spatial-temporal patterns of urban anthropogenic heat discharge in
   Fuzhou, China, observed from sensible heat flux using Landsat TM/ETM
   plus data
SO INTERNATIONAL JOURNAL OF REMOTE SENSING
LA English
DT Article
ID ENERGY-BALANCE; SURFACE-TEMPERATURE; RADIATION BALANCE; CARBON-DIOXIDE;
   EVAPORATION; ASTER; WATER; AREA; IMPACT; FOREST
AB The urban heat island (UHI) effect is the phenomenon of increased surface temperatures in urban environments compared to their surroundings. It is linked to decreased vegetation cover, high proportions of artificial impervious surfaces, and high proportions of anthropogenic heat discharge. We evaluated the surface heat balance to clarify the contribution of anthropogenic heat discharges into the urban thermal environment. We used a heat balance model and satellite images (Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images acquired in 1989 and 2001), together with meteorological station data to assess the urban thermal environment in the city of Fuzhou, China. The objective of this study was to estimate the anthropogenic heat discharge in the form of sensible heat flux in complex urban environments. In order to increase the accuracy of the anthropogenic heat flux analysis, the sub-pixel fractional vegetation cover (FVC) was calculated by linear spectral unmixing. The results were then used to estimate latent heat flux in urban areas and to separate anthropogenic heat discharge from heat radiation due to insolation. Spatial and temporal distributions of anthropogenic heat flux were analysed as a function of land-cover type, percentage of impervious surface area, and FVC. The accuracy of heat fluxes was assessed using the ratios of sensible heat flux (H), latent heat flux (L), and ground heat flux (G) to net radiation (R-n), which were compared to the results from other studies. It is apparent that the contribution of anthropogenic heat is smaller in suburban areas and larger in high-density urban areas. However, seasonal disparities of anthropogenic heat discharge are small, and the variance of anthropogenic heat discharge is influenced by urban expansion, land-cover change, and increasing energy consumption. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban climate change adaptation strategies. Remote sensing can play a role in mapping the spatial and temporal patterns of UHIs and can differentiate the anthropogenic heat from the solar radiative fluxes. The findings presented here have important implications for urban development planning.
C1 [Zhang, Youshui; Wu, Xiongchang] Fujian Normal Univ, Coll Geog, Fuzhou 350007, Peoples R China.
   [Balzter, Heiko] Univ Leicester, Ctr Landscape & Climate Res, Leicester LE1 7RH, Leics, England.
   [Balzter, Heiko] Univ Leicester, Dept Geog, Leicester LE1 7RH, Leics, England.
C3 Fujian Normal University; University of Leicester; University of
   Leicester
RP Zhang, YS (corresponding author), Fujian Normal Univ, Coll Geog, Fuzhou 350007, Peoples R China.
EM zhangyoushui@sina.com
RI Balzter, Heiko/B-5976-2008
OI Balzter, Heiko/0000-0002-9053-4684
CR Amiri R, 2009, REMOTE SENS ENVIRON, V113, P2606, DOI 10.1016/j.rse.2009.07.021
   Anandakumar K, 1999, ATMOS ENVIRON, V33, P3911, DOI 10.1016/S1352-2310(99)00133-8
   [Anonymous], 1982, Evaporation Into the Atmosphere
   Bastiaanssen WGM, 1998, J HYDROL, V212, P198, DOI 10.1016/S0022-1694(98)00254-6
   Bastiaanssen WGM, 2000, J HYDROL, V229, P87, DOI 10.1016/S0022-1694(99)00202-4
   Campbell G.S., 1998, An introduction to environmental biophysics, V2nd, P286, DOI [10.1007/978-1-4612-1626-1, DOI 10.1007/978-1-4612-1626-1]
   Chander G, 2003, IEEE T GEOSCI REMOTE, V41, P2674, DOI 10.1109/TGRS.2003.818464
   CHOUDHURY BJ, 1986, AGR FOREST METEOROL, V37, P75, DOI 10.1016/0168-1923(86)90029-8
   Christen A, 2004, INT J CLIMATOL, V24, P1395, DOI 10.1002/joc.1074
   Chrysoulakis N, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2003JD003396
   Franks SW, 1997, J GEOPHYS RES-ATMOS, V102, P23991, DOI 10.1029/97JD02011
   Gay L. W., 1991, HYDROL INTERACTIONS, V204, P147
   Grimmond CSB, 2004, J GEOPHYS RES-ATMOS, V109, DOI 10.1029/2004JD004936
   GRIMMOND CSB, 1992, INT J CLIMATOL, V12, P481, DOI 10.1002/joc.3370120506
   Hansen S. V., 1993, 880225501 NM ARL US, P88002
   Hipps L. E., 1996, SCALING HYDROLOGY US, P113
   Ichinose T, 1999, ATMOS ENVIRON, V33, P3897, DOI 10.1016/S1352-2310(99)00132-6
   Iqbal M., 1983, INTRO SOLAR RAD
   JARVIS PG, 1976, PHILOS T ROY SOC B, V273, P593, DOI 10.1098/rstb.1976.0035
   KALMA JD, 1990, AGR FOREST METEOROL, V51, P223, DOI 10.1016/0168-1923(90)90110-R
   Kato S, 2005, REMOTE SENS ENVIRON, V99, P44, DOI 10.1016/j.rse.2005.04.026
   Kato S, 2007, REMOTE SENS ENVIRON, V110, P1, DOI 10.1016/j.rse.2007.02.011
   KELLIHER FM, 1995, AGR FOREST METEOROL, V73, P1, DOI 10.1016/0168-1923(94)02178-M
   KIMURA F, 1991, ATMOS ENVIRON B-URB, V25, P155, DOI 10.1016/0957-1272(91)90050-O
   Klysik K, 1996, ATMOS ENVIRON, V30, P3397, DOI 10.1016/1352-2310(96)00043-X
   Kondo J., 2000, ATMOSPHERIC SCI NEAR, P324
   Kondo J., 1994, Meteorology of the water environment: Water and heat balance of the Earth's surface, P350
   Kosugi Y., 1996, THESIS KYOTO U KYOTO
   Monteith JL, 1990, PRINCIPLES ENV PHYS, DOI DOI 10.1063/1.3128494
   Moriwaki R, 2004, J APPL METEOROL, V43, P1700, DOI 10.1175/JAM2153.1
   Nishida K, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD002062
   Offerle B, 2005, J CLIMATE, V18, P3983, DOI 10.1175/JCLI3520.1
   OKE TR, 1988, PROG PHYS GEOG, V12, P471, DOI 10.1177/030913338801200401
   PIELKE RA, 1983, B AM METEOROL SOC, V64, P243, DOI 10.1175/1520-0477(1983)064<0243:TUOAMN>2.0.CO;2
   Piringer M, 2002, URBAN AIR QUALITY - RECENT ADVANCES, PROCEEDINGS, P1
   Sailor DJ, 2007, ENVIRON MODELL SOFTW, V22, P1529, DOI 10.1016/j.envsoft.2006.11.005
   Sailor DJ, 2004, ATMOS ENVIRON, V38, P2737, DOI 10.1016/j.atmosenv.2004.01.034
   Schroeder TA, 2006, REMOTE SENS ENVIRON, V103, P16, DOI 10.1016/j.rse.2006.03.008
   Silberstein R, 2001, AGR FOREST METEOROL, V109, P79, DOI 10.1016/S0168-1923(01)00263-5
   Snyder WC, 1998, INT J REMOTE SENS, V19, P2753, DOI 10.1080/014311698214497
   Stull R. B., 1988, An Introduction to Boundary Layer Meteorology, P666, DOI DOI 10.1007/978-94-009-3027-8
   Tanaka H., 2000, Journal of the Japanese Forestry Society, V82, P259
   TODA M, 2000, J JPN SOC HYDROL WAT, V13, P276
   Wang JM, 1995, J METEOROL SOC JPN, V73, P1235, DOI 10.2151/jmsj1965.73.6_1235
   Weng QH, 2009, ISPRS J PHOTOGRAMM, V64, P335, DOI 10.1016/j.isprsjprs.2009.03.007
   White A. M., 2000, EARTH INTERACT, V4, P85
   Yasuda N., 1995, FUNDAMENTAL ATMOSPHE, P204
   Yuan F, 2007, REMOTE SENS ENVIRON, V106, P375, DOI 10.1016/j.rse.2006.09.003
   Zhang Xiaochuan, 1998, Journal of Agricultural Meteorology, V54, P1
   Zhang YS, 2009, INT J APPL EARTH OBS, V11, P256, DOI 10.1016/j.jag.2009.03.001
NR 50
TC 25
Z9 26
U1 5
U2 18
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 0143-1161
EI 1366-5901
J9 INT J REMOTE SENS
JI Int. J. Remote Sens.
PY 2013
VL 34
IS 4
BP 1459
EP 1477
DI 10.1080/01431161.2012.718465
PG 19
WC Remote Sensing; Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Remote Sensing; Imaging Science & Photographic Technology
GA 025QW
UT WOS:000310208000026
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Koomson, P
   Koomson, I
AF Koomson, Paul
   Koomson, Isaac
TI Toward vulnerability-responsive climate adaptation decision making:
   group inclusiveness as prime driver of local participation
SO CLIMATE AND DEVELOPMENT
LA English
DT Article; Early Access
DE Climate change; participatory adaptation; group inclusiveness;
   Communicative practices; CoP-BIS
ID PUBLIC-PARTICIPATION; GENDER; BELONGINGNESS; LIVELIHOODS; COMMUNITY;
   KNOWLEDGE
AB Although inclusive local participation in climate adaptation is touted as the panacea to ensure that project outcomes serve the needs of the most vulnerable, there is no objective measure for group inclusiveness. This study departs from the existing psycho-affective scales and employs principal factor analysis to compute a communicative practice-based inclusiveness scale (CoP-BIS). CoP-BIS measures group inclusiveness with five indicators-ideas solicitation, acknowledgment of views, views utilization, feedback provision, and member involvement. Ordinary least squares analytical procedure is applied to estimate the association between group inclusiveness and group members' participation in decision making, based on data from a survey with 225 respondents randomly sampled from farmers' and fishers' groups in Ghana's Effutu Municipality. We found that group inclusiveness has a statistically significant positive association with all three dimensions of participation (feeling encouraged to participate, willingness to make efforts to participate, and actual participation) in adaptation decision making at the 1% alpha level when other relevant factors are controlled for. Thus, fostering group inclusiveness through inclusive communicative practices is critical in promoting diverse participation in adaptation decision making. The implications for policy and practice are discussed.
C1 [Koomson, Paul] Francis Marion Univ, Dept Mass Commun, 11D CEMC,4822 E Palmetto St, Florence, SC 29506 USA.
   [Koomson, Isaac] Univ Queensland, Ctr Business & Econ Hlth, St Lucia, Qld, Australia.
   [Koomson, Isaac] Network Socioecon Res & Advancement NESRA, Accra, Ghana.
C3 University of Queensland
RP Koomson, P (corresponding author), Francis Marion Univ, Dept Mass Commun, 11D CEMC,4822 E Palmetto St, Florence, SC 29506 USA.
EM paulkoomson@gmail.com
RI Koomson, Isaac/S-8710-2019
OI Koomson, Isaac/0000-0002-2929-4992
FX This University of Oregon's IRB reviewed the study protocol and
   determined that it qualified for exemption. IRB Protocol Number:
   02102020.017
CR Adadan E, 2012, INT J SCI EDUC, V34, P513, DOI 10.1080/09500693.2011.636084
   Aikin SF, 2010, J APPL PHILOS, V27, P409, DOI 10.1111/j.1468-5930.2010.00494.x
   Akinsemolu AA, 2020, J CLEAN PROD, V246, DOI 10.1016/j.jclepro.2019.119015
   Akutse P., 2015, Baseline survey report for Winneba and Apam (GH2014ACT013SNV, P90
   Alhassan SI, 2019, INT J CLIM CHANG STR, V11, P195, DOI 10.1108/IJCCSM-10-2016-0156
   Alston M., 2018, Women and climate change in Bangladesh
   Ankrah J, 2018, OCEAN COAST MANAGE, V161, P141, DOI 10.1016/j.ocecoaman.2018.04.029
   Arora-Jonsson S, 2011, GLOBAL ENVIRON CHANG, V21, P744, DOI 10.1016/j.gloenvcha.2011.01.005
   Ashikali T, 2015, REV PUBLIC PERS ADM, V35, P146, DOI 10.1177/0734371X13511088
   Ayman R, 2010, AM PSYCHOL, V65, P157, DOI 10.1037/a0018806
   Bisaro A, 2010, ENVIRON SCI POLICY, V13, P637, DOI 10.1016/j.envsci.2010.08.004
   Buggy L, 2016, CLIM DEV, V8, P270, DOI 10.1080/17565529.2015.1041445
   Carr ER, 2008, GLOBAL ENVIRON CHANG, V18, P689, DOI 10.1016/j.gloenvcha.2008.06.004
   Chu E, 2016, CLIM POLICY, V16, P372, DOI 10.1080/14693062.2015.1019822
   Chu EK, 2018, URBAN STUD, V55, P1766, DOI 10.1177/0042098016686509
   Craney T. A., 2002, Quality Engineering, V14, P391, DOI 10.1081/QEN-120001878
   Davidson D, 2016, NAT CLIM CHANGE, V6, P433, DOI 10.1038/nclimate3007
   Derven Marjorie, 2014, Industrial and Commercial Training, V46, P84, DOI 10.1108/ICT-09-2013-0063
   DeWall CN, 2011, J PERS, V79, P979, DOI 10.1111/j.1467-6494.2010.00695.x
   Edmondson AC, 2014, ANNU REV ORGAN PSYCH, V1, P23, DOI 10.1146/annurev-orgpsych-031413-091305
   Ellemers N, 2013, PERS SOC PSYCHOL REV, V17, P3, DOI 10.1177/1088868312453086
   EMA, 2018, Effutu municipal assembly: Annual progress report for the year 2017
   EMA, 2020, Composite budget for 2020: Effutu Municipal Assembly
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   ETHIER KA, 1994, J PERS SOC PSYCHOL, V67, P243, DOI 10.1037/0022-3514.67.2.243
   Etikan I., 2016, American Journal of Theoretical and Applied Statistics, V5, P1, DOI [10.11648/j.ajtas.20160501.11, DOI 10.11648/J.AJTAS.20160501.11]
   Fabricius C., 2007, Water Policy, V9, P83
   Ferkany Matt, 2011, Philosophy of Education, V67, P331
   Few R, 2007, CLIM POLICY, V7, P46, DOI 10.1080/14693062.2007.9685637
   Fung A, 2006, PUBLIC ADMIN REV, V66, P66, DOI 10.1111/j.1540-6210.2006.00667.x
   Greenaway KH, 2015, GROUP PROCESS INTERG, V18, P173, DOI 10.1177/1368430214536063
   Heryana D.K., 2020, INT RES J MANAGEMENT, V7, P9, DOI [10.21744/irjmis.v7n2.854, DOI 10.21744/IRJMIS.V7N2.854]
   Hinneh S., 2016, GhanaWeb
   Hoogervorst N, 2012, LEADERSHIP QUART, V23, P883, DOI 10.1016/j.leaqua.2012.05.006
   Hsieh Chih-wei., 2006, Review of Public Personnel Administration, V26, P276, DOI DOI 10.1177/0734371X05281785
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jansen WS, 2020, EUR J SOC PSYCHOL, V50, P520, DOI 10.1002/ejsp.2633
   Jansen WS, 2014, EUR J SOC PSYCHOL, V44, P370, DOI 10.1002/ejsp.2011
   Johansen M, 2017, AM REV PUBLIC ADM, V47, P797, DOI 10.1177/0275074016634201
   Jost C, 2016, CLIM DEV, V8, P133, DOI 10.1080/17565529.2015.1050978
   Koomson D., 2022, EARTH SCI SYSTEMS SO, V2, P10052, DOI [https://doi.org/10.3389/esss.2022.10052, DOI 10.3389/ESSS.2022.10052]
   Koomson I, 2021, J DEV STUD, V57, P1912, DOI 10.1080/00220388.2021.1928641
   Koomson P., 2023, Power considerations as invisible filters of local Involvement in participatory climate adaptation: The case of Ghana's Effutu Municipality
   Koomson P, 2024, DEV PRACT, V34, P1058, DOI 10.1080/09614524.2024.2354473
   Koomson P, 2024, CLIM DEV, V16, P459, DOI 10.1080/17565529.2023.2236587
   KREJCIE RV, 1970, EDUC PSYCHOL MEAS, V30, P607, DOI 10.1177/001316447003000308
   Lahai JI, 2020, ROU CONTEMP AFR, P1
   Larson RB, 2019, INT J MARKET RES, V61, P534, DOI 10.1177/1470785318805305
   Latpate R., 2021, Advanced Sampling Methods
   Leary MR, 2000, ADV EXP SOC PSYCHOL, V32, P1, DOI 10.1016/S0065-2601(00)80003-9
   Lioubimtseva E, 2022, DISCOV SUSTAIN, V3, DOI 10.1007/s43621-022-00071-0
   Lund JF, 2015, FOREST POLICY ECON, V60, P1, DOI 10.1016/j.forpol.2015.07.009
   Lund JF, 2013, WORLD DEV, V46, P104, DOI 10.1016/j.worlddev.2013.01.028
   Mansuri Ghazala, 2013, Localizing Development: Does Participation Work?
   McCright AM, 2010, POPUL ENVIRON, V32, P66, DOI 10.1007/s11111-010-0113-1
   Melkote S. R., 2015, Communication for development: Theory and practice for empowerment and social justice, V3rd
   Mooi E., 2018, MARKET RES, DOI [10.1007/978-981-10-5218-7, DOI 10.1007/978-981-10-5218-7]
   Mor-Barak M.E., 2013, Managing diversity: Toward a globally inclusive workplace, V3rd ed.
   Munaretto S, 2014, ECOL SOC, V19, DOI 10.5751/ES-06381-190274
   Nelson A, 2021, REV PUBLIC PERS ADM, V41, P294, DOI 10.1177/0734371X19881681
   Phillips AW, 2016, MED TEACH, V38, P217, DOI 10.3109/0142159X.2015.1105945
   Russell DW, 2002, PERS SOC PSYCHOL B, V28, P1629, DOI 10.1177/014616702237645
   Schwartz SH, 2006, COMP SOCIOL, V5, P137, DOI 10.1163/156913306778667357
   Sen Roy S, 2018, SPRINGER CLIMATE, P1, DOI 10.1007/978-3-319-75777-3_1
   Shantz AFS, 2020, ACAD MANAGE J, V63, P503, DOI 10.5465/amj.2018.0335
   Shore LM, 2022, GROUP ORGAN MANAGE, V47, P723, DOI 10.1177/1059601121999580
   Smyth JD, 2010, AM BEHAV SCI, V53, P1423, DOI 10.1177/0002764210361695
   Sultana F, 2014, PROF GEOGR, V66, P372, DOI 10.1080/00330124.2013.821730
   Sundblad EL, 2007, J ENVIRON PSYCHOL, V27, P97, DOI 10.1016/j.jenvp.2007.01.003
   Takao Y, 2012, PAC AFF, V85, P767, DOI 10.5509/2012854767
   Tinel C, 2020, AM J TRANSPLANT, V20, P3462, DOI 10.1111/ajt.15959
   Tuominen M, 2022, SOC INDIC RES, V159, P617, DOI 10.1007/s11205-021-02762-z
   Uittenbroek CJ, 2019, J ENVIRON PLANN MAN, V62, P2529, DOI 10.1080/09640568.2019.1569503
   van der Geest S, 1997, AFRICA, V67, P534, DOI 10.2307/1161107
   Vohra N., 2015, VIKALPA, V40, P324, DOI [10.1177/0256090915601515, DOI 10.1177/0256090915601515]
NR 75
TC 0
Z9 0
U1 2
U2 2
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1756-5529
EI 1756-5537
J9 CLIM DEV
JI Clim. Dev.
PD 2024 JUN 20
PY 2024
DI 10.1080/17565529.2024.2368173
EA JUN 2024
PG 14
WC Development Studies; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology
GA WS5K8
UT WOS:001256874600001
DA 2025-01-10
ER

PT J
AU Qi, JJ
   Dauvergne, P
AF Qi, Jianfeng Jeffrey
   Dauvergne, Peter
TI China's rising influence on climate governance: Forging a path for the
   global South
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Global climate governance; China; Climate action; Developing countries;
   Climate adaptation; Low-carbon transition
ID POLITICS; BELT; ADAPTATION; RISE
AB China's influence on climate governance has been steadily increasing since the adoption of the Paris Agreement on climate change in 2015. Much of this influence, this article argues, has come from China forging a path for climate adaptation and mitigation for the global South. This is having far-reaching consequences, the article further argues, for the politics of global climate governance. China's discursive and diplomatic power in climate politics is growing as China builds alliances across the global South. China is leveraging this enhanced soft power to elevate the importance of adaptation in multilateral climate negotiations, advance a technocentric approach to climate mitigation, export its development model, and promote industrial-scale afforestation as a nature-based climate solution. China's strategy is enhancing climate financing, technology transfers, renewable power, and adaptation infrastructure across the global South. To some extent, this is helping with a transition to a lowcarbon world economy. Yet China's leadership is also reinforcing incremental, technocratic, and growthoriented solutions in global climate governance. These findings advance the understanding of China's role in global environmental politics, especially its growing influence on climate governance in the global South.
C1 [Qi, Jianfeng Jeffrey; Dauvergne, Peter] Univ British Columbia, Dept Polit Sci, C425-1866 Main Mall, Vancouver, BC V6T 1Z1, Canada.
C3 University of British Columbia
RP Dauvergne, P (corresponding author), Univ British Columbia, Dept Polit Sci, C425-1866 Main Mall, Vancouver, BC V6T 1Z1, Canada.
EM peter.dauvergne@ubc.ca
OI Dauvergne, Peter/0000-0003-2887-8168; Qi, Jianfeng
   Jeffrey/0000-0001-5676-6169
FU Social Sciences and Humanities Research Council of Canada
   [435-2014-0115]
FX This work was supported by a grant from the Social Sciences and
   Humanities Research Council of Canada (Grant No. 435-2014-0115).
CR Addaney M, 2020, CLIM CHANG MANAG, P481, DOI 10.1007/978-3-030-37425-9_25
   Allan JI, 2019, GLOBAL ENVIRON POLIT, V19, P4, DOI 10.1162/glep_a_00488
   Allan JI, 2013, THIRD WORLD Q, V34, P1307, DOI 10.1080/01436597.2013.831536
   Amanor K.S., 2013, 54 FAC
   Andonova LB, 2009, GLOBAL ENVIRON POLIT, V9, P52, DOI 10.1162/glep.2009.9.2.52
   [Anonymous], 2020, EASTDAY NEWS
   [Anonymous], 2020, WRONGED EMPIRE
   [Anonymous], 2021, THE GUARDIAN 1106
   [Anonymous], 2010, Spiegel
   [Anonymous], 2013, YALE ENV 360
   Ascensao F, 2018, NAT SUSTAIN, V1, P206, DOI 10.1038/s41893-018-0059-3
   Bernstein S, 2019, NAT CLIM CHANGE, V9, P919, DOI 10.1038/s41558-019-0618-2
   Blair R. A., 2018, 59 AIDDATA
   Blaxekjaer L. O., 2020, COALITIONS CLIMATE C, P113, DOI [https://doi.org/10.4324/9780429316258-9, DOI 10.4324/9780429316258-9]
   Bodansky D., 2018, Carbon and Climate Law Review, V12/, P184, DOI 10.21552/cclr/2018/3/4
   Bogojevic S, 2021, TRANSNATL ENVIRON LA, V10, P35, DOI 10.1017/S2047102520000278
   Brigc, 2020, BELT ROAD GREEN DEV
   BRIGC, 2020, BRI GREEN EN ENV AN
   BRIGC, 2020, Key Biodiversity Areas and Impact Assessment in BRI-Covered Areas
   BRIGC (Belt and Road Initiative International Green Development Coalition), 2019, BELT ROAD GREEN DEV
   Bulkeley H, 2014, TRANSNATIONAL CLIMATE CHANGE GOVERNANCE, P1, DOI 10.1017/CBO9781107706033
   Calliari E, 2019, CLIM RISK MANAGE POL, P155, DOI 10.1007/978-3-319-72026-5_6
   Carlson D, 2021, ENERG POLICY, V155, DOI 10.1016/j.enpol.2021.112350
   Castro P., 2020, COALITIONS CLIMATE C, P17
   CCICED, 2020, Policy Studies Release
   Chaney E., 2021, CONTRADICTIONS COMPA
   China Development Bank UNDP, 2019, HARM INV FIN STAND S
   Ciplet D, 2013, GLOBAL ENVIRON POLIT, V13, P49, DOI 10.1162/GLEP_a_00153
   Coen D., 2020, Global climate governance
   Colenbrander S., 2021, Five Expert Views on China's Pledge to Become Carbon Neutral by 2060
   Collard RC, 2015, ENVIRON HUMANITIES, V7, P227, DOI 10.1215/22011919-3616425
   Colman Z., 2021, POLITICO
   Cousins JJ, 2021, ECOL ECON, V180, DOI 10.1016/j.ecolecon.2020.106874
   Dauvergne P., 2021, GLOBAL GOVERNANCE FU, P26
   Dauvergne P, 2022, REV INT POLIT ECON, V29, P696, DOI 10.1080/09692290.2020.1814381
   Dauvergne P, 2010, GLOBAL ENVIRON POLIT, V10, P1, DOI 10.1162/glep.2010.10.2.1
   Dauvergne Peter., 2016, Environmentalism of the Rich
   Dimitrov RS, 2016, GLOBAL ENVIRON POLIT, V16, P1, DOI 10.1162/GLEP_a_00361
   Dimitrov RS, 2010, GLOBAL ENVIRON POLIT, V10, P18, DOI 10.1162/glep.2010.10.2.18
   Dossani R., 2020, WR1338 RAND CORP, DOI [10.7249/WR1338, DOI 10.7249/WR1338]
   Downie C, 2018, GLOB POLICY, V9, P398, DOI 10.1111/1758-5899.12550
   Dubash NK, 2016, EARTH SYST GOV-SER, P315
   EbA South (Ecosystem-based Adaptation through South-South Cooperation), 2021, ECOSYSTEM BASED ADAP
   Engels A, 2018, PALGR COMMUN, V4, DOI 10.1057/s41599-018-0150-4
   FECC (Foreign Economic Cooperation Center), 2018, TRIP AGR CHIN FAO SR
   Fijalkowski L, 2011, J CONTEMP AFR STUD, V29, P223, DOI 10.1080/02589001.2011.555197
   Fish M.S., 2016, OXFORD HDB POLITICS, P1, DOI [10.1093/oxfordhb/9780199845156.013.1, DOI 10.1093/OXFORDHB/9780199845156.013.1]
   Freeman D, 2020, ROUT STUD COMP ASI P, P174
   Gao Z., 2018, STUDY TIMES
   Garca-Herrero A., 2019, COUNTRIESPERCEPTIONS
   GCA (Global Commission on Adaptation), 2021, GCA CHIN
   GCF (Green Climate Fund), 2019, FP082 GCF
   Green BRI Center, 2021, GREEN INFRASTRUCTURE
   Gu A, 2020, ECOSYST HEALTH SUST, V6, DOI 10.1080/20964129.2020.1747947
   Hansen MH, 2018, GLOBAL ENVIRON CHANG, V53, P195, DOI 10.1016/j.gloenvcha.2018.09.014
   Harris RL, 2016, J DEV SOC, V32, P508, DOI 10.1177/0169796X16674108
   Harvey F., 2020, THE GUARDIAN 0922
   IEA, 2021, GLOB EN REV, DOI DOI 10.1787/39351842-EN
   IISD-ENB, 2019, EARTH NEGOTIATIONS B, V12
   IISD-ENB (International Institute for Sustainable Development and Earth Negotiation Bulletin), 2018, EARTH NEGOTIATIONS B, V12
   Jackson MM, 2021, ENERGY SUSTAIN DEV, V60, DOI 10.1016/j.esd.2020.12.006
   Jagers SC, 2003, GLOB GOV, V9, P385, DOI 10.1163/19426720-00903009
   Keohane Robert., 2010, The Regime Complex for Climate Change, P10
   Klawitter N., 2021, SPIEGEL WIRTSCHAFT
   Lawrence M., 2019, China's High-Speed Rail Development, DOI [DOI 10.1596/978-1-4648-1425-9, DOI 1476316/CHINAS-HIGH-SPEED-RAIL-DEVELOPMENT]
   Li CL, 2020, ISL STUD J, V15, P173, DOI 10.24043/isj.134
   Li HM, 2020, INT REV, V3, P57
   Li Q., 2019, Int. Forum, V6, P3
   Li S., 2021, CONT WORLD, V05, P10, DOI [10.19422/j.cnki.ddsj.2021.05.002, DOI 10.19422/J.CNKI.DDSJ.2021.05.002]
   Li X, 2019, FOREIGN AFFAIRS REV, V36, P32, DOI [10.13569/j.cnki.far.2019.04.032, DOI 10.13569/J.CNKI.FAR.2019.04.032]
   Lin J.Y., 2017, Going beyond aid: Development cooperation for structural transformation, DOI DOI 10.1017/9781316597354
   Liu J., 2021, CarbonBrief
   Liu L, 2019, ASIA EUR J, V17, P243, DOI 10.1007/s10308-018-00530-2
   Liu L, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.483
   Liu MS, 2021, J CHIN GOV, V6, P417, DOI 10.1080/23812346.2020.1721230
   Liu S., 2018, ADV CLIM CHANG RES, V14, P210, DOI [10.12006/j.issn.1673-1719.2017.169, DOI 10.12006/J.ISSN.1673-1719.2017.169]
   Liu Y., 2017, TRANSCR MIN FOR AFF
   [刘迎春 Liu Yingchun], 2019, [生态学报, Acta Ecologica Sinica], V39, P4002
   Lo K, 2015, ENVIRON SCI POLICY, V54, P152, DOI 10.1016/j.envsci.2015.06.001
   Lo V., 2016, UN CONV BIOL DIV
   Lu F, 2018, P NATL ACAD SCI USA, V115, P4039, DOI 10.1073/pnas.1700294115
   Luoma J., 2012, YALE ENV 360
   Mallapaty S, 2020, NATURE, V586, P482, DOI 10.1038/d41586-020-02927-9
   Maller C, 2021, CITIES, V113, DOI 10.1016/j.cities.2021.103155
   McBeath Jerry., 2008, AM J CHINESE STUDIES, V15, P1
   MEE, 2020, MEM UND SIGN CER CHI
   Mee, 2019, CHIN POL ACT CLIM CH
   MEE, 2021, CHIN POL ACT CLIM CH
   MEE, 2017, CHIN POL ACT CLIM CH
   MEE, 2021, MIN EC ENV HUANG RUN
   MEE, 2020, VIRT M MIN EC ENV NO
   MEE, 2016, CHIN POL ACT CLIM CH
   MEE, 2021, 30 BASIC MIN M CLIM
   MEE, 2021, LET GREEN WAT GREEN
   MEE, 2020, CHIN AFR ENV COOP CT
   MEE, 2020, 29 BASIC MIN M CLIM
   MEE, 2018, CHIN POL ACT CLIM CH
   Mee, 2019, CHIN CLIM ACT CONS D
   MEE, 2019, S S COOP MICR ADDR C
   MEE, 2021, MIN EC ENV HELD M MI
   MEE, 2021, GUID OP COORD STRENG
   MEE (Ministry of Ecology and Environment of China), 2015, CHIN POL ACT CLIM CH
   Meng SS, 2020, J HYDROL, V591, DOI 10.1016/j.jhydrol.2020.125689
   MFA, 2020, CHIN BOTSW SIGN MEM
   MFA, 2021, XI JP INTERVENTION 7
   MFA, 2021, FOR MIN SPOK HUA CHU
   Mills A., 2015, GREEN WALL HEART TAK
   Monheim K., 2014, EFFECTIVE NEGOTIATIO, DOI [10.4324/9781315757070, DOI 10.4324/9781315757070]
   Myers SL., 2020, The New York Times
   Nature4Climate, 2019, NATURE BASED SOLUTIO
   NCCCP (National Congress of the Chinese Communist Party), 2017, NATL C CHINESE COMMU
   NCSC, 2020, RES CHIN STRAT COUNT
   NCSC (National Center for Climate Change Strategy and International Cooperation), 2015, GLOB GOV CLIM CHANG
   NDRC, 2020, SEEK BUILD GLOB EC C
   NDRC, 2017, 58 ENVINT NAT DEV RE
   NDRC (National Development and Reform Commission of the People's Republic of China), 2013, NAT AD STRAT 2013 20
   Newell P., 2021, POWER SHIFT GLOBAL P
   Ngounou B., 2020, AFRIK 21 1203
   Nye JS, 2008, ANN AM ACAD POLIT SS, V616, P94, DOI 10.1177/0002716207311699
   PAAGGW (Pan-African Agency of the Great Green Wall), 2017, MEM COOP PAAGGW XINJ
   Pearson MM, 2019, HBK RES INT POLIT EC, P411
   Pu XY, 2018, CHIN POLITICAL SCI R, V3, P48, DOI 10.1007/s41111-017-0079-6
   Qin YQ, 2014, CHIN J INT POLIT, V7, P285, DOI 10.1093/cjip/pou034
   Rathi A., 2021, Bloomberg News
   Runqiu Huang, 2021, 12 PET CLIM DIAL MIN
   Schreurs M.A., 2018, NATL PATHWAYS LOW CA, P169
   Schulz F., 2021, DER TAGESSPIEGEL
   Shepard Wade., 2020, Forbes
   State Council, 2021, CHIN INT DEV COOP NE
   State Council, 2017, ENH CHIN DISC POW IN
   State Council, 2021, NOT STAT COUNC ISS A
   State Council, 2020, PROGR REP CHIN EN RE
   State Council, 2021, The 14th five year plan for national economic and social development of the people's Republic of China and the outline of long-term objectives for 2035
   Stevenson H, 2012, ENVIRON POLIT, V21, P189, DOI 10.1080/09644016.2012.651898
   Su C., 2018, CHINANEWS 1209
   Su M., 2014, COUNTRY BRIEF CLIMAT
   Sun Y., 2016, Rising Powers Quarterly, V1, P43
   Sutter RobertG., 2016, Chinese Foreign Relations: Power and Policy since the Cold War, VFourth
   Townsend J, 2020, FACETS, V5, P551, DOI 10.1139/facets-2019-0058
   Trombetta MJ, 2019, CHINA Q INT STRATEG, V5, P97, DOI 10.1142/S2377740019500076
   UNCCD, 2020, GREAT GREEN WALL INI
   UNEP, 2020, CHIN UNEP PARTN PROM
   UNEP (United Nations Environment Programme), 2019, COMP CONTR NAT BAS S
   UNEP-IEMP, 2019, JOINT RES PRACT TECH
   UNEP-IEMP (United Nations Environment Programme-China International Ecosystem Management Partnership), 2018, ECOSYSTEM BASED ADAP
   UNFCCC, 2021, INF STOCKT PLEN PRES
   UNFCCC (United Nations Framework Convention on Climate Change), 2019, 25 YEARS AD UNFCCC R
   United Nations, 2019, GAEF3516 UN DEP EC S
   Urban F, 2018, ENERG POLICY, V113, P320, DOI 10.1016/j.enpol.2017.11.007
   Vadell J, 2014, REV BRAS POLIT INT, V57, P91, DOI 10.1590/0034-7329201400206
   Wallace-Wells David, 2019, The Uninhabitable Earth: Life after Warming
   Wang C, 2018, RENEW SUST ENERG REV, V81, P1350, DOI 10.1016/j.rser.2017.05.099
   Wang XM, 2010, J ARID ENVIRON, V74, P13, DOI 10.1016/j.jaridenv.2009.08.001
   Wang-Kaeding H., 2021, China's environmental foreign relations
   Weigel M., 2021, The Palgrave Handbook of Development Cooperation for Achieving the 2030 Agenda, P605, DOI [10.1007/978-3-030-57938-828, DOI 10.1007/978-3-030-57938-828]
   World Bank, 2021, IND GDP CURR US
   Xie Z., 2021, BJX CLIMATE
   Xie ZH, 2020, ENVIRON SCI ECOTECH, V1, DOI 10.1016/j.ese.2019.100001
   Xinhua, 2019, XINHUA NEWS AGENCY
   Xinhua, 2017, XINHUA NEWS AGENCY
   Xinhua, 2016, XINHUA NEWS AGENCY
   XU L., 2021, CHINESE PERSPECTIVE, P69, DOI [10.1163/9789004439436_006, DOI 10.1163/9789004439436_006]
   Ye Q., 2020, THE PEOPLES DAILY
   Yu HY, 2019, CHINA Q INT STRATEG, V5, P417, DOI 10.1142/S2377740019500246
   Zhang L, 2021, ECOSYST HEALTH SUST, V7, DOI 10.1080/20964129.2020.1868272
   Zhang XL, 2020, APPL ENERG, V279, DOI 10.1016/j.apenergy.2020.115858
   Zhao KJ, 2016, CHIN POLITICAL SCI R, V1, P539, DOI 10.1007/s41111-016-0037-8
   Zhen L., 2017, MULTIFUNCTIONAL LAND, P29, DOI 10.1007/978-3-319-54957-6_3
   [郑秋红 Zheng Qiuhong], 2020, [中国人口·资源与环境, China Population Resources and Environment], V30, P10
   Zhu YC, 2011, J CHIN POLIT SCI, V16, P123, DOI 10.1007/s11366-011-9140-8
NR 170
TC 32
Z9 32
U1 32
U2 143
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD MAR
PY 2022
VL 73
AR 102484
DI 10.1016/j.gloenvcha.2022.102484
EA FEB 2022
PG 13
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 1D3XV
UT WOS:000793737900011
DA 2025-01-10
ER

PT J
AU Doss-Gollin, J
   Farnham, DJ
   Steinschneider, S
   Lall, U
AF Doss-Gollin, James
   Farnham, David J.
   Steinschneider, Scott
   Lall, Upmanu
TI Robust Adaptation to Multiscale Climate Variability
SO EARTHS FUTURE
LA English
DT Article
DE climate adaptation; climate change; climate dynamics; robust decisions
ID FLOOD RISK; EL-NINO; WAVELET; MODEL; TIME; STATIONARITY; PREDICTABILITY;
   OSCILLATION; INFERENCE; IMPACTS
AB The assessment and implementation of structural or financial instruments for climate risk mitigation requires projections of future climate risk over the operational life of each proposed instrument. A point often neglected in the climate adaptation literature is that the physical sources of predictability differ between projects with long and short planning periods: While historical and paleo climate records emphasize low-frequency modes of variability, anthropogenic climate change is expected to alter their occurrence at longer time scales. In this paper we present a set of stylized experiments to assess the uncertainties and biases involved in estimating future climate risk over a finite future period, given a limited observational record. These experiments consider both quasi-periodic and secular change for the underlying risk, as well as statistical models for estimating this risk from an N-year historical record. The uncertainty of IPCC-like future scenarios is considered through an equivalent sample size N. The relative importance of estimating short- or long-term risk depends on the investment life M. Shorter design lives are preferred for situations where interannual to decadal variability can be successfully identified and predicted, highlighting the importance of sequential investment strategies for adaptation.
C1 [Doss-Gollin, James; Farnham, David J.; Lall, Upmanu] Columbia Univ, Dept Earth & Environm Engn, New York, NY 10027 USA.
   [Doss-Gollin, James; Farnham, David J.; Lall, Upmanu] Columbia Univ, Columbia Water Ctr, New York, NY 10027 USA.
   [Steinschneider, Scott] Cornell Univ, Dept Biol & Environm Engn, Ithaca, NY USA.
C3 Columbia University; Columbia University; Cornell University
RP Doss-Gollin, J (corresponding author), Columbia Univ, Dept Earth & Environm Engn, New York, NY 10027 USA.; Doss-Gollin, J (corresponding author), Columbia Univ, Columbia Water Ctr, New York, NY 10027 USA.
EM james.doss-gollin@columbia.edu
RI Doss-Gollin, James/J-4273-2014; Lall, Upmanu/B-7992-2009
OI Lall, Upmanu/0000-0003-0529-8128; Steinschneider,
   Scott/0000-0002-8882-1908; Doss-Gollin, James/0000-0002-3428-2224;
   Farnham, David J./0000-0002-6690-4251
FU NSF GRFP program [DGE 16-44869]; SERDP program [2516]
FX The authors thank Celine Mari, Alberto Montanari, and one anonymous
   reviewer for comments which greatly improved this manuscript. The
   authors thank Nandini Ramesh of Columbia University for providing the
   synthetic NINO3 index from a 100,000-year run of the Cane-Zebiak model
   as described in Ramesh et al. (2016). The authors thank John High of the
   U.S. Army Corps of Engineers for providing the naturalized daily
   streamflows at the Folsom Dam. J. D. G. thanks the NSF GRFP program
   (grant DGE 16-44869: "Understanding & Predicting Climate Drivers of
   Extreme, Mid-latitude River Floods") and SERDP program (grant 2516: "
   Climate Informed Estimation of Hydrologic Extremes for Robust Adaptation
   to Non-Stationary Climate") for support. All codes and data used to
   generate this paper are available in a live repository
   (https://github.com/jdossgollin/2018-robust-adaptation-cyclical-risk/)
   and a permanent archive (https://doi.org/10.5281/zenodo.1294280).
CR 197;ngstrom A., 1935, GEOGR ANN, V17, P242, DOI DOI 10.1080/20014422.1935.11880600
   [Anonymous], 2011, The no-u-turn sampler: Adaptively setting path lengths in hamiltonian monte carlo
   [Anonymous], 2010, The El Nino-Southern Oscillation Phenomenon
   [Anonymous], TECH REP
   [Anonymous], 2013, The Weather and Climate: Emergent Laws and Multifractal Cascades
   Barnes EA, 2015, WIRES CLIM CHANGE, V6, P277, DOI 10.1002/wcc.337
   Beran J., 1994, Statistics for long memory process, Vvol. 61
   Betancourt Michael, 2017, ARXIV
   BHATTACHARYA RN, 1983, J APPL PROBAB, V20, P649, DOI 10.2307/3213900
   Blöschl G, 2010, HYDROL PROCESS, V24, P374, DOI 10.1002/hyp.7574
   Borgomeo E, 2018, EARTHS FUTURE, V6, P468, DOI 10.1002/2017EF000730
   Bracken C, 2016, WATER RESOUR RES, V52, P7837, DOI 10.1002/2016WR018887
   Brown C, 2010, J WATER RES PLAN MAN, V136, P143, DOI 10.1061/(ASCE)WR.1943-5452.65
   Bullmore ET, 2001, HUM BRAIN MAPP, V12, P61, DOI 10.1002/1097-0193(200102)12:2<61::AID-HBM1004>3.0.CO;2-W
   Carpenter Bob, 2017, J Stat Softw, V76, DOI 10.18637/jss.v076.i01
   Chamoli A, 2007, COMPUT GEOSCI-UK, V33, P83, DOI 10.1016/j.cageo.2006.05.008
   City of New York, 2013, TECH REP
   Cook ER, 2010, J QUATERNARY SCI, V25, P48, DOI 10.1002/jqs.1303
   Coumou D, 2012, NAT CLIM CHANGE, V2, P491, DOI 10.1038/NCLIMATE1452
   Delgado JM, 2014, NAT HAZARD EARTH SYS, V14, P1579, DOI 10.5194/nhess-14-1579-2014
   Di Baldassarre G, 2018, HYDROL EARTH SYST SC, V22, P5629, DOI 10.5194/hess-22-5629-2018
   Dittes B., 2017, HYDROLOGICAL EARTH S, V22, P1, DOI [10.5194/hess-2017-576, DOI 10.5194/HESS-2017-576]
   Dugan PJ, 2010, AMBIO, V39, P344, DOI 10.1007/s13280-010-0036-1
   Farnham DJ, 2018, WATER RESOUR RES, V54, P3809, DOI 10.1002/2017WR021318
   Feng H, 2005, COMMUN STAT-SIMUL C, V34, P393, DOI 10.1081/SAC-200055722
   GEI Consultants Inc, 2017, TECH REP
   Gelman A, 2017, ENTROPY-SWITZ, V19, DOI 10.3390/e19100555
   Geweke J., 1983, Journal of time series analysis, V4, P221, DOI DOI 10.1111/J.1467-9892.1983.TB00371.X
   Haasnoot M, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/10/105008
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Held IM, 2005, B AM METEOROL SOC, V86, P1609, DOI 10.1175/BAMS-86-11-1609
   Hodgkins GA, 2017, J HYDROL, V552, P704, DOI 10.1016/j.jhydrol.2017.07.027
   Hoyer S., 2017, Journal of Open Research Software, V5, P10, DOI [10.5334/jors.148, DOI 10.5334/JORS.148]
   Hunter JD, 2007, COMPUT SCI ENG, V9, P90, DOI 10.1109/MCSE.2007.55
   Jain S, 2001, WATER RESOUR RES, V37, P3193, DOI 10.1029/2001WR000495
   JIN FF, 1994, SCIENCE, V264, P70, DOI 10.1126/science.264.5155.70
   Jones E., 2001, SciPy: Open source scientific tools for Python
   Jongman B, 2012, GLOBAL ENVIRON CHANG, V22, P823, DOI 10.1016/j.gloenvcha.2012.07.004
   Kiem AS, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2002GL015992
   Koutsoyiannis D, 2003, HYDROLOG SCI J, V48, P3, DOI 10.1623/hysj.48.1.3.43481
   Kwon H.-H., 2007, WATER RESOUR RES, V43, P1, DOI [DOI 10.1029/2006WR005258, 10.1029/2006WR005258]
   Lempert RJ, 2007, RISK ANAL, V27, P1009, DOI 10.1111/j.1539-6924.2007.00940.x
   Lima CHR, 2016, J HYDROL, V541, P816, DOI 10.1016/j.jhydrol.2016.07.042
   Lovejoy S, 2012, GEOPHYS MONOGR SER, V196, P231, DOI 10.1029/2011GM001087
   Lovejoy S., 2013, EOS T AM GEOPHYS UN, V94, P1, DOI DOI 10.1002/2013EO010001
   MANDELBR.BB, 1969, WATER RESOUR RES, V5, P967, DOI 10.1029/WR005i005p00967
   MANDELBROT BB, 1985, PHYS SCRIPTA, V32, P257, DOI 10.1088/0031-8949/32/4/001
   Mantua NJ, 1997, B AM METEOROL SOC, V78, P1069, DOI 10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2
   Markonis Y, 2013, SURV GEOPHYS, V34, P181, DOI 10.1007/s10712-012-9208-9
   Maruyama F., 2018, Journal of Applied Mathematics and Physics, V06, P1301, DOI DOI 10.4236/JAMP.2018.66109
   McKinney W., 2010, P 9 PYTH SCI ID AUST
   Merz B, 2014, NAT HAZARD EARTH SYS, V14, P1921, DOI 10.5194/nhess-14-1921-2014
   Merz R, 2008, WATER RESOUR RES, V44, DOI 10.1029/2007WR006744
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Montanari A, 2003, THEORY AND APPLICATIONS OF LONG-RANGE DEPENDENCE, P461
   Montanari A, 2014, WATER RESOUR RES, V50, P9748, DOI 10.1002/2014WR016092
   Müller B, 2014, SOL ENERGY, V99, P272, DOI 10.1016/j.solener.2013.11.013
   Newman M, 2016, J CLIMATE, V29, P4399, DOI 10.1175/JCLI-D-15-0508.1
   O'Connell PE, 2016, HYDROLOG SCI J, V61, P1571, DOI 10.1080/02626667.2015.1125998
   O'Gorman PA, 2009, P NATL ACAD SCI USA, V106, P14773, DOI 10.1073/pnas.0907610106
   Palmer T., 1993, Weather, V48, P314
   Papakonstantinou V., 2016, TECH REP
   Peduzzi P, 2012, NAT CLIM CHANGE, V2, P289, DOI 10.1038/NCLIMATE1410
   Powers K., 2003, RL31976 C RES SERV
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Ramesh N, 2017, CLIM DYNAM, V49, P2291, DOI 10.1007/s00382-016-3446-3
   Roesch A., 2016, WaveletComp: Computational wavelet analysis
   RojoHernandez J. D., 2017, AGU FALL M, V41
   ROPELEWSKI CF, 1987, MON WEATHER REV, V115, P1606, DOI 10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2
   Salas JD, 2018, HYDROLOG SCI J, V63, P325, DOI 10.1080/02626667.2018.1426858
   Schreiber Jacob, 2017, The Journal of Machine Learning Research, V18, P5992
   Schuster-Bockler Benjamin, 2007, Curr Protoc Bioinformatics, VAppendix 3, p3A, DOI 10.1002/0471250953.bia03as18
   Selvam AM, 2017, PURE APPL GEOPHYS, V174, P413, DOI 10.1007/s00024-016-1394-9
   Serinaldi F, 2015, ADV WATER RESOUR, V77, P17, DOI 10.1016/j.advwatres.2014.12.013
   Shaw TA, 2016, NAT GEOSCI, V9, P656, DOI [10.1038/ngeo2783, 10.1038/NGEO2783]
   Simonsen I, 1998, PHYS REV E, V58, P2779, DOI 10.1103/PhysRevE.58.2779
   Simpson D, 2017, STAT SCI, V32, P1, DOI 10.1214/16-STS576
   Sodastrom E., 1999, Land and Water Law Review, V34, P1
   Spence CM, 2016, WATER RESOUR RES, V52, P8650, DOI 10.1002/2016WR018981
   Swierczynski T, 2012, GEOLOGY, V40, P1047, DOI 10.1130/G33493.1
   Torrence C, 1998, B AM METEOROL SOC, V79, P61, DOI 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
   Trenberth KE, 2003, B AM METEOROL SOC, V84, P1205, DOI 10.1175/BAMS-84-9-1205
   USACE, 2007, TECH REP
   van der Walt S, 2011, COMPUT SCI ENG, V13, P22, DOI 10.1109/MCSE.2011.37
   Walker WE, 2013, SUSTAINABILITY-BASEL, V5, P955, DOI 10.3390/su5030955
   Ward PJ, 2014, P NATL ACAD SCI USA, V111, P15659, DOI 10.1073/pnas.1409822111
   Woollings T, 2015, CLIM DYNAM, V45, P539, DOI 10.1007/s00382-014-2237-y
   ZEBIAK SE, 1987, MON WEATHER REV, V115, P2262, DOI 10.1175/1520-0493(1987)115<2262:AMENO>2.0.CO;2
   Zivkovic T, 2013, J GEOPHYS RES-ATMOS, V118, P2161, DOI 10.1002/jgrd.50190
NR 89
TC 18
Z9 22
U1 1
U2 4
PU AMER GEOPHYSICAL UNION
PI WASHINGTON
PA 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA
EI 2328-4277
J9 EARTHS FUTURE
JI Earth Future
PD JUL
PY 2019
VL 7
IS 7
BP 734
EP 747
DI 10.1029/2019EF001154
PG 14
WC Environmental Sciences; Geosciences, Multidisciplinary; Meteorology &
   Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric
   Sciences
GA IO3KV
UT WOS:000479280100004
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Bastidas-Arteaga, E
   Stewart, MG
AF Bastidas-Arteaga, Emilio
   Stewart, Mark G.
TI Damage risks and economic assessment of climate adaptation strategies
   for design of new concrete structures subject to chloride-induced
   corrosion
SO STRUCTURAL SAFETY
LA English
DT Article
DE Reliability; Climate change; Adaptation; Benefit-to-cost ratio; Chloride
   ingress; Reinforced concrete
ID RC STRUCTURES; TIME; MAINTENANCE; RELIABILITY; DURABILITY; INITIATION;
   MODEL
AB Reinforced concrete (RC) structures are subject to environmental actions affecting their performance, serviceability and safety. Among these actions, chloride ingress leads to corrosion initiation and its interaction with service loading could reduce its operational life. Experimental evidence indicates that chloride ingress is highly influenced by weather conditions in the surrounding environment and therefore by climate change. Consequently, both structural design and maintenance should be adapted to these new environmental conditions. This work focuses on the assessment of the costs and benefits of two climate adaptation strategies for new RC structures placed in chloride-contaminated environments under various climate change scenarios. Their cost-effectiveness is measured in terms of the benefit-to-cost ratio (BCR) and the probability that BCR exceeds unity -i.e., Pr(BCR > 1). It was found that increasing concrete strength grade is more cost-effective than increasing design cover. The results also indicate that the cost-effectiveness of a given adaptation strategy depends mainly on the type of structural component, exposure conditions and climate change scenarios. (C) 2014 Elsevier Ltd. All rights reserved.
C1 [Bastidas-Arteaga, Emilio] Univ Nantes, LUNAM Univ, Ecole Cent Nantes,CNRS,UMR 6183,FR 3473, GeM,Inst Res Civil & Mech Engn,Sea & Littoral Res, Nantes, France.
   [Stewart, Mark G.] Univ Newcastle, Ctr Infrastruct Performance & Reliabil, Callaghan, NSW 2308, Australia.
C3 Centre National de la Recherche Scientifique (CNRS); CNRS - Institute
   for Engineering & Systems Sciences (INSIS); Nantes Universite; Ecole
   Centrale de Nantes; University of Newcastle
RP Bastidas-Arteaga, E (corresponding author), Univ Nantes, LUNAM Univ, Ecole Cent Nantes,CNRS,UMR 6183,FR 3473, GeM,Inst Res Civil & Mech Engn,Sea & Littoral Res, Nantes, France.
EM emilio.bastidas@univ-nantes.fr; mark.stewart@newcastle.edu.au
RI Stewart, Mark/G-7415-2013; Bastidas-Arteaga, Emilio/A-6090-2012
OI Bastidas-Arteaga, Emilio/0000-0002-7370-5218; Stewart,
   Mark/0000-0001-6887-6533
FU University of Nantes
FX Some of this work was undertaken while the Professor Mark G. Stewart was
   visiting the Institute for Research in Civil and Mechanical Engineering
   at the University of Nantes. The support of the University of Nantes for
   funding this position of Visiting Scholar is gratefully acknowledged.
CR Akita H, 1997, MAG CONCRETE RES, V49, P129, DOI 10.1680/macr.1997.49.179.129
   Andrade C, 2002, CEMENT CONCRETE COMP, V24, P55, DOI 10.1016/S0958-9465(01)00026-9
   [Anonymous], CORROSION COSTS PREV
   [Anonymous], RES LIF MOD CONCR RE
   [Anonymous], 1985, CIVIL ENG TS
   [Anonymous], 2014, CLIMATE CHANGE 2014, V80, P1
   [Anonymous], ROL REG FAC CONSTR A
   [Anonymous], INT C SAF RISK RE RE
   [Anonymous], RSMEANS BUILD CONSTR
   [Anonymous], MOD DEGR DURACRETE P
   [Anonymous], EUR 1 2 BAS DES ACT
   [Anonymous], BEST PRACT REG HDB
   [Anonymous], SAFETY RELIAB RISK L
   [Anonymous], SERVICE LIFE MODELS
   Bastidas-Arteaga E, 2011, ENG STRUCT, V33, P720, DOI 10.1016/j.engstruct.2010.11.008
   Bastidas-Arteaga E, 2010, STRUCT SAF, V32, P238, DOI 10.1016/j.strusafe.2010.03.002
   Bastidas-Arteaga E, 2013, ENG STRUCT, V51, P259, DOI 10.1016/j.engstruct.2013.01.006
   Bastidas-Arteaga E, 2012, ENG STRUCT, V41, P50, DOI 10.1016/j.engstruct.2012.03.011
   Boardman AE, 2011, J BENEFIT-COST ANAL, V2, DOI 10.2202/2152-2812.1050
   Canisius TDG, 2004, P I CIVIL ENG-STR B, V157, P149
   de Larrard T, 2014, CIV ENG ENVIRON SYST, V31, P153, DOI 10.1080/10286608.2014.913033
   DEQUE M, 1994, CLIM DYNAM, V10, P249, DOI 10.1007/BF00208992
   Duracrete, 2000, Statistical quantification of the variables in the limit state functions
   El Maaddawy T, 2007, CEMENT CONCRETE COMP, V29, P168, DOI 10.1016/j.cemconcomp.2006.11.004
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Inman M, 2011, NAT CLIM CHANGE, V1, P7, DOI 10.1038/nclimate1058
   Khan AA, 1998, ACI MATER J, V95, P293
   Madsen H.O., 2013, SAFETY RELIABILITY R, P81
   MIRZA SA, 1979, J STRUCT DIV-ASCE, V105, P1021
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Mullard JA, 2012, J BRIDGE ENG, V17, P353, DOI 10.1061/(ASCE)BE.1943-5592.0000248
   Mullard JA, 2011, ACI STRUCT J, V108, P71
   Neville AM., 1981, Properties of concrete
   Peng LZL, 2014, MAG CONCRETE RES, V66, P1154, DOI 10.1680/macr.14.00098
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   SAETTA AV, 1993, ACI MATER J, V90, P441
   Schmitt G., 2009, GLOBAL NEEDS KNOWLED
   Stewart M.G., 1997, Probabilistic Risk Assessment of Engineering Systems
   Stewart MG, 2012, STRUCT SAF, V35, P29, DOI 10.1016/j.strusafe.2011.10.002
   Stewart MG, 2011, ENG STRUCT, V33, P1326, DOI 10.1016/j.engstruct.2011.01.010
   Stewart MG, 1996, STRUCT SAF, V18, P225, DOI 10.1016/0167-4730(96)00012-4
   Talukdar S, 2012, CEMENT CONCRETE COMP, V34, P931, DOI 10.1016/j.cemconcomp.2012.04.012
   Treasury H.M. S., 2003, GREEN BOOK APPR EV C
   Val DV, 2008, RELIAB ENG SYST SAFE, V93, P364, DOI 10.1016/j.ress.2006.12.010
   Val DV, 2003, STRUCT SAF, V25, P343, DOI 10.1016/S0167-4730(03)00014-6
   Viscusi WK, 2007, U CHICAGO LAW REV, V74, P209
   Vu KAT, 2000, STRUCT SAF, V22, P313, DOI 10.1016/S0167-4730(00)00018-7
   Wang XM, 2012, CLIMATIC CHANGE, V110, P941, DOI 10.1007/s10584-011-0124-7
   Wigley TML, 1996, NATURE, V379, P240, DOI 10.1038/379240a0
NR 49
TC 62
Z9 67
U1 1
U2 33
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0167-4730
EI 1879-3355
J9 STRUCT SAF
JI Struct. Saf.
PY 2015
VL 52
BP 40
EP 53
DI 10.1016/j.strusafe.2014.10.005
PN A
PG 14
WC Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering
GA AY4YR
UT WOS:000347581400005
DA 2025-01-10
ER

PT J
AU Glaas, E
   Juhola, S
AF Glaas, Erik
   Juhola, Sirkku
TI New Levels of Climate Adaptation Policy: Analyzing the Institutional
   Interplay in the Baltic Sea Region
SO SUSTAINABILITY
LA English
DT Article
DE adaptation; Baltic Sea Region; climate change; EU; institutional
   interplay
ID CAPACITY; GOVERNANCE; LINKAGES; CITIES; SCALES
AB International policy development and expected climate change impacts such as flooding, landslides, and the extinction of sensitive species have forced countries around the Baltic Sea to begin working on national climate adaptation policies. Simultaneously, the EU is building both a central and a macro-regional Baltic Sea-wide adaptation strategy to support national policy developments. However, it yet remains unclear how these EU strategies will complement each other or national policies. This article analyzes the constraints and opportunities presented by this new institutional interplay and discusses the potential of the forthcoming EU strategies to support national policy. It does so by mapping how adaptation is institutionalized in two case countries, Sweden and Finland, and is organized in the two EU approaches. The vertical institutional interplay between scales is analyzed in terms of three factors: competence, capacity, and compatibility. Results indicate institutional constraints related to: risks of policy complexity for subnational actors, an unclear relationship between the two EU approaches, an overly general approach to targeting contextualized climate change vulnerabilities, and a general lack of strategies to steer adaptation. However, there are also opportunities linked to an anticipated increased commitment to the national management of adaptation, especially related to biodiversity issues.
C1 [Glaas, Erik] Linkoping Univ, Dept Themat Studies Water & Environm Studies, Ctr Climate Sci & Policy Res CSPR, SE-60174 Norrkoping, Sweden.
   [Juhola, Sirkku] Aalto Univ, Dept Real Estate Planning & Geoinformat, FI-00076 Helsinki, Finland.
   [Juhola, Sirkku] Univ Helsinki, Dept Environm Sci, FI-00014 Helsinki, Finland.
C3 Linkoping University; Aalto University; University of Helsinki
RP Glaas, E (corresponding author), Linkoping Univ, Dept Themat Studies Water & Environm Studies, Ctr Climate Sci & Policy Res CSPR, SE-60174 Norrkoping, Sweden.
EM erik.glaas@liu.se; sirkku.juhola@aalto.fi
RI Juhola, Sirkku/IXW-8093-2023
OI Juhola, Sirkku/0000-0003-0095-2282; Glaas, Erik/0000-0002-5126-3973
FU Swedish Research Council for Environment, Agricultural Sciences and
   Spatial Planning (FORMAS); Aalto Starting Grant at Aalto University;
   Norden Top-level Research Initiative sub-programme "Effect Studies and
   Adaptation to Climate Change"
FX The authors would like to thank three anonymous reviewers as well as
   Mathias Friman, Ola Uhrqvist and Johan Alberth for valuable comments on
   an earlier draft of this article. The study was funded by the Swedish
   Research Council for Environment, Agricultural Sciences and Spatial
   Planning (FORMAS) and by the Aalto Starting Grant at Aalto University.
   Research presented in this paper contributes to the Nordic Centre of
   Excellence for Strategic Adaptation Research (NORD-STAR), which is
   funded by the Norden Top-level Research Initiative sub-programme "Effect
   Studies and Adaptation to Climate Change".
CR Adger WN, 2000, ANN ASSOC AM GEOGR, V90, P738, DOI 10.1111/0004-5608.00220
   Andonova LB, 2009, GLOBAL ENVIRON POLIT, V9, P52, DOI 10.1162/glep.2009.9.2.52
   [Anonymous], 1200908 FG GERM I IN
   [Anonymous], COM2009248 EUR COMM
   [Anonymous], COM20091474 EUR COMM
   [Anonymous], ILMASTONMUUTOKSEN SO
   [Anonymous], 1990, I I CHANGE EC PERFOR
   [Anonymous], 2007, CLIMATE CHANGE 2007
   [Anonymous], 2009, PEER No. 1
   Betsill M, 2007, LOCAL ENVIRON, V12, P447, DOI 10.1080/13549830701659683
   Carter JG, 2011, CURR OPIN ENV SUST, V3, P193, DOI 10.1016/j.cosust.2010.12.015
   Cash DW, 2006, ECOL SOC, V11
   Dreyfus M, 2012, MITIG ADAPT STRAT GL, V17, P849, DOI 10.1007/s11027-011-9348-0
   Ellison D, 2010, DEVELOPING ADAPTATION POLICY AND PRACTICE IN EUROPE: MULTI-LEVEL GOVERNANCE OF CLIMATE CHANGE, P39, DOI 10.1007/978-90-481-9325-7_2
   Engle NL, 2010, GLOBAL ENVIRON CHANG, V20, P4, DOI 10.1016/j.gloenvcha.2009.07.001
   European Commission, 2009, SEC20093087 EUR COMM
   European Commission, 2007, COM2007354 EUR COMM
   European Commission, 2009, 2009038 EUR COMM
   European Commission, 2009, SEC20097122 EUR COMM
   Gagnon-Lebrun F, 2007, CLIM POLICY, V7, P392, DOI 10.1080/14693062.2007.9685664
   Glaas E, 2010, LOCAL ENVIRON, V15, P525, DOI 10.1080/13549839.2010.487525
   Goulet R., 2010, EUROPEAN UNION STRAT
   Hjerpe M, 2012, MITIG ADAPT STRAT GL, V17, P471, DOI 10.1007/s11027-011-9337-3
   Inderberg TH, 2011, LOCAL ENVIRON, V16, P303, DOI 10.1080/13549839.2011.569538
   Jonsson AC, 2012, LOCAL ENVIRON, V17, P735, DOI 10.1080/13549839.2012.685880
   Jordan A, 2012, GLOBAL ENVIRON POLIT, V12, P43, DOI 10.1162/GLEP_a_00108
   Jordan A, 2010, ENVIRON POLICY GOV, V20, P147, DOI 10.1002/eet.539
   Juhola S, 2012, LOCAL ENVIRON, V17, P629, DOI 10.1080/13549839.2012.665860
   Juhola S, 2011, ENVIRON POLIT, V20, P445, DOI 10.1080/09644016.2011.589571
   Juhola S, 2011, ENVIRON SCI POLICY, V14, P239, DOI 10.1016/j.envsci.2010.12.006
   Keskitalo C., 2012, J ENV PLANN MAN, V54, P1
   Keskitalo ECH, 2010, DEVELOPING ADAPTATION POLICY AND PRACTICE IN EUROPE: MULTI-LEVEL GOVERNANCE OF CLIMATE CHANGE, P1, DOI 10.1007/978-90-481-9325-7
   Kvale D., 1996, INTERVIEWS
   Lehmann A, 2011, CLIM RES, V46, P185, DOI 10.3354/cr00876
   Lidskog R., 2010, Transboundary Risk Governance
   Lidskog R, 2011, AMBIO, V40, P111, DOI 10.1007/s13280-010-0123-3
   Ministry of Agriculture and Forestry, 2005, PUBL MIN AGR FOR, V1a/2005
   Ministry of Agriculture and Forestry, 2009, PUBL MIN AGR FOR, V4a/2009
   Ministry of the Environment, 1997, MIN PUBL SER DS, V26
   Ministry of the Environment, 2006, 4 MIN ENV
   Ministry of the Environment, 1995, FINL NAT REP UN FRAM
   Ministry of the Environment, 2007, SWED GOV OFF REP, V60
   Ministry of the Environment, 2001, 3 MIN ENV
   Ministry of the Environment, 1994, MIN PUBL SER DS, V121
   Ministry of the Environment, 2005, MIN PUBL SER DS, V55
   Ministry of the Environment, 2009, MIN PUBL SER DS, V63
   Moss B, 2008, SCI TOTAL ENVIRON, V400, P32, DOI 10.1016/j.scitotenv.2008.04.029
   Oberthur Sebastian., 2006, Institutional Interaction in Global Environmental Governance. Synergy and Conflict Among International and EU Policies
   Ostrom E, 1999, SCIENCE, V284, P278, DOI 10.1126/science.284.5412.278
   [Parry ML. IPCC IPCC], 2007, Climate change 2007: Impacts, adaptation and vulnerability, P7, DOI DOI 10.2134/JEQ2008.0015BR
   Peters G.B., 2019, Institutional theory in political science: The new institutionalism, V4th
   Petersen T, 2009, ECOL ECON, V68, P2058, DOI 10.1016/j.ecolecon.2009.01.008
   Prutsch A., 2010, GUIDING PRINCIPLES A
   Ribeiro M. M., 2009, G1ETU20080093R DG EN
   Rydell B., 2010, Klimatanpassning i Sverige - en oversikt [Climate adaptation in Sweden - an overview]
   Schipper E.L.F., 2006, Rev. Eur. Comp. Int. Environ. Law, V15, P82, DOI [DOI 10.1111/J.1467-9388.2006.00501.X, 10.1111/j.1467-9388.2006.00501.x]
   Smith ME, 2004, EUR J INT RELAT, V10, P95, DOI 10.1177/1354066104040570
   Stokke O. S., 2001, 142001 FNI
   Storbjörk S, 2011, OCEAN COAST MANAGE, V54, P265, DOI 10.1016/j.ocecoaman.2010.12.007
   Swedish Civil Contingencies Agency, 2012, SWED CIV CONT AG PUB, VMSB422
   Swedish Environmental Protection Agency, 1989, VAXTH ORS EFF MOJL A
   Underdal A, 2008, INSTITUTIONS AND ENVIRONMENTAL CHANGE: PRINCIPAL FINDINGS, APPLICATIONS, AND RESEARCH FRONTIERS, P49
   United Nations, 1992, AAC23718 UN
   Westerhoff L, 2011, CLIM POLICY, V11, P1071, DOI 10.1080/14693062.2011.579258
   Westerhoff L, 2010, INT J CLIM CHANG STR, V2, P222, DOI 10.1108/17568691011063024
   Yohe G, 2002, GLOBAL ENVIRON CHANG, V12, P25, DOI 10.1016/S0959-3780(01)00026-7
   Young OR, 1996, GLOB GOV, V2, P1
   Young O, 2006, ECOL SOC, V11
   Young R.O., 2002, I DIMENSION ENV CHAN
NR 69
TC 16
Z9 19
U1 0
U2 21
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JAN
PY 2013
VL 5
IS 1
BP 256
EP 275
DI 10.3390/su5010256
PG 20
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 213GR
UT WOS:000324044300016
OA Green Published, Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Sanga, U
   Sidibé, A
   Olabisi, LS
AF Sanga, Udita
   Sidibe, Amadou
   Olabisi, Laura Schmitt
TI Dynamic pathways of barriers and opportunities for food security and
   climate adaptation in Southern Mali
SO WORLD DEVELOPMENT
LA English
DT Article
DE Barriers; Climate adaptation; Food security; Participatory games; Causal
   mapping; Mali; West Africa
ID ROLE-PLAYING GAME; SYSTEM DYNAMICS; OVERCOMING BARRIERS;
   DECISION-MAKING; WEST-AFRICA; VARIABILITY; PERSPECTIVE; SIMULATION;
   VULNERABILITY; STAKEHOLDERS
AB Barriers to food security and climate adaptation operate in complex and dynamic ways but are often perceived as static impediments to be overcome. In this study, we apply systems thinking for the assessment of barriers in agricultural decision-making for food security and climate adaptation. Using a mixed method approach of participatory simulation game design and causal loop diagrams, we explore the dynamic pathways through which barriers inhibit farmers from achieving food security and climate adaptation in Southern Mali. Results show that the key barriers in the region are financial, land, and climate-related barriers including unavailability of formal credit sources, high input prices, inadequate land access and ownership rights, time and labor constraints in collective vs individual plots, and climate risks such as early and late season droughts, high temperature, excessive rainfall, water scarcity, and pest incidences. These barriers operate in complex, interdependent, and dynamic ways where factors that act as enablers in one context can also function as barriers in another context. We see such interdependencies in three cases: i) access to interlocked credit and loans for cotton cultivation acts as enablers of income generation for male farmers but become barriers to female farmers who do not cultivate cotton ii) land ownership and land use rights for male farmers act as enablers for cultivation of income generating cash and food crops but acts as a barrier for female farmers by way of intra-household labor dynamics within collective plots iii) increase in land allocation to cotton and maize cultivation acts as enablers for increased household income but becomes a barrier to food security due to higher vulnerability to climate risks. Assessment of causal loop diagrams identified deep and shallow leverage points. Policies and interventions that focused on input subsidies and credit facilities are shallow leverage points where incremental changes will only lead to small improvements in farmers' livelihoods. Policies that support improved access and ownership of land to female farmers are deep leverage points that can potentially shift the dominant cropping pattern to more diversified and climate-resilient production. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
C1 [Sanga, Udita; Olabisi, Laura Schmitt] Michigan State Univ, Dept Community Sustainabil, 151 Nat Resources, E Lansing, MI 48824 USA.
   [Sanga, Udita] Stockholm Univ, Stockholm Resilience Ctr, S-10691 Stockholm, Sweden.
   [Sidibe, Amadou] Inst Polytech Rural Format & Rech Appl IPR IFRA K, BP 06, Koulikoro, Mali.
C3 Michigan State University; Stockholm University
RP Sanga, U (corresponding author), Michigan State Univ, Dept Community Sustainabil, 151 Nat Resources, E Lansing, MI 48824 USA.; Sanga, U (corresponding author), Stockholm Univ, Stockholm Resilience Ctr, S-10691 Stockholm, Sweden.
EM udita.sanga@su.se
OI Sanga, Udita/0000-0003-0552-4797
FU National Science Foundation from IBSSR award [1416730]; Michigan State
   University; START International, Washington D.C; SBE Off Of
   Multidisciplinary Activities; Direct For Social, Behav & Economic Scie
   [1416730] Funding Source: National Science Foundation
FX This work was supported by the National Science Foundation under funding
   received from IBSSR award #1416730, Michigan State University and the
   ASSAR Small Opportunities grant by START International, Washington D.C.
   The authors are grateful to Ms. Kadiatou Toure for her invaluable help
   and support during field data collection. We extend our heartfelt thanks
   to Dr. Maria Claudia Lopez, Dr. Arika Ligmann-Zielinska, Dr. Julie
   Winkler as well as colleagues at the Department of Community
   Sustainability, MSU and ICRISAT-Mali for their support and helpful
   feedback that enabled the writing of this manuscript.
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Almeida Celia, 2006, Cad. Saúde Pública, V22, pS7
   Andrieu N, 2017, AGR SYST, V154, P13, DOI 10.1016/j.agsy.2017.02.008
   [Anonymous], 1991, HLTH SERVICES RES KE
   Antwi-Agyei P, 2015, CLIM DEV, V7, P297, DOI 10.1080/17565529.2014.951013
   Barnett J, 2015, BARRIERS LIMITS CLIM, V20
   Barreteau O., 2013, SIMULATING SOCIAL CO, P197, DOI [DOI 10.1007/978-3-540-93813-2_10, 10.1007/978-3-540-93813-2_10]
   Barreteau O, 2007, SIMULAT GAMING, V38, P185, DOI 10.1177/1046878107300660
   BECKER LC, 1990, GEOGR J, V156, P313, DOI 10.2307/635532
   Becu N, 2003, LECT NOTES ARTIF INT, V2927, P131
   Bharwani S, 2006, SOC SCI COMPUT REV, V24, P78, DOI 10.1177/0894439305282346
   Bharwani S, 2005, PHILOS T R SOC B, V360, P2183, DOI 10.1098/rstb.2005.1742
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Binder CR, 2013, ECOL SOC, V18, DOI 10.5751/ES-05551-180426
   Bingen RJ, 1998, J MOD AFR STUD, V36, P265, DOI 10.1017/S0022278X98002742
   Brandt E., 2006, Proceedings of the 9th Conference on Participatory Design: Expanding Boundaries in Design, P57, DOI [https://doi.org/10.1145/1147261.1147271, DOI 10.1145/1147261.1147271]
   Briot Jean-pierre., 2007, AISCMS, P183
   Brown ME, 2009, ENVIRON SCI TECHNOL, V43, P8016, DOI 10.1021/es901162d
   Castella JC, 2005, ECOL SOC, V10
   Cavana R. Y., 2013, 31 INT C SYST DYN SO
   Cooper MW, 2017, ECOL FOOD NUTR, V56, P101, DOI 10.1080/03670244.2016.1263947
   Coyle G, 2000, SYST DYNAM REV, V16, P225, DOI 10.1002/1099-1727(200023)16:3<225::AID-SDR195>3.0.CO;2-D
   Crane TA, 2011, NJAS-WAGEN J LIFE SC, V57, P179, DOI 10.1016/j.njas.2010.11.002
   d'Aquino P, 2013, ECOL SOC, V18, DOI 10.5751/ES-05876-180416
   Delarue J, 2009, SIKASSO PARADOX COTT
   Dingkuhn M, 2006, AGR WATER MANAGE, V80, P241, DOI 10.1016/j.agwat.2005.07.016
   Dury S, 2012, CAH AGRIC, V21, P324, DOI 10.1684/agr.2012.0584
   Eakin H, 2006, ANNU REV ENV RESOUR, V31, P365, DOI 10.1146/annurev.energy.30.050504.144352
   Eakin H, 2016, REG ENVIRON CHANGE, V16, P801, DOI 10.1007/s10113-015-0789-y
   Eisenack K, 2012, Human/nature interactions in the Anthropocene: Potentials of social-ecological systems analysis, P107
   Eisenack K, 2013, SIMULAT GAMING, V44, P245, DOI 10.1177/1046878113490568
   Eisenack K, 2014, NAT CLIM CHANGE, V4, P867, DOI 10.1038/NCLIMATE2350
   Ericksen P.J., 2009, Food security and global environmental change: emerging challenges
   FAO, 2017, COUNTR FACT SHEET FO
   Fischer J, 2019, PEOPLE NAT, V1, P115, DOI 10.1002/pan3.13
   FORRESTER JW, 1994, SYST DYNAM REV, V10, P245, DOI 10.1002/sdr.4260100211
   Giannini A, 2017, EARTHS FUTURE, V5, P144, DOI 10.1002/2016EF000404
   Grist JP, 2001, J CLIMATE, V14, P1337, DOI 10.1175/1520-0442(2001)014<1337:ASOTDF>2.0.CO;2
   Haraldsson HV., 2004, Introduction to system thinking and causal loop diagrams, P3
   Jones L, 2011, GLOBAL ENVIRON CHANG, V21, P1262, DOI 10.1016/j.gloenvcha.2011.06.002
   Klabbers J. H., 2003, Simulation Gaming, V34, P488
   Larsen K, 2009, HABITAT INT, V33, P260, DOI 10.1016/j.habitatint.2008.10.007
   Luna-Reyes LF, 2003, SYST DYNAM REV, V19, P271, DOI 10.1002/sdr.280
   Maedows D., 1999, LEVERAGE POINTS PLAC
   Majone G., 1989, EVIDENCE ARGUMENT PE
   Matasci C, 2014, MITIG ADAPT STRAT GL, V19, P1239, DOI 10.1007/s11027-013-9471-1
   Mendler de Suarez J., 2012, pardee center task force report
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Nicholson SE, 2000, J CLIMATE, V13, P2628, DOI 10.1175/1520-0442(2000)013<2628:AAORRC>2.0.CO;2
   Nielsen JO, 2010, GLOBAL ENVIRON CHANG, V20, P142, DOI 10.1016/j.gloenvcha.2009.10.002
   Pak MV, 2010, ENVIRON MODELL SOFTW, V25, P1322, DOI 10.1016/j.envsoft.2010.03.015
   Reckien D, 2013, SIMULAT GAMING, V44, P253, DOI 10.1177/1046878113480867
   Richards P, 1993, CULTIVATION KNOWLEDG, P61
   Richards P, 2007, IDS BULL-I DEV STUD, V38, P21
   Richardson KJ, 2018, CLIMATIC CHANGE, V147, P327, DOI 10.1007/s10584-018-2137-y
   Risbey J., 1999, Mitigation and Adaptation Strategies for Global Change, V4, P137, DOI DOI 10.1023/A:1009636607038
   Rivers Louie III, 2018, Environment Systems & Decisions, V38, P274, DOI 10.1007/s10669-018-9682-9
   Roudier P, 2011, GLOBAL ENVIRON CHANG, V21, P1073, DOI 10.1016/j.gloenvcha.2011.04.007
   Roxas F.M. Y., 2019, World Futures, V75, P609, DOI DOI 10.1080/02604027.2019.1654784
   Ruohomaki V, 1994, VIEWPOINTS LEARNING, P13
   Shackleton S, 2015, WIRES CLIM CHANGE, V6, P321, DOI 10.1002/wcc.335
   Sissoko K, 2011, REG ENVIRON CHANGE, V11, pS119, DOI 10.1007/s10113-010-0164-y
   Souchère V, 2010, ENVIRON MODELL SOFTW, V25, P1359, DOI 10.1016/j.envsoft.2009.03.002
   Spires M, 2018, CLIM DEV, V10, P432, DOI 10.1080/17565529.2017.1410088
   Staatz J., 2011, Malian agricultural sector assessment 2011
   Sterk M, 2017, CURR OPIN ENV SUST, V28, P108, DOI 10.1016/j.cosust.2017.09.003
   Sultan B, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104006
   Sultan B, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/1/014040
   Sultan B, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01262
   Thornton PK, 2008, AFR J AGRIC RESOUR E, V2, P24
   Tittonell P, 2013, FIELD CROP RES, V143, P76, DOI 10.1016/j.fcr.2012.10.007
   Traore B, 2015, EXP AGR, V51, P615, DOI 10.1017/S0014479714000507
   Traore B, 2013, EUR J AGRON, V49, P115, DOI 10.1016/j.eja.2013.04.004
   Traoré PCS, 2007, CLIMATE PREDICTION AND AGRICULTURE: ADVANCES AND CHALLENGES, P189, DOI 10.1007/978-3-540-44650-7_19
   Uittenbroek CJ, 2013, REG ENVIRON CHANGE, V13, P399, DOI 10.1007/s10113-012-0348-8
   Valkering P, 2013, SIMULAT GAMING, V44, P366, DOI 10.1177/1046878112441693
   van Pelt SC, 2015, ENVIRON SCI POLICY, V45, P41, DOI 10.1016/j.envsci.2014.09.004
   Vervoort JM, 2014, GLOBAL ENVIRON CHANG, V28, P383, DOI 10.1016/j.gloenvcha.2014.03.001
   Voinov A, 2010, ENVIRON MODELL SOFTW, V25, P1268, DOI 10.1016/j.envsoft.2010.03.007
   WEISS CH, 1979, PUBLIC ADMIN REV, V39, P426, DOI 10.2307/3109916
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
   Wolstenholme E F., 1983, Journal of the Operational Research Society, V34, P885
NR 82
TC 14
Z9 14
U1 5
U2 24
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0305-750X
EI 1873-5991
J9 WORLD DEV
JI World Dev.
PD DEC
PY 2021
VL 148
AR 105663
DI 10.1016/j.worlddev.2021.105663
EA AUG 2021
PG 14
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA WH0SI
UT WOS:000707398800004
OA hybrid
DA 2025-01-10
ER

PT J
AU Morenikeji, OB
   Ajayi, OO
   Peters, SO
   Mujibi, FD
   De Donato, M
   Thomas, BN
   Imumorin, IG
AF Morenikeji, Olanrewaju B.
   Ajayi, Oyeyemi O.
   Peters, Sunday O.
   Mujibi, Fidalis D.
   De Donato, Marcos
   Thomas, Bolaji N.
   Imumorin, Ikhide G.
TI RNA-seq profiling of skin in temperate and tropical cattle
SO JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY
LA English
DT Article
DE Cattle; Genes; RNA-seq; Skin; Temperate; Tropics
ID FALSE-DISCOVERY RATE; ANCIENT DNA ANALYSIS; HEAT-STRESS; DIFFERENTIAL
   EXPRESSION; BODY-TEMPERATURE; CLIMATE-CHANGE; RIG-I; RESISTANCE;
   RESPONSES; BREEDS
AB Skin is a major thermoregulatory organ in the body controlling homeothermy, a critical function for climate adaptation. We compared genes expressed between tropical- and temperate-adapted cattle to better understand genes involved in climate adaptation and hence thermoregulation. We profiled the skin of representative tropical and temperate cattle using RNAseq. A total of 214,754,759 reads were generated and assembled into 72,993,478 reads and were mapped to unique regions in the bovine genome. Gene coverage of unique regions of the reference genome showed that of 24,616 genes, only 13,130 genes (53.34%) displayed more than one count per million reads for at least two libraries and were considered suitable for downstream analyses. Our results revealed that of 255 genes expressed differentially, 98 genes were upregulated in tropically-adapted White Fulani (WF; Bos indicus) and 157 genes were down regulated in WF compared to Angus, AG (Bos taun.is). Fifteen pathways were identified from the differential gene sets through gene ontology and pathway analyses. These include the significantly enriched melanin metabolic process, proteinaceous extracellular matrix, inflammatory response, defense response, calcium ion binding and response to wounding. Quantitative PCR was used to validate six representative genes which are associated with skin thermoregulation and epithelia dysfunction (mean correlation 0.92; p < 0.001). Our results contribute to identifying genes and understanding molecular mechanisms of skin thermoregulation that may influence strategic genomic selection in cattle to withstand climate adaptation, microbial invasion and mechanical damage.
C1 [Morenikeji, Olanrewaju B.] Fed Univ Technol Akure, Dept Anim Prod & Hlth, Akure, Nigeria.
   [Morenikeji, Olanrewaju B.; Thomas, Bolaji N.] Rochester Inst Technol, Dept Biomed Sci, Rochester, NY 14623 USA.
   [Morenikeji, Olanrewaju B.; Ajayi, Oyeyemi O.; Imumorin, Ikhide G.] Cornell Univ, Coll Agr & Life Sci, Anim Genet & Genom Lab, Off Int Programs, Ithaca, NY 14853 USA.
   [Ajayi, Oyeyemi O.] Fed Univ Agr, Dept Anim Breeding & Genet, Abeokuta, Nigeria.
   [Peters, Sunday O.] Berry Coll, Dept Anim Sci, Mt Berry, GA 30149 USA.
   [Mujibi, Fidalis D.] Usomi Ltd, Nairobi, Kenya.
   [De Donato, Marcos] Tecnol Monterrey, Escuela Ingn & Ciencias, Queretaro 76130, Mexico.
   [Imumorin, Ikhide G.] African Inst Biosci Res & Training, Ibadan, Nigeria.
   [Imumorin, Ikhide G.] First Tech Univ, Dept Biol Sci, Ibadan, Nigeria.
   [Imumorin, Ikhide G.] Georgia Inst Technol, Sch Biol Sci, Atlanta, GA 30332 USA.
C3 Rochester Institute of Technology; Cornell University; University of
   Agriculture, Abeokuta; Tecnologico de Monterrey; University System of
   Georgia; Georgia Institute of Technology
RP Imumorin, IG (corresponding author), Georgia Inst Technol, Sch Biol Sci, Atlanta, GA 30332 USA.
EM igi2@biology.gatech.edu
RI Morenikeji, Olanrewaju/AAV-5029-2020; Mujibi, Denis/LBJ-9987-2024;
   Peters, Sunday/AAE-9683-2021; De Donato, Marcos/I-5307-2012
OI Peters, Sunday/0000-0002-0216-926X; De Donato,
   Marcos/0000-0001-8860-6020; Mujibi, Denis Fidalis/0000-0002-1478-9001
FU College of Agriculture and Life Sciences, Cornell University, Ithaca,
   NY; Zoetis, Inc.; National Research Initiative Competitive Grant Program
   from the USDA National Institute of Food and Agriculture
   [200635205-16864]; USDA-NIFA [2009-6520505635, 2010-34444-20729]; USDA
   Federal formula Hatch funds; Tertiary Education Trust Fund (TETFund) of
   the Federal Republic of Nigeria; American Association of Immunologists
   Careers in Immunology Fellowship Program; NIFA [580883,
   2010-34444-20729] Funding Source: Federal RePORTER
FX This work was partly supported by College of Agriculture and Life
   Sciences, Cornell University, Ithaca, NY and Pfizer Animal Health, Inc.
   (now Zoetis, Inc.). Additional support by National Research Initiative
   Competitive Grant Program (Grant No. 200635205-16864) from the USDA
   National Institute of Food and Agriculture, USDA-NIFA Research
   Agreements (Nos. 2009-6520505635, 2010-34444-20729) and USDA Federal
   formula Hatch funds appropriated to the Cornell University Agricultural
   Experiment Station are gratefully acknowledged. OBM is supported by the
   Tertiary Education Trust Fund (TETFund) of the Federal Republic of
   Nigeria appropriated to the Federal University of Technology, Akure,
   Nigeria and through the American Association of Immunologists Careers in
   Immunology Fellowship Program. The funders had no role in study design,
   data collection and analysis, decision to publish, or preparation of the
   manuscript.
CR Aberdam E, 1998, J BIOL CHEM, V273, P19560, DOI 10.1074/jbc.273.31.19560
   Adolfsen B, 2004, J CELL BIOL, V166, P249, DOI 10.1083/jcb.200312054
   Ahmad N, 2004, J INVEST DERMATOL, V123, P417, DOI 10.1111/j.0022-202X.2004.23307.x
   Ajayi OO, 2014, 22 INT C PLANT AN GE
   André G, 2011, J DAIRY SCI, V94, P4502, DOI 10.3168/jds.2010-4139
   Ank N, 2006, J INTERF CYTOK RES, V26, P373, DOI 10.1089/jir.2006.26.373
   Arai I, 2004, EUR J PHARMACOL, V505, P229, DOI 10.1016/j.ejphar.2004.10.031
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Bramanti B, 2003, HUM BIOL, V75, P105, DOI 10.1353/hub.2003.0017
   Brito LFC, 2004, THERIOGENOLOGY, V61, P511, DOI 10.1016/S0093-691X(03)00231-0
   Chiu YH, 2009, CELL, V138, P576, DOI 10.1016/j.cell.2009.06.015
   Collier RJ, 2008, J DAIRY SCI, V91, P445, DOI 10.3168/jds.2007-0540
   Collier R.J., 2012, Environmental stress and amelioration in livestock production, P379, DOI [10.1007/978-3-642-29205-714, DOI 10.1007/978-3-642-29205-714, DOI 10.1007/978-3-642-29205-7_14]
   Cone RD, 1996, RECENT PROG HORM RES, V51, P287
   da Silva RG, 2003, T ASAE, V46, P913
   Das GK, 2010, REPROD DOMEST ANIM, V45, pe483, DOI 10.1111/j.1439-0531.2010.01598.x
   Di Francesco S, 2011, ANIM REPROD SCI, V123, P48, DOI 10.1016/j.anireprosci.2010.11.009
   Edwards CJ, 2004, J ARCHAEOL SCI, V31, P695, DOI 10.1016/j.jas.2003.11.001
   Fang X, 2006, AM J PHYSIOL-HEART C, V290, pH55, DOI 10.1152/ajpheart.00427.2005
   Furumura M, 1996, PIGM CELL RES, V9, P191, DOI 10.1111/j.1600-0749.1996.tb00109.x
   Gaughan JB, 2010, INT J BIOMETEOROL, V54, P617, DOI 10.1007/s00484-009-0233-4
   Gebremedhin KG, 2011, APPL ENG AGRIC, V27, P999
   Hansen PJ, 2015, REPROD FERT DEVELOP, V27, P22, DOI 10.1071/RD14311
   Hanusova E., 2010, SLOVAK J ANIM SCI, V43, P63
   Hayes BJ, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0006676
   Hoffmann I, 2013, ANIMAL, V7, P346, DOI 10.1017/S1751731113000815
   Hoffmann I, 2010, ANIM GENET, V41, P32, DOI 10.1111/j.1365-2052.2010.02043.x
   Horowitz M, 2010, ANN NY ACAD SCI, V1188, P199, DOI 10.1111/j.1749-6632.2009.05101.x
   Howard JT, 2014, INT J BIOMETEOROL, V58, P1665, DOI 10.1007/s00484-013-0773-5
   Huang C, 2009, J DAIRY SCI, V92, P4641, DOI 10.3168/jds.2008-1982
   Ilatsia ED, 2012, TROP ANIM HEALTH PRO, V44, P519, DOI 10.1007/s11250-011-9928-8
   Johnson EN, 1999, J INVEST DERMATOL, V112, P861, DOI 10.1046/j.1523-1747.1999.00595.x
   JOHNSON HD, 1961, J DAIRY SCI, V44, P1191
   Johnston D. J., 2009, Matching genetics and environment: a new look at an old topic. Proceedings of the 18th Conference of the Association for the Advancement of Animal Breeding and Genetics, Barossa Valley, South Australia, Australia, 28 September-1 October, 2009, P30
   Keating AF, 2008, IRISH J AGR FOOD RES, V47, P99
   KOBAYASHI T, 1994, EMBO J, V13, P5818, DOI 10.1002/j.1460-2075.1994.tb06925.x
   KROUMPOUZOS G, 1994, BIOCHEM BIOPH RES CO, V202, P1060, DOI 10.1006/bbrc.1994.2036
   Lacetera N, 2006, J DAIRY SCI, V89, P4606, DOI 10.3168/jds.S0022-0302(06)72510-3
   Langmead B, 2009, GENOME BIOL, V10, DOI 10.1186/gb-2009-10-3-r25
   Leutenegger CM, 2000, VET IMMUNOL IMMUNOP, V77, P275, DOI 10.1016/S0165-2427(00)00243-9
   Lewis-Ballester A, 2016, SCI REP-UK, V6, DOI 10.1038/srep35169
   Ling CC, 2006, BIOCHEM BIOPH RES CO, V349, P906, DOI 10.1016/j.bbrc.2006.08.111
   Mader TL, 2010, J ANIM SCI, V88, P2153, DOI 10.2527/jas.2009-2586
   Megahed GA, 2008, REPROD DOMEST ANIM, V43, P672, DOI 10.1111/j.1439-0531.2007.00968.x
   Morenikeji OB, 2019, J GENET, V98, DOI 10.1007/s12041-019-1060-y
   Moroi M, 1997, BLOOD, V90, P4413
   Niture SK, 2010, TOXICOL APPL PHARM, V244, P37, DOI 10.1016/j.taap.2009.06.009
   Oshlack A, 2009, BIOL DIRECT, V4, DOI 10.1186/1745-6150-4-14
   Paula-Lopes FF, 2003, REPRODUCTION, V125, P285, DOI 10.1530/rep.0.1250285
   Pichlmair A, 2007, IMMUNITY, V27, P370, DOI 10.1016/j.immuni.2007.08.012
   Pilotte L, 2012, P NATL ACAD SCI USA, V109, P2497, DOI 10.1073/pnas.1113873109
   Renaudeau D, 2012, ANIMAL, V6, P707, DOI 10.1017/S1751731111002448
   Rhoads ML, 2009, J DAIRY SCI, V92, P1986, DOI 10.3168/jds.2008-1641
   Rissanen TT, 2003, CIRC RES, V92, P1098, DOI 10.1161/01.RES.0000073584.46059.E3
   ROBBINS LS, 1993, CELL, V72, P827, DOI 10.1016/0092-8674(93)90572-8
   Robinson MD, 2010, BIOINFORMATICS, V26, P139, DOI 10.1093/bioinformatics/btp616
   Ross PJ, 2010, CELL REPROGRAM, V12, P709, DOI 10.1089/cell.2010.0036
   Satoh T, 2006, CHEM-BIOL INTERACT, V162, P195, DOI 10.1016/j.cbi.2006.07.001
   Schmuth M, 2005, J INVEST DERMATOL, V125, P1174, DOI 10.1111/j.0022-202X.2005.23934.x
   Scholtz M. M., 2013, Natural Science, V5, P106
   Sertznig P, 2008, AM J CLIN DERMATOL, V9, P15, DOI 10.2165/00128071-200809010-00002
   Shelton M., 2000, SHEEP PRODUCTION HOT, P155
   Slimen IB, 2016, J ANIM PHYSIOL AN N, V100, P401, DOI 10.1111/jpn.12379
   St-Pierre NR, 2003, J DAIRY SCI, V86, pE52, DOI 10.3168/jds.S0022-0302(03)74040-5
   Starkey L., 2007, AM SOC ANIM SCI S S2, V85, P42
   Szwajkowska M, 2011, ANIM SCI PAP REP, V29, P269
   Ten Kate MK, 2008, HAEMOPHILIA, V14, P1222, DOI 10.1111/j.1365-2516.2008.01775.x
   TRIPATHI RK, 1992, J BIOL CHEM, V267, P23707
   Uutela M, 2004, BLOOD, V104, P3198, DOI 10.1182/blood-2004-04-1485
   Volanakis J.E., 1998, HUMAN COMPLEMENT SYS, P9, DOI [10.1201/9780367800772, DOI 10.1201/B14212-3]
   Walsh G, 2002, EUR J PHARM SCI, V15, P135, DOI 10.1016/S0928-0987(01)00222-6
   Wheelock JB, 2010, J DAIRY SCI, V93, P644, DOI 10.3168/jds.2009-2295
   Wojta J, 2002, BLOOD, V100, P517, DOI 10.1182/blood.V100.2.517
   Wolfenson D, 2000, ANIM REPROD SCI, V60, P535, DOI 10.1016/S0378-4320(00)00102-0
   Yang TY, 2013, EVOL BIOINFORM, V9, P467, DOI 10.4137/EBO.S13099
   Yoshihara M, 2005, SCIENCE, V310, P858, DOI 10.1126/science.1117541
   Zevini A, 2017, TRENDS IMMUNOL, V38, P194, DOI 10.1016/j.it.2016.12.004
NR 77
TC 11
Z9 13
U1 2
U2 9
PU KOREAN SOCIETY ANIMAL SCIENCE & TECHNOLOGY
PI SEOUL
PA ROOM 1618, 8-13 GWANGPYEONG-RO 56 GIL, GANGNAM, SEOUL, 06367, SOUTH
   KOREA
SN 2672-0191
EI 2055-0391
J9 J ANIM SCI TECHNOL
JI J. Anim. Sci. Technol.
PY 2020
VL 62
IS 2
BP 141
EP +
DI 10.5187/jast.2020.62.2.141
PG 28
WC Agriculture, Dairy & Animal Science; Biotechnology & Applied
   Microbiology; Veterinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Biotechnology & Applied Microbiology; Veterinary Sciences
GA LD0JQ
UT WOS:000525719800003
PM 32292922
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Neset, TS
   Wilk, J
   Cruz, S
   Graça, M
   Rod, JK
   Maarse, MJ
   Wallin, P
   Andersson, L
AF Neset, T-S
   Wilk, J.
   Cruz, S.
   Graca, M.
   Rod, J. K.
   Maarse, M. J.
   Wallin, P.
   Andersson, L.
TI Co-designing a citizen science climate service
SO CLIMATE SERVICES
LA English
DT Article
DE Citizen sensing; Climate adaptation; Urban resilience; Participatory
   processes; Co-creation
ID BOUNDARY OBJECTS; KNOWLEDGE; COPRODUCTION; INFORMATION; EXPERIMENTATION;
   USABILITY; VOLUNTARY; CREATION; SUCCESS; LEARN
AB Interactive mobile technologies provide an emerging opportunity for citizens to engage with and enhance urban climate resilience, both as providers of locally situated data on climate variables, impacts and climate adaptation measures as well as to obtain information on local conditions and recommendations. This paper examines the process of co-designing a citizen science application for urban climate resilience in four European cities. Further, the paper studies if and how the system enables knowledge co-production to increase urban resilience following process principles for co-production of climate services and discusses the legitimacy, transparency, credibility, and relevance of the process. We further assess the role that a citizen science climate service could play as a boundary object in knowledge co-production. We draw on experiences from a co-design process that included municipal stakeholders from different sectors as well as municipal employees and civil society end-users involved in campaigns. This study identified a set of barriers and enablers for the co-design process and concludes that the CitizenSensing application can fulfil the role of a boundary object, but that the co-design process is a balancing act between navigating time constraints, including stakeholders' different and changing demands and perspectives while retaining a high level of flexibility and reflexivity.
C1 [Neset, T-S; Wilk, J.] Linkoping Univ, Ctr Climate Sci & Policy Res, Dept Themat Studies Environm Change, S-58183 Linkoping, Sweden.
   [Cruz, S.; Graca, M.] Univ Porto, Res Ctr Terr Transports & Environm CITTA, Fac Engn, P-4200465 Porto, Portugal.
   [Rod, J. K.] Norwegian Univ Sci & Technol NTNU, Fac Social & Educ Sci, Dept Geog, NO-7491 Trondheim, Norway.
   [Maarse, M. J.] Deltares, NL-2600 MH Delft, Netherlands.
   [Wallin, P.; Andersson, L.] Swedish Meteorol & Hydrol Inst SMHI, S-60176 Norrkoping, Sweden.
C3 Linkoping University; Universidade do Porto; Norwegian University of
   Science & Technology (NTNU); Deltares; Swedish Meteorological &
   Hydrological Institute
RP Neset, TS (corresponding author), Linkoping Univ, Ctr Climate Sci & Policy Res, Dept Themat Studies Environm Change, S-58183 Linkoping, Sweden.
EM tina.neset@liu.se
RI Cruz, Sara/AAN-2203-2021
OI Graca, Marisa/0000-0002-2231-8752; Santos Cruz,
   Sara/0000-0002-1776-4985; Neset, Tina-Simone/0000-0003-1151-9943
FU FCT (Portugal) [ERA4CS/0001/2016]; FORMAS (Sweden) [201701719]; NWO (The
   Netherlands) [438.17.805]; RCN (Norway) [274192]; European Union
   [690462]; Fundação para a Ciência e a Tecnologia [ERA4CS/0001/2016]
   Funding Source: FCT
FX This research is part of the project `Citizen Sensing -Urban Climate
   Resilience through Participatory Risk Management Systems' that is part
   of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FCT
   (Portugal, Grant ERA4CS/0001/2016), FORMAS (Sweden, Grant 201701719),
   NWO (The Netherlands, Grant 438.17.805), and RCN (Norway, Grant 274192)
   with co-funding by the European Union (Grant 690462).
CR Akpo E, 2015, J AGRIC EDUC EXT, V21, P369, DOI 10.1080/1389224X.2014.939201
   Balazs CL, 2013, ENVIRON JUSTICE, V6, P9, DOI 10.1089/env.2012.0017
   Bonney R, 2014, SCIENCE, V343, P1436, DOI 10.1126/science.1251554
   Bouzguenda I, 2019, SUSTAIN CITIES SOC, V50, DOI 10.1016/j.scs.2019.101627
   Bremer S, 2019, ENVIRON SCI POLICY, V94, P245, DOI 10.1016/j.envsci.2018.12.029
   Bremer S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.482
   Briley L, 2015, CLIM RISK MANAG, V9, P41, DOI 10.1016/j.crm.2015.04.004
   Campbell LK, 2016, ENVIRON MANAGE, V57, P1262, DOI 10.1007/s00267-016-0680-8
   Carlile PR, 2002, ORGAN SCI, V13, P442, DOI 10.1287/orsc.13.4.442.2953
   Cash DW, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187376
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Cvitanovic C, 2015, OCEAN COAST MANAGE, V112, P25, DOI 10.1016/j.ocecoaman.2015.05.002
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Djenontin INS, 2018, ENVIRON MANAGE, V61, P885, DOI 10.1007/s00267-018-1028-3
   Donnelly C, 2018, CLIM SERV, V11, P24, DOI 10.1016/j.cliser.2018.06.002
   Ertiö TP, 2015, PLAN PRACT RES, V30, P303, DOI 10.1080/02697459.2015.1052942
   European Citizen Science Association, 2015, Ten Principles of Citizen Science, DOI 10.17605/OSF.IO/XPR2N
   Fazey I, 2018, CLIM DEV, V10, P197, DOI 10.1080/17565529.2017.1301864
   Foley R, 2017, SUSTAIN SCI, V12, P123, DOI 10.1007/s11625-016-0393-1
   Fox NJ, 2011, SOCIOLOGY, V45, P70, DOI 10.1177/0038038510387196
   Fung A, 2015, PUBLIC ADMIN REV, V75, P513, DOI 10.1111/puar.12361
   FUNTOWICZ SO, 1993, FUTURES, V25, P739, DOI 10.1016/0016-3287(93)90022-L
   Gabrys J, 2017, SOCIOL REV, V65, P172, DOI 10.1177/0081176917710421
   Gaskin CJ, 2017, WEATHER CLIM SOC, V9, P801, DOI 10.1175/WCAS-D-16-0126.1
   Glaas E, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12020705
   Golding Nicola, 2017, Climate Services, V8, P72, DOI 10.1016/j.cliser.2017.11.002
   Goodchild MF, 2007, INT J SPAT DATA INFR, V2, P24
   Graca M., 2021, SUSTAINABLE POLICIES, DOI [10.1007/978-3-030-86304-3_11, DOI 10.1007/978-3-030-86304-3_11]
   Gramberger M, 2015, CLIMATIC CHANGE, V128, P201, DOI 10.1007/s10584-014-1225-x
   Hegger D, 2012, ENVIRON SCI POLICY, V18, P52, DOI 10.1016/j.envsci.2012.01.002
   Holand IS, 2011, NORSK GEOGR TIDSSKR, V65, P1, DOI 10.1080/00291951.2010.550167
   Jacobs KL, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100199
   Keeys LA, 2017, INT J PROJ MANAG, V35, P1196, DOI 10.1016/j.ijproman.2017.02.008
   Kirchhoff CJ, 2013, ANNU REV ENV RESOUR, V38, P393, DOI 10.1146/annurev-environ-022112-112828
   Kirono DGC, 2014, REG ENVIRON CHANGE, V14, P355, DOI 10.1007/s10113-013-0498-3
   Kjellstrom Erik, 2016, Clim Serv, V2-3, P15, DOI 10.1016/j.cliser.2016.06.004
   Klein RJT, 2014, ENVIRON SCI POLICY, V40, P101, DOI 10.1016/j.envsci.2014.01.011
   Kloprogge P, 2006, CLIMATIC CHANGE, V75, P359, DOI 10.1007/s10584-006-0362-2
   Kraaijvanger R, 2016, AGR SYST, V147, P38, DOI 10.1016/j.agsy.2016.05.001
   Kullenberg C, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0147152
   Lember V, 2019, PUBLIC MANAG REV, V21, P1665, DOI 10.1080/14719037.2019.1619807
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Lemos MC, 2005, GLOBAL ENVIRON CHANG, V15, P57, DOI 10.1016/j.gloenvcha.2004.09.004
   Mauser W, 2013, CURR OPIN ENV SUST, V5, P420, DOI 10.1016/j.cosust.2013.07.001
   McCall MK, 2012, GEOFORUM, V43, P81, DOI 10.1016/j.geoforum.2011.07.007
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Meier F, 2017, URBAN CLIM, V19, P170, DOI 10.1016/j.uclim.2017.01.006
   Menzel S, 2013, J ENVIRON MANAGE, V131, P351, DOI 10.1016/j.jenvman.2013.10.010
   Navarra C, 2021, ENVIRON EARTH SCI, V80, DOI 10.1007/s12665-021-09948-1
   Polack E, 2008, IDS BULL-I DEV STUD, V39, P16
   Pritchard H., 2016, GeoHumanities, V2, P354, DOI DOI 10.1080/2373566X.2016.1234355
   Rhoades JL, 2018, GERONTOLOGIST, V58, P567, DOI 10.1093/geront/gnw167
   Roux DJ, 2006, ECOL SOC, V11
   Sheth A, 2009, IEEE INTERNET COMPUT, V13, P87, DOI 10.1109/MIC.2009.77
   STAR SL, 1989, SOC STUD SCI, V19, P387, DOI 10.1177/030631289019003001
   Street R. B., 2015, EUR RES INN ROADM CL, DOI [10.2777/702151, DOI 10.2777/702151]
   Street R.B., 2016, Climate Services, V1, P2, DOI [DOI 10.1016/J.CLISER.2015.12.001, 10.1016/j.cliser.2015.12, DOI 10.1016/J.CLISER.2015.12]
   Sui D.Z., 2013, Crowdsourcing geographic knowledge, DOI [DOI 10.1007/978-94-007-4587-21, DOI 10.1007/978-94-007-4587-2_1]
   Suman AB, 2020, J ENVIRON PLANN MAN, V63, P546, DOI 10.1080/09640568.2019.1598852
   Tonurist P, 2017, VOLUNTAS, V28, P223, DOI 10.1007/s11266-016-9734-z
   Turnhout E, 2009, SCI PUBL POLICY, V36, P403, DOI 10.3152/030234209X442007
   Vaughan C, 2018, WEATHER CLIM SOC, V10, P373, DOI 10.1175/WCAS-D-17-0030.1
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Vollstedt B, 2021, CLIM SERV, V22, DOI 10.1016/j.cliser.2021.100225
   White DD, 2010, SCI PUBL POLICY, V37, P219, DOI 10.3152/030234210X497726
   Whitman G., 2015, J ENVIRON PLANN MAN, V58, P1291, DOI DOI 10.1080/09640568.2014.921596
   Wiek A, 2012, SUSTAIN SCI, V7, P5, DOI 10.1007/s11625-011-0148-y
   Williams DS, 2020, CLIM SERV, V19, DOI 10.1016/j.cliser.2020.100180
NR 68
TC 13
Z9 14
U1 3
U2 23
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD DEC
PY 2021
VL 24
AR 100273
DI 10.1016/j.cliser.2021.100273
EA NOV 2021
PG 10
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA YE1IC
UT WOS:000740883000001
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Little, LR
   Lin, BB
AF Little, L. Richard
   Lin, Brenda B.
TI A decision analysis approach to climate adaptation: a structured method
   to consider multiple options
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Simulations; Decision analysis; Adaptation pathway; Sea-level rise;
   Climate change; Beach recession
ID MANAGEMENT STRATEGY EVALUATION; FISHERIES MANAGEMENT; RISK;
   CONSERVATION; UNCERTAINTY; INFORMATION; ROBUST
AB Decision-making for climate adaptation operates in an uncertain environment. Formal processes to decision-making under uncertainty weigh the ability of a decision rule to achieve multiple and sometimes conflicting objectives in an evaluation procedure. Increasingly, computer simulation models are being applied for this reason, so that the effectiveness of decisions can be evaluated before actually implementing them in reality. In this paper, we develop a simple stochastic simulation model of beach recession under climate change in Australia and evaluate decision rules for beach replenishment in the context of three management objectives: (i) to reduce beach recession, (ii) reduce variation in beach recession, and (iii) do so cost-effectively. Results indicate that a decision to intervene and replenish the beach based on a trigger level would be effective at maintaining shoreline position, with relatively little variation, but did so at a relatively high cost of multiple interventions. A decision procedure to intervene at a fixed period resulted in greater shoreline position variation but constrained management efforts and costs. This structured approach offers an evidence-based process to decision-making that lays bare the assumptions upon which decisions are made. This, in turn, allows for a more complete analysis of all the uncertainties and better outcomes.
C1 [Little, L. Richard] CSIRO Oceans Atmosphere Flagship, GPO BOX 1538, Hobart, Tas 2001, Australia.
   [Lin, Brenda B.] CSIRO Land & Water Flagship, PMB 1,107-121 Stn St, Aspendale, Vic 3195, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO)
RP Lin, BB (corresponding author), CSIRO Land & Water Flagship, PMB 1,107-121 Stn St, Aspendale, Vic 3195, Australia.
EM brenda.lin@csiro.au
RI Lin, Brenda/A-8834-2011; Little, Rich/E-7578-2011
OI Lin, Brenda/0000-0002-6011-9172
FU CSIRO Climate Adaptation Flagship
FX We thank Russell Gorddard and Art Langston from the Land and Water
   Flagship of the CSIRO for their comments and suggestions in earlier
   drafts of the paper. This research was funded by the CSIRO Climate
   Adaptation Flagship.
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   [Anonymous], 2014, CARIAA ASSAR
   Bather John, 2000, Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions
   Beach D., 2002, Coastal Sprawl: The Effects of Urban Design on Aquatic Ecosystems of the United States
   Boschetti F, 2010, ENVIRON MODELL SOFTW, V25, P1075, DOI 10.1016/j.envsoft.2010.02.009
   Bunnefeld N, 2011, TRENDS ECOL EVOL, V26, P441, DOI 10.1016/j.tree.2011.05.003
   Callaghan DP, 2013, COAST ENG, V82, P64, DOI 10.1016/j.coastaleng.2013.08.007
   Collins D, 2009, INT J URBAN REGIONAL, V33, P147, DOI 10.1111/j.1468-2427.2009.00836.x
   Cowell PJ, 2006, J COASTAL RES, V22, P232, DOI 10.2112/05A-0018.1
   Dessai S, 2004, CLIM POLICY, V4, P107
   Dessai S., 2011, WORLD RESOURCES REPO
   Fankhauser S, 1999, ECOL ECON, V30, P67, DOI 10.1016/S0921-8009(98)00117-7
   Francis RICC, 1997, CAN J FISH AQUAT SCI, V54, P1699, DOI 10.1139/cjfas-54-8-1699
   Groves DG, 2007, GLOBAL ENVIRON CHANG, V17, P73, DOI 10.1016/j.gloenvcha.2006.11.006
   Hammond J.S., 1999, Smart choices: a practical guide to making better decisions
   Harwood J, 2000, BIOL CONSERV, V95, P219, DOI 10.1016/S0006-3207(00)00036-7
   Headache classification Committee of the International Headache Society (IHS), 2018, Cephalalgia, V38, P1, DOI [10.1177/0333102417738202, DOI 10.1177/0333102417738202, DOI 10.2833/9937]
   Heggenhougen HK, 2008, INT ENCY PUBLIC HLTH, P71, DOI 10.1016/B978-012373960-5.00332-4
   Hilborn Ray, 1997, V28
   Hillen R, 1993, DEV IMPLEMENTATION C
   Hunter J, 2010, CLIMATIC CHANGE, V99, P331, DOI 10.1007/s10584-009-9671-6
   Jongejan RB, 2011, AUST J CIV ENG, V9, P47, DOI 10.1080/14488353.2011.11463968
   Jotzo F, 2009, CLIM POLICY, V9, P402, DOI 10.3763/cpol.2009.0624
   Keeney R.L., 1976, Decisions with Multiple Objectives: Preferences and Value Tradeoffs
   Lempert RJ, 2007, RISK ANAL, V27, P1009, DOI 10.1111/j.1539-6924.2007.00940.x
   Mapstone BD, 2008, FISH RES, V94, P315, DOI 10.1016/j.fishres.2008.07.013
   Mariani A., 2012, GENERIC DESIGN COAST
   Milligan J, 2009, LAND USE POLICY, V26, P203, DOI 10.1016/j.landusepol.2008.01.004
   Milner-Gulland E.J., 2007, Conservation and sustainable use: a handbook of techniques
   NEW M., 2000, Integr. Assess, V1, P203, DOI DOI 10.1023/A:1019144202120
   New M, 2007, PHILOS T R SOC A, V365, P2117, DOI 10.1098/rsta.2007.2080
   Nicholls RJ., 1995, J Coast Res, P2643
   Peterman RM, 1999, HUM ECOL RISK ASSESS, V5, P231, DOI 10.1080/10807039991289383
   Plagányi ÉE, 2013, CLIMATIC CHANGE, V119, P181, DOI 10.1007/s10584-012-0596-0
   Punt AE, 1997, REV FISH BIOL FISHER, V7, P35, DOI 10.1023/A:1018419207494
   Raiffa H, 1979, DECISION ANAL INTRO
   Ranasinghe R, 2012, CLIMATIC CHANGE, V110, P561, DOI 10.1007/s10584-011-0107-8
   Rosenberg AA, 1993, CANADIAN SPECIAL PUB, V120
   Rosenzweig C, 2011, CLIMATIC CHANGE, V106, P93, DOI 10.1007/s10584-010-0002-8
   Sainsbury KJ, 2000, ICES J MAR SCI, V57, P731, DOI 10.1006/jmsc.2000.0737
   Short A, 2012, WAVE DOMINATED BEACH
   Smith MD, 2009, J ENVIRON ECON MANAG, V58, P58, DOI 10.1016/j.jeem.2008.07.011
   Stainforth DA, 2005, NATURE, V433, P403, DOI 10.1038/nature03301
   Weaver CP, 2013, WIRES CLIM CHANGE, V4, P39, DOI 10.1002/wcc.202
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
NR 45
TC 5
Z9 6
U1 2
U2 14
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1381-2386
EI 1573-1596
J9 MITIG ADAPT STRAT GL
JI Mitig. Adapt. Strateg. Glob. Chang.
PD JAN
PY 2017
VL 22
IS 1
BP 15
EP 28
DI 10.1007/s11027-015-9658-8
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EJ2JQ
UT WOS:000393036700002
DA 2025-01-10
ER

PT J
AU Szucs, M
   Schaffner, U
   Price, WJ
   Schwarzlaender, M
AF Szucs, Marianna
   Schaffner, Urs
   Price, William J.
   Schwarzlaender, Mark
TI Post-introduction evolution in the biological control agent Longitarsus
   jacobaeae (Coleoptera: Chrysomelidae)
SO EVOLUTIONARY APPLICATIONS
LA English
DT Article
DE aestivation; biological control agent; body size; climatic adaptation;
   contemporary evolution; larval development
ID LIFE-HISTORY ADAPTATION; ADAPTIVE EVOLUTION; LOCAL ADAPTATION;
   CLIMATE-CHANGE; TANSY RAGWORT; FLEA BEETLE; SENECIO-JACOBAEA; RAPID
   EVOLUTION; INVASIVE PLANT; GENETIC RESCUE
AB Rapid evolution has rarely been assessed in biological control systems despite the similarity with biological invasions, which are widely used as model systems. We assessed post-introduction climatic adaptation in a population of Longitarsus jacobaeae, a biological control agent of Jacobaea vulgaris, which originated from a low-elevation site in Italy and was introduced in the USA to a high-elevation site (Mt. Hood, Oregon) in the early 1980s. Life-history characteristics of beetle populations from Mt. Hood, from two low-elevation sites in Oregon (Italian origin) and from a high-elevation site from Switzerland were compared in common gardens. The performance of low- and high-elevation populations at a low- and a high-elevation site was evaluated using reciprocal transplants. The results revealed significant changes in aestival diapause and shifts in phenology in the Mt. Hood population, compared with the low-elevation populations. We found increased performance of the Mt. Hood population in its home environment compared with the low-elevation populations that it originated from. The results indicate that the beetles at Mt. Hood have adapted to the cooler conditions by life-history changes that conform to predictions based on theory and the phenology of the cold-adapted Swiss beetles.
C1 [Szucs, Marianna] Colorado State Univ, Dept Bioagr Sci & Pest Management, Ft Collins, CO 80523 USA.
   [Szucs, Marianna; Schwarzlaender, Mark] Univ Idaho, Dept Plant Soil & Entomol Sci, Moscow, ID 83843 USA.
   [Schaffner, Urs] CABI Europe Switzerland, Delemont, Switzerland.
   [Price, William J.] Univ Idaho, Stat Programs, Moscow, ID 83843 USA.
C3 Colorado State University; University of Idaho; University of Idaho
RP Szucs, M (corresponding author), Colorado State Univ, Dept Bioagr Sci & Pest Management, Ft Collins, CO 80523 USA.
EM marianna.szucs@colostate.edu
OI Szucs, Marianna/0000-0001-7972-9571
FU Palouse Cooperative Weed Management Area, Moscow, ID; US Forest Service
   Clearwater National Forest, Potlatch Ranger Station, Potlatch, ID;
   Potlatch Corporation, Spokane, WA; University of Idaho's Department of
   Plant, Soil and Entomological Sciences
FX We are grateful to Eric Coombs for assisting with setup and maintenance
   of field sites in Oregon. We thank Ruth Hufbauer and two reviewers for
   their thorough and insightful suggestions on this manuscript. We also
   thank Bradley L. Harmon and all assistants who helped with field or
   laboratory work. This research was partially funded by the Palouse
   Cooperative Weed Management Area, Moscow, ID; the US Forest Service
   Clearwater National Forest, Potlatch Ranger Station, Potlatch, ID; the
   Potlatch Corporation, Spokane, WA; and the University of Idaho's
   Department of Plant, Soil and Entomological Sciences. This is a
   publication of the Idaho Agricultural Experimental Station.
CR Abrams PA, 1996, AM NAT, V147, P381, DOI 10.1086/285857
   Bean D. W., 2012, EVOLUTIONAR IN PRESS
   Berner D, 2004, ECOGRAPHY, V27, P733, DOI 10.1111/j.0906-7590.2005.04012.x
   Blanckenhorn WU, 2004, INTEGR COMP BIOL, V44, P413, DOI 10.1093/icb/44.6.413
   BLANCKENHORN WU, 1995, J EVOLUTION BIOL, V8, P21, DOI 10.1046/j.1420-9101.1995.8010021.x
   Bossdorf O, 2005, OECOLOGIA, V144, P1, DOI 10.1007/s00442-005-0070-z
   Boulding EG, 2001, HEREDITY, V86, P313, DOI 10.1046/j.1365-2540.2001.00829.x
   Bradshaw WE, 2008, MOL ECOL, V17, P157, DOI 10.1111/j.1365-294X.2007.03509.x
   Colautti RI, 2010, P ROY SOC B-BIOL SCI, V277, P1799, DOI 10.1098/rspb.2009.2231
   Cox G.W., 2004, ALIEN SPECIES EVOLUT
   DINGLE H, 1990, OECOLOGIA, V84, P199, DOI 10.1007/BF00318272
   Dlugosch KM, 2008, MOL ECOL, V17, P431, DOI 10.1111/j.1365-294X.2007.03538.x
   FRICK KE, 1973, ANN ENTOMOL SOC AM, V66, P358, DOI 10.1093/aesa/66.2.358
   FRICK KE, 1972, ANN ENTOMOL SOC AM, V65, P406, DOI 10.1093/aesa/65.2.406
   FRICK KE, 1971, ANN ENTOMOL SOC AM, V64, P834, DOI 10.1093/aesa/64.4.834
   FRICK KE, 1970, CALIF AGR, V24, P12
   Garant D, 2007, FUNCT ECOL, V21, P434, DOI 10.1111/j.1365-2435.2006.01228.x
   Gienapp P, 2008, MOL ECOL, V17, P167, DOI 10.1111/j.1365-294X.2007.03413.x
   Gomulkiewicz R, 1999, THEOR POPUL BIOL, V55, P283, DOI 10.1006/tpbi.1998.1405
   Handley LJL, 2011, BIOCONTROL, V56, P409, DOI 10.1007/s10526-011-9386-2
   Harris P., 1984, BIOLOGICAL CONTROL P, P95
   Hawkes R.B., 1980, P INT S BIOLOGICAL C, P623
   Hedrick PW, 2011, CONSERV BIOL, V25, P1069, DOI 10.1111/j.1523-1739.2011.01751.x
   Hendry AP, 2011, EVOL APPL, V4, P159, DOI 10.1111/j.1752-4571.2010.00165.x
   Hendry AP, 2001, GENETICA, V112, P1, DOI 10.1023/A:1013368628607
   Hereford J, 2009, AM NAT, V173, P579, DOI 10.1086/597611
   Holt RD, 1997, AM NAT, V149, P563, DOI 10.1086/286005
   Hufbauer RA, 2005, BIOL CONTROL, V35, P227, DOI 10.1016/j.biocontrol.2005.04.004
   Hufbauer RA, 2002, ECOL APPL, V12, P66, DOI 10.1890/1051-0761(2002)012[0066:EFNEIP]2.0.CO;2
   Isaacson D. L., 1978, Proceedings of the 4th International Symposium on Biological Control of Weeds, Gainesville, 1976., P189
   Julien M.H., 1998, Biological Control of Weeds. A World Catalogue of Agents and Their Target Weeds, V4th
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Kinnison MT, 2001, GENETICA, V112, P145, DOI 10.1023/A:1013375419520
   Lambrinos JG, 2004, ECOLOGY, V85, P2061, DOI 10.1890/03-8013
   Lee CE, 2002, TRENDS ECOL EVOL, V17, P386, DOI 10.1016/S0169-5347(02)02554-5
   Littlefield J. L., 2008, Proceedings of the XII International Symposium on Biological Control of Weeds, La Grande Motte, France, 22-27 April, 2007, P573, DOI 10.1079/9781845935061.0573
   Maron JL, 2004, ECOL MONOGR, V74, P261, DOI 10.1890/03-4027
   MCEVOY P, 1991, ECOL APPL, V1, P430, DOI 10.2307/1941900
   McEvoy P. B., 2012, EVOLUTIONAR IN PRESS
   MOUSSEAU TA, 1991, ANNU REV ENTOMOL, V36, P511, DOI 10.1146/annurev.en.36.010191.002455
   Murray N.D., 1982, P17
   Myers J.H., 1980, P INT S BIOLOGICAL C, P91
   Orr MR, 1996, EVOLUTION, V50, P704, DOI 10.1111/j.1558-5646.1996.tb03880.x
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Phillips CB, 2008, J APPL ECOL, V45, P948, DOI 10.1111/j.1365-2664.2008.01461.x
   Puliafico K. P., 2008, Proceedings of the XII International Symposium on Biological Control of Weeds, La Grande Motte, France, 22-27 April, 2007, P200, DOI 10.1079/9781845935061.0200
   Reinhold K, 2002, J HERED, V93, P400, DOI 10.1093/jhered/93.6.400
   Reznick DN, 2001, GENETICA, V112, P183, DOI 10.1023/A:1013352109042
   Roderick GK, 2003, NAT REV GENET, V4, P889, DOI 10.1038/nrg1201
   Roff Derek, 2002, pi
   Root TL, 2003, NATURE, V421, P57, DOI 10.1038/nature01333
   Scott SM, 1987, BIOL SURVEY CANADA M, V62, P452, DOI 10.1086/415671
   Shingleton AW, 2007, BIOESSAYS, V29, P536, DOI 10.1002/bies.20584
   Stockwell CA, 2003, TRENDS ECOL EVOL, V18, P94, DOI 10.1016/S0169-5347(02)00044-7
   Szucs M., 2012, EVOLUTIONAR IN PRESS
   Szucs M, 2011, BIOL CONTROL, V58, P44, DOI 10.1016/j.biocontrol.2011.03.010
   Tallmon DA, 2004, TRENDS ECOL EVOL, V19, P489, DOI 10.1016/j.tree.2004.07.003
   Tauber M.J., 1986, SEASONAL ADAPTATIONS
   Whitney KD, 2008, DIVERS DISTRIB, V14, P569, DOI 10.1111/j.1472-4642.2008.00473.x
   WINDIG JJ, 1991, ENTOMOPHAGA, V36, P605, DOI 10.1007/BF02374443
NR 61
TC 38
Z9 41
U1 0
U2 57
PU WILEY-BLACKWELL
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1752-4571
J9 EVOL APPL
JI Evol. Appl.
PD DEC
PY 2012
VL 5
IS 8
BP 858
EP 868
DI 10.1111/j.1752-4571.2012.00264.x
PG 11
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA 060WL
UT WOS:000312808900008
PM 23346230
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU van der Voorn, T
   Pahl-Wostl, C
   Quist, J
AF van der Voorn, Tom
   Pahl-Wostl, Claudia
   Quist, Jaco
TI Combining backcasting and adaptive management for climate adaptation in
   coastal regions: A methodology and a South African case study
SO FUTURES
LA English
DT Article
ID SOCIOECONOMIC SCENARIOS; IMPACT ASSESSMENT; SUSTAINABILITY; UNCERTAINTY;
   RESILIENCE; POLICY; FUTURE; VULNERABILITY; PERSPECTIVE; SCIENCE
AB Developing adaptation strategies for deltaic and coastal regions is a major challenge, due to future uncertainties of climate change and complexity of the social-ecological systems to be managed. This paper investigates how desirable futures or normative scenarios approaches, in particular backcasting, can be used to develop more robust climate strategies in coastal regions. The paper develops a methodology in which participatory backcasting and adaptive management are combined, and its applicability is demonstrated for the Breede-Overberg coastal region in South Africa where a catchment management strategy has been developed. It is concluded that the methodology offers an adequate framework for developing and implementing long-term climate adaptation strategies and policies, including a transition management scheme for intermediate assessments. (C) 2011 Elsevier Ltd. All rights reserved.
C1 [van der Voorn, Tom; Pahl-Wostl, Claudia] Univ Osnabruck, Inst Environm Syst Res, D-49069 Osnabruck, Germany.
   [Quist, Jaco] Delft Univ Technol, Fac Technol, NL-2600 GA Delft, Netherlands.
C3 University Osnabruck; Delft University of Technology
RP van der Voorn, T (corresponding author), Univ Osnabruck, Inst Environm Syst Res, Barbarastr 12, D-49069 Osnabruck, Germany.
EM tvanderv@uni-osnabrueck.de
RI Pahl-Wostl, Claudia/ABW-9068-2022; Quist, Jaco/D-9679-2014;
   Van+Der+Voorn, Tom/K-9427-2019
OI Quist, Jaco/0000-0002-6365-4082; van der Voorn, Tom/0000-0003-1851-8089
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P1, DOI 10.1016/j.gloenvcha.2004.12.002
   Adger WN, 2000, PROG HUM GEOG, V24, P347, DOI 10.1191/030913200701540465
   Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Alcamo J., 2008, ENV FUTURES, P123, DOI 10.1016/S1574-101X
   Alcamo J, 2009, DEV INTEG ENVIRON, V2, P13
   [Anonymous], 1999, MULTIORGANIZATIONAL
   [Anonymous], 1996, Social Systems
   [Anonymous], 2005, Collapse: How Civilizations Choose to Fail and Succeed
   [Anonymous], 2001, TECHN SUMM CLIM CHAN
   [Anonymous], DESASTRES SON NATURA
   Arnell NW, 2004, GLOBAL ENVIRON CHANG, V14, P3, DOI 10.1016/j.gloenvcha.2003.10.004
   Beck U., 1977, RETHINKING MODERNITY
   Bell W., 2002, FDN FUTURE STUDIES H
   Berg S., 2000, UTIL POLICY, V9, P159, DOI [DOI 10.1016/S0957-1787(01)00012-1, 10.1016/S0957-1787(01)00012-1]
   Berkes F., 2003, ECOLOGY SOC, V9
   Berkes F., 1998, LINKING SOCIAL ECOLO
   Berkhout F, 2000, GLOBAL ENVIRON CHANG, V10, P165, DOI 10.1016/S0959-3780(00)00029-7
   Berkhout F, 2002, GLOBAL ENVIRON CHANG, V12, P83, DOI 10.1016/S0959-3780(02)00006-7
   Berkhout F., 2002, Greener Manag. Int, P37, DOI DOI 10.9774/GLEAF.3062.2002.SP.00005
   Biber E., 2009, CLIMATE CHANGE BACKL
   Bijker W., 1987, The Social Construction of Technological Systems, DOI DOI 10.1177/030631289019001010
   BOHLE HG, 2007, GEOGRAPHISCHE RUNDSC, V59, P20
   Borowski Ilke, 2008, European Environment, V18, P216, DOI 10.1002/eet.479
   Breede-Overberg Management Agency, 2010, 1 DRAFT BREED OV CAT
   Brooks H., 1986, Sustainable development of the biosphere
   Carlsson-Kanyama A, 2008, FUTURES, V40, P34, DOI 10.1016/j.futures.2007.06.001
   Cumming GS, 2006, ECOL SOC, V11
   De Laat B., 1996, SCRIPTS FUTURE TECHN
   Dessai S, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2005JD005919
   Dessai S, 2007, GLOBAL ENVIRON CHANG, V17, P1, DOI 10.1016/j.gloenvcha.2006.12.001
   Dewulf A, 2005, WATER SCI TECHNOL, V52, P115, DOI 10.2166/wst.2005.0159
   Dierkes M., 1996, Visions of technology: Social institutional factors shaping the development of new technologies
   Dierkes M., 1992, WISSENSCHAFTSZENTRUM
   Dobzhansky Theodosius., 1968, Population biology and evolution; proceedings of the international symposium, June 7-9, 1967, Syracuse, New York, P109
   Doll P., 2008, ENV FUTURES PRACTICE, P151
   Dortmans PJ, 2005, FUTURES, V37, P273, DOI 10.1016/j.futures.2004.07.003
   Dreborg KH, 1996, FUTURES, V28, P813, DOI 10.1016/S0016-3287(96)00044-4
   Durance P, 2010, TECHNOL FORECAST SOC, V77, P1488, DOI 10.1016/j.techfore.2010.06.007
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Giddens Anthony., 2009, POLITICS CLIMATE CHA
   GILOVICH T, 1981, J PERS SOC PSYCHOL, V40, P797, DOI 10.1037/0022-3514.40.5.797
   Girod B, 2009, ENVIRON SCI POLICY, V12, P103, DOI 10.1016/j.envsci.2008.12.006
   Glantz M.H., 1988, SOC RESPONSES REGION
   Godet M., 1987, Scenarios and Strategic Management
   GRIFFIN LJ, 1992, HIST METHOD, V25, P166, DOI 10.1080/01615440.1992.10112723
   Grin J, 2000, WISSENSCH TECHNIKFOL, V4, P9
   Gunderson L. H., 2002, Panarchy: understanding transformations in human and natural systems
   Harrison P., 1995, CLIMATE CHANGE AGR E
   Höjer M, 2000, FUTURES, V32, P613, DOI 10.1016/S0016-3287(00)00012-4
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Holling C.S., 1985, SCI PRAXIS COMPLEXIT, P217
   Holling C.S., 1978, Adaptive environmental assessment and management
   Holling CS., 1986, Sustainable Development and the Biosphere
   Holmberg J., 1998, Greener Management International, P30
   Hughes T.P., 1983, NETWORKS POWER ELECT, DOI DOI 10.56021/9780801828737
   Huitema D, 2009, ECOL SOC, V14
   Huntjens P, 2010, REG ENVIRON CHANGE, V10, P263, DOI 10.1007/s10113-009-0108-6
   IPCC, 2000, FIN DRAFT SPEC REP E
   Isendahl N, 2010, J ENVIRON MANAGE, V91, P844, DOI 10.1016/j.jenvman.2009.10.016
   Isendahl N, 2009, WATER RESOUR MANAG, V23, P3191, DOI 10.1007/s11269-009-9429-y
   Jacobson C, 2009, SOC NATUR RESOUR, V22, P484, DOI 10.1080/08941920902762321
   KAHN H, 1967, DAEDALUS, V96, P705
   Kemp R., 2001, SYSTEM INNOVATION TR, P137
   Klein RJT, 2005, ENVIRON SCI POLICY, V8, P579, DOI 10.1016/j.envsci.2005.06.010
   KORIAT A, 1980, J EXP PSYCHOL-HUM L, V6, P107, DOI 10.1037/0278-7393.6.2.107
   Lee K.N., 1999, CONSERV ECOL, V3, pxiii
   Leemans R, 2009, INTEGRATED REGIONAL, P312
   Lewis P.C.M., 2009, GREAT TRANSITION NAV
   List D, 2004, FUTURES, V36, P23, DOI 10.1016/S0016-3287(03)00140-X
   Loorbach D, 2006, ENVIRON POLICY, V44, P187
   Lovins A.B., 1977, Soft energy paths: Toward a durable peace
   LOVINS AB, 1976, FOREIGN AFF, V55, P65, DOI 10.2307/20039628
   Mahoney James., 2003, COMP HIST ANAL SOCIA
   Mambrey P, 2000, WISSENSCH TECHNIKFOL, V4, P33
   Mambrey P., 1992, P 13 WORLD COMP C 94, P223
   Martin BR, 2010, TECHNOL FORECAST SOC, V77, P1438, DOI 10.1016/j.techfore.2010.06.009
   Maxim L, 2011, ENVIRON SCI POLICY, V14, P482, DOI 10.1016/j.envsci.2011.01.003
   Pahl-Wostl C., 2007, Ecology and Society, V12, P30
   Pahl-Wostl C, 2002, AQUAT SCI, V64, P394, DOI 10.1007/PL00012594
   Pahl-Wostl C., 2005, NEWATER REPORT SERIE
   Pahl-Wostl C., 2008, Adaptive and Integrated Water Management: Coping with Complexity and Uncertainty
   Pahl-Wostl C, 2007, WATER RESOUR MANAG, V21, P49, DOI 10.1007/s11269-006-9040-4
   Pahl-Wostl C, 2006, ECOL SOC, V11
   Pahl-Wostl C, 2009, DEV INTEG ENVIRON, V2, P105
   Pahl-Wostl C, 2009, ECOL SOC, V14
   Pahl-Wostl C, 2009, GLOBAL ENVIRON CHANG, V19, P354, DOI 10.1016/j.gloenvcha.2009.06.001
   Parsons T., 1934, STRUCTURE SOCIAL ACT
   Pierson Paul., 2003, COMP HIST ANAL SOCIA, P177, DOI DOI 10.1017/CBO9780511803963.006
   Ponting C., 1991, GREEN HIST WORLD ENV
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Quist J., 2001, Int. J. Sustain. Dev., V4, P75, DOI DOI 10.1504/IJSD.2001.001547
   Quist J., 2007, Backcasting for a sustainable future: the impact after 10 years
   Quist J, 2006, FUTURES, V38, P1027, DOI 10.1016/j.futures.2006.02.010
   Quist J, 2011, TECHNOL FORECAST SOC, V78, P883, DOI 10.1016/j.techfore.2011.01.011
   Reilly JM, 1999, CLIMATIC CHANGE, V43, P745, DOI 10.1023/A:1005553518621
   Ringland G., 2002, Scenarios in Public Policy
   ROBINSON JB, 1988, TECHNOL FORECAST SOC, V33, P325, DOI 10.1016/0040-1625(88)90029-7
   ROBINSON JB, 1982, ENERG POLICY, V10, P337, DOI 10.1016/0301-4215(82)90048-9
   ROBINSON JB, 1990, FUTURES, V22, P820, DOI 10.1016/0016-3287(90)90018-D
   Rothman D.S., 2008, Environmental Futures: The practice of environmental scenario analysis, P37
   Rotmans JR., 2001, FORESIGHT J FUTURE S, V3, P15, DOI [DOI 10.1108/14636680110803003, 10.1108/14636680110803003]
   Sardar Z., 1999, RESCUING ALL OUR FUT
   Scheffer M, 2003, TRENDS ECOL EVOL, V18, P648, DOI 10.1016/j.tree.2003.09.002
   SCHOEMAKER PJH, 1993, STRATEGIC MANAGE J, V14, P193, DOI 10.1002/smj.4250140304
   Shapiro E., 1996, RECLAIMING COURAGE M, P3
   Smit B., 2000, CLIMATIC CHANGE, V45, P19, DOI DOI 10.1023/A:1005661622966
   Smit B., 1999, MITIG ADAPT STRAT GL, V4, P199, DOI [10.1023/a:1009652531101, DOI 10.1023/A:1009652531101, https://doi.org/10.1023/A:1009652531101]
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smithers J, 1997, GLOBAL ENVIRON CHANG, V7, P129, DOI 10.1016/S0959-3780(97)00003-4
   Sondeijker S, 2006, FORESIGHT, V8, P15, DOI 10.1108/14636680610703063
   Tewari DD, 2009, WATER SA, V35, P693
   Van der Heijden K., 1996, SCENARIOS ART STRATE
   van der Helm R, 2009, FUTURES, V41, P96, DOI 10.1016/j.futures.2008.07.036
   van der Sluijs JP, 2007, ENVIRON MODELL SOFTW, V22, P590, DOI 10.1016/j.envsoft.2005.12.020
   van der Sluijs JP, 2010, CURR OPIN ENV SUST, V2, P409, DOI 10.1016/j.cosust.2010.10.003
   van Notten PWF, 2005, TECHNOL FORECAST SOC, V72, P175, DOI 10.1016/j.techfore.2003.12.003
   van Notten PWF, 2003, FUTURES, V35, P423, DOI 10.1016/S0016-3287(02)00090-3
   van't Klooster SA, 2006, FUTURES, V38, P15, DOI 10.1016/j.futures.2005.04.019
   van' t Klooster SA, 2011, FUTURES, V43, P86, DOI 10.1016/j.futures.2010.10.015
   Vergragt PJ, 2011, TECHNOL FORECAST SOC, V78, P747, DOI 10.1016/j.techfore.2011.03.010
   Voss JP, 2006, REFLEXIVE GOVERNANCE FOR SUSTAINABLE DEVELOPMENT, P3
   VOSS JP, 2005, ESEE C LISB
   Walters C., 1986, ADAPTIVE MANAGEMENT
   Weaver P., 2000, Sustainable Technology Development
   Wisner BenBlaikie., 2005, At Risk: Natural Hazards, People's Vulnerability and Disasters, VSecond
NR 127
TC 72
Z9 76
U1 3
U2 38
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0016-3287
EI 1873-6378
J9 FUTURES
JI Futures
PD MAY
PY 2012
VL 44
IS 4
BP 346
EP 364
DI 10.1016/j.futures.2011.11.003
PG 19
WC Economics; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Business & Economics; Public Administration
GA 927DT
UT WOS:000302887900007
DA 2025-01-10
ER

PT J
AU Berkhout, F
AF Berkhout, F
TI Rationales for adaptation in EU climate change policies
SO CLIMATE POLICY
LA English
DT Article
DE climate change; adaptation; public policy
ID IMPACT
AB This article sets out a series of rationales for public policy related to adaptation to the impacts of climatic change in the EU. It begins by arguing that both mitigation and adaptation are necessary parts of a coordinated policy response to the problem of climatic change, However, the 'problem structure' of adaptation is significantly different from that of mitigation. For instance, adaptation may generate private benefits that are likely to be experienced over the short term, relative to benefits associated with the impacts of mitigation actions which are public and experienced over the longer term. This divergence influences public policy rationales for adaptation and poses challenges for the integration of mitigation and adaptation in climate policies. Five key challenges facing climate adaptation are identified, and these are used as a basis for proposing rationales for policy action on climate adaptation. These relate to: information provision and research; early warning and disaster relief, facilitating adaptation options; regulating the distributional impacts of adaptation; and regulating infrastructures. The article concludes by arguing that the real integration problem for adaptation policy relates to how it is embedded in sectoral policies such as agriculture and transport, rather than how to achieve integration with mitigation policies.
C1 Vrije Univ Amsterdam, Inst Environm Studies, NL-1081 HV Amsterdam, Netherlands.
C3 Vrije Universiteit Amsterdam
RP Vrije Univ Amsterdam, Inst Environm Studies, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands.
EM frans.berkhout@ivm.vu.nl
RI Berkhout, Frans/N-4196-2013
OI Berkhout, Frans/0000-0001-8668-0470
CR ADGER NN, 2004, 7 UEA TYND CTR
   Adger WN, 2003, ECON GEOGR, V79, P387
   [Anonymous], 1998, HUMAN CHOICE CLIMATE
   Arnell NW, 1998, CLIMATIC CHANGE, V39, P83, DOI 10.1023/A:1005339412565
   BERKHOUT F, 2004, 47 UEA TYND CTR CLIM
   *CEC, 2005, 200535 COM CEC
   Easterling W.E., 2004, COPING GLOBAL CLIMAT
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   FUKUI H, 1979, P WORLD CLIM C GEN, P426
   Hertin J, 2003, BUILD RES INF, V31, P278, DOI 10.1080/0961321032000097683
   Hewitt K., 1971, The Hazardousness of a place: A regional ecology of damaging events
   Houghton J.T., 2001, CONTRIBUTION WORKING, P1
   HULME M, 2002, UKCIP02 U E ANGL SCH
   KLEIN RJT, 1997, FCCCTP19973 UNFCC SE
   Maddison D, 2001, CLIMATIC CHANGE, V49, P193, DOI 10.1023/A:1010742511380
   Mendelsohn R, 2000, CLIMATIC CHANGE, V45, P553, DOI 10.1023/A:1005598717174
   Meyer WilliamB., 1998, HUMAN CHOICE CLIMATE, P217
   Mortimore Michael., 1989, ADAPTING DROUGHT FAR
   PARRY ML, 1986, SUSTAINABLE DEV BIOS, P378
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   ROSENZWEIG C, 1994, NATURE, V367, P133, DOI 10.1038/367133a0
   Smit B., 2003, CLIMATE CHANGE ADAPT, P9, DOI DOI 10.1142/97818609458160002
   Tol RSJ, 1998, GLOBAL ENVIRON CHANG, V8, P109, DOI 10.1016/S0959-3780(98)00004-1
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   *UNEP, 2004, EARL WARN EM ENV THR, V2
   Warrick R.A., 1986, Scope 29: The Greenhouse Effect, Climatic Change and Ecosystems, P393
   WILBANKS TJ, 2003, INTEGRATING MITIGATI
NR 27
TC 42
Z9 46
U1 2
U2 33
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PY 2005
VL 5
IS 3
BP 377
EP 391
PG 15
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA 991UN
UT WOS:000233839700010
DA 2025-01-10
ER

PT J
AU Brackel, L
   Boelens, R
   Bruins, B
   Doorn, N
   Pesch, U
AF Brackel, Lieke
   Boelens, Rutgerd
   Bruins, Bert
   Doorn, Neelke
   Pesch, Udo
TI People in PowerPoint Pixels: Competing justice claims and scalar
   politics in water development planning
SO POLITICAL GEOGRAPHY
LA English
DT Article
DE Scalar politics; Justice; Displacement; Informal settlements; Adaptation
   planning
ID ECOLOGICAL BOUNDARIES; GOVERNANCE; DISASTER; RISK
AB Coastal megacities all over the world face challenges related to climate adaptation, ecosystem protection and inclusive development. In response, governments develop high-level and long-term climate adaptation plans to guide coastal development. In Metro Manila, a consortium of Dutch and Philippine consultants developed the Manila Bay Sustainable Development Master Plan (MBSDMP). The planning team stressed the importance of inclusive and participatory planning, yet, the pre-set premises of the masterplan, such as the high-level and longterm planning scale and corresponding problem formulation, determined which justice claims were foregrounded in the project, disadvantaging small-scale fishing and informal settlement communities. 'Justice' is a contested concept. Hence, we deploy a critical theory and politics of expert knowledge lens to investigate how struggles over competing justice claims unfold in water development planning. The scalar politics as manifested in the MBSDMP planning process hides particular conceptions of justice while privileging others in congruence with the larger scale uneven political-economic development dynamics. We provide three examples of scale framing in the planning process that functioned to legitimize the contested displacement of informal settlements by pointing to economic development, disaster risk reduction, or environmental protection. Planning design choices involving scalar out-zooming enabled the uptake of these justice claims, while backgrounding the justice claims of negatively affected groups: namely, the urban poor and small-scale fishing communities. The case analysis provides conceptual-empirical insights relevant for coastal cities' grassroots and policy action platforms anticipating climate change impacts and strategizing their stance in the politics of climate adaptation planning.
C1 [Brackel, Lieke; Doorn, Neelke; Pesch, Udo] Delft Univ Technol, Fac Technol Policy & Management, Delft, Netherlands.
   [Boelens, Rutgerd; Bruins, Bert] Wageningen Univ & Res, Water Resources Management Grp, Wageningen, Netherlands.
   [Boelens, Rutgerd] Univ Amsterdam, Ctr Latin Amer Res & Documentat, Amsterdam, Netherlands.
   [Brackel, Lieke] Jaffalaan 7, NL-2628 BX Delft, Netherlands.
C3 Delft University of Technology; Wageningen University & Research;
   University of Amsterdam
RP Brackel, L (corresponding author), Jaffalaan 7, NL-2628 BX Delft, Netherlands.
EM a.k.c.brackel@tudelft.nl
RI Boelens, Rutgerd/E-5157-2012
OI Brackel, Lieke/0000-0002-0353-1291; Doorn, Neelke/0000-0002-1090-579X;
   boelens, rutgerd/0000-0002-8412-3109; Pesch, Udo/0000-0002-8980-5205
CR ABS CBN, 2019, ABS-CBN News
   ACCORD CARE Nederland CNDR, 2012, Training on disaster preparedness and contingency planning: Community based disaster risk management (CBDRM)
   Ajibade I, 2022, ANN AM ASSOC GEOGR, V112, P2230, DOI 10.1080/24694452.2022.2062290
   Ajibade I, 2019, CLIMATIC CHANGE, V157, P299, DOI 10.1007/s10584-019-02535-1
   Alvarez MK, 2019, INT J URBAN REGIONAL, V43, P227, DOI 10.1111/1468-2427.12757
   Anders Gunther., 1980, ANTIQUIERTHEIT MENSC, VII
   Asare Okyere S., 2015, Journal of Studies in Social Science, V13, P75
   Aspinwall N., 2019, The News Lens: Environment: Science and Policy for Sustainable Development
   Bakker M., 2017, Social justice at bay: The Dutch role in Jakartas coastal defence and land reclamation
   Bankoff G, 1999, PAC REV, V12, P381, DOI 10.1080/09512749908719297
   Barham E, 2001, SOC NATUR RESOUR, V14, P181, DOI 10.1080/08941920119376
   Barkan J, 2017, ANN AM ASSOC GEOGR, V107, P33, DOI 10.1080/24694452.2016.1230422
   Barnett C, 2018, ANN AM ASSOC GEOGR, V108, P317, DOI 10.1080/24694452.2017.1365581
   Barnett Clive, 2017, The Priority of Injustice: Locating Democracy in Critical Theory
   Boelens R, 2016, WATER INT, V41, P1, DOI 10.1080/02508060.2016.1134898
   Borras M. S. J., 2008, Citizens building responsive states, P1, DOI [10.1209/0295-5075/84/27003, DOI 10.1209/0295-5075/84/27003]
   Boskalis, 2020, Boskalis receives eur 1.5 billion land development project for Manila International Airport in the Philippines
   CARE Philippines ACCORD, 2020, Stakeholder feedback on the Manila bay sustainable development master plan results of consultations conducted by CARE and ACCORD
   Castelo M., 2019, Mongabay
   Cobarrubias S, 2020, POLIT GEOGR, V80, DOI 10.1016/j.polgeo.2020.102184
   Cohen A, 2014, ENVIRON PLANN D, V32, P128, DOI 10.1068/d0813
   COHEN JM, 1980, WORLD DEV, V8, P213, DOI 10.1016/0305-750X(80)90011-X
   Colven E, 2020, ENVIRON PLAN C-POLIT, V38, P961, DOI 10.1177/2399654420911947
   Cooke B., 2011, Participation: The new Tyranny?
   Cornwall A., 2008, Community Development Journal, V43, P269, DOI [DOI 10.1093/CDJ/BSN010, 10.1093/cdj/bsn010]
   Cox KR, 1998, POLIT GEOGR, V17, P1, DOI 10.1016/S0962-6298(97)00048-6
   Delaney D, 1997, POLIT GEOGR, V16, P93, DOI 10.1016/S0962-6298(96)00045-5
   Deltares, 2018, Dutch knowledge used to develop and protect Manila Bay-24 jan. 2018
   Deltares OIDCI Tractabel UPLBPI Engie, 2021, Stakeholder engagement report in reference materials
   DENR, 2019, Announcement Manila bay clean up program (2017-2022
   Duarte-Abadía B, 2023, TERRIT POLIT GOV, V11, P1480, DOI 10.1080/21622671.2021.1913216
   Dupuits E, 2020, ECOL ECON, V172, DOI 10.1016/j.ecolecon.2020.106625
   Dutch Expert Team, 2015, DRR mission report-Manila bay master plan-towards integrated management and development of Manila bay
   Engels B, 2021, POLIT GEOGR, V84, DOI 10.1016/j.polgeo.2020.102295
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   Escobar A, 2001, POLIT GEOGR, V20, P139, DOI 10.1016/S0962-6298(00)00064-0
   Evers J, 2019, J ENVIRON PLANN MAN, V62, P1636, DOI 10.1080/09640568.2019.1603843
   Fauveaud G, 2019, CONTEMP SOCIOL, V48, P217, DOI 10.1177/0094306119828696ll
   Ferguson J., 1994, Ecologist, V24, P176
   Flaminio S, 2021, WATER ALTERN, V14, P204
   Forst R., 2017, Normativity and Power: Analyzing Social Orders of Justification (C. Cronin
   Fraser N, 2005, NEW LEFT REV, P69
   Gabriel N, 2014, GEOGR COMPASS, V8, P38, DOI 10.1111/gec3.12110
   Gascon M., 2018, Philippine Daily Inquirer
   Gomez E. J., 2019, Manila Times
   Grove K, 2009, GEOFORUM, V40, P207, DOI 10.1016/j.geoforum.2008.09.005
   Harvey D., 1996, The Geographical Journal, V163, DOI [10.2307/3059769, DOI 10.2307/3059769]
   Harvey D, 1973, SOCIAL JUSTICE CITY
   Hasan S, 2020, ENVIRON SCI POLICY, V104, P161, DOI 10.1016/j.envsci.2019.11.001
   Hasan S, 2019, J ENVIRON PLANN MAN, V62, P1583, DOI 10.1080/09640568.2019.1592745
   Heynen N, 2018, PROG HUM GEOG, V42, P446, DOI 10.1177/0309132517693336
   Heynen N, 2016, PROG HUM GEOG, V40, P839, DOI 10.1177/0309132515617394
   Heynen N, 2014, PROG HUM GEOG, V38, P598, DOI 10.1177/0309132513500443
   Hilterman M., 2020, Dangerous red-tagging of environmental defenders in the Philippines
   Honneth A., 1982, Prax. Int.: Phil. J., V2, P12
   Human Cities Coalition, 2017, Manila's promising future: A conversation with H.E. Marion Derckx, The Netherlands Ambassador to the Philippines
   Jaggar A.M., 2009, Philosophical Topics, V37, P1
   Jones JP, 2017, ANTIPODE, V49, P138, DOI 10.1111/anti.12254
   Kanger L, 2022, POLIT GEOGR, V93, DOI 10.1016/j.polgeo.2021.102544
   Kurtz HE, 2003, POLIT GEOGR, V22, P887, DOI 10.1016/j.polgeo.2003.09.001
   Lefebvre Henri., 1979, CRITICAL SOCIOLOGY E
   Leitner H, 2007, T I BRIT GEOGR, V32, P116, DOI 10.1111/j.1475-5661.2007.00236.x
   LONG N, 1989, SOCIOL RURALIS, V29, P226, DOI 10.1111/j.1467-9523.1989.tb00368.x
   MacKinnon D, 2011, PROG HUM GEOG, V35, P21, DOI 10.1177/0309132510367841
   Marston SA, 2005, T I BRIT GEOGR, V30, P416, DOI 10.1111/j.1475-5661.2005.00180.x
   Martin Deborah., 2003, MOBILIZATION, V8, P143, DOI DOI 10.17813/MAIQ.8.2.M886W54361J81261
   Massey D, 2002, GEOGRAPHY, V87, P293
   MBSDMP, 2020, What is the Manila bay sustainable development master plan? Frequently asked questions
   MBSDMP, 2019, Our vision: A sustainable and resilient Manila bay
   Menga F, 2018, EARTHSCAN STUD WATER, P1
   Minkman E., 2018, Reconstructing the impasse in the transfer of delta plans: Evaluating the translation of Dutch water management strategies to Jakarta
   Minkman E, 2019, ENVIRON SCI POLICY, V96, P114, DOI 10.1016/j.envsci.2019.03.005
   Murakami A, 2005, LANDSCAPE URBAN PLAN, V70, P251, DOI 10.1016/j.landurbplan.2003.10.021
   Nauta H., 2018, Met Nederlandse hulp moet Manila weer de "Parel van de Orient"worden
   Nauta H., 2018, Trouw
   NEDA N.E. and D.A., 2017, PHIL DEV PLAN 2017 2
   Norman E., 2012, Water Alternatives, V5, P52
   OIDCI Tracetebel Engie UPLBFI Deltares, 2020, MBSDMP, P142, DOI [10.1017/CBO9781107415324.004, DOI 10.1017/CBO9781107415324.004]
   OIDCI Tractabel Engie UPLBPI Deltares, 2018, Manila bay area situation Atlas
   OIDCI Tractebel Engie UPLBFI Deltares, 2020, Final master plan Annex 1 ICZM planning framework
   OIDCI Tractebel Engie UPLBFI Deltares, 2018, Situation analysis report-focal theme reports-water quality improvement, P38
   OIDCI Tractebel Engie UPLBFI Deltares, Final master plan Annex 7 Process and activities
   OIDCI Tractebel Engie UPLBFI Deltares, 2018, Situation analysis report: Upgrading informal settlements
   Pesch U, 2024, CRIT REV INT SOC POL, V27, P95, DOI 10.1080/13698230.2021.1913887
   Przybylinski S, 2022, GEOGR COMPASS, V16, DOI 10.1111/gec3.12615
   Pugh J, 2005, AREA, V37, P384, DOI 10.1111/j.1475-4762.2005.00654.x
   Pugh J, 2005, INT DEV PLANN REV, V27, P385, DOI 10.3828/idpr.27.4.1
   Pulido L, 2018, ENVIRON PLAN E-NAT, V1, P76, DOI 10.1177/2514848618770363
   Purba FD, 2018, BMC PUBLIC HEALTH, V18, DOI 10.1186/s12889-018-5706-0
   Robbins P., 2012, Lawn people: How grasses, weeds, and chemicals make us who we are
   Rodan G, 2021, J CONTEMP ASIA, V51, P233, DOI 10.1080/00472336.2019.1607531
   Roth D, 2017, OCEAN COAST MANAGE, V150, P51, DOI 10.1016/j.ocecoaman.2017.02.020
   Schlosberg David., 2007, DEFINING ENV JUSTICE
   Seijger C, 2019, J ENVIRON PLANN MAN, V62, P1654, DOI 10.1080/09640568.2019.1622516
   Sen Amartya., 2009, The Idea of Justice
   Shannon M., 2019, Built Environment, V44, P397
   Shannon M., 2022, in de baai van Manilla staat haaks op bescherming natuur, V1-8
   Smith N., 1992, POSTMODERNISM SOCIAL, P57, DOI [10.1007/978-1-349-22183-7_4, DOI 10.1007/978-1-349-22183-7_4]
   Stravens M., 2018, Sustainable deltas, water special 2018, vice versa, V49-50
   Stravens M., 2018, Tijd voor tegengas. Duurzame Delta's-vice versa-water special
   Sultana F, 2022, POLIT GEOGR, V99, DOI 10.1016/j.polgeo.2022.102638
   Sultana F, 2022, GEOGR J, V188, P118, DOI 10.1111/geoj.12417
   Swyngedouw E, 2003, ANTIPODE, V35, P898, DOI 10.1111/j.1467-8330.2003.00364.x
   Swyngedouw Erik., 2004, Scale and Geographic Inquiry: Nature, Society, and Method, P129, DOI [10.1002/9780470999141.ch7, DOI 10.1002/9780470999141.CH7, 10.1002/9780470999141.CH7]
   Teves C., 2018, DENR sets tightened crackdown vs. pollution in Manila Bay
   The World Bank Group, 2017, Philippines urbanization review, DOI [10.1596/27667, DOI 10.1596/27667]
   The World Bank Group, 2017, Philippines urbanization review policy notes, DOI [10.1596/27141, DOI 10.1596/27141]
   Valente S, 2020, J ENVIRON PLANN MAN, V63, P389, DOI 10.1080/09640568.2018.1557609
   Van der Veen M., 2021, Both Ends News
   Van Lieshout M, 2017, J ENVIRON POL PLAN, V19, P550, DOI 10.1080/1523908X.2014.936581
   van Lieshout M, 2011, ECOL SOC, V16
   Walker G, 2009, ANTIPODE, V41, P614, DOI 10.1111/j.1467-8330.2009.00691.x
   Weinger BK, 2021, POLIT GEOGR, V88, DOI 10.1016/j.polgeo.2021.102409
   Woodhouse P, 2017, WORLD DEV, V92, P225, DOI 10.1016/j.worlddev.2016.11.014
   Young I. M., 1990, Justice and the Politics of difference (new Prince), DOI [10.1155/2010/706872, DOI 10.1155/2010/706872]
   Young IM, 1998, ANTIPODE, V30, P36, DOI 10.1111/1467-8330.00065
   Zeiderman A, 2016, ANTIPODE, V48, P809, DOI 10.1111/anti.12207
   Zeiderman A, 2016, J ROY ANTHROPOL INST, V22, P163, DOI 10.1111/1467-9655.12399
   Zeiderman A, 2012, ENVIRON PLANN A, V44, P1570, DOI 10.1068/a44283
   Zwarteveen M., 2018, Flows. Hypotheses
   Zwarteveen MZ, 2014, WATER INT, V39, P143, DOI 10.1080/02508060.2014.891168
NR 121
TC 2
Z9 2
U1 5
U2 11
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0962-6298
EI 1873-5096
J9 POLIT GEOGR
JI Polit. Geogr.
PD NOV
PY 2023
VL 107
AR 102974
DI 10.1016/j.polgeo.2023.102974
EA OCT 2023
PG 12
WC Geography; Political Science
WE Social Science Citation Index (SSCI)
SC Geography; Government & Law
GA X5AV8
UT WOS:001098584300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Xiao, J
   Yuizono, T
AF Xiao, Jing
   Yuizono, Takaya
TI Climate-adaptive landscape design: Microclimate and thermal comfort
   regulation of station square in the Hokuriku Region, Japan
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Climate adaptation; Outdoor thermal comfort; Urban microclimate;
   Landscape design; Landscape layout pattern; Vegetation configuration
ID PUBLIC SQUARES; MITIGATION STRATEGIES; NUMERICAL-SIMULATION; URBAN
   MICROCLIMATE; STREET-CANYONS; MICRO-CLIMATE; TILIA-CORDATA; GREEN AREAS;
   HOT-SUMMER; OUTDOOR
AB Strategic landscape design can ameliorate local thermal stress and enhance climate resilience in urban areas. Densely populated station squares are particularly important outdoor activity areas which more require the mitigation of thermal conditions during extreme weather. The traditional station square design focuses on the transport system and lacks the co-regulation of landscape services (e.g., climate change, scale, and element configuration). Moreover, holistic optimal design strategies are still deficient. This study examines how thermal comfort is positively affected by various landscape layout patterns, the configuration ratio of deciduous to evergreen trees and vegetation structure. We selected a typical station square of the Hokuriku region as an example, measured a landscape microclimate environment in winter and summer during extremely cold and hot days. The thermal comfort performance, represented by the Predicted Mean Vote (PMV) thermal index, was compared using the ENVI-met simulation to reproduce the original case and new landscape design scenarios. The results indicated that planting trees in an array layout pattern with low PMV distributions improved thermal performance at 14:00 (0.3 PMV increase in winter and 1.3 PMV decrease in summer). The tree configuration ratio is a critical greening indicator that also regulates thermal comfort during the day and night. The finds of the research can be used optimized scenarios as a guide for urban station square design to mitigate thermal comfort issues and to promote the development of station square planning complying with climate-adaptive design strategies and the construction of sustainable cities.
C1 [Xiao, Jing; Yuizono, Takaya] Japan Adv Inst Sci & Technol, Grad Sch Adv Sci & Technol, 1-1 Asahidai, Nomi, Ishikawa 9231292, Japan.
C3 Japan Advanced Institute of Science & Technology (JAIST)
RP Xiao, J (corresponding author), Japan Adv Inst Sci & Technol, Grad Sch Adv Sci & Technol, 1-1 Asahidai, Nomi, Ishikawa 9231292, Japan.
EM s1920419@jaist.ac.jp; yuizono@jaist.ac.jp
OI Yuizono, Takaya/0000-0002-9576-362X; Xiao, Jing/0000-0001-7346-3426
CR Abdi B, 2020, SUSTAIN CITIES SOC, V56, DOI 10.1016/j.scs.2020.102085
   Aboelata A, 2019, BUILD ENVIRON, V166, DOI 10.1016/j.buildenv.2019.106407
   Alfano FRD, 2011, BUILD ENVIRON, V46, P1361, DOI 10.1016/j.buildenv.2011.01.001
   [Anonymous], 2012, URBAN MICROCLIMATE D
   Battista G, 2019, SOL ENERGY, V180, P608, DOI 10.1016/j.solener.2019.01.074
   Chatzidimitriou A, 2015, ENERG BUILDINGS, V108, P156, DOI 10.1016/j.enbuild.2015.08.048
   Chen L, 2015, BUILD ENVIRON, V94, P644, DOI 10.1016/j.buildenv.2015.10.020
   Chen L, 2012, CITIES, V29, P118, DOI 10.1016/j.cities.2011.08.006
   Cui LH, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13052736
   Dain J., ICUC9 9 INT C URB CL
   Dimoudi A, 2003, ENERG BUILDINGS, V35, P69, DOI 10.1016/S0378-7788(02)00081-6
   El-Bardisy WM, 2016, PROCD SOC BEHV, V216, P206, DOI 10.1016/j.sbspro.2015.12.029
   Eliasson I, 2000, LANDSCAPE URBAN PLAN, V48, P31, DOI 10.1016/S0169-2046(00)00034-7
   Eliasson I, 2007, LANDSCAPE URBAN PLAN, V82, P72, DOI 10.1016/j.landurbplan.2007.01.020
   Fabbri K, 2020, BUILD ENVIRON, V175, DOI 10.1016/j.buildenv.2020.106816
   Gaspari J, 2018, SUSTAIN CITIES SOC, V42, P206, DOI 10.1016/j.scs.2018.07.015
   Gatto E, 2020, FORESTS, V11, DOI 10.3390/f11020228
   Gehan E., 2000, INFRASTRUCT PLANN RE, V17, P481, DOI [10.2208/JOURNALIP.17.481, DOI 10.2208/JOURNALIP.17.481]
   Ghaffarianhoseini A, 2015, BUILD ENVIRON, V87, P154, DOI 10.1016/j.buildenv.2015.02.001
   Gilani SIU, 2015, ENRGY PROCED, V75, P1373, DOI 10.1016/j.egypro.2015.07.218
   Gómez F, 2004, BUILD ENVIRON, V39, P1077, DOI 10.1016/j.buildenv.2004.02.001
   Gromke C, 2015, BUILD ENVIRON, V83, P11, DOI 10.1016/j.buildenv.2014.04.022
   Hong B, 2015, RENEW ENERG, V73, P18, DOI 10.1016/j.renene.2014.05.060
   Höppe P, 2002, ENERG BUILDINGS, V34, P661, DOI 10.1016/S0378-7788(02)00017-8
   Huang HJ, 2020, IOP C SER EARTH ENV, V467, DOI 10.1088/1755-1315/467/1/012215
   Huttner S., 7 INT C URB CLIM ICU
   Karakounos I, 2018, ENERG BUILDINGS, V158, P1266, DOI 10.1016/j.enbuild.2017.11.035
   Kariminia S, 2013, PROCD SOC BEHV, V85, P523, DOI 10.1016/j.sbspro.2013.08.381
   Kidokoro T., 2019, Transit-oriented development policies and station area development in Asian cities
   Kleerekoper L, 2012, RESOUR CONSERV RECY, V64, P30, DOI 10.1016/j.resconrec.2011.06.004
   Knez I, 2006, INT J BIOMETEOROL, V50, P258, DOI 10.1007/s00484-006-0024-0
   Koppe C., 2004, Heat Waves: Risks and Responses, V2
   Kottek M., 2006, Meteor. Z., V15, P259, DOI [10.1127/0941-2948/2006/0130, DOI 10.1127/0941-2948/2006/0110]
   Lin BR, 2008, J WIND ENG IND AEROD, V96, P1707, DOI 10.1016/j.jweia.2008.02.006
   Lindén J, 2016, URBAN FOR URBAN GREE, V20, P198, DOI 10.1016/j.ufug.2016.09.001
   Liu WW, 2016, ENERG BUILDINGS, V128, P190, DOI 10.1016/j.enbuild.2016.06.086
   Liu ZX, 2021, BUILD ENVIRON, V200, DOI 10.1016/j.buildenv.2021.107939
   Liu ZX, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9050198
   López-Cabeza VP, 2018, BUILD ENVIRON, V144, P129, DOI 10.1016/j.buildenv.2018.08.013
   Marcal NA, 2019, BUILD ENVIRON, V152, P145, DOI 10.1016/j.buildenv.2019.02.016
   Moonen P, 2012, FRONT ARCHIT RES, V1, P197, DOI 10.1016/j.foar.2012.05.002
   Morakinyo TE, 2016, BUILD ENVIRON, V103, P262, DOI 10.1016/j.buildenv.2016.04.025
   Moser A, 2017, INT J BIOMETEOROL, V61, P1095, DOI 10.1007/s00484-016-1290-0
   Ng E, 2012, BUILD ENVIRON, V47, P256, DOI 10.1016/j.buildenv.2011.07.014
   Nikolopoulou M, 2007, BUILD ENVIRON, V42, P3691, DOI 10.1016/j.buildenv.2006.09.008
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Ouyang WL, 2020, BUILD ENVIRON, V174, DOI 10.1016/j.buildenv.2020.106772
   Perini K., 2018, Nature Based Strategies for Urban and Building Sustainability, P119, DOI DOI 10.1016/B978-0-12-812150-4.00011-2
   Potchter O, 2018, SCI TOTAL ENVIRON, V631-632, P390, DOI 10.1016/j.scitotenv.2018.02.276
   Rahman MA, 2018, SCI TOTAL ENVIRON, V633, P100, DOI 10.1016/j.scitotenv.2018.03.168
   Rahman MA, 2017, AGR FOREST METEOROL, V232, P443, DOI 10.1016/j.agrformet.2016.10.006
   Robitu M, 2006, SOL ENERGY, V80, P435, DOI 10.1016/j.solener.2005.06.015
   Rui LY, 2019, BUILD SIMUL-CHINA, V12, P183, DOI 10.1007/s12273-018-0498-9
   Rui LY, 2018, FORESTS, V9, DOI 10.3390/f9040224
   Salata F, 2017, SUSTAIN CITIES SOC, V30, P79, DOI 10.1016/j.scs.2017.01.006
   Salata F, 2016, SUSTAIN CITIES SOC, V26, P318, DOI 10.1016/j.scs.2016.07.005
   Shahidan MF, 2012, BUILD ENVIRON, V58, P245, DOI 10.1016/j.buildenv.2012.07.012
   Shinichi S, 2021, STRENGTH JAPANS TOD
   Shooshtarian S, 2020, BUILD ENVIRON, V177, DOI 10.1016/j.buildenv.2020.106917
   Simon H, 2020, FORESTS, V11, DOI 10.3390/f11080869
   Sodoudi S, 2018, URBAN FOR URBAN GREE, V34, P85, DOI 10.1016/j.ufug.2018.06.002
   Spangenberg J., 2008, REV SBAU, V4, P1, DOI [10.5380/revsbau.v3i2.66265, DOI 10.5380/REVSBAU.V3I2.66265, https://doi.org/10.5380/revsbau.v3i2.66265]
   Srivanit M, 2013, BUILD ENVIRON, V66, P158, DOI 10.1016/j.buildenv.2013.04.012
   Stocco S, 2021, BUILD SIMUL-CHINA, V14, P763, DOI 10.1007/s12273-020-0691-5
   Stocco S, 2015, URBAN FOR URBAN GREE, V14, P323, DOI 10.1016/j.ufug.2015.03.001
   Thorsson S, 2007, ENVIRON BEHAV, V39, P660, DOI 10.1177/0013916506294937
   Yang YJ, 2019, BUILD ENVIRON, V159, DOI 10.1016/j.buildenv.2019.05.029
   Yang YJ, 2018, SUSTAIN CITIES SOC, V37, P563, DOI 10.1016/j.scs.2017.09.033
   Zhang AX, 2017, BUILD ENVIRON, V124, P369, DOI 10.1016/j.buildenv.2017.08.024
   Zhang L, 2018, BUILD ENVIRON, V130, P27, DOI 10.1016/j.buildenv.2017.12.014
   Zheng SL, 2016, URBAN FOR URBAN GREE, V18, P138, DOI 10.1016/j.ufug.2016.05.008
   Zölch T, 2019, BUILD ENVIRON, V149, P640, DOI 10.1016/j.buildenv.2018.12.051
NR 72
TC 30
Z9 30
U1 25
U2 120
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-1323
EI 1873-684X
J9 BUILD ENVIRON
JI Build. Environ.
PD MAR 15
PY 2022
VL 212
AR 108813
DI 10.1016/j.buildenv.2022.108813
EA FEB 2022
PG 19
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA 5E8NI
UT WOS:000865878600005
DA 2025-01-10
ER

PT J
AU Yu, ZW
   Yao, YW
   Yang, GY
   Wang, XR
   Vejre, H
AF Yu, Zhaowu
   Yao, Yawen
   Yang, Gaoyuan
   Wang, Xiangrong
   Vejre, Henrik
TI Strong contribution of rapid urbanization and urban agglomeration
   development to regional thermal environment dynamics and evolution
SO FOREST ECOLOGY AND MANAGEMENT
LA English
DT Article
DE Rapid urbanization; Land cover conversion; Regional thermal environment;
   Dynamic and evolution; Climate adaption and mitigation; Environmental
   Kuznets curve
ID LAND-SURFACE TEMPERATURE; HEAT-ISLAND; GREEN SPACE; MITIGATION
   TECHNOLOGIES; CLIMATE-CHANGE; LANDSCAPE; CITIES; PATTERN; IMPACTS; COVER
AB Urbanization has significantly transformed natural surfaces into impervious surfaces, which has subsequently disturbed the balance of the global surface thermal energy. However, key landscape dynamic transfer processes that can affect land surface temperature (LST) and regional thermal environment (RTE) remain poorly understood, especially in the context of urban agglomerations. Hence we selected one of the world's most rapidly urbanized regions - the Pearl-River-Delta Metropolitan Region (PRDR) located in southern China as the case. With the help of Google Cloud Computing, Markov model, and spatial analyses, we have further quantified the strong contributions of urbanization and urban agglomeration development to RTE dynamics and evolution. Specifically, we revealed (1) the cooling effects of ecological land loss and gain are significantly different, which provides evidence that the existing natural ecosystems (especially forests) are valuable for climatic adaptation because newly constructed ecological land does not provide the same cooling effect. (2) We found that the RTE is not only influenced by land cover patterns and process but also significantly dominated by the specific land conversion processes. (3) From 1995 to 2015 in the PRDR, built-up land increased significantly, while the ecological land was significantly reduced, and the isolated urban heat islands were gradually connected and interacted with each other, forming the regional heat island. (4) We also proposed that the relationship between urbanization rate and temperature (RLST) may conform to the Environmental Kuznets Curve. This study enhances the understanding of RTE dynamics and evolution in urban agglomeration and provides important insights into existing natural ecosystem protection and climate adaptation planning.
C1 [Yu, Zhaowu; Yao, Yawen; Yang, Gaoyuan; Vejre, Henrik] Univ Copenhagen, Dept Geosci & Nat Resource Management, Fac Sci, Copenhagen, Denmark.
   [Yu, Zhaowu] Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Shanghai, Peoples R China.
   [Wang, Xiangrong] Fudan Univ, Dept Environm Sci & Engn, Shanghai, Peoples R China.
C3 University of Copenhagen; Fudan University
RP Yu, ZW (corresponding author), Univ Copenhagen, Dept Geosci & Nat Resource Management, Fac Sci, Copenhagen, Denmark.; Yu, ZW (corresponding author), Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Shanghai, Peoples R China.
EM zhyu@ign.ku.dk
RI Gaoyuan, Yang/HKO-4087-2023; Yawen, Yao/HTO-6339-2023; Yu,
   Zhaowu/E-8032-2016; Vejre, Henrik/P-7142-2014
OI Yang, Gaoyuan/0000-0001-9735-6529; Yu, Zhaowu/0000-0003-4576-4541;
   Vejre, Henrik/0000-0002-6820-0389; Yang, Gaoyuan/0000-0002-9652-1323
FU Open Foundation of the State Key Laboratory of Urban and Regional
   Ecology of China [SKLURE2019-2-6]; Shanghai Key Lab for Urban Ecological
   Processes and Eco-Restoration [SHUES2019A01]; National Social Science
   Fund of China for Major Program [14ZDB140]; National Key Research and
   Development Program for the 13th Five Year Plan of China
   [2016YFC0502700]; China Scholarship Council [201504910797]
FX This study is financed by (1) Open Foundation of the State Key
   Laboratory of Urban and Regional Ecology of China (grant no.
   SKLURE2019-2-6); (2) Shanghai Key Lab for Urban Ecological Processes and
   Eco-Restoration (grant no. SHUES2019A01); (3) National Social Science
   Fund of China for Major Program (14ZDB140); (4) National Key Research
   and Development Program for the 13th Five Year Plan of China
   (2016YFC0502700); (4) China Scholarship Council (grant no.
   201504910797). We also thank you so much the reviewers for their
   constructive comments.
CR Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   [Anonymous], 2005, P SPIE
   [Anonymous], 2015, HEAT WAVE SOCIAL AUT, DOI DOI 10.7208/CHICAGO/9780226026718.001.0001
   [Anonymous], 2002, BOUNDARY LAYER CLIMA, DOI DOI 10.4324/9780203407219
   [Anonymous], 1996, Landscape Ecology in Theory and Practice: Pattern and Process
   [Anonymous], ENV SCI TECHNOL
   Bai X., 2000, International Review for Environmental Strategies, V1, P135
   Bakar S. B, 2016, IOP C SERIES EARTH E
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Cai DL, 2017, SCI TOTAL ENVIRON, V589, P200, DOI 10.1016/j.scitotenv.2017.02.148
   Cao Q, 2018, SCI TOTAL ENVIRON, V625, P416, DOI 10.1016/j.scitotenv.2017.12.290
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   Chapman S, 2017, LANDSCAPE ECOL, V32, P1921, DOI 10.1007/s10980-017-0561-4
   Chen YC, 2017, LANDSCAPE URBAN PLAN, V157, P247, DOI 10.1016/j.landurbplan.2016.06.014
   Dinda S, 2004, ECOL ECON, V49, P431, DOI 10.1016/j.ecolecon.2004.02.011
   Dronova I, 2018, URBAN FOR URBAN GREE, V34, P44, DOI 10.1016/j.ufug.2018.05.009
   Ellison D, 2017, GLOBAL ENVIRON CHANG, V43, P51, DOI 10.1016/j.gloenvcha.2017.01.002
   Fan HY, 2019, AGR FOREST METEOROL, V265, P338, DOI 10.1016/j.agrformet.2018.11.027
   Fang CL, 2017, J GEOGR SCI, V27, P1431, DOI 10.1007/s11442-017-1445-x
   Feng HH, 2014, ADV SPACE RES, V53, P463, DOI 10.1016/j.asr.2013.11.028
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Forman RTT, 2014, URBAN ECOLOGY: SCIENCE OF CITIES, P1
   Gilbert H, 2016, ENERG BUILDINGS, V114, P20, DOI 10.1016/j.enbuild.2015.06.023
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Hoag H, 2015, NATURE, V524, P402, DOI 10.1038/524402a
   Huang GL, 2016, LANDSCAPE ECOL, V31, P2507, DOI 10.1007/s10980-016-0437-z
   Jiao M, 2017, AGR FOREST METEOROL, V247, P293, DOI 10.1016/j.agrformet.2017.08.013
   Jiménez-Muñoz JC, 2014, IEEE GEOSCI REMOTE S, V11, P1840, DOI 10.1109/LGRS.2014.2312032
   Kang S, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-05252-y
   Kent CW, 2017, J WIND ENG IND AEROD, V169, P168, DOI 10.1016/j.jweia.2017.07.016
   Kuang WH, 2015, LANDSCAPE ECOL, V30, P357, DOI 10.1007/s10980-014-0128-6
   Ma T, 2012, REMOTE SENS ENVIRON, V124, P99, DOI 10.1016/j.rse.2012.04.018
   Madanian M, 2018, SUSTAIN CITIES SOC, V39, P650, DOI 10.1016/j.scs.2018.03.018
   O'Malley C, 2015, SUSTAIN CITIES SOC, V19, P222, DOI 10.1016/j.scs.2015.05.009
   Peng J, 2018, REMOTE SENS ENVIRON, V215, P255, DOI 10.1016/j.rse.2018.06.010
   Peng J, 2016, LANDSCAPE ECOL, V31, P1077, DOI 10.1007/s10980-015-0319-9
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Qiu GY, 2017, HABITAT INT, V68, P30, DOI 10.1016/j.habitatint.2017.07.009
   Ren Y, 2016, ENVIRON POLLUT, V216, P519, DOI 10.1016/j.envpol.2016.06.004
   Santamouris M, 2014, SOL ENERGY, V103, P682, DOI 10.1016/j.solener.2012.07.003
   Santamouris M, 2018, J CIV ENG MANAG, V24, P638, DOI 10.3846/jcem.2018.6604
   Santarnouris M, 2015, ENERG BUILDINGS, V98, P125, DOI 10.1016/j.enbuild.2014.08.050
   Seneviratne SI, 2006, NATURE, V443, P205, DOI 10.1038/nature05095
   Song X.-P, 2018, NATURE, V1
   Sun RH, 2018, J CLEAN PROD, V170, P601, DOI 10.1016/j.jclepro.2017.09.153
   Sun RH, 2017, ECOSYST SERV, V23, P38, DOI 10.1016/j.ecoser.2016.11.011
   Sun Y, 2014, NAT CLIM CHANGE, V4, P1082, DOI 10.1038/NCLIMATE2410
   Takada T, 2010, LANDSCAPE ECOL, V25, P561, DOI 10.1007/s10980-009-9433-x
   Taleghani M, 2018, RENEW SUST ENERG REV, V81, P2011, DOI 10.1016/j.rser.2017.06.010
   Tran DX, 2017, ISPRS J PHOTOGRAMM, V124, P119, DOI 10.1016/j.isprsjprs.2017.01.001
   Turner BL, 2007, P NATL ACAD SCI USA, V104, P20666, DOI 10.1073/pnas.0704119104
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wang Y, 2016, MATER TECHNOL, V31, P13, DOI 10.1179/1753555715Y.0000000017
   Wang YF, 2014, BUILD ENVIRON, V77, P88, DOI 10.1016/j.buildenv.2014.03.021
   Weng Qihao, 2007, Urban Ecosystems, V10, P203, DOI 10.1007/s11252-007-0020-0
   Wu JG, 2004, LANDSCAPE ECOL, V19, P125, DOI 10.1023/B:LAND.0000021711.40074.ae
   Xiong YZ, 2012, REMOTE SENS-BASEL, V4, P2033, DOI 10.3390/rs4072033
   Yu WJ, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9010045
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Yu Zhao-wu, 2015, Yingyong Shengtai Xuebao, V26, P636
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Yu ZW, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-25296-w
   Yu ZW, 2018, URBAN FOR URBAN GREE, V29, P113, DOI 10.1016/j.ufug.2017.11.008
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Zeng C, 2016, HABITAT INT, V55, P46, DOI 10.1016/j.habitatint.2016.02.006
   Zhou DC, 2018, SCI TOTAL ENVIRON, V628-629, P415, DOI 10.1016/j.scitotenv.2018.02.074
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
NR 68
TC 80
Z9 86
U1 8
U2 152
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0378-1127
EI 1872-7042
J9 FOREST ECOL MANAG
JI For. Ecol. Manage.
PD AUG 15
PY 2019
VL 446
BP 214
EP 225
DI 10.1016/j.foreco.2019.05.046
PG 12
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Forestry
GA IF8XN
UT WOS:000473376700021
DA 2025-01-10
ER

PT J
AU Toparlar, Y
   Blocken, B
   Vos, P
   van Heijst, GJF
   Janssen, WD
   van Hooff, T
   Montazeri, H
   Timmermans, HJP
AF Toparlar, Y.
   Blocken, B.
   Vos, P.
   van Heijst, G. J. F.
   Janssen, W. D.
   van Hooff, T.
   Montazeri, H.
   Timmermans, H. J. P.
TI CFD simulation and validation of urban microclimate: A case study for
   Bergpolder Zuid, Rotterdam
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Urban environment; Climate adaptation; Building aerodynamics; Heat
   stress and thermal comfort; Built environment; Urban physics
ID OUTDOOR THERMAL ENVIRONMENT; FIELD POLLUTANT DISPERSION; CONVECTIVE
   HEAT-TRANSFER; WIND-DRIVEN-RAIN; CLIMATE-CHANGE; COUPLED SIMULATION;
   CROSS-VENTILATION; STREET CANYONS; HUMAN HEALTH; ENERGY
AB Considering climate change and the rapid trend towards urbanization, the analysis of urban microclimate is gaining importance. The Urban Heat Island (UHI) effect and summer-time heat waves can significantly affect urban microclimate with negative consequences for human mortality and morbidity and building energy demand. So far, most studies on urban microclimate employed observational approaches with field measurements. However, in order to provide more information towards the design of climate adaptive urban areas, deterministic analyses are required. In this study, Computational Fluid Dynamics (CFD) simulations are performed to predict urban temperatures in the Bergpolder Zuid region in Rotterdam, which is planned to be renovated to increase its climate resilience. 3D unsteady Reynolds-averaged Navier-Stokes (URANS) simulations with the realizable k-epsilon turbulence model are performed on a high-resolution computational grid. The simulations include wind flow and heat transfer by conduction, convection and radiation. The resulting surface temperatures are validated using experimental data from high-resolution thermal infrared satellite imagery performed during the heat wave of July 2006. The results show that the CFD simulations are able to predict urban surface temperatures with an average deviation of 7.9% from the experimental data. It is concluded that CFD has the potential of accurately predicting urban microclimate. Results from CFD simulations can therefore be used to identify problem areas and to evaluate the effect of climate adaptation measures in these areas such as urban greening and evaporative cooling. (C) 2014 Elsevier Ltd. All rights reserved.
C1 [Toparlar, Y.; Blocken, B.; Janssen, W. D.; van Hooff, T.; Montazeri, H.] Eindhoven Univ Technol, Dept Built Environm, Bldg Phys & Serv, NL-5600 MB Eindhoven, Netherlands.
   [Toparlar, Y.; Vos, P.] Flemish Inst Technol Res, Mol, Belgium.
   [Blocken, B.] Katholieke Univ Leuven, Dept Civil Engn, Bldg Phys Sect, B-3001 Heverlee, Belgium.
   [van Heijst, G. J. F.] Eindhoven Univ Technol, Dept Appl Phys, Fluid Dynam Lab, NL-5600 MB Eindhoven, Netherlands.
   [Timmermans, H. J. P.] Eindhoven Univ Technol, Dept Built Environm, NL-5600 MB Eindhoven, Netherlands.
C3 Eindhoven University of Technology; VITO; KU Leuven; Eindhoven
   University of Technology; Eindhoven University of Technology
RP Toparlar, Y (corresponding author), Eindhoven Univ Technol, Bldg Phys & Serv, POB 513, NL-5600 MB Eindhoven, Netherlands.
EM y.toparlar@tue.nl
RI Montazeri, Hamid/H-9139-2012; Toparlar, Yasin/AAL-3063-2020; van Hooff,
   Twan/A-4695-2013; Blocken, Bert/A-1880-2009
OI Toparlar, Yasin/0000-0001-7919-6226; Blocken, Bert/0000-0003-2935-9562;
   van Hooff, Twan/0000-0002-7811-2745; Rosales Medina, Perla
   Yanet/0000-0003-3405-152X
FU Dutch Knowledge for Climate Research Program within the theme Climate
   Proof Cities (CPC)
FX This research was supported by the Dutch Knowledge for Climate Research
   Program within the theme Climate Proof Cities (CPC).
CR Albers RAW, 2015, BUILD ENVIRON, V83, P1, DOI 10.1016/j.buildenv.2014.09.006
   Allegrini J, 2014, BUILD ENVIRON, V72, P63, DOI 10.1016/j.buildenv.2013.10.021
   Allegrini J, 2012, J WIND ENG IND AEROD, V104, P464, DOI 10.1016/j.jweia.2012.02.003
   [Anonymous], 2012, WORLD URBANIZATION P
   [Anonymous], 2005, The Dynamics of Global Urban Expansion. Transport and Urban Development Department
   [Anonymous], 2009, ANSYS FLUENT Theory Guide
   Arnfield AJ, 1998, ENERG BUILDINGS, V27, P61, DOI 10.1016/S0378-7788(97)00026-1
   Arnfield AJ, 2003, INT J CLIMATOL, V23, P1, DOI 10.1002/joc.859
   Ashie Y, 1999, J WIND ENG IND AEROD, V81, P237, DOI 10.1016/S0167-6105(99)00020-3
   Berkovic S, 2012, SOL ENERGY, V86, P1173, DOI 10.1016/j.solener.2012.01.010
   Bjerg B, 2013, BIOSYST ENG, V116, P259, DOI 10.1016/j.biosystemseng.2013.06.012
   Blocken B, 2008, J WIND ENG IND AEROD, V96, P1817, DOI 10.1016/j.jweia.2008.02.049
   Blocken B, 2004, J WIND ENG IND AEROD, V92, P1079, DOI 10.1016/j.jweia.2004.06.003
   Blocken B, 2012, ENVIRON MODELL SOFTW, V30, P15, DOI 10.1016/j.envsoft.2011.11.009
   Blocken B, 2009, BUILD ENVIRON, V44, P2396, DOI 10.1016/j.buildenv.2009.04.004
   Blocken B, 2007, ATMOS ENVIRON, V41, P238, DOI 10.1016/j.atmosenv.2006.08.019
   Blocken B, 2014, J WIND ENG IND AEROD, V129, P69, DOI 10.1016/j.jweia.2014.03.008
   Blocken B, 2011, J BUILD PERFORM SIMU, V4, P157, DOI 10.1080/19401493.2010.513740
   Bo-ot LM, 2012, ENERGIES, V5, P3723, DOI 10.3390/en5103723
   Bruse M, 1998, ENVIRON MODELL SOFTW, V13, P373, DOI 10.1016/S1364-8152(98)00042-5
   Ca VT, 1999, J WIND ENG IND AEROD, V81, P181, DOI 10.1016/S0167-6105(99)00016-1
   Casey M, 2000, ERCOFYAC SPECIAL INT
   Cebeci T., 1977, Momentum Transfer in Boundary Layers
   Changnon SA, 1996, B AM METEOROL SOC, V77, P1497, DOI 10.1175/1520-0477(1996)077<1497:IARTTH>2.0.CO;2
   Chen H, 2004, ENERG BUILDINGS, V36, P1247, DOI 10.1016/j.enbuild.2003.07.003
   Chen H, 2008, BUILD ENVIRON, V43, P18, DOI 10.1016/j.buildenv.2006.11.039
   Chen H, 2009, BUILD ENVIRON, V44, P2290, DOI 10.1016/j.buildenv.2009.03.012
   Chen QY, 2009, BUILD ENVIRON, V44, P848, DOI 10.1016/j.buildenv.2008.05.025
   CHOI ECC, 1993, J WIND ENG IND AEROD, V46-7, P721, DOI 10.1016/0167-6105(93)90342-L
   Christen A, 2004, INT J CLIMATOL, V24, P1395, DOI 10.1002/joc.1074
   Conti S, 2005, ENVIRON RES, V98, P390, DOI 10.1016/j.envres.2004.10.009
   Di Sabatino S, 2013, INT J ENVIRON POLLUT, V52, P172, DOI 10.1504/IJEP.2013.058454
   Dimitrova R, 2009, BOUND-LAY METEOROL, V131, P223, DOI 10.1007/s10546-009-9368-4
   Emmanuel R, 2012, BUILD ENVIRON, V53, P137, DOI 10.1016/j.buildenv.2012.01.020
   Erell E., 2011, Urban Microclimate: Designing the Spaces Between Buildings
   Franke J, 2007, BEST PRACTICE GULDEL
   Fujino T, 1999, J WIND ENG IND AEROD, V81, P159, DOI 10.1016/S0167-6105(99)00014-8
   Garssen J, 2005, Euro Surveill, V10, P165
   Gousseau P, 2011, ATMOS ENVIRON, V45, P428, DOI 10.1016/j.atmosenv.2010.09.065
   Grimmond CSB, 2002, J APPL METEOROL, V41, P792, DOI 10.1175/1520-0450(2002)041<0792:THFIUA>2.0.CO;2
   GRIMMOND CSB, 1991, WATER RESOUR RES, V27, P1739, DOI 10.1029/91WR00557
   Haines A, 2006, PUBLIC HEALTH, V120, P585, DOI 10.1016/j.puhe.2006.01.002
   Heusinkveld BG, 2014, J GEOPHYS RES-ATMOS, V119, P677, DOI 10.1002/2012JD019399
   Hsieh CM, 2010, BUILD SIMUL-CHINA, V3, P51, DOI 10.1007/s12273-010-0306-7
   Jakeman AJ, 2006, ENVIRON MODELL SOFTW, V21, P602, DOI 10.1016/j.envsoft.2006.01.004
   Kaoru I, 2011, BUILD ENVIRON, V46, P1632, DOI 10.1016/j.buildenv.2011.01.029
   KATO S, 1992, J WIND ENG IND AEROD, V44, P2575, DOI 10.1016/0167-6105(92)90049-G
   Klok L, 2012, RESOUR CONSERV RECY, V64, P23, DOI 10.1016/j.resconrec.2012.01.009
   Kolokotroni M, 2012, ENERG BUILDINGS, V47, P302, DOI 10.1016/j.enbuild.2011.12.019
   Launder B. E., 1974, Computer Methods in Applied Mechanics and Engineering, V3, P269, DOI 10.1016/0045-7825(74)90029-2
   Li XT, 2005, BUILD ENVIRON, V40, P853, DOI 10.1016/j.buildenv.2004.08.022
   Lin BR, 2008, J WIND ENG IND AEROD, V96, P1707, DOI 10.1016/j.jweia.2008.02.006
   Ma J, 2012, BUILD SIMUL-CHINA, V5, P157, DOI 10.1007/s12273-012-0079-2
   Martilli A, 2002, BOUND-LAY METEOROL, V104, P261, DOI 10.1023/A:1016099921195
   Masson V, 2000, BOUND-LAY METEOROL, V94, P357, DOI 10.1023/A:1002463829265
   Memon RA, 2011, THEOR APPL CLIMATOL, V103, P441, DOI 10.1007/s00704-010-0310-y
   Memon RA, 2011, ENVIRON FLUID MECH, V11, P465, DOI 10.1007/s10652-010-9202-z
   Memon RA, 2010, BUILD ENVIRON, V45, P176, DOI 10.1016/j.buildenv.2009.05.015
   Mills G, 2006, THEOR APPL CLIMATOL, V84, P69, DOI 10.1007/s00704-005-0145-0
   Mirzaei PA, 2010, BUILD ENVIRON, V45, P2192, DOI 10.1016/j.buildenv.2010.04.001
   Mochida A, 1997, J WIND ENG IND AEROD, V67-8, P459, DOI 10.1016/S0167-6105(97)00060-3
   Mochida A, 2008, J WIND ENG IND AEROD, V96, P1498, DOI 10.1016/j.jweia.2008.02.033
   Moonen P, 2012, FRONT ARCHIT RES, V1, P197, DOI 10.1016/j.foar.2012.05.002
   Murakami S, 2006, FLUID DYN RES, V38, P108, DOI 10.1016/j.fluiddyn.2004.10.006
   MURAKAMI S, 1993, J WIND ENG IND AEROD, V46-7, P21, DOI 10.1016/0167-6105(93)90112-2
   Murakami S, 1999, J WIND ENG IND AEROD, V81, P57, DOI 10.1016/S0167-6105(99)00009-4
   NUNEZ M, 1980, GEOGR ANAL, V12, P373
   Offerle B, 2006, THEOR APPL CLIMATOL, V84, P103, DOI 10.1007/s00704-005-0148-x
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   OKE TR, 1992, ATMOS ENVIRON B-URB, V26, P433, DOI 10.1016/0957-1272(92)90050-3
   Oke TR, 1987, BOUNDARY LAYER CLIMA, DOI [10.4324/9780203407219, DOI 10.4324/9780203407219]
   Priyadarsini R, 2008, SOL ENERGY, V82, P727, DOI 10.1016/j.solener.2008.02.008
   Qu YF, 2012, J WIND ENG IND AEROD, V104, P474, DOI 10.1016/j.jweia.2012.03.008
   Ramponi R, 2012, BUILD ENVIRON, V53, P34, DOI 10.1016/j.buildenv.2012.01.004
   RICHARDS PJ, 1993, J WIND ENG IND AEROD, V46-7, P145, DOI 10.1016/0167-6105(93)90124-7
   Sarrat C, 2006, ATMOS ENVIRON, V40, P1743, DOI 10.1016/j.atmosenv.2005.11.037
   SHIH TH, 1995, COMPUT FLUIDS, V24, P227, DOI 10.1016/0045-7930(94)00032-T
   Smith C, 2008, ENERG POLICY, V36, P4558, DOI 10.1016/j.enpol.2008.09.011
   Stathopoulos T, 2006, J WIND ENG IND AEROD, V94, P769, DOI 10.1016/j.jweia.2006.06.011
   Takahashi K, 2004, ENERG BUILDINGS, V36, P771, DOI 10.1016/j.enbuild.2004.01.033
   Tan JG, 2010, INT J BIOMETEOROL, V54, P75, DOI 10.1007/s00484-009-0256-x
   Tominaga Y, 2008, J WIND ENG IND AEROD, V96, P1749, DOI 10.1016/j.jweia.2008.02.058
   Tominaga Y, 2013, ATMOS ENVIRON, V79, P716, DOI 10.1016/j.atmosenv.2013.07.028
   van Hooff T, 2010, ENVIRON MODELL SOFTW, V25, P51, DOI 10.1016/j.envsoft.2009.07.008
   Vos PEJ, 2013, ENVIRON POLLUT, V183, P113, DOI 10.1016/j.envpol.2012.10.021
   Watkiss P., 2011, The ClimateCost Project, Final Report" Volume, V1
   WIERINGA J, 1992, J WIND ENG IND AEROD, V41, P357, DOI 10.1016/0167-6105(92)90434-C
   Xu P, 2012, ENERGY, V44, P792, DOI 10.1016/j.energy.2012.05.013
   Yang XS, 2013, BUILD ENVIRON, V60, P93, DOI 10.1016/j.buildenv.2012.11.008
   Yoshie R, 2007, J WIND ENG IND AEROD, V95, P1551, DOI 10.1016/j.jweia.2007.02.023
   ,, 2007, Climate change 2007: Synthesis Report. Contribution of Working Group I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers
NR 91
TC 258
Z9 274
U1 24
U2 383
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-1323
EI 1873-684X
J9 BUILD ENVIRON
JI Build. Environ.
PD JAN
PY 2015
VL 83
SI SI
BP 79
EP 90
DI 10.1016/j.buildenv.2014.08.004
PG 12
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA AY5FA
UT WOS:000347597200007
OA Green Published, Green Submitted
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Planas-Carbonell, A
   Anguelovski, I
   Oscilowicz, E
   Shokry, G
   Perez-del-Pulgar, C
AF Planas-Carbonell, Aina
   Anguelovski, Isabelle
   Oscilowicz, Emilia
   Shokry, Galia
   Perez-del-Pulgar, Carmen
TI From greening the climate-adaptive city to green climate gentrification?
   Civic perceptions of short-lived benefits and exclusionary protection in
   Boston, Philadelphia, Amsterdam and Barcelona
SO URBAN CLIMATE
LA English
DT Article
DE Urban adaptation planning; Green urban infrastructure; Displacement;
   Climate injustice; Green climate gentrification; Europe; North America;
   Climate resilience
ID ADAPTATION; NEIGHBORHOODS; RESILIENCE
AB Municipal governments are increasingly promoting green climate-adaptive infrastructure projects to address climate threats and impacts while maximizing multiple socio-environmental benefits. Although these strategies are repeatedly advanced as "win-win" solutions for all, recent literature has drawn attention to numerous negative effects, especially the displacement and exclusion of vulnerable social groups, pointing at yet another layer of climate injustice. In this article, we focus our analysis on the experienced and/or perceived negative social effects of greening interventions for climate adaptation on historically marginalized groups through a cross-case qualitative com-parison of four neighborhoods in North American and European cities (Boston, Philadelphia, Amsterdam and Barcelona). Interviews conducted among a diverse sample of civic groups related to each neighborhood reveal that most respondents highly value green resilient infrastructures for their socio-environmental benefits. However, unless these green interventions are implemented alongside policies that guarantee equitable outcomes for all, then civic respondents mostly identify negative social impacts on marginalized residents, making those benefits short-lived. Most promi-nent negative impacts include physical displacement and the related threat of more displacement together with risks that new (green) real estate developments and resilient greening will remain exclusionary for marginalized groups. Such similar findings across different socio-political contexts point to the need for bolder policies that guarantee that investments in green climate adaptation interventions secure both environmental and social benefits in underinvested and environmentally neglected neighborhoods and mitigate the negative impacts of such interventions, namely socio-cultural and physical displacement and overall exclusionary climate protection.
C1 [Anguelovski, Isabelle] UAB Univ Autonoma Barcelona, BCNUEJ Barcelona Lab Urban Environm Justice & Sust, ICTA Inst Environm Sci & Technol, ICREA Institucio Catalana Recerca & Estudis Avanca, Barcelona, Spain.
   [Planas-Carbonell, Aina; Oscilowicz, Emilia; Shokry, Galia] UAB Univ Autonoma Barcelona, BCNUEJ Barcelona Lab Urban Environm Justice & Sust, ICTA Inst Environm Sci & Technol, Barcelona, Spain.
   [Perez-del-Pulgar, Carmen] UFZ Helmholtz Ctr Environm Res, Dept Environm Polit, Leipzig, Germany.
   [Perez-del-Pulgar, Carmen] Friedrich Schiller Univ, Dept Polit Sci, Jena, Germany.
   [Shokry, Galia] Kean Univ, Dept Environm & Sustainabil Sci, Barcelona, Spain.
C3 Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); Friedrich Schiller University of Jena
RP Anguelovski, I (corresponding author), UAB Univ Autonoma Barcelona, BCNUEJ Barcelona Lab Urban Environm Justice & Sust, ICTA Inst Environm Sci & Technol, ICREA Institucio Catalana Recerca & Estudis Avanca, Barcelona, Spain.
EM Isabelle.Anguelovski@uab.cat
RI Oscilowicz, Emilia/JGM-5412-2023; Shokry, Galia/ABP-5934-2022
OI Shokry, Galia/0000-0002-2959-3677
FU European Research Council [678034, CEX2019-000940-M]; Spanish Ministry
   of Science; European Research Council (ERC) [678034] Funding Source:
   European Research Council (ERC)
FX The study was funded by the European Research Council under grant
   agreement [No 678034] and CEX2019-000940-M for the Maria de Maetzu from
   the Spanish Ministry of Science. None of the funding organizations were
   involved in the design, analysis or writing of this article.
CR Aerts R, 2018, BRIT MED BULL, V127, P5, DOI 10.1093/bmb/ldy021
   Al Sayah M., 2021, EGU GEN ASSEMBLY C A
   Anguelovski Isabelle, 2021, Health Place, V72, P102698, DOI 10.1016/j.healthplace.2021.102698
   Anguelovski I, 2019, P NATL ACAD SCI USA, V116, P26139, DOI 10.1073/pnas.1920490117
   Anguelovski I, 2019, PROG HUM GEOG, V43, P1064, DOI 10.1177/0309132518803799
   Anguelovski I, 2018, URBAN GEOGR, V39, P458, DOI 10.1080/02723638.2017.1349987
   Anguelovski I, 2018, LANCET PUBLIC HEALTH, V3, pE270, DOI 10.1016/S2468-2667(18)30096-3
   Anguelovski I, 2016, J PLAN EDUC RES, V36, P333, DOI 10.1177/0739456X16645166
   Anguelovski Isabelle, 2021, GREEN CITY SOCIAL IN
   Aune KT, 2020, ENVIRON RES, V185, DOI 10.1016/j.envres.2020.109384
   Benedict M. A., 2002, Renewable Resources Journal, V20, P12
   BPDA, 2020, BOST NUMB
   BPDA, 2017, E BOST
   Bulkeley H, 2013, LOCAL ENVIRON, V18, P646, DOI 10.1080/13549839.2013.788479
   City of Philadelphia, 2019, HLTH CITY 2019
   Cole H.V., 2020, Cities Health, P1, DOI DOI 10.1080/23748834.2020.1785176
   Connolly JJT, 2021, FRONT ECOL EVOL, V9, DOI 10.3389/fevo.2021.621783
   Ding L, 2016, REG SCI URBAN ECON, V61, P38, DOI 10.1016/j.regsciurbeco.2016.09.004
   European Commission, 2020, ADAPTATION CLIMATE C
   Fainstein SS, 2008, INT J URBAN REGIONAL, V32, P768, DOI 10.1111/j.1468-2427.2008.00826.x
   Fusch P, 2018, J SOCIAL CHANGE, V10, P2, DOI DOI 10.5590/JOSC.2018.10.1.02
   Gaffin SR, 2012, NAT CLIM CHANGE, V2, P704, DOI 10.1038/nclimate1685
   Gaston M., 2021, ELS VEINS DELS ENTOR
   Gibbons J, 2020, URBAN STUD, V57, P1143, DOI 10.1177/0042098019829331
   Gibbons J, 2019, SSM-POPUL HLTH, V7, DOI 10.1016/j.ssmph.2019.100358
   Gould KA, 2018, CITY COMMUNITY, V17, P12, DOI 10.1111/cico.12283
   Haase D, 2017, HABITAT INT, V64, P41, DOI 10.1016/j.habitatint.2017.04.005
   Hopkins A.L., 2012, HUNTING PARK AIR QUA
   Hyra D, 2019, HOUS POLICY DEBATE, V29, P421, DOI 10.1080/10511482.2018.1529695
   Jennings J., 2016, Trotter Review, V23, P4
   Keenan JM, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabb32
   Kim SK, 2022, URBAN STUD, V59, P360, DOI 10.1177/0042098021989951
   Llop NL, 2017, URBAN RES PRACT, V10, P120, DOI 10.1080/17535069.2017.1250522
   Maiorano G, 2020, GREEN CITY CLEAN WAT
   Marcuse P., 1985, J URBAN CONT LAW, V28.1, P195, DOI DOI 10.1525/SP.2007
   Meerow S, 2020, CITIES, V100, DOI 10.1016/j.cities.2020.102621
   Meerow S, 2019, URBAN GEOGR, V40, P309, DOI 10.1080/02723638.2016.1206395
   Mees H., 2011, Climate Law, V2, P251, DOI [DOI 10.1163/CL-2011-036, 10.3233/CL-2011-036, DOI 10.3233/CL-2011-036]
   Moeys N, 2021, MOSTLY TRUE NETHERLA
   Nordgren J, 2016, ENVIRON SCI POLICY, V66, P344, DOI 10.1016/j.envsci.2016.05.006
   OOS, 2020, GREENW PHIL
   Oscilowicz E., 2022, CITIES HLTH, P1, DOI DOI 10.1080/23748834.2022.2072057
   Oscilowicz E., 2021, Policy and Planning Tools for Urban Green Justice: Fighting Displacement and Gentrification and Improving Accessibility and Inclusiveness to Green Amenities
   Oscilowicz E, 2020, LOCAL ENVIRON, V25, P765, DOI 10.1080/13549839.2020.1835849
   Perez-del-Pulgar C., 2021, GREEN CITY SOCIAL IN
   Perez-del-Pulgar Carmen, 2021, GREEN CITY SOCIAL IN, P267
   Planas-Carbonell A, 2021, SOCIAL EFFECTS GREEN
   Saunders B, 2018, QUAL QUANT, V52, P1893, DOI 10.1007/s11135-017-0574-8
   Shi LD, 2016, NAT CLIM CHANGE, V6, P131, DOI 10.1038/NCLIMATE2841
   Shojaee Far M, 2019, DEALING GEOPOLITICAL
   Shokry G, 2022, HOUS POLICY DEBATE, V32, P211, DOI 10.1080/10511482.2021.1944269
   Shokry G, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100539
   Shokry Galia., 2021, The Green City and Social Injustice: 21 Tales from North America and Europe
   Statista, 2022, TOT POP AMST 2009 20
   Statistical Institute of Catalonia, 2020, MUN XIFR BARC
   van Gent W, 2018, URBAN STUD, V55, P2337, DOI 10.1177/0042098017717214
   Veldboer L., 2011, RC21 C AMST
   Versey HS, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16234633
NR 58
TC 14
Z9 15
U1 17
U2 48
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0955
J9 URBAN CLIM
JI Urban CLim.
PD MAR
PY 2023
VL 48
AR 101295
DI 10.1016/j.uclim.2022.101295
EA JAN 2023
PG 17
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 8H5LX
UT WOS:000921075900001
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Kimengsi, JN
   Akumbo, CM
   Balgah, RA
   Tingum, EN
   Tume, SJP
   Akhere, GS
AF Kimengsi, Jude Ndzifon
   Akumbo, Chia Michael
   Balgah, Roland Azibo
   Tingum, Ernest Ngeh
   Tume, Suiven John Paul
   Akhere, Gwan Solange
TI Farm-based climate adaptation dynamics: insights from the vegetable
   sector in the Western Highlands of Cameroon
SO COGENT SOCIAL SCIENCES
LA English
DT Article
DE climate adaptation; evolution; vegetable farmers; crop performance;
   determinants; Cameroon
ID SUB-SAHARAN AFRICA; FOOD SECURITY; SYSTEMS; REGION
AB Agro-based climate adaptation has gained traction in scholarly and policy circles, albeit with limited comprehensive empirical evidence on the pathways of crop sector-specific adaptation approaches in sub-Saharan Africa (SSA). To stem this knowledge gap, this study examines the evolution of farm-based climate adaptation practices in the vegetable subsector of Cameroon's western highlands. Specifically, we (i) explore the different adaptation practices, (ii) estimate the determinants of farm-based adaptation, and (iii) determine the effects of farm-based adaptation on vegetable performance. Data were collected from a representative sample of farming households (N = 150) in two communities using a semi-structured questionnaire, complemented by key informant interviews (N = 10) and focus group discussions (N = 5). The Product Moment Correlation established an evolution from traditional practices to more modern scientific practices with changing climate, as vegetable farmers shifted from using local seeds to improved ones, intensified pest control strategies and adopted water pump-based irrigation practices. The binary logistic regression model revealed that belonging to farming groups, increase in income and access to credit significantly explained farm-based adaptation (p = 0.041). Furthermore, farm-based practices were significantly reflected in crop performance, mirrored through an increase in vegetable quantity (p = 0.003) and perceived quality (p = 0.046). The results suggest the need for further research to blend traditional and conventional adaptation approaches, and to create enabling environments to foster social capital (belonging to groups) and access to credit as key levers for climate-resilient vegetable production in the western highlands of Cameroon.
C1 [Kimengsi, Jude Ndzifon] Tech Univ Dresden, Fac Environm Sci, Forest Inst & Int Dev FIID Res Grp, Dresden, Germany.
   [Kimengsi, Jude Ndzifon] Univ Bamenda, Dept Geog, Bamenda, Cameroon.
   [Akumbo, Chia Michael; Tume, Suiven John Paul; Akhere, Gwan Solange] Univ Bamenda, Dept Geog & Planning, Bamenda, Cameroon.
   [Balgah, Roland Azibo] Univ Bamenda, Coll Technol, Bamenda, Cameroon.
   [Tingum, Ernest Ngeh] Univ Namibia, Dept Econ, Windhoek, Namibia.
C3 Technische Universitat Dresden; University of Namibia
RP Kimengsi, JN (corresponding author), Tech Univ Dresden, Fac Environm Sci, Forest Inst & Int Dev FIID Res Grp, Dresden, Germany.
EM jude_ndzifon.kimengsi@tu-dresden.de
RI Balgah, Roland/AGT-9655-2022; Tingum, Ernest/AAL-5646-2021
OI Tingum, Ernest Ngeh/0000-0002-2309-9694; Kimengsi, Jude
   Ndzifon/0000-0002-1927-7443; John Paul Tume, Suiven/0000-0002-2159-4608
CR Abass R., 2018, West African Journal of Applied Ecology, V26, P56
   Abid M, 2015, EARTH SYST DYNAM, V6, P225, DOI 10.5194/esd-6-225-2015
   Afari-Sefa V, 2018, ECON BULL, V38, P1231
   Alhassan H, 2020, MARGIN, V14, P226, DOI 10.1177/0973801020904490
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Angelsen A., 2011, Measuring livelihoods and environmental dependence:methods for research and fieldwork
   Angong, 2005, VILLAGE STUDY REPORT
   [Anonymous], 2008, HUNG RIS
   Apata T G., 2009, INT ASS AGR ECONOMIS
   Arimi K., 2014, Journal of Agriculture and Rural Development in the Tropics and Subtropics, V115, P91
   Armi K., 2015, DETERMINANTS CLIMATE
   Aryal J. P., 2021, Environ. Challenges, V3, P100035, DOI [10.1016/j.envc.2021.100035, DOI 10.1016/J.ENVC.2021.100035]
   Azibo BR, 2015, PROCEDIA ENVIRON SCI, V29, P126, DOI 10.1016/j.proenv.2015.07.214
   Bate BG, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11071921
   Batung ES, 2023, ENVIRON DEV SUSTAIN, V25, P321, DOI 10.1007/s10668-021-02056-x
   Bele MY, 2013, CLIMATIC CHANGE, V119, P875, DOI 10.1007/s10584-013-0738-z
   Bisson L., 2020, COVID-19 impact on West African value chains
   Borras SM, 2009, J PEASANT STUD, V36, P5, DOI 10.1080/03066150902820297
   Calzadilla A, 2014, WATER RESOUR ECON, V5, P24, DOI 10.1016/j.wre.2014.03.001
   Cameroon H., 2001, TUBAH MONOGRAPHIC ST
   Campbell BM, 2016, GLOB FOOD SECUR-AGR, V11, P34, DOI 10.1016/j.gfs.2016.06.002
   Clay N, 2019, WORLD DEV, V116, P1, DOI 10.1016/j.worlddev.2018.11.022
   Croft MM, 2018, J DEV STUD, V54, P758, DOI 10.1080/00220388.2017.1308487
   Dahal R., 2019, SAARC J AGR, V17, P239, DOI [10.3329/sja.v17i2, DOI 10.3329/SJA.V17I2]
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Diallo A, 2020, CLIMATIC CHANGE, V159, P309, DOI 10.1007/s10584-020-02684-8
   Dumba H., 2021, AFRICAN HDB CLIMATE, P1033, DOI [10.1007/978-3-030-45106-6_29, DOI 10.1007/978-3-030-45106-6_29]
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   FAO, 2016, CLIM CHANG PRED SUB
   Gujarati DN, 2009, The McGraw-Hill Series
   Gur A. S., 2015, Environment and Natural Resources Research, V5, P14
   Ikeme J., 2003, Mitigation and Adaptation Strategies for Global Change, V8, P29, DOI 10.1023/A:1025838610473
   Jiotsa A., 2015, J ALPINE RES, V103, P1
   Ketaren K., 2017, International Journal ofApplied Engineering Research, V12, P9067
   Kimengsi J. N., 2013, Environment and Natural Resources Research, V3, P144
   Kimengsi J.N., 2022, DO ENDOGENOUS CULTUR
   Kimengsi J.N., 2013, Greener J Agric Sci, V3, P606, DOI [DOI 10.15580/GJAS.2013.3.022713505, 10.15580/GJAS.2013.3.022713505]
   Kimengsi JN, 2022, ENVIRON SCI POLICY, V128, P68, DOI 10.1016/j.envsci.2021.11.010
   Kimengsi JN, 2021, FOREST POLICY ECON, V125, DOI 10.1016/j.forpol.2021.102406
   Kimengsi JN, 2020, SOC NATUR RESOUR, V33, P876, DOI 10.1080/08941920.2020.1769243
   Kimengsi JN, 2015, PROCEDIA ENVIRON SCI, V29, P117, DOI 10.1016/j.proenv.2015.07.196
   Long J. S., 2006, REGRESSION MODELS CA
   Maddison DavidJ., 2007, PERCEPTION ADAPTATIO, DOI 10.1596/1813-9450-4308
   Marie M, 2020, HELIYON, V6, DOI 10.1016/j.heliyon.2020.e03867
   Meza FJ, 2009, CLIMATIC CHANGE, V94, P143, DOI [10.1007/s10584-009-9544-z, 10.1007/s10584-009-9544-Z]
   Mitter H, 2019, ENVIRON MANAGE, V63, P804, DOI 10.1007/s00267-019-01158-7
   Molua E., 2007, ASSESSING IMPACT CLI
   Nabikolo D., 2012, African Crop Science Journal, V20, P203
   Nchu IN, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11143767
   Nhamo L, 2019, AGRICULTURE-BASEL, V9, DOI 10.3390/agriculture9020030
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Nji T.M., 2019, SOCIOL INT J, V3, P372, DOI [10.15406/sij.2019.03.00202, DOI 10.15406/SIJ.2019.03.00202]
   Ojo TO, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2019.04.007
   Ostrom E., 1990, GOVERNING COMMONS EV
   Oyekale AS, 2012, J FOOD AGRIC ENVIRON, V10, P1562
   Pretzsch J., 2014, FORESTS RURAL DEV, DOI [10.1007/978-3-642-41404-6, DOI 10.1007/978-3-642-41404-6]
   Tingem M, 2009, AGRON SUSTAIN DEV, V29, P247, DOI 10.1051/agro:2008053
   Tiwari K.R., 2014, International Journal of Multidisciplinary and Current Research, P234
   Tubah Council, 2012, TUB COUNC DEV PLAN P
   Tui SHK, 2021, CLIMATIC CHANGE, V168, DOI 10.1007/s10584-021-03151-8
   Tume S.J.P., 2021, INT J ENVIRON STUD, V78, P1, DOI [10.1080/00207233.2020.1977538, DOI 10.1080/00207233.2020.1977538]
   Tume SJP, 2019, CLIMATE, V7, DOI 10.3390/cli7120138
   World Bank, 2010, Economic evaluation of climate change adaptation projects: Approaches for the agricultural sector and beyond
   World Bank, 2021, AGR FOR FISH VAL ADD
NR 64
TC 2
Z9 2
U1 0
U2 3
PU TAYLOR & FRANCIS AS
PI OSLO
PA KARL JOHANS GATE 5, NO-0154 OSLO, NORWAY
SN 2331-1886
J9 COGENT SOC SCI
JI Cogent Soc. Sci.
PD DEC 31
PY 2022
VL 8
IS 1
AR 2126452
DI 10.1080/23311886.2022.2126452
PG 22
WC Social Sciences, Interdisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Social Sciences - Other Topics
GA 4W7TQ
UT WOS:000860361100001
OA gold
DA 2025-01-10
ER

PT J
AU Abdel-Fattah, A
   Al Hiary, M
AF Abdel-Fattah, Ahmad
   Al Hiary, Masnat
TI A participatory multicriteria decision analysis of the adaptive
   capacity-building needs of Jordan's agribusiness actors discloses the
   indirect needs downstream the value chain as "post-requisites" to the
   direct upstream needs
SO FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
LA English
DT Article
DE participatory; multi-criteria decision analysis (MCDA); climate adaptive
   capacity needs; agribusiness; value chain actors; Jordan Valley
ID CLIMATE-CHANGE
AB Climate adaptive capacity-building initiatives and activities in developing countries, particularly those implemented by developmental agencies and international organizations, commonly focus on the upstream direct adaptive capacity-building needs of targeted vulnerable sectors. However, overlooking a holistic climate-adaptive capacity-building of a vulnerable sector down to the last link of its value chain renders inadequate contribution, jeopardizes the adaptation intervention, and prevents achieving a high level of buy-in of the chain actors for the results of the sought capacity-building programs. Thus, this study developed a hybrid system-wide and participatory (focus groups-based) multi-criteria decision analysis (MCDA) to conduct adaptive-capacity needs assessments for the actors of the agribusiness value chain of the developing country of Jordan. Our holistic approach enabled highlighting the sector's climate vulnerability along the value chain, conducting self-regulated adaptive training needs assessment (TNA) of the sector's actors and identifying and prioritizing their real adaptive capacity-building needs. This approach proved to be uniquely advantageous in comparison to the sector's commonly used questionnaire-based surveys that are limited-participatory, researcher-regulated, and subsystem-oriented approaches. The advantages of this hybrid hands-on and wide-ranging MCDA-TNA approach are evident from its revelation of unique results. The approach enabled actors of such a highly vulnerable sector to spontaneously identify and prioritize the indirect downstream climate adaptive capacity-building needs surprisingly over the direct needs. This is because the actors considered the indirect needs more important to their businesses and livelihoods than the direct needs, thus considering the indirect needs as "post-requisites" of the fate of the direct upstream needs. The hybrid approach also enabled the beneficiaries to formulate the intervention outcomes, unveil the factors ignored by the conventional researcher-controlled approaches, secure high buy-in of the self-attained results, and prioritize the actual adaptive capacity-building demands. This robust combination of qualitative research methods and tools could be straightforwardly applied to design and conduct efficient and cost-effective adaptive capacity-building programs, especially during time-restricted and resource-limited interventions. The results of such types of quick and cost-effective qualitative investigations of adaptive capacity-building needs could be considered a preliminary and a first step toward deeper and more extensive quantitative studies, if needed.
C1 [Abdel-Fattah, Ahmad] Minist Planning & Int Cooperat, Directorate Local Dev & Enhanced Prod, Amman, Jordan.
   [Al Hiary, Masnat] Natl Agr Res Ctr NARC, Directorate Socio econ Res, Al Baqa, Jordan.
RP Abdel-Fattah, A (corresponding author), Minist Planning & Int Cooperat, Directorate Local Dev & Enhanced Prod, Amman, Jordan.
EM ahmad.abdelfattah72@gmail.com
OI Abdel-Fattah, Ahmad/0000-0003-3909-5142
FU Adaptation Fund [JOR/NIE/Multi/2012/1]
FX This exercise was conducted as part of the activities of an Adaptation
   Fund-sponsored Program in Jordan (Grant No. JOR/NIE/Multi/2012/1),
   addressing the adaptation of the agricultural sector to the impacts of
   climate change, entitled Increasing the Resilience of Poor and
   Vulnerable Communities to Climate Change Impacts in Jordan by
   Implementing Innovative Projects in Water and Agriculture in Support of
   Adaptation to Climate Change (Adaptation Fund, 2022). At the time of
   conducting the exercise, AA-F was serving as the National Manager of the
   said program implemented by the Jordan Ministry of Planning and
   International Cooperation (MoPIC) and MA was serving as the coordinator
   of one of the nine subprojects of the program, particularly the
   subproject concerned with grubbiness adaptation, entitled Jordan Valley
   Water Sustainability and Agribusiness Competitiveness executed by NARC.
CR Abdel-Fattah A., 2013, POLICY ORIENTED NATL
   Abdel-Fattah A., 2017, CLIMATE CHANGE TECHN
   Abdel-Fattah A., 2016, CLIMATE CHANGE TECHN
   Adams A, 2008, RESEARCH METHODS FOR HUMAN-COMPUTER INTERACTION, P17
   Adaptation Fund, 2022, INCREASING RESILIENC
   Al-Bakri J, 2011, PHYS CHEM EARTH, V36, P125, DOI 10.1016/j.pce.2010.06.001
   [Anonymous], 2010, RURAL POVERTY REPORT
   [Anonymous], 2009, Agriculture at a Crossroads: Global Report
   [Anonymous], 2009, MULTICRITERIA ANAL M
   [Anonymous], 2021, Which trends offer opportunities or pose threats on the European outbound tourism market?
   [Anonymous], 1955, Survey Design and Analysis
   Arsenopoulos A., 2021, INT J MULTICRIT DECI, V8, P276, DOI [10.1504/IJMCDM.2021.119451, DOI 10.1504/IJMCDM.2021.119451]
   Beiske B., 2002, Research Methods: Uses and Limitations of Questionnaires, Interviews, and Case Studies
   Bell J., 1999, DOING YOUR RES PROJE, V3rd
   Boettcher M, 2016, REPRESENTATIVE IS QU
   Carey A., 2018, Assessing Adaptive Capacity of Pioneer Valley Farmers
   CBI, 2018, FRESH FRUIT VEGETABL
   Cinner JE, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-30991-4
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   D'Angelo D., 2012, SNAPSHOT BUSINESS EN
   de Janvry A., 2019, Achieving Coordination in Agricultural Value Chains: The Role of Lead Agents and Multi-stakeholder Platforms
   DOS, 2021, POPULATION ESTIMATES
   DOS, 2018, NUMBERS CHARACTERIST
   Dowling C., 2019, CLIMATE CHANGE FOOD
   Einola K, 2021, J MANAGE INQUIRY, V30, P102, DOI 10.1177/1056492620938139
   Fanack: Chronicle of the Middle East and North Africa, 2021, Economy of Jordan
   FAO, 2015, JORDAN WATER FOOD CH
   [Field CB. IPCC IPCC], 2014, CLIMATE CHANGE 2014, P1132
   Fielding Nigel., 2001, Researching Social Life, V2nd, P145
   Food and Agriculture Organization of the United Nations (FAO), 2016, CLIMATE CHANGE FOOD
   Freudenberger K.S., 2008, Rapid rural appraisal (RRA) and participatory rural appraisal (PRA): A manual for CRS field workers and partners
   Goedde L., 2015, Pursuing the global opportunity in food and agribusiness
   Gunderson M A., 2014, Encyclopedia of Agriculture and Food Systems, V1, P51, DOI DOI 10.1016/B978-0-444-52512-3.00117-0
   Heeb L, 2019, J PEST SCI, V92, P951, DOI 10.1007/s10340-019-01083-y
   Henfrey T., 2015, Permaculture and climate change adaptation: Inspiring ecological, social, economic and cultural responses for resilience and transformation
   Holmgren D., 2018, RetroSuburbia: the downshifter's guide to a resilient future
   Holmgren D., 2002, PERMACULTURE PRINCIP
   Horton P, 2017, FOOD SECUR, V9, P195, DOI 10.1007/s12571-017-0648-4
   Horton P, 2016, J CLEAN PROD, V120, P164, DOI 10.1016/j.jclepro.2015.08.092
   Iacuessa M., 2021, PERMACULTURE GARDEN
   Ickowitz A, 2019, GLOB FOOD SECUR-AGR, V20, P9, DOI 10.1016/j.gfs.2018.11.002
   Kalaitzandonakes M., 2022, CLIMATE CHANGE FOOD
   Kanaan T.H., 2002, The story of Economic Growth in Jordan: 1950-2000
   Kayed M., 2017, JORDAN TIMES
   Kinross B., 2017, A Literature Review of Training Needs Assessment (TRNA) Methodology, DOI [10.2900/6672, DOI 10.2900/6672]
   Kumar K, 2020, CHILDHOOD TRAUMAS: NARRATIVES AND REPRESENTATIONS, P1
   Kumar L., 2022, FUTURE FOODS
   Limantol AM, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2433-9
   Lockwood M, 2015, ECOL SOC, V20, DOI 10.5751/ES-07203-200137
   McLeod S. A., 2018, Questionnaire: definition, examples, design and types. Simply psychology
   MDGF, 2011, IDENTIFY SCREEN ADAP
   MoA, 2021, INSTRUCTIONS NOG1 20
   MoEnv, 2014, Jordans Third National Communication on Climate Change Submitted to The United Nations Framework Convention on Climate Change (UNFCCC), Funded by GEF and UNDP
   MoEnv, 2009, JORDANS 2 NATL COMMU
   Mollison B., 1997, Introduction to permaculture
   Mollison Bill., 1978, PERMACULTURE ONE PER
   Namrouqa H., 2017, UAE SAYS VEGETABLE B
   Ng D. W., 2009, Int, V12, P1, DOI [10.22004/ag.econ.92566, DOI 10.22004/AG.ECON.92566]
   O'Leary Z., 2004, ESSENTIAL GUIDE DOIN
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   PRI, 2022, GREENING DESERT PROJ
   Rajsekhar D, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1700581
   Rikken R., 2016, EXPORT VALUE CHAIN A
   Roesch-McNally G, 2020, RENEW AGR FOOD SYST, V35, P626, DOI 10.1017/S1742170519000267
   Roya News, 2017, UAE LIFTS BAN JORDAN
   Singh S, 2021, ASIAN J PSYCHIATR, V65, DOI 10.1016/j.ajp.2021.102850
   Stathers T, 2013, FOOD SECUR, V5, P361, DOI 10.1007/s12571-013-0262-z
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tong A, 2007, INT J QUAL HEALTH C, V19, P349, DOI 10.1093/intqhc/mzm042
   Trarup S. L. M., 2015, EVALUATING PRIORITIZ
   Trudge C., 2016, 6 STEPS BACK LAND
   Vicsek L, 2010, QUAL REP, V15, P122
   Yuan Z, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19116572
   Zaytuna Farm, 2022, US
NR 74
TC 1
Z9 1
U1 1
U2 5
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2571-581X
J9 FRONT SUSTAIN FOOD S
JI Front. Sustain. Food Syst.
PD FEB 7
PY 2023
VL 6
AR 1026432
DI 10.3389/fsufs.2022.1026432
PG 21
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA 9C4IB
UT WOS:000935381900001
OA gold
DA 2025-01-10
ER

PT J
AU Ingram, JSI
   Gregory, PJ
   Izac, AM
AF Ingram, J. S. I.
   Gregory, P. J.
   Izac, A. -M.
TI The role of agronomic research in climate change and food security
   policy
SO AGRICULTURE ECOSYSTEMS & ENVIRONMENT
LA English
DT Article
DE climate change; adaptation; environmental feedbacks; food security
ID GLOBAL ENVIRONMENTAL-CHANGE; ELEVATED CO2; SYSTEMS
AB Societal concern is growing about the consequences of climate change for food systems and, in a number of regions. for food security. There is also concern that meeting the rising demand for food is leading to environmental degradation thereby exacerbating factors in part responsible for climate change. and further undermining the food systems upon which food security is based, A major emphasis of climate change/food security research over recent years has addressed the agronomic aspects of climate change, and particularly crop yield. This has provided an excellent foundation for assessments of how climate change may affect crop productivity, but the connectivity between these results and the broader issues of food security at large are relatively poorly explored; too often discussions of food security policy appear to be based on a relatively narrow agronomic perspective.
   To overcome the limitation of current agronomic research outputs there are several scientific challenges where further agronomic effort is necessary, and where agronomic research results can effectively contribute to the broader issues underlying food security. First is the need to better understand how climate change will affect cropping systems including both direct effects on the crops themselves and indirect effects as a result of changed pest and weed dynamics and altered soil and water conditions. Second is the need to assess technical and policy options for either reducing the deleterious impacts or enhancing the benefits of climate change on cropping systems while minimising further environmental degradation. Third is the need to understand how best to address the information needs of policy makers and report and communicate agronomic research results in a manner that will assist the development of food systems adapted to climate change.
   There are, however, two important considerations regarding these agronomic research contributions to the food security/climate change debate. The first concerns scale. Agronomic research has traditionally been conducted at plot scale over a growing season or perhaps a few years, but many of the issues related to food security operate at larger spatial and temporal scales. Over the last decade, agronomists have begun to establish trials at landscape scale, but there are a number of methodological challenges to be overcome at such scales. The second concerns the position of crop production (which is a primary focus of agronomic research) in the broader context of food security. Production is clearly important, but food distribution and exchange also determine food availability while access to food and food utilisation are other important components of food security.
   Therefore, while agronomic research alone cannot address all food security/climate change issues (and hence the balance of investment in research and development for crop production vis vis other aspects of food security needs to be assessed), it will nevertheless continue to have an important role to play: it both improves understanding of the impacts of climate change on crop production and helps to develop adaptation options; and also - and crucially - it improves understanding of the consequences of different adaptation options on further climate forcing. This role can further be strengthened if agronomists work alongside other scientists to develop adaptation options that are not only effective in terms of crop production, but are also environmentally and economically robust, at landscape and regional scales. Furthermore, such integrated approaches to adaptation research are much more likely to address the information need of policy makers. The potential for stronger linkages between the results of agronomic research in the context of climate change and the policy environment will thus be enhanced. (c) 2008 Elsevier B.V. All rights reserved.
C1 [Ingram, J. S. I.] Univ Oxford, Ctr Environm, Environm Change Inst, GECAFS,Int Project Off, Oxford, England.
   [Gregory, P. J.] Scottish Crop Res Inst, Dundee DD2 5DA, Scotland.
   [Izac, A. -M.] IFAD, CGIAR Ctr, Rome, Italy.
C3 University of Oxford; James Hutton Institute; CGIAR
RP Ingram, JSI (corresponding author), Univ Oxford, Ctr Environm, Environm Change Inst, GECAFS,Int Project Off, S Pk Rd, Oxford, England.
EM john.ingram@eci.ox.ac.uk
CR Aggarwal PK, 2004, ENVIRON SCI POLICY, V7, P487, DOI 10.1016/j.envsci.2004.07.006
   ALEXANDRATOS N, 1995, WORLD AGR TOWARDS 20
   [Anonymous], CLIMATE CHANGE 2001
   Döös BR, 2002, AMBIO, V31, P417, DOI 10.1639/0044-7447(2002)031[0417:TPOPGF]2.0.CO;2
   Dyson T., 1996, POPULATION FOOD
   Ericksen PJ, 2008, GLOBAL ENVIRON CHANG, V18, P234, DOI 10.1016/j.gloenvcha.2007.09.002
   Evans L. T., 1998, FEEDING TEN BILLION
   Ewert F, 2005, AGR ECOSYST ENVIRON, V107, P101, DOI 10.1016/j.agee.2004.12.003
   FAO, 2002, World Agriculture: Towards 2015/2030 Summary Report, DOI 10.1016/S0264-8377(03)00047-4
   Fischer Gunther., 2001, Global agro-ecological assessment for agriculture in the 21st century
   Fuhrer J, 2003, AGR ECOSYST ENVIRON, V97, P1, DOI 10.1016/S0167-8809(03)00125-7
   Grace P. R., 2003, Improving the productivity and sustainability of rice-wheat systems: issues and impacts. Proceedings of an international symposium, held at the 2001 Annual Meetings of the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Charlotte, NC, USA, 22 October 2001, P27
   Greenland D. J., 1998, P39
   Gregory PJ, 2005, PHILOS T R SOC B, V360, P2139, DOI 10.1098/rstb.2005.1745
   Gregory PJ, 2002, AGR ECOSYST ENVIRON, V88, P279, DOI 10.1016/S0167-8809(01)00263-8
   GREGORY PJ, 1999, IGBP BOOK SERIES, P229
   *HADL CTR, 2006, EFF CLIM CHANG DEV C
   Hulme M, 2001, CLIM RES, V17, P145, DOI 10.3354/cr017145
   Jones PG, 2003, GLOBAL ENVIRON CHANG, V13, P51, DOI 10.1016/S0959-3780(02)00090-0
   Kettlewell PS, 1999, J CEREAL SCI, V29, P205, DOI 10.1006/jcrs.1999.0258
   KURUKULASURIYA PR, 2006, WILL AFRICA SURVICE
   MANO R, UNPUB ENV SCI POLICY
   Parry ML, 2004, GLOBAL ENVIRON CHANG, V14, P53, DOI 10.1016/j.gloenvcha.2003.10.008
   PRETTY J., 2005, Regenerating Agriculture: Policies and Practice for Sustainability and Self-reliance
   Rosegrant MW, 2003, SCIENCE, V302, P1917, DOI 10.1126/science.1092958
   Sanchez P. A., 1997, Replenishing soil fertility in Africa. Proceedings of an international symposium, Indianapolis, USA, 6 November 1996., P1
   Scholes R.J., 2004, Ecosystem services in southern Africa: a regional assessment
   Slingo JM, 2005, PHILOS T R SOC B, V360, P1983, DOI 10.1098/rstb.2005.1755
   Steffen W., 2004, Global change and the earth system: a planet under pressure, DOI [10.1007/b137870, DOI 10.1007/B137870]
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Stige LC, 2006, P NATL ACAD SCI USA, V103, P3049, DOI 10.1073/pnas.0600057103
   SUTHERST R, 2007, TERRESTRIAL ECOSYSTE, P336
   Tilman D, 2002, NATURE, V418, P671, DOI 10.1038/nature01014
   Tubiello FN, 2000, EUR J AGRON, V13, P179, DOI 10.1016/S1161-0301(00)00073-3
   TYSON P., 2002, Global-regional linkages in the earth system
   *UN DESA, 2004, WORLD POP PROSP 2004, pCH1
   *UNDP, 2006, 2006 HUM DEV REP BEY
   Vitousek PM, 1997, SCIENCE, V277, P494, DOI 10.1126/science.277.5325.494
   World Food Summit, 1996, Report of the World Food Summit
NR 39
TC 85
Z9 88
U1 0
U2 117
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0167-8809
EI 1873-2305
J9 AGR ECOSYST ENVIRON
JI Agric. Ecosyst. Environ.
PD JUN
PY 2008
VL 126
IS 1-2
BP 4
EP 12
DI 10.1016/j.agee.2008.01.009
PG 9
WC Agriculture, Multidisciplinary; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Environmental Sciences & Ecology
GA 298NP
UT WOS:000255694700002
DA 2025-01-10
ER

PT J
AU Zhai, C
   Wu, W
AF Zhai, Chong
   Wu, Wei
TI Seasonal performance and climatic adaptability of a solar-powered
   microchannel membrane-based absorption refrigeration system
SO APPLIED THERMAL ENGINEERING
LA English
DT Article
DE Solar-powered; Absorption refrigeration; Membrane-based heat exchanger;
   Geometries optimization; Seasonal performance; Climatic adaptability
ID LITHIUM BROMIDE; OPTIMIZATION; ENERGY; DENSITY
AB Microchannel membrane-based absorption refrigeration system (MMARS) has vast potential to satisfy the increasing cooling demand by utilizing renewable and waste thermal energy. To maximize its potential for future large-scale applications, the geometries of the MMARS were optimized for the first time to obtain the lowest system cost under various weather conditions and cooling demands in different climate zones of China. After optimization, Kunming (mild region) has the highest levelized cooling demand cost of 0.2710 $/kWh because of its high initial cost, while Beijing (cold region) has the lowest cost of 0.1508 $/kWh due to its rich solar energy to reduce the operating cost and sufficient cooling demand to levelize the initial cost. It is worth noting that if only natural gas is counted in energy consumption, Kunming, with rich solar energy, achieves the highest seasonal COP of 2.654, but Hong Kong (hot summer and warm winter region) with insufficient solar energy only gets 1.318 because of the low proportion (48.84%) of solar energy in its heat sources. This paper provides a seasonal performance-based geometries optimization of the MMARS and studies its climatic adaptability in different climate zones, facilitating the reasonable design and application of efficient and compact absorption refrigeration systems.
C1 [Wu, Wei] City Univ Hong Kong, Sch Energy & Environm, Hong Kong, Peoples R China.
   City Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China.
C3 City University of Hong Kong; Shenzhen Research Institute, City
   University of Hong Kong; City University of Hong Kong
RP Wu, W (corresponding author), City Univ Hong Kong, Sch Energy & Environm, Hong Kong, Peoples R China.
EM weiwu53@cityu.edu.hk
RI Chong, ZHAI/LBH-3193-2024; Wu, Wei/AAB-1458-2019
OI Wu, Wei/0000-0002-9657-6682; Zhai, Chong/0000-0002-9791-7848
FU CityU Teaching Development Grant [6000762]; Guangdong Basic and Applied
   Basic Research Foundation [2022A1515011183]; Research Grants Council of
   Hong Kong [CityU 11212620, CityU 11215621]; Central Government Fund for
   Guiding Local Scientific and Technological Development under Shenzhen
   Virtual University Park; Shenzhen Science and Technology Innovation
   Committee [2021Szvup125]
FX The authors gratefully acknowledge the supports from the Central
   Government Fund for Guiding Local Scientific and Technological
   Development under Shenzhen Virtual University Park, Shenzhen Science and
   Technology Innovation Committee (Project number: 2021Szvup125), the
   CityU Teaching Development Grant (Project number: 6000762), the
   Guangdong Basic and Applied Basic Research Foundation (2022A1515011183),
   and the Research Grants Council of Hong Kong (Project number: CityU
   11212620, CityU 11215621).
CR Ahmadi MH, 2015, ENERG CONVERS MANAGE, V90, P175, DOI 10.1016/j.enconman.2014.11.021
   Ali AHH, 2009, INT J REFRIG, V32, P1886, DOI 10.1016/j.ijrefrig.2009.07.009
   [Anonymous], 2005, ASHRAE HDB FUND
   [Anonymous], 1993, Multicomponent Mass Transfer
   Bertsch SS, 2009, INT J HEAT MASS TRAN, V52, P2110, DOI 10.1016/j.ijheatmasstransfer.2008.10.022
   Borri E, 2021, APPL THERM ENG, V189, DOI 10.1016/j.applthermaleng.2021.116666
   Cobetter,, 2022, POL PTFE MEM INF
   Dezhou Weiren Water Supply Equipment Co. Ltd, 2022, STAINL STEEL MOD WAT
   DIGUILIO RM, 1990, ASHRAE TRAN, V96, P702
   E.R. Association,, 1967, STEAM TABL
   Esfahani IJ, 2014, ENERGY, V75, P312, DOI 10.1016/j.energy.2014.07.081
   Esfahani S, 2015, J NAT GAS SCI ENG, V22, P348, DOI 10.1016/j.jngse.2014.12.003
   Fani M, 2017, ENERG BUILDINGS, V136, P100, DOI 10.1016/j.enbuild.2016.11.052
   Farahat S, 2009, RENEW ENERG, V34, P1169, DOI 10.1016/j.renene.2008.06.014
   Fixr,, 2021, NAT BOIL COSTS
   Ganapathy H, 2015, CHEM ENG J, V266, P258, DOI 10.1016/j.cej.2014.12.028
   Harr L., 1984, NBSNRC STEAM TABLE
   Henchoz S, 2015, ENERGY, V85, P221, DOI 10.1016/j.energy.2015.03.079
   Huang YW, 2008, INT J THERM SCI, V47, P479, DOI 10.1016/j.ijthermalsci.2007.03.013
   IEA, 2022, SPAC COLL TRACK REP
   Isfahani RN, 2013, INT J REFRIG, V36, P2297, DOI 10.1016/j.ijrefrig.2013.07.019
   Isfahani RN, 2013, INT J HEAT MASS TRAN, V63, P82, DOI 10.1016/j.ijheatmasstransfer.2013.03.053
   IYOKI S, 1989, INT J REFRIG, V12, P323, DOI 10.1016/0140-7007(89)90063-7
   Jacobson MZ, 2018, SOL ENERGY, V169, P55, DOI 10.1016/j.solener.2018.04.030
   Jin Q, 2019, APPL THERM ENG, V160, DOI 10.1016/j.applthermaleng.2019.113849
   Khanmohammadi S, 2020, J CLEAN PROD, V256, DOI 10.1016/j.jclepro.2020.120600
   Kidnay A.J., 2006, Fundamentals of Natural Gas Processing. CRC Press: Taylor, DOI DOI 10.1201/9781420014044
   Klein S., 2020, F CHART SOFTWARE
   LEE RJ, 1990, ASHRAE TRAN, V96, P709
   Liu B, 2020, INT J HYDROGEN ENERG, V45, P1385, DOI 10.1016/j.ijhydene.2019.11.056
   LOCKHART RW, 1949, CHEM ENG PROG, V45, P39
   Shah R. K., 2014, LAMINAR FLOW FORCED
   Shirazi A, 2017, ENERG CONVERS MANAGE, V132, P281, DOI 10.1016/j.enconman.2016.11.039
   Stankus SV, 2007, HIGH TEMP+, V45, P429, DOI 10.1134/S0018151X07030212
   Venegas M, 2020, APPL THERM ENG, V167, DOI 10.1016/j.applthermaleng.2019.114781
   Venegas M, 2016, INT J REFRIG, V71, P108, DOI 10.1016/j.ijrefrig.2016.08.013
   Wang J., 2019, ENERG CONVERS MANAGE, V199
   Wang LK, 1999, HEAT TRANSFER ENG, V20, P71
   Wang R, 2022, BUILD SIMUL-CHINA, V15, P1209, DOI 10.1007/s12273-021-0818-3
   Wang TT, 2020, ENERGY, V196, DOI 10.1016/j.energy.2020.117105
   Wang Y., 2021, ENERG CONVERS MANAGE, V233
   World Bank Group,, 2022, SOL RES MAP DIR NORM
   Wu W, 2020, APPL THERM ENG, V172, DOI 10.1016/j.applthermaleng.2020.115145
   Wu W, 2015, ENERG CONVERS MANAGE, V98, P290, DOI 10.1016/j.enconman.2015.03.041
   Wu Z., 2020, ENERG CONVERS MANAGE, V223
   Yan D, 2008, BUILD SIMUL-CHINA, V1, P95, DOI 10.1007/s12273-008-8118-8
   Yang CR, 2021, INT J REFRIG, V121, P33, DOI 10.1016/j.ijrefrig.2020.09.020
   Yang L, 2008, APPL ENERG, V85, P800, DOI 10.1016/j.apenergy.2007.11.002
   Zambolin E, 2012, RENEW ENERG, V43, P37, DOI 10.1016/j.renene.2011.11.011
   Zang H., 2016, SUSTAINABILITY-BASEL, V8
   Zhai C., 2022, ENERGY, V239
   Zhai C, 2021, RENEW ENERG, V177, P663, DOI 10.1016/j.renene.2021.05.156
   Zhai C, 2021, ENERGY, V229, DOI 10.1016/j.energy.2021.120669
   Zhai C, 2021, INT J REFRIG, V127, P203, DOI 10.1016/j.ijrefrig.2021.01.029
   Zhai C, 2021, ENERG CONVERS MANAGE, V239, DOI 10.1016/j.enconman.2021.114213
   Zhai C, 2021, APPL THERM ENG, V186, DOI 10.1016/j.applthermaleng.2021.116554
   Zhai XQ, 2009, RENEW SUST ENERG REV, V13, P1523, DOI 10.1016/j.rser.2008.09.022
NR 57
TC 5
Z9 5
U1 3
U2 12
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 1359-4311
EI 1873-5606
J9 APPL THERM ENG
JI Appl. Therm. Eng.
PD JAN 25
PY 2023
VL 219
AR 119627
DI 10.1016/j.applthermaleng.2022.119627
EA NOV 2022
PN C
PG 29
WC Thermodynamics; Energy & Fuels; Engineering, Mechanical; Mechanics
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Energy & Fuels; Engineering; Mechanics
GA 9A2QA
UT WOS:000933906500004
DA 2025-01-10
ER

PT J
AU Elliott, JR
   Loughran, K
   Brown, PL
AF Elliott, James R.
   Loughran, Kevin
   Brown, Phylicia Lee
TI Divergent Residential Pathways from Flood-Prone Areas: How Neighborhood
   Inequalities Are Shaping Urban Climate Adaptation
SO SOCIAL PROBLEMS
LA English
DT Article
DE urban; environment; policy; inequality; flooding
ID BUYOUTS; STATE; INEQUITIES; RELOCATION; ATTACHMENT; ECOLOGY; HOUSTON;
   RISK
AB Flood risks are rising across the United States, putting the economic and social values of growing numbers of homes at risk. In response, the federal government is funding the purchase and demolition of housing in areas of greatest jeopardy, tacitly promoting residential resettlement as a strategy of climate adaptation, especially in cities. Despite these developments little is known about where people move when they engage in such resettlement or how answers to that question vary by the racial and economic status of their flood-prone neighborhoods. The present study begins to fill that gap. We introduce a new typology for classifying environmental resettlement along two socio-spatial dimensions of community attachment: (a) distance moved from one's flood-prone home; and (b) average distance resettled from similarly relocated neighbors. Next, we analyze data from 1,572 homeowners who accepted government-funded buyouts across 39 neighborhood areas in Harris County, Texas - Houston's urban core. Results indicate that homeowners from more privileged neighborhoods resettle closer to their flood-prone homes and to one another, thus helping to preserve the social and economic value of their homes; homeowners from less privileged areas end up farther away from both. Implications for understanding social inequities in government-funded urban climate adaptation are discussed.
C1 [Elliott, James R.; Brown, Phylicia Lee] Rice Univ, Houston, TX USA.
   [Loughran, Kevin] Temple Univ, Philadelphia, PA 19122 USA.
C3 Rice University; Pennsylvania Commonwealth System of Higher Education
   (PCSHE); Temple University
RP Elliott, JR (corresponding author), Rice Univ, Dept Sociol, Houston, TX 77005 USA.
EM jre5@rice.edu
FU Rice University's BRIDGE (Building Research on Inequality and Diversity
   to Grow Equity) initiative
FX The authors thank Allison Yelvington and Aubrey Calaway for their
   valuable research assistance and the members of Rice University's
   Spatial Processes and City Environments Collaborative (SPACE Co.) for
   feedback on earlier drafts. We are also grateful for support from Rice
   University's BRIDGE (Building Research on Inequality and Diversity to
   Grow Equity) initiative, directed by Dr. Jenifer Bratter, as well as
   statistical advice from Dr. Jing Li. Please direct correspondence to the
   first author at the Department of Sociology, Rice University, Houston,
   TX 77005-1827; email: jre5@rice.edu.
CR Arcaya M, 2020, ANNU REV SOCIOL, V46, P671, DOI 10.1146/annurev-soc-121919-054827
   Baker CK, 2018, RISK HAZARDS CRISIS, V9, P455, DOI 10.1002/rhc3.12144
   Berke P, 2012, NAT HAZARDS REV, V13, P139, DOI 10.1061/(ASCE)NH.1527-6996.0000063
   Binder SB, 2019, ENVIRON HAZARDS-UK, V18, P127, DOI 10.1080/17477891.2018.1511404
   Blind I, 2018, CESIFO ECON STUD, V64, P292, DOI 10.1093/cesifo/ify014
   Boehm, 2013, CEP DISCUSSION PAPER
   Braamskamp A., 2018, ENV MANAGE SUSTAIN D, V7, P108, DOI [10.5296/emsd.v7i2.12851, DOI 10.5296/EMSD.V7I2.12851]
   Bronen R., 2011, NYU Review of Law and Social Change, V35, P357
   Chakraborty J, 2014, NAT HAZARDS REV, V15, DOI 10.1061/(ASCE)NH.1527-6996.0000140
   Dahl MS, 2010, SOC FORCES, V89, P633, DOI 10.1353/sof.2010.0078
   Dahl MS, 2010, J URBAN ECON, V67, P33, DOI 10.1016/j.jue.2009.09.009
   Davenport C., 2016, New York Times
   Davies PS, 2001, J REGIONAL SCI, V41, P337, DOI 10.1111/0022-4146.00220
   de Vries D.H., 2012, International Journal of Mass Emergencies Disasters, V30, P1, DOI [DOI 10.1017/CBO9781107415324.004, 10.1017/CBO9781107415324.004]
   Dermot, 2018, ARCTICTODAY 0429
   Devine-Wright P, 2013, GLOBAL ENVIRON CHANG, V23, P61, DOI 10.1016/j.gloenvcha.2012.08.003
   Devon, 2020, CLIMATE ADAPTATION K
   Elliott JR, 2020, SOCIUS, V6, DOI 10.1177/2378023120905439
   Elliott R, 2019, BRIT J SOCIOL, V70, P1067, DOI 10.1111/1468-4446.12381
   Elliott R, 2017, POLIT SOC, V45, P415, DOI 10.1177/0032329217714785
   Erdman Jon., 2017, WEATHER UNDERGROUND
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Faber JW, 2015, HUM ECOL, V43, P363, DOI 10.1007/s10745-015-9757-x
   FEMA, 2019, Hazard mitigation grant program
   FEMA (Federal Emergency Management Agency), BUYOUTS WIN WIN HARR
   GAO (United States Government Accountability Office), 2013, FLOOD INS MOR INF NE
   GAO (United States Government Accountability Office), 2019, HIGH RISK SER SUBST
   Hauer ME, 2017, NAT CLIM CHANGE, V7, P321, DOI [10.1038/nclimate3271, 10.1038/NCLIMATE3271]
   Henwood K, 2008, HEALTH RISK SOC, V10, P421, DOI 10.1080/13698570802381451
   Hirsch Arnold R., 1983, Making the Second Ghetto: Race and Housing in Chicago 1940-1960
   Hofstaeder Emily., 2019, AM ER CRIS SHISHM TA
   Huang FL, 2016, J EXP EDUC, V84, P175, DOI 10.1080/00220973.2014.952397
   KASARDA JD, 1974, AM SOCIOL REV, V39, P328, DOI 10.2307/2094293
   Kate, 2019, MOTHERJONES 0902
   Keenan JM, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabb32
   Kinder Institute for Urban Research, 2018, CAS STUD FLOODPL BUY
   Kinder Institute for Urban Research, KIND COMM TAB AR
   King RawleO., 2013, The National Flood Insurance Program: Status and Remaining Issues for Congress
   Klinenberg E, 2020, ANNU REV SOCIOL, V46, P649, DOI 10.1146/annurev-soc-121919-054750
   Knobloch DM, 2005, J CONTEMP WAT RES ED, V130, P41, DOI 10.1111/j.1936-704X.2005.mp130001008.x
   Koslov L, 2016, PUBLIC CULTURE, V28, P359, DOI 10.1215/08992363-3427487
   Kousky C., 2018, Risk Management and Insurance Review, V21, P11, DOI DOI 10.1111/RMIR.12090
   Lawrence J, 2020, CURR CLIM CHANGE REP, V6, P66, DOI 10.1007/s40641-020-00161-z
   Loughran K, 2019, SOC CURR, V6, P121, DOI 10.1177/2329496518797851
   Loughran K, 2019, POPUL ENVIRON, V41, P52, DOI 10.1007/s11111-019-00324-7
   Lynn KA, 2017, J POLIT ECOL, V24, P951, DOI 10.2458/v24i1.20977
   Mach KJ, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax8995
   Maldonado JK, 2013, CLIMATIC CHANGE, V120, P601, DOI 10.1007/s10584-013-0746-z
   Marino E, 2018, GLOBAL ENVIRON CHANG, V49, P10, DOI 10.1016/j.gloenvcha.2018.01.002
   Marlay MatthewC., 2010, SEASONALITY MOVES DU
   NAC (National Advisory Council), 2020, NAT ADV COUNC REP FE
   Natl Acad Sci Engn Med, 2019, FRAMING THE CHALLENGE OF URBAN FLOODING IN THE UNITED STATES, P1, DOI 10.17226/25381
   Robert Freudenberg, 2016, BUY IN BUYOUTS CASE
   Rose, 2020, WASH POST
   Rush ElizabethA., 2018, Rising: Dispatches from the New American Shore, VFirst
   Sampson Robert J., 2012, Great American City: Chicago and the Enduring Neighborhood Effect
   Sharkey P., 2013, STUCK PLACE URBAN NE, DOI DOI 10.7208/CHICAGO/9780226924267.001.0001
   Sharkey P, 2014, ANNU REV SOCIOL, V40, P559, DOI 10.1146/annurev-soc-071913-043350
   Shelton Kyle., 2017, POWER MOVES TRANSPOR
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   Smiley KT, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/aba0fe
   SPEARE A, 1982, SOC FORCES, V61, P551, DOI 10.2307/2578241
   Thomas W. I., 1938, CHILD AM
   Tristan Baurick, 2017, NOLA 1219
   United States Department of Transportation Bureau of Transportation Statistics, 2020, NAT HOUS TRAV SURV D
NR 65
TC 12
Z9 15
U1 4
U2 13
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0037-7791
EI 1533-8533
J9 SOC PROBL
JI Soc. Probl.
PD OCT 14
PY 2023
VL 70
IS 4
BP 869
EP 892
DI 10.1093/socpro/spab059
EA SEP 2021
PG 24
WC Sociology
WE Social Science Citation Index (SSCI)
SC Sociology
GA U2QW1
UT WOS:000764774900001
DA 2025-01-10
ER

PT J
AU Tarumi, E
   Tsuiki, M
   Mori, A
AF Tarumi, Erina
   Tsuiki, Mikinori
   Mori, Akinori
TI Cool-season grass productivity estimation model evaluating the effects
   of global warming and climate adaptation strategies
SO GRASSLAND SCIENCE
LA English
DT Article
DE Akaike&apos; s information criterion; climate adaptation strategies;
   cool&#8208; season grass; global warming; model
ID TIMOTHY GROWTH; SIMULATION
AB Various climate adaptation strategies are being studied for the agricultural sector to address the effects of climate change. Global warming is predicted to have a significant influence on cool-season grass production in Japan in terms of decreasing grass dry matter yield. The authors have studied adaptation strategies to maintain grass dry matter yield using orchardgrass, a cool-season grass. However, it may be difficult to adapt to future climate conditions using management methods such as fertilizer application or changing grassland renovation cycles using only one grass species. In this study, a model was constructed formulating the relationship between temperature and yields of the main cool-season grasses in Japan, and the effects of global warming on grass productivity were predicted. Two models were constructed, and the optimal one was selected using Akaike's information criterion. The selected model was then validated using correlations with observation data. We also compared areas suitable for cultivation at current and higher temperatures, which were produced as maps using the selected model. Bahiagrass, which is a warm-season grass, was suitable for cultivation in coastal areas in southern Kanto under increased temperature condition. It may be useful, therefore, to convert to heat-resistant grasses, such as orchardgrass or tall fescue, as temperatures rise.
C1 [Tarumi, Erina; Tsuiki, Mikinori] Iwate Univ, Fac Agr, Morioka, Iwate 0208550, Japan.
   [Mori, Akinori] NARO, Inst Livestock & Grassland Sci, Nasushiobara, Japan.
C3 Iwate University; National Agriculture & Food Research Organization -
   Japan
RP Tarumi, E (corresponding author), Iwate Univ, Fac Agr, Morioka, Iwate 0208550, Japan.
EM etarumi@iwate-u.ac.jp
OI Erina, Tarumi/0000-0001-5223-4835
FU Ministry of Agriculture, Forestry and Fisheries of Japan
FX This work was financially supported by the Ministry of Agriculture,
   Forestry and Fisheries of Japan through the "Development of technologies
   for mitigation and adaptation to climate change in Agriculture, Forestry
   and Fisheries" research project.
CR AKAIKE H, 1974, IEEE T AUTOMAT CONTR, VAC19, P716, DOI 10.1109/TAC.1974.1100705
   Brereton A.J., 1996, Agrometeorology of Grass and Grasslands for Middle Latitudes
   Chaplin-Kramer R, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0057723
   Goto S., 2007, FEATURES GEOGRAPHIC
   GUSTAVSSON AM, 1995, AGR SYST, V47, P73, DOI 10.1016/0308-521X(94)P3276-Z
   Höglind M, 2001, NEW PHYTOL, V151, P355, DOI 10.1046/j.0028-646x.2001.00195.x
   Hokkaido Research Organization, 2005, ORCH NEW BREED CAND
   Hurtado-Uria C, 2013, J AGR SCI-CAMBRIDGE, V151, P91, DOI 10.1017/S0021859612000317
   Ihaka R., 1996, Journal of computational and graphical statistics, V5, P299, DOI [10.1080/10618600.1996.10474713, 10.2307/1390807, DOI 10.1080/10618600.1996.10474713]
   Japan Grassland Agriculture and Forage Seed Association (GAFSA), 2014, GRASS SEED
   Japan Grassland Agriculture and Forage Seed Association (GASFA), 2011, FARM TECHN MAN PUBL
   Japan Meteorological Agency (JMA), 2019, ANN AV TEMP JAP
   Jégo G, 2013, FIELD CROP RES, V151, P65, DOI 10.1016/j.fcr.2013.07.003
   Jing Q, 2014, CAN J PLANT SCI, V94, P213, DOI [10.4141/CJPS2013-279, 10.4141/cjps2013-279]
   Jing Q, 2012, ECOL MODEL, V232, P64, DOI 10.1016/j.ecolmodel.2012.02.016
   JOHNSON IR, 1983, PLANT CELL ENVIRON, V6, P721, DOI 10.1111/1365-3040.ep11588103_6_9
   Jouven M, 2006, GRASS FORAGE SCI, V61, P112, DOI 10.1111/j.1365-2494.2006.00515.x
   Kondo K., 1972, TOHOKU AGR RES, V13, P167
   Magalhaes A. L. B., 1996, Arquivo Brasileiro de Medicina Veterinaria e Zootecnia, V48, P85
   Masuyama G., 1962, FIND EXPT FORMULA, P64
   Ministry of Agriculture Forestry and Fisheries (MAFF), 2019, AD STRAT GLOB WARM
   Ministry of Foreign Affairs of Japan (MOFA), 2019, PAR AGR ROAD HIST AG
   Ministry of Land Infrastructure Transport and Tourism (MLIT), 2019, NAT LAND INF NORM VA
   Ministry of the Environment (MOE), 2014, OV IPCC 5 ASS REP
   Ministry of the Environment (MOE), 2015, EV REP CLIM CHANG IM
   Mori K., 2012, Japanese Journal of Grassland Science, V58, P83
   NARO (National Agriculture and Food Research Organization), 2010, STAND TABL FEED COMP
   National Institute for Environmental Studies (NIES), 2020, THINK GLOB WARM
   Okubo T., 1990, GRASSL SCI, P37
   Riedo M, 1998, ECOL MODEL, V105, P141, DOI 10.1016/S0304-3800(97)00110-5
   Sasaki Hiroyuki, 2004, Grassland Science, V49, P606
   Sasaki Hiroyuki, 1998, Grassland Science, V44, P138
   Sato T., 2012, LIVESTOCK TECHNOLOGY, V685, P38
   Schapendonk AHCM, 1998, EUR J AGRON, V9, P87, DOI 10.1016/S1161-0301(98)00027-6
   Snow Brand Seed Co. Ltd, 2019, CHAR VAR ORCH
   Sugiura T, 2009, Global environmental research, V14, P207
   Takeuchi H., 1983, J SOC INSTRUMENT CON, V22, P445, DOI [10.11499/sicejl1962.22.445, DOI 10.11499/SICEJL1962.22.445]
   Tarumi E., 2018, J JPN AGR SYS SOC, V34, P7
NR 38
TC 4
Z9 4
U1 0
U2 12
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1744-6961
EI 1744-697X
J9 GRASSL SCI
JI Grassl. Sci.
PD JUL
PY 2021
VL 67
IS 3
BP 234
EP 240
DI 10.1111/grs.12310
EA NOV 2020
PG 7
WC Agriculture, Multidisciplinary; Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA TS7EA
UT WOS:000589228300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Kafy, AA
   Altuwaijri, HA
AF Kafy, Abdulla Al
   Altuwaijri, Hamad Ahmed
TI Eco-climatological modeling approach for exploring spatiotemporal
   dynamics of ecosystem service values in response to land use and land
   cover changes in Riyadh, Saudi Arabia
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
ID NEURAL-NETWORK; CLASSIFICATION; VALUATION
AB Rapid urbanization and land use/land cover (LULC) changes have become global phenomena, significantly impacting ecosystems and climate, which are key concerns in eco-climatology. Focusing on Riyadh, the rapidly growing capital of Saudi Arabia, this study investigated the spatiotemporal dynamics of ecosystem service values (ESVs) in response to LULC changes using an eco-climatological modeling approach. Support vector machine algorithms were employed on Google Earth Engine to classify Landsat imagery and map LULC in Riyadh for 1993, 2003, 2013, and 2023. ESVs were quantified using global coefficients to assess the impact of LULC changes on the eco-climatological system. Results revealed substantial LULC changes during 1993-2023, with built-up areas expanded by 330.79% (777.76 km(2)), vegetation by 114.30% (32.14 km(2)), and waterbody areas by 888.89% (7.20 km(2)). Conversely, barren soil and cropland areas declined by 9.41% (727.90 km(2)) and 84.40% (89.14 km(2)), respectively. These LULC changes led to significant alterations in ESVs, with barren soil and cropland losses resulting in ESV reductions of $591.56 million and $555.91 million, respectively. However, increased vegetated areas contributed to $750.40 million ESV rise. Spatially, western Riyadh experienced the most pronounced ESV declines due to rapid urbanization. Overall, total ESV decreased by $206.37 million over the 30-year, with supporting and cultural service values declining by $174.04 million and $39.91 million, respectively. Provisioning and regulating services increased by $3.58 million and $4.02 million. The eco-climatological modeling approach effectively captured the complex interactions between LULC dynamics, ecosystems, and ESVs in this arid environment, highlighting the need for sustainable land management strategies that balance urban growth, ecosystem preservation, and climate change adaptation and mitigation. This study contributes to eco-climatology by demonstrating advanced modeling techniques for assessing spatiotemporal ESV dynamics in response to LULC changes, informing future research and policy in rapidly urbanizing regions.
C1 [Kafy, Abdulla Al] Univ Texas Austin, Dept Geog & Environm, 1 Univ Stn A3100, Austin, TX 78712 USA.
   [Altuwaijri, Hamad Ahmed] King Saud Univ, Coll Humanities & Social Sci, Dept Geog, Riyadh 11451, Saudi Arabia.
C3 University of Texas System; University of Texas Austin; King Saud
   University
RP Kafy, AA (corresponding author), Univ Texas Austin, Dept Geog & Environm, 1 Univ Stn A3100, Austin, TX 78712 USA.
EM abdulla-al.kafy@localpathways.org; haaltuwaijri@ksu.edu.sa
RI Altuwaijri, Hamad/GRE-8676-2022; Kafy, Abdulla Al/AAF-2173-2020
OI Kafy, Abdulla Al/0000-0002-7544-5165
FU King Saud University [RSPD2024R848]; King Saud University, Riyadh, Saudi
   Arabia
FX The authors extend their appreciation to the Researchers Supporting
   Project number (RSPD2024R848), King Saud University, Riyadh, Saudi
   Arabia.
CR Abdallah S, 2019, ARAB J GEOSCI, V12, DOI 10.1007/s12517-019-4474-1
   Abdelkarim A., 2023, Geol. Ecol. Landsc, P1, DOI DOI 10.1080/24749508.2022.2163741
   Abdelkarim A, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11216003
   Abou-Korin A.A., 2015, Journal of Sustainable Development, V8, P52, DOI DOI 10.5539/JSD.V8N9P52
   Acharya RP, 2019, ECOSYST SERV, V39, DOI 10.1016/j.ecoser.2019.100979
   Adem E, 2024, SUSTAIN CHEM PHARM, V39, DOI 10.1016/j.scp.2024.101539
   Adla K., 2022, One Health, P281, DOI DOI 10.1016/C2019-0-04850-9
   Admasu S, 2023, HELIYON, V9
   Aina YA, 2017, INT ARCH PHOTOGRAMM, V42-3, P9, DOI 10.5194/isprs-archives-XLII-3-W2-9-2017
   AIPH, 2024, RIYADH SAUDI ARABIA
   Al-Taisan WA, 2022, SCIENTIFICA, V2022, DOI 10.1155/2022/2907921
   Aljehani L., 2024, INT J GEOINFORMATICS, V20, P82
   Almulhim AI, 2023, INT J SUST DEV WORLD, V30, P359, DOI 10.1080/13504509.2022.2152199
   Alqadhi S, 2021, EARTH SCI INFORM, V14, P1547, DOI 10.1007/s12145-021-00633-2
   Alqahtany A, 2023, ALEX ENG J, V62, P269, DOI 10.1016/j.aej.2022.07.020
   Alqurashi AF, 2019, GEOCARTO INT, V34, P78, DOI 10.1080/10106049.2017.1367423
   Alsharif M, 2022, FORESTS, V13, DOI 10.3390/f13101530
   Alshehri F, 2023, ADV SPACE RES, V72, P1739, DOI 10.1016/j.asr.2023.04.051
   Alyami SH, 2019, IEEE ACCESS, V7, P178584, DOI 10.1109/ACCESS.2019.2959026
   Arpitha M, 2023, EARTH SCI INFORM, V16, P3057, DOI 10.1007/s12145-023-01073-w
   Atef I, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-11224-7
   Avci C, 2023, INT J ENG GEOSCI, V8, P1, DOI 10.26833/ijeg.987605
   Barbosa CCD, 2015, ECOL INDIC, V52, P430, DOI 10.1016/j.ecolind.2015.01.007
   Baskaran R, 2010, ECOL ECON, V69, P1010, DOI 10.1016/j.ecolecon.2010.01.008
   Belay T, 2022, HELIYON, V8, DOI 10.1016/j.heliyon.2022.e12246
   Bindajam Ahmed Ali, 2024, Environ Sci Pollut Res Int, V31, P44120, DOI 10.1007/s11356-024-34051-w
   Boretti A, 2019, NPJ CLEAN WATER, V2, DOI 10.1038/s41545-019-0039-9
   Boutwell JL, 2013, RESOURCES-BASEL, V2, P517, DOI 10.3390/resources2040517
   Boyle KJ, 2017, OXFORD RES ENCY ENV
   Burrell AL, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-17710-7
   Chopra B., 2022, Anthropocene Science, V1, P342, DOI [10.1007/s44177-022-00034-0, DOI 10.1007/S44177-022-00034-0]
   Costanza R, 1997, NATURE, V387, P253, DOI 10.1038/387253a0
   Darem AA, 2023, EGYPT J REMOTE SENS, V26, P341, DOI 10.1016/j.ejrs.2023.04.005
   Davis DK, 2016, HIST SUSTAIN FUTUR, P1
   Ebrahimy H, 2022, REMOTE SENS APPL, V27, DOI 10.1016/j.rsase.2022.100785
   Elmahdy SI, 2023, GEOCARTO INT, V38, DOI 10.1080/10106049.2023.2184500
   Fan X, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph182111121
   Frumkin H., 2024, CLIM CHANGE PUBLIC H, V359, P367
   Gaur M.K., 2018, Climate Variability Impacts on Land Use and Livelihoods in Drylands, DOI [DOI 10.1007/978-3-319-56681-8, 10.1007/978-3-319-56681-8_1]
   Gichuhi G., 2021, AFRICAN HDB CLIMATE, DOI [10.1007/978-3-030-45106-667, DOI 10.1007/978-3-030-45106-667]
   Gomez-Baggethun E., 2016, Routledge handbook of ecosystem services, P99
   Grimm NB, 2016, CLIMATIC CHANGE, V135, P97, DOI 10.1007/s10584-015-1547-3
   Guerry AD, 2021, URBAN NATURE BIODIVE
   Hackbart VCS, 2017, ECOSYST SERV, V23, P218, DOI 10.1016/j.ecoser.2016.12.010
   He Y, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-82497-6
   Hiscock K.M., 2011, SUSTAINING GROUNDWAT, P207, DOI [10.1007/978-90-481-3426-7_13, DOI 10.1007/978-90-481-3426-7_13]
   Hossain NUI, 2024, REMOTE SENS APPL, V34, DOI 10.1016/j.rsase.2024.101180
   Vanegas-Espinosa LI, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19063160
   Imam A., 2023, Journal of Umm Al-Qura University for Engineering and Architecture, V14, P201
   Jia Y, 2021, ENVIRON PROCESS, V8, P713, DOI 10.1007/s40710-021-00514-2
   Kavzoglu T, 2009, INT J APPL EARTH OBS, V11, P352, DOI 10.1016/j.jag.2009.06.002
   Khorrami M, 2021, SCI TOTAL ENVIRON, V799, DOI 10.1016/j.scitotenv.2021.149304
   Koetse MJ, 2015, ECOSYSTEM SERVICES: FROM CONCEPT TO PRACTICE, P108
   Li BW, 2022, ECOL ENG, V179, DOI 10.1016/j.ecoleng.2022.106612
   Li H, 2024, LAND-BASEL, V13, DOI 10.3390/land13030276
   Liu SY, 2024, FRONT ECOL EVOL, V11, DOI 10.3389/fevo.2023.1307274
   Mahmoud SH, 2018, SCI TOTAL ENVIRON, V633, P1329, DOI 10.1016/j.scitotenv.2018.03.290
   Mallick J, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13132632
   Mas JF, 2013, ISPRS INT J GEO-INF, V2, P869, DOI 10.3390/ijgi2030869
   Mohammed AT., 2023, EUR J ARCHIT URBAN P, V2, P1, DOI [10.24018/ejarch.2023.2.4.33, DOI 10.24018/EJARCH.2023.2.4.33]
   Morshed SR., 2022, FUTURE ECOSYSTEM SER, P103021
   Moscatelli M., 2023, AGATHN INT J ARCHIT, V13, P75
   Muller F., 2015, Ecosystem Services and River Basin Ecohydrology, P7, DOI DOI 10.1007/978-94-017-9846-4_2
   Najmuddin O, 2022, LAND-BASEL, V11, DOI 10.3390/land11111906
   Ouma Y, 2022, INT ARCH PHOTOGRAMM, V43-B3, P681, DOI 10.5194/isprs-archives-XLIII-B3-2022-681-2022
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Vo QT, 2012, ECOL INDIC, V23, P431, DOI 10.1016/j.ecolind.2012.04.022
   Rahman MT, 2016, INT ARCH PHOTOGRAMM, V41, P1017, DOI 10.5194/isprsarchives-XLI-B8-1017-2016
   Rao YX, 2018, J CLEAN PROD, V186, P662, DOI 10.1016/j.jclepro.2018.03.119
   Reuters, 2023, SAUDI POPULATION 322
   Richardson L, 2015, ECOL ECON, V115, P51, DOI 10.1016/j.ecolecon.2014.02.018
   Rotich B., 2022, ENV CHALL, V8, DOI [10.1016/j.envc.2022.100576, DOI 10.1016/J.ENVC.2022.100576]
   Royal Commission for Riyadh City, 2024, GREEN RIYADH PROJECT
   Rundel P.W., 2007, The Physical Geography of South America, P158
   Shao Y, 2012, ISPRS J PHOTOGRAMM, V70, P78, DOI 10.1016/j.isprsjprs.2012.04.001
   Tracy J., 2019, AQUIFER DEPLETION PO
   UN-HABITAT, 2023, COUNTRY PROFILE SAUD
   Van der Biest K, 2015, J ENVIRON MANAGE, V156, P41, DOI 10.1016/j.jenvman.2015.03.018
   Wallace KJ, 2007, BIOL CONSERV, V139, P235, DOI 10.1016/j.biocon.2007.07.015
   Wei RH, 2024, ECOL MODEL, V488, DOI 10.1016/j.ecolmodel.2023.110579
   World Bank, 2024, GLOBAL GROWTH IS STA
   Zhang JJ, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13214449
   Zhang YM, 2023, SCI TOTAL ENVIRON, V857, DOI 10.1016/j.scitotenv.2022.159695
   Zhou JB, 2020, J CLEAN PROD, V276, DOI 10.1016/j.jclepro.2020.122988
   Zhou YQ, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14163911
NR 85
TC 0
Z9 0
U1 2
U2 2
PU SPRINGER WIEN
PI Vienna
PA Prinz-Eugen-Strasse 8-10, A-1040 Vienna, AUSTRIA
SN 0177-798X
EI 1434-4483
J9 THEOR APPL CLIMATOL
JI Theor. Appl. Climatol.
PD NOV
PY 2024
VL 155
IS 11
BP 9497
EP 9516
DI 10.1007/s00704-024-05199-9
EA OCT 2024
PG 20
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA K5T9H
UT WOS:001324187100001
DA 2025-01-10
ER

PT J
AU Bostenaru Dan, M
   Ibric, A
   Popescu, M
   Craciun, C
AF Bostenaru Dan, Maria
   Ibric, Adrian
   Popescu, Mara
   Craciun, Cerasella
TI Architectural Heritage and Archetypal Landscape Approaches Facing
   Environmental Hazards
SO SUSTAINABILITY
LA English
DT Article
DE water; fire; earthquake; archetypal landscape; retrofit; 20th century
   architecture
ID WALKING
AB The research question in this paper concerns elements of nature, such as earth, water, fire, and air, as they have a dual meaning, indicating both hazard and heritage. The relationship of cities with blue-green infrastructure is an example of this. Cities might be surrounded by either water or forest, though the latter has been less investigated as a nature-based solution for climate change adaptation. The connection between water and architecture can also be seen in the seafront type of architectural design, in the architecture of harbours, port facilities, aquariums or thermal baths. This paper aims to present a comprehensive analysis of all of these various architecture programs that were carried out during the first half of the twentieth century. Although the styles of Art Nouveau and Interwar were widely spread, otherness in regional geographical locations drew lessons from the vernacular architecture. Inspiration was drawn mainly from southern Europe in the Cycladic islands for the interwar/international style and towards the east and centre of the continent in Romania and Hungary and up to the north in the Baltic states for the national romantic art nouveau style. A local seismic culture is prevalent in areas that are affected by earthquakes. In the context of the geological conditions related to water and earthquake hazard, the anthropic reshaping of rivers and canals (and alluvial soil deposits) generates liquefaction vulnerability. Significant also is the way in which the urban wildland interface shapes the relationship between wild green space and cities. Urban protected nature parks and urban forests contribute to wellbeing but are also vulnerable to wildfire. This research attempts to find equivalents to the local seismic culture in cases of climate change-induced hazards, such as floods and wildfires, in Romania, Italy and Portugal. As part of the project presented for the case study featured in this paper, significant documentation was achieved through literature reviews and field trips. For the latter, walkscape methodology was used, which was also useful for the first round of results and the mapping required to indicate earthquake hazards near water locations in Bucharest, Romania.
C1 [Bostenaru Dan, Maria; Ibric, Adrian; Popescu, Mara] Ion Mincu Univ Architecture & Urbanism, Dept Res, Bucharest 010014, Romania.
   [Popescu, Mara] George Emil Palade Univ Med Pharm Sci & Technol, Dept Ind Engn & Management, Architecture Study Program, Targu Mures 540142, Romania.
   [Craciun, Cerasella] Ion Mincu Univ Architecture & Urbanism, Dept Urban & Landscape Design, Bucharest 010014, Romania.
C3 Ion Mincu University of Architecture & Urbanism; George Emil Palade
   University of Medicine, Pharmacy, Science, & Technology of Targu Mures;
   Ion Mincu University of Architecture & Urbanism
RP Bostenaru Dan, M (corresponding author), Ion Mincu Univ Architecture & Urbanism, Dept Res, Bucharest 010014, Romania.
EM maria.bostenaru-dan@alumni.kit.edu
RI Ibric, Adrian/KZQ-3288-2024; Bostenaru Dan, Maria/B-6089-2011; Craciun,
   Cerasella/F-4200-2015
OI Ibric, Adrian/0000-0002-7488-2419; Bostenaru Dan,
   Maria/0000-0002-0855-8979; Craciun, Cerasella/0000-0003-4326-886X
FU UEFISCDI
FX No Statement Available
CR Al Sayah MJ, 2022, URBAN CLIM, V44, DOI 10.1016/j.uclim.2022.101229
   Alexander C., 1977, A pattern language: towns, buildings, construction
   [Anonymous], 2022, MONITORUL OFICIAL, P708
   Bassett K, 2004, J GEOGR HIGHER EDUC, V28, P397, DOI 10.1080/0309826042000286965
   Batista Teresa, 2022, New Metropolitan Perspectives: Post COVID Dynamics: Green and Digital Transition, between Metropolitan and Return to Villages Perspectives. Lecture Notes in Networks and Systems (482), P1658, DOI 10.1007/978-3-031-06825-6_159
   Ben Salem S., 2020, P SZIENTIFIC M YOUNG
   Biasin A, 2023, LAND-BASEL, V12, DOI 10.3390/land12020280
   Bostenaru Dan M, 2005, NAT HAZARD EARTH SYS, V5, P397, DOI 10.5194/nhess-5-397-2005
   Bostenaru Dan M., 2003, FORSCHUNGSBERICHTE G, VVolume 1, P93
   Bostenaru Dan M., 2023, ARGUMENT, V15, P209, DOI [10.54508/Argument.15.12, DOI 10.54508/ARGUMENT.15.12]
   Bostenaru Dan M., 2023, CREATIVE NEGOTIATION, P267
   Bostenaru Dan M., 2023, P EGU GEN ASSEMBLY 2
   Bostenaru Dan M., 2022, P EGU GEN ASSEMBLY 2
   Bostenaru Dan M, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12155925
   Bratianu G.I., 1942, ENIGME MIRACLE HISTO
   Calliari E, 2022, CLIM RISK MANAG, V37, DOI 10.1016/j.crm.2022.100450
   Caniggia G., 1986, MORPHOLOGISCHE BETRA
   Caquard S., 2017, Mappe Monde, V121, P1, DOI DOI 10.4000/MAPPEMONDE.3386
   Carley K.M., 2014, Encyclopedia of social network analysis and mining, P1219, DOI DOI 10.1007/978-1-4614-6170-8
   Cataldi G, 2002, URBAN MORPHOL, V6, P3
   Craciun C., 2011, CULTURAL LANDSCAPE D, P163
   Craciun C., 2023, ARCHITECTURE INSPIRE
   Craciun C, 2012, ROM ASTRON J, V22, P55
   Craciun C, 2014, ENVIR HAZARD, P67, DOI 10.1007/978-94-007-7981-5_4
   Dantas G.S., 2021, CHALLENGES NOWADAYS, P53
   de Vries J., 2022, LENOTRE LANDSCAPE FO
   Debord G., 1955, SITUATIONIST INT
   DeBord Guy., 1967, Society of the Spectacle
   Deleuze Giles, 1980, Mille Plateaux
   Di Pirro E, 2023, LAND-BASEL, V12, DOI 10.3390/land12030603
   Di Pirro E, 2022, LAND-BASEL, V11, DOI 10.3390/land11081254
   Di Salvatore S, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095240
   Eliade M., 2016, SACRED AND PROFANE
   Enache C, 2013, PROCD SOC BEHV, V92, P309, DOI 10.1016/j.sbspro.2013.08.677
   Federal Emergency Management Agency (FEMA), 1988, FEMA 155 ATC 21 1 RA
   Geneletti D., 2022, NATURE BASED SOLUTIO
   Gimbutas Marija., 2007, The Goddesses and Gods of Old Europe
   Gociman C.O., 2006, MANAGEMENTUL REDUCER
   Harmanescu M., 2016, SEISMIC RETROFITTING
   Hasnas D., 2022, GOLDSTEIN MAICU VILE
   Hillier B., 1984, The Social Logic of Space, DOI 10.1017/CBO9780511597237
   Ibric A., 2022, ARGUMENT, V14, P270, DOI [10.54508/Argument.14.18, DOI 10.54508/ARGUMENT.14.18]
   Ioan A., 2022, ARHITECTURA, V5-6, P208
   Ioan A., 2012, ARHITECTURA, V3, P22
   Jimenez-Vicario P.M., 2022, DIGITAL MODERNISM HE
   Johnson B A., 2022, Nature-Based Solutions, V2, P100042, DOI DOI 10.1016/J.NBSJ.2022.100042
   Kelman I, 2017, ENVIRON CONSERV, V44, P244, DOI 10.1017/S0376892917000042
   Lagomarsino S, 2006, B EARTHQ ENG, V4, P415, DOI 10.1007/s10518-006-9024-z
   Langenbach R, 2007, INT J ARCHIT HERIT, V1, P29, DOI 10.1080/15583050601125998
   Legutko-Kobus P, 2023, LAND-BASEL, V12, DOI 10.3390/land12010245
   Lejeune Jean-Francois., 2010, Modern Architecture and the Mediterranean: Vernacular Dialogues and Contested Identities
   Li YL, 2022, LAND-BASEL, V11, DOI 10.3390/land11081227
   Liritzis I, 2019, J COASTAL RES, V35, P1307, DOI 10.2112/JCOASTRES-D-19-00035.1
   LUNGU DM, 1994, DGEB PUBL, P51
   Lynch Kevin, 1960, The Image of the City
   Machado e Moura C., 2023, REPOSITORY 49 METHOD
   Marymor L, 2018, ARTS, V7, DOI 10.3390/arts7020014
   Masiero M, 2022, FORESTS, V13, DOI 10.3390/f13030444
   Meier M., 2012, HIST DISASTERS CONTE, P15
   Muratori S., 1960, STUDI OPERANTE STORI, P97
   Muratori Saverio., 1963, Studi per un Operante Storia Urbana di Roma
   Nickayin SS, 2023, LAND-BASEL, V12, DOI 10.3390/land12030604
   Norberg-Schulz Christian., 1982, Genius loci. Landschaft, Lebensraum
   Papina C., 2023, ARCHITECTURE INSPIRE
   Peixoto P, 2016, AGUA COMO PATRIMONIO: EXPERIENCIAS DE REQUALIFCACAO DAS CIDADES COM AGUA E DAS PAISAGENS FLUVIAIS, P1, DOI 10.14195/978-989-26-1025-2
   Pfammatter Ulrich., 1997, Der Erfindung des modernen Architekten
   Popescu D., 2022, PITORESC MEDITERANEE
   Puczko L., 2007, CULTURAL TOURISM, P131
   Rana IA, 2022, J INTEGR ENVIRON SCI, V19, P65, DOI 10.1080/1943815X.2022.2108458
   RENFREW C, 1973, P PREHIST SOC, V39, P474, DOI 10.1017/S0079497X0001183X
   Sassu M., 2005, CASA TORRE CONSTRUCT
   Savonea, 2023, RATIONALISME ALE SUD
   Schenk G., 2009, UNTERGANG POMPEJIS B
   Schenk GJ, 2017, TRANSCULT RES, P1, DOI 10.1007/978-3-319-49163-9
   Silva Dantas G., 2022, P FABOS C LANDSCAPE
   Smith P, 2013, SCAND J HOSP TOUR, V13, P103, DOI 10.1080/15022250.2013.796223
   Sokolov VY, 2009, SOIL DYN EARTHQ ENG, V29, P364, DOI 10.1016/j.soildyn.2008.04.004
   Stefano P, 2014, PROC ECON FINANC, V18, P173, DOI 10.1016/S2212-5671(14)00928-9
   Thompson A, 2023, SUSTAIN DEV, V31, P1991, DOI 10.1002/sd.2510
   Tice J., 2005, NOLLI MAP ROME INFOG
   Tice J., 2021, INTERACTIVE NOLLI MA
   Tobriner Stephen., 2006, Bracing for Disaster: Earthquake-resistant Architecture and Engineering in San Francisco, 1838-1933
   Tsianaka E, 2006, WIT TRANS BUILT ENV, V86, P93, DOI 10.2495/ARC060101
   Vojvodíková B, 2022, LAND-BASEL, V11, DOI 10.3390/land11101712
   Wieczorek A., 2014, MENSCH NATUR KATASTR
   Wiley D, 2010, ARCHIT THEORY REV, V15, P9, DOI 10.1080/13264821003629220
   Zuccaro G., 2021, P COMPDYN 2021 8 ECC
NR 87
TC 1
Z9 1
U1 11
U2 20
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD FEB
PY 2024
VL 16
IS 4
AR 1505
DI 10.3390/su16041505
PG 22
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA IT1Z4
UT WOS:001168505400001
OA gold
DA 2025-01-10
ER

PT J
AU Valness, CM
   Libby, WJ
   Berrill, JP
AF Valness, Christopher M.
   Libby, William J.
   Berrill, John-Pascal
TI Assisted Migration of <i>Sequoiadendron</i> Genotypes for Conservation
   and Timber: Performance and Morphology in a Warmer Climate Outside of
   Their Range
SO CONSERVATION
LA English
DT Article
DE climate-change adaptation; conservation genetics; forest genetics; giant
   sequoia; provenance test; stem-form traits; tree-species mixtures
ID FLUTED WESTERN HEMLOCK; GIANT SEQUOIA; SIERRA-NEVADA; GROWTH; ALASKA
AB Sequoiadendron giganteum (giant sequoia) has a fragmented distribution of 75 groves found along the western slope of the Sierra Nevada Mountains, California, USA. Outplanting and range expansion or assisted migration of this iconic species for the objectives of genetic conservation and timber production would be supported by information on growth and morphology to guide seed-collection decisions. We measured and assessed giant sequoia planted as seedlings and clonal stock originating from 22 groves in two common-garden experiments at Foresthill, California, north of the current species range, after 29 growing seasons. Traits examined were tree-size parameters, fluting and asymmetry of the lower stem, basal swelling, fullness of the live crown, epicormic sprouting, and heartwood decay resistance in cut stumps. Performance in terms of tree size after 29 years varied widely among genotypes with different grove origins. Morphology and decay resistance also exhibited some variation according to grove origins. The seedling stock outperformed the clonal stock of the same grove origins in terms of size and is therefore recommended when faster early growth is desired to outcompete other trees or for other management objectives. However, more fluting was exhibited by the larger fast-growing giant sequoia, while fewer seedlings had epicormic sprouts than the clonal stock of the same grove origins. At our warm low-elevation study site, giant sequoia from Mountain Home, Giant Forest, and Converse Basin consistently exhibited above-average growth among other giant sequoia in a pure planting and in an intimate mixture with five common conifer associates. Therefore, seed collected from these three groves should perform relatively well at other locations with a similar climate. When conservation of the species and its genetic diversity is the primary objective, we recommend collecting from a wide range of groves and undertaking assisted migration by planting at multiple locations inside and outside giant sequoia's range as a hedge against the loss of native groves.
C1 [Valness, Christopher M.; Berrill, John-Pascal] Calif State Polytech Univ Humboldt, Dept Forestry Fire & Rangeland Management, Arcata, CA 95521 USA.
   [Libby, William J.] Univ Calif Berkeley, Coll Nat Resources, Berkeley, CA 94720 USA.
C3 University of California System; University of California Berkeley
RP Berrill, JP (corresponding author), Calif State Polytech Univ Humboldt, Dept Forestry Fire & Rangeland Management, Arcata, CA 95521 USA.
EM chris.valness@gmail.com; pberrill@humboldt.edu
FU Save-the-Redwoods League; Sierra Pacific Industries
FX This research was funded by the Save-the-Redwoods League and Sierra
   Pacific Industries.
CR Ahuja MR, 2009, EUPHYTICA, V165, P5, DOI 10.1007/s10681-008-9813-3
   Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   [Anonymous], 2013, NPS/SEKI/NRR-2013/665
   Burdon R.D., 2017, Domestication of Radiata Pine
   CONOVER WJ, 1981, TECHNOMETRICS, V23, P351, DOI 10.2307/1268225
   Cox LE, 2021, FOREST ECOL MANAG, V488, DOI 10.1016/j.foreco.2021.119033
   De La Mare P., 2004, The Proceedings of a Farm Forestry Seminar on Special Purpose Tree Plantings, P11
   Deal RL, 2003, FORESTRY, V76, P401, DOI 10.1093/forestry/76.4.401
   Debell Jeffrey D., 1997, Western Journal of Applied Forestry, V12, P9
   DeSilva R, 2020, AM J BOT, V107, P45, DOI 10.1002/ajb2.1406
   Dirnböck T, 2011, GLOBAL CHANGE BIOL, V17, P990, DOI 10.1111/j.1365-2486.2010.02266.x
   FINS L, 1982, SILVAE GENET, V31, P102
   Fins L., 1979, THESIS U CALIFORNIA
   Harris A.S., 1974, General Technical Report PNW-25
   HARRY DE, 1987, CAN J FOREST RES, V17, P484, DOI 10.1139/x87-082
   Hartesveldt RJ., 1975, GIANT SEQUOIA SIERRA
   Harvey H T., 1980, Scientific Monograph Series, V12
   Harvey H.T., 1986, General Technical Report PSW-95
   JULIN KR, 1993, FOREST ECOL MANAG, V60, P133, DOI 10.1016/0378-1127(93)90027-K
   JULIN KR, 1993, FOREST ECOL MANAG, V60, P119, DOI 10.1016/0378-1127(93)90026-J
   KELLOGG RM, 1981, CAN J FOREST RES, V11, P714, DOI 10.1139/x81-099
   Kitzmiller JH, 2012, WEST J APPL FOR, V27, P196, DOI 10.5849/wjaf.11-029
   Kozlowski T.T., 1997, PHYSL WOODY PLANTS
   Libby W.J., 1986, General Technical Report
   LIBBY WJ, 1980, SILVAE GENET, V29, P183
   Mahalovich M.F., 1985, Masters Thesis
   Millar CI, 1999, TRANS N AM WILDL NAT, P206
   O'Hara KL, 2008, FORESTRY, V81, P103, DOI 10.1093/forestry/cpm049
   O'Hara KL, 2009, ANN FOREST SCI, V66, DOI 10.1051/forest/2009015
   Páques LE, 2001, SILVAE GENET, V50, P69
   Piirto D.D., 1986, General Technical Report PSW-95
   Pile LS, 2019, FORESTS, V10, DOI 10.3390/f10030237
   Pretzsch H, 2020, TREES-STRUCT FUNCT, V34, P957, DOI 10.1007/s00468-020-01973-0
   RUNDEL P W, 1972, Madrono, V21, P319
   RUNDEL PW, 1971, AM MIDL NAT, V85, P478, DOI 10.2307/2423770
   RUNDEL PW, 1972, AM MIDL NAT, V87, P81, DOI 10.2307/2423883
   Rydelius J.A., 1993, Clonal Forestry II, P158, DOI DOI 10.1007/978-3-642-84813-1_9
   Sáenz-Romero C, 2021, FORESTS, V12, DOI 10.3390/f12010009
   Sexton JP, 2014, EVOLUTION, V68, P1, DOI 10.1111/evo.12258
   STEPHENSON NL, 1994, USDA PAC SW, V151, P56
   Thornton P.E., 2012, DAYMET DAILY SURFACE, DOI DOI 10.3334/ORNLDAAC/DAYMETV2
   Ukrainetz NK, 2008, CAN J FOREST RES, V38, P1536, DOI 10.1139/X07-234
   van Mantgem PJ, 2009, SCIENCE, V323, P521, DOI 10.1126/science.1165000
   Waring KM, 2005, WEST J APPL FOR, V20, P228, DOI 10.1093/wjaf/20.4.228
   Weatherspoon C.P., 1990, Silv. N. Am, V1, P552
   Willard D., 2000, Guide to the Sequoia Groves of California
   WRCC Western Regional Climate Center, 2014, Cooperative Climatological Data Summaries
   York RA, 2013, WEST J APPL FOR, V28, P30, DOI 10.5849/wjaf.12-017
NR 48
TC 1
Z9 1
U1 0
U2 0
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2673-7159
J9 CONSERVATION-BASEL
JI Conservation
PD DEC
PY 2023
VL 3
IS 4
BP 543
EP 568
DI 10.3390/conservation3040035
PG 26
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Emerging Sources Citation Index (ESCI)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA YY7Y2
UT WOS:001272125300001
OA gold
DA 2025-01-10
ER

PT J
AU Shin, S
   Her, Y
   Khare, Y
AF Shin, Satbyeol
   Her, Younggu
   Khare, Yogesh
TI Evaluation of impacts of climate change on natural and managed wetland
   basins
SO JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
LA English
DT Article
DE wetland watershed; climate change; Western Everglades; Watershed
   Assessment Model; runoff; total phosphorus
ID WATER-QUALITY MODELS; MULTISITE CALIBRATION; SEASONAL RAINFALL; FUTURE
   CHANGES; RIVER FLOW; PROJECTIONS; UNCERTAINTY; VARIABILITY; PERFORMANCE;
   VALIDATION
AB Low floodplain wetlands such as the Western Everglades in South Florida are vulnerable to extreme weather events, and their water quality and ecosystem functions vary greatly depending on changes in water levels and discharges. The future (i.e., the mid and late 21st century) climate is projected to result in increased frequency and magnitude of extreme events, which could negatively affect the hydroecological function of the wetlands. Wetland management practices have commonly been implemented to protect wetlands and their functions, but it is not clear whether the current management practices can still be effective in projected climate change scenarios. The main goal of this study was to evaluate the impacts of climate change on the runoff and total phosphorus (TP) of natural (L28 Gap) and managed (L28) wetland watersheds in the Western Everglades. For the assessment, we employed future climate projections made using 29 general circulation models (GCMs) and the Watershed Assessment Model (WAM), a watershed loading model. The WAM was calibrated and validated for the baseline period (2000-2014), and the bias-corrected climate projections were incorporated into the model to project the runoff discharge and TP loads for the near-future (2030-2044) and far-future (2070-2084) periods in two carbon emission scenarios. The modeling results show that the natural wetland watershed would be more vulnerable to projected climate change than the managed wetland watershed. The impact of projected climate change scenarios on daily runoff and TP loads was modulated by water control facilities and practices in the managed watershed, highlighting the significance of watershed management practices for improved water quality under projected climate change. This study demonstrates how the local natural and managed wetland watersheds distinctly respond to the global-scale changes and emphasizes the role of water management practices in wetland basins, which are expected to help develop effective climate change adaptation plans for improved sustainability of wetland systems.
C1 [Shin, Satbyeol] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL USA.
   [Shin, Satbyeol] Univ Michigan, Sch Environm & Sustainabil, Ann Arbor, MI USA.
   [Her, Younggu] Univ Florida, Trop Res & Educ Ctr, Dept Agr & Biol Engn, 18905 SW 280th St, Homestead, FL 33031 USA.
   [Khare, Yogesh] Everglades Fdn, Palmetto Bay, FL USA.
   [Khare, Yogesh] South Florida Water Management Dist, W Palm Beach, FL USA.
C3 State University System of Florida; University of Florida; University of
   Michigan System; University of Michigan; State University System of
   Florida; University of Florida; South Florida Water Management District
RP Her, Y (corresponding author), Univ Florida, Trop Res & Educ Ctr, Dept Agr & Biol Engn, 18905 SW 280th St, Homestead, FL 33031 USA.
EM yher@ufl.edu
RI HER, YOUNG GU/Q-7975-2018
OI HER, YOUNG GU/0000-0003-3700-5115; Khare, Yogesh/0000-0001-7849-714X;
   Shin, Satbyeol/0000-0002-8205-9385
FU National Institute of Food and Agriculture [FLA-TRC-005551]; Everglades
   Foundation
FX Everglades Foundation; National Institute of Food and Agriculture,
   Grant/Award Number: FLA-TRC- 005551
CR Abbaspour KC, 2018, WATER-SUI, V10, DOI 10.3390/w10010006
   Ali A, 2000, J AM WATER RESOUR AS, V36, P833, DOI 10.1111/j.1752-1688.2000.tb04310.x
   Almazroui M, 2012, ATMOS RES, V111, P29, DOI 10.1016/j.atmosres.2012.02.013
   Aryal K., 2019, Emerg. Sci. J, V3, P303, DOI DOI 10.28991/ESJ-2019-01193
   Bottcher AB, 2012, T ASABE, V55, P1367
   Brown A. E., 2006, 806 CSIRO LAND WAT S
   Cannon AJ, 2015, J CLIMATE, V28, P6938, DOI 10.1175/JCLI-D-14-00754.1
   Chebud Y, 2011, J ENVIRON MONITOR, V13, P66, DOI 10.1039/c0em00321b
   Corrales J, 2014, J ENVIRON MANAGE, V143, P162, DOI 10.1016/j.jenvman.2014.04.031
   Crimp S, 2019, CLIM DYNAM, V52, P1247, DOI 10.1007/s00382-018-4188-1
   Daggupati P, 2015, T ASABE, V58, P1705
   Daggupati P, 2015, HYDROL PROCESS, V29, P5307, DOI 10.1002/hyp.10536
   Dobler C, 2012, HYDROL EARTH SYST SC, V16, P4343, DOI 10.5194/hess-16-4343-2012
   Erwin KL, 2009, WETL ECOL MANAG, V17, P71, DOI 10.1007/s11273-008-9119-1
   Estenoz S, 2015, ENVIRON MANAGE, V55, P876, DOI 10.1007/s00267-015-0452-x
   Fan XW, 2021, WEATHER CLIM EXTREME, V32, DOI 10.1016/j.wace.2021.100328
   Fan ZM, 2021, SCI TOTAL ENVIRON, V796, DOI 10.1016/j.scitotenv.2021.148918
   Ficklin DL, 2018, P NATL ACAD SCI USA, V115, P8553, DOI 10.1073/pnas.1801026115
   Florida Department of Environmental Protection (FDEP), 2017, FIN 2016 PROGR REP L
   Florida Department of Environmental Protection (FDEP), 2013, STAT LAND US LAND CO
   Fossey M, 2016, J ENVIRON MANAGE, V184, P327, DOI 10.1016/j.jenvman.2016.09.043
   Fowler HJ, 2007, J GEOPHYS RES-ATMOS, V112, DOI 10.1029/2007JD008619
   Glotter M, 2014, P NATL ACAD SCI USA, V111, P8776, DOI 10.1073/pnas.1314787111
   Graham WD., 2009, PEER REV WATERSHED A
   Grimm NB, 2013, FRONT ECOL ENVIRON, V11, P474, DOI 10.1890/120282
   Gupta HV, 1999, J HYDROL ENG, V4, P135, DOI 10.1061/(ASCE)1084-0699(1999)4:2(135)
   Hansen J., 2008, Open Atmosphere Science Journal, V2, P217, DOI 10.2174/1874282300802010217
   HDR and SWET, 2009, WAM ENH APPL LAK OK
   Her Y, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-41334-7
   Hewitt JE, 2016, GLOBAL CHANGE BIOL, V22, P2665, DOI 10.1111/gcb.13176
   Hidalgo HG, 2015, INT J CLIMATOL, V35, P3397, DOI 10.1002/joc.4216
   Hoang LP, 2016, HYDROL EARTH SYST SC, V20, P3027, DOI 10.5194/hess-20-3027-2016
   HUBBARD KG, 1994, AGR FOREST METEOROL, V68, P29, DOI 10.1016/0168-1923(94)90067-1
   Jehanzaib M, 2020, STOCH ENV RES RISK A, V34, P7, DOI 10.1007/s00477-019-01760-5
   Johnson F, 2009, J CLIMATE, V22, P4373, DOI 10.1175/2009JCLI2681.1
   Kalla P.I., 2017, EVERGLADES ECOSYSTEM
   Khare Y, 2019, WATER-SUI, V11, DOI 10.3390/w11020327
   Khare YP, 2021, LAND-BASEL, V10, DOI 10.3390/land10090977
   Khare YP, 2020, ECOL ENG, V143, DOI 10.1016/j.ecoleng.2019.105663
   Kirtman B.P., 2017, FLORIDAS CLIMATE CHA, DOI [10.17125/fci2017.ch18, DOI 10.17125/FCI2017.CH18]
   Knisel WG., 1993, GLEAMS: groundwater loading effects of agricultural management systems, V2.10
   Knutti R, 2010, J CLIMATE, V23, P2739, DOI 10.1175/2009JCLI3361.1
   Lasch P., 1999, Environmental Modeling & Assessment, V4, P273, DOI 10.1023/A:1019024619886
   Lee SK, 2011, J CLIMATE, V24, P1264, DOI 10.1175/2010JCLI3883.1
   Lehmann J, 2015, CLIMATIC CHANGE, V132, P501, DOI 10.1007/s10584-015-1434-y
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Leta OT, 2017, J HYDROL ENG, V22, DOI 10.1061/(ASCE)HE.1943-5584.0001471
   Lewsey C, 2004, MAR POLICY, V28, P393, DOI 10.1016/j.marpol.2003.10.016
   Li Y, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8060456
   Lin PR, 2018, J AM WATER RESOUR AS, V54, P40, DOI 10.1111/1752-1688.12585
   Madsen MS, 2017, GEOPHYS RES LETT, V44, P11606, DOI 10.1002/2017GL075627
   Mattos TS, 2021, J HYDROL ENG, V26, DOI 10.1061/(ASCE)HE.1943-5584.0002143
   Michener WK, 1997, ECOL APPL, V7, P770, DOI 10.1890/1051-0761(1997)007[0770:CCHATS]2.0.CO;2
   Miller R.L., 2004, 034249 US GEOL SURV
   Misra Vasubandhu., 2011, CLIMATE SCENARIOS FL
   Moriasi DN, 2015, T ASABE, V58, P1763
   Murawski A, 2016, HYDROL EARTH SYST SC, V20, P4283, DOI 10.5194/hess-20-4283-2016
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   National Academics of Sciences Engineering and Medicine (NASEM), 2018, PROGR RESTORING EVER, DOI [10.17226/25198, DOI 10.17226/25198]
   National Research Council (NRC), 2011, UNDERSTANDING EARTHS, DOI [10.17226/13111, DOI 10.17226/13111]
   Nkiaka E, 2018, STOCH ENV RES RISK A, V32, P1665, DOI 10.1007/s00477-017-1466-0
   Obeysekera J., 2011, Past and projected trends in climate and sea level for South Florida
   Obeysekera J, 2015, ENVIRON MANAGE, V55, P749, DOI 10.1007/s00267-014-0315-x
   Oo HT, 2019, CIV ENG J-TEHRAN, V5, P2152, DOI 10.28991/cej-2019-03091401
   Pearlstine LG, 2010, J N AM BENTHOL SOC, V29, P1510, DOI 10.1899/10-045.1
   PRIESTLEY CHB, 1972, MON WEATHER REV, V100, P81, DOI 10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2
   Qi YJ, 2017, INT J CLIMATOL, V37, P109, DOI 10.1002/joc.4690
   Qiu JX, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00312.1
   Rajib A, 2018, J HYDROL, V567, P668, DOI 10.1016/j.jhydrol.2018.10.024
   Rauscher SA, 2011, J CLIMATE, V24, P2003, DOI 10.1175/2010JCLI3536.1
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Ritter A, 2013, J HYDROL, V480, P33, DOI 10.1016/j.jhydrol.2012.12.004
   Ruane A.C., 2017, EARTH PERSPECTIVES, V4, P1, DOI [DOI 10.1186/S40322-017-0036-4, 10.1186/s40322-017-0036-4]
   Scheidt D., 2000, 904R00003 EPA
   Schwalm CR, 2020, P NATL ACAD SCI USA, V117, P19656, DOI 10.1073/pnas.2007117117
   Singh VP, 1997, HYDROL PROCESS, V11, P1649, DOI 10.1002/(SICI)1099-1085(19971015)11:12<1649::AID-HYP495>3.0.CO;2-1
   Soil and Water Engineering Technology (SWET), 2018, WATERSHED ASSESSMENT
   Song JH, 2020, HYDROLOG SCI J, V65, P1490, DOI 10.1080/02626667.2020.1750616
   South Florida Water Management District (SFWMD), 2011, MOD DOC REP DRAFT RS
   South Florida Water Management District (SFWMD), 2018, 2018 S FLOR ENV REP, VI
   South Florida Water Management District (SFWMD), 2010, DRAFT REPORT CAL VAL
   Swain S, 2015, CLIM DYNAM, V44, P2737, DOI 10.1007/s00382-014-2255-9
   Tao YM, 2018, INT J CLIMATOL, V38, P467, DOI 10.1002/joc.5188
   Tegegne G, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135357
   Thompson JR, 2013, J HYDROL, V486, P1, DOI 10.1016/j.jhydrol.2013.01.029
   Thomson AM, 2011, CLIMATIC CHANGE, V109, P77, DOI 10.1007/s10584-011-0151-4
   Torres IBL, 2011, HYDROL PROCESS, V25, P2032, DOI 10.1002/hyp.7955
   United States Army Corps of Engineers (USACE), 2017, W EV REST PROJ
   United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS), 2012, SOIL SURV GEOGR DAT
   University of Florida GeoPlan Center (GeoPlan), 2013, FLOR COMP DIG EL MOD
   Veraart AJ, 2012, NATURE, V481, P357, DOI 10.1038/nature10723
   Vose JM, 2012, IAHS-AISH P, V353, P12
   Wang S, 2012, HYDROL EARTH SYST SC, V16, P4621, DOI 10.5194/hess-16-4621-2012
   Westra S, 2014, REV GEOPHYS, V52, P522, DOI 10.1002/2014RG000464
   Woldemeskel FM, 2016, J GEOPHYS RES-ATMOS, V121, P3, DOI 10.1002/2015JD023719
   Xie YL, 2020, J ENVIRON MANAGE, V261, DOI 10.1016/j.jenvman.2020.110249
   Yuan Y, 2015, T ASABE, V58, P1721
   Zamani R, 2020, WATER RESOUR MANAG, V34, P1093, DOI 10.1007/s11269-020-02486-8
   Zhang J, 1999, APPL ENG AGRIC, V15, P441
   Zhao GJ, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0091048
NR 100
TC 2
Z9 2
U1 5
U2 15
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1093-474X
EI 1752-1688
J9 J AM WATER RESOUR AS
JI J. Am. Water Resour. Assoc.
PD DEC
PY 2023
VL 59
IS 6
BP 1549
EP 1568
DI 10.1111/1752-1688.13140
EA JUN 2023
PG 20
WC Engineering, Environmental; Geosciences, Multidisciplinary; Water
   Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA GP4G1
UT WOS:001007921400001
OA Bronze
DA 2025-01-10
ER

PT J
AU Patsch, K
   Jenkins, S
   King, P
AF Patsch, Kiki
   Jenkins, Sarah
   King, Philip
TI All according to plan: Maldevelopment, moral hazard, federal aid, and
   climate change adaptation on Dauphin Island, Alabama, USA
SO OCEAN & COASTAL MANAGEMENT
LA English
DT Article
ID IVAN SEPTEMBER 16; PATHWAYS; HISTORY; IMPACT; CHAIN
AB Dauphin Island, Alabama is a particularly egregious example of moral hazard and maldevelopment and the policies and practices that allow this to take place. The west end of Dauphin Island offers a clear case study of such practices and illustrates the crucial role that State and local regulation play in curtailing many of the moral hazard effects of federal disaster relief funding in promoting maldevelopment. Where unrestricted, moral hazard can act as an incentive to build or rebuild in at-risk areas, and unlike many other coastal areas, Dauphin Island lacks policies and requirements which restrict such development. Using the richest dataset available for the island and geospatial visualization, this analysis presents Dauphin Island as a case study of the potential consequences of unrestricted, heavily subsidized maldevelopment, and outlines the policies that enabled it to take place.Dauphin Island demonstrates that Federal disaster relief programs other than the National Flood Insurance Program (NFIP) can contribute to maldevelopment. On Dauphin Island, Federal disaster relief from a combination of programs created a continual cycle of rebuilding on the island since 1979. Crucially, local coastal management policy acts as a valve restricting and directing the flow of federal funds. On Dauphin Island, those funds have not been directed towards resiliency, but towards maintaining and rebuilding the most vulnerable portion of the island.Geospatial visualization of current parcel development patterns clearly shows the consequences of these incentives to build and rebuild in areas that are known to be risky in terms of future storms and flooding. In particular, this analysis indicates that the "typical" property on the island is: (1) not owned by island residents, and (2) is a second home either rented out or used seasonally. Thus, a significant portion of the State, Local, and Federal expenditures designed for local disaster relief benefit property owned by off-island and out-of-state residents used for second homes. These high-value, high-risk properties result in the island receiving disproportionately high (FEMA) expenditures.
C1 [Patsch, Kiki] Calif State Univ Channel Isl, Camarillo, CA 93012 USA.
   [Jenkins, Sarah] Univ Pacific, Stockton, CA USA.
   [King, Philip] San Francisco State Univ, San Francisco, CA USA.
C3 California State University System; California State University Channel
   Islands; University of the Pacific; California State University System;
   San Francisco State University
RP Patsch, K (corresponding author), Calif State Univ Channel Isl, Camarillo, CA 93012 USA.
EM kiki.patsch@csuci.edu
CR AECOM Michael Baker, 2013, IMPACT CLIMATE CHANG
   Altmaier D., 2017, 1704 CIPR
   Amin Samir., 1990, Maldevelopment: Anatomy of a Global Failure
   Anderson D., 2022, SHORE BEACH, V90, P16, DOI [10.34237/1009012, DOI 10.34237/1009012]
   Barnett J, 2014, NAT CLIM CHANGE, V4, P1103, DOI 10.1038/NCLIMATE2383
   Beatley T., 1989, International Journal of Mass Emergencies and Disasters, V7, P5
   Bilskie MV, 2016, EARTHS FUTURE, V4, P177, DOI 10.1002/2015EF000347
   Boyd CA., 2012, Coastal Alabama Living Shorelines Policies, Rules, and Model Ordinance Manual, P50
   Byrnes M.R., 2010, CHANNEL DREDGING GEO
   Byrnes M.R., 2012, ERDCCHLTR129
   Calil J., 2017, J OCEAN COAST EC, V4, DOI [10.15351/2373-8456.1074, DOI 10.15351/2373-8456.1074]
   Congressional Research Service, 2022, R45999 C RES SERV
   Dauphin Island Chamber of Commerce, 2022, HIST DAUPH ISL
   David CG, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-26082-5
   Del Angel DC, 2022, DATA, V7, DOI 10.3390/data7060071
   Douglas S.L., 1992, COASTAL PROCESSES DA
   DOUGLASS SL, 1994, J COASTAL RES, V10, P306
   Elko N., 2016, SHORE BEACH, V84, P1
   Feagin RA, 2008, J COASTAL RES, V24, P1063, DOI 10.2112/07-0862.1
   Federal Emergency Management Agency, 2021, FEMA OFF MOR EQ FLOO
   Federal Emergency Management Agency, 2020, MIT ASS BUILD RES IN
   Federal Emergency Management Agency, 2011, GUID SEV REP LOSS PR
   Federal Emergency Management Agency, 2021, PART IMPL FED FLOOD
   Federal Emergency Management Agency, 2020, EC SERV BEN BEN COST
   Federal Emergency Management Agency, 2020, HAZ MIT ACT PORTF
   Federal Emergency Management Agency, 2021, DAUPH ISL NFIP COMPL
   Federal Emergency Management Agency, 2019, 10400903 FP FED EM M
   Federal Emergency Management Agency, 2017, 16600022 OMB FED EM
   Flocks J.G., 2017, ANAL SEAFLOOR CHANGE, P1987, DOI [10.3133/ofr20171112, DOI 10.3133/OFR20171112]
   Frank S., 2021, Inviting danger: How federal disaster, insurance and infrastructure policies are magnifying the harm of climate change
   Froede C.R., 2007, Journal of Coastal Research, V233, P807
   Froede CR, 2008, J COASTAL RES, V24, P110, DOI 10.2112/06-0782.1
   Froede CR, 2007, J COASTAL RES, V23, P1602, DOI 10.2112/07A-0019.1
   Froede CR, 2010, J COASTAL RES, V26, P699, DOI 10.2112/JCOASTRES-D-09-00028.1
   Froede CR, 2009, J COASTAL RES, V25, P793, DOI 10.2112/08-1176.1
   Froede CR, 2006, J COASTAL RES, V22, P371, DOI 10.2112/04-0174.1
   Froede CR, 2006, J COASTAL RES, V22, P561, DOI 10.2112/05-0438.1
   Gaul G.M., 2019, ALABAMA COAST UNLUCK
   Gillis J., 2012, NEW YORK TIMES  1119, P1
   Godschalk D., 2004, Breaking the disaster cycle: Future directions in natural hazard mitigation (Session 4, FEMA Training Series)
   Haasnoot M, 2012, CLIMATIC CHANGE, V115, P795, DOI 10.1007/s10584-012-0444-2
   Habete D, 2017, NAT HAZARDS REV, V18, DOI 10.1061/(ASCE)NH.1527-6996.0000262
   Hardin JD., 1976, Shoreline and bathymetric changes in the coastal area of Alabama
   Hutagalung S.S., 2020, INT J SCI TECHNOL RE, V9, P48
   Jones S.C., 2012, Comprehensive shoreline mapping, Baldwin and Mobile counties
   Juita E., 2020, INT J MANAG HUMAN, V4, P49
   King R.O., 2012, National flood insurance program: Background, challenges, and financial status, V40650
   King RawleO., 2005, FEDERAL FLOOD INSURA
   Lester C, 2022, J COASTAL RES, DOI 10.2112/JCOASTRES-D-22A-00010.1
   LIEBOWITZ SJ, 1995, J LAW ECON ORGAN, V11, P205
   Lin BB, 2017, COAST MANAGE, V45, P384, DOI 10.1080/08920753.2017.1349564
   McGee M., 2014, MORAL HAZARD NATL FL
   Miner M.D., 2008, METHODS ERROR ANAL B, V1
   Moore R., 2017, SEEKING HIGHER GROUN, P14
   Morton RA, 2008, J COASTAL RES, V24, P1587, DOI 10.2112/07-0953.1
   Naping H, 2019, IOP C SER EARTH ENV, V235, DOI 10.1088/1755-1315/235/1/012033
   National Oceanic and Atmospheric Administration, 2022, NAT DAT BUOY CTR
   National Research Council, 2012, Disaster Resilience: A National Imperative
   Okubo T, 2016, J CULT HERIT, V20, P715, DOI 10.1016/j.culher.2016.03.014
   ONeill J., 2013, DISASTER, V62, P18
   OTVOS EG, 1985, J COASTAL RES, V1, P267
   OTVOS EG, 1981, MAR GEOL, V43, P195, DOI 10.1016/0025-3227(81)90181-X
   Otvos EG, 2004, SEDIMENT GEOL, V169, P47, DOI 10.1016/j.sedgeo.2004.04.008
   OTVOS EG, 1970, GEOL SOC AM BULL, V81, P241, DOI 10.1130/0016-7606(1970)81[241:DAMOBI]2.0.CO;2
   Otvos EG, 2006, J COASTAL RES, V22, P1585, DOI 10.2112/06A-0013.1
   Parker D.W., 1979, HURRICANE FREDERIC P
   Putnam R. D., 2000, BOWLING ALONE COLLAP, DOI [10.1145/358916.361990, DOI 10.1145/358916.361990]
   Revell D, 2021, WATER-SUI, V13, DOI 10.3390/w13091324
   Rowell D, 2012, J RISK INSUR, V79, P1051, DOI 10.1111/j.1539-6975.2011.01448.x
   Sanchez T.A., 1994, 941 COLL ENG
   Sayre K., 2008, DAUPHIN ISLAND BERM
   Scawthorn C., 2006, Natural Hazards Review, V7, P60, DOI 10.1061/(ASCE)1527-6988(2006)7:2(60)
   Scawthorn C., 2006, NAT HAZARDS REV, V7, P60, DOI DOI 10.1061/(ASCE)1527-6988(2006)7:2(72)
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   Schneider P. J., 2006, Nat Hazards Rev, V7, P40, DOI [10.1061/(ASCE1527-6988(2006)7:2(40, DOI 10.1061/(ASCE1527-6988(2006)7:2(40, 10.1061/(ASCE)1527-6988(2006)7:2(40), DOI 10.1061/(ASCE)1527-6988(2006)7:2(40)]
   Seifert-Dahnn I, 2018, NAT HAZARD EARTH SYS, V18, P2409, DOI 10.5194/nhess-18-2409-2018
   Sheppard SRJ, 2011, FUTURES, V43, P400, DOI 10.1016/j.futures.2011.01.009
   Smith W.E., 1990, PROFILES ALABAMA GUL
   Starbuck K.T., 2016, THESIS NAVAL POSTGRA
   Swann L., 2018, MISSISSIPPI ALABAMA
   USACE USGS State of Alabama & NFWF, 2020, STAT AL NFWF
   VanDoren P.M., 2022, NATL FLOOD INSURANCE, P16, DOI [10.2139/ssrn.4061079, DOI 10.2139/SSRN.4061079]
   Werners SE, 2021, ENVIRON SCI POLICY, V116, P266, DOI 10.1016/j.envsci.2020.11.003
NR 83
TC 2
Z9 2
U1 1
U2 7
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0964-5691
EI 1873-524X
J9 OCEAN COAST MANAGE
JI Ocean Coastal Manage.
PD FEB 15
PY 2023
VL 233
AR 106451
DI 10.1016/j.ocecoaman.2022.106451
EA DEC 2022
PG 10
WC Oceanography; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Oceanography; Water Resources
GA 8A9IX
UT WOS:000916548000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Zacharias, L
   Christy, J
   Roopesh, BN
   Binu, VS
   Das, SK
   Sekar, K
AF Zacharias, Lithin
   Christy, Jayakumar
   Roopesh, B. N.
   Binu, V. S.
   Das, Sumit K.
   Sekar, K.
TI Development of an instrument on psychosocial adaptation for people
   living in a disaster-prone area
SO INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
LA English
DT Article
DE Content validity; Disaster-prone area; Psychosocial adaptation
   instrument; Disaster risk reduction
ID CLIMATE-CHANGE ADAPTATION; ITEM FIT INDEX; LOCAL KNOWLEDGE; SAMPLE-SIZE;
   IMPACT; PERFORMANCE; STRATEGIES; FARMERS; S-X-2; SCALE
AB Background: Adaptation is a process of adjusting to the current or expected climate change. The varied adverse outcomes enable people towards necessary adaptation. People living in disaster-prone areas go through a relatively higher frequency of emergencies and exigencies. Gradually people learn to cope with stress and over a while, they develop various strategies for adaptation. The ability to rapidly adapt to such changes helps people to better fit in the environment and prepare themselves for future emergencies. There is no instrument available to measure psychosocial adaptation objectively. The current study reports on the development and validation of psychosocial adaptation instrument.
   Methods: Cross-sectional study design was adopted for the study. The study population consisted of people living in high-intensity hazard zones for cyclones, earthquakes, and floods in the Cuttack city of Odisha in India. The development of psychosocial adaptation instrument consisted of two phases. Content validity index, Kappa statistic, and intraclass correlation coefficient (ICC) were measured. Adopting the multistage sampling method a total of 400 participants were selected using the KISH method and were interviewed. Exploratory factor analysis was attempted to assess the factor structure. Further, the performance of items and total scale were analyzed using the item response theory approach.
   Results: The psychosocial adaptation instrument showed excellent validity of individual items (I-CVI range: 0.75 to 1.00) and good Kappa (Kappa range: 0.71 to 1.00). The Kuder-Richardson coefficient for the 50 items was (KR20 = 0.851) suggesting that the items have good internal consistency. The test-retest reliability ICC estimate of single measures was 0.916 (95% CI: 0.796, 0.959). Three items were removed as the discrimination parameters were found to be less than one in the item response theory analysis.
   Conclusion: The developed instrument is valid and has acceptable test-retest reliability. This instrument could pave a new way of quantifying the psychosocial adaption strategies that are widely used by people living in a disaster-prone area.
C1 [Zacharias, Lithin] Natl Inst Mental Hlth & Neurosci, Dept Psychiat Social Work, Bengaluru, India.
   [Christy, Jayakumar] Natl Inst Mental Hlth & Neurosci, Dept Psychiat Social Work, Ctr Psychosocial Support Disaster Management, Bengaluru, India.
   [Roopesh, B. N.] Natl Inst Mental Hlth & Neurosci, Dept Clin Psychol, Bengaluru, India.
   [Binu, V. S.; Das, Sumit K.] Natl Inst Mental Hlth & Neurosci, Dept Biostat, Bengaluru, India.
   [Sekar, K.] Natl Inst Mental Hlth & Neurosci, Ctr Psychosocial Support Disaster Management, Bengaluru 560029, India.
C3 National Institute of Mental Health & Neurosciences - India; National
   Institute of Mental Health & Neurosciences - India; National Institute
   of Mental Health & Neurosciences - India; National Institute of Mental
   Health & Neurosciences - India; National Institute of Mental Health &
   Neurosciences - India
RP Sekar, K (corresponding author), Natl Inst Mental Hlth & Neurosci, Ctr Psychosocial Support Disaster Management, Bengaluru 560029, India.
EM lithinzacharias@gmail.com; jaipsy@gmail.com; bn.roopesh@gmail.com;
   binuvstvm@gmail.com; sumitdas382@gmail.com; sekarkasi@gmail.com
RI V S, BINU/H-5723-2019; Das, Sumit/AAE-1920-2020
OI DAS, SUMIT KUMAR/0000-0001-6952-3676; Zacharias, Dr.
   Lithin/0000-0001-5209-3200
NR 0
TC 7
Z9 7
U1 0
U2 7
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-4209
J9 INT J DISAST RISK RE
JI Int. J. Disaster Risk Reduct.
PD JAN
PY 2022
VL 68
AR 102716
DI 10.1016/j.ijdrr.2021.102716
EA JAN 2022
PG 10
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA ZI9QD
UT WOS:000761945700004
DA 2025-01-10
ER

PT J
AU Maghrabi, A
   Alyamani, A
   Addas, A
AF Maghrabi, Ahmad
   Alyamani, Abdulelah
   Addas, Abdullah
TI Exploring Pattern of Green Spaces (GSs) and Their Impact on Climatic
   Change Mitigation and Adaptation Strategies: Evidence from a Saudi
   Arabian City
SO FORESTS
LA English
DT Article
DE green spaces; climate change; well-being; urban sustainability;
   vulnerability
ID URBAN HEAT ISLANDS; LAND-SURFACE TEMPERATURE; ECOSYSTEM SERVICES;
   PHYSICAL-ACTIVITY; SPATIOTEMPORAL PATTERNS; RAPID URBANIZATION;
   INFRASTRUCTURE; CITIES; PERCEPTIONS; GARDENS
AB Green spaces (GSs) are significant, nature-based solutions to climate change and have immense potential to reduce vulnerability to heat waves while enhancing the resilience of urban areas in the light of climate change. However, in the Saudi context, the availability of GSs across cities and their perceived role in climate change mitigations and adaptation strategies remain unexplored. This study aimed to examine the per capita availability of GSs in the Jeddah megacity in Saudi Arabia, and their role in climate change mitigation and adaptation strategies. This study assessed the per capita availability of GS in Jeddah city using GIS techniques, and a questionnaire survey (online and an onsite) was conducted to assess the GSs users' perception of the role of GSs on climate change mitigation and adaptation strategies. Non-parametric tests were also used to find differences in roles based on socio-demographic attributes. The findings of the study revealed that: (i) the per capita availability of GS in Jeddah is relatively low in comparison to international organization recommendations (such as World Health Organization and European Union). As per the survey result, it was reported that GSs play crucial role for climate change mitigation such as temperature regulation, reduction in heat stress, enhancement outdoor thermal comfort, and the maintenance of air quality. More than 85% of the total respondents agreed with the very high importance of GSs for climate change mitigation. More than 80% of respondents in the city highly agreed with climate change adaptation strategies such as the enhancement of accessibility to GSs, ecosystem-based protection of GSs, and the improvement of per capita availability of GSs. The findings of the study will be very helpful to planners and policymakers in implementing nature-based solutions to reduce vulnerability to climate change in Jeddah city, and particularly other cities in a desert environment.
C1 [Maghrabi, Ahmad; Alyamani, Abdulelah; Addas, Abdullah] King Abdulaziz Univ, Fac Architecture & Planning, Landscape Architecture Dept, POB 80210, Jeddah 21589, Saudi Arabia.
C3 King Abdulaziz University
RP Maghrabi, A (corresponding author), King Abdulaziz Univ, Fac Architecture & Planning, Landscape Architecture Dept, POB 80210, Jeddah 21589, Saudi Arabia.
EM aamaghrabi@kau.edu.sa; aalyamani0060@stu.kau.edu.sa; aaddas@kau.edu.sa
RI Addas, Abdullah/U-7798-2018
OI Addas, Abdullah/0000-0003-3674-758X
FU Science and Technology Unit-King Abdulaziz University-Kingdom of Saudi
   Arabia [UE-41-116]
FX This project was funded by Science and Technology Unit-King Abdulaziz
   UniversityKingdom of Saudi Arabia-award number UE-41-116.
CR Abastante F, 2020, GREEN ENERGY TECHNOL, P486
   Abubakar IR, 2020, ENVIRON DEV SUSTAIN, V22, P5129, DOI 10.1007/s10668-019-00417-1
   Abubakar IR, 2016, ADV ELECT GOV DIVIDE, P42, DOI 10.4018/978-1-5225-0187-9.ch003
   Addas A., 2018, EMIR J ENG RES, V24
   Addas A., 2020, Current Urban Studies, V8, P184, DOI DOI 10.4236/CUS.2020.82010
   Addas A, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17165970
   Addas A, 2020, SAGE OPEN, V10, DOI 10.1177/2158244020920608
   Aguado M, 2018, ECOSYST SERV, V34, P1, DOI 10.1016/j.ecoser.2018.09.002
   AHERN J, 1995, LANDSCAPE URBAN PLAN, V33, P131, DOI 10.1016/0169-2046(95)02039-V
   Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   Almazroui M, 2012, INT J CLIMATOL, V32, P953, DOI 10.1002/joc.3446
   Alqurashi AF, 2019, GEOCARTO INT, V34, P78, DOI 10.1080/10106049.2017.1367423
   Alqurashi AF, 2016, HABITAT INT, V58, P75, DOI 10.1016/j.habitatint.2016.10.001
   Baró F, 2014, AMBIO, V43, P466, DOI 10.1007/s13280-014-0507-x
   Belcáková I, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10090552
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Brook I, 2010, ETHICS POLICY ENV, V13, P295, DOI 10.1080/1366879X.2010.522046
   Byrne J, 2009, AUST PLAN, V46, P35, DOI 10.1080/07293682.2009.10753420
   Byrne JA, 2015, LANDSCAPE URBAN PLAN, V138, P132, DOI 10.1016/j.landurbplan.2015.02.013
   Cameron RWF, 2012, URBAN FOR URBAN GREE, V11, P129, DOI 10.1016/j.ufug.2012.01.002
   Carvalho D, 2017, URBAN CLIM, V19, P1, DOI 10.1016/j.uclim.2016.11.005
   Caspersen OH, 2010, URBAN FOR URBAN GREE, V9, P101, DOI 10.1016/j.ufug.2009.06.007
   Das M, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100591
   Davies ZG, 2011, J APPL ECOL, V48, P1125, DOI 10.1111/j.1365-2664.2011.02021.x
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   Detommaso M, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063138
   Duan JY, 2018, ENVIRON MANAGE, V62, P500, DOI 10.1007/s00267-018-1068-8
   Eckstein David., 2018, GLOBAL CLIMATE RISK
   Egorov A., 2016, URBAN GREEN SPACES H
   Enssle F, 2020, ENVIRON SCI POLICY, V109, P36, DOI 10.1016/j.envsci.2020.04.008
   Faehnle M, 2015, GEOJOURNAL, V80, P411, DOI 10.1007/s10708-014-9560-z
   Fan PL, 2017, LANDSCAPE URBAN PLAN, V165, P177, DOI 10.1016/j.landurbplan.2016.11.007
   Farrugia Simon, 2013, International Journal of Biodiversity Science Ecosystem Services & Management, V9, P136, DOI 10.1080/21513732.2013.782342
   Gilbert H, 2016, ENERG BUILDINGS, V114, P20, DOI 10.1016/j.enbuild.2015.06.023
   Giles-Corti B, 2005, AM J PREV MED, V28, P169, DOI 10.1016/j.amepre.2004.10.018
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Heinelt Hubert., 2015, Wissen und Entscheiden: Lokale Strategien gegen den Klimawandel in Frankfurt am Main, Munchen und Stuttgart
   Hoehner CM, 2005, AM J PREV MED, V28, P105, DOI 10.1016/j.amepre.2004.10.023
   Jaganmohan M, 2016, J ENVIRON QUAL, V45, P134, DOI 10.2134/jeq2015.01.0062
   Kabisch N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08373-210239
   Kithiia J, 2011, ENVIRON URBAN, V23, P251, DOI 10.1177/0956247810396054
   Laukkonen J, 2009, HABITAT INT, V33, P287, DOI 10.1016/j.habitatint.2008.10.003
   Leal W, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13020753
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   Ma LB, 2020, SUSTAIN CITIES SOC, V54, DOI 10.1016/j.scs.2019.101877
   Martins B, 2018, URBAN FOR URBAN GREE, V34, P134, DOI 10.1016/j.ufug.2018.06.014
   Mathey J, 2011, LOCAL SUSTAIN, V1, P479, DOI 10.1007/978-94-007-0785-6_47
   Mathieson K, 1991, INFORM SYST RES, V2, P173, DOI 10.1287/isre.2.3.173
   Matthews T, 2015, LANDSCAPE URBAN PLAN, V138, P155, DOI 10.1016/j.landurbplan.2015.02.010
   McDonald R., 2016, PLANTING HLTH AIR GL
   McGinn AP, 2007, HEALTH PLACE, V13, P588, DOI 10.1016/j.healthplace.2006.07.002
   Montazeri H, 2017, LANDSCAPE URBAN PLAN, V159, P85, DOI 10.1016/j.landurbplan.2016.10.001
   Mukherjee N, 2019, CHINESE GEOGR SCI, V29, P417, DOI 10.1007/s11769-019-1042-2
   Nasar JL, 2008, AM J PREV MED, V34, P357, DOI 10.1016/j.amepre.2008.01.013
   Naumann S., 2010, Final Report to the European Commission, DG Environment, Contract
   Ndubisi F.O, 2014, ECOLOGICAL DESIGN PL, V3rd ed., P632
   Niu L, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12020478
   O'Malley C, 2015, SUSTAIN CITIES SOC, V19, P222, DOI 10.1016/j.scs.2015.05.009
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Paul A, 2020, URBAN FOR URBAN GREE, V55, DOI 10.1016/j.ufug.2020.126825
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Pitman SD, 2015, T ROY SOC SOUTH AUST, V139, P97, DOI 10.1080/03721426.2015.1035219
   Poortinga W, 2006, SOC SCI MED, V63, P2835, DOI 10.1016/j.socscimed.2006.07.018
   Raymond CM, 2017, ENVIRON SCI POLICY, V77, P15, DOI 10.1016/j.envsci.2017.07.008
   Russo A, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15102180
   Santamouris M, 2015, SCI TOTAL ENVIRON, V512, P582, DOI 10.1016/j.scitotenv.2015.01.060
   Scholes RJ, 2013, CURR OPIN ENV SUST, V5, P16, DOI 10.1016/j.cosust.2013.01.004
   Schwarz N, 2012, ECOL INDIC, V18, P693, DOI 10.1016/j.ecolind.2012.01.001
   Shen YA, 2017, URBAN FOR URBAN GREE, V27, P59, DOI 10.1016/j.ufug.2017.06.018
   Shiflett SA, 2017, SCI TOTAL ENVIRON, V579, P495, DOI 10.1016/j.scitotenv.2016.11.069
   Shih WY, 2017, HABITAT INT, V60, P69, DOI 10.1016/j.habitatint.2016.12.006
   Sugiyama T, 2009, HEALTH PLACE, V15, P1058, DOI 10.1016/j.healthplace.2009.05.001
   Sun RH, 2017, ECOSYST SERV, V23, P38, DOI 10.1016/j.ecoser.2016.11.011
   Tarawneh QY, 2018, CLIMATE, V6, DOI 10.3390/cli6010008
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wai ATP, 2018, SUSTAIN CITIES SOC, V37, P323, DOI 10.1016/j.scs.2017.10.038
   Ward K, 2016, SCI TOTAL ENVIRON, V569, P527, DOI 10.1016/j.scitotenv.2016.06.119
   Wei JX, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10020327
   Yang Jun, 2005, Urban Forestry & Urban Greening, V3, P65, DOI 10.1016/j.ufug.2004.09.001
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Yu ZW, 2018, URBAN FOR URBAN GREE, V29, P113, DOI 10.1016/j.ufug.2017.11.008
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Yuen B, 2005, LANDSCAPE URBAN PLAN, V73, P263, DOI 10.1016/j.landurbplan.2004.08.001
   Zhao L, 2014, NATURE, V511, P216, DOI 10.1038/nature13462
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
NR 86
TC 9
Z9 9
U1 4
U2 55
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1999-4907
J9 FORESTS
JI Forests
PD MAY
PY 2021
VL 12
IS 5
AR 629
DI 10.3390/f12050629
PG 16
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Forestry
GA SH1VT
UT WOS:000653924000001
OA gold
DA 2025-01-10
ER

PT J
AU Cradock-Henry, NA
AF Cradock-Henry, Nicholas A.
TI Linking the social, economic, and agroecological: a resilience framework
   for dairy farming
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE adaptation; agriculture; complex adaptive systems; farm systems;
   resilience assessment; social-ecological systems; vulnerability
ID CLIMATE-CHANGE ADAPTATION; AOTEAROA-NEW-ZEALAND; COMMUNITY RESILIENCE;
   COLLECTIVE ACTION; MILK-PRODUCTION; VULNERABILITY; INSIGHTS;
   SUSTAINABILITY; STRATEGIES; AGRICULTURE
AB Agriculture is a major economic driver in Aotearoa-New Zealand (New Zealand), led by export earnings from dairy farming. Dairying is uniquely exposed to climatic- and nonclimatic socioeconomic stressors, which have their greatest effects on production and yield. The growing need to consider these and other changes is accelerating efforts aimed at ensuring greater resilience, adaptability, and flexibility within the industry. To gain insight into these dynamics at the farm-level, a resilience-based assessment framework was piloted with three different types of dairy farming systems, following extensive drought on the east coast of the North Island. Using a participatory and bottom-up approach, the framework was used to qualitatively explore the potential significance of varying social, economic, and agroecological attributes between high-input, low-input, and organic systems, and their implications for resilience. The "lock in trap" of highly intensive systems, although profitable in the near term, may be less resilient to climate shocks because these are likely to occur in conjunction with changing market and financial risks. Low-input systems are less dependent, in particular, on fossil fuels and are associated with higher levels of farmer satisfaction and well-being. Organic farming provides ecological benefits, and the financial premium paid to farmers may act as a short-term buffer. The framework provides insight into the current context at the farm level and can draw out individual perspectives on where to target interventions and build resilience. Results demonstrate the potential of in-depth qualitative assessments of resilience, which can usefully complement quantitative metrics. The framework can be used as the basis for further empirical assessment and inform the design of similar approaches for cross-sector comparative analysis, large-N surveys, or modelling. Furthermore, the preliminary characterization of resilient farm-systems has the potential to contribute to broader sustainability frameworks for agriculture and can inform strategic adaptation planning in the face of climate change.
C1 [Cradock-Henry, Nicholas A.] Manaaki Whenua Landcare Res, Landscape Policy & Governance, Lincoln, New Zealand.
C3 Landcare Research - New Zealand
RP Cradock-Henry, NA (corresponding author), Manaaki Whenua Landcare Res, Landscape Policy & Governance, Lincoln, New Zealand.
OI Cradock-Henry, Nicholas/0000-0002-4409-9976
FU Ministry for Primary Industries' Sustainable Land Management and Climate
   Change (SLMACC) fund and Resilience to Nature's Challenges National
   Science Challenge
FX This work was supported through the Ministry for Primary Industries'
   Sustainable Land Management and Climate Change (SLMACC) fund and
   Resilience to Nature's Challenges National Science Challenge. Special
   thanks to Claire Mortimer (MBIE) for assisting with the original
   interviews and analysis. We gratefully acknowledge the support of
   interviewees and workshop participants who generously contributed their
   time and insights. Thank you also to the anonymous reviewers whose
   feedback has helped improve the manuscript.
CR Adger WN, 2011, WIRES CLIM CHANGE, V2, P757, DOI 10.1002/wcc.133
   Adger WN, 2003, ECON GEOGR, V79, P387
   Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Aldrich DP, 2015, AM BEHAV SCI, V59, P254, DOI 10.1177/0002764214550299
   Aldunce P, 2015, GLOBAL ENVIRON CHANG, V30, P1, DOI 10.1016/j.gloenvcha.2014.10.010
   Alessa L, 2008, ENVIRON MANAGE, V42, P523, DOI 10.1007/s00267-008-9152-0
   Alexander DE, 2013, NAT HAZARD EARTH SYS, V13, P2707, DOI 10.5194/nhess-13-2707-2013
   [Anonymous], 2009, FIELD GUIDE CROPPING
   [Anonymous], 2006, DISASTER RESILIENCE
   [Anonymous], 2011, 201113 MAF
   Arnold CA, 2017, ECOL SOC, V22, DOI 10.5751/ES-09734-220414
   Arnott JC, 2016, ENVIRON SCI POLICY, V66, P383, DOI 10.1016/j.envsci.2016.06.017
   BANDURA A, 1982, AM PSYCHOL, V37, P122, DOI 10.1037/0003-066X.37.2.122
   Barnett Jon, 2005, Environment Development and Sustainability, V7, P271, DOI 10.1007/s10668-005-7316-0
   Baskaran R, 2009, NEW ZEAL J AGR RES, V52, P377, DOI 10.1080/00288230909510520
   Basset-Mens C, 2009, ECOL ECON, V68, P1615, DOI 10.1016/j.ecolecon.2007.11.017
   Beilin R, 2013, ECOL SOC, V18, DOI 10.5751/ES-05360-180230
   Bélanger V, 2012, ECOL INDIC, V23, P421, DOI 10.1016/j.ecolind.2012.04.027
   Benatar JR, 2011, EUR J CARDIOV PREV R, V18, P615, DOI 10.1177/1741826710389415
   Bennett EM, 2005, ECOSYSTEMS, V8, P945, DOI 10.1007/s10021-005-0141-3
   Berardi G, 2011, HUM ECOL REV, V18, P115
   Berke P, 2015, J AM PLANN ASSOC, V81, P287, DOI 10.1080/01944363.2015.1093954
   Berkes F, 2002, CONSERV ECOL, V5
   Berkes F, 2006, HUM ECOL, V34, P479, DOI 10.1007/s10745-006-9008-2
   Beukes PC, 2019, AGR SYST, V174, P95, DOI 10.1016/j.agsy.2019.05.002
   Birkmann J., 2007, Environmental Hazards, V7, P20, DOI 10.1016/j.envhaz.2007.04.002
   Bronen R, 2015, ECOL SOC, V20, DOI 10.5751/ES-07801-200336
   Brown K, 2011, ANNU REV ENV RESOUR, V36, P321, DOI 10.1146/annurev-environ-052610-092905
   Buckle RA, 2007, ECON MODEL, V24, P990, DOI 10.1016/j.econmod.2007.04.003
   Buelow F, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041133
   Burton RJF, 2014, J RURAL STUD, V33, P82, DOI 10.1016/j.jrurstud.2013.11.002
   Cabell JF, 2012, ECOL SOC, V17, DOI 10.5751/ES-04666-170118
   Campos M, 2014, LAND USE POLICY, V38, P533, DOI 10.1016/j.landusepol.2013.12.017
   Carpenter S, 2001, ECOSYSTEMS, V4, P765, DOI 10.1007/s10021-001-0045-9
   Carpenter SR, 2005, ECOSYSTEMS, V8, P941, DOI 10.1007/s10021-005-0170-y
   Carpenter SR, 2012, SUSTAINABILITY-BASEL, V4, P3248, DOI 10.3390/su4123248
   Choko OP, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11113100
   Cinner JE, 2019, ONE EARTH, V1, P51, DOI 10.1016/j.oneear.2019.08.003
   Clark DA, 2007, NEW ZEAL J AGR RES, V50, P203, DOI 10.1080/00288230709510291
   Collins M, 2010, NAT GEOSCI, V3, P391, DOI 10.1038/NGEO868
   Cooper MH, 2014, J RURAL STUD, V36, P391, DOI 10.1016/j.jrurstud.2014.06.008
   Cradock-Henry NA, 2020, ENVIRON SCI POLICY, V107, P66, DOI 10.1016/j.envsci.2020.02.020
   Cradock-Henry NA, 2019, ECOL SOC, V24, DOI 10.5751/ES-11075-240309
   Cradock-Henry NA, 2019, CLIM RISK MANAG, V25, DOI 10.1016/j.crm.2019.100190
   Cradock-Henry NA, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab370c
   Cradock-Henry NA, 2019, ENVIRON SCI POLICY, V94, P182, DOI 10.1016/j.envsci.2019.01.015
   Cradock-Henry NA, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061952
   Cradock-Henry NA, 2017, REG ENVIRON CHANGE, V17, P245, DOI 10.1007/s10113-016-1000-9
   Crane TA, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.464
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   DairyNZ, 2021, DAIRYNZ
   Dakos V, 2015, PHILOS T R SOC B, V370, DOI 10.1098/rstb.2013.0263
   DANTAS A., 2006, Journal of Contingencies Crisis Management, V14, P38, DOI DOI 10.1111/J.1468-5973.2006.00479.X
   Darnhofer I, 2014, EUR REV AGRIC ECON, V41, P461, DOI 10.1093/erae/jbu012
   Darnhofer I, 2010, AGRON SUSTAIN DEV, V30, P545, DOI 10.1051/agro/2009053
   Darnhofer I, 2010, INT J AGR SUSTAIN, V8, P186, DOI 10.3763/ijas.2010.0480
   Darnhofer I, 2010, ENVIRON POLICY GOV, V20, P212, DOI 10.1002/eet.547
   De Herde V, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11164405
   Deppisch S, 2013, NAT HAZARDS, V67, P117, DOI 10.1007/s11069-011-9821-9
   Dias F. N., 2008, Proceedings of the New Zealand Society of Animal Production, V68, P111
   Diserens F, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10124435
   Dowd AM, 2014, NAT CLIM CHANGE, V4, P558, DOI [10.1038/NCLIMATE2275, 10.1038/nclimate2275]
   Duncan R, 2017, CASE STUD ENVIRON, V1, DOI 10.1525/cse.2017.sc.433549
   Ebi KL, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15091943
   England JR, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135345
   Faulkner L, 2018, ECOL SOC, V23, DOI 10.5751/ES-09784-230124
   Fazey I, 2007, FRONT ECOL ENVIRON, V5, P375, DOI 10.1890/1540-9295(2007)5[375:ACALTL]2.0.CO;2
   Fekete A, 2014, INT J DISAST RISK SC, V5, P3, DOI 10.1007/s13753-014-0008-3
   Fielke SJ, 2018, SUSTAIN SCI, V13, P255, DOI 10.1007/s11625-017-0432-6
   Fletcher C. S., 2006, P 50 ANN M ISSS 2006
   Folke C, 2016, ECOL SOC, V21, DOI 10.5751/ES-08748-210341
   Folke C, 2010, ECOL SOC, V15, DOI 10.5751/es-03610-150420
   Foote KJ, 2015, ENVIRON MANAGE, V56, P709, DOI 10.1007/s00267-015-0517-x
   Fowler A, 2004, INT J CLIMATOL, V24, P1947, DOI 10.1002/joc.1100
   Gadgil M., 2003, Navigating Social-Ecological Systems: Building Resilience for Complexity and Change
   George DA, 2019, AUSTRALAS J ENV MAN, V26, P6, DOI 10.1080/14486563.2018.1506948
   Gillmore D., 2010, RESERVE BANK NZ B, V73, P35
   Gray S, 2010, NEW ZEAL GEOGR, V66, P1, DOI 10.1111/j.1745-7939.2010.01173.x
   Greig B, 2019, NEW ZEAL GEOGR, V75, P21, DOI 10.1111/nzg.12207
   Griffiths F, 2011, UPDATED CLIMATE CHAN
   Guzmán GI, 2013, AGROECOL SUST FOOD, V37, P127, DOI 10.1080/10440046.2012.718997
   Hallegatte S, 2019, CLIM RISK MANAG, V23, P1, DOI 10.1016/j.crm.2018.12.001
   Hammond B, 2013, AGROECOL SUST FOOD, V37, P316, DOI 10.1080/10440046.2012.746251
   Harrington L, 2014, B AM METEOROL SOC, V95, pS45
   Harrington LJ, 2016, J GEOPHYS RES-ATMOS, V121, P12766, DOI 10.1002/2016JD025602
   Harrison MT, 2017, AGR SYST, V155, P19, DOI 10.1016/j.agsy.2017.04.003
   Hewitt K, 2013, NAT HAZARDS, V66, P3, DOI 10.1007/s11069-012-0205-6
   Jackson N., 2013, N. Z. Popul. Rev., V39, P77
   James T, 2019, SOC NATUR RESOUR, V32, P133, DOI 10.1080/08941920.2018.1506069
   Jay M, 2007, FOOD POLICY, V32, P266, DOI 10.1016/j.foodpol.2006.09.002
   Jones RN, 2011, WIRES CLIM CHANGE, V2, P296, DOI 10.1002/wcc.97
   Joy M., 2015, POLLUTED INHERITANCE, DOI [10.7810/9780908321612_2, DOI 10.7810/9780908321612_2]
   Kalaugher E, 2017, AGR SYST, V153, P53, DOI 10.1016/j.agsy.2017.01.008
   Kalaugher E, 2013, ENVIRON MODELL SOFTW, V39, P176, DOI 10.1016/j.envsoft.2012.03.018
   Kandulu JM, 2012, ECOL ECON, V79, P105, DOI 10.1016/j.ecolecon.2012.04.025
   Kenny G, 2011, CLIMATIC CHANGE, V106, P441, DOI 10.1007/s10584-010-9948-9
   Kirk N, 2017, LAND USE POLICY, V65, P53, DOI 10.1016/j.landusepol.2017.03.034
   Knook J, 2020, ENVIRON MANAGE, V65, P243, DOI 10.1007/s00267-019-01242-y
   Kremen C, 2012, ECOL SOC, V17, DOI 10.5751/ES-05103-170444
   Kummer S., 2012, Sustainable Agriculture Research, V1, P308
   Lee JM, 2013, GRASS FORAGE SCI, V68, P485, DOI 10.1111/gfs.12039
   Leith P, 2012, SOC NATUR RESOUR, V25, P775, DOI 10.1080/08941920.2011.637548
   Li CY, 2013, ENVIRON MANAGE, V52, P894, DOI 10.1007/s00267-013-0139-0
   Liu JG, 2007, SCIENCE, V317, P1513, DOI 10.1126/science.1144004
   Liu WT, 2014, ECOL SOC, V19, DOI 10.5751/ES-06843-190421
   Livestock Improvement Corporation Limited (LIC) DairyNZ Limited (DNZ)., 2019, NZ DAIR STAT 2018 20
   Macdonald KA, 2011, J DAIRY SCI, V94, P2581, DOI 10.3168/jds.2010-3688
   Malone EL, 2011, WIRES CLIM CHANGE, V2, P462, DOI 10.1002/wcc.116
   Mapfumo P, 2013, ENVIRON DEV, V5, P6, DOI 10.1016/j.envdev.2012.11.001
   Marshall NA, 2007, ECOL SOC, V12, DOI 10.5751/es-01940-120101
   Meeske R., 2014, 6th Australasian Dairy Science Symposium Proceedings, November 19-21, 2014, Hamilton, New Zealand, P405
   Meinke H, 2009, CURR OPIN ENV SUST, V1, P69, DOI 10.1016/j.cosust.2009.07.007
   Miller F, 2010, ECOL SOC, V15
   Ministry for the Environment, 2018, CLIM CHANG PROJ NZ A
   Morad M., 1999, BRIT REV NZ STUDIES, V12, P45
   MPI, 2015, IMP PALM KERN EXP IN
   Nayak PK, 2014, REG ENVIRON CHANGE, V14, P2067, DOI 10.1007/s10113-012-0369-3
   Naylor A, 2020, ONE EARTH, V2, P444, DOI 10.1016/j.oneear.2020.04.011
   Nelson R, 2010, ENVIRON SCI POLICY, V13, P8, DOI 10.1016/j.envsci.2009.09.006
   Nelson R, 2010, ENVIRON SCI POLICY, V13, P18, DOI 10.1016/j.envsci.2009.09.007
   New Zealand Ministry of Primary Industries, 2020, DEEM VAL GUID
   Nicholas KA, 2012, GLOBAL ENVIRON CHANG, V22, P483, DOI 10.1016/j.gloenvcha.2012.01.001
   Niles MT, 2016, GLOBAL ENVIRON CHANG, V39, P133, DOI 10.1016/j.gloenvcha.2016.05.002
   Norris FH, 2008, AM J COMMUN PSYCHOL, V41, P127, DOI 10.1007/s10464-007-9156-6
   Olsson L, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1400217
   Parsons M, 2016, GLOBAL ENVIRON CHANG, V38, P82, DOI 10.1016/j.gloenvcha.2016.01.010
   Paton D., 2013, IDRiM Journal, V3, P1, DOI DOI 10.5595/IDRIM.2013.0050
   Pomeroy A, 2015, NEW ZEAL GEOGR, V71, P146, DOI 10.1111/nzg.12106
   Preston BL, 2011, SUSTAIN SCI, V6, P177, DOI 10.1007/s11625-011-0129-1
   Pullar W. A., 1985, 86 DEP SCI IND RES
   Reisinger A, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1371
   Revell P, 2019, REG ENVIRON CHANGE, V19, P967, DOI 10.1007/s10113-018-1390-y
   Rickards L, 2012, CROP PASTURE SCI, V63, P240, DOI 10.1071/CP11172
   Rodima-Taylor D, 2012, APPL GEOGR, V33, P128, DOI 10.1016/j.apgeog.2011.10.005
   Ross H, 2014, SOC NATUR RESOUR, V27, P787, DOI 10.1080/08941920.2014.905668
   Rowarth JS, 2013, ECOSYSTEM SERVICES IN NEW ZEALAND: CONDITIONS AND TRENDS, P85
   Salinger MJ, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab012a
   Schroter D., 2005, Mitigation and Adaptation Strategies for Global Change, V10, P573, DOI 10.1007/s11027-005-6135-9
   Shadbolt NM, 2016, INT FOOD AGRIBUS MAN, V19, P33
   Siegrist M, 2000, RISK ANAL, V20, P713, DOI 10.1111/0272-4332.205064
   Simmie J, 2010, CAMB J REG ECON SOC, V3, P27, DOI 10.1093/cjres/rsp029
   Sinclair K, 2014, AGR HUM VALUES, V31, P371, DOI 10.1007/s10460-014-9488-4
   Skinner M.W., 2004, MITIG ADAPT STRAT GL, V7, P85
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smith W., 2019, HEARTLAND STRONG RUR, P46
   Smith W, 2011, DISASTERS, V35, P540, DOI 10.1111/j.1467-7717.2011.01228.x
   Spector S, 2019, REG ENVIRON CHANGE, V19, P543, DOI 10.1007/s10113-018-1418-3
   Stock P, 2013, INT J SOCIOL AGR FOO, V21, P7, DOI [DOI 10.48416/IJSAF.V21I1.152, 10.48416/ijsaf.v21i1.152]
   STOCKDALE CR, 1995, AUST J EXP AGR, V35, P19, DOI 10.1071/EA9950019
   Tanner T, 2015, NAT CLIM CHANGE, V5, P23, DOI 10.1038/NCLIMATE2431
   Turner BL, 2016, RESOURCES-BASEL, V5, DOI 10.3390/resources5040040
   van Apeldoorn DF, 2013, AGR ECOSYST ENVIRON, V172, P16, DOI 10.1016/j.agee.2013.04.002
   van Wyngaard JDV, 2017, S AFR J ANIM SCI, V47, P219, DOI 10.4314/sajas.v47i2.14
   Verkerk G, 2003, THERIOGENOLOGY, V59, P553, DOI 10.1016/S0093-691X(02)01239-6
   Walker B, 2004, ECOL SOC, V9
   Walker B., 2012, Resilience Practice: Building Capacity to Absorb Disturbance and Maintain Function, DOI [10.5822/978-1-61091-231-0, DOI 10.5822/978-1-61091-231-0]
   Walker BH, 2009, ECOL SOC, V14
   Yletyinen J, 2019, BIOSCIENCE, V69, P335, DOI 10.1093/biosci/biz031
NR 158
TC 19
Z9 21
U1 1
U2 42
PU RESILIENCE ALLIANCE
PI WOLFVILLE
PA ACADIA UNIV, BIOLOGY DEPT, WOLFVILLE, NS B0P 1X0, CANADA
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PD MAR
PY 2021
VL 26
IS 1
AR 3
DI 10.5751/ES-12122-260103
PG 19
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA RK4KM
UT WOS:000638266300012
OA gold
DA 2025-01-10
ER

PT J
AU Woodward, KD
   Pricope, NG
   Stevens, FR
   Gaughan, AE
   Kolarik, NE
   Drake, MD
   Salerno, J
   Cassidy, L
   Hartter, J
   Bailey, KM
   Luwaya, HM
AF Woodward, Kyle D.
   Pricope, Narcisa G.
   Stevens, Forrest R.
   Gaughan, Andrea E.
   Kolarik, Nicholas E.
   Drake, Michael D.
   Salerno, Jonathan
   Cassidy, Lin
   Hartter, Joel
   Bailey, Karen M.
   Luwaya, Henry Maseka
TI Modeling Community-Scale Natural Resource Use in a Transboundary
   Southern African Landscape: Integrating Remote Sensing and Participatory
   Mapping
SO REMOTE SENSING
LA English
DT Article
DE remote sensing; participatory mapping; NTFP; grazing; random forest;
   natural resources; drylands; savanna woodlands
ID TIMBER FOREST PRODUCTS; LAND-COVER CLASSIFICATION; MACHINE LEARNING
   ALGORITHMS; TREE SPECIES CLASSIFICATION; CLIMATE-CHANGE ADAPTATION;
   SUB-SAHARAN AFRICA; WOODY BIOMASS; RURAL LIVELIHOODS; PRECIPITATION
   VARIABILITY; ECOLOGICAL KNOWLEDGE
AB Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas.
C1 [Woodward, Kyle D.; Pricope, Narcisa G.] Univ N Carolina, Dept Earth & Ocean Sci, 601 S Coll Rd, Wilmington, NC 28403 USA.
   [Stevens, Forrest R.; Gaughan, Andrea E.; Kolarik, Nicholas E.] Univ Louisville, Dept Geog & Geosci, Lutz Hall, Louisville, KY 40292 USA.
   [Drake, Michael D.; Hartter, Joel; Bailey, Karen M.] Univ Colorado, Environm Studies Program, Sustainabil Energy & Environm Commun, 4001 Discovery Dr, Boulder, CO 80303 USA.
   [Salerno, Jonathan] Colorado State Univ, Grad Degree Program Ecol, Dept Human Dimens Nat Resources, Campus Box 1480, Ft Collins, CO 80523 USA.
   [Cassidy, Lin] Univ Botswana, Okavango Res Inst, P Bag 285, Maun, Botswana.
   [Luwaya, Henry Maseka] Dept Natl Pk & Wildlife, Private Bag 1,Kafue Rd, Chilanga, Zambia.
C3 University of North Carolina; University of North Carolina Wilmington;
   University of Louisville; University of Colorado System; University of
   Colorado Boulder; Colorado State University; University of Botswana
RP Woodward, KD (corresponding author), Univ N Carolina, Dept Earth & Ocean Sci, 601 S Coll Rd, Wilmington, NC 28403 USA.
EM kdwoody11@gmail.com; pricopen@uncw.edu; forrest.stevens@louisville.edu;
   ae.gaughan@louisville.edu; nicholaskolarik@u.boisestate.edu;
   Michael.Drake-1@colorado.edu; jonathan.salerno@colostate.edu;
   lcassidy@ub.ac.bw; joel.hartter@colorado.edu; Karen.bailey@colorado.edu;
   henrymaseka@gmail.com
RI Cassidy, Lin/AAC-7140-2022; Stevens, Forrest/B-1673-2013; Woodward,
   Kyle/AAE-9090-2020; PRICOPE, NARCISA/D-7123-2015
OI PRICOPE, NARCISA/0000-0002-6591-7237; Bailey, Karen
   Michelle/0000-0002-7610-8646; Stevens, Forrest/0000-0002-9328-3753;
   Drake, Michael/0000-0003-0774-2034; Cassidy, Lin/0000-0001-5469-5002;
   Kolarik, Nicholas/0000-0003-0527-058X
FU National Science Foundation [1560700]; Direct For Social, Behav &
   Economic Scie; Division Of Behavioral and Cognitive Sci [1560700]
   Funding Source: National Science Foundation
FX This research was funded by National Science Foundation, grant number
   1560700.
CR Adams WM, 2001, ORYX, V35, P193, DOI 10.1017/S0030605300031847
   Adelabu S, 2013, J APPL REMOTE SENS, V7, DOI 10.1117/1.JRS.7.073480
   Adjorlolo C, 2014, PROC SPIE, V9239, DOI 10.1117/12.2066330
   Albers HJ, 2013, ECOL ECON, V92, P87, DOI 10.1016/j.ecolecon.2012.01.021
   Anderson J R., 1976, Professional Paper
   Angelsen A, 2014, WORLD DEV, V64, pS12, DOI 10.1016/j.worlddev.2014.03.006
   [Anonymous], 1998, PEOPLE PIXELS LINKIN
   [Anonymous], 2016, ZAMBIA DEP NATL PARK
   [Anonymous], 1999, ENTERPRISE DEV COMMU
   Bailey KM, 2020, APPL GEOGR, V125, DOI 10.1016/j.apgeog.2020.102326
   Belcher B, 2005, WORLD DEV, V33, P1435, DOI 10.1016/j.worlddev.2004.10.007
   Belgiu M, 2016, ISPRS J PHOTOGRAMM, V114, P24, DOI 10.1016/j.isprsjprs.2016.01.011
   Biswal A, 2011, INT ARCH PHOTOGRAMM, V38-8, P82
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Breiman L, 1996, MACH LEARN, V24, P123, DOI 10.1007/bf00058655
   Brown MI, 2018, APPL GEOGR, V94, P71, DOI 10.1016/j.apgeog.2018.03.006
   Brown ME, 2006, WORLD DEV, V34, P751, DOI 10.1016/j.worlddev.2005.10.002
   Buchhorn M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12061044
   Bunting EL, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10071013
   Burke JJ, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8080676
   Butt B, 2010, LAND DEGRAD DEV, V21, P520, DOI 10.1002/ldr.989
   Bwangoy JRB, 2010, REMOTE SENS ENVIRON, V114, P73, DOI 10.1016/j.rse.2009.08.004
   Chagumaira C, 2016, ENVIRON DEV SUSTAIN, V18, P237, DOI 10.1007/s10668-015-9637-y
   CHAMBERS R, 1994, WORLD DEV, V22, P953, DOI 10.1016/0305-750X(94)90141-4
   Chan JCW, 2008, REMOTE SENS ENVIRON, V112, P2999, DOI 10.1016/j.rse.2008.02.011
   Chrysafis I, 2019, INT J APPL EARTH OBS, V77, P1, DOI 10.1016/j.jag.2018.12.004
   Dalponte M, 2013, IEEE T GEOSCI REMOTE, V51, P2632, DOI 10.1109/TGRS.2012.2216272
   Del Rio T, 2018, DATA BRIEF, V19, P2297, DOI 10.1016/j.dib.2018.07.009
   Dennis RA, 2005, HUM ECOL, V33, P465, DOI 10.1007/s10745-005-5156-z
   Dent D., 2013, Rural planning in developing countries: supporting natural resource management and sustainable livelihoods
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Diniz FH, 2013, INT FOREST REV, V15, P442, DOI 10.1505/146554813809025658
   Dons K, 2014, APPL GEOGR, V55, P292, DOI 10.1016/j.apgeog.2014.08.018
   Duro DC, 2012, REMOTE SENS ENVIRON, V118, P259, DOI 10.1016/j.rse.2011.11.020
   Eddy IMS, 2017, ECOL INDIC, V82, P106, DOI 10.1016/j.ecolind.2017.06.033
   Fauchereau N, 2003, NAT HAZARDS, V29, P139, DOI 10.1023/A:1023630924100
   Foody GM, 2008, INT J REMOTE SENS, V29, P3137, DOI 10.1080/01431160701442120
   Funk C, 2008, P NATL ACAD SCI USA, V105, P11081, DOI 10.1073/pnas.0708196105
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Gaughan AE, 2012, J ARID ENVIRON, V82, P19, DOI 10.1016/j.jaridenv.2012.02.007
   Gaughan AE, 2016, INT J CLIMATOL, V36, P1643, DOI 10.1002/joc.4448
   Gaughan AE, 2019, LAND-BASEL, V8, DOI 10.3390/land8070111
   Genuer R, 2010, PATTERN RECOGN LETT, V31, P2225, DOI 10.1016/j.patrec.2010.03.014
   Ghimire B, 2010, REMOTE SENS LETT, V1, P45, DOI 10.1080/01431160903252327
   Ghimire B, 2012, GISCI REMOTE SENS, V49, P623, DOI 10.2747/1548-1603.49.5.623
   Guan K, 2012, REMOTE SENS ENVIRON, V124, P653, DOI 10.1016/j.rse.2012.06.005
   Haarmeyer DH, 2013, AGROFOREST SYST, V87, P1363, DOI 10.1007/s10457-013-9644-7
   Hansen MC, 2002, REMOTE SENS ENVIRON, V83, P320, DOI 10.1016/S0034-4257(02)00080-9
   Hayashi SN, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0217754
   He HB, 2009, IEEE T KNOWL DATA EN, V21, P1263, DOI 10.1109/TKDE.2008.239
   Herlihy PH, 2003, HUM ORGAN, V62, P303, DOI 10.17730/humo.62.4.8763apjq8u053p03
   Heubach K, 2011, ECOL ECON, V70, P1991, DOI 10.1016/j.ecolecon.2011.05.015
   Hijmanns R.J., 2019, **DATA OBJECT**
   Hitztaler SK, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/045020
   Hoffman-Hall A, 2019, REMOTE SENS ENVIRON, V233, DOI 10.1016/j.rse.2019.111386
   Hopping KA, 2018, APPL GEOGR, V94, P147, DOI [10.1016/j, 10.1016/j.apgeog.2018.03.013]
   HUETE AR, 1988, REMOTE SENS ENVIRON, V25, P295, DOI 10.1016/0034-4257(88)90106-X
   Jackson Q, 2001, IEEE T GEOSCI REMOTE, V39, P2664, DOI 10.1109/36.975001
   Jacquin A, 2010, INT J APPL EARTH OBS, V12, pS3, DOI 10.1016/j.jag.2009.11.004
   Jin YH, 2018, INT J REMOTE SENS, V39, P8703, DOI 10.1080/01431161.2018.1490976
   Joos-Vandewalle S, 2018, ECOSYST SERV, V30, P342, DOI 10.1016/j.ecoser.2018.02.007
   Kaaya E, 2017, ENVIRON MANAGE, V60, P464, DOI 10.1007/s00267-017-0856-x
   Kakembo V, 2019, LAND DEGRAD DEV, V30, P1052, DOI 10.1002/ldr.3292
   King B, 2018, HUM ECOL, V46, P865, DOI 10.1007/s10745-018-0039-2
   Kowe P, 2019, J APPL REMOTE SENS, V13, DOI 10.1117/1.JRS.13.024523
   Kugler TA, 2019, POPUL ENVIRON, V41, P209, DOI 10.1007/s11111-019-00326-5
   Lam NSN, 2018, REMOTE SENS ENVIRON, V209, P253, DOI 10.1016/j.rse.2017.12.034
   Laris P, 2002, HUM ECOL, V30, P155, DOI 10.1023/A:1015685529180
   Leiterer R, 2018, APPL GEOGR, V93, P1, DOI 10.1016/j.apgeog.2018.01.013
   Lepper CM, 2010, DEV SO AFR, V27, P725, DOI 10.1080/0376835X.2010.522834
   Li W, 2020, REMOTE SENS ENVIRON, V247, DOI 10.1016/j.rse.2020.111953
   Liverman DM, 2008, EARTH SURF PROC LAND, V33, P1458, DOI 10.1002/esp.1715
   Lloyd CT, 2019, BIG EARTH DATA, V3, P108, DOI 10.1080/20964471.2019.1625151
   Lloyd CT, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.1
   Martínez-Verduzco GC, 2012, APPL GEOGR, V34, P1, DOI 10.1016/j.apgeog.2011.10.001
   Martiny N, 2006, INT J REMOTE SENS, V27, P5201, DOI 10.1080/01431160600567787
   Marumbwa FM, 2019, PHYS CHEM EARTH, V114, DOI 10.1016/j.pce.2019.10.004
   Maxwell AE, 2014, GISCI REMOTE SENS, V51, P301, DOI 10.1080/15481603.2014.912874
   Maxwell AE, 2018, INT J REMOTE SENS, V39, P2784, DOI 10.1080/01431161.2018.1433343
   McCall MK, 2005, GEOGR J, V171, P340, DOI 10.1111/j.1475-4959.2005.00173.x
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Mosomtai G, 2020, J APPL REMOTE SENS, V14, DOI 10.1117/1.JRS.14.044513
   Mugido W, 2019, FOREST POLICY ECON, V109, DOI 10.1016/j.forpol.2019.101983
   Mulenga BP, 2014, ENVIRON DEV ECON, V19, P487, DOI 10.1017/S1355770X13000569
   Myint SW, 2003, INT J REMOTE SENS, V24, P1925, DOI 10.1080/01431160210155992
   Naughton-Treves L, 2007, BIOL CONSERV, V134, P232, DOI 10.1016/j.biocon.2006.08.020
   Ndanyalasi HJ, 2007, BIOL CONSERV, V134, P242, DOI 10.1016/j.biocon.2006.06.020
   Nieves JJ, 2017, J R SOC INTERFACE, V14, DOI 10.1098/rsif.2017.0401
   Nkambwe M, 2006, ENVIRON MANAGE, V37, P281, DOI 10.1007/s00267-005-2776-4
   Norris D, 2016, FOREST ECOL MANAG, V377, P182, DOI 10.1016/j.foreco.2016.07.008
   Palmer C, 2009, ENVIRON DEV ECON, V14, P693, DOI 10.1017/S1355770X08005007
   Peres CA, 2003, CONSERV BIOL, V17, P521, DOI 10.1046/j.1523-1739.2003.01413.x
   Pricope NG, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11232783
   Pricope NG, 2015, LAND-BASEL, V4, P627, DOI 10.3390/land4030627
   Pricope NG, 2020, SOC NATUR RESOUR, V33, P418, DOI 10.1080/08941920.2019.1680783
   Read JM, 2002, INT J REMOTE SENS, V23, P2457, DOI 10.1080/01431160110106140
   Ringrose S, 2002, ENVIRON MANAGE, V30, P98, DOI 10.1007/s00267-002-2486-0
   Rist S, 2007, J RURAL STUD, V23, P23, DOI 10.1016/j.jrurstud.2006.02.006
   Robiglio V, 2005, FOREST CHRON, V81, P392, DOI 10.5558/tfc81392-3
   Rodriguez-Galiano VF, 2012, REMOTE SENS ENVIRON, V121, P93, DOI 10.1016/j.rse.2011.12.003
   Colditz RR, 2015, REMOTE SENS-BASEL, V7, P9655, DOI 10.3390/rs70809655
   Ryan CM, 2016, PHILOS T R SOC B, V371, DOI 10.1098/rstb.2015.0312
   Salerno J, 2020, CONSERV BIOL, V34, P891, DOI 10.1111/cobi.13480
   Salerno J, 2018, AM SCI, V106, P34
   Sardeshpande M, 2019, FORESTS, V10, DOI 10.3390/f10060467
   Schlesinger J, 2015, APPL GEOGR, V56, P107, DOI 10.1016/j.apgeog.2014.11.013
   Serdeczny O, 2017, REG ENVIRON CHANGE, V17, P1585, DOI 10.1007/s10113-015-0910-2
   Shackleton C. M., 2005, African Journal of Range & Forage Science, V22, P127, DOI 10.2989/10220110509485870
   Shackleton C, 2011, NON-TIMBER FOREST PRODUCTS IN THE GLOBAL CONTEXT, P3, DOI 10.1007/978-3-642-17983-9_1
   Shanley P., 2014, Tropical forestry handbook, P1, DOI [10.1007/978-3-642-41554-8_, DOI 10.1007/978-3-642-41554-8]
   Sheffield J, 2014, B AM METEOROL SOC, V95, P861, DOI 10.1175/BAMS-D-12-00124.1
   Shrestha S, 2016, J ETHNOBIOL, V36, P326, DOI 10.2993/0278-0771-36.2.326
   Sileshi GW, 2008, AGROFOREST SYST, V72, P87, DOI 10.1007/s10457-007-9082-5
   Sitati NW, 2005, J APPL ECOL, V42, P1175, DOI 10.1111/j.1365-2664.2005.01091.x
   Sorichetta A, 2016, SCI DATA, V3, DOI 10.1038/sdata.2016.66
   Souverijns N, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12223817
   Srivastava VK, 2010, TROP ECOL, V51, P107
   Stehman SV, 2019, REMOTE SENS ENVIRON, V231, DOI 10.1016/j.rse.2019.05.018
   Stevens FR, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0107042
   Stone M.T., 2015, In institutional arrangements for conservation development and tourism in Eastern and Southern Africa, P81
   Timko JA, 2010, INT FOREST REV, V12, P284, DOI 10.1505/ifor.12.3.284
   Tompkins EL, 2004, ECOL SOC, V9
   Vadjunec JM, 2009, ECOL SOC, V14
   Verburg PH, 2013, CURR OPIN ENV SUST, V5, P433, DOI 10.1016/j.cosust.2013.08.001
   Vergara-Asenjo G, 2015, CONSERV LETT, V8, P432, DOI 10.1111/conl.12161
   Walsh S.J., 2003, PEOPLE ENV, P91
   Wen X.B., 2009, INFLUENCE NUMBER FEA, P1088
   Williams D, 2018, ENVIRON CONSERV, V45, P173, DOI 10.1017/S0376892917000418
   Wingate VR, 2018, INT J REMOTE SENS, V39, P577, DOI 10.1080/01431161.2017.1390271
   Wingate VR, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8080681
   Wu WC, 2013, INT J REMOTE SENS, V34, P4525, DOI 10.1080/01431161.2013.777487
   Yu L, 2014, INT J REMOTE SENS, V35, P4573, DOI 10.1080/01431161.2014.930206
   Zaehringer JG, 2018, J LAND USE SCI, V13, P16, DOI [10.1080/1747423x.2018.1447033, 10.1080/1747423X.2018.1447033]
   Zhang WM, 2018, BIOGEOSCIENCES, V15, P319, DOI 10.5194/bg-15-319-2018
   Zhang XY, 2003, REMOTE SENS ENVIRON, V84, P471, DOI 10.1016/S0034-4257(02)00135-9
   Zheng XY, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9050486
NR 137
TC 3
Z9 4
U1 3
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2072-4292
J9 REMOTE SENS-BASEL
JI Remote Sens.
PD FEB
PY 2021
VL 13
IS 4
AR 631
DI 10.3390/rs13040631
PG 30
WC Environmental Sciences; Geosciences, Multidisciplinary; Remote Sensing;
   Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging
   Science & Photographic Technology
GA QQ3GL
UT WOS:000624412200001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Gosnell, H
   Gill, N
   Voyer, M
AF Gosnell, Hannah
   Gill, Nicholas
   Voyer, Michelle
TI Transformational adaptation on the farm: Processes of change and
   persistence in transitions to 'climate-smart' regenerative agriculture
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate change adaptation and mitigation; Holistic Management;
   Transformative learning; Communities of practice; Earth stewardship;
   Relational thinking
ID PRECISION AGRICULTURE; CARBON SEQUESTRATION; ENVIRONMENTAL-CHANGE; SOIL
   CARBON; PLACE; AUSTRALIA; SUSTAINABILITY; RANGELANDS; IDENTITY;
   OPPORTUNITIES
AB Regenerative agriculture, an alternative form of food and fiber production, concerns itself with enhancing and restoring resilient systems supported by functional ecosystem processes and healthy, organic soils capable of producing a full suite of ecosystem services, among them soil carbon sequestration and improved soil water retention. As such, climate change mitigation and adaptation are incidental to a larger enterprise that employs a systems approach to managing landscapes and communities. The transformative potential of regenerative agriculture has seen growing attention in the popular press, but few empirical studies have explored the processes by which farmers enter into, navigate, and, importantly, sustain the required paradigm shift in their approach to managing their properties, farm businesses, and personal lives. We draw on theories and insights associated with relational thinking to analyze the experiences of farmers in Australia who have undertaken and sustained transitions from conventional to regenerative agriculture. We present a conceptual framework of "zones of friction and traction" occurring in personal, practical, and political spheres of transformation that both challenge and facilitate the transition process. Our findings illustrate the ways in which deeply held values and emotions influence and interact with mental models, worldviews, and cultural norms as a result of regular monitoring; and how behavioral change is sustained through the establishment of self-amplifying positive feedbacks involving biophilic emotions, a sense of well-being, and an ever-expanding worldview. We conclude that transitioning to regenerative agriculture involves more than a suite of 'climate-smart' mitigation and adaptation practices supported by technical innovation, policy, education, and outreach. Rather, it involves subjective, nonmaterial factors associated with culture, values, ethics, identity, and emotion that operate at individual, household, and community scales and interact with regional, national and global processes. Findings have implications for strategies aimed at facilitating a large-scale transition to climate-smart regenerative agriculture.
C1 [Gosnell, Hannah] Oregon State Univ, Coll Earth Ocean & Atmospher Sci, 104 CEOAS Adm Bldg, Corvallis, OR 97331 USA.
   [Gill, Nicholas] Univ Wollongong, Australian Ctr Culture Environm Soc & Space, Northfields Ave, Wollongong, NSW 2522, Australia.
   [Voyer, Michelle] Univ Wollongong, Fac Law Humanities & Arts, Northfields Ave, Wollongong, NSW 2522, Australia.
C3 Oregon State University; University of Wollongong; University of
   Wollongong
RP Gosnell, H (corresponding author), Oregon State Univ, Coll Earth Ocean & Atmospher Sci, 104 CEOAS Adm Bldg, Corvallis, OR 97331 USA.
EM gosnellh@geo.oregonstate.edu; ngill@uow.edu.au; mvoyer@uow.edu.au
RI Gill, Nicholas/H-6240-2016; Voyer, Michelle/U-6134-2019
OI Voyer, Michelle/0000-0001-6170-9994
FU USDA Forest Service Pacific Northwest Research Station, Portland,
   Oregon, USA; Australian Centre for Culture, Environment, Society and
   Space, University of Wollongong, Australia
FX This work was supported by the USDA Forest Service Pacific Northwest
   Research Station, Portland, Oregon, USA; and the Australian Centre for
   Culture, Environment, Society and Space, University of Wollongong,
   Australia.
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Adger WN, 2011, GLOBAL ENVIRON POLIT, V11, P1, DOI 10.1162/GLEP_a_00051
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Anderson D. M., 2015, Rangelands, V37, P62, DOI 10.1016/j.rala.2015.01.006
   [Anonymous], SUCCESSFUL ADAPTATIO
   [Anonymous], 2010, REG ENV CHANG HUM AC
   [Anonymous], British Food Journal
   [Anonymous], 2003, COMFORT CLEANLINESS
   [Anonymous], 2016, REGRARIANS HDB
   [Anonymous], 1985, Enough food: Achieving food security through regenerative agriculture
   [Anonymous], 2013, Sourcebook on Climate Smart Agriculture, Forestry and Fisheries
   [Anonymous], 2006, Resilience Thinking: Sustaining Ecosystems and People in a Changing World
   [Anonymous], PNWGTR801 USDA FOR S
   [Anonymous], 2010, CLIM SMART AGR POL P
   [Anonymous], AUSTR FARM SURV RES
   [Anonymous], 2010, Principles of Ecosystem Stewardship: Resilience-based Natural Resource Management in a Changing World
   [Anonymous], LEVELS REGNERATIVE A
   [Anonymous], 2013, AGR FOOD SECUR, DOI DOI 10.1186/2048-7010-2-12
   [Anonymous], 2012, DAIRY AUSTR
   [Anonymous], 2013, SUCCESSFUL ADAPTATIO
   Argent N, 2002, AUST GEOGR, V33, P97, DOI 10.1080/00049180220125033
   Armitage D, 2008, GLOBAL ENVIRON CHANG, V18, P86, DOI 10.1016/j.gloenvcha.2007.07.002
   Bell LW, 2014, CROP PASTURE SCI, V65, P489, DOI 10.1071/CP13420
   Bernard Harvey R., 2011, Research methods in anthropology Qualitative and quantitative approaches
   Briske DD, 2008, RANGELAND ECOL MANAG, V61, P3, DOI 10.2111/06-159R.1
   Briske DD, 2011, RANGELAND ECOL MANAG, V64, P325, DOI 10.2111/REM-D-10-00084.1
   Briske DD, 2014, AGR SYST, V125, P50, DOI 10.1016/j.agsy.2013.12.001
   Brown G., 2018, Dirt to soil: one family's journey into regenerative agriculture
   Brown K, 2019, GLOBAL ENVIRON CHANG, V56, P11, DOI 10.1016/j.gloenvcha.2019.03.003
   Burton RJF, 2006, J RURAL STUD, V22, P95, DOI 10.1016/j.jrurstud.2005.07.004
   Burton RJF, 2004, SOCIOL RURALIS, V44, P195, DOI 10.1111/j.1467-9523.2004.00270.x
   Burton RJF, 2014, J ENVIRON MANAGE, V135, P19, DOI 10.1016/j.jenvman.2013.12.005
   Burton RJF, 2012, LANDSCAPE RES, V37, P51, DOI 10.1080/01426397.2011.559311
   Carolan M, 2017, SOCIOL RURALIS, V57, P135, DOI 10.1111/soru.12120
   Castree N, 2015, GEOGR RES-AUST, V53, P244, DOI 10.1111/1745-5871.12125
   Castree N, 2014, NAT CLIM CHANGE, V4, P763, DOI 10.1038/NCLIMATE2339
   Chapin FS, 2011, ECOSPHERE, V2, DOI 10.1890/ES11-00166.1
   Chapin FS, 2010, TRENDS ECOL EVOL, V25, P241, DOI 10.1016/j.tree.2009.10.008
   Clifford KR, 2018, GLOBAL ENVIRON CHANG, V49, P1, DOI 10.1016/j.gloenvcha.2017.12.007
   Creswell J. W., 2018, Research design: qualitative, quantitative, and mixed methods approaches
   Cross R, 2017, SOC NATUR RESOUR, V30, P585, DOI 10.1080/08941920.2016.1230915
   Darnhofer I, 2016, J RURAL STUD, V44, P111, DOI 10.1016/j.jrurstud.2016.01.013
   Deleuze G., 1988, SPINOZA PRACTICAL PH
   Dowd AM, 2014, NAT CLIM CHANGE, V4, P558, DOI [10.1038/NCLIMATE2275, 10.1038/nclimate2275]
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Evans Megan C., 2016, Pacific Conservation Biology, V22, P130, DOI 10.1071/PC15052
   FAO: Food and Agriculture Organization of the United Nations, 2010, INTEGRATED CROP MANA, V9-2010
   Folke C, 2011, AMBIO, V40, P719, DOI 10.1007/s13280-011-0184-y
   Folke C, 2010, ECOL SOC, V15
   Fresque-Baxter JA, 2012, WIRES CLIM CHANGE, V3, P251, DOI 10.1002/wcc.164
   Fynn RWS, 2012, RANGELAND ECOL MANAG, V65, P319, DOI 10.2111/REM-D-11-00141.1
   Gibson C., 2013, Household Sustainability: Challenges and Dilemmas in Everyday Life
   Gill N, 2015, ENERG POLICY, V87, P83, DOI 10.1016/j.enpol.2015.08.038
   Gill N, 2014, T I BRIT GEOGR, V39, P265, DOI 10.1111/tran.12025
   Gosnell H., 2011, RANGELANDS, V33, P20, DOI 10.2111/1551-501X-33.5.20
   Hayman P, 2012, CROP PASTURE SCI, V63, P203, DOI 10.1071/CP11196
   Head L, 2013, AUSTRALAS J ENV MAN, V20, P351, DOI 10.1080/14486563.2013.835286
   Head L, 2011, ANN ASSOC AM GEOGR, V101, P1089, DOI 10.1080/00045608.2011.579533
   Herman A, 2015, J RURAL STUD, V42, P102, DOI 10.1016/j.jrurstud.2015.10.003
   Higgins V, 2017, J RURAL STUD, V55, P193, DOI 10.1016/j.jrurstud.2017.08.011
   Hobson K, 2006, ETHICS POLICY ENV, V9, P317, DOI 10.1080/13668790600902375
   Hodbod J, 2016, J ENVIRON MANAGE, V183, P379, DOI 10.1016/j.jenvman.2016.05.064
   Holmes J, 2012, J RURAL STUD, V28, P252, DOI 10.1016/j.jrurstud.2012.01.004
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Hulme M., 2014, Humanities, V3, P299, DOI DOI 10.3390/H3030299
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Lal R, 2015, J SOIL WATER CONSERV, V70, p55A, DOI 10.2489/jswc.70.3.55A
   Lawrence G, 2013, J RURAL STUD, V29, P30, DOI 10.1016/j.jrurstud.2011.12.005
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Macy J., 2012, ACTIVE HOPE
   Marshall NA, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034022
   Marshall NA, 2010, GLOBAL ENVIRON CHANG, V20, P36, DOI 10.1016/j.gloenvcha.2009.10.003
   Marshall N, 2019, SUSTAIN SCI, V14, P579, DOI 10.1007/s11625-019-00666-z
   Massy C., 2017, Call of the reed warbler: A new agriculture-A new earth
   Maxwell J.A., 2004, Qualitative research design: An interactive approach, V2nd
   McHenry MP, 2009, AGR ECOSYST ENVIRON, V129, P1, DOI 10.1016/j.agee.2008.08.006
   McKenzie F, 2013, AUST GEOGR, V44, P81, DOI 10.1080/00049182.2013.765349
   Mcsherry ME, 2013, GLOBAL CHANGE BIOL, V19, P1347, DOI 10.1111/gcb.12144
   Mezirow J., 2000, JOSSEY BASS HIGHER A
   Miles M. B., 1994, QUALITATIVE DATA ANA
   Montgomery D.R., 2017, Growing a revolution: Bringing our soil back to life
   O'Brien K., 2013, P TRANSFORMATION CHA, P16
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   O'Brien KL, 2010, WIRES CLIM CHANGE, V1, P232, DOI 10.1002/wcc.30
   Olsson L, 2002, AMBIO, V31, P471, DOI 10.1639/0044-7447(2002)031[0471:SCSIDS]2.0.CO;2
   Olsson P, 2014, ECOL SOC, V19, DOI 10.5751/ES-06799-190401
   Panda A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.520
   Pannell DJ, 2006, AUST J EXP AGR, V46, P1407, DOI 10.1071/EA05037
   Park SE, 2012, GLOBAL ENVIRON CHANG, V22, P115, DOI 10.1016/j.gloenvcha.2011.10.003
   Patton MQ., 1990, QUALITATIVE EVALUATI, V2
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   Plummer R, 2006, NAT RESOUR FORUM, V30, P51, DOI 10.1111/j.1477-8947.2006.00157.x
   Provenza F., 2013, RANGELANDS, V35, P6, DOI DOI 10.2111/RANGELANDS-D-13-00013.1
   Rhodes CJ, 2017, SCI PROGRESS-UK, V100, P80, DOI 10.3184/003685017X14876775256165
   Richards C, 2009, LAND USE POLICY, V26, P630, DOI 10.1016/j.landusepol.2008.08.016
   Rickards L, 2012, CROP PASTURE SCI, V63, P240, DOI 10.1071/CP11172
   Savory A., 1999, Holistic Management: A Framework for Decision Making. The Center for Resource Economics
   Savory A., 2016, Holistic management: a commonsense revolution to restore our environment
   Scannell L, 2010, J ENVIRON PSYCHOL, V30, P1, DOI 10.1016/j.jenvp.2009.09.006
   Scherr S.J., 2012, Agriculture Food Security, V1, P1
   Sharma M., 2007, KOSMOS J
   Sherren K, 2019, RENEW AGR FOOD SYST, V34, P77, DOI 10.1017/S1742170517000308
   Sherren K, 2012, AGR SYST, V106, P72, DOI 10.1016/j.agsy.2011.11.001
   Smith MS, 2011, PHILOS T R SOC A, V369, P196, DOI 10.1098/rsta.2010.0277
   Teague R, 2017, AFR J RANGE FOR SCI, V34, P77, DOI 10.2989/10220119.2017.1334706
   Teague R, 2013, J ENVIRON MANAGE, V128, P699, DOI 10.1016/j.jenvman.2013.05.064
   Teague WR, 2016, J SOIL WATER CONSERV, V71, P156, DOI 10.2489/jswc.71.2.156
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Tidball KG, 2012, ECOL SOC, V17, DOI 10.5751/ES-04596-170205
   Toensmeier E., 2016, CARBON FARMING SOLUT
   Waters C.M., 2016, LAND DEGRAD DEV, V28, P1363, DOI [10.1002/ldr.2602, DOI 10.1002/ldr.2602]
   Westley F, 2011, AMBIO, V40, P762, DOI 10.1007/s13280-011-0186-9
NR 112
TC 153
Z9 168
U1 30
U2 372
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD NOV
PY 2019
VL 59
AR 101965
DI 10.1016/j.gloenvcha.2019.101965
PG 13
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA JU4LF
UT WOS:000501648400016
OA Bronze, Green Submitted
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Liu, YJ
   Chen, QM
   Tan, QH
AF Liu, Yujie
   Chen, Qiaomin
   Tan, Qinghua
TI Responses of wheat yields and water use efficiency to climate change and
   nitrogen fertilization in the North China plain
SO FOOD SECURITY
LA English
DT Article
DE Climate change; Nitrogen fertilization; Wheat yields; Water use
   efficiency; The North China plain
ID WINTER-WHEAT; CERES-WHEAT; CROP YIELD; MANAGEMENT; TRENDS; TEMPERATURE;
   PHENOLOGY; MODELS; IMPACT; PRECIPITATION
AB Ensuring food security for the 1.4 billion people of China is a critical challenge, and therefore the accurate assessment of crop yield responses to climate change is a key scientific issue. However, the extent to which the variation in crop growth can be accounted for by the variability in climate variables or by management adaptations remains unclear. Based on daily weather data and management information at six stations, we constructed three sets of simulation experiments using the Crop Environment Resource Synthesis (CERES)-Wheat model. This allowed quantifying the responses of wheat yield and water use efficiency (yield/evapotranspiration, WUE) to climate change and nitrogen (N) fertilization for the period 1981 to 2008 in the North China Plain. Our results indicated that the simulated median values of the wheat yield/WUE decreased (2.62% to 14.26%)/(1.58% to 9.33%) with increasing temperature (T), increased (0.17% to 6.81%)/(0.70% to 4.55%) with elevated CO2 concentration, and changed little with decreasing precipitation in 15 simulation experiments of individual climate variables. Under the combined changes in temperature, N fertilization (T/N), and CO2 concentration, the effects of changes in T/N fertilization on wheat yields and WUE were stronger than the effects of change in CO2 concentration. Interactions between T and CO2 concentration, N fertilization and CO2 concentration appear to play very significant roles in wheat yield. Our study suggests that proper N fertilizer application, changing crop establishment dates, and cultivating new cultivars could be efficient measures for food production prediction and climate change adaptation in the North China Plain. A main result of this work is therefore that proper N application, shifts in crop establishment dates, and the cultivation of new high-temperature tolerant wheat cultivars could contribute safeguarding food security in China, and globally.
C1 [Liu, Yujie; Chen, Qiaomin; Tan, Qinghua] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
   [Chen, Qiaomin; Tan, Qinghua] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Geographic Sciences & Natural
   Resources Research, CAS; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS
RP Liu, YJ (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
EM liuyujie@igsnrr.ac.cn
RI Chen, Qiaomin/LKM-5162-2024
OI Chen, Qiaomin/0000-0003-0628-8896; Liu, Yujie/0000-0002-0751-6857
FU National Natural Science Foundation of China [41671037, 41301091]; Youth
   Innovation Promotion Association, CAS [2016049]; Program for "Kezhen"
   Excellent Talents in IGSNRR, CAS [2017RC101]; Key Research Program of
   Frontier Sciences, CAS [QYZDB-SSW-DQC005]
FX This study was supported by the National Natural Science Foundation of
   China (Grant No. 41671037, 41301091); the Youth Innovation Promotion
   Association, CAS (Grant No. 2016049); Program for "Kezhen" Excellent
   Talents in IGSNRR, CAS (Grant No.2017RC101); and the Key Research
   Program of Frontier Sciences, CAS (QYZDB-SSW-DQC005). We also thank the
   ChinaMeteorological Administration for providing data support.
CR Ali G, 2017, ENVIRON SCI POLICY, V77, P166, DOI 10.1016/j.envsci.2017.08.019
   [Anonymous], 2015, CHIN STAT YB, P244
   Asseng S, 2013, NAT CLIM CHANGE, V3, P827, DOI [10.1038/nclimate1916, 10.1038/NCLIMATE1916]
   Asseng S, 2011, GLOBAL CHANGE BIOL, V17, P997, DOI 10.1111/j.1365-2486.2010.02262.x
   Basso B, 2016, ADV AGRON, V136, P27, DOI 10.1016/bs.agron.2015.11.004
   Borgesen CD, 2011, NAT HAZARD EARTH SYS, V11, P2541, DOI 10.5194/nhess-11-2541-2011
   Chen C, 2013, CLIMATIC CHANGE, V116, P767, DOI 10.1007/s10584-012-0509-2
   Chen QM, 2018, LAND USE POLICY, V76, P1, DOI 10.1016/j.landusepol.2018.04.018
   Ingram J, 2011, FOOD SECUR, V3, P417, DOI 10.1007/s12571-011-0149-9
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Jin XL, 2018, PRECIS AGRIC, V19, P1, DOI 10.1007/s11119-016-9469-2
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Kruijt B, 2008, J HYDROL, V349, P257, DOI 10.1016/j.jhydrol.2007.10.052
   Li KN, 2016, INT J BIOMETEOROL, V60, P21, DOI 10.1007/s00484-015-1002-1
   Liu B, 2016, GLOBAL CHANGE BIOL, V22, P1890, DOI 10.1111/gcb.13212
   Liu WX, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01798
   Liu YJ, 2018, SCI CHINA EARTH SCI, V61, P1088, DOI 10.1007/s11430-017-9149-0
   Liu YJ, 2018, AGR FOREST METEOROL, V248, P518, DOI 10.1016/j.agrformet.2017.09.008
   Liu YJ, 2013, J APPL METEOROL CLIM, V52, P114, DOI 10.1175/JAMC-D-12-039.1
   Lo AY, 2019, CLIMATIC CHANGE, V157, P565, DOI 10.1007/s10584-019-02562-y
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Lobell DB, 2003, SCIENCE, V299, P1032, DOI 10.1126/science.1077838
   Malone EL, 2011, WIRES CLIM CHANGE, V2, P462, DOI 10.1002/wcc.116
   Maltais-Landry G, 2012, AGRON J, V104, P301, DOI 10.2134/agronj2011.0220
   Montesino-San Martín M, 2014, AGR FOREST METEOROL, V187, P1, DOI 10.1016/j.agrformet.2013.11.009
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   O'Leary GJ, 2015, GLOBAL CHANGE BIOL, V21, P2670, DOI 10.1111/gcb.12830
   Paymard P, 2018, NAT HAZARDS, V91, P1237, DOI 10.1007/s11069-018-3180-8
   Persson T, 2010, EUR J AGRON, V32, P272, DOI 10.1016/j.eja.2010.01.004
   Pirttioja N, 2015, CLIM RES, V65, P87, DOI 10.3354/cr01322
   Rötter RP, 2011, NAT CLIM CHANGE, V1, P175
   Savary S, 2019, NAT ECOL EVOL, V3, P430, DOI 10.1038/s41559-018-0793-y
   Scott GJ, 2019, FOOD SECUR, V11, P43, DOI 10.1007/s12571-019-00897-z
   Seremesic S, 2011, PLANT SOIL ENVIRON, V57, P216, DOI 10.17221/207/2010-PSE
   Tao FL, 2012, CLIM RES, V54, P233, DOI 10.3354/cr01131
   Tao FL, 2010, EUR J AGRON, V33, P103, DOI 10.1016/j.eja.2010.04.002
   Thornton PK, 2009, GLOBAL ENVIRON CHANG, V19, P54, DOI 10.1016/j.gloenvcha.2008.08.005
   Wang J, 2012, CLIMATIC CHANGE, V113, P825, DOI 10.1007/s10584-011-0385-1
   Willocquet L, 2008, FIELD CROP RES, V107, P12, DOI 10.1016/j.fcr.2007.12.013
   Xiao GJ, 2013, AGR ECOSYST ENVIRON, V181, P108, DOI 10.1016/j.agee.2013.09.019
   Xiong W, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/4/044014
   Yang P, 2014, REG ENVIRON CHANGE, V14, P61, DOI 10.1007/s10113-013-0484-9
   Zhang D, 2019, NUTR CYCL AGROECOSYS, V114, P19, DOI 10.1007/s10705-019-09984-1
   Zhang S, 2013, EUR J AGRON, V45, P165, DOI 10.1016/j.eja.2012.10.005
   Zhong YQW, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0098850
NR 45
TC 12
Z9 14
U1 15
U2 172
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1876-4517
EI 1876-4525
J9 FOOD SECUR
JI Food Secur.
PD DEC
PY 2019
VL 11
IS 6
BP 1231
EP 1242
DI 10.1007/s12571-019-00976-1
EA OCT 2019
PG 12
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA JT6BB
UT WOS:000490207800001
DA 2025-01-10
ER

PT J
AU Martinsen, V
   Munera-Echeverri, JL
   Obia, A
   Cornelissen, G
   Mulder, J
AF Martinsen, Vegard
   Munera-Echeverri, Jose Luis
   Obia, Alfred
   Cornelissen, Gerard
   Mulder, Jan
TI Significant build-up of soil organic carbon under climate-smart
   conservation farming in Sub-Saharan Acrisols
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Hand-hoe tillage; Planting basin; Soil fertility; Soil sampling;
   Phosphorus; CEC
ID AGRICULTURE SYSTEMS; MANAGEMENT; MATTER; SEQUESTRATION; STABILIZATION;
   PRODUCTIVITY; CAPACITY; BIOCHAR; QUALITY; ENVIRONMENTS
AB Conservation farming (CF) involving minimumtillage, mulching and crop rotation may offer climate change adaptation and mitigation benefits. However, reported effects of CF, as applied by smallholders, on storage of soil organic carbon (SOC) and soil fertility in Sub-Saharan Africa differ considerably between studies. This is partly due to differences in management practice, soil type and adoption level between individual farmers. Where CF involves planting basins, year-to-year changes in position of basins make SOC stock estimates more uncertain. Here we assess the difference in SOC build-up and soil quality between inside planting basins (receiving inputs of lime and fertilizer; basins opened each year) and outside planting basins (no soil disturbance or inputs other than residues) under hand-hoe tilled CF in an Acrisol at Mkushi, Zambia. Seven years of strict CF husbandry significantly improved soil quality inside planting basins as compared with outside basins. Significant effects were found for SOC concentration (0.74 +/- 0.06% vs. 0.57 +/- 0.08%), SOC stock (20.1 +/- 2.0 vs. 16.4 +/- 2.6 t ha(-1), 0-20 cm), soil pH (6.3 +/- 0.2 vs. 4.95 +/- 0.4) and cation exchange capacity (3.8 +/- 0.7 vs. 1.6 +/- 0.4 cmol(c) kg(-1)). As planting basins only occupy 9.3% of the field, the absolute rate of increase in SOC, compared with outside basins, was 0.05 t C ha(-1) yr(-1). This corresponds to an overall relative increase of 2.95% SOC yr(-1) in the upper 20 cm of the soil. Also, hot water extractable carbon (HWEC), a proxy for labile organic matter, and potential nitrification rates were consistently greater inside than outside basins. The significant increase in quantity and quality of SOC may be due to increased inputs of roots, due to favorable conditions for plant growth through input of fertilizer and lime, along with increased rainwater infiltration in the basins. (c) 2019 Elsevier B.V. All rights reserved.
C1 [Martinsen, Vegard; Munera-Echeverri, Jose Luis; Cornelissen, Gerard; Mulder, Jan] Norwegian Univ Life Sci, Fac Environm Sci & Nat Resource Management, POB 5003, N-1432 As, Norway.
   [Obia, Alfred; Cornelissen, Gerard] Norwegian Geotech Inst, POB 3930, N-0806 Oslo, Norway.
   [Obia, Alfred] Gulu Univ, Fac Agr & Environm, Dept Agron, POB 166, Gulu, Uganda.
C3 Norwegian University of Life Sciences; Norwegian Geotechnical Institute,
   NGI
RP Martinsen, V (corresponding author), Norwegian Univ Life Sci, Fac Environm Sci & Nat Resource Management, POB 5003, N-1432 As, Norway.
EM vegard.martinsen@nmbu.no
RI Obia, Alfred/AAE-7257-2019; Martinsen, Vegard/H-9406-2014
OI Martinsen, Vegard/0000-0002-7096-1806; Obia, Alfred/0000-0003-0960-7020;
   Munera Echeverri, Jose Luis/0000-0002-8162-9649
FU Faculty of Environmental Sciences and Natural Resource Management at the
   Norwegian University of Life Sciences; R&D project "Soil Benefits
   Parameters Research, Conventional and Conservation Agriculture";
   Conservation Farming Unit (CFU) in Zambia; DFID
FX The study was funded by the Faculty of Environmental Sciences and
   Natural Resource Management at the Norwegian University of Life Sciences
   and by the R&D project "Soil Benefits Parameters Research, Conventional
   and Conservation Agriculture" funded by the Conservation Farming Unit
   (CFU) in Zambia with support from DFID. Thanks to Jeremy Selby for
   allowing access to his fields, for careful management of the research
   plots and for his hospitality. CENA farms and YARA are acknowledged for
   donation of fertilizers. Victor Shitumbanuma at the Department of Soil
   Science, School of Agriculture, University of Zambia is gratefully
   acknowledged for constructive inputs to the project. Magdalena Rygalska,
   Irene E. Dahl, Oddny Gimmingsrud, Valentina Zivanovic, Kelvin and Edward
   Bwalya are acknowledged for their technical assistance in the lab and in
   the field.
CR Abiven S, 2015, PLANT SOIL, V395, P45, DOI 10.1007/s11104-015-2533-2
   [Anonymous], PRACTICE CONVENTIONA
   [Anonymous], PROCEDURES SOIL ANAL
   [Anonymous], SOIL ORG CARB HIDD P
   [Anonymous], 1982, METHODS SOIL ANAL PA
   [Anonymous], GEOLOGI JORDBUNDSLAE
   [Anonymous], SOIL TILLAGE R UNPUB
   [Anonymous], FOOD SEC
   Breeuwsma A., 1992, Rapport-DLO Staring Centre, Wageningen, ppp
   Cheesman S, 2016, SOIL TILL RES, V156, P99, DOI 10.1016/j.still.2015.09.018
   Chivenge PP, 2007, SOIL TILL RES, V94, P328, DOI 10.1016/j.still.2006.08.006
   Corbeels M., 2015, Conservation agriculture in sub-Saharan africa, Conservation Agriculture, P443, DOI [10.1007/978-3-319-11620-4_18, DOI 10.1007/978-3-319-11620-4_18]
   Corbeels M, 2019, SOIL TILL RES, V188, P16, DOI 10.1016/j.still.2018.02.015
   Curtin D, 2017, SOIL SCI SOC AM J, V81, P979, DOI 10.2136/sssaj2016.08.0265
   Ellert BH, 1995, CAN J SOIL SCI, V75, P529, DOI 10.4141/cjss95-075
   Elonen P., 1971, Suomen Maataloustieteellinen Seuran Julkaisuja, V122
   FAO, 2017, The Future of Food and Agriculture: Trends and Challenges
   Gatere L, 2013, AGR ECOSYST ENVIRON, V179, P200, DOI 10.1016/j.agee.2013.08.006
   Ghani A, 2003, SOIL BIOL BIOCHEM, V35, P1231, DOI 10.1016/S0038-0717(03)00186-X
   Giller KE, 2009, FIELD CROP RES, V114, P23, DOI 10.1016/j.fcr.2009.06.017
   Gruba P, 2015, SCI TOTAL ENVIRON, V511, P655, DOI 10.1016/j.scitotenv.2015.01.013
   Johansen C, 2012, FIELD CROP RES, V132, P18, DOI 10.1016/j.fcr.2011.11.026
   KU HH, 1966, J RES NBS C ENG INST, VC 70, P263, DOI 10.6028/jres.070C.025
   Lal R, 2007, SOIL TILL RES, V93, P1, DOI 10.1016/j.still.2006.11.004
   Lal R, 2004, SCIENCE, V304, P1623, DOI 10.1126/science.1097396
   Lal R, 2004, GEODERMA, V123, P1, DOI 10.1016/j.geoderma.2004.01.032
   Lal R, 2015, J SOIL WATER CONSERV, V70, p55A, DOI 10.2489/jswc.70.3.55A
   Lal Rattan, 2013, Ecohydrology & Hydrobiology, V13, P8, DOI 10.1016/j.ecohyd.2013.03.006
   Mafongoya P, 2016, AGR ECOSYST ENVIRON, V220, P211, DOI 10.1016/j.agee.2016.01.017
   Martinsen V, 2017, AGR ECOSYST ENVIRON, V241, P168, DOI 10.1016/j.agee.2017.03.010
   McNeill AM., 2007, Nutrient Cycling in Terrestrial Ecosystems, P37, DOI DOI 10.1007/978-3-540-68027-7_2
   Minasny B, 2017, GEODERMA, V292, P59, DOI 10.1016/j.geoderma.2017.01.002
   Mloza-Banda HR, 2016, J ARID ENVIRON, V127, P7, DOI 10.1016/j.jaridenv.2015.11.001
   Mutsamba EF, 2016, CROP PROT, V82, P60, DOI 10.1016/j.cropro.2016.01.004
   Nyamangara J, 2014, SOIL USE MANAGE, V30, P550, DOI 10.1111/sum.12149
   Nyamangara J, 2013, SOIL TILL RES, V126, P19, DOI 10.1016/j.still.2012.07.018
   Obia A, 2017, SOIL TILL RES, V170, P114, DOI 10.1016/j.still.2017.03.009
   Obia A, 2016, SOIL TILL RES, V155, P35, DOI 10.1016/j.still.2015.08.002
   Olsen S. R., 1982, Methods of soil analysis. Part 2. Chemical and microbiological properties, P403
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   Pisante M., 2015, Conservation Agriculture, P579, DOI [DOI 10.1007/978-3-319-11620-422, 10.1007/978-3-319-11620-4_22]
   Pittelkow CM, 2015, NATURE, V517, P365, DOI 10.1038/nature13809
   Poulton P, 2018, GLOBAL CHANGE BIOL, V24, P2563, DOI 10.1111/gcb.14066
   Powlson DS, 2016, AGR ECOSYST ENVIRON, V220, P164, DOI 10.1016/j.agee.2016.01.005
   Powlson DS, 2014, NAT CLIM CHANGE, V4, P678, DOI 10.1038/NCLIMATE2292
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   SCHOLLENBERGER CJ, 1945, SOIL SCI, V59, P13, DOI 10.1097/00010694-194501000-00004
   Six J, 2002, PLANT SOIL, V241, P155, DOI 10.1023/A:1016125726789
   Sommer R, 2018, AGR ECOSYST ENVIRON, V254, P82, DOI 10.1016/j.agee.2017.11.004
   Sparling G, 1998, SOIL BIOL BIOCHEM, V30, P1469, DOI 10.1016/S0038-0717(98)00040-6
   Steward PR, 2018, AGR ECOSYST ENVIRON, V251, P194, DOI 10.1016/j.agee.2017.09.019
   Thierfelder C, 2012, SOIL USE MANAGE, V28, P209, DOI 10.1111/j.1475-2743.2012.00406.x
   Thierfelder C, 2016, AGR ECOSYST ENVIRON, V222, P112, DOI 10.1016/j.agee.2016.02.009
   Thierfelder C, 2015, RENEW AGR FOOD SYST, V30, P328, DOI 10.1017/S1742170513000550
   Thierfelder C, 2013, SOIL TILL RES, V126, P246, DOI 10.1016/j.still.2012.09.002
   Umar B. B., 2011, Journal of Agricultural Science (Toronto), V3, P50
   VANBREEMEN N, 1984, NATURE, V307, P599, DOI 10.1038/307599a0
   von Lützow M, 2007, SOIL BIOL BIOCHEM, V39, P2183, DOI 10.1016/j.soilbio.2007.03.007
   Wang QK, 2011, APPL SOIL ECOL, V47, P210, DOI 10.1016/j.apsoil.2010.12.004
   Wendt JW, 2013, EUR J SOIL SCI, V64, P58, DOI 10.1111/ejss.12002
NR 60
TC 14
Z9 14
U1 7
U2 78
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD APR 10
PY 2019
VL 660
BP 97
EP 104
DI 10.1016/j.scitotenv.2018.12.452
PG 8
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA HK2FV
UT WOS:000457725700011
PM 30639722
OA Green Accepted
DA 2025-01-10
ER

PT S
AU Onoja, AO
   Abraha, AZ
   Girma, A
   Achike, AI
AF Onoja, Anthony O.
   Abraha, Amanuel Z.
   Girma, Atkilt
   Achike, Anthonia I.
BE Castro, P
   Azul, AM
   Filho, WL
   Azeiteiro, UM
TI Climate-Smart Agricultural Practices (CSA) Adoption by Crop Farmers in
   Semi-arid Regions of West and East Africa: Evidence from Nigeria and
   Ethiopia
SO CLIMATE CHANGE-RESILIENT AGRICULTURE AND AGROFORESTRY: ECOSYSTEM
   SERVICES AND SUSTAINABILITY
SE Climate Change Management
LA English
DT Article; Book Chapter
DE Agroforestry; Climate smart agriculture; Climate change; Farming
   systems; Multiple cropping
ID WATER CONSERVATION; ADAPTATION; SOIL
AB The study was designed to scientifically identify two analogous African sites in semi-arid regions experiencing climate change so as to share their common experiences and then document CSA practices adopted in these regions. It identified analogous sites in Nigeria and Ethiopia for the purpose of studying their climate change adaptation experiences; assessed the socio-economic attributes of crop farmers in the semi-arid regions of these countries under stress and risk of climate change; ascertained the perception of crop farmers on climate change risks in the areas and then described the CSAs adopted in the two analogous sites. Identification of sites were done using GIS tool called CCAFs. Then 120 crop farmers each were randomly selected from the two countries (240 farmers) in a stratified manner. Primary data were collected with the aid of Focus Group Discussion method, a set of structured questionnaire and interview schedule after validating the questionnaire. Data collected were analyzed using descriptive statistics and ranking techniques; analysis of variance and t test. It was found that the socioeconomic attributes of farmers in Ethiopia and Nigerian farms varied especially with respect to food assess, types of crops cultivated, household size, education and extension contacts even though major crops in the regions were similar (sorghum, maize, millet and sesame). The two countries had similarities in the adoption of CSAs with the most common CSAs being crop rotation, agro-forestry, adoption of water management techniques, terracing/bunding and contour cropping. In Nigerian farms, while changing of planting dates (76%), diversification of crops (71%) and planting of high resistant varieties (82%) were common CSAs adopted by the farmers, Ethiopian farmers did not adopt these on a high scale. There was no difference in rate of adoption of CSAs in the two countries. It was recommended that farmers should be assisted to build capacities in applying more reliable CSAs such as use of drought tolerant varieties of seeds, improved water management techniques, and to have better access to early warning information on climate; irrigation facilities and finance.
C1 [Onoja, Anthony O.] Univ Port Harcourt, Dept Agr Econ & Extens, Port Harcourt, Nigeria.
   [Abraha, Amanuel Z.; Girma, Atkilt] Mekelle Univ, Inst Climate & Soc, Mekelle, Ethiopia.
   [Achike, Anthonia I.] Univ Nigeria, Dept Agr Econ, Nsukka, Nigeria.
   [Abraha, Amanuel Z.; Girma, Atkilt] Mekelle Univ, Dept Land Resources Management & Environm Protect, Mekelle, Ethiopia.
C3 University of Port Harcourt; Mekelle University; University of Nigeria;
   Mekelle University
RP Onoja, AO (corresponding author), Univ Port Harcourt, Dept Agr Econ & Extens, Port Harcourt, Nigeria.
EM tonyojonimi@gmail.com
RI Abraha, Amanuel Zenebe/JFA-0811-2023
OI ABRAHA, Amanuel Zenebe/0000-0001-6571-9065; Onoja,
   Anthony/0000-0003-2864-1574
FU TRECC Africa (An Intra ACP Training) programme based in Stellenbosch
   University
FX The researchers are very grateful to TRECC Africa (An Intra ACP
   Training) programme based in Stellenbosch University, for the fund and
   opportunity provided to conduct this study via its Ph.D. research
   exchange scholarship programme on Transdisciplinary Knowledge in climate
   change studies for the 2014/2015 batch awarded to the Principal
   Investigator, Anthony Ojonimi Onoja as a Ph.D. researcher at the
   Department of Agricultural Economics, University of Nigeria, Nsukka. We
   are also grateful to the university of the Principal Investigator,
   University of Port Harcourt, Nigeria, for releasing him to do the
   research and training. Thanks too, the Institute of Climate and Society,
   Mekelle University for providing some logistic support for the success
   of this research.
CR Acquah, 2011, AGRIS, V3, P31
   Anley Y, 2007, LAND DEGRAD DEV, V18, P289, DOI 10.1002/ldr.775
   [Anonymous], SLM WOR TIGR REG
   [Anonymous], 2010, STATE FOOD INSECURIT
   [Anonymous], 2004, AM J AGR EC
   [Anonymous], 2010, CLIM SMART AGR POL P
   Arango D, 2014, CONCEPT CLIMATE SCEN
   Ati OF, ARE WE EXPERIENCING
   Aynsau A, 2007, ECOL ECON, V61, P294, DOI 10.1016/j.ecolecon.2006.01.014
   Charles N, 2007, 00714 IFPRI
   Climate Change Agriculture and Food Security CCAFS, 2014, CLIM AN
   Deressa T, ANAL PERCEPTION ADAP
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Deressa TT, 2008, Discussion paper 00798
   Diao X, 2007, 00695 IFPRI
   ECOWAS-SWAC/OECD/CILSS, 2008, ENV SER
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   Food and Agricultural Organization FAO, 1996, FAO GLOB INF EARL WA
   Fosu-Mensah B., 2010, WORLD FOOD SYST C TR
   Gebrehiwot T, 2013, ENVIRON MANAGE, V52, P29, DOI 10.1007/s00267-013-0039-3
   Gornall J, 2010, PHILOS T R SOC B, V365, P2973, DOI 10.1098/rstb.2010.0158
   James SJ, 2013, J AGR SCI, V5
   Kaliba ARM, 2009, 42 U ARK PIN BLUFF, P493
   Maddison D., 2006, The perception of and adaptation to climate change in Africa
   Mengistu D. K., 2011, Agricultural Sciences, V2, P138, DOI 10.4236/as.2011.22020
   Nwanya SC, 2013, CLIMATE CHANGE REALI, DOI DOI 10.5772/55225
   Onoja AO, 2014, THESIS U NIGERIA NSU
   Onoja AO, 2014, 17 ICABR C BOOK RES
   Onyeneke R, 2010, COMMERCIAL AGR BANKI, P369
   Sarr B, 2012, ATMOS SCI LETT, V13, P108, DOI 10.1002/asl.368
   Spielman DJ, 2013, IFPRI 2013 GLOBAL FO, P44
   Temesgen D, 2008, 806 IFPRI
   United Nations Economic Commission for Africa UNECA, 2014, KEEP CLIM IMP BAY 6
   United Nations Economic Commission for Africa UNECA, 2014, CONC NOT 9 AFR DEV F
   Walker PA, 2005, PROG HUM GEOG, V29, P73, DOI 10.1191/0309132505ph530pr
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   You GJY, 2011, CAN AFRICAN AGR ADAP
NR 37
TC 5
Z9 5
U1 0
U2 7
PU SPRINGER-VERLAG BERLIN
PI BERLIN
PA HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
SN 1610-2010
BN 978-3-319-75004-0; 978-3-319-75003-3
J9 CLIM CHANG MANAG
PY 2019
BP 89
EP 113
DI 10.1007/978-3-319-75004-0_6
D2 10.1007/978-3-319-75004-0
PG 25
WC Agronomy; Green & Sustainable Science & Technology; Ecology; Forestry
WE Book Citation Index – Science (BKCI-S)
SC Agriculture; Science & Technology - Other Topics; Environmental Sciences
   & Ecology; Forestry
GA BQ8FX
UT WOS:000620171600007
DA 2025-01-10
ER

PT J
AU Ndhleve, S
   Nakin, MDV
   Longo-Mbenza, B
AF Ndhleve, S.
   Nakin, M. D. V.
   Longo-Mbenza, B.
TI Impacts of supplemental irrigation as a climate change adaptation
   strategy for maize production: a case of the Eastern Cape Province of
   South Africa
SO WATER SA
LA English
DT Article
DE agronomic practices; climatic hazards; supplemental irrigation;
   semi-arid areas
ID WATER PRODUCTIVITY; FARMING SYSTEMS; YIELD; MANAGEMENT
AB Dry spells and climatic hazards are responsible for maize output decline, sometimes to levels below potential yield levels. There is a pressing need to reduce the gap between actual and potential maize yield/ha, especially among farmers in semi-arid regions. This present study examines the potential role of supplemental irrigation and its differential impact on maize yield in the Eastern Cape Province of South Africa. In this study, maize yield data were generated from information recorded over a period of 20 years by farmers in Ntabankulu through cross-sectional interviews with 124 randomly-selected farming households. Maize yields for interviewed farmers were analysed for each of the experienced climatic hazards, for yield decline per ha and preferable adaptation strategies. Maize yield analyses show a maximum ceiling/attainable yield of 0.234 t/ha and average farm yield of 0.146 t/ha. Floods or hailstorms cause 75% decline in maize yield/ha and there was no significant difference between farmers practising irrigation and those practising dryland farming (P > 0.05). Low/no rains throughout the season; delay or low onset of rainfall and a rain-break for a week or more in a season results in 75%; 54% and 50.5% decline in maize yield/ha, respectively. On a scale of 1 to 10, farmers highly rank practicing supplementary irrigation (8.4) and change of planting date (7.8) as important adaptation strategies. Rescheduling planting date from the traditional planting times to earlier or later planting dates, assisted by use of weather reports and forecasting, to some extent curbs the impact of delays or slow onset of rainfall on yield. Supplemental irrigation is instrumental in reducing the impact of midseason drought (rains break for a week) and light rainfall throughout the season. Analyses of actual yields and yield decline against each of the experienced climatic hazards provided insight into management possibilities to stabilize maize output.
C1 [Ndhleve, S.; Nakin, M. D. V.; Longo-Mbenza, B.] Walter Sisulu Univ, Risk & Vulnerabil Assessment Ctr, Nelson Mandela Dr Campus,Private Bag X1, ZA-5100 Mthatha, South Africa.
C3 Walter Sisulu University
RP Ndhleve, S (corresponding author), Walter Sisulu Univ, Risk & Vulnerabil Assessment Ctr, Nelson Mandela Dr Campus,Private Bag X1, ZA-5100 Mthatha, South Africa.
EM ndhleve@gmail.com
RI Nakin, Motebang/ABE-4021-2020
OI Ndhleve, Simbarashe/0000-0003-0428-4824; Nakin,
   Motebang/0000-0002-6382-3165
FU DST/NRF
FX The authors gratefully acknowledge DST/NRF for financing the research
   activities and Walter Sisulu University's Risk and Vulnerability Science
   Centre for providing enumerators and transport during data collection.
CR Akpalu W., 2008, IFPRI Paper 843
   [Anonymous], 2007, INT FOOD POLICY RES
   [Anonymous], 2007, Climate Change 2007: The Scientific Basis
   [Anonymous], 1988, RISE FALL S AFRICAN
   [Anonymous], 2007, LIVELIHOODS LANDSCAP
   Archer DR, 2010, HYDROL EARTH SYST SC, V14, P1669, DOI 10.5194/hess-14-1669-2010
   Barrios S, 2006, J URBAN ECON, V60, P357, DOI 10.1016/j.jue.2006.04.005
   Bembridge T.J., 1984, THESIS
   Blignaut J, 2009, S AFR J SCI, V105, P61, DOI 10.1590/s0038-23532009000100022
   Cairns JE, 2012, ADV AGRON, V114, P1, DOI 10.1016/B978-0-12-394275-3.00006-7
   CHISHAKWE NE, 2010, SO AFRICA SUBR UNPUB
   Cooper PJM, 2008, AGR ECOSYST ENVIRON, V126, P24, DOI 10.1016/j.agee.2008.01.007
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Di Falco S, 2013, LAND ECON, V89, P743, DOI 10.3368/le.89.4.743
   Duvick DN, 1999, CROP SCI, V39, P1622, DOI 10.2135/cropsci1999.3961622x
   Fanadzo M, 2010, WATER SA, V36, P27
   [Field C.B. IPCC. IPCC.], 2011, Workshop Report of the Intergovernmental Panel on Climate Change Workshop on Impacts of Ocean Acidification on Marine Biology and Ecosystems, DOI DOI 10.1093/WENTK/9780199996698.003.0009
   Fischer R. A., 2009, How to feed the World in 2050. Proceedings of a technical meeting of experts, Rome, Italy, 24-26 June 2009, P1
   Foster V., 2008, 15 AICD WORLD BANK, P15, DOI 11804244/Main-report
   Fosu-Mensah B. Y., 2012, Environment Development and Sustainability, V14, P495, DOI 10.1007/s10668-012-9339-7
   Grassini P, 2011, FIELD CROP RES, V120, P142, DOI 10.1016/j.fcr.2010.09.012
   Harrison L, 2011, CLIM RES, V46, P211, DOI 10.3354/cr00979
   Intergovernmental Panel on Climate Change (IPCC), 2014, CLIM CHANG 2014 WORK
   MAFEJE A, 1988, CODESRIA B, V1
   Mandleni B., 2011, Journal of Agricultural Science (Toronto), V3, P258, DOI 10.5539/jas.v3n3p258
   Meza FJ, 2009, CLIMATIC CHANGE, V94, P143, DOI [10.1007/s10584-009-9544-z, 10.1007/s10584-009-9544-Z]
   Nyong A., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P787, DOI 10.1007/s11027-007-9099-0
   Oweis T, 2006, AGR WATER MANAGE, V80, P57, DOI 10.1016/j.agwat.2005.07.004
   PINNSCHMIDT HO, 1997, APPL SYSTEM APPROACH, V2
   Sinyolo Sikhulumile, 2014, Water SA, V40, P145
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Tollenaar M, 2002, FIELD CROP RES, V75, P161, DOI 10.1016/S0378-4290(02)00024-2
   van Ittersum MK, 2013, FIELD CROP RES, V143, P4, DOI 10.1016/j.fcr.2012.09.009
   Wolf J, 2013, GLOBAL ENVIRON CHANG, V23, P548, DOI 10.1016/j.gloenvcha.2012.11.007
NR 34
TC 16
Z9 19
U1 3
U2 32
PU WATER RESEARCH COMMISSION
PI PRETORIA
PA PO BOX 824, PRETORIA 0001, SOUTH AFRICA
SN 0378-4738
EI 1816-7950
J9 WATER SA
JI Water SA
PD APR
PY 2017
VL 43
IS 2
BP 222
EP 228
DI 10.4314/wsa.v43i2.06
PG 7
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Water Resources
GA FE8AU
UT WOS:000408428800006
OA gold, Green Submitted
DA 2025-01-10
ER

PT C
AU Simonovic, SP
   Arunkumar, R
AF Simonovic, S. P.
   Arunkumar, R.
BE Schumann, AH
   Bloschl, G
   Castellarin, A
   Dietrich, J
   Grimaldi, S
   Haberlandt, U
   Montanari, A
   Rosbjerg, D
   Viglione, A
   Vorogushyn, S
TI Quantification of resilience to water scarcity, a dynamic measure in
   time and space
SO SPATIAL DIMENSIONS OF WATER MANAGEMENT - REDISTRIBUTION OF BENEFITS AND
   RISKS
SE Proceedings of the International Association of Hydrological Sciences
   (IAHS)
LA English
DT Proceedings Paper
CT 7th International Water Resources Management Conference of ICWRS
CY MAY 18-20, 2016
CL Bochum, GERMANY
SP ICWRS, Int Assoc Hydrol Sci
ID DEFINITION; SYSTEMS
AB There are practical links between water resources management, climate change adaptation and sustainable development leading to reduction of water scarcity risk and re-enforcing resilience as a new development paradigm. Water scarcity, due to the global change (population growth, land use change and climate change), is of serious concern since it can cause loss of human lives and serious damage to the economy of a region. Unfortunately, in many regions of the world, water scarcity is, and will be unavoidable in the near future. As the scarcity is increasing, at the same time it erodes resilience, therefore global change has a magnifying effect on water scarcity risk. In the past, standard water resources management planning considered arrangements for prevention, mitigation, preparedness and recovery, as well as response. However, over the last ten years substantial progress has been made in establishing the role of resilience in sustainable development. Dynamic resilience is considered as a novel measure that provides for better understanding of temporal and spatial dynamics of water scarcity. In this context, a water scarcity is seen as a disturbance in a complex physical-socio-economic system. Resilience is commonly used as a measure to assess the ability of a system to respond and recover from a failure. However, the time independent static resilience without consideration of variability in space does not provide sufficient insight into system's ability to respond and recover from the failure state and was mostly used as a damage avoidance measure. This paper provides an original systems framework for quantification of resilience. The framework is based on the definition of resilience as the ability of physical and socio-economic systems to absorb disturbance while still being able to continue functioning. The disturbance depends on spatial and temporal perspectives and direct interaction between impacts of disturbance (social, health, economic, and other) and adaptive capacity of the system to absorb disturbance. Utility of the dynamic resilience is demonstrated through a single-purpose reservoir operation subject to different failure (water scarcity) scenarios. The reservoir operation is simulated using the system dynamics (SD) feedback-based object-oriented simulation approach.
C1 [Simonovic, S. P.; Arunkumar, R.] Univ Western Ontario, Dept Civil & Environm Engn, London, ON N6A 5B9, Canada.
C3 Western University (University of Western Ontario)
RP Simonovic, SP (corresponding author), Univ Western Ontario, Dept Civil & Environm Engn, London, ON N6A 5B9, Canada.
EM simonovic@uwo.ca
RI Arunkumar, R/A-4206-2013
OI Arunkumar, R/0000-0002-4211-7480
CR [Anonymous], 2005, VENT SYST VENS US GU
   Arunkumar R., 2012, Journal of The Institution of Engineers (India): Series A, V93, P111, DOI DOI 10.1007/S40030-012-0013-8
   Ayyub BM, 2014, RISK ANAL, V34, P340, DOI 10.1111/risa.12093
   Bruneau M, 2003, EARTHQ SPECTRA, V19, P733, DOI 10.1193/1.1623497
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Haimes YY, 2009, RISK ANAL, V29, P498, DOI 10.1111/j.1539-6924.2009.01216.x
   HASHIMOTO T, 1982, WATER RESOUR RES, V18, P14, DOI 10.1029/WR018i001p00014
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Simonovic S. P., 2013, British Journal of Environment and Climate Change, V3, P378, DOI 10.9734/BJECC/2013/2504
   Vugrin ED, 2010, SUSTAINABLE AND RESILIENT CRITICAL INFRASTRUCTURE SYSTEMS: SIMULATION, MODELING, AND INTELLIGENT ENGINEERING, P77, DOI 10.1007/978-3-642-11405-2_3
NR 10
TC 9
Z9 11
U1 2
U2 13
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLE 1E, GOTTINGEN, 37081, GERMANY
SN 2199-899X
J9 P INT ASS HYDROL SCI
PY 2016
VL 373
BP 13
EP 17
DI 10.5194/piahs-373-13-2016
PG 5
WC Engineering, Civil; Water Resources
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Engineering; Water Resources
GA BG6YP
UT WOS:000391006000003
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Tofa, AI
   Kamara, AY
   Mohamed, AML
   Garba, M
   Souley, AM
   Salissou, H
   Kapran, BI
   Abdoulaye, T
AF Tofa, Abdullahi I.
   Kamara, Alpha. Y.
   Mohamed, Ali M. L.
   Garba, Maman
   Souley, Abdoulkader M.
   Salissou, Hanarou
   Kapran, Balkissa I.
   Abdoulaye, Tahirou
TI Assessment of climate change impact and adaptation strategy for millet
   in the Sudano-Sahelian region of Niger
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Agriculture; Climate change; Millet yield; Food security; AEZs
ID PEARL-MILLET; AGRICULTURAL PRODUCTION; SELECTION
AB Pearl millet is an important food and fodder crop in West African semi-arid regions. Climate change is projected to have a significant impact on the productivity of the crops in these regions. Adaptation strategies to sustain agricultural production are therefore urgently required to sustain millet productivity. The Decision Support System for Agrotechnology Transfer (DSSAT) CERES-Millet model was used to assess the impact of climate change and adaptation strategies on millet in Niger. Three millet varieties and five sowing windows were evaluated as climate change adaptation strategies. We found that temperature and rainfall will increase in the future relative to baseline conditions. The impact of climate change varied with the agroecological zone (AEZ) with higher yield reduction in the Sahel than in the other AEZs. The yield of early-maturing variety (CHAKTI) is projected to decline by 30-72% in all locations and AEZs under all scenarios. Replacing the reference variety HKP with CHAKTI is projected to reduce yields by 35-39% in the Sudan AEZ, 24-32% in the Sudan Sahel AEZ, and 11-18% in the Sahel AEZs. Conversely, using H80-10GR is expected to improve yields by 0-1%, 2-3%, and 0-2% in the respective AEZs, indicating that H80-10GR can be used along with the reference variety (HKP) under future climate. The optimal sowing window for maximum yields under current conditions is consistently identified as June 15-21 across all AEZs, with yield declining significantly with delayed sowing. Future climate scenarios show different impacts by AEZ and climate scenarios. In Sudan AEZ, early sowing on June 1-14 can improve grain yield under RCP 4.5 but may lead to drastic declines by the end of the century under more severe RCP 8.5 conditions for all varieties. In Sudan-Sahel and Sahel AEZs, the optimal sowing window for all varieties is July 1-7 under all climate scenarios. Our results show that early maturity did not result in yield advantage under climate change.
C1 [Tofa, Abdullahi I.; Kamara, Alpha. Y.] Int Inst Trop Agr IITA, Kano 700241, Nigeria.
   [Mohamed, Ali M. L.; Garba, Maman; Salissou, Hanarou; Kapran, Balkissa I.] Int Inst Trop Agr IITA, Niamey 12404, Niger.
   [Garba, Maman; Souley, Abdoulkader M.] Inst Natl Rech Agron Niger INRAN, BP 429, Niamey, Niger.
   [Abdoulaye, Tahirou] Int Inst Trop Agr IITA, Bamako, Mali.
C3 CGIAR; International Institute of Tropical Agriculture (IITA)
RP Tofa, AI (corresponding author), Int Inst Trop Agr IITA, Kano 700241, Nigeria.
EM A.Tofa@cgiar.org
OI Tofa, Abdullahi Ibrahim/0000-0002-7617-4395
FU Norwegian Ministry of Foreign Affairs [NER-17/0005]
FX The Norwegian Ministry of Foreign Affairs funded this research through
   Climate Smart Agricultural Technologies (CSAT) project in Niger
   Republic. Grant number NER-17/0005.
CR Affoh R, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14020759
   Ahmed K, 2019, HYDROL EARTH SYST SC, V23, P4803, DOI 10.5194/hess-23-4803-2019
   Ali MGM, 2022, INT J BIOMETEOROL, V66, P971, DOI 10.1007/s00484-022-02253-x
   Alvar-Beltrán J, 2023, EUR J AGRON, V142, DOI 10.1016/j.eja.2022.126667
   Araya A, 2022, CLIM RISK MANAG, V36, DOI 10.1016/j.crm.2022.100436
   Ben Mohamed A, 2002, CLIMATIC CHANGE, V54, P327, DOI 10.1023/A:1016189605188
   Carr TW, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac61c8
   Chekole FC, 2023, J AGR FOOD RES, V11, DOI 10.1016/j.jafr.2022.100480
   Chisanga CB, 2020, FOOD ENERGY SECUR, V9, DOI 10.1002/fes3.231
   Defrance D, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187585
   FAOSTAT, 2022, Food and agriculture organization of the United Nations
   Faye A, 2022, REG ENVIRON CHANGE, V22, DOI 10.1007/s10113-022-01940-0
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Ganyo KK, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9110697
   Gaoh BSB, 2023, AGRONOMY-BASEL, V13, DOI 10.3390/agronomy13010166
   Garba M, 2024, CABI AGR BIOSCI, V5, DOI 10.1186/s43170-024-00254-x
   Gebrechorkos SH, 2018, HYDROL EARTH SYST SC, V22, P4547, DOI 10.5194/hess-22-4547-2018
   GYGA Niger, 2016, Global yield gap atlas Niger
   Hoogenboom G., 2024, Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.8.2
   ICRISATInternational Crop Research Institute for the Semi-Arid Tropics, 2022, INT MILL FEST FESTIM
   Jiang R, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-020-79988-3
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Joseph J, 2020, CCAFS Working Paper no. 322, DOI [10.13140/RG.2.2.27548.31367, DOI 10.13140/RG.2.2.27548.31367]
   Kamara AY, 2023, HELIYON, V9, DOI 10.1016/j.heliyon.2023.e17829
   LeBarbe L, 1997, J HYDROL, V188, P43, DOI 10.1016/S0022-1694(96)03154-X
   Li Z, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15174345
   Lobell DB, 2008, ENVIRON RES LETT, V3, DOI 10.1088/1748-9326/3/3/034007
   Mangani R, 2019, REG ENVIRON CHANGE, V19, P1441, DOI [10.1007/s10113-019-01486-8, 10.1007/s10113-019-01500-z]
   Mavindidze D., 2020, IRON PEARL MILLET CR
   Mohamed AML, 2023, J CROP IMPROV, V37, P41, DOI 10.1080/15427528.2022.2048764
   Ndjeunga J., 2000, WORKING PAPER SERIES, V3
   Nwajei Sunday Ebonka, 2019, Acta Agriculturae Slovenica, V114, P169, DOI 10.14720/aas.2019.114.2.3
   Omanya GO, 2007, EXP AGR, V43, P5, DOI 10.1017/S0014479706004248
   Potsdam Institute and GIZ, 2021, Climate risk profile: Niger
   Rezaei EE, 2014, EUR J AGRON, V55, P77, DOI 10.1016/j.eja.2014.02.001
   Rosenzweig C, 2013, AGR FOREST METEOROL, V170, P166, DOI 10.1016/j.agrformet.2012.09.011
   Seo SN, 2009, ENVIRON RESOUR ECON, V43, P313, DOI 10.1007/s10640-009-9270-z
   Silungwe FR, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11164330
   Singh P, 2017, SCI TOTAL ENVIRON, V601, P1226, DOI 10.1016/j.scitotenv.2017.06.002
   SIVAKUMAR MVK, 1992, CLIMATIC CHANGE, V20, P297, DOI 10.1007/BF00142424
   Soler CMT, 2008, J AGR SCI-CAMBRIDGE, V146, P445, DOI 10.1017/S0021859607007617
   Srivastava A, 2022, Ecological footprints of climate change, DOI [10.1007/978-3-031-15501-72, DOI 10.1007/978-3-031-15501-72]
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Sultan B, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/1/014040
   Tofa AI, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-88277-6
   Ullah A, 2019, ENVIRON SCI POLLUT R, V26, P6745, DOI 10.1007/s11356-018-3925-7
   Van Duivenbooden N, 2002, CLIMATIC CHANGE, V54, P349, DOI 10.1023/A:1016188522934
   Vigouroux Y, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019563
   World Bank, 2021, Current Climate
   World Bank, 2017, Report No. 115661-NE, P126
   Zhang ZX, 2019, IND CROP PROD, V131, P41, DOI 10.1016/j.indcrop.2019.01.028
NR 51
TC 0
Z9 0
U1 3
U2 3
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD DEC
PY 2024
VL 24
IS 4
AR 151
DI 10.1007/s10113-024-02313-5
PG 15
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA H8G6W
UT WOS:001325774000001
DA 2025-01-10
ER

PT J
AU Dadrasi, A
   Soltani, E
   Makowski, D
   Lamichhane, JR
AF Dadrasi, Amir
   Soltani, Elias
   Makowski, David
   Lamichhane, Jay Ram
TI Does shifting from normal to early or late sowing dates provide yield
   benefits? A global meta-analysis
SO FIELD CROPS RESEARCH
LA English
DT Article
DE Climate; Sowing date adaptation; Seedling emergence; Plant biomass; Pest
   and disease; Crop yield
ID SPRING MALTING BARLEY; PLANTING DATE; CLIMATE-CHANGE; USE EFFICIENCY;
   SEEDING RATE; GRAIN-YIELD; SUPPLEMENTAL IRRIGATION; PHYSIOLOGICAL
   TRAITS; MOTH LEPIDOPTERA; CROPPING SYSTEM
AB Context: Shifting the sowing date has been proposed as a simple agronomic lever to enhance crop establishment, growth, and yield, which could be a climate change adaptation strategy. Objective or research question: Previous research showed that the experimental data assessing the effect of sowing date are not consistent and vary between trials and publications. We hypothesized that the difference in pedoclimatic conditions and management practices may be responsible for the contrasting impact of sowing dates on crop establishment, growth, and yield. Methods: A global meta-analysis of 94 studies and 3145 observations was conducted to quantify the effect of covariates related to crop types and pedoclimatic conditions in relation to early and late sowing dates compared to normal sowing dates. Results: On average, early sowing significantly increased seedling emergence vigor (53 %, confidence interval (95 %) = [49 %,58 %]) and disease and pest control (88 % [20 %,195 %]) without significant effect on plant biomass (2 % [-2 %,5 %]) and yield (-10 % [-20 %, +0.8 %]) compared to normal sowing date. In contrast, late sowing had no significant effect on seedling emergence vigor (28 %[-4 %,72 %]) or disease and pest control (14 %[-1 %,31 %]) while it significantly decreased plant biomass (-21 %[-21.42 %,-21.12 %]) and yield (-24 % [-28 %, -19 %]) compared to normal sowing date, in particular when the sowing delay exceeded three weeks and when the average minimum temperature was above 13 degrees C during the growing season. Conclusions: Early sowing does not affect crop productivity while late sowing reduces crop yield. Shifting from normal to late sowing dates may lead to yield losses exceeding 20 %, especially in warm conditions. Implications or significance: This study offers an important insight into the potential of crop yield improvement by adjusting sowing dates to aid decision-making in relation to specific pedoclimatic conditions and cropping practices.
C1 [Dadrasi, Amir] Charles Univ Environm Ctr, Prague, Czech Republic.
   [Soltani, Elias] Univ Tehran, Coll Aburaihan, Dept Agron & Plant Breeding Sci, Tehran, Iran.
   [Makowski, David] Univ Paris Saclay, AgroParisTech, INRAE, UMR 518 MIA, F-91120 Palaiseau, France.
   [Lamichhane, Jay Ram] Univ Toulouse, INRAE, UMR AGIR, Castanet Tolosan, France.
C3 Charles University Prague; University of Tehran; Universite Paris
   Saclay; AgroParisTech; INRAE; INRAE; Universite de Toulouse
RP Lamichhane, JR (corresponding author), Univ Toulouse, INRAE, UMR AGIR, Castanet Tolosan, France.
EM jay-ram.lamichhane@inrae.fr
RI Makowski, David/V-4233-2019; Soltani, Elias/AAP-5571-2020; Dadrasi,
   Amir/LVR-8902-2024
FU Soystainable project
FX This study was partially supported by the Soystainable project (please
   see the acknowledgement section for detailed information).
CR Abbas G, 2017, AGR FOREST METEOROL, V247, P42, DOI 10.1016/j.agrformet.2017.07.012
   Abendroth LJ, 2017, CROP FORAGE TURF MAN, V3, DOI 10.2134/cftm2017.02.0015
   Baldwin B., 1980, Fabis, V2, P39
   Balwinder-Singh, 2016, FIELD CROP RES, V197, P83, DOI 10.1016/j.fcr.2016.08.016
   Bange MP, 1997, AUST J AGR RES, V48, P231, DOI 10.1071/A96079
   Bassu S, 2009, FIELD CROP RES, V111, P109, DOI 10.1016/j.fcr.2008.11.002
   Bastidas AM, 2008, CROP SCI, V48, P727, DOI 10.2135/cropsci2006.05.0292
   Basto S, 2015, PLANT ECOL, V216, P1163, DOI 10.1007/s11258-015-0499-z
   Bonelli LE, 2016, FIELD CROP RES, V198, P215, DOI 10.1016/j.fcr.2016.09.003
   Borenstein M., 2021, Introduction to meta-analysis
   Carta A, 2022, ANN BOT-LONDON, V129, P775, DOI 10.1093/aob/mcac037
   Caubel J, 2017, EUR J AGRON, V90, P53, DOI 10.1016/j.eja.2017.07.004
   Chatha E., 1999, Int J. Agric. Biol., V1, P250
   Chauhan R. S., 2000, Agricultural Science Digest, V20, P36
   Chauhan R. S., 2000, Agricultural Science Digest, V20, P58
   Conry MJ, 1998, J AGR SCI, V130, P307, DOI 10.1017/S0021859698005267
   Cooper RL, 2003, FIELD CROP RES, V82, P27, DOI 10.1016/S0378-4290(03)00003-0
   Dai XL, 2017, CROP J, V5, P541, DOI 10.1016/j.cj.2017.05.003
   Danalatos NG, 2010, IND CROP PROD, V32, P231, DOI 10.1016/j.indcrop.2010.04.013
   Dandnaik B. P., 1996, International Arachis Newsletter, P29
   De Bruin JL, 2008, AGRON J, V100, P696, DOI 10.2134/agronj2007.0115
   Dhillon B. S., 2016, Current Advances in Agricultural Sciences, V8, P69
   Duncan JMA, 2015, GLOBAL CHANGE BIOL, V21, P1541, DOI 10.1111/gcb.12660
   Ehdaie B, 2001, FIELD CROP RES, V73, P47, DOI 10.1016/S0378-4290(01)00181-2
   Fernandez AL, 2012, AGRON J, V104, P1056, DOI 10.2134/agronj2012.0031
   Fountaine JM, 2010, PLANT PATHOL, V59, P330, DOI 10.1111/j.1365-3059.2009.02213.x
   Gallardo-Carrera A, 2007, SOIL TILL RES, V95, P207, DOI 10.1016/j.still.2007.01.001
   Getachew E., 2015, Adv. Res. J. Educ. Res. Rev.
   Gill JS, 2000, PLANT SOIL, V221, P113, DOI 10.1023/A:1004606016745
   GRAU CR, 1994, J PROD AGRIC, V7, P347, DOI 10.2134/jpa1994.0347
   Hall R.G., 2009, Corn planting guide, P13
   Hassan M.T., 2006, Ind. Cotton, V3, P367
   Hassan M.T., 2005, Ind. Cotton, V2, P251, DOI [10.3923/pjbs.2000.1901.1903, DOI 10.3923/PJBS.2000.1901.1903]
   Hu Q, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9040615
   Husson O, 2021, PLANT SOIL, V466, P391, DOI 10.1007/s11104-021-05047-z
   Iqbal J., 2012, Pakistan Journal of Science, V64, P59
   Iqbal M., 2010, AAB Bioflux, V2, P25
   Iqbal M, 2011, AFR J BIOTECHNOL, V10, P7367
   Kantolic AG, 2001, FIELD CROP RES, V72, P109, DOI 10.1016/S0378-4290(01)00168-X
   Khaeim H, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14073887
   Knapp S, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-05956-1
   Knodel JJ, 2011, J ECON ENTOMOL, V104, P1236, DOI 10.1603/EC11012
   Kumagai E, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10010066
   Kumar S, 2018, RENEW SUST ENERG REV, V90, P160, DOI 10.1016/j.rser.2018.03.049
   Kumar V, 2006, EXP AGR, V42, P19, DOI 10.1017/S0014479705003042
   LaBeaud AD, 2008, PLOS NEGLECT TROP D, V2, DOI 10.1371/journal.pntd.0000247
   Landa BB, 2004, PHYTOPATHOLOGY, V94, P946, DOI 10.1094/PHYTO.2004.94.9.946
   LAUNDERS T E, 1971, Australian Journal of Experimental Agriculture and Animal Husbandry, V11, P39, DOI 10.1071/EA9710039
   Lee KiWon Lee KiWon, 2019, Journal of the Korean Society of Grassland and Forage Science, V39, P148
   Li CJ, 2020, NAT PLANTS, V6, P653, DOI 10.1038/s41477-020-0680-9
   LUESCHEN WE, 1992, J PROD AGRIC, V5, P254, DOI 10.2134/jpa1992.0254
   Ma SC, 2018, FIELD CROP RES, V221, P166, DOI 10.1016/j.fcr.2018.02.028
   Makowski D., 2019, EXPT NETWORK META AN, DOI [DOI 10.1007/978-94-024-1696-1, 10.1007/978-94-024-1696-1_1]
   Maleki K, 2024, AGR FOREST METEOROL, V346, DOI 10.1016/j.agrformet.2023.109865
   MARCELLOS H, 1986, AUST J EXP AGR, V26, P493, DOI 10.1071/EA9860493
   Mariani L, 2017, HORTICULTURAE, V3, DOI 10.3390/horticulturae3040052
   Masin R, 2010, WEED RES, V50, P120, DOI 10.1111/j.1365-3180.2010.00762.x
   Matsuo N, 2016, PLANT PROD SCI, V19, P370, DOI 10.1080/1343943X.2016.1155417
   McDonald AJ, 2022, NAT FOOD, V3, P542, DOI 10.1038/s43016-022-00549-0
   McDonald GK, 2009, FIELD CROP RES, V111, P11, DOI 10.1016/j.fcr.2008.10.001
   Médiène S, 2011, AGRON SUSTAIN DEV, V31, P491, DOI 10.1007/s13593-011-0009-1
   Mourtzinis S, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-38971-3
   Muluneh A, 2017, J AGR SCI-CAMBRIDGE, V155, P703, DOI 10.1017/S0021859616000897
   Mushtaq Ali Mushtaq Ali, 2004, International Journal of Agriculture and Biology, V6, P644
   Nouri M, 2017, AGR WATER MANAGE, V186, P108, DOI 10.1016/j.agwat.2017.03.004
   OSETO CY, 1989, J ECON ENTOMOL, V82, P910, DOI 10.1093/jee/82.3.910
   Palomo Gil A., 2000, ITEA Produccion Vegetal, V96, P95
   Pandey GC, 2015, PHYSIOL MOL BIOL PLA, V21, P93, DOI 10.1007/s12298-014-0267-x
   Patane C., 2012, Ital. J. Agron., V7, P30, DOI [10.4081/IJA.2012.E30, DOI 10.4081/IJA.2012.E30]
   Pedersen P, 2004, AGRON J, V96, P1372, DOI 10.2134/agronj2004.1372
   Pettersson CG, 2007, EUR J AGRON, V27, P205, DOI 10.1016/j.eja.2007.04.002
   Philibert A, 2012, AGR ECOSYST ENVIRON, V148, P72, DOI 10.1016/j.agee.2011.12.003
   Pulakkatu-Thodi I, 2014, J ECON ENTOMOL, V107, P646, DOI 10.1603/EC13395
   Rajinder-Pal, 2018, INT J PLANT PROD, V12, P95, DOI 10.1007/s42106-018-0010-6
   Ren AX, 2019, J INTEGR AGR, V18, P33, DOI [10.1016/S2095-3119(18)61980-X, 10.1016/s2095-3119(18)61980-x]
   Santiago-Arenas R, 2022, J SOIL SCI PLANT NUT, V22, P2805, DOI 10.1007/s42729-022-00847-3
   Schwarte AJ, 2005, AGRON J, V97, P1333, DOI 10.2134/agronj2005.0010
   Schwarting HN, 2015, J KANSAS ENTOMOL SOC, V88, P411, DOI 10.2317/0022-8567-88.4.411
   SEWELL GWF, 1992, ANN APPL BIOL, V121, P199, DOI 10.1111/j.1744-7348.1992.tb04001.x
   Shah T, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9110757
   Siddique KHM, 1998, AUST J AGR RES, V49, P613, DOI 10.1071/A97128
   SILIM SN, 1991, EXP AGR, V27, P145, DOI 10.1017/S0014479700018809
   Avelar RIS, 2018, J SEED SCI, V40, P146, DOI 10.1590/2317-1545v40n2185719
   Soltani E, 2018, PLANT ECOL, V219, P1283, DOI 10.1007/s11258-018-0878-3
   Sotelo PA, 2014, J ECON ENTOMOL, V107, P1969, DOI 10.1603/EC14055
   Spink JH, 2000, ANN APPL BIOL, V137, P179, DOI 10.1111/j.1744-7348.2000.tb00049.x
   Srivastava RK, 2018, FIELD CROP RES, V221, P339, DOI 10.1016/j.fcr.2017.06.019
   Subedi B, 2023, J AGR FOOD RES, V14, DOI 10.1016/j.jafr.2023.100733
   Tamm L, 2010, EUR J PLANT PATHOL, V127, P465, DOI 10.1007/s10658-010-9612-2
   Tavakkoli AR, 2004, AGR WATER MANAGE, V65, P225, DOI 10.1016/j.agwat.2003.09.001
   Thapa R, 2018, J ENVIRON QUAL, V47, P1400, DOI 10.2134/jeq2018.03.0107
   Tsimba R, 2013, FIELD CROP RES, V150, P135, DOI 10.1016/j.fcr.2013.05.028
   Turner NC, 2004, J EXP BOT, V55, P2413, DOI 10.1093/jxb/erh154
   Viechtbauer W, 2010, J STAT SOFTW, V36, P1, DOI 10.18637/jss.v036.i03
   Waha K, 2013, GLOBAL ENVIRON CHANG, V23, P130, DOI 10.1016/j.gloenvcha.2012.11.001
   Wang WC, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.814755
   WARDLAW IF, 1989, AUST J AGR RES, V40, P15, DOI 10.1071/AR9890015
   Yang Ning Yang Ning, 2014, Transactions of the Chinese Society of Agricultural Engineering, V30, P81
   Yau SK, 2013, ARCH AGRON SOIL SCI, V59, P1659, DOI 10.1080/03650340.2013.766322
   Yeates SJ, 2010, FIELD CROP RES, V116, P278, DOI 10.1016/j.fcr.2010.01.005
   Zhang MH, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e07436
   Zhang ZX, 2019, AGR FOREST METEOROL, V269, P257, DOI 10.1016/j.agrformet.2019.02.027
NR 102
TC 0
Z9 0
U1 16
U2 16
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0378-4290
EI 1872-6852
J9 FIELD CROP RES
JI Field Crop. Res.
PD NOV 1
PY 2024
VL 318
AR 109600
DI 10.1016/j.fcr.2024.109600
EA SEP 2024
PG 14
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA I2C7Q
UT WOS:001328393300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Hamlet, AF
   Ehsani, N
   Tank, JL
   Silver, Z
   Byun, K
   Mahl, UH
   Speir, SL
   Trentman, MT
   Royer, TV
AF Hamlet, Alan F.
   Ehsani, Nima
   Tank, Jennifer L.
   Silver, Zachariah
   Byun, Kyuhyun
   Mahl, Ursula H.
   Speir, Shannon L.
   Trentman, Matt T.
   Royer, Todd V.
TI Effects of climate and winter cover crops on nutrient loss in
   agricultural watersheds in the midwestern US
SO CLIMATIC CHANGE
LA English
DT Article
DE Nutrient pollution, Agricultural watersheds; Nitrate losses; Soluble
   reactive phosphorus losses; Climate variability; Cover crops; Climate
   change; Adaptation; SWAT
ID HYDROLOGIC EXTREMES; GREAT-LAKES; SOIL; REGION; IMPACT
AB Nutrient runoff from agricultural regions of the midwestern U.S. corn belt has degraded water quality in many inland and coastal water bodies such as the Great Lakes and Gulf of Mexico. Under current climate, observational studies have shown that winter cover crops can reduce dissolved nitrogen and phosphorus losses from row-cropped agricultural watersheds, but performance of cover crops in response to climate variability and climate change has not been systematically evaluated. Using the Soil & Water Assessment Tool (SWAT) model, calibrated using multiple years of field-based data, we simulated historical and projected future nutrient loss from two representative agricultural watersheds in northern Indiana, USA. For 100% cover crop coverage, historical simulations showed a 31-33% reduction in nitrate (NO3-) loss and a 15-23% reduction in Soluble Reactive Phosphorus (SRP) loss in comparison with a no-cover-crop baseline. Under climate change scenarios, without cover crops, projected warmer and wetter conditions strongly increased nutrient loss, especially in the fallow period from Oct to Apr when changes in infiltration and runoff are largest. In the absence of cover crops, annual nutrient losses for the RCP8.5 2080s scenario were 26-38% higher for NO3-, and 9-46% higher for SRP. However, the effectiveness of cover crops also increased under climate change. For an ensemble of 60 climate change scenarios based on CMIP5 RCP4.5 and RCP8.5 scenarios, 19 out of 24 ensemble-mean simulations of future nutrient loss with 100% cover crops were less than or equal to historical simulations with 100% cover crops, despite systematic increases in nutrient loss due to climate alone. These results demonstrate that planting winter cover crops over row-cropped land areas constitutes a robust climate change adaptation strategy for reducing nutrient losses from agricultural lands, enhancing resilience to a projected warmer and wetter winter climate in the midwestern U.S.
C1 [Hamlet, Alan F.; Ehsani, Nima; Silver, Zachariah] Univ Notre Dame, Dept Civil & Environm Engn & Earth Sci, Notre Dame, IN 46556 USA.
   [Ehsani, Nima] Southern Calif Edison, Rosemead, CA 91770 USA.
   [Tank, Jennifer L.; Mahl, Ursula H.; Speir, Shannon L.; Trentman, Matt T.] Univ Notre Dame, Dept Biol Sci, Notre Dame, IN USA.
   [Silver, Zachariah] Western Connecticut State Univ, Dept Phys Astron & Meteorol, Danbury, CT USA.
   [Byun, Kyuhyun] Incheon Natl Univ, Dept Environm Engn, Incheon 22012, South Korea.
   [Speir, Shannon L.] Univ Arkansas, Dept Crop Soil & Environm Sci, Fayetteville, AR 72701 USA.
   [Trentman, Matt T.] Univ Montana, Oconnor Ctr Rocky Mt West, Missoula, MT 59812 USA.
   [Royer, Todd V.] Indiana Univ, ONeill Sch Publ & Environm Affairs, Bloomington, IN USA.
C3 University of Notre Dame; University of Notre Dame; Connecticut State
   University System; Western Connecticut State University; Incheon
   National University; University of Arkansas System; University of
   Arkansas Fayetteville; University of Montana System; University of
   Montana; Indiana University System; Indiana University Bloomington
RP Hamlet, AF (corresponding author), Univ Notre Dame, Dept Civil & Environm Engn & Earth Sci, Notre Dame, IN 46556 USA.
EM hamlet.1@nd.edu
RI Trentman, Matt/J-5757-2019; Ehsani, Nima/F-9693-2017
FU U.S. Environmental Protection Agency [GL-00E02207]; Environmental
   Protection Agency under the Great Lakes Restoration Initiative
FX This research was funded by the Environmental Protection Agency under
   the Great Lakes Restoration Initiative (Grant # GL-00E02207, PI: A. F.
   Hamlet, CoPIs: J. L. Tank and T. V. Royer). Special thanks to Dr.
   Mohamed Aboelnour, postdoc at the University of Notre Dame, for
   assistance with additional SWAT validation during the review process.
CR Altieri MA, 2017, CLIMATIC CHANGE, V140, P33, DOI 10.1007/s10584-013-0909-y
   Appling AP, 2015, ECOSPHERE, V6, DOI 10.1890/ES14-00517.1
   Basche A, 2017, SOIL SCI SOC AM J, V81, P1179, DOI 10.2136/sssaj2017.03.0077
   Basu NB, 2022, NAT GEOSCI, V15, P97, DOI 10.1038/s41561-021-00889-9
   Brunetto G, 2011, NUTR CYCL AGROECOSYS, V90, P299, DOI 10.1007/s10705-011-9430-8
   Byun K, 2019, SCI TOTAL ENVIRON, V650, P1261, DOI 10.1016/j.scitotenv.2018.09.063
   Byun K, 2018, INT J CLIMATOL, V38, pE531, DOI 10.1002/joc.5388
   Cherkauer KA, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-02979-4
   Christianson R, 2021, T ASABE, V64, P1007, DOI 10.13031/trans.14028
   Christianson R, 2018, J ENVIRON MANAGE, V206, P1072, DOI 10.1016/j.jenvman.2017.11.051
   Christopher SF, 2021, J ENVIRON QUAL, V50, P667, DOI 10.1002/jeq2.20217
   Cober JR, 2018, AGRON J, V110, P1036, DOI 10.2134/agronj2017.08.0449
   Dodds WK, 2009, ENVIRON SCI TECHNOL, V43, P12, DOI 10.1021/es801217q
   Essig RR, 2017, PhD Dissertation
   Ficklin DL, 2009, J HYDROL, V374, P16, DOI 10.1016/j.jhydrol.2009.05.016
   Gampe D, 2021, NAT CLIM CHANGE, V11, P772, DOI 10.1038/s41558-021-01112-8
   Gassman PW, 2007, T ASABE, V50, P1211, DOI 10.13031/2013.23637
   Gupta R, 2023, J ENVIRON MANAGE, V339, DOI 10.1016/j.jenvman.2023.117946
   Hamlet AF, 2020, CLIMATIC CHANGE, V163, P1881, DOI 10.1007/s10584-018-2309-9
   Hamlet AF, 2013, ATMOS OCEAN, V51, P392, DOI 10.1080/07055900.2013.819555
   Hanrahan BR, 2018, AGR ECOSYST ENVIRON, V265, P513, DOI 10.1016/j.agee.2018.07.004
   Huidobro Marin GC-M., 2023, J Hydrometeorol, V24, P873, DOI [10.1175/JHM-D-22-0148.1, DOI 10.1175/JHM-D-22-0148.1]
   Kaspar TC, 2007, J ENVIRON QUAL, V36, P1503, DOI 10.2134/jeq2006.0468
   Kaspar TC, 2011, ACSESS PUBL, P321, DOI 10.2136/2011.soilmanagement.c21
   Kaye JP, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-016-0410-x
   Lychuk TE, 2021, AGR WATER MANAGE, V252, DOI 10.1016/j.agwat.2021.106850
   Malone R, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187630
   Osterman LE, 2005, GEOLOGY, V33, P329, DOI 10.1130/G21341.1
   Paerl HW, 2016, ENVIRON SCI TECHNOL, V50, P10805, DOI 10.1021/acs.est.6b02575
   Robertson DM, 2011, J AM WATER RESOUR AS, V47, P1011, DOI 10.1111/j.1752-1688.2011.00574.x
   Schwalm CR, 2020, P NATL ACAD SCI USA, V117, P19656, DOI 10.1073/pnas.2007117117
   Speir SL, 2022, AGR ECOSYST ENVIRON, V326, DOI 10.1016/j.agee.2021.107765
   Speir SL, 2021, BIOGEOCHEMISTRY, V156, P319, DOI 10.1007/s10533-021-00847-y
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Tohver IM, 2014, J AM WATER RESOUR AS, V50, P1461, DOI 10.1111/jawr.12199
   Trentman MT, 2020, HYDROL PROCESS, V34, P4446, DOI 10.1002/hyp.13870
   Van Liew M. W., 2012, International Journal of Agricultural and Biological Engineering, V5, P13
   Van Meter KJ, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7bf4
   Wang LL, 2018, WATER-SUI, V10, DOI 10.3390/w10040442
   Yang W, 2020, AGRON J, V112, P1201, DOI 10.1002/agj2.20110
NR 41
TC 1
Z9 1
U1 7
U2 18
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0165-0009
EI 1573-1480
J9 CLIMATIC CHANGE
JI Clim. Change
PD JAN
PY 2024
VL 177
IS 1
AR 9
DI 10.1007/s10584-023-03656-4
PG 21
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA DL6H9
UT WOS:001132232900001
DA 2025-01-10
ER

PT J
AU Haque, A
   Fatema, K
AF Haque, Ashraful
   Fatema, Kaniz
TI Disaster risk reduction for whom? The gap between centrally planned
   Disaster Management Program and people?s risk perception and adaptation
SO INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
LA English
DT Article
DE Disaster risk reduction; Perceived risk; Objective risk; Adaptation;
   Intervention efficacy
ID FIELD EXPERIMENT; CLIMATE-CHANGE; ADAPTIVE CAPACITY; TECHNOLOGY;
   VULNERABILITY; DETERMINANTS; HOUSEHOLDS; KNOWLEDGE; RESPONSES; FARMERS
AB Integration of Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) is gaining popularity to address the increasing threat of climate change. People living in high disaster-prone impoverished areas can benefit from risk reduction interventions and subsequent adaptation of new technologies and behavior if those interventions diminish the perceived risk of disaster. Perceived risk of disaster plays an important role in influencing adaptive behavior. Disaster risk reduction interventions therefore can be benefitted from inclusive local consultation during the planning and implementation of the risk reduction interventions by taking local people's perceived risk of disaster into account. We studied a national-level disaster risk reduction program called 'The comprehensive Disaster Management Program (CDMP)' in Bangladesh to understand the linkage between risk reduction interventions, perceived risk of disaster, and adaptation. Following a mixed-method approach, we collected quantitative administrative data, interviewed local people, and conducted Focus Group Discussions in two disaster-prone neighboring coastal unions of Bangladesh. We have found that if risk reduction interventions designed by the central government are not aligned with the perceived risk of the local people, the implementation of these interventions does not reduce perceived risk significantly, and consequently, people do not adopt new technologies and behavior to increase their resilience to climate change shocks. Furthermore, people's valuation of a risk reduction intervention in reducing the perceived risk of disasters does not change after an actual disaster takes place insinuating the relative accuracy and robustness of local people's assessment of such interventions. We also found that risk reduction interventions implemented in a holistic way addressing multiple sources of risks can reduce perceived risk significantly. Lastly, we demonstrated that reducing perceived risk is a necessary condition but is not sufficient to encourage adaptation. Our study can contribute to improving the design and implementation of large-scale risk-reduction interventions implemented at the community level.
C1 [Haque, Ashraful] Northsouth Univ & Sci, Adjunct Fac, Econs, Bangladesh.
   [Fatema, Kaniz] BRAC Microfinance, Sylhet, Bangladesh.
RP Haque, A (corresponding author), Northsouth Univ & Sci, Adjunct Fac, Econs, Bangladesh.
EM haqash.01@gmail.com; kanizfatema303@gmail.com
OI Haque, Ashraful/0000-0002-0764-359X
CR Abaluck J, 2022, SCIENCE, V375, P160, DOI 10.1126/science.abi9069
   Alatas V, 2012, AM ECON REV, V102, P1206, DOI 10.1257/aer.102.4.1206
   Arnold Margaret., 2014, Climate and Disaster Resilience: The Role for Community-Driven Development. Social Development Department
   Banwell N, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15040793
   Barham BL, 2014, J ECON BEHAV ORGAN, V97, P204, DOI 10.1016/j.jebo.2013.06.014
   (BBS) B. B, 2017, POV MAP BANGL
   (BBS) B. B, 2013, POP CENS COMM REP KH
   Beath A, 2015, INT PEACEKEEPING, V22, P302, DOI 10.1080/13533312.2015.1059287
   Beck U., 2007, ENV RISKS PUBLIC PER
   Begum RA, 2014, INT J DISAST RISK RE, V10, P362, DOI 10.1016/j.ijdrr.2014.10.011
   Birkmann J, 2013, NAT HAZARDS, V67, P193, DOI 10.1007/s11069-013-0558-5
   Björkman M, 2009, Q J ECON, V124, P735, DOI 10.1162/qjec.2009.124.2.735
   Bouma D.J., 2009, I CAPACITY MARKET A
   Brewer NT, 2004, ANN BEHAV MED, V27, P125, DOI 10.1207/s15324796abm2702_7
   Brouwer R, 2007, RISK ANAL, V27, P313, DOI 10.1111/j.1539-6924.2007.00884.x
   Bryan G, 2014, ECONOMETRICA, V82, P1671, DOI 10.3982/ECTA10489
   Casey K, 2018, ANNU REV ECON, V10, P139, DOI 10.1146/annurev-economics-080217-053339
   Cologna V, 2017, CLIM RISK MANAG, V17, P1, DOI 10.1016/j.crm.2017.04.005
   Deressa T., 2010, ANAL DETERMINANTS FA
   Gaillard JC, 2013, PROG HUM GEOG, V37, P93, DOI 10.1177/0309132512446717
   Gallagher J, 2014, AM ECON J-APPL ECON, V6, P206, DOI 10.1257/app.6.3.206
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Hampson SE, 2006, HEALTH PSYCHOL, V25, P530, DOI 10.1037/0278-6133.25.4.530
   Hansen T, 2019, J MARKET TRENDS, V5, P13
   Hardoy J, 2011, ENVIRON URBAN, V23, P401, DOI 10.1177/0956247811416435
   II C, 2009, CDMP 2 2010 2014 PRO
   Jones L, 2019, CLIM DEV, V11, P3, DOI 10.1080/17565529.2017.1374237
   Khwaja AI, 2004, J EUR ECON ASSOC, V2, P427, DOI 10.1162/154247604323068113
   Lam JMS, 2017, J STUD INT EDUC, V21, P83, DOI 10.1177/1028315316662980
   Lindell MK, 2008, RISK ANAL, V28, P539, DOI 10.1111/j.1539-6924.2008.01032.x
   Liu EM, 2013, REV ECON STAT, V95, P1386, DOI 10.1162/REST_a_00295
   Madajewicz M, 2021, J DEV ECON, V150, DOI 10.1016/j.jdeveco.2020.102609
   McGee T., 2003, ENVIRON HAZARDS-UK, V5, P1, DOI [10.1016/j.hazards.2003.04.001, DOI 10.1016/J.HAZARDS.2003.04.001]
   Mercer J, 2010, DISASTERS, V34, P214, DOI 10.1111/j.1467-7717.2009.01126.x
   Mortreux C, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.467
   Olken BA, 2010, AM POLIT SCI REV, V104, P243, DOI 10.1017/S0003055410000079
   Paton D., 2003, Disaster Prevention and Management, V12, P210, DOI DOI 10.1108/09653560310480686
   Patt A, 2002, GLOBAL ENVIRON CHANG, V12, P185, DOI 10.1016/S0959-3780(02)00013-4
   Piya L, 2013, REG ENVIRON CHANGE, V13, P437, DOI 10.1007/s10113-012-0359-5
   Satterthwaite D, 2011, ENVIRON URBAN, V23, P339, DOI 10.1177/0956247811420009
   SATTLER DN, 1995, J SOC BEHAV PERS, V10, P891
   Setbon M, 2005, RISK ANAL, V25, P813, DOI 10.1111/j.1539-6924.2005.00634.x
   Sherman M, 2016, WIRES CLIM CHANGE, V7, P707, DOI 10.1002/wcc.416
   Singh C, 2018, ENVIRON DEV, V25, P43, DOI 10.1016/j.envdev.2017.11.004
   Skoufias E, 2003, WORLD DEV, V31, P1087, DOI 10.1016/S0305-750X(03)00069-X
   UNISDR UN/ISDR (United Nations Office for Disaster Risk Reduction), 2008, LINK DIS RISK RED PO
   Wachinger G.R.O., 2010, WP3 CAPHAZ NET
   WILDAVSKY A, 1990, DAEDALUS, V119, P41
NR 48
TC 6
Z9 6
U1 12
U2 27
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-4209
J9 INT J DISAST RISK RE
JI Int. J. Disaster Risk Reduct.
PD NOV
PY 2022
VL 82
AR 103229
DI 10.1016/j.ijdrr.2022.103229
EA SEP 2022
PG 15
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA 9A2KM
UT WOS:000933892000001
DA 2025-01-10
ER

PT J
AU Ali, HF
   Ghoneim, SM
AF Ali, Hala F.
   Ghoneim, Sobhi M.
TI Satellite-based silica mapping as an essential mineral for clean energy
   transition: Remote sensing mineral exploration as a climate change
   adaptation approach
SO JOURNAL OF AFRICAN EARTH SCIENCES
LA English
DT Article
DE Remote sensing; Mineral exploration; Silica; Clean energy; Climate
   change
ID SPACEBORNE THERMAL EMISSION; PORPHYRY COPPER-DEPOSITS; CENTRAL EASTERN
   DESERT; ASTER DATA; SPECTRAL-ANALYSIS; ALTERATION ZONES; EGYPT; AREA;
   PETROGENESIS; ROCKS
AB One of the most important challenges in facing climate changes is transition to clean energy to reduce the warm gases emissions. The technologies of clean energy transition require more mineral resources than the traditional fossil fuel methods. The present study sheds the light on the role of mineral exploration using remote sensing techniques to fulfill the requirements of the clean energy technologies from mineral resources. In this study, the capabilities of ASTER data in mapping silica (an essential mineral for solar energy technologies) were demonstrated. Two case study areas with different geological environments of silica-rich rock units were studied. The Faiyum area contains sedimentary silica-rich rock units; mainly white sand, sandstone, and sand dunes. While the Higlig-Suwayqat area contains basement silica-rich rock units; mainly quartz plugs and veins included in the granitic rocks. Two remote sensing techniques; Band ratio (BR), and Constrained Energy Minimization (CEM) supervised classification techniques were applied to the ASTER surface reflectance. Several ASTER band ratios were tested; the ratio of b14/b12 was found the most effective band ratio for delineating the silica-rich areas. On the other hand, the CEM technique was applied using the USGS spectral signature of quartz mineral. CEM technique enabled mapping the pixels that have similar signatures to the input quartz signature as silica-rich areas. A field study was conducted in both the studied case areas to validate the remote sensing results; several silica-rich units were observed including; white sand, sandstone, sand dunes, quartz plugs/veins, and sand-rich wadi deposits. Based on the distribution of the silica-rich units mapped by both the adopted techniques as compared to the field observations, it is found that the accuracy of both the techniques is very high with an advantage of the CEM technique over the BR technique.
C1 [Ali, Hala F.; Ghoneim, Sobhi M.] Natl Author Remote Sensing & Space Sci NARSS, Geol Div, Cairo, Egypt.
C3 Egyptian Knowledge Bank (EKB); National Authority for Remote Sensing &
   Space Sciences (NARSS)
RP Ghoneim, SM (corresponding author), Natl Author Remote Sensing & Space Sci NARSS, Geol Div, Cairo, Egypt.
EM sobhy.mahmoud@narss.sci.eg
RI Ghoneim, Sobhi/LRC-3423-2024
OI Ghoneim, Sobhi/0000-0002-8907-3307
FU Egypt's National Authority for Remote Sensing and Space Sciences (NARSS)
FX The authors would like to acknowledge the anonymous ?Editors and
   Reviewers? of the Journal of African Earth Sciences that their fruitful
   comments helped enhancing the previous version of this manuscript. Also,
   "Egypt's National Authority for Remote Sensing and Space Sciences
   (NARSS) is acknowledged for facilitating and funding the field study
   conducted for this work.
CR Aboelkhair H, 2010, J AFR EARTH SCI, V58, P141, DOI 10.1016/j.jafrearsci.2010.01.007
   ABRAMS MJ, 1983, ECON GEOL, V78, P591, DOI 10.2113/gsecongeo.78.4.591
   Ali-Bik MW, 2012, J AFR EARTH SCI, V64, P77, DOI 10.1016/j.jafrearsci.2011.11.002
   Ali-Bik MW, 2020, GEOL J, V55, P5330, DOI 10.1002/gj.3742
   Amer R, 2010, J AFR EARTH SCI, V56, P75, DOI 10.1016/j.jafrearsci.2009.06.004
   Beadnell H. J. L., 1905
   Boardman J., 1998, JPL Publication, P97
   Cardoso-Fernandes J, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10051785
   Chen Q, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14051253
   CROWLEY JK, 1989, REMOTE SENS ENVIRON, V29, P121, DOI 10.1016/0034-4257(89)90021-7
   Di Tommaso I, 2007, ORE GEOL REV, V32, P275, DOI 10.1016/j.oregeorev.2006.05.004
   Drury S.A., 1993, Image Interpretation in Geology, Vsecond, P283, DOI [10.1080/01431169508954438, DOI 10.1080/01431169508954438]
   EGSMA (Egyptian Geological Survey and Mining Authority), 1992, GEOL MAP WAD AI BARR
   El-Baz F., 2000, EGYPT J REMOTE SEN S, V2, P1
   Francos N, 2021, APPL SPECTROSC, V75, P882, DOI 10.1177/0003702821998302
   Fraunhofer I., 2014, Photovoltaics report
   Ghoneim E.-S., 2018, Egypt. J Geol., DOI [10.21608/egjg.2018.216381, DOI 10.21608/EGJG.2018.216381]
   Ghoneim SM, 2022, EGYPT J REMOTE SENS, V25, P323, DOI 10.1016/j.ejrs.2022.02.001
   Ghoneim SM, 2021, J AFR EARTH SCI, V178, DOI 10.1016/j.jafrearsci.2021.104181
   Hewson R., 2002, SUMM 22 ASTER SCI M, P20
   IEA, 2022, World Energy Outlook
   Imran Muhammad, 2022, Arabian Journal of Geosciences, V15, DOI 10.1007/s12517-022-09806-9
   International Energy Agency, 2020, WORLD EN OUTL
   Kusky T.M., 2009, STRUCTURAL TECTONIC
   Lux Research, 2014, SOL MARK GROW 65 GW
   Lux Research, 2013, SUNS SIL
   Madani AA, 2011, ARAB J GEOSCI, V4, P45, DOI 10.1007/s12517-009-0059-8
   Mbianya GN, 2021, J AFR EARTH SCI, V184, DOI 10.1016/j.jafrearsci.2021.104386
   Ninomiya Y, 2005, REMOTE SENS ENVIRON, V99, P127, DOI 10.1016/j.rse.2005.06.009
   Ninomiya Y, 2003, INT GEOSCI REMOTE SE, P1552
   Ninomiya Y., 2002, J REMOTE SENSING SOC, V22, P50
   Oriel SS., 1980, Geologic map of the Preston 1 degree by 2 degrees Quadrangle, southeastern Idaho and western Wyoming No, DOI DOI 10.3133/GQ1574
   Qiu F, 2006, J AFR EARTH SCI, V44, P169, DOI 10.1016/j.jafrearsci.2005.10.009
   Rowan LC, 2006, REMOTE SENS ENVIRON, V104, P74, DOI 10.1016/j.rse.2006.05.014
   Rowan LC, 2005, REMOTE SENS ENVIRON, V99, P105, DOI 10.1016/j.rse.2004.11.021
   Rowan LC, 2003, REMOTE SENS ENVIRON, V84, P350, DOI 10.1016/S0034-4257(02)00127-X
   Sadek MF, 2015, ARAB J GEOSCI, V8, P10459, DOI 10.1007/s12517-015-1973-6
   Said R., 1972, ARCHAEOLOGIA POLONA, V13, P7
   Salem SM, 2014, ARAB J GEOSCI, V7, P1717, DOI 10.1007/s12517-013-0874-9
   SULTAN M, 1986, GEOLOGY, V14, P995, DOI 10.1130/0091-7613(1986)14<995:MOSITE>2.0.CO;2
   Wambo JDT, 2020, ORE GEOL REV, V122, DOI 10.1016/j.oregeorev.2020.103530
   Weckend S., 2016, END LIFE MANAGEMENT
   Zadeh MH, 2014, ORE GEOL REV, V62, P191, DOI 10.1016/j.oregeorev.2014.03.013
   Zoheir B, 2012, J AFR EARTH SCI, V66-67, P22, DOI 10.1016/j.jafrearsci.2012.02.007
NR 44
TC 7
Z9 8
U1 3
U2 16
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 1464-343X
EI 1879-1956
J9 J AFR EARTH SCI
JI J. Afr. Earth Sci.
PD DEC
PY 2022
VL 196
AR 104683
DI 10.1016/j.jafrearsci.2022.104683
EA AUG 2022
PG 11
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA 4E9NU
UT WOS:000848146000002
DA 2025-01-10
ER

PT J
AU Zhai, R
   Tao, FL
   Chen, Y
   Dai, HC
   Liu, ZW
   Fu, BJ
AF Zhai, Ran
   Tao, Fulu
   Chen, Yi
   Dai, Huichao
   Liu, Zhiwu
   Fu, Bojie
TI Future water security in the major basins of China under the 1.5 °C and
   2.0 °C global warming scenarios
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Droughts; Water withdrawal; Water resource; Water
   shortage
ID SHARED SOCIOECONOMIC PATHWAYS; CLIMATE-CHANGE IMPACTS; USE EFFICIENCY;
   AGRICULTURAL PRODUCTION; TEMPERATURE STRESS; RICE YIELD; MODEL;
   IRRIGATION; RESOURCES; SCARCITY
AB Freshwater is an essential resource for human lives, agriculture, industry, and ecology. Future water supply, water withdrawal, and water security under the impacts of climate change and human interventions have been of key concern. Numerous studies have projected future changes in river runoff and surface water resources under climate change. However, the changes in the major water withdrawal components including agricultural irrigation water, industrial, domestic and ecological water withdrawal, as well as the balance between water supply and withdrawal, under the joint impacts of climate change and socio-economic development have been seldom investigated, especially at the basin and national scales. In this study, changes in surface water resources, agricultural irrigation water, industrial, domestic and ecological water withdrawal, as well as the balances between water supply and withdrawal, under the baseline climate (2006-2015), 1.5 degrees C and 2.0 degrees C warming scenarios (2106-2115) in the 10 major basins across China, were investigated by combining modelling and local census data. The results showed that water withdrawal exceeded water supply in the basins of Liao River, Northwest River, Hai River, Yellow River and Huai River in the baseline period. Under the 1.5 degrees C and 2.0 degrees C warming scenarios, the shortage of water resources would aggravate in the above-mentioned basins and the Songhua River basin. And the surplus of water resources would reduce substantially in the basins of Yangtze River, Southeast River and Pearl River. Overall, the difference between water supply and water withdrawal was 435.88 billion m(3) during the baseline period, and would be 261.84 and 218.39 billion m(3), respectively, under the 1.5 degrees C and 2.0 degrees C warming scenarios. This study provides a comprehensive perspective on future water security in the 10 major basins across China, has important implications for water resources management and climate change adaptation.
C1 [Tao, Fulu; Chen, Yi] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
   [Zhai, Ran; Dai, Huichao; Liu, Zhiwu] China Three Gorges Corp, Inst Sci & Technol, Beijing 100038, Peoples R China.
   [Tao, Fulu; Chen, Yi; Fu, Bojie] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.
   [Tao, Fulu] Nat Resources Inst Finland Luke, Helsinki 00790, Finland.
   [Fu, Bojie] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, Beijing, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Geographic Sciences & Natural
   Resources Research, CAS; China Three Gorges Corporation; Chinese Academy
   of Sciences; University of Chinese Academy of Sciences, CAS; Natural
   Resources Institute Finland (Luke); Chinese Academy of Sciences;
   Research Center for Eco-Environmental Sciences (RCEES)
RP Tao, FL (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
EM taofl@igsnrr.ac.cn
RI Fu, Bojie/B-1493-2009; Dai, Huichao/ACM-9898-2022; Zhai,
   Ran/AAD-6190-2022; LIU, ZHIPENG/GWQ-5972-2022
FU National Key Research and Development Program of China [2017YFA0604703];
   National Natural Science Foundation of China [U2040212]; China Three
   Gorges Corporation [202103584]
FX This work was supported by the National Key Research and Development
   Program of China (no. 2017YFA0604703), the National Natural Science
   Foundation of China (project U2040212) and China Three Gorges
   Corporation (Contract Number: 202103584).
CR Alcamo J, 2003, HYDROLOG SCI J, V48, P317, DOI 10.1623/hysj.48.3.317.45290
   Alcamo J, 2007, HYDROLOG SCI J, V52, P247, DOI 10.1623/hysj.52.2.247
   Asseng S, 2015, NAT CLIM CHANGE, V5, P143, DOI [10.1038/nclimate2470, 10.1038/NCLIMATE2470]
   Asseng S, 2013, NAT CLIM CHANGE, V3, P827, DOI [10.1038/nclimate1916, 10.1038/NCLIMATE1916]
   Bassu S, 2014, GLOBAL CHANGE BIOL, V20, P2301, DOI 10.1111/gcb.12520
   Cannon AJ, 2015, J CLIMATE, V28, P1260, DOI 10.1175/JCLI-D-14-00636.1
   Chen Y, 2018, EARTH SYST DYNAM, V9, P543, DOI 10.5194/esd-9-543-2018
   Chen Y, 2017, FIELD CROP RES, V206, P11, DOI 10.1016/j.fcr.2017.02.012
   Dan L, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD017131
   Deryng D, 2016, NAT CLIM CHANGE, V6, P786, DOI [10.1038/nclimate2995, 10.1038/NCLIMATE2995]
   DUAN QY, 1994, J HYDROL, V158, P265, DOI 10.1016/0022-1694(94)90057-4
   Elliott J, 2014, P NATL ACAD SCI USA, V111, P3239, DOI 10.1073/pnas.1222474110
   Fader M, 2016, HYDROL EARTH SYST SC, V20, P953, DOI 10.5194/hess-20-953-2016
   Fischer G, 2007, TECHNOL FORECAST SOC, V74, P1083, DOI 10.1016/j.techfore.2006.05.021
   Flörke M, 2013, GLOBAL ENVIRON CHANG, V23, P144, DOI 10.1016/j.gloenvcha.2012.10.018
   Frieler K, 2017, GEOSCI MODEL DEV, V10, P4321, DOI 10.5194/gmd-10-4321-2017
   Gerten D, 2011, J HYDROMETEOROL, V12, P885, DOI 10.1175/2011JHM1328.1
   Hanasaki N, 2013, HYDROL EARTH SYST SC, V17, P2393, DOI 10.5194/hess-17-2393-2013
   Hanasaki N, 2013, HYDROL EARTH SYST SC, V17, P2375, DOI 10.5194/hess-17-2375-2013
   Hayashi A, 2013, MITIG ADAPT STRAT GL, V18, P591, DOI 10.1007/s11027-012-9377-3
   Heinke J, 2019, EARTH SYST DYNAM, V10, P205, DOI 10.5194/esd-10-205-2019
   Katsavounidis I, 1994, IEEE SIGNAL PROC LET, V1, P144, DOI 10.1109/97.329844
   Leng GY, 2015, SCI CHINA EARTH SCI, V58, P739, DOI 10.1007/s11430-014-4987-0
   Li T, 2015, GLOBAL CHANGE BIOL, V21, P1328, DOI 10.1111/gcb.12758
   Liang X, 1994, J GEOPHYS RES-ATMOS, V99, P14415, DOI 10.1029/94JD00483
   Liang X, 1996, GLOBAL PLANET CHANGE, V13, P195, DOI 10.1016/0921-8181(95)00046-1
   Liu JG, 2009, WATER RESOUR RES, V45, DOI 10.1029/2007WR006051
   Mitchell D, 2017, GEOSCI MODEL DEV, V10, P571, DOI 10.5194/gmd-10-571-2017
   Monfreda C, 2008, GLOBAL BIOGEOCHEM CY, V22, DOI 10.1029/2007GB002947
   Nijssen B, 2001, J CLIMATE, V14, P3307, DOI 10.1175/1520-0442(2001)014<3307:PTDOGR>2.0.CO;2
   Piao SL, 2010, NATURE, V467, P43, DOI 10.1038/nature09364
   Purola T, 2018, AGR SYST, V162, P191, DOI 10.1016/j.agsy.2018.01.018
   Ramankutty N, 2008, GLOBAL BIOGEOCHEM CY, V22, DOI 10.1029/2007GB002952
   Rosenzweig C, 2014, P NATL ACAD SCI USA, V111, P3268, DOI 10.1073/pnas.1222463110
   Rost S, 2008, WATER RESOUR RES, V44, DOI 10.1029/2007WR006331
   Schewe J, 2014, P NATL ACAD SCI USA, V111, P3245, DOI 10.1073/pnas.1222460110
   Shen YJ, 2008, HYDROLOG SCI J, V53, P11, DOI 10.1623/hysj.53.1.11
   Shiklomanov IA, 2000, WATER INT, V25, P11, DOI 10.1080/02508060008686794
   Shuai JB, 2016, INT J CLIMATOL, V36, P424, DOI 10.1002/joc.4360
   Tao F, 2003, AGR ECOSYST ENVIRON, V95, P203, DOI 10.1016/S0167-8809(02)00093-2
   Tao FL, 2013, AGR FOREST METEOROL, V170, P146, DOI 10.1016/j.agrformet.2011.10.003
   Tao FL, 2013, J APPL METEOROL CLIM, V52, P531, DOI 10.1175/JAMC-D-12-0100.1
   Tao FL, 2009, AGR FOREST METEOROL, V149, P1266, DOI 10.1016/j.agrformet.2009.02.015
   Tao F, 2009, AGR FOREST METEOROL, V149, P831, DOI 10.1016/j.agrformet.2008.11.004
   Wada Y, 2016, GEOSCI MODEL DEV, V9, P175, DOI 10.5194/gmd-9-175-2016
   Wada Y, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009792
   Wang GQ, 2012, HYDROL EARTH SYST SC, V16, P231, DOI 10.5194/hess-16-231-2012
   Wang HM, 2018, HYDROL EARTH SYST SC, V22, P3739, DOI 10.5194/hess-22-3739-2018
   Wang JX, 2017, GLOB FOOD SECUR-AGR, V14, P9, DOI 10.1016/j.gfs.2017.01.003
   Wang P, 2016, CLIMATIC CHANGE, V134, P635, DOI 10.1007/s10584-015-1545-5
   Wang WG, 2017, AGR FOREST METEOROL, V232, P89, DOI 10.1016/j.agrformet.2016.08.008
   Wang WG, 2014, AGR WATER MANAGE, V146, P249, DOI 10.1016/j.agwat.2014.08.019
   Xie ZH, 2007, J HYDROMETEOROL, V8, P447, DOI 10.1175/JHM568.1
   Yin YY, 2017, HYDROL EARTH SYST SC, V21, DOI 10.5194/hess-21-791-2017
   Zhai R, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001398
   Zhai R, 2018, EARTH SYST DYNAM, V9, P717, DOI 10.5194/esd-9-717-2018
   Zhang Z, 2017, INT J CLIMATOL, V37, P4814, DOI 10.1002/joc.5125
   Zhou S, 2017, GLOBAL BIOGEOCHEM CY, V31, P1639, DOI 10.1002/2017GB005733
NR 58
TC 19
Z9 19
U1 10
U2 156
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 25
PY 2022
VL 849
AR 157928
DI 10.1016/j.scitotenv.2022.157928
EA AUG 2022
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 4S0DA
UT WOS:000857121700016
PM 35952883
DA 2025-01-10
ER

PT J
AU Xin, Y
   Tao, FL
AF Xin, Yue
   Tao, Fulu
TI Have the agricultural production systems in the North China Plain
   changed towards to climate smart agriculture since 2000?
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Carbon footprint; Climate change adaptation; GHG mitigation; Cropping
   system; Economic benefit; Resource use efficiency
ID GREENHOUSE-GAS EMISSIONS; NITROUS-OXIDE EMISSIONS; SOIL CARBON STORAGE;
   WINTER-WHEAT; ADAPTATION PROGRAM; CROPPING SYSTEMS; FOOD-PRODUCTION;
   ECO-EFFICIENCY; NO-TILLAGE; MANAGEMENT
AB Developing climate-smart agricultural systems has become an important strategy to meet the food production, environmental and economic goals simultaneously. However, the comprehensive analyses on the climate-smartness of current agricultural production systems have been lack. Here, we assessed the changes in agricultural production systems and their influences on food productivity, greenhouse gas (GHG) emissions, food carbon footprint (CF), nitrogen and water use efficiency, and economic profit of major crops in the North China Plain (NCP) at sub-provincial level over 2000-2016. We further identified the prior areas and agronomic management practices to be improved where nitrogen and water use efficiency was low, CF was high, or/and economic profit was low. The results showed that wheat, maize, vegetables, and oil crops were always dominant crops in the NCP and maize planting area increased most among all crops types over 2000-2016. The non-uniformity of agricultural landscape led to the decline of Shannon-Wiener Index and Simpson's diversity Index. Agricultural GHG emissions and CF had spatially explicit patterns, along with crop yields and agricultural inputs. Among the agricultural inputs, fertilizer played a dominant role and contributed about 58.0%, 81.6%, and 77.3% respectively to the CF of wheat, maize, and oil crops, and plastic film contributed up to 55.1% to the CF of vegetables. The CF had a decreasing trend, while nitrogen use efficiency, irrigation water use efficiency and economic profit had an increasing trend, mainly due to increased yields, reduced agricultural inputs including fertilizers and irrigation, and improved agronomic managements. This study demonstrates a framework to evaluate and improve the climate-smartness of agricultural production system accounting for the multiple objectives simultaneously, and provides theoretical guidance and practical methods for government and farmers to improve agricultural production systems.
   (c) 2021 Elsevier Ltd. All rights reserved.
C1 [Tao, Fulu] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
   [Xin, Yue] Hebei Agr Univ, Coll Forestry, Baoding 071001, Hebei, Peoples R China.
   [Tao, Fulu] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.
   [Tao, Fulu] Nat Resources Inst Finland Luke, FI-00790 Helsinki, Finland.
   [Xin, Yue] Hebei Agr Univ, State Key Lab North China Crop Improvement & Regu, Baoding 071001, Hebei, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Geographic Sciences & Natural
   Resources Research, CAS; Hebei Agricultural University; Chinese Academy
   of Sciences; University of Chinese Academy of Sciences, CAS; Natural
   Resources Institute Finland (Luke); Hebei Agricultural University
RP Tao, FL (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
EM taofl@igsnrr.ac.cn
FU National Science Foundation of China [31761143006, 41571493]; National
   Key RAMP;D Program of China [2017YFA0604703, 2019YFA0607401]; scientific
   research projects for talents introduce in Hebei Agricultural University
   [YJ2020052]
FX This study is supported by the National Science Foundation of China
   (Project Nos. 31761143006, 41571493) , the National Key R&D Program of
   China (Project Nos. 2017YFA0604703, 2019YFA0607401) , and the scientific
   research projects for talents introduce in Hebei Agricultural University
   (YJ2020052) .
CR Ahmed A, 2015, ENVIRON SCI POLLUT R, V22, P9494, DOI 10.1007/s11356-015-4110-x
   Ali SA, 2017, J CLEAN PROD, V140, P608, DOI 10.1016/j.jclepro.2016.04.135
   [Anonymous], 2013, IRRIGATION SCI, DOI DOI 10.1007/s00271-012-0398-1
   [Anonymous], 2011, BIOGEOSCIENCES, DOI DOI 10.5194/bg-8-3011-2011
   [Anonymous], 2006, AGR FORESTRY OTHER L
   Banna H, 2016, CAH AGRIC, V25, DOI 10.1051/cagri/2016014
   Buendia E., 2019, 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol- ume 4: Agriculture, Forestry and Other Land Use
   Chai RS, 2019, CARBON BAL MANAGE, V14, DOI 10.1186/s13021-019-0133-9
   Chen XP, 2014, NATURE, V514, P486, DOI 10.1038/nature13609
   Chen Y, 2018, EARTH SYST DYNAM, V9, P543, DOI 10.5194/esd-9-543-2018
   Cheng K, 2011, AGR ECOSYST ENVIRON, V142, P231, DOI 10.1016/j.agee.2011.05.012
   Cui JX, 2019, J CLEAN PROD, V213, P300, DOI 10.1016/j.jclepro.2018.12.174
   Dai XQ, 2013, FIELD CROP RES, V149, P141, DOI 10.1016/j.fcr.2013.04.027
   Dalin C, 2015, P NATL ACAD SCI USA, V112, P4588, DOI 10.1073/pnas.1504345112
   Deng AX, 2017, CROP J, V5, P136, DOI 10.1016/j.cj.2016.06.015
   Fang QX, 2013, J ENVIRON QUAL, V42, P1466, DOI 10.2134/jeq2013.03.0086
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   Feng YP, 2020, J CLEAN PROD, V244, DOI 10.1016/j.jclepro.2019.118887
   Finkbeiner M, 2009, INT J LIFE CYCLE ASS, V14, P91, DOI 10.1007/s11367-009-0064-x
   Gan YT, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms6012
   Guo S, 2015, ENVIRON SCI TECHNOL, V49, P403, DOI 10.1021/es503637f
   Han D, 2018, GLOBAL CHANGE BIOL, V24, P987, DOI 10.1111/gcb.13898
   He G, 2017, J CLEAN PROD, V164, P567, DOI 10.1016/j.jclepro.2017.06.085
   Huang JX, 2019, J CLEAN PROD, V225, P939, DOI 10.1016/j.jclepro.2019.04.044
   Jia JX, 2012, AGR ECOSYST ENVIRON, V150, P27, DOI 10.1016/j.agee.2012.01.011
   Kang SZ, 2017, AGR WATER MANAGE, V179, P5, DOI 10.1016/j.agwat.2016.05.007
   Kang YH, 2010, AGR WATER MANAGE, V97, P1303, DOI 10.1016/j.agwat.2010.03.006
   Kanter DR, 2018, AGR SYST, V163, P73, DOI 10.1016/j.agsy.2016.09.010
   Li M, 2020, J CLEAN PROD, V258, DOI 10.1016/j.jclepro.2020.120785
   Liu HJ, 2007, IRRIGATION SCI, V25, P149, DOI 10.1007/s00271-006-0042-z
   Luo YC, 2020, EARTH SYST SCI DATA, V12, P197, DOI 10.5194/essd-12-197-2020
   Man JG, 2014, FIELD CROP RES, V161, P26, DOI 10.1016/j.fcr.2014.02.001
   Masud MM, 2017, J CLEAN PROD, V156, P698, DOI 10.1016/j.jclepro.2017.04.060
   Petersen SO, 2006, AGR ECOSYST ENVIRON, V112, P200, DOI 10.1016/j.agee.2005.08.021
   Pittelkow CM, 2015, NATURE, V517, P365, DOI 10.1038/nature13809
   Pretty J, 2018, NAT SUSTAIN, V1, P441, DOI 10.1038/s41893-018-0114-0
   Pretty J, 2014, ANN BOT-LONDON, V114, P1571, DOI 10.1093/aob/mcu205
   R Core Team, 2013, R: A language and environment for statistical computing
   Ren YJ, 2018, SCI TOTAL ENVIRON, V635, P1102, DOI 10.1016/j.scitotenv.2018.04.204
   Rosseel Y, 2012, J STAT SOFTW, V48, P1, DOI 10.18637/jss.v048.i02
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P1
   Sun Xueping, 2014, Journal of Natural Disasters, V23, P33, DOI 10.13577/j.jnd.2014.0305
   Syswerda SP, 2011, SOIL SCI SOC AM J, V75, P92, DOI 10.2136/sssaj2009.0414
   Tao FL, 2019, SOIL TILL RES, V186, P70, DOI 10.1016/j.still.2018.10.009
   Tao FL, 2014, GLOBAL CHANGE BIOL, V20, P3686, DOI 10.1111/gcb.12684
   Tian K, 2015, AGR ECOSYST ENVIRON, V204, P40, DOI 10.1016/j.agee.2015.02.008
   Wang J, 2012, CLIMATIC CHANGE, V113, P825, DOI 10.1007/s10584-011-0385-1
   Wang XL, 2018, J INTEGR AGR, V17, P2822, DOI 10.1016/S2095-3119(18)61928-8
   Wang ZB, 2017, J CLEAN PROD, V141, P1267, DOI 10.1016/j.jclepro.2016.09.120
   Wang ZB, 2016, J CLEAN PROD, V112, P149, DOI 10.1016/j.jclepro.2015.06.084
   Xia LL, 2016, SCI TOTAL ENVIRON, V556, P116, DOI 10.1016/j.scitotenv.2016.02.204
   Xiao DP, 2017, AGR SYST, V153, P109, DOI 10.1016/j.agsy.2017.01.018
   Xin Y, 2020, AGR ECOSYST ENVIRON, V291, DOI 10.1016/j.agee.2019.106791
   Xin Y, 2019, SCI TOTAL ENVIRON, V654, P480, DOI 10.1016/j.scitotenv.2018.11.126
   Yang XL, 2014, J CLEAN PROD, V76, P131, DOI 10.1016/j.jclepro.2014.03.063
   Yuan WP, 2018, EARTHS FUTURE, V6, P634, DOI 10.1002/2017EF000641
   Zhang FS, 2013, NATURE, V497, P33, DOI 10.1038/497033a
   Zhang G, 2018, J CLEAN PROD, V194, P613, DOI 10.1016/j.jclepro.2018.05.024
   Zhang G, 2019, J CLEAN PROD, V237, DOI 10.1016/j.jclepro.2019.117650
   Zhang WF, 2013, P NATL ACAD SCI USA, V110, P8375, DOI 10.1073/pnas.1210447110
   Zhang XY, 2006, AGRON J, V98, P1620, DOI 10.2134/agronj2005.0358
   Zhang Y, 2014, BIOGEOSCIENCES, V11, P1717, DOI 10.5194/bg-11-1717-2014
   Zhao X, 2017, EUR J AGRON, V84, P67, DOI 10.1016/j.eja.2016.11.009
   Zhao ZG, 2015, AGR ECOSYST ENVIRON, V210, P36, DOI 10.1016/j.agee.2015.05.005
   Zhu YC, 2018, J CLEAN PROD, V172, P2143, DOI 10.1016/j.jclepro.2017.11.205
NR 65
TC 28
Z9 29
U1 6
U2 118
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-6526
EI 1879-1786
J9 J CLEAN PROD
JI J. Clean Prod.
PD MAY 25
PY 2021
VL 299
AR 126940
DI 10.1016/j.jclepro.2021.126940
EA APR 2021
PG 24
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology
GA RV9GZ
UT WOS:000646135200005
DA 2025-01-10
ER

PT J
AU Kim, JY
   Koide, D
   Ishihama, F
   Kadoya, T
   Nishihiro, J
AF Kim, Ji Yoon
   Koide, Dai
   Ishihama, Fumiko
   Kadoya, Taku
   Nishihiro, Jun
TI Current site planning of medium to large solar power systems accelerates
   the loss of the remaining semi-natural and agricultural habitats
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Renewable energy; Land cover change; Habitat fragmentation; Sustainable
   development; Cumulative effect; Climate change adaptation
ID RENEWABLE ENERGY; ENVIRONMENTAL IMPACTS; ECOSYSTEM SERVICES; LAND
   REQUIREMENTS; BIODIVERSITY; PLANTS; GREEN; SUSTAINABILITY; TRANSITIONS;
   ELECTRICITY
AB The global transition to renewable energy sources has accelerated to mitigate the effects of global climate change. Sudden increases in solar power facilities have caused the physical destruction of wildlife habitats, thereby resulting in the decline of biodiversity and ecosystem functions. However, previous assessments have been based on the environmental impact of large solar photovoltaics (PVs). The impact of medium-sized PV facilities (0.5-10 MW), which can alter small habitat patches through the accumulation of installations has not been assessed. Here, we quantified the amount of habitat loss directly related to the construction of PV facilities with different size classes and estimated their siting attributes using construction patterns in Japan and South Korea. We identified that a comparable amount of natural and semi-natural habitats were lost due to the recent installation of medium solar facilities (approximately 66.36 and 85.73% of the overall loss in Japan and South Korea, respectively). Compared to large solar PVs, medium PV installations resulted in a higher area loss of semi-natural habitats, including secondary/planted forests, secondary/artificial grasslands, and agricultural lands. The siting attributes of medium and large solar PV facilities indicated a preference for cost-based site selec-tion rather than prioritizing habitat protection for biodiversity conservation. Moreover, even conservation areas were developed when economic and topological conditions were suitable for energy production. Our simulations indicate that increasing the construction of PVs in urban areas could help reduce the loss of natural and semi -natural habitats. To improve the renewable energy share while mitigating the impacts on biodiversity, our results stress the need for a proactive assessment to enforce sustainable site-selection criteria for solar PVs in renewable energy initiatives. The revised criteria should consider the cumulative impacts of varied size classes of solar power facilities, including medium PVs, and the diverse aspects of the ecological value of natural habitats.
   (c) 2021 Elsevier B.V. All rights reserved.
C1 [Kim, Ji Yoon; Koide, Dai; Nishihiro, Jun] Natl Inst Environm Studies, Ctr Climate Change Adaptat, Tsukuba, Ibaraki 3058506, Japan.
   [Ishihama, Fumiko; Kadoya, Taku] Natl Inst Environm Studies, Ctr Environm Biol & Ecosyst Studies, Tsukuba, Ibaraki 3058506, Japan.
C3 National Institute for Environmental Studies - Japan; National Institute
   for Environmental Studies - Japan
RP Kim, JY (corresponding author), Natl Inst Environm Studies, Ctr Climate Change Adaptat, Tsukuba, Ibaraki 3058506, Japan.
EM tapegrass.kim@gmail.com
RI Koide, Dai/ADM-5841-2022; Kadoya, Taku/L-7536-2013; Ishihama,
   Fumiko/AAC-1461-2022
OI Ishihama, Fumiko/0000-0001-8515-5914; Koide, Dai/0000-0002-1535-9652;
   Nishihiro, Jun/0000-0002-7353-3970
CR Aiello-Lammens ME, 2015, ECOGRAPHY, V38, P541, DOI 10.1111/ecog.01132
   Akasaka M, 2014, ECOL RES MONOGR, P209, DOI 10.1007/978-4-431-54783-9_10
   Amado M, 2014, ENRGY PROCED, V48, P1539, DOI 10.1016/j.egypro.2014.02.174
   [Anonymous], 2020, Renewable Energy Finance: Green Bonds
   Barron-Gafford GA, 2016, SCI REP-UK, V6, DOI 10.1038/srep35070
   Bernardino J, 2018, BIOL CONSERV, V222, P1, DOI 10.1016/j.biocon.2018.02.029
   Bradbury K, 2016, SCI DATA, V3, DOI 10.1038/sdata.2016.106
   Bruckner T., 2014, IPCC WORK GROUP 3 CO
   Cagle AE, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12198154
   Capellán-Pérez I, 2017, RENEW SUST ENERG REV, V77, P760, DOI 10.1016/j.rser.2017.03.137
   Castillo CP, 2016, ENERG POLICY, V88, P86, DOI 10.1016/j.enpol.2015.10.004
   CBD, 2020, UPDATED ZERO DRAFT P
   Chabert A, 2020, AGR ECOSYST ENVIRON, V292, DOI 10.1016/j.agee.2019.106815
   Chapman A, 2019, SUSTAIN SCI, V14, P355, DOI 10.1007/s11625-018-0613-y
   Child M, 2018, RENEW SUST ENERG REV, V91, P321, DOI 10.1016/j.rser.2018.03.079
   Davis F.W., 2013, STATE LOCAL GOVT SER, VCEC-500-2015- 062
   Doesburg SM, 2009, PLOS ONE, V4, DOI [10.1371/journal.pone.0006802, 10.1371/journal.pone.0006142]
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Fujioka M, 2010, WATERBIRDS, V33, P8, DOI 10.1675/063.033.s102
   Gasparatos A, 2017, RENEW SUST ENERG REV, V70, P161, DOI 10.1016/j.rser.2016.08.030
   Gastli A, 2010, RENEW SUST ENERG REV, V14, P821, DOI 10.1016/j.rser.2009.08.020
   Gibson L, 2017, TRENDS ECOL EVOL, V32, P922, DOI 10.1016/j.tree.2017.09.007
   Goodale MW, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab205b
   Green EJ, 2019, CONSERV BIOL, V33, P1360, DOI 10.1111/cobi.13322
   Greenhouse Gas Inventory and Research Center (GGIRC), 2019, NATL GREENHOUSE GAS
   Grippo M, 2015, ENVIRON MANAGE, V55, P244, DOI 10.1007/s00267-014-0384-x
   Hanson JO, 2020, NATURE, V580, P232, DOI 10.1038/s41586-020-2138-7
   Hashimoto S., 2014, J REMOTE SENSING SOC, V34, P102, DOI DOI 10.11440/RSSJ.34.102
   Heiner M, 2019, ENVIRON IMPACT ASSES, V74, P1, DOI 10.1016/j.eiar.2018.09.002
   Hernandez RR, 2014, RENEW SUST ENERG REV, V29, P766, DOI 10.1016/j.rser.2013.08.041
   Hernandez RR, 2020, PLANTS-BASEL, V9, DOI 10.3390/plants9091125
   Hernandez RR, 2015, P NATL ACAD SCI USA, V112, P13579, DOI 10.1073/pnas.1517656112
   Hladik ML, 2016, SCI TOTAL ENVIRON, V542, P469, DOI 10.1016/j.scitotenv.2015.10.077
   Hofierka J, 2009, RENEW ENERG, V34, P2206, DOI 10.1016/j.renene.2009.02.021
   IEA, 2019, TRACK POW 2019
   Jacobson AP, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-50558-6
   Kammen DM, 2016, SCIENCE, V352, P922, DOI 10.1126/science.aad9302
   Katayama N, 2015, AGR SYST, V132, P73, DOI 10.1016/j.agsy.2014.09.001
   Kern F, 2016, ENERGY RES SOC SCI, V22, P13, DOI 10.1016/j.erss.2016.08.016
   Kim JY, 2020, WETL ECOL MANAG, V28, P217, DOI 10.1007/s11273-020-09707-2
   Kim JY, 2018, ECOSPHERE, V9, DOI 10.1002/ecs2.2109
   Köppel J, 2014, ENVIRON MANAGE, V54, P744, DOI 10.1007/s00267-014-0333-8
   Koyanagi TF, 2013, BIOL CONSERV, V167, P1, DOI 10.1016/j.biocon.2013.07.012
   Kuldna P, 2009, ECOL ECON, V69, P32, DOI 10.1016/j.ecolecon.2009.01.005
   Lange K, 2018, FRONT ECOL ENVIRON, V16, P397, DOI 10.1002/fee.1823
   Lee CY, 2017, APPL ENERG, V197, P29, DOI 10.1016/j.apenergy.2017.03.124
   Li AT, 2019, ENERG POLICY, V134, DOI 10.1016/j.enpol.2019.110950
   Lineman M, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0138996
   Lobaccaro G, 2019, RENEW SUST ENERG REV, V108, P209, DOI 10.1016/j.rser.2019.03.041
   Lovich JE, 2011, BIOSCIENCE, V61, P982, DOI 10.1525/bio.2011.61.12.8
   MacLean SA, 2017, GLOBAL CHANGE BIOL, V23, P4094, DOI 10.1111/gcb.13736
   Matos FAR, 2020, GLOBAL CHANGE BIOL, V26, P509, DOI 10.1111/gcb.14824
   Matsuno Y, 2006, PADDY WATER ENVIRON, V4, P189, DOI 10.1007/s10333-006-0048-4
   Ministry of Land Infrastructure Transport and Tourism (MLIT), 2020, NAT LAND NUM INF DOW
   MOE, 2020, GUID SOL PV
   Moore-O'Leary KA, 2017, FRONT ECOL ENVIRON, V15, P385, DOI 10.1002/fee.1517
   Murphy-Mariscal M, 2018, COMPREHENSIVE GUIDE TO SOLAR ENERGY SYSTEMS: WITH SPECIAL FOCUS ON PHOTOVOLTAIC SYSTEMS, P391, DOI 10.1016/B978-0-12-811479-7.00020-8
   Nakahama N, 2018, HEREDITY, V121, P155, DOI 10.1038/s41437-018-0057-2
   Nam K, 2020, RENEW SUST ENERG REV, V122, DOI 10.1016/j.rser.2020.109725
   Natuhara Y, 2013, ECOL ENG, V56, P97, DOI 10.1016/j.ecoleng.2012.04.026
   Noda A, 2019, ONE ECOSYSTEM, P4, DOI DOI 10.3897/ONEECO.4.E37669
   Ohashi H, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-13241-y
   Palmer-Wilson K, 2019, ENERG POLICY, V129, P193, DOI 10.1016/j.enpol.2019.01.071
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2017, ECOGRAPHY, V40, P887, DOI 10.1111/ecog.03049
   Popescu VD, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-64501-7
   Pravalie R, 2019, J CLEAN PROD, V209, P692, DOI 10.1016/j.jclepro.2018.10.239
   Reeg J, 2018, ENVIRON TOXICOL CHEM, V37, P1707, DOI 10.1002/etc.4122
   Rehbein JA, 2020, GLOBAL CHANGE BIOL, V26, P3040, DOI 10.1111/gcb.15067
   REN21, 2020, REN 2020 GLOB STAT
   Renner IW, 2013, BIOMETRICS, V69, P274, DOI 10.1111/j.1541-0420.2012.01824.x
   Sampei Y, 2009, GLOBAL ENVIRON CHANG, V19, P203, DOI 10.1016/j.gloenvcha.2008.10.005
   Santangeli A, 2016, GCB BIOENERGY, V8, P941, DOI 10.1111/gcbb.12299
   Scheidel A, 2012, GLOBAL ENVIRON CHANG, V22, P588, DOI 10.1016/j.gloenvcha.2011.12.005
   Semeraro T, 2018, ENERG POLICY, V117, P218, DOI 10.1016/j.enpol.2018.01.050
   Shah SM, 2019, J CLEAN PROD, V239, DOI 10.1016/j.jclepro.2019.118019
   Shorabeh SN, 2019, RENEW ENERG, V143, P958, DOI 10.1016/j.renene.2019.05.063
   Singh GK, 2013, ENERGY, V53, P1, DOI 10.1016/j.energy.2013.02.057
   Singh R, 2015, SOL ENERGY, V115, P589, DOI 10.1016/j.solener.2015.03.016
   Sinha P, 2018, CASE STUD ENVIRON, V2, DOI 10.1525/cse.2018.001123
   Smith AC, 2017, ECOSYST SERV, V26, P111, DOI 10.1016/j.ecoser.2017.06.006
   Stoms DM, 2013, RENEW ENERG, V57, P289, DOI 10.1016/j.renene.2013.01.055
   Suuronen A, 2017, ENVIRON MANAGE, V60, P630, DOI 10.1007/s00267-017-0906-4
   Tang CQ, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-06837-3
   Tilman D, 2017, NATURE, V546, P73, DOI 10.1038/nature22900
   Torok P., 2017, Grasslands of the World
   Trainor AM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0162269
   Turney D, 2011, RENEW SUST ENERG REV, V15, P3261, DOI 10.1016/j.rser.2011.04.023
   Uchida K, 2015, J APPL ECOL, V52, P1033, DOI 10.1111/1365-2664.12443
   Uematsu Y, 2010, AGR ECOSYST ENVIRON, V135, P304, DOI 10.1016/j.agee.2009.10.010
   UN Environment Programme, 2019, EM GAP REP 2019 EM GAP REP 2019
   Walston LJ, 2016, RENEW ENERG, V92, P405, DOI 10.1016/j.renene.2016.02.041
   West AM, 2016, CLIMATIC CHANGE, V134, P565, DOI 10.1007/s10584-015-1553-5
   Williams DR, 2021, NAT SUSTAIN, V4, P314, DOI 10.1038/s41893-020-00656-5
   Willsteed E, 2017, SCI TOTAL ENVIRON, V577, P19, DOI 10.1016/j.scitotenv.2016.10.152
   Wilson MC, 2016, LANDSCAPE ECOL, V31, P219, DOI 10.1007/s10980-015-0312-3
   Wintle BA, 2019, P NATL ACAD SCI USA, V116, P909, DOI 10.1073/pnas.1813051115
   Yamamichi M, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.1067
   Yamaura Y, 2019, BIOL LETTERS, V15, DOI 10.1098/rsbl.2018.0577
   Yañez-Arenas C, 2016, CLIMATIC CHANGE, V134, P697, DOI 10.1007/s10584-015-1544-6
   Yu JF, 2018, JOULE, V2, P2605, DOI 10.1016/j.joule.2018.11.021
NR 101
TC 35
Z9 40
U1 12
U2 103
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD JUL 20
PY 2021
VL 779
AR 146475
DI 10.1016/j.scitotenv.2021.146475
EA MAR 2021
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA SJ7BE
UT WOS:000655685000003
PM 33752006
DA 2025-01-10
ER

PT J
AU Mafi-Gholami, D
   Jaafari, A
   Zenner, EK
   Kamari, AN
   Bui, DT
AF Mafi-Gholami, Davood
   Jaafari, Abolfazl
   Zenner, Eric K.
   Kamari, Akram Nouri
   Bui, Dieu Tien
TI Vulnerability of coastal communities to climate change: Thirty-year
   trend analysis and prospective prediction for the coastal regions of the
   Persian Gulf and Gulf of Oman
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Vulnerability; Coastal hazard; Climate change; Adaptation; Demographic
   indicators, RCP 8.5
ID STUDY MANGROVE FORESTS; SEA-LEVEL RISE; SOCIAL VULNERABILITY; HORMOZGAN
   PROVINCE; NATURAL HAZARDS; CHANGE IMPACTS; RESILIENCE; ADAPTATION;
   INDICATORS; FRAMEWORK
AB This study relates changes in social vulnerability of 20 counties on the northern coasts of the Persian Gulf (PG) and the Gulf of Oman (GO) over a 30-year period (1988-2017) to changing socio-economic conditions and environmental (climate) hazard. Social vulnerability in 2030, 2040 and 2050 is predicted based on the RCP8.5 climate change scenario that projects drought intensities and rising sea levels. Social vulnerability was based on the three dimensions of sensitivity, exposure, and adaptive capacity using 18 socio-economic and five climate indicators identified by experts. All but one indicator related very strongly to the dimension it sought to represent. Despite improvements in adaptive capacity over time, social vulnerability increased between 1988 and 2017 and rates of change accelerated after change point years that occurred between 1998 and 2002 in most counties. Extrapolating past changes of each indicator over time enabled forecasts of social vulnerability in the future. While social variability decreased between 2017 and 2030, it increased again between 2030 and 2050. The lowest future social vulnerability is expected along the eastern PG coast, the greatest along the western PG and the GO. The worsening of socio-economic indicators contributed to increased sensitivity, and increased drought intensities plus the expected rise in sea levels will lead to social vulnerabilities in 2050 comparable to present levels. Between 1.4 and 1.7 M people will live in areas that are likely submerged by water in the future. About 80% of these people live in six counties with variable social vulnerabilities. While counties with lower social variabilities migh/be better able to cope with the challenges posed by climate change, adaptation programs to enhance the resilience of the residents in these and the remaining counties along the PG and the GO need to be implemented soon to avoid uncontrolled mass migration of millions of people from the region. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Mafi-Gholami, Davood] Shahrekord Univ, Fac Nat Resources & Earth Sci, Dept Forest Sci, Shahrekord, Iran.
   [Jaafari, Abolfazl] Agr Res Educ & Extens Org AREEO, Res Inst Forests & Rangelands, Tehran, Iran.
   [Zenner, Eric K.] Penn State Univ, Dept Ecosyst Sci & Management, Forest Resources Bldg, University Pk, PA 16802 USA.
   [Kamari, Akram Nouri] Univ Tehran, Fac Nat Resource, Dept Environm, Tehran, Iran.
   [Bui, Dieu Tien] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam.
C3 Shahrekord University; Pennsylvania Commonwealth System of Higher
   Education (PCSHE); Pennsylvania State University; Pennsylvania State
   University - University Park; University of Tehran; Duy Tan University
RP Mafi-Gholami, D (corresponding author), Shahrekord Univ, Fac Nat Resources & Earth Sci, Dept Forest Sci, Shahrekord, Iran.; Bui, DT (corresponding author), Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam.
EM a.nourikamari@ut.ac.ir; jaafari@rifr-ac.ir; eric.zenner@psu.edu;
   a.nourikamari@ut.ac.ir; buitiendieu@duytan.edu.vn
RI Jaafari, Abolfazl/AAG-5500-2019; Tien Bui, Dieu/LGZ-9302-2024; Mafi
   Gholami, Davood/T-1267-2017
OI Mafi Gholami, Davood/0000-0003-4431-5381
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Adger WN, 2011, WIRES CLIM CHANGE, V2, P757, DOI 10.1002/wcc.133
   Ahsan MN, 2014, INT J DISAST RISK RE, V8, P32, DOI 10.1016/j.ijdrr.2013.12.009
   [Anonymous], 1966, 79 WMO
   Asadzadeh A, 2015, INT J DISAST RISK RE, V14, P504, DOI 10.1016/j.ijdrr.2015.10.002
   Barlow M, 2016, J CLIMATE, V29, P8547, DOI 10.1175/JCLI-D-13-00692.1
   BUISHAND TA, 1984, J HYDROL, V73, P51, DOI 10.1016/0022-1694(84)90032-5
   Chang DY, 1996, EUR J OPER RES, V95, P649, DOI 10.1016/0377-2217(95)00300-2
   Chen WF, 2013, INT J DISAST RISK SC, V4, P169, DOI 10.1007/s13753-013-0018-6
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Cutter SL, 2008, P NATL ACAD SCI USA, V105, P2301, DOI 10.1073/pnas.0710375105
   Depietri Y, 2013, INT J DISAST RISK RE, V6, P98, DOI 10.1016/j.ijdrr.2013.10.001
   Eslami-Andargoli L, 2009, ESTUAR COAST SHELF S, V85, P292, DOI 10.1016/j.ecss.2009.08.011
   Esmaeilpoorarabi N, 2018, LAND USE POLICY, V76, P471, DOI 10.1016/j.landusepol.2018.02.027
   Fekete A., 2009, NATURAL HAZARDS EART, V9
   Fekete A, 2019, NAT HAZARDS, V95, P585, DOI 10.1007/s11069-018-3506-6
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Finucane ML, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17020482
   Flanagan BE, 2011, J HOMEL SECUR EMERG, V8, DOI 10.2202/1547-7355.1792
   Ford JD, 2004, ARCTIC, V57, P389, DOI 10.14430/arctic516
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Hagenlocher M, 2018, SCI TOTAL ENVIRON, V631-632, P71, DOI 10.1016/j.scitotenv.2018.03.013
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   HILDEBRAND LP, 1992, MAR POLLUT BULL, V25, P94, DOI 10.1016/0025-326X(92)90194-B
   HUBERT P, 1989, J HYDROL, V110, P349, DOI 10.1016/0022-1694(89)90197-2
   Integrated Coastal Zone Management of Iran (ICZM), 2017, PORTS MAR ORG IR
   International Federation of Red Cross, 2002, RED CRESC SOC CTR RE
   Korf B, 2004, DEV CHANGE, V35, P275, DOI 10.1111/j.1467-7660.2004.00352.x
   Kuchaksaraei BS, 2019, INT J ENVIRON SCI TE, V16, P8061, DOI 10.1007/s13762-019-02238-1
   LEE AFS, 1977, TECHNOMETRICS, V19, P503, DOI 10.2307/1267892
   Lee YJ, 2014, ENVIRON IMPACT ASSES, V44, P31, DOI 10.1016/j.eiar.2013.08.002
   Libiseller C., 2004, A Program for Computation of Multivariate and Partial MANN-Kendall Test
   Mafi-Gholami D., 2015, Advances in Bio Research, V6, P78
   Mafi-Gholami D, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105972
   Mafi-Gholami D, 2019, J ENVIRON MANAGE, V252, DOI 10.1016/j.jenvman.2019.109628
   Mafi-Gholami D, 2019, SCI TOTAL ENVIRON, V656, P1326, DOI 10.1016/j.scitotenv.2018.11.462
   Mafi-Gholami D, 2017, ESTUAR COAST SHELF S, V199, P141, DOI 10.1016/j.ecss.2017.10.008
   Mafi-Gholami Davood, 2015, AES Bioflux, V7, P442
   Mendes N., 2011, 2011 Proceedings of 5th Latin-American Symposium on Dependable Computing (LADC 2011), P55, DOI 10.1109/LADC.2011.14
   Metzger MJ, 2006, AGR ECOSYST ENVIRON, V114, P69, DOI 10.1016/j.agee.2005.11.025
   Naghadehi MZ, 2009, EXPERT SYST APPL, V36, P8218, DOI 10.1016/j.eswa.2008.10.006
   Neumann B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118571
   Newton A, 2012, ESTUAR COAST SHELF S, V96, P39, DOI 10.1016/j.ecss.2011.07.012
   Nguyen TTX, 2016, OCEAN COAST MANAGE, V123, P18, DOI 10.1016/j.ocecoaman.2015.11.022
   Parry M.L., 2007, IPCC Climate Change 2007: Impacts, Adaptation and Vulnerability
   Pettitt A. N., 1979, Applied Statistics, V28, P126, DOI 10.2307/2346729
   Sahin O, 2014, NAT HAZARDS, V70, P395, DOI 10.1007/s11069-013-0818-4
   Seingier G, 2020, SPRINGER CLIMATE, P301, DOI 10.1007/978-3-030-22464-6_17
   Siagian TH, 2014, NAT HAZARDS, V70, P1603, DOI 10.1007/s11069-013-0888-3
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Sousa PHGO, 2013, OCEAN COAST MANAGE, V77, P24, DOI 10.1016/j.ocecoaman.2012.03.003
   Spielman SE, 2020, NAT HAZARDS, V100, P417, DOI 10.1007/s11069-019-03820-z
   Su SL, 2015, OCEAN COAST MANAGE, V116, P1, DOI 10.1016/j.ocecoaman.2015.06.026
   Tate E, 2012, NAT HAZARDS, V63, P325, DOI 10.1007/s11069-012-0152-2
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Wang GY, 2019, J FORESTRY RES, V30, P277, DOI 10.1007/s11676-018-0827-y
   Warner K, 2010, GLOBAL ENVIRON CHANG, V20, P402, DOI 10.1016/j.gloenvcha.2009.12.001
   Wu SY, 2002, CLIM RES, V22, P255, DOI 10.3354/cr022255
   Yin J, 2012, J COAST CONSERV, V16, P123, DOI 10.1007/s11852-012-0180-9
   Zhang SR, 2008, GLOBAL PLANET CHANGE, V60, P365, DOI 10.1016/j.gloplacha.2007.04.003
NR 60
TC 36
Z9 37
U1 0
U2 39
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 1
PY 2020
VL 741
AR 140305
DI 10.1016/j.scitotenv.2020.140305
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA NN5FT
UT WOS:000568815100011
PM 32887018
DA 2025-01-10
ER

PT J
AU Córdova, R
   Hogarth, NJ
   Kanninen, M
AF Cordova, Raid
   Hogarth, Nicholas J.
   Kanninen, Markku
TI Mountain Farming Systems' Exposure and Sensitivity to Climate Change and
   Variability: Agroforestry and Conventional Agriculture Systems Compared
   in Ecuador's Indigenous Territory of Kayambi People
SO SUSTAINABILITY
LA English
DT Article
DE smallholder farmers; agroforestry and conventional agricultural systems;
   climate change and variability; exposure and sensitivity; traditional
   and indigenous knowledge; tropical Andes
ID US CORN-BELT; TROPICAL ANDES; FOOD SECURITY; ELEVATED CO2; IMPACTS;
   SMALLHOLDER; 20TH-CENTURY; KNOWLEDGE; PATTERNS; HAIL
AB Smallholder farming is considered one of the most vulnerable sectors to the impacts of climate change, variability, and extremes, especially in the developing world. This high vulnerability is due to the socioeconomic limitations and high environmental sensitivity which affect the biophysical and socioeconomic components of their farming systems. Therefore, systems' functionality and farmers' livelihoods will also be affected, with significant implications for global food security, land-use/land-cover change processes and agrobiodiversity conservation. Thus, less vulnerable and more resilient smallholder farming systems constitute an important requisite for sustainable land management and to safeguard the livelihoods of millions of rural and urban households. This study compares a comprehensive socioeconomic and environmental dataset collected in 2015-2016 based on household interviews of 30 farmers of highland agroforestry systems and 30 farmers of conventional agriculture systems, to determine which system provides better opportunities to reduce exposure and sensitivity. A modified Climate Change Questionnaire Version 2 of the World Overview of Conservation Approaches and Technologies (WOCAT) was applied to collect the data. The interview data are based on the perceptions of Kayambi indigenous farmers about the levels of exposure and sensitivity of their farming systems during the last decade. Descriptive statistics were applied to analyze the data from the 60 farms. Results indicate that both agroforesters and conventional farmers clearly perceived increases in temperature and reductions in precipitation for the last decade, and expected this trend to continue in the next decade. Furthermore, conventional farmers perceived greater exposure to droughts (20%), solar radiation (43%), and pests, weeds and disease outbreaks (40%) than agroforesters. Additionally, results emphasize the better ability of agroforestry systems to reduce exposure and sensitivity to climate change and variability. These findings support the well-known assumptions about the key role played by agroforestry systems for climate change adaptation and mitigation, especially in developing countries.
C1 [Cordova, Raid; Hogarth, Nicholas J.; Kanninen, Markku] Univ Helsinki, Dept Forest Sci, Viikki Trop Resources Inst VITRI, Latokartanonkaari 7,POB 27, Helsinki 0014, Finland.
   [Hogarth, Nicholas J.] Univ Helsinki, Helsinki Inst Sustainabil Sci HELSUS, Helsinki 0014, Finland.
C3 University of Helsinki; University of Helsinki
RP Córdova, R (corresponding author), Univ Helsinki, Dept Forest Sci, Viikki Trop Resources Inst VITRI, Latokartanonkaari 7,POB 27, Helsinki 0014, Finland.
EM raul.cordova@helsinki.fi; nicholas.hogarth@helsinki.fi;
   markku.kanninen@helsinki.fi
RI Kanninen, Markku/AAW-9606-2021; Córdova, Raúl/N-8161-2019
OI Cordova, Raul/0000-0002-9302-7469; Hogarth,
   Nicholas/0000-0003-0954-5982; Kanninen, Markku/0000-0002-5708-9443
FU National Secretariat of Higher Education, Science, Technology and
   Innovation (SENESCYT); University of Helsinki; Viikki Tropical Resources
   Institute (VITRI)
FX This study was supported by the Ecuadorian people and government through
   a scholarship from the National Secretariat of Higher Education,
   Science, Technology and Innovation (SENESCYT). We thank the University
   of Helsinki and the Viikki Tropical Resources Institute (VITRI) for the
   academic and extra financial support for the field work. We are grateful
   to the Kayambi People Organization and all the farmers who contributed
   and shared their traditional knowledge.
CR Alexander C, 2011, BIOSCIENCE, V61, P477, DOI 10.1525/bio.2011.61.6.10
   [Anonymous], 2007, CLIM CHANG
   [Anonymous], 2007, Climate Change 2007: A Synthesis Report, P22
   [Anonymous], 2001, CLIMATE CHANGE 2001
   Basso E, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P693
   Belanger J., 2019, STATE WORLDS BIODIVE, P572
   Berdegue J.A., 2011, NEW DIRECTIONS SMALL
   Brimelow JC, 2017, NAT CLIM CHANGE, V7, P516, DOI [10.1038/nclimate3321, 10.1038/NCLIMATE3321]
   Brito C., 2014, THESIS
   Buytaert W, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011755
   Buytaert W, 2010, HYDROL EARTH SYST SC, V14, P1247, DOI 10.5194/hess-14-1247-2010
   BUYTAERT W, 2012, PANORAMA ANDINO CAMB, P37
   Buytaert W, 2011, GLOBAL ECOL BIOGEOGR, V20, P19, DOI 10.1111/j.1466-8238.2010.00585.x
   Cabay I., 1991, ANO ANO FIESTAS SAN, P132
   Canadas L, 1983, El mapa bioclimatico del Ecuador
   Cepeda E., 2010, THESIS
   CODEMIA, 2015, SIST AN RES CAR AGR
   Córdova R, 2018, LAND-BASEL, V7, DOI 10.3390/land7020045
   Cuesta F., 2012, Biodiversidad y Cambio Climatico en los Andes Tropicales-Conformacion de una red de investigacion para monitorear sus impactos y delinear acciones de adaptacion, P180
   Dasgupta P, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P613
   De Bievre B., 2012, PANORAMA ANDINO CAMB, P59
   De Boef W., 2016, MAINSTREAMING AGROBI, P30
   de la Torre A, 2011, ATMOS RES, V101, P112, DOI 10.1016/j.atmosres.2011.01.015
   De Noni G., 1996, LAND HUSBANDRY COMPO
   De Noni G., 1986, EROSION ECUADOR, P6
   Donat MG, 2013, J GEOPHYS RES-ATMOS, V118, P2098, DOI 10.1002/jgrd.50150
   Dooley K., MISSING PATHWAYS 1 5
   Ecuador Festival Inti Raymi, LONG DAY
   Emk P., 2007, THESIS
   FAO (Food and Agriculture Organization of the United Nations) IFAD (International Fund for Agricultural Development) UNICEF (United Nations Children's Fund) (WFP) World Food Programme & WHO (World Health Organization), 2018, The state of food security and nutrition in the world 2018. Building climate resilience for food security and nutrition, P181
   Fernandez MA, 2015, SPRINGERPLUS, V4, DOI 10.1186/s40064-015-1536-z
   Francou B., 2014, GLACIARES ANDES TROP, P99
   Garrity D., 2012, AGROFORESTRY THE FUT, VVolume 9, P21, DOI DOI 10.1016/j.gfs.2012.08.001
   Arjona RH, 2016, ANN I SUPER SANITA, V52, P368, DOI 10.4415/ANN_16_03_08
   Hatfield JL, 2004, J SOIL WATER CONSERV, V59, P51
   Haylock MR, 2006, J CLIMATE, V19, P1490, DOI 10.1175/JCLI3695.1
   Hofstede R., 2001, Los paramos del Ecuador. Particularidades, problemas y perspectivas, P161
   HORN R, 1995, SOIL TILL RES, V35, P23, DOI 10.1016/0167-1987(95)00479-C
   INAMHI, MAP PREC MED MULT 19
   INEC, POBL SUP KM 2 DENS P
   INEC, POBL AR SEG PROV CAN
   Jime'nez S., PROYECTO IMPACTO CAM
   Kotschi J, 2007, GAIA, V16, P98, DOI 10.14512/gaia.16.2.8
   Lasco RD, 2014, WIRES CLIM CHANGE, V5, P825, DOI 10.1002/wcc.301
   Leakey R., 2012, ADV AGROFORESTRY, V9, P21
   Lee JJ, 1996, AGR SYST, V52, P503, DOI 10.1016/S0308-521X(96)00015-7
   Liniger HP, 2007, LAND IS GREENER CASE, P364
   Lowder SK, 2016, WORLD DEV, V87, P16, DOI 10.1016/j.worlddev.2015.10.041
   Lucas R., 2006, GLOBAL BURDEN DIS SO, P250
   Magrin G.O., ADAPTACION CAMBIO CL
   Magrin GO, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1499
   Maldonado P., 2016, MAPA TERRITORIO CONF
   Marengo JA, 2004, J CLIMATE, V17, P2261, DOI 10.1175/1520-0442(2004)017<2261:COTLJE>2.0.CO;2
   Medina G., 2001, PARAMOS ECUADOR PART, P1
   Mejia R., 1998, ESTUDIO CAMBIO CLIMA, P85
   Mezher RN, 2012, ATMOS RES, V114, P70, DOI 10.1016/j.atmosres.2012.05.020
   Moreno L., 2015, ACTUALIZACION PLAN D
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Munoz A.G., VALIDACION ANALISIS
   Naess LO, 2013, WIRES CLIM CHANGE, V4, P99, DOI 10.1002/wcc.204
   Ni X, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-11395-7
   Olesen JE, 2014, CABI CLIM CHANGE SER, V5, P17, DOI 10.1079/9781780642895.0017
   Olsson L, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P793
   Ortiz R, 2011, AGROBIODIVERSITY MANAGEMENT FOR FOOD SECURITY: A CRITICAL REVIEW, P189, DOI 10.1079/9781845937614.0189
   Otavalo C., 2015, SISTEMATIZACION RESS
   Pachauri R.K., 2012, Agroforestry-The Future of Global Land Use, P13
   Palacios E., 1998, ESTUDIO CAMBIO CLIMA, P124
   Pascual U, 2011, ECON AGRAR RECUR NAT, V11, P191, DOI 10.7201/earn.2011.01.09
   Phillips DL, 1996, AGR SYST, V52, P481, DOI 10.1016/S0308-521X(96)00014-5
   Pilataxi C., 2001, PLAN ESTRATEGICO DES
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Postigo J., 2012, PANORAMA ANDINO CAMB, P141
   Rapsomanikis G., 2015, I5251E11215 FAO UN
   Rasmussen KL, 2014, GEOPHYS RES LETT, V41, P7359, DOI 10.1002/2014GL061767
   Reyer CPO, 2017, REG ENVIRON CHANGE, V0017
   Ribot J, 2010, NEW FRONT SOC POLICY, P47
   Ricciardi V, 2018, GLOB FOOD SECUR-AGR, V17, P64, DOI 10.1016/j.gfs.2018.05.002
   Rossing WAH, 2014, CABI CLIM CHANGE SER, V5, P69, DOI 10.1079/9781780642895.0069
   Salmi T., DETECTING TRENDS ANN
   Saposnik G, 2018, FRONT NEUROL, V9, DOI 10.3389/fneur.2018.00522
   Schoolmeester T., 2016, OUTLOOK CLIMATE CHAN, P94
   Selvarajh-Jaffery R., 2007, ANN REPORT 2006 WORL, P60
   Settele J, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P271
   Sietz D, 2012, REG ENVIRON CHANGE, V12, P489, DOI 10.1007/s10113-011-0246-5
   Soto B., 2007, POLITICAS AGR FAMILI
   St Clair SB, 2010, PLANT SOIL, V335, P101, DOI 10.1007/s11104-010-0328-z
   Steiner A., 2012, Agroforestry-The Future of Global Land Use, P17, DOI [10.1007/978-94-007-4676-3_5, DOI 10.1007/978-94-007-4676-3_5]
   Thrupp L. A., 2004, Journal of Crop Improvement, V12, P315, DOI 10.1300/J411v12n01_03
   Tuomisto HL, 2012, J ENVIRON MANAGE, V112, P309, DOI 10.1016/j.jenvman.2012.08.018
   Urrutia R, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2008JD011021
   Vadjunec JM, 2016, LAND-BASEL, V5, DOI 10.3390/land5040034
   Valdivia C., 2013, Advances in Geosciences, V33, P69, DOI DOI 10.5194/ADGEO-33-69-2013
   van Noordwijk M, 2014, CABI CLIM CHANGE SER, V5, P216, DOI 10.1079/9781780642895.0216
   Vecchia P., 2007, PROTECTING WORKERS U, P109
   Verchot L. V., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P901, DOI 10.1007/s11027-007-9105-6
   Vuille M, 2003, CLIMATIC CHANGE, V59, P75, DOI 10.1023/A:1024406427519
   Vuille M., CLLIIMATE CHANGE T 1
   Vuille M, 2008, EARTH-SCI REV, V89, P79, DOI 10.1016/j.earscirev.2008.04.002
   Wasterlund S.D., 2018, MANAGING HEAT AGR WO, P53
   Webber H, 2014, CABI CLIM CHANGE SER, V5, P167, DOI 10.1079/9781780642895.0167
   WOCAT, QUEST AD SLM TECHN G
   WWF, 2018, LIV PLAN REP 2018 AI, P144
   Morocho PY, 2015, SOPHIA-COLECCION FIL, P231, DOI 10.17163/soph.n18.2015.12
   Zomer R.J., TREES FARMS UPDATE R
NR 104
TC 13
Z9 15
U1 3
U2 34
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD MAY 1
PY 2019
VL 11
IS 9
AR 2623
DI 10.3390/su11092623
PG 30
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA IA4FF
UT WOS:000469518700171
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Garschagen, M
   Surtiari, GAK
   Harb, M
AF Garschagen, Matthias
   Surtiari, Gusti Ayu Ketut
   Harb, Mostapha
TI Is Jakarta's New Flood Risk Reduction Strategy Transformational?
SO SUSTAINABILITY
LA English
DT Article
DE transformation; flood risk reduction; Jakarta; risk governance
ID CLIMATE-CHANGE; URBAN-DEVELOPMENT; ADAPTATION; IMPACT; COMMUNITY;
   PATHWAYS
AB On a conceptual and normative level, the debate around transformation in the context of disaster risk reduction and climate change adaptation has been rising sharply over the recent years. Yet, whether and how transformation occurs in the messy realities of policy and action, and what separates it from other forms of risk reduction, is far from clear. Jakarta appears to be the perfect example to study these questions. It is amongst the cities with the highest flood risk in the world. Its flood hazard is driven by land subsidence, soil sealing, changes in river discharge, andincreasinglysea level rise. As all of these trends are set to continue, Jakarta's flood hazard is expected to intensify in the future. Designing and implementing large-scale risk reduction and adaption measures therefore has been a priority of risk practitioners and policy-makers at city and national level. Against this background, the paper draws on a document analysis and original empirical household survey data to review and evaluate current adaptation measures and to analyze in how far they describe a path that is transformational from previous risk reduction approaches. The results show that the focus is clearly on engineering solutions, foremost in the Giant Sea Wall project. The project is likely to transform the city's flood hydrology. However, it cements rather than transforms the current risk management paradigm which gravitates around the goal of controlling flood symptoms, rather than addressing their largely anthropogenic root causes. The results also show that the planned measures are heavily contested due to concerns about ecological impacts, social costs, distributional justice, public participation, and long-term effectiveness. On the outlook, the results therefore suggest that the more the flood hazard intensifies in the future, the deeper a societal debate will be needed about the desired pathway in flood risk reduction and overall development planningparticularly with regards to the accepted levels of transformation, such as partial retreat from the most flood-affected areas.
C1 [Garschagen, Matthias; Surtiari, Gusti Ayu Ketut; Harb, Mostapha] United Nations Univ, Inst Environm & Human Secur, UN Campus,Pl Vereinten Nationen 1, D-53113 Bonn, Germany.
RP Garschagen, M (corresponding author), United Nations Univ, Inst Environm & Human Secur, UN Campus,Pl Vereinten Nationen 1, D-53113 Bonn, Germany.
EM garschagen@ehs.unu.edu; surtiari@ehs.unu.edu; harb@ehs.unu.edu
OI Harb, Mostapha/0000-0001-8951-8700
FU German Federal Ministry of Education and Research within the TWIN-SEA
   research grant
FX This research was funded by the German Federal Ministry of Education and
   Research within the TWIN-SEA research grant.
CR Abidin HZ, 2015, P INT ASS HYDROL SCI, V370, P15, DOI 10.5194/piahs-370-15-2015
   [Anonymous], 2014, ARS CLIM CHANG 2014
   [Anonymous], 2012, SPECIAL REPORT WORKI
   [Anonymous], 2015, The Jakarta Post
   Badan Pusat Statistik (BPS) Statistical Office of Indonesia, 2015, JAK PROV FIG
   Budiyono Y, 2016, NAT HAZARD EARTH SYS, V16, P757, DOI 10.5194/nhess-16-757-2016
   Caljouw M, 2005, BIJDR TAAL-LAND-V, V161, P454
   Chan F, 2017, STRAITS TIME    1012
   Colven E, 2017, WATER ALTERN, V10, P250
   Congedo M, 2016, P 24 EUR SIGN PROC C
   Coordinating Ministry for Economic Affairs (CMEA), 2014, NAT CAP INT COAST DE
   DiGregorio M, POLITICAL EC URBANIS
   Djalante R, 2017, DISAST RISK REDUCT, P1, DOI 10.1007/978-3-319-54466-3
   Elyda Corry, 2015, Jakarta Post
   Few R, 2017, PALGR COMMUN, V3, DOI 10.1057/palcomms.2017.92
   Gillard R, 2016, WIRES CLIM CHANGE, V7, P251, DOI 10.1002/wcc.384
   Glöckner A, 2010, FOUNDATIONS FOR TRACING INTUITION: CHALLENGES AND METHODS, P83
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Hanson B, 2005, SCIENCE, V309, P1029, DOI 10.1126/science.309.5737.1029
   Hanson S, 2011, CLIMATIC CHANGE, V104, P89, DOI 10.1007/s10584-010-9977-4
   Hidayatno A, 2017, INT J INNOV SUSTAIN, V11, P37, DOI 10.1504/ijisd.2017.10000468
   International Federation of the Red Cross and Red Crescent Societies (IFRC), 2007, IND JAK FLOODS APP M
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Koch W., 2015, NAT GEOGR
   Mapfumo P, 2017, CLIM DEV, V9, P439, DOI 10.1080/17565529.2015.1040365
   Marfai MA, 2015, NAT HAZARDS, V75, P1127, DOI 10.1007/s11069-014-1365-3
   Mas JF, 2017, EUR J REMOTE SENS, V50, P626, DOI 10.1080/22797254.2017.1387505
   Mezzi P., 2016, GREAT GARUDA MASTERP
   Neise T, 2018, ENVIRON PLAN C-POLIT, V36, P1522, DOI 10.1177/2399654418771079
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   Oh S, 2018, J CLEAN PROD, V178, P507, DOI 10.1016/j.jclepro.2017.12.283
   Padawangi R, 2012, RES URBAN SOCIOL, V12, P321, DOI 10.1108/S1047-0042(2012)0000012016
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Pelling M., 2014, J EXTREME EVENTS, V01
   Pelling M, 2015, CLIMATIC CHANGE, V133, P113, DOI 10.1007/s10584-014-1303-0
   Ribot J, 2011, GLOBAL ENVIRON CHANG, V21, P1160, DOI 10.1016/j.gloenvcha.2011.07.008
   Rustiadi E., 2015, URBAN DEV CHALLENGES, P421
   Solecki W, 2017, ECOL SOC, V22, DOI 10.5751/ES-09102-220238
   Sumantyo JTS, 2016, IEEE GEOSCI REMOTE S, V13, P1472, DOI 10.1109/LGRS.2016.2592940
   Surtiari GAK, 2017, DISAST RISK REDUCT, P469, DOI 10.1007/978-3-319-54466-3_19
   Thomalla F, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10051458
   Van Dijk M. P., 2016, J COAST ZONE MANAG, V19, DOI [10.4172/2473-3350.1000435, DOI 10.4172/2473-3350.1000435]
   van Voorst R, 2016, HABITAT INT, V52, P5, DOI 10.1016/j.habitatint.2015.08.023
   Ward PJ, 2013, ENVIRON POLIT, V22, P518, DOI 10.1080/09644016.2012.683155
   WBGU (German Advisory Council on Global Change), 2011, WORLD TRANS SOC CONS
   Wijayanti P, 2017, NAT HAZARDS, V86, P1059, DOI 10.1007/s11069-016-2730-1
   Win TL, 2017, FLOOD PRONE JAKARTA
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
NR 49
TC 29
Z9 30
U1 1
U2 39
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD AUG
PY 2018
VL 10
IS 8
AR 2934
DI 10.3390/su10082934
PG 18
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA GW3CI
UT WOS:000446767700350
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Zhang, J
   Nielsen, SE
   Stolar, J
   Chen, YH
   Thuiller, W
AF Zhang, Jian
   Nielsen, Scott E.
   Stolar, Jessica
   Chen, Youhua
   Thuiller, Wilfried
TI Gains and losses of plant species and phylogenetic diversity for a
   northern high-latitude region
SO DIVERSITY AND DISTRIBUTIONS
LA English
DT Article
DE climate refugia; ecological niche modelling; ensemble forecast;
   evolutionary diversity; extinction risk; range shift
ID CLIMATE-CHANGE; NONRANDOM EXTINCTION; DISTRIBUTION MODELS; HALF-CENTURY;
   RANGE SHIFTS; SELECTION; IMPACTS; RISK; TREE; CONSEQUENCES
AB Aim Forecasting potential patterns in species' distributions and diversity under climate change is crucial for biodiversity conservation. Although high-latitude regions are expected to experience some of the greatest increases in temperature due to global warming, little is known on how individual responses in species will affect patterns in phylogenetic diversity (PD).
   Location Alberta, Canada.
   Method sWe used 160,589 occurrence records for 1541 species of seed plants in Alberta (nearly 90% of the province's seed flora) and ensemble niche models to project current and future suitable habitats. We then examined climate change vulnerability of individual species and the potential impacts of climate change on species richness, PD and both taxonomic and phylogenetic endemism (PE). We also assessed whether predicted losses of PD were distributed randomly across the plant tree of life.
   Results We found that 368 species (24%) may lose on average >80% of their current suitable climates (habitats), while 539 species (35%) were projected to more than double their current suitable range. Both species richness and PD were predicted to increase in most areas, except for the species-rich Rocky Mountains, which are predicted to experience future declines. Maps of taxonomic and PE identified several regions with high conservation value and climate change threat suggesting priorities for conservation and climate change adaptation. Overall, a non-random extinction risk was found for Alberta's flora, demonstrating potential future impacts of climate change on the loss of evolutionary history.
   Main conclusions Our analyses suggest that climate change will have asymmetrical effects on the distribution of Alberta's plant diversity and endemism and a non-random extinction risk of the current state of species evolutionary history. Our results provide practical guidance for biodiversity conservation and management in this region by prioritizing species' vulnerabilities and places with higher taxonomic or evolutionary risk due to future climate change.
C1 [Zhang, Jian; Nielsen, Scott E.; Stolar, Jessica; Chen, Youhua] Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2H1, Canada.
   [Zhang, Jian] Aarhus Univ, Dept Biosci, Sect Ecoinformat & Biodivers, DK-8000 Aarhus C, Denmark.
   [Thuiller, Wilfried] Univ Grenoble Alpes, Lab Ecol Alpine LECA, F-38000 Grenoble, France.
   [Thuiller, Wilfried] CNRS, Lab Ecol Alpine LECA, F-38000 Grenoble, France.
C3 University of Alberta; Aarhus University; Communaute Universite Grenoble
   Alpes; Universite Grenoble Alpes (UGA); Centre National de la Recherche
   Scientifique (CNRS); Universite Savoie Mont Blanc; Communaute Universite
   Grenoble Alpes; Universite Grenoble Alpes (UGA); Centre National de la
   Recherche Scientifique (CNRS); Universite Savoie Mont Blanc
RP Zhang, J (corresponding author), Aarhus Univ, Dept Biosci, Ecoinformat & Biodivers Grp, Ny Munkegade 116,Bldg 1540, DK-8000 Aarhus C, Denmark.
EM jzhang1982@gmail.com
RI Zhang, Jian/JAN-8204-2023; Nielsen, Scott/O-7482-2019; Thuiller,
   Wilfried/G-3283-2010; Zhang, Jian/A-7878-2008
OI Zhang, Jian/0000-0003-0589-6267
FU CCEMC (Climate Change and Emissions Management Corporation); ABMI
   (Alberta Biodiversity Monitoring Institute); COSIA (Canada's Oil Sands
   Innovation Alliance); European Research Council under the European
   Community's Seven Framework Programme FP7 [281422]
FX This study was supported by CCEMC (Climate Change and Emissions
   Management Corporation), ABMI (Alberta Biodiversity Monitoring
   Institute) and COSIA (Canada's Oil Sands Innovation Alliance). W.T.
   received funding from the European Research Council under the European
   Community's Seven Framework Programme FP7/2007-2013 Grant Agreement no.
   281422 (TEEMBIO). The LECA is part of labex OSUG@2020 (ANR10 LABX56). We
   would like to thank Dr. Joyce Gould and Dr. Shongming Huang for sharing
   their species occurrence data, and Ms. Amy Nixon, Mr. Jingxian Wang and
   Dr. Xianli Wang for technical support.
CR Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Allouche O, 2006, J APPL ECOL, V43, P1223, DOI 10.1111/j.1365-2664.2006.01214.x
   [Anonymous], 2014, PREDICTING INVASIVE
   [Anonymous], 1982, The Lake Athabasca Sand Dunes of northern Saskatchewan and Alberta, Canada. I. The land and vegetation
   [Anonymous], 2014, ARS CLIM CHANG 2014
   [Anonymous], OPEC ANN STAT B 2013
   [Anonymous], 2005, EC HUM WELL BEING BI
   [Anonymous], 1981, The Biological Aspects of Rare Plant Conservation
   [Anonymous], NAT REG SUBR ALB
   [Anonymous], 2013, ENV SUSTAINABLE RESO
   [Anonymous], APPL ECOL
   [Anonymous], 1990, Generalized additive models
   [Anonymous], 2014, NatureServe Explorer: An online encyclopedia of life
   [Anonymous], 2001, Machine Learning
   [Anonymous], THESIS U ALBERTA EDM
   Araújo MB, 2007, TRENDS ECOL EVOL, V22, P42, DOI 10.1016/j.tree.2006.09.010
   Araújo MB, 2012, ECOLOGY, V93, P1527, DOI 10.1890/11-1930.1
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Barrow E., 2005, CLIMATE SCENARIOS AL
   Bergengren JC, 2011, CLIMATIC CHANGE, V107, P433, DOI 10.1007/s10584-011-0065-1
   Boyce MS, 2002, ECOL MODEL, V157, P281, DOI 10.1016/S0304-3800(02)00200-4
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Clavel J, 2011, FRONT ECOL ENVIRON, V9, P222, DOI 10.1890/080216
   Colles A, 2009, ECOL LETT, V12, P849, DOI 10.1111/j.1461-0248.2009.01336.x
   Crisp MD, 2001, J BIOGEOGR, V28, P183, DOI 10.1046/j.1365-2699.2001.00524.x
   Darwin C., 1859, ORIGIN SPECIES MEANS
   FAITH DP, 1992, BIOL CONSERV, V61, P1, DOI 10.1016/0006-3207(92)91201-3
   Flannigan MD, 2005, CLIMATIC CHANGE, V72, P1, DOI 10.1007/s10584-005-5935-y
   Franklin J., 2009, Mapping species distributions - spatial inference and prediction
   Friedman JH, 2001, ANN STAT, V29, P1189, DOI 10.1214/aos/1013203451
   Hamann A, 2006, ECOLOGY, V87, P2773, DOI 10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2
   Hamann A, 2013, B AM METEOROL SOC, V94, P1307, DOI 10.1175/BAMS-D-12-00145.1
   Hogg EH, 2008, CAN J FOREST RES, V38, P1373, DOI 10.1139/X08-001
   Isaac NJB, 2007, PLOS ONE, V2, DOI 10.1371/journal.pone.0000296
   Jetz W, 2007, PLOS BIOL, V5, P1211, DOI 10.1371/journal.pbio.0050157
   Kulig JJ, 1996, QUATERN INT, V32, P53, DOI 10.1016/S1040-6182(96)90014-2
   Kurek J, 2013, P NATL ACAD SCI USA, V110, P1761, DOI 10.1073/pnas.1217675110
   Kurz WA, 2008, NATURE, V452, P987, DOI 10.1038/nature06777
   Lempriere T.C., 2008, The Importance of Forest Sector Adaptation to Climate Change
   Lenoir J, 2015, ECOGRAPHY, V38, P15, DOI 10.1111/ecog.00967
   Malcolm JR, 2002, J BIOGEOGR, V29, P835, DOI 10.1046/j.1365-2699.2002.00702.x
   MARQUARDT DW, 1970, TECHNOMETRICS, V12, P591, DOI 10.2307/1267205
   McKinney ML, 1999, TRENDS ECOL EVOL, V14, P450, DOI 10.1016/S0169-5347(99)01679-1
   Minteer BA, 2010, ECOL APPL, V20, P1801, DOI 10.1890/10-0318.1
   Moss E.H., 1983, Flora of Alberta. A manual of flowering plants, conifers, ferns and fern allies found growing without cultivation in the province of Alberta, VSecond
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Nielsen SE, 2010, BIOL CONSERV, V143, P1623, DOI 10.1016/j.biocon.2010.04.007
   Nielsen SE, 2003, ECOSCIENCE, V10, P1
   Palen WJ, 2014, NATURE, V510, P465, DOI 10.1038/510465a
   Peterson A.T., 2011, Ecological Niches and Geographic Distributions (MPB- 49), V56
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2009, ECOL APPL, V19, P181, DOI 10.1890/07-2153.1
   Pimm SL, 2014, SCIENCE, V344, P987, DOI 10.1126/science.1246752
   Pio DV, 2014, GLOBAL CHANGE BIOL, V20, P1538, DOI 10.1111/gcb.12524
   Post E., 2013, ECOLOGY CLIMATE CHAN
   Price D.T., 2011, High resolution interpolation of IPCC AR4 GCM climate scenarios for Canada
   Price DT, 2013, ENVIRON REV, V21, P322, DOI 10.1139/er-2013-0042
   Purvis A, 2000, SCIENCE, V288, P328, DOI 10.1126/science.288.5464.328
   Roquet C, 2013, ECOGRAPHY, V36, P13, DOI 10.1111/j.1600-0587.2012.07773.x
   Rosauer D, 2009, MOL ECOL, V18, P4061, DOI 10.1111/j.1365-294X.2009.04311.x
   Scheffer M, 2001, NATURE, V413, P591, DOI 10.1038/35098000
   Stolar J, 2015, DIVERS DISTRIB, V21, P595, DOI 10.1111/ddi.12279
   Team RC, 2014, R: A Language and Environment for Statistical Computing
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Thomas CD, 2011, TRENDS ECOL EVOL, V26, P216, DOI 10.1016/j.tree.2011.02.006
   Thuiller W, 2003, GLOBAL CHANGE BIOL, V9, P1353, DOI 10.1046/j.1365-2486.2003.00666.x
   Thuiller W, 2005, P NATL ACAD SCI USA, V102, P8245, DOI 10.1073/pnas.0409902102
   Thuiller W, 2014, ECOGRAPHY, V37, P1254, DOI 10.1111/ecog.00670
   Thuiller W, 2011, NATURE, V470, P531, DOI 10.1038/nature09705
   Thuiller W, 2009, ECOGRAPHY, V32, P369, DOI 10.1111/j.1600-0587.2008.05742.x
   Vamosi JC, 2008, ECOL LETT, V11, P1047, DOI 10.1111/j.1461-0248.2008.01215.x
   Webb CO, 2008, BIOINFORMATICS, V24, P2098, DOI 10.1093/bioinformatics/btn358
   Webb CO, 2002, ANNU REV ECOL SYST, V33, P475, DOI 10.1146/annurev.ecolsys.33.010802.150448
   Webb CO, 2000, AM NAT, V156, P145, DOI 10.1086/303378
   Winter M, 2013, TRENDS ECOL EVOL, V28, P199, DOI 10.1016/j.tree.2012.10.015
   Yesson C, 2007, PLOS ONE, V2, DOI 10.1371/journal.pone.0001124
   Zanne AE, 2014, NATURE, V506, P89, DOI 10.1038/nature12872
   Zhang J, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103920
   Zhang J, 2014, BIOGEOSCIENCES, V11, P2793, DOI 10.5194/bg-11-2793-2014
   Zhang J, 2015, P NATL ACAD SCI USA, V112, P4009, DOI 10.1073/pnas.1420844112
   Zhang J, 2014, J PLANT ECOL, V7, P188, DOI 10.1093/jpe/rtt068
NR 81
TC 34
Z9 38
U1 0
U2 105
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1366-9516
EI 1472-4642
J9 DIVERS DISTRIB
JI Divers. Distrib.
PD DEC
PY 2015
VL 21
IS 12
BP 1441
EP 1454
DI 10.1111/ddi.12365
PG 14
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA CV5TM
UT WOS:000364334100007
DA 2025-01-10
ER

PT J
AU Baytelieva, A
   Lee, WK
   Wang, SW
   Iskakova, A
   Ziyayeva, G
   Shilibek, K
   Azatov, N
   Zholamanov, N
   Minarbekov, Z
AF Baytelieva, Anar
   Lee, Woo-Kyun
   Wang, Sonam Wangyel
   Iskakova, Aliya
   Ziyayeva, Gulnar
   Shilibek, Kenzhegali
   Azatov, Nurakhmet
   Zholamanov, Nurzhan
   Minarbekov, Zhamalkhan
TI Assessing the Vulnerability of Nomadic Pastoralists' Livelihoods to
   Climate Change in the Zhetysu Region of Kazakhstan
SO LAND
LA English
DT Article
DE livelihood vulnerability index; nomads; sensitivity; adaptive ability;
   climate change; environmental code of Kazakhstan Republic
AB Kazakhstan is historically a livestock-producing country. For the first time in this study, we attempted to assess the vulnerability of nomadic pastoralists in Kazakhstan to climate change using the Livelihood Vulnerability Index (LVI). To collect data, a survey of 100 household heads was conducted on fourteen main components and fifty-six sub-components. The study was conducted in the period from May to July 2022 in the Panfilov (PD) and Kerbulak (KD) districts of the Zhetysu region, where the Altyn-Emel State National Nature Park is located. The results of the study were combined using a composite index method and comparing different vulnerability indicators. Natural disasters, which manifest as the effects of drought, temperature fluctuations, and precipitation, contribute most to the vulnerability of nomads living in remote mountain areas with a complex infrastructure. According to the results of the study, nomads of both regions have high vulnerability in such components as natural resources, human-wildlife conflict, housing type, agriculture and food security, and social networks. High vulnerability in the "Finances and incomes" component was found only in the pastoralists of the PD. Identifying the levels of vulnerability of nomadic households to climate change, as well as understanding their adaptation strategies, will enable pastoralists to gain access to new ways of reducing the vulnerability of their livelihoods. Currently, the country practices a strategy to reduce the vulnerability of pastoral nomads' livelihoods by insuring livestock against natural or natural hazards and other risks; involving the population in environmental-protection activities and helping them to obtain sustainable financial resources when they refuse to hunt endangered animals; non-agricultural diversification of high-altitude ecotourism in rural areas in their area of residence; and improving financial literacy by providing training and providing information on low-interest loans under state projects and livestock subsidy mechanisms, as well as training in organizing cooperatives within the framework of legal status, which will ensure them stable sales of products and income growth. The results of software research serve as a basis for taking measures within the framework of the development and implementation of state programs for climate change adaptation of the Environmental Code of the Republic of Kazakhstan, where agriculture is one of the priority areas of management.
C1 [Baytelieva, Anar; Ziyayeva, Gulnar; Shilibek, Kenzhegali; Azatov, Nurakhmet; Zholamanov, Nurzhan; Minarbekov, Zhamalkhan] MKh Dulaty Taraz Reg Univ, Inst Water Management & Environm Management, Taraz 080000, Kazakhstan.
   [Lee, Woo-Kyun] Korea Univ, Div Environm Sci & Ecol Engn, Seoul 02841, South Korea.
   [Wang, Sonam Wangyel] Korea Univ, OJEong Resilience Inst, Div Environm Sci & Ecol Engn, Seoul 02841, South Korea.
   [Iskakova, Aliya] Temirbek Zhurgenov Kazakh Natl Acad Arts, Alma Ata 050000, Kazakhstan.
C3 Korea University; Korea University
RP Wang, SW (corresponding author), Korea Univ, OJEong Resilience Inst, Div Environm Sci & Ecol Engn, Seoul 02841, South Korea.
EM am.bajtelieva@dulaty.kz; leewk@korea.ac.kr; wangsonam@korea.ac.kr;
   gk.ziyaeva@dulaty.kz; kk.shilibek@dulaty.kz; std.a.nurakhmet@dulaty.kz;
   nzh.zholamanov@dulaty.kz; zhi.minarbekov@dulaty.kz
RI Lee, Woo-Kyun/AAP-9837-2020; Zyaeva, Gulnar/AGH-9651-2022
OI Lee, Woo-Kyun/0000-0002-2188-359X; Ziyayeva, Gulnar/0000-0001-7260-2164
FU Core Research Institute Basic Science Research Program through the
   National Research Foundation of Korea (NRF); National Research
   Foundation of Korea; OJEong Resilience Institute at Korea University
FX The authors would like to thank the National Research Foundation of
   Korea and the OJEong Resilience Institute at Korea University for
   supporting this research. In addition, we would also like to thank the
   employees of "Kazhydromet" Republican State Enterprise's branch for
   providing data.
CR Abakanov Y.N., 2021, Environmental Policy in Kazakhstan: Outlines and Prospects, P28
   Abd Majid N, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11246935
   adilet.zan.kz, Law of the Republic of Kazakhstan Dated February 20, 2017 No. 47-VI "On Pastures
   Agrawal A, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P350
   [Anonymous], 2022, Law of the Republic of Kazakhstan No. 178-VII LRK
   [Anonymous], Demographic Statistics. 21 Series
   [Anonymous], 2022, Global Food Security Index 2022
   [Anonymous], 2015, Sendai Framework for Disaster Risk Reduction 20152030, V1st, P9
   [Anonymous], 2001, Oecd annual report 2001, DOI DOI 10.1787/ANNREP-2001-EN
   [Anonymous], 2007, Human Development Report 2007/2008
   [Anonymous], Code of the Republic of Kazakhstan Dated January 2, 2021 No. 400-VI "Environmental Code of the Republic of Kazakhstan
   Antonov O., 2014, Green Energy of Kazakhstan in the 21st Century: Myths, Reality and Prospects
   baiterek, Insurance of Fields and Animals Will Cost Farmers Cheaper
   Batyrbekov I., Legislation in the Field of Renewable Energy Sources in Kazakhstan
   Beringer AL, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10051452
   Downing TE, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P105
   Dzhabagieva K., 2023, News Acad. Sci. Repub. Kazakhstan Ser. Geol. Tech. Sci, V2, P57, DOI [10.32014/2023.2518-170X.280, DOI 10.32014/2023.2518-170X.280]
   el.kz, By 2027, All Villages in Kazakhstan Will Be Connected to the Internet Available
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Hales S, 2003, LANCET, V362, P1775, DOI 10.1016/S0140-6736(03)14939-2
   Handayani W, 2017, ADV CLIM CHANG RES, V8, P286, DOI 10.1016/j.accre.2017.11.002
   How the Auyl Amanats Program, Will Help Raise the Standard of Living of Villagers in Kazakhstan
   IEA, 2006, World Energy Outlook 2006, V2nd, P385
   Iliev O. L., 2013, World Applied Sciences Journal, V24, P561
   Immunization, 2005, CH-1211
   impact.economist, Blue Peace Index Economist Impact
   Joseph J, 2013, DISASTERS, V37, P185, DOI 10.1111/j.1467-7717.2012.01299.x
   kapital.kz, 76,000 Kazakhstanis to Undergo Financial Literacy Training
   Kayastha RB, 2023, LAND-BASEL, V12, DOI 10.3390/land12051105
   Kazhydromet, Will Report Unfavorable Meteorological Conditions in Populated Areas of Kazakhstan
   Kerven C., 2011, Pastoralism and Farming in Central Asias Mountains: A Research Review, P8, DOI [10.5167/uzh-52730, DOI 10.5167/UZH-52730]
   Khajuria A., 2012, J. Earth Sci. Clim. Chang., V3, P110, DOI [10.4172/2157-7617.1000110, DOI 10.4172/2157-7617.1000110]
   Kushnarenko T.V., 2020, Bull. Rostov State Univ. Econ, V2, P53
   kz, Kazakhstanis Can Insure Pets under the New System
   kz.kursiv.media, How the Number of Livestock and Poultry in Kazakhstan Has Changed Over 10 Years
   Leiter T., 2018, Adaptation Metrics: Perspectives on Measuring, Aggregating and Comparing Adaptation Results: Pitfalls and Potential of Measuring Climate Change Adaptation Through Adaptation Metrics
   Ludi E, 2003, MT RES DEV, V23, P119, DOI 10.1659/0276-4741(2003)023[0119:SPMIKA]2.0.CO;2
   Maxwell S., 1992, HOUSEHOLD FOOD SECUR, P24
   Ministry of National Economy of the Republic of Kazakhstan and Economic Research Institute JSC, 2022, Kazakhstan on the Implementation of the 2030 Agenda for Sustainable Development, P13
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   old.stat, Dynamics of the Main Indicators of Socio-Economic Development of the Almaty Region for 1991-2021
   old.stat.gov, Main Socio-Economic Indicators by Regions, Cities and Single-Industry Towns Rus-1
   Rai P, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14042339
   Rosenzweig C, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P79
   Sachs J., The Decade of Action for the Sustainable Development Goals: Sustainable Development Report 2021, P268
   Sangeeta S., 2022, Financ. Theory Pract, V26, P121, DOI [10.26794/2587-5671-2022-26-5-121-131, DOI 10.26794/2587-5671-2022-26-5-121-131]
   Sarsenbaev K. N., 2013, World Applied Sciences Journal, V23, P638
   Sen A.K., 2000, SOCIAL EXCLUSION CON
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P1
   Sujakhu NM, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11102977
   Sullivan C., 2002, Derivation and Testing of the Water Poverty Index Phase 1, Final Report, P2
   Tsyba Y., 2017, Current State of the Electric Power Industry: Kazakhstan's Electric Power Industry and Prospects for Using Renewable Energy Sources
   United Nations, 2020, United Nations Sustainable Development Cooperation Frame Work Country Kazakhstan. Year 20212025
   United Nations, 2020, United Nations E-Government Survey 2020: Digital Government in the Decade of Action for Sustainable Development: With Addendum on COVID-19 Response, P48
   Venus TE, 2022, ENVIRON DEV SUSTAIN, V24, P1981, DOI 10.1007/s10668-021-01516-8
   Wu Q., 2014, J. Capital Normal Univ. (Nat. Sci. Ed.), V35, P61, DOI [10.19789/j.1004-9398.2014.03.013, DOI 10.19789/J.1004-9398.2014.03.013]
   Yerlan A.E., 2020, RGUFKSMiT 2020, P84
   zakon, Only 39% of Residents of Zhetysu Region Have Access to 4G
   Zhao XY, 2022, ENVIRON DEV SUSTAIN, V24, P9665, DOI 10.1007/s10668-021-01827-w
   Zhao Yan-xia, 2007, Shengtaixue Zazhi, V26, P754
NR 60
TC 1
Z9 1
U1 3
U2 10
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD NOV
PY 2023
VL 12
IS 11
AR 2038
DI 10.3390/land12112038
PG 26
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA Z7LY5
UT WOS:001113865500001
OA gold
DA 2025-01-10
ER

PT J
AU Jacobs, P
   Carbutt, C
   Beever, EA
   Foggin, JM
   Martin, M
   Orchard, S
   Sayre, R
AF Jacobs, Peter
   Carbutt, Clinton
   Beever, Erik A. A.
   Foggin, J. Marc
   Martin, Madeline
   Orchard, Shane
   Sayre, Roger
TI A Decision-Support Tool to Augment Global Mountain Protection and
   Conservation, including a Case Study from Western Himalaya
SO LAND
LA English
DT Article
DE biodiversity hotspots; decision-support tool; ecosystem services; global
   mountain priorities; Key Biodiversity Areas; mountain biodiversity;
   mountain protected and conserved areas; western Himalaya; world
   ecosystems
ID CLIMATE-CHANGE; SYSTEMS; HABITAT; FUTURE; MATTER; AREA
AB Mountains are remarkable storehouses of global biodiversity that provide a broad range of ecosystem services underpinning billions of livelihoods. The world's network of protected areas includes many iconic mountain landscapes. However, only ca. 19% of mountain areas globally are protected (excluding Antarctica); many mountain areas are inadequately (<30% of their total terrestrial area) or completely unprotected. To support the UN Convention on Biological Diversity's Global Biodiversity Framework goal of protecting at least 30% of the world's lands by 2030, we have developed a strategic decision-support tool for identifying and prioritizing which candidate mountain areas most urgently require protection. To test its efficacy, we applied the tool to the Western Himalaya Case Study Area (WHCSA). The six-step algorithm harnesses multiple datasets including mountain Key Biodiversity Areas (KBAs), World Terrestrial Ecosystems, Biodiversity Hotspots, and Red List species and ecosystems. It also makes use of other key attributes including opportunities for disaster risk reduction, climate change adaptation, developing mountain tourism, maintaining elevational gradients and natural ecological corridors, and conserving flagship species. This method resulted in nine categories of potential action-four categories for follow-up action (ranked by order of importance and priority), and five categories requiring no further immediate action (either because countries are inadequately equipped to respond to protection deficits or because their KBAs are deemed adequately protected). An area-based analysis of the WHCSA identified 33 mountain KBAs regarded as inadequately protected, which included 29 inadequately protected World Mountain Ecosystems. All 33 inadequately protected KBAs in the WHCSA are Category A1: first-priority mountain KBAs (located in the Himalaya Biodiversity Hotspot in developing countries), requiring the most urgent attention for protection and conservation. Priorities for action can be fine-filtered by regional teams with sufficient local knowledge and country-specific values to finalize lists of priority mountain areas for protection. This rapid assessment tool ensures a repeatable, unbiased, and scientifically credible method for allocating resources and priorities to safeguard the world's most biodiverse mountain areas facing myriad threats in the Anthropocene.
C1 [Jacobs, Peter] IUCN WCPA Mt Specialist Grp, Bright, Vic 3741, Australia.
   [Carbutt, Clinton] Univ KwaZulu Natal, Sch Life Sci, ZA-3209 Scottsville, South Africa.
   [Carbutt, Clinton] Ezemvelo KZN Wildlife, Sci Serv, ZA-3202 Pietermaritzburg, South Africa.
   [Beever, Erik A. A.] Northern Rocky Mt Sci Ctr, US Geol Survey, Bozeman, MT 59715 USA.
   [Beever, Erik A. A.] Montana State Univ, Dept Ecol, Bozeman, MT 59715 USA.
   [Foggin, J. Marc] Univ Oxford, Sch Geog & Environm, Oxford OX1 3QY, England.
   [Foggin, J. Marc] Univ British Columbia, Inst Asian Res, Vancouver, BC V6T 1Z2, Canada.
   [Martin, Madeline] US Geol Survey, Climate Res & Dev Program, Reston, VA 20192 USA.
   [Orchard, Shane] Univ Canterbury, Sch Earth & Environm, Christchurch 8041, New Zealand.
   [Orchard, Shane] Univ Canterbury, Sch Biol Sci, Christchurch 8041, New Zealand.
   [Sayre, Roger] US Geol Survey, Land Change Sci Program, Reston, VA 20192 USA.
C3 University of Kwazulu Natal; United States Department of the Interior;
   United States Geological Survey; Montana State University System;
   Montana State University Bozeman; University of Oxford; University of
   British Columbia; United States Department of the Interior; United
   States Geological Survey; University of Canterbury; University of
   Canterbury; United States Department of the Interior; United States
   Geological Survey
RP Carbutt, C (corresponding author), Univ KwaZulu Natal, Sch Life Sci, ZA-3209 Scottsville, South Africa.; Carbutt, C (corresponding author), Ezemvelo KZN Wildlife, Sci Serv, ZA-3202 Pietermaritzburg, South Africa.
EM buffalo_springs@bigpond.com; carbuttc@ukzn.ac.za; ebeever@usgs.gov;
   marc.foggin@ouce.ox.ac.uk; mtmartin@usgs.gov; s.orchard@waterlink.nz;
   rsayre@usgs.gov
RI Foggin, Marc/W-3277-2019
OI Orchard, Shane/0000-0002-9040-6404; Sayre, Roger/0000-0001-6703-7105;
   Beever, Erik/0000-0002-9369-486X; Foggin, Marc/0000-0002-2663-6715;
   Carbutt, Clinton/0000-0002-1540-0029
CR ANDREN H, 1994, OIKOS, V71, P355, DOI 10.2307/3545823
   [Anonymous], 2016, PROTECTED PLANET REP, P1
   [Anonymous], 2006, PRINCIPLES CONSERVAT
   Beever EA, 2016, J MAMMAL, V97, P1495, DOI 10.1093/jmammal/gyw128
   Beever EA, 2014, CONSERV BIOL, V28, P302, DOI 10.1111/cobi.12233
   Beier P, 2010, CONSERV BIOL, V24, P701, DOI 10.1111/j.1523-1739.2009.01422.x
   Bellard C, 2012, ECOL LETT, V15, P365, DOI 10.1111/j.1461-0248.2011.01736.x
   Bentley LK, 2019, BIODIVERS CONSERV, V28, P131, DOI 10.1007/s10531-018-1643-6
   Bjornsen Gurung A., 2010, CHALLENGES MOUNTAIN, P197
   Borrini-Feyerabend G, 2015, PROTECTED AREA GOVERNANCE AND MANAGEMENT, P169
   Carbutt C., 2022, IMPERILED ENCY CONSE, VVolume 2, P243
   Carbutt C, 2021, LAND-BASEL, V10, DOI 10.3390/land10101024
   CBD, 2022, KUNM MONTR GLOB BIOD, P1
   CBD, 2004, EC APPR CONV BIOL DI, P1
   cepf, CRIT EC PARTN FUND P
   Chakraborty A, 2021, GEOJOURNAL, V86, P585, DOI 10.1007/s10708-019-10079-1
   Cohen-Shacham E., 2016, NATURE BASED SOLUTIO, P1
   Cohen-Shacham E, 2019, ENVIRON SCI POLICY, V98, P20, DOI 10.1016/j.envsci.2019.04.014
   conservation, BIODIVERSITY HOTSPOT
   conservationcorridor, CONS CORR CONN SCI C
   Critical Ecosystem Partnership Fund, US
   Dudley N., 2015, PROTECTED AREAS TOOL, P1
   Dudley N., 2008, Guidelines for Applying Protected Area Management Categories, P1
   Dudley N., 2013, ROLE ECOSYSTEMS DISA, P371
   Egan P.A., 2017, MOUNTAIN ECOSYSTEM S, P1
   Elsen PR, 2018, P NATL ACAD SCI USA, V115, P6004, DOI 10.1073/pnas.1720141115
   Flint CG, 2016, MT RES DEV, V36, P528, DOI 10.1659/MRD-JOURNAL-D-15-00110.1
   Foggin JM, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132212884
   Freeman BG, 2018, GLOBAL ECOL BIOGEOGR, V27, P1268, DOI 10.1111/geb.12774
   globalsnowleopard, GLOB SNOW LEOP EC PR
   Hilty J., 2020, BEST PRACT PROTECT A, P1
   HOCKINGS M., 2006, Evaluating Effectiveness: A framework for assessing management effectiveness of protected areas, V2nd, P1, DOI 10.2305/IUCN.CH.2005.PAG.14.en
   ibat-alliance, ABOUT US
   ICCA, REG AN ONL INF PLATF
   ICCA Consortium, 2021, TERR LIF 2021 REP, P1
   International Monetary Fund, World Economic Outlook Database
   IUCN, 2016, GLOB STAND ID KEY BI, P1
   iucn, IUCN COMM EC MAN
   IUCN, 2020, GLOB STAND NAT BAS S, V1st, P1
   IUCN-International union for conservation of nature, 2019, Takin, Budorcas taxicolor
   IUCN-WCPA Task Force on OECMs, 2019, REC REP OTH EFF AR B, P1
   Joppa LN, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0008273
   keybiodiversityareas, WORLD DAT KEY BIOD A
   Korner C., 2005, ECOSYSTEMS HUMAN WEL, P681
   Leung Y.-F., 2018, BEST PRACT PROTECT A
   Makino Y, 2019, SCIENCE, V365, P1084, DOI 10.1126/science.aay8855
   Martín-López B, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0217847
   Michalak JL, 2018, CONSERV BIOL, V32, P1414, DOI 10.1111/cobi.13130
   Mittermeier R.A., 2011, Biodiversity hotspots: Distribution and protection of conservation priority areas, P3, DOI DOI 10.1007/978-3-642-20992-5_1
   Monty F., 2016, HELPING NATURE HELP, P1
   Murti R., 2014, SAFE HAVENS PROTECTE, P1
   natureserve, PROT AR COV KEY BIOD
   Neugarten R.A., 2018, TOOLS MEASURING MODE, P1
   Nogués-Bravo D, 2007, GLOBAL ENVIRON CHANG, V17, P420, DOI 10.1016/j.gloenvcha.2006.11.007
   Payne D, 2017, CURR OPIN ENV SUST, V29, P40, DOI 10.1016/j.cosust.2017.11.001
   Pepin NC, 2022, REV GEOPHYS, V60, DOI 10.1029/2020RG000730
   Perrigo A, 2020, J BIOGEOGR, V47, P315, DOI 10.1111/jbi.13731
   protectedplanet, PROT PLAN WORLD DAT
   Rahbek C, 2019, SCIENCE, V365, P1108, DOI 10.1126/science.aax0149
   Rapacciuolo G, 2014, GLOBAL CHANGE BIOL, V20, P2841, DOI 10.1111/gcb.12638
   Rodríguez-Rodríguez D, 2011, BIOL CONSERV, V144, P2978, DOI 10.1016/j.biocon.2011.08.023
   Rumpf SB, 2019, GLOBAL ECOL BIOGEOGR, V28, P533, DOI 10.1111/geb.12865
   Sajeva G., 2019, MEANINGS MORE POLICY, P1
   Sanderson EW, 2015, CONSERV BIOL, V29, P649, DOI 10.1111/cobi.12502
   Sayre R, 2020, GLOB ECOL CONSERV, V21, DOI 10.1016/j.gecco.2019.e00860
   Schirpke U, 2021, ECOSYST SERV, V49, DOI 10.1016/j.ecoser.2021.101302
   Shepherd G., 2004, ECOSYSTEM APPROACH, P1
   tbpa, IUCN WCPA GLOB TRANS
   The, IUCN RED LIST THREAT
   The United Nations Development Programme's Human Development Reports, 2018, HUM DEV IND IND STAT
   UN, 2011, MILL DEV GOALS REP, P1
   UNEP-WCMC IUCN, 2018, PROTECTED PLANET REP, P1
   unesco, UNESCO WORLD HER CON
   United States Geological Survey, MAPS KEY BIOD AR WOR
   Wehrli A, 2014, MT RES DEV, V34, P405, DOI 10.1659/MRD-JOURNAL-D-14-00096.1
   Wirzba N, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15021388
   Zanjani LV, 2023, CURR OPIN ENV SUST, V63, DOI 10.1016/j.cosust.2023.101298
NR 77
TC 1
Z9 1
U1 2
U2 7
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD JUL
PY 2023
VL 12
IS 7
AR 1323
DI 10.3390/land12071323
PG 21
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA N3DV1
UT WOS:001035868900001
OA gold
DA 2025-01-10
ER

PT J
AU Yang, XY
   Tan, L
   He, RM
   Fu, GT
   Ye, JY
   Liu, Q
   Wang, GQ
AF Yang, Xiaoying
   Tan, Lit
   He, Ruimin
   Fu, Guangtao
   Ye, Jinyin
   Liu, Qun
   Wang, Guoqing
TI Stochastic sensitivity analysis of nitrogen pollution to climate change
   in a river basin with complex pollution sources
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE Climate change; Complex pollution sources; Nitrogen; Sensitivity
   analysis; SWAT; Upper Huai River basin
ID LAND-USE CHANGES; WATER-QUALITY; CHANGE IMPACTS; WEATHER GENERATORS;
   FUTURE CLIMATE; STREAMFLOW; HYDROLOGY; PHOSPHORUS; SIMULATION;
   MANAGEMENT
AB It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by -10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 degrees C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the subdaily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.
C1 [Yang, Xiaoying; Tan, Lit] Fudan Univ, Dept Environm Engn Sci, Shanghai 200433, Peoples R China.
   [He, Ruimin; Wang, Guoqing] Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Jiangsu, Peoples R China.
   [Fu, Guangtao] Univ Exeter, Coll Engn Math & Phys Sci, Ctr Water Syst, Exeter EX4 4QF, Devon, England.
   [Ye, Jinyin] Anhui Prov Meteorol Observ, Hefei 230001, Anhui, Peoples R China.
   [Liu, Qun] Zhumadian City Bur Environm Protect, Zhumadian 463000, Peoples R China.
C3 Fudan University; Nanjing Hydraulic Research Institute; University of
   Exeter
RP Yang, XY (corresponding author), Fudan Univ, Dept Environm Engn Sci, Shanghai 200433, Peoples R China.; Wang, GQ (corresponding author), Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Jiangsu, Peoples R China.
EM xiaoying@fudan.edu.cn; gqwang@nhri.cn
RI WANG, GUOQING/AAP-8796-2020; Fu, Guangtao/ABE-3874-2021
FU Open Foundation of State Key Laboratory of Hydrology-Water Resources and
   Hydraulic Engineering [2016490411]; National Key Research and
   Development Program of China [2016YFA0601501]; Chinese Natural Science
   Foundation [41201191]; Chinese National Engineering Laboratory for
   Circular Economy
FX This work was supported by the Open Foundation of State Key Laboratory
   of Hydrology-Water Resources and Hydraulic Engineering (2016490411),
   National Key Research and Development Program of China (2016YFA0601501),
   Chinese Natural Science Foundation (41201191), and Chinese National
   Engineering Laboratory for Circular Economy.
CR [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Chattaraj S, 2014, AGR ECOSYST ENVIRON, V197, P174, DOI 10.1016/j.agee.2014.07.023
   Chen J, 2014, INT J CLIMATOL, V34, P3089, DOI 10.1002/joc.3896
   Dessu SB, 2013, HYDROL PROCESS, V27, P2973, DOI 10.1002/hyp.9434
   Detrembleur S, 2015, NAT HAZARDS, V77, P1533, DOI 10.1007/s11069-015-1661-6
   Dunn SM, 2012, J HYDROL, V434, P19, DOI 10.1016/j.jhydrol.2012.02.039
   El-Khoury A, 2015, J ENVIRON MANAGE, V151, P76, DOI 10.1016/j.jenvman.2014.12.012
   Fatichi S, 2011, ADV WATER RESOUR, V34, P448, DOI 10.1016/j.advwatres.2010.12.013
   Gassman PW, 2007, T ASABE, V50, P1211, DOI 10.13031/2013.23637
   Gassman PW, 2014, J ENVIRON QUAL, V43, P1, DOI 10.2134/jeq2013.11.0466
   Geng RunZhe Geng RunZhe, 2015, Transactions of the Chinese Society of Agricultural Engineering, V31, P240
   Glavan M, 2015, HYDROL PROCESS, V29, P3124, DOI 10.1002/hyp.10429
   Gupta SC, 2015, WATER RESOUR RES, V51, P5301, DOI 10.1002/2015WR017323
   Hay LE, 2000, J AM WATER RESOUR AS, V36, P387, DOI 10.1111/j.1752-1688.2000.tb04276.x
   Hrdinka T, 2012, J HYDRO-ENVIRON RES, V6, P145, DOI 10.1016/j.jher.2012.01.008
   Huttunen I, 2015, SCI TOTAL ENVIRON, V529, P168, DOI 10.1016/j.scitotenv.2015.05.055
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jha MK, 2014, HYDROL PROCESS, V28, P2772, DOI 10.1002/hyp.9836
   Jisun C, 2013, DISASTER ADV, V6, P134
   Johnson T, 2015, J AM WATER RESOUR AS, V51, P1321, DOI 10.1111/1752-1688.12308
   Kharel G, 2015, J AM WATER RESOUR AS, V51, P1221, DOI 10.1111/1752-1688.12300
   Lu GH, 2013, J HYDROL ENG, V18, P1077, DOI 10.1061/(ASCE)HE.1943-5584.0000632
   Ma C, 2016, THEOR APPL CLIMATOL, V123, P859, DOI 10.1007/s00704-015-1386-1
   Mendoza-Resendiz A, 2013, ATMOS RES, V132, P411, DOI 10.1016/j.atmosres.2013.07.001
   Molina-Navarro E, 2014, J HYDROL, V509, P354, DOI 10.1016/j.jhydrol.2013.11.053
   Nepal S, 2016, J HYDRO-ENVIRON RES, V10, P76, DOI 10.1016/j.jher.2015.12.001
   Trang NTT, 2017, SCI TOTAL ENVIRON, V576, P586, DOI 10.1016/j.scitotenv.2016.10.138
   Nkomozepi T, 2014, J HYDRO-ENVIRON RES, V8, P358, DOI 10.1016/j.jher.2013.08.006
   Peterson TC, 2014, J AIR WASTE MANAGE, V64, P184, DOI 10.1080/10962247.2013.851044
   Prudhomme C, 2010, J HYDROL, V390, P198, DOI 10.1016/j.jhydrol.2010.06.043
   Prudhomme C, 2013, CLIMATIC CHANGE, V119, P933, DOI 10.1007/s10584-013-0748-x
   Puig A, 2016, ENVIRON SCI POLLUT R, V23, P11430, DOI 10.1007/s11356-015-5744-4
   Ravazzani G, 2015, WATER RESOUR MANAG, V29, P1193, DOI 10.1007/s11269-014-0868-8
   Semenov MA, 1997, CLIMATIC CHANGE, V35, P397, DOI 10.1023/A:1005342632279
   Semenov MA, 1998, CLIMATE RES, V10, P95, DOI 10.3354/cr010095
   Semenov MA, 2008, CLIM RES, V35, P203, DOI 10.3354/cr00731
   Thomas D, 2016, J ENVIRON MANAGE, V165, P243, DOI 10.1016/j.jenvman.2015.09.039
   Vanuytrecht E, 2014, AGR FOREST METEOROL, V195, P12, DOI 10.1016/j.agrformet.2014.04.017
   Verma S, 2015, CLEAN-SOIL AIR WATER, V43, P1464, DOI 10.1002/clen.201400724
   Viola MR, 2015, INT J CLIMATOL, V35, P1054, DOI 10.1002/joc.4038
   Wang GQ, 2015, QUATERN INT, V380, P180, DOI 10.1016/j.quaint.2015.02.005
   [王国庆 WANG Guoqing], 2011, [水科学进展, Advances in Water Science], V22, P307
   Wu L, 2012, J HYDROL, V475, P26, DOI 10.1016/j.jhydrol.2012.08.022
   Xia XH, 2015, J ENVIRON INFORM, V25, P85, DOI 10.3808/jei.201400263
   Xu H, 2016, PEARL RIVER, V37, P43
   Yang XY, 2016, WATER RES, V94, P187, DOI 10.1016/j.watres.2016.02.040
   Yang XY, 2016, STOCH ENV RES RISK A, V30, P959, DOI 10.1007/s00477-015-1099-0
   [姚允龙 Yao Yunlong], 2012, [地理研究, Geographical Research], V31, P409
   Zhang C, 2015, ENVIRON SCI POLLUT R, V22, P18372
   Zhang YY, 2013, STOCH ENV RES RISK A, V27, P11, DOI 10.1007/s00477-011-0546-9
   Zhao FZ, 2008, J YUNNAN U NAT SCI E, V30, P329
NR 51
TC 14
Z9 16
U1 4
U2 90
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0944-1344
EI 1614-7499
J9 ENVIRON SCI POLLUT R
JI Environ. Sci. Pollut. Res.
PD DEC
PY 2017
VL 24
IS 34
BP 26545
EP 26561
DI 10.1007/s11356-017-0257-y
PG 17
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA FP1KW
UT WOS:000417372600033
PM 28952024
DA 2025-01-10
ER

PT J
AU Lin, TP
   Lin, FY
   Wu, PR
   Hämmerle, M
   Höfle, B
   Bechtold, S
   Hwang, RL
   Chen, YC
AF Lin, Tzu-Ping
   Lin, Feng-Yi
   Wu, Pei-Ru
   Haemmerle, Martin
   Hoefle, Bernhard
   Bechtold, Sebastian
   Hwang, Ruey-Lung
   Chen, Yu-Cheng
TI Multiscale analysis and reduction measures of urban carbon dioxide
   budget based on building energy consumption
SO ENERGY AND BUILDINGS
LA English
DT Article
DE CO2 emissions; CO2 absorption; Urban CO2 system; Geographic information
   system; Solar potential; Photovoltaics
ID NEIGHBORHOOD; ENVIRONMENT; EMISSIONS; FOOTPRINT; HEAT; FLUX; CO2
AB As urban areas continue to develop and expand, carbon dioxide (CO2) emissions from their energy use are growing exponentially. This has made carbon reduction a global concern. Previous studies have provided a limited understanding of carbon budgets because they have used top-down data on a single spatial or temporal scale. In this study, urban spatial and statistical data for metropolitan Tainan in southwestern Taiwan are used to explore inside and outside of the CO2 system of the city and estimate the amount of CO2 emissions from road traffic, the use of electricity and gas in buildings, and the amount of CO2 absorbed by green spaces and water bodies within the system. Innovative annual and monthly carbon budget maps composed of 200 x 200-m grids are developed for the city through a geographic information system (GIS). An analysis of the highly detailed maps yields the following findings: First, CO2 emissions are concentrated in over-urbanized areas, where the population density is higher than 5000 people/km(2). Buildings account for the majority of carbon dioxide emissions (54%) and produced 11% more carbon dioxide in summer than in winter (owing to air-conditioning usage). Second, road traffic is the main source of CO2 emissions for under-urbanized areas (87%), and emissions from this source exhibit insignificant seasonal variation. On the basis of these findings, the carbon budgets of four different over-urbanized areas are formulated and presented on 50 x 50-m grids. The results suggest that green spaces in these areas absorb limited amounts of carbon dioxide. Therefore, this study assesses the annual and monthly carbon-reduction potential of rooftops equipped with solar panels occupying 30% of their area. The annual carbon-reduction potential for the four areas was 4.5-31.1 kg CO2 m(-2) yr(-1), and the solar energy replacement rate is higher in winter than in summer. In summary, this study presents carbonbudgets in high-resolution grids, quantifies the carbon-reduction potential of rooftops with solar panels, and proposes a reduction strategy for reducing CO2 emissions from urban activities to improve the sustainability of urban areas and their environs and inform urban planning and climate change adaptation. (C) 2017 Elsevier B.V. All rights reserved.
C1 [Lin, Tzu-Ping; Lin, Feng-Yi; Wu, Pei-Ru; Chen, Yu-Cheng] Natl Cheng Kung Univ, Dept Architecture, Tainan, Taiwan.
   [Haemmerle, Martin; Hoefle, Bernhard; Bechtold, Sebastian] Heidelberg Univ, Inst Geog, GISci & Spatial Data Proc Grp 3D, Heidelberg, Germany.
   [Hoefle, Bernhard] Heidelberg Univ, HCE, Heidelberg, Germany.
   [Hwang, Ruey-Lung] Natl Kaohsiung Normal Univ, Dept Ind Technol Educ, Kaohsiung, Taiwan.
C3 National Cheng Kung University; Ruprecht Karls University Heidelberg;
   Ruprecht Karls University Heidelberg; National Kaohsiung Normal
   University
RP Lin, TP (corresponding author), Natl Cheng Kung Univ, Dept Architecture, Tainan, Taiwan.
EM lin678@gmail.com
RI Hwang, Ruey-Lung/JXN-2420-2024; chen, yu-cheng/IQT-1648-2023; Lin,
   Tzu-Ping/D-2719-2014; Hofle, Bernhard/A-4702-2010
OI CHEN, YU CHENG/0000-0002-4315-2608; Lin, Feng-Yi/0000-0002-4008-8823;
   Hofle, Bernhard/0000-0001-5849-1461; Chen, Yu-Cheng/0000-0003-1696-4667;
   Hammerle, Martin/0000-0001-7527-8515
FU Ministry of Science and Technology of Taiwan [105-2633-E-006-002,
   106-2633-E-006-001]
FX The authors would like to thank the Ministry of Science and Technology
   of Taiwan, for financially supporting this research under Contract No
   105-2633-E-006-002 and 106-2633-E-006-001.
CR [Anonymous], 2015, STAT CARBON DIOXIDE
   Bureau of Transportation Tainan City Government, 2015, INV AN TRAFF VOL TAI
   Chang C. T., 2015, INT C ENG INF KYOT J
   Chang H. W., LIBERTY TIMES NET
   Chang Y.-S., 2002, Life cycle assessment on the reduction of carbon dioxide emission of buildings
   Chen J. H., 2009, CLASSIFICATION MODEL
   Chiang L. Y., 2010, FORUM URBAN PLANN, V14
   Christen A, 2011, ATMOS ENVIRON, V45, P6057, DOI 10.1016/j.atmosenv.2011.07.040
   Dong YJ, 2014, ENVIRON SCI POLICY, V44, P181, DOI 10.1016/j.envsci.2014.07.013
   Huang P. H., 2014, METABOLISM APPROACH
   Jochem A, 2011, REMOTE SENS-BASEL, V3, P650, DOI 10.3390/rs3030650
   Kotthaus S, 2014, URBAN CLIM, V10, P281, DOI 10.1016/j.uclim.2013.10.001
   Kotthaus S, 2012, ATMOS ENVIRON, V57, P301, DOI 10.1016/j.atmosenv.2012.04.024
   Lietzke B, 2015, INT J CLIMATOL, V35, P3921, DOI 10.1002/joc.4255
   Lin F. Y., 2017, ENERGY BUILD
   Lin H. T., 2015, BUILDING CARBON FOOT
   Lin TP, 2010, TOURISM MANAGE, V31, P285, DOI 10.1016/j.tourman.2009.03.009
   Liu B. H., 2014, QUANTIFYING CARBON S
   Mohajeri N, 2016, RENEW ENERG, V93, P469, DOI 10.1016/j.renene.2016.02.053
   Santos T, 2014, APPL GEOGR, V51, P48, DOI 10.1016/j.apgeog.2014.03.008
   Stewart ID, 2017, INT J BIOMETEOROL, V61, P1159, DOI 10.1007/s00484-016-1296-7
   Takebayashi H, 2015, SOL ENERGY, V119, P362, DOI 10.1016/j.solener.2015.05.039
   Tsay Y.-S., 2015, GREEN BUILDING EVALU
   Ueyama M, 2016, ATMOS CHEM PHYS, V16, P14727, DOI 10.5194/acp-16-14727-2016
   Velasco E, 2014, ATMOS ENVIRON, V97, P226, DOI 10.1016/j.atmosenv.2014.08.018
   Velasco E, 2013, ATMOS CHEM PHYS, V13, P10185, DOI 10.5194/acp-13-10185-2013
   Wang BC, 2012, COMPUT ENVIRON URBAN, V36, P342, DOI 10.1016/j.compenvurbsys.2011.12.004
   Wang SJ, 2015, ECOL INDIC, V49, P121, DOI 10.1016/j.ecolind.2014.10.004
NR 28
TC 19
Z9 20
U1 4
U2 54
PU ELSEVIER SCIENCE SA
PI LAUSANNE
PA PO BOX 564, 1001 LAUSANNE, SWITZERLAND
SN 0378-7788
EI 1872-6178
J9 ENERG BUILDINGS
JI Energy Build.
PD OCT 15
PY 2017
VL 153
BP 356
EP 367
DI 10.1016/j.enbuild.2017.07.084
PG 12
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA FJ7SQ
UT WOS:000412959600029
DA 2025-01-10
ER

PT J
AU Bobrowski, M
   Gerlitz, L
   Schickhoff, U
AF Bobrowski, Maria
   Gerlitz, Lars
   Schickhoff, Udo
TI Modelling the potential distribution of Betula utilis in the Himalaya
SO GLOBAL ECOLOGY AND CONSERVATION
LA English
DT Article
DE Climatic space; Ecological niche modeling; Habitat; Range shift;
   Treeline dynamics; Treeline ecotone
ID PLANT-SPECIES DISTRIBUTIONS; CLIMATE-CHANGE; THRESHOLD CRITERIA;
   TREELINE; LIMITS; NICHE; TEMPERATURE; PERFORMANCE; VEGETATION; PATTERNS
AB Developing sustainable adaptation pathways under climate change conditions in mountain regions requires accurate predictions of treeline shifts and future distribution ranges of treeline species. Here, we model for the first time the potential distribution of Betula utilis, a principal Himalayan treeline species, to provide a basis for the analysis of future range shifts. Our target species Betula utilis is widespread at alpine treelines in the Himalayan mountains, the distribution range extends across the Himalayan mountain range. Our objective is to model the potential distribution of B. utilis in relation to current climate conditions. We generated a dataset of 590 occurrence records and used 24 variables for ecological niche modelling. We calibrated Generalized Linear Models using the Akaike Information Criterion (AIC) and evaluated model performance using threshold-independent (AUC, Area Under the Curve) and threshold-dependent (TSS, True Skill Statistics) characteristics as well as visual assessments of projected distribution maps. We found two temperature-related (Mean Temperature of the Wettest Quarter, Temperature Annual Range) and three precipitation-related variables (Precipitation of the Coldest Quarter, Average Precipitation of March, April and May and Precipitation Seasonality) to be useful for predicting the potential distribution of B. utilis. All models had high predictive power (AUC >= 0.98 and TSS >= 0.89). The projected suitable area in the Himalayan mountains varies considerably, with most extensive distribution in the western and central Himalayan region. A substantial difference between potential and real distribution in the eastern Himalaya points to decreasing competitiveness of B. utilis under more oceanic conditions in the eastern part of the mountain system. A comparison between the vegetation map of Schweinfurth (1957) and our current predictions suggests that B. utilis does not reach the upper elevational limit in vast areas of its potential distribution range due to anthropogenically caused treeline depressions. This study underlines the significance of accuracies of current environmental niche models for species distribution modelling under climate change scenarios. Analysing and understanding the environmental factors driving the current distribution of B. utilis is crucial for the prediction of future range shifts of B. utilis and other treeline species, and for deriving appropriate climate change adaptation strategies. (C) 2017 The Authors. Published by Elsevier B.V.
C1 [Bobrowski, Maria; Gerlitz, Lars; Schickhoff, Udo] Univ Hamburg, Ctr Earth Syst Res & Sustainabil, Inst Geog, Bundesstr 55, D-20146 Hamburg, Germany.
   [Gerlitz, Lars] GFZ German Res Ctr Geosci, Helmholtz Ctr Potsdam, D-14473 Potsdam, Germany.
C3 University of Hamburg; Helmholtz Association; Helmholtz-Center Potsdam
   GFZ German Research Center for Geosciences
RP Bobrowski, M (corresponding author), Univ Hamburg, Ctr Earth Syst Res & Sustainabil, Inst Geog, Bundesstr 55, D-20146 Hamburg, Germany.
EM maria.bobrowski@uni-hamburg.de
FU German Research Foundation [SCHI 436/14-1]
FX We would like to thank Kim Stolle (University of Hamburg) for
   georeferencing and digitalizing the Schweinfurth vegetation map. We also
   express our gratitude to Himalayan colleagues, guides and local people
   who accompanied us on numerous field trips to Betula treelines.
   Additionally we would like to thank two anonymous reviewers for their
   comments and suggestions. The study was conducted under the framework
   TREELINE project and partially supported by a specific grant from the
   German Research Foundation (SCHI 436/14-1).
CR AKAIKE H, 1974, IEEE T AUTOMAT CONTR, VAC19, P716, DOI 10.1109/TAC.1974.1100705
   Allouche O, 2006, J APPL ECOL, V43, P1223, DOI 10.1111/j.1365-2664.2006.01214.x
   Anderson RP, 2012, ANN NY ACAD SCI, V1260, P66, DOI 10.1111/j.1749-6632.2011.06440.x
   Anderson RP, 2011, ECOL MODEL, V222, P2796, DOI 10.1016/j.ecolmodel.2011.04.011
   [Anonymous], 2010, Tree Rings Archaeol Climatol Ecol
   [Anonymous], 2002, Information and Likelihood Theory: A Basis for Model Selection and Inference
   [Anonymous], THESIS
   [Anonymous], BOT MAGAZINE MONOGRA
   [Anonymous], BONNER GEOGRAPHISCHE
   [Anonymous], MITTL DTSCH DENDROL
   [Anonymous], CLIM PAST
   [Anonymous], ERDWISSENSCHAFTLICHE
   [Anonymous], 2016, Climate Change, Glacier Response, and Vegetation Dynamics in the Himalaya, DOI DOI 10.1007/978-3-319-28977-9_15
   [Anonymous], 2013, hier.part: Hierarchical partitioning
   [Anonymous], 2015, raster: Geographic Data Analysis and Modeling
   [Anonymous], ENV RES LETT
   [Anonymous], ENGLERA 19
   [Anonymous], 1993, Bonner Geographische Abhandlungen
   [Anonymous], 2014, ECOLOGY, DOI DOI 10.1890/13-1904.1
   [Anonymous], 2021, RTS RATER TIME SERIE
   [Anonymous], BONNER GEOGRAPHISCHE
   [Anonymous], ERDKUNDE
   [Anonymous], CULTURE AREA KARAKOR
   [Anonymous], ERDKUNDE
   [Anonymous], NEPAL PROG PHYS GEOG
   [Anonymous], 1968, A revised survey of forest types of India
   [Anonymous], INDIAN FOR
   [Anonymous], PLANT FORM DIVERSITY
   [Anonymous], THESIS
   [Anonymous], ARXIV160700217
   Araújo MB, 2005, GLOBAL CHANGE BIOL, V11, P1504, DOI 10.1111/j.1365-2486.2005.01000.x
   Araújo MB, 2006, J BIOGEOGR, V33, P1677, DOI 10.1111/j.1365-2699.2006.01584.x
   Austin MP, 2006, ECOL MODEL, V199, P197, DOI 10.1016/j.ecolmodel.2006.05.023
   Austin MP, 1999, OIKOS, V86, P170, DOI 10.2307/3546582
   Austin MP, 2002, ECOL MODEL, V157, P101, DOI 10.1016/S0304-3800(02)00205-3
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Barry S, 2006, J APPL ECOL, V43, P413, DOI 10.1111/j.1365-2664.2006.01136.x
   Bhattacharyya A, 2006, CURR SCI INDIA, V91, P754
   Bohner J., 2015, NEPAL INTRO NATURAL, P385
   BONAN GB, 1992, J VEG SCI, V3, P495, DOI 10.2307/3235806
   Broennimann O., 2015, ecospat: Spatial ecology miscellaneous methods
   Dawadi B, 2013, QUATERN INT, V283, P72, DOI 10.1016/j.quaint.2012.05.039
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Dufour-Tremblay G, 2012, AM J BOT, V99, P1638, DOI 10.3732/ajb.1200279
   Dullinger S, 2004, J ECOL, V92, P241, DOI 10.1111/j.0022-0477.2004.00872.x
   Eberhardt E, 2007, ERDKUNDE, V61, P93, DOI 10.3112/erdkunde.2007.01.06
   Elith J, 2002, PREDICTING SPECIES OCCURRENCES: ISSUES OF ACCURACY AND SCALE, P303
   Fang JY, 2006, J BIOGEOGR, V33, P1804, DOI 10.1111/j.1365-2699.2006.01533.x
   Fielding AH, 1997, ENVIRON CONSERV, V24, P38, DOI 10.1017/S0376892997000088
   Flueck J.A., 1987, 10 C PROBABILITY STA, P69
   Franklin J, 1995, PROG PHYS GEOG, V19, P474, DOI 10.1177/030913339501900403
   Freeman EA, 2008, ECOL MODEL, V217, P48, DOI 10.1016/j.ecolmodel.2008.05.015
   Freeman EA, 2008, J STAT SOFTW, V23, P1
   Gaire NP., 2013, Fuuast Journal of Biology, V3, P1
   Gerlitz L, 2014, CLIM RES, V58, P235, DOI 10.3354/cr01193
   Gottfried M, 2012, NAT CLIM CHANGE, V2, P111, DOI [10.1038/nclimate1329, 10.1038/NCLIMATE1329]
   Grosjean P.Ibanez., 2014, pastecs: Package for Analysis of Space-Time Ecological Series
   Guisan A, 2002, ECOL MODEL, V157, P89, DOI 10.1016/S0304-3800(02)00204-1
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Harsch MA, 2009, ECOL LETT, V12, P1040, DOI 10.1111/j.1461-0248.2009.01355.x
   Heikkinen RK, 2006, PROG PHYS GEOG, V30, P751, DOI 10.1177/0309133306071957
   Hijmans R.J., 2011, dismo: Species distribution modeling. R package version 1
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Holtmeier F.K., 2009, ADV GLOB CHANGE RES, V36
   Holtmeier F.K., 2010, Polarforschung, V79, P139, DOI [10.2312/polarforschung.79.3.139, DOI 10.2312/POLARFORSCHUNG.79.3.139]
   Huo CF, 2010, J FOREST RES-JPN, V15, P176, DOI 10.1007/s10310-009-0173-1
   Institute of HeartMath, 2012, ARCGIS 10 2 DESKT
   Irl SDH, 2016, ECOGRAPHY, V39, P427, DOI 10.1111/ecog.01266
   Jiménez-Valverde A, 2007, ACTA OECOL, V31, P361, DOI 10.1016/j.actao.2007.02.001
   Korner C., 2012, ALPINE TREELINES FUN
   Kuhn M., 2020, CARET CLASSIFICATION
   Kullman L, 1998, AMBIO, V27, P312
   Kumar P, 2012, BIODIVERS CONSERV, V21, P1251, DOI 10.1007/s10531-012-0279-1
   Kunreuther H, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P151
   Lobo JM, 2008, GLOBAL ECOL BIOGEOGR, V17, P145, DOI 10.1111/j.1466-8238.2007.00358.x
   McCullagh P., 1989, Generalized Linear Models, VSecond
   Miehe G., 2015, Nepal: An introduction to the natural history, ecology and human environment of the Himalayas, P385
   Miehe G., 2015, NEPAL INTRO NATURAL
   Müller M, 2016, ARCT ANTARCT ALP RES, V48, P501, DOI 10.1657/AAAR0016-004
   NELDER JA, 1972, J R STAT SOC SER A-G, V135, P370, DOI 10.2307/2344614
   Nix HA., 1986, ATLAS ELAPID SNAKES, P415
   Nusser M., 2002, Erdkunde, P37, DOI DOI 10.3112/ERDKUNDE.2002.01.03
   Parolo G, 2008, J APPL ECOL, V45, P1410, DOI 10.1111/j.1365-2664.2008.01516.x
   Pauli H, 2012, SCIENCE, V336, P353, DOI 10.1126/science.1219033
   Paulsen J, 2014, ALPINE BOT, V124, P1, DOI 10.1007/s00035-014-0124-0
   Pearce J, 2000, ECOL MODEL, V133, P225, DOI 10.1016/S0304-3800(00)00322-7
   Peterson A.T., 2011, Ecological Niches and Geographic Distributions (MPB- 49), V56
   Peterson AT, 2012, NAT CONSERVACAO, V10, P102, DOI 10.4322/natcon.2012.019
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Polunin O., 1987, Concise Flowers of the Himalaya
   R Core Team, 2015, VERSION 3 1 3 R CORE
   Rai ID., 2013, high altitude rangelands and their interfaces in the Hindu Kush Himalayas, P91
   Randin CF, 2009, GLOBAL CHANGE BIOL, V15, P1557, DOI 10.1111/j.1365-2486.2008.01766.x
   Ranjitkar S, 2014, GLOB ECOL CONSERV, V1, P2, DOI 10.1016/j.gecco.2014.07.001
   Reineking B, 2006, ECOL MODEL, V193, P675, DOI 10.1016/j.ecolmodel.2005.10.003
   Schibalski A, 2014, ECOGRAPHY, V37, P321, DOI 10.1111/j.1600-0587.2013.00368.x
   Schickhoff U, 2005, MOUNTAIN ECOSYSTEMS: STUDIES IN TREELINE ECOLOGY, P275
   Schickhoff U, 2015, EARTH SYST DYNAM, V6, P245, DOI 10.5194/esd-6-245-2015
   SCHICKHOFF U, 1995, MT RES DEV, V15, P3, DOI 10.2307/3673697
   Schickhoff U., 2011, Handbook of biogeography, P313
   Schwab N., 2016, CLIMATE CHANGE GLACI, P307, DOI [10.1007/978-3-319-28977-916, DOI 10.1007/978-3-319-28977-916]
   Shi P, 2008, FUNCT ECOL, V22, P213, DOI 10.1111/j.1365-2435.2007.01370.x
   Shrestha BB, 2007, MT RES DEV, V27, P259, DOI 10.1659/mrdd.0784
   Shrestha KB, 2015, J PLANT ECOL, V8, P347, DOI 10.1093/jpe/rtu035
   Simko V., 2017, GitHub Repositories
   Singh CP, 2012, CURR SCI INDIA, V102, P559
   Singh CP, 2013, TROP ECOL, V54, P321
   Soberón J, 2004, PHILOS T R SOC B, V359, P689, DOI 10.1098/rstb.2003.1439
   Soria-Auza RW, 2010, ECOL MODEL, V221, P1221, DOI 10.1016/j.ecolmodel.2010.01.004
   Speed JDM, 2011, FOREST ECOL MANAG, V261, P1344, DOI 10.1016/j.foreco.2011.01.017
   Stainton J.D.A., 1972, Forests of Nepal
   STONE M, 1974, J R STAT SOC B, V36, P111, DOI 10.1111/j.2517-6161.1974.tb00994.x
   Svenning JC, 2008, J ECOL, V96, P1117, DOI 10.1111/j.1365-2745.2008.01422.x
   Telwala Y, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0057103
   Thuiller W, 2003, GLOBAL CHANGE BIOL, V9, P1353, DOI 10.1046/j.1365-2486.2003.00666.x
   Thuiller W, 2005, GLOBAL ECOL BIOGEOGR, V14, P347, DOI 10.1111/j.1466-822x.2005.00162.x
   Thuiller W, 2008, PERSPECT PLANT ECOL, V9, P137, DOI 10.1016/j.ppees.2007.09.004
   Troll C., 1967, Khumbu Himal, V1, P353
   Troll C., 1972, GEOECOLOGY HIGH MOUN, P264
   Truong C, 2007, J EVOLUTION BIOL, V20, P369, DOI 10.1111/j.1420-9101.2006.01190.x
   Tsoar A, 2007, DIVERS DISTRIB, V13, P397, DOI 10.1111/j.1472-4642.2007.00346.x
   VanDerWal J, 2009, ECOL MODEL, V220, P589, DOI 10.1016/j.ecolmodel.2008.11.010
   Veloz SD, 2009, J BIOGEOGR, V36, P2290, DOI 10.1111/j.1365-2699.2009.02174.x
   Warren DL, 2011, ECOL APPL, V21, P335, DOI 10.1890/10-1171.1
   Wieser G, 2014, PLANT ECOPHYSIOL, V9, P221, DOI 10.1007/978-94-017-9100-7_10
   Wiley E.O., 2003, OCEANOGRAPHY, V15, P120
   Zurick D., 2006, ILLUSTRATED ATLAS HI
NR 128
TC 62
Z9 66
U1 4
U2 22
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
EI 2351-9894
J9 GLOB ECOL CONSERV
JI Glob. Ecol. Conserv.
PD JUL
PY 2017
VL 11
BP 69
EP 83
DI 10.1016/j.gecco.2017.04.003
PG 15
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA FK1YG
UT WOS:000413278900006
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Jiricka, A
   Formayer, H
   Schmidt, A
   Völler, S
   Leitner, M
   Fischer, TB
   Wachter, TF
AF Jiricka, Alexandra
   Formayer, Herbert
   Schmidt, Anna
   Voeller, Sonja
   Leitner, Markus
   Fischer, Thomas B.
   Wachter, Thomas F.
TI Consideration of climate change impacts and adaptation in EIA practice -
   Perspectives of actors in Austria and Germany
SO ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
LA English
DT Article
DE Environmental Impact Assessment; Climate change adaptation; Actors
ID MASS MOVEMENTS; STRATEGIES; TEMPERATURES
AB Current political discussions and developments indicate the importance and urgency of incorporating climate change considerations into EIA processes. The recent revision of the EU Directive 2014/52/EU on Environmental Impact Assessment (EIA) requires changes in the EIA practice of the EU member states. This paper investigates the extent to which the Environmental Impact Assessment (EIA) can contribute to an early consideration of climate change consequences in planning processes. In particular the roles of different actors in order to incorporate climate change impacts and adaptation into project planning subject to EIA at the appropriate levels are a core topic. Semi-structured expert interviews were carried out with representatives of the main infrastructure companies and institutions responsible in these sectors in Austria, which have to carry out EIA regularly. In a second step expert interviews were conducted with EIA assessors and EIA authorities in Austria and Germany, in order to examine the extent to which climate-based changes are already considered in EIA processes. This paper aims to discuss the different perspectives in the current EIA practice with regard to integrating climate change impacts as well as barriers and solutions identified by the groups of actors involved, namely project developers, environmental competent authorities and consultants (EIA assessors/practitioners). The interviews show that different groups of actors consider the topic to different degrees. Downscaling of climate change scenarios is in this context both, a critical issue with regards to availability of data and costs. Furthermore, assistance for the interpretation of relevant impacts, to be deducted from climate change scenarios, on the specific environmental issues in the area is needed. The main barriers identified by the EIA experts therefore include a lack of data as well as general uncertainty as to how far climate change should be considered in the process without reliable data but in the presence of knowledge about possible consequences at an abstract level. A joint strategy on how to cope with uncertain prognoses about main impacts on environmental issues for areas without reliable data requires a discussion and cooperation between EIA consultants and environmental authorities. (C) 2015 Elsevier Inc. All rights reserved.
C1 [Jiricka, Alexandra; Formayer, Herbert; Schmidt, Anna] Univ Nat Resources & Appl Life Sci, Vienna, Austria.
   [Jiricka, Alexandra; Formayer, Herbert; Schmidt, Anna] Inst Landscape Dev Recreat & Conservat Planning, Dept Landscape Spatial & Infrastruct Sci, Peter Jordan Str 82, A-1190 Vienna, Austria.
   [Voeller, Sonja; Leitner, Markus] Environm Agcy Austria, Environm Impact Assessment & Climate Change, Spittelauer Lande 5, A-1090 Vienna, Austria.
   [Fischer, Thomas B.] Univ Liverpool, Sch Environm Sci, Environm Assessment & Management, 74 Bedford St South, Liverpool L69 7ZQ, Merseyside, England.
   [Wachter, Thomas F.] Buro Umweltplanung Dr Wachter, Wiesnerring 2c, Hamburg, Germany.
C3 BOKU University; University of Liverpool
RP Jiricka, A (corresponding author), Univ Nat Resources & Appl Life Sci, Vienna, Austria.; Jiricka, A (corresponding author), Inst Landscape Dev Recreat & Conservat Planning, Dept Landscape Spatial & Infrastruct Sci, Peter Jordan Str 82, A-1190 Vienna, Austria.
EM alexandra.jiricka@boku.ac.at
RI Fischer, Thomas/ABD-5130-2021
OI Fischer, Thomas B/0000-0003-1436-1221; Jiricka-Purrer,
   Alexandra/0000-0002-6842-1835; Formayer, Herbert/0000-0002-2126-9696
FU Austrian Climate Research Programme
FX This article was funded under the Austrian Climate Research Programme.
   The authors thank OIR, Vienna, which was the managing institution of the
   project "envisage-cc" in particular Erich Dalhammer and Gregori Stanzer.
CR Akerlof K, 2013, GLOBAL ENVIRON CHANG, V23, P81, DOI 10.1016/j.gloenvcha.2012.07.006
   Altvater S., 2011, Assessment of the Most Significant Threats to the EU Posed by the Changing Climate in the Short, Medium and Long Term-Task 1 Report
   [Anonymous], INLAND TRANSPORT CLI
   [Anonymous], NONP GUID PROJ MAN M
   [Anonymous], IOP C SERIES EARTH E
   [Anonymous], COASTLINE REPORTS
   [Anonymous], IMPACT CLIMATE CHANG
   [Anonymous], INC CLIM CHANG CONS
   [Anonymous], ADAPT PERISH REV PLA
   [Anonymous], 2009, PLANNING CLIMATE CHA
   [Anonymous], 9 INT S EC
   [Anonymous], SUPPORT DEV EU ST 1
   [Anonymous], STRATEGISCHE UNTERST
   [Anonymous], INT BEST PRACTICE PR
   [Anonymous], J GEOPHYS RES EARTH
   [Anonymous], ADAPTATION INFRASTRU
   [Anonymous], TOWN COUNTRY PLANN
   [Anonymous], 2014, HERAUSFORDERUNGEN BE
   [Anonymous], J ANIM ECOL
   [Anonymous], GUID INT CLIM CHANG
   [Anonymous], 2011, CLIM RES INFR PREP C
   [Anonymous], ICAM 32 C ALP MET 3
   [Anonymous], 2013, BIODIVERSITAT KLIMAW
   [Anonymous], PLANUNGS MANAGEMENTS
   [Anonymous], REALLY FRONT RUNNER
   [Anonymous], LEITF KLIM EN RAHM U
   [Anonymous], KLIMAANDERUNGSSZENAR
   [Anonymous], DEP RAUM LANDSCHAFT
   [Anonymous], STATE ART FORSCHUNG
   [Anonymous], UVP REPORT
   [Anonymous], THESIS U LIVERPOOL
   [Anonymous], 24 OECD
   Araújo MB, 2007, GLOBAL ECOL BIOGEOGR, V16, P743, DOI 10.1111/j.1466-8238.2007.00359.x
   Biesbroek GR, 2010, GLOBAL ENVIRON CHANG, V20, P440, DOI 10.1016/j.gloenvcha.2010.03.005
   Birkmann J, 2009, RAUMFORSCH RAUMORDN, V67, P114, DOI 10.1007/BF03185700
   Dullinger S, 2012, NAT CLIM CHANGE, V2, P619, DOI 10.1038/NCLIMATE1514
   EC-European Commission, 2013, GUID INT CLIM CHANG
   ENEI R, 2011, VULNERABILITY TRANSP
   Essl F, 2013, BIODIVERSITAT KLIMAW
   Essl F, 2011, P NATL ACAD SCI USA, V108, pE221, DOI 10.1073/pnas.1107028108
   Essl F, 2009, BIOL CONSERV, V142, P2547, DOI 10.1016/j.biocon.2009.05.027
   Fischer T.B., 2006, Impact Assessment and Project Appraisal, V24, P183, DOI DOI 10.3152/147154606781765183
   Fischer T.B., 1999, Journal of Environmental Planning and Management, V42, P189, DOI DOI 10.1080/09640569911217
   Fischer T.B., 2002, STRATEGIC ENV ASSESS
   Fischer Thomas B., 2011, Journal of Environmental Assessment Policy and Management, V13, P541, DOI 10.1142/S1464333211004000
   Fischer TB, 2009, ENVIRON IMPACT ASSES, V29, P421, DOI 10.1016/j.eiar.2009.03.001
   Gottfried M, 2012, NAT CLIM CHANGE, V2, P111, DOI [10.1038/nclimate1329, 10.1038/NCLIMATE1329]
   Jha-Thakur U., 2009, Impact Assessment and Project Appraisal, V27, P133, DOI DOI 10.3152/146155109X454302
   Jiricka A, 2009, ENVIRON IMPACT ASSES, V29, P379, DOI 10.1016/j.eiar.2009.02.001
   Jochem E, 2009, ADAPTATION MITIGATIO
   Kamau JW, 2013, INT J CLIM CHANG STR, V5, P152, DOI 10.1108/17568691311327569
   Kuckartz U., 2007, Qualitative Evaluation, V1st
   Larsen SV, 2014, IMPACT ASSESS PROJ A, V32, P234, DOI 10.1080/14615517.2014.898386
   Li YM, 2013, INTEGR ZOOL, V8, P145, DOI 10.1111/1749-4877.12001
   Marshall R., 2006, Journal of Environmental Planning and Management, V49, P279, DOI [DOI 10.1080/09640560500508155, 10.1080/09640560500508155]
   Mayring P, 2010, Qualitative Inhaltsanalyse. Grundlagen und Techniken, DOI 10.1007/978-3-531-92052-8_42
   Melcher A.H., 2012, CURRENT QUESTIONS WA, P117
   Miller F, 2013, IMPACT ASSESS PROJ A, V31, P190, DOI 10.1080/14615517.2013.819724
   Moser SC, 2010, WIRES CLIM CHANGE, V1, P31, DOI 10.1002/wcc.11
   Nelson FE, 2001, NATURE, V410, P889, DOI 10.1038/35073746
   Newig J., 2007, RES PRACTICE SUSTAIN, V1, P51, DOI DOI 10.1016/j.jenvman.2009.01.001
   Ohsawa T, 2014, IMPACT ASSESS PROJ A, V32, P222, DOI 10.1080/14615517.2014.913761
   Peterson T.C., 2008, Climate variability and change with implications for transportation
   Rannow S, 2010, LANDSCAPE URBAN PLAN, V98, P160, DOI 10.1016/j.landurbplan.2010.08.017
   Rebelo H, 2010, GLOBAL CHANGE BIOL, V16, P561, DOI 10.1111/j.1365-2486.2009.02021.x
   Refsgaard JC, 2013, MITIG ADAPT STRAT GL, V18, P337, DOI 10.1007/s11027-012-9366-6
   Rehnus M, 2013, HYSTRIX, V24, P161, DOI 10.4404/hystrix-24.2-4703
   Robine JM, 2008, CR BIOL, V331, P171, DOI 10.1016/j.crvi.2007.12.001
   Roeser S, 2012, RISK ANAL, V32, P1033, DOI 10.1111/j.1539-6924.2012.01812.x
   Runge K., 2010, UVP REPORT, V24, P165
   Runge Karsten, 2010, Naturschutz und Landschaftsplanung, V42, P141
   Sathaye JA, 2013, GLOBAL ENVIRON CHANG, V23, P499, DOI 10.1016/j.gloenvcha.2012.12.005
   Schmid M, 2014, CLIMATIC CHANGE, V124, P301, DOI 10.1007/s10584-014-1087-2
   Sherwin HA, 2013, MAMMAL REV, V43, P171, DOI 10.1111/j.1365-2907.2012.00214.x
   Sok V., 2011, Impact Assessment and Project Appraisal, V29, P317
   Stoffel M, 2014, SCI TOTAL ENVIRON, V493, P1255, DOI 10.1016/j.scitotenv.2014.02.102
   Stoffel M, 2012, PROG PHYS GEOG, V36, P421, DOI 10.1177/0309133312441010
   Valiela I, 2003, AMBIO, V32, P476, DOI 10.1639/0044-7447(2003)032[0476:SIWDIB]2.0.CO;2
   World Health Organization, 2012, ATL HLTH CLIM CHANG
NR 79
TC 30
Z9 32
U1 1
U2 22
PU ELSEVIER SCIENCE INC
PI NEW YORK
PA STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA
SN 0195-9255
EI 1873-6432
J9 ENVIRON IMPACT ASSES
JI Environ. Impact Assess. Rev.
PD FEB
PY 2016
VL 57
BP 78
EP 88
DI 10.1016/j.eiar.2015.11.010
PG 11
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA DH3GL
UT WOS:000372675400009
DA 2025-01-10
ER

PT J
AU Jhariya, MK
   Singh, L
   Toppo, S
AF Jhariya, Manoj Kumar
   Singh, Lalji
   Toppo, Shalini
TI Wildfires and carbon budget of certain seasonally dry forests in India
SO LAND DEGRADATION & DEVELOPMENT
LA English
DT Article
DE carbon sequestration; CO2 mitigation; tropical forest; vegetation;
   wildfire
ID TROPICAL FOREST; DECIDUOUS FORESTS; URBAN SETUP; SOIL; BIOMASS; FIRE;
   ACCUMULATION; CHHATTISGARH; DIVERSITY; DYNAMICS
AB Globally, the increasing fire events in addition to climate change due to the emission of carbon dioxide (CO2) as well as other greenhouse gases exerts huge pressure on natural resources and their management. This phenomenon is more severe in the tropical region due to increasing population, urbanization, industrialization, existing pressures, and limiting conditions. In the present study, carbon (C) stock, carbon sequestration (C-seq), CO2 mitigation potential, C budget, and C flux of the seasonally dry forest ecosystem of Chhattisgarh under the influence of wildfire in the protected area and its proximity were evaluated. Four sites namely, high fire zone (HFZ), medium fire zone (MFZ), low fire zone (LFZ), and non-fire zone (NFZ) were selected and marked based on fire return intervals (frequency) and extent of damage. The present work is a novel approach that assesses the impact of different fire frequencies on C dynamics of fire-affected zones. The stratified sampling technique was used within a permanent plot of 1 hectare. Forest stands on each site were analyzed using 10 randomly placed quadrats (each 10 x 10 m in size) and data were collected from each site. Across the sites higher tree density was observed at NFZ and the lowest at HFZ.Total tree biomass ranged between 116.0 and 358.4 t ha(-1) across the fire regimes. Total vegetation C stock ranged between 59.1 and 169.5 t ha-1 in different sites. The C mitigation and C-seq potential ranged between 186.2 and 575.3 t ha(-1), and 7.1 and 15.9 t ha(-1), respectively being highest in NFZ and lowest in HFZ. The species such as Anogeissus latifolia, Buchanania lanzan, Shorea robusta, Lannea coromandelica, Lagerstroemia parviflora, Ougeinia oojeinensis, Terminalia chebula, Terminalia tomentosa are the major contributor in biomass, C stock, C mitigation, and Cseq potential in different fire regimes. Thus, our findings would be highly useful in the restoration process of fire-affected zones through the plantation of selective plant species. Therefore, the aforementioned species could be effectively utilized while going for an afforestation/reforestation program, and will be helpful in climate change adaptation and mitigation strategies under different fire zones.
C1 [Jhariya, Manoj Kumar] St Gahira Guru Vishwavidyalaya, Dept Farm Forestry, Ambikapur 497001, CG, India.
   [Singh, Lalji; Toppo, Shalini] Indira Gandhi Krishi Vishwavidyalaya, Coll Agr, Dept Forestry, Raipur, Ambikapur, India.
C3 Sant Gahira Guru Vishwavidyalaya, Sarguja; Indira Gandhi Krishi
   Vishwavidyalaya (IGKV)
RP Jhariya, MK (corresponding author), St Gahira Guru Vishwavidyalaya, Dept Farm Forestry, Ambikapur 497001, CG, India.
EM manu9589@gmail.com
RI JHARIYA, DR. MANOJ KUMAR/AAX-3442-2021
OI JHARIYA, DR. MANOJ KUMAR/0000-0002-5661-4904
FU UGC (RGNF) New Delhi; Indira Gandhi Krishi Vishwavidyalaya, Raipur,
   Chhattisgarh, India
FX The first author is thankful to the State Forest Department (C.G.) for
   granting permission and necessary support. Financial support to MKJ from
   UGC (RGNF) New Delhi during Ph.D. is highly acknowledged. Thanks are due
   to Dr. J.S. Singh, Professor Emeritus, Department of Botany, Banaras
   Hindu University, Varanasi, India for the valuable suggestions for
   improving the manuscript, and to Prof. Rup Narayan, Department of
   Botany, Chaudhary Charan Singh University, Meerut, India for vetting the
   language. Thanks, are also due to the authorities of Indira Gandhi
   Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India for granting the
   necessary permissions as and when required during the study period. The
   authors are also thankful to the reviewers and editor for closer looks
   into the MS and for valuable comments and suggestions.
CR Abhishek R., 2021, ECOLOGICAL INTENSIFI, P137
   Almagro M, 2009, SOIL BIOL BIOCHEM, V41, P594, DOI 10.1016/j.soilbio.2008.12.021
   Anderegg WRL, 2020, SCIENCE, V368, P1327, DOI 10.1126/science.aaz7005
   [Anonymous], 2007, IPCC Fourth Assessment Report: Climate Change 2007
   [Anonymous], 2013, Research, DOI DOI 10.7537/MARSRSJ050313.01
   Baboo B, 2017, TROP ECOL, V58, P409
   Babu KN, 2023, FOREST ECOL MANAG, V540, DOI 10.1016/j.foreco.2023.121057
   Bae MS, 2019, ENVIRON POLLUT, V246, P274, DOI 10.1016/j.envpol.2018.12.013
   Bargali H., 2022, Trees, Forests and People, V9, DOI [DOI 10.1016/J.TFP.2022.100300, 10.1016/j.tfp.2022.100300]
   Bargali H, 2023, FRONT FOR GLOB CHANG, V6, DOI 10.3389/ffgc.2023.1198143
   Behera SK, 2017, ECOL ENG, V99, P513, DOI 10.1016/j.ecoleng.2016.11.046
   Boisvenue C, 2006, GLOBAL CHANGE BIOL, V12, P862, DOI 10.1111/j.1365-2486.2006.01134.x
   Bonham CD., 2013, Measurements for terrestrial vegetation, P117, DOI [10.1002/9781118534540, DOI 10.1002/9781118534540]
   Calfapietra C., 2015, Ecosystem Health and Sustainability, V1, P25, DOI 10.1890/EHS15-0023
   Caretto S, 2015, INT J MOL SCI, V16, P26378, DOI 10.3390/ijms161125967
   Chaturvedi RK, 2017, J VEG SCI, V28, P997, DOI 10.1111/jvs.12547
   Chaturvedi RK, 2015, FOREST ECOL MANAG, V339, P11, DOI 10.1016/j.foreco.2014.12.002
   Chaturvedi RK, 2011, FOREST ECOL MANAG, V262, P1576, DOI 10.1016/j.foreco.2011.07.006
   Collalti A, 2020, GLOBAL CHANGE BIOL, V26, P1739, DOI 10.1111/gcb.14857
   CURTIS JT, 1950, ECOLOGY, V31, P434, DOI 10.2307/1931497
   de Meira MS Jr, 2020, CARBON BAL MANAGE, V15, DOI 10.1186/s13021-020-00147-2
   Devi A, 2023, S AFR J BOT, V162, P171, DOI 10.1016/j.sajb.2023.09.012
   Dhar T, 2023, REMOTE SENS APPL, V29, DOI 10.1016/j.rsase.2022.100883
   Foster CN, 2017, ECOL APPL, V27, P2369, DOI 10.1002/eap.1614
   Jaboyedoff M, 2016, LANDSLIDES AND ENGINEERED SLOPES: EXPERIENCE, THEORY AND PRACTICE, VOLS 1-3, P217
   Jandl R, 2007, GEODERMA, V137, P253, DOI 10.1016/j.geoderma.2006.09.003
   Jhariya MK, 2021, INT J ENVIRON SCI TE, V18, P3967, DOI 10.1007/s13762-020-03062-8
   Jhariya M. K., 2018, Journal of Forest and Environmental Science, V34, P1
   Jhariya M. K., 2017, Journal of Forest and Environmental Science, V33, P330
   Jhariya M. K., 2014, International Journal of Ecology and Environmental Sciences, V40, P57
   Jhariya MK, 2012, VEGETOS, V25, P210
   Jhariya M. K., 2023, INT RES J PLANT SCI, V14, P1, DOI [10.14303/irjps.2023.47, DOI 10.14303/IRJPS.2023.47]
   Jhariya M.K., 2019, Sustainable Agriculture, Forest and Environmental Management, DOI [10.1007/978-981-13-6830-1, DOI 10.1007/978-981-13-6830-1]
   Jhariya MK, 2021, ENVIRON DEV SUSTAIN, V23, P6800, DOI 10.1007/s10668-020-00892-x
   Jhariya MK, 2017, ENVIRON MONIT ASSESS, V189, DOI 10.1007/s10661-017-6246-2
   Kauppi PE, 2010, FOREST ECOL MANAG, V259, P1239, DOI 10.1016/j.foreco.2009.07.044
   Khan N., 2021, Ecol. Intensif. Nat. Resour. Sustain. Agric., P461, DOI [10.1007/978-981-33-4203-3_13, DOI 10.1007/978-981-33-4203-313]
   Khan N., 2021, Ecological Intensification of Natural Resources for Sustainable Agriculture, P565, DOI [DOI 10.1007/978-981-33-4203-3_16, 10.1007/978-981-33-4203-3_16]
   Khan N, 2024, ENVIRON DEV SUSTAIN, V26, P11623, DOI 10.1007/s10668-023-03436-1
   Khan N, 2020, ENVIRON SCI POLLUT R, V27, P5418, DOI 10.1007/s11356-019-07172-w
   Khan N, 2020, ENVIRON SCI POLLUT R, V27, P2881, DOI 10.1007/s11356-019-07182-8
   Kittur BH, 2014, J FORESTRY RES, V25, P857, DOI 10.1007/s11676-014-0471-0
   Kujur E, 2021, ENVIRON EARTH SCI, V80, DOI 10.1007/s12665-021-10019-8
   Kujur E, 2022, ENVIRON DEV SUSTAIN, V24, P2861, DOI 10.1007/s10668-021-01557-z
   Lasco RD., 2003, Ann Trop Res, V25, P37, DOI DOI 10.1007/S11707-020-0825-1
   Liski J, 2006, ANN FOREST SCI, V63, P687, DOI 10.1051/forest:2006049
   Meena A, 2019, ECOL PROCESS, V8, DOI 10.1186/s13717-019-0163-y
   Miller JED, 2020, GLOBAL ECOL BIOGEOGR, V29, P1621, DOI 10.1111/geb.13115
   Mina U, 2023, FIRE ECOL, V19, DOI 10.1186/s42408-023-00177-4
   North MP, 2011, FOREST ECOL MANAG, V261, P1115, DOI 10.1016/j.foreco.2010.12.039
   Pandey R, 2023, LAND DEGRAD DEV, V34, P1522, DOI 10.1002/ldr.4550
   Pawar G. V., 2014, Journal of Applied and Natural Science, V6, P383
   Pérez-Cabello F, 2012, J ARID ENVIRON, V76, P88, DOI 10.1016/j.jaridenv.2011.08.007
   Ponomarev E, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12050559
   Pragasan LA, 2005, CURR SCI INDIA, V88, P1255
   Proctor J., 1983, Tropical rain forest; ecology and management, P267
   Pugh TAM, 2019, NAT GEOSCI, V12, P730, DOI 10.1038/s41561-019-0427-2
   RAJ A., 2022, Biodiversity, Conservation and Sustainability in Asia: Volume 2: Prospects and Challenges in South and Middle Asia, V2, P33
   Raj A, 2021, J ENVIRON MANAGE, V293, DOI 10.1016/j.jenvman.2021.112829
   Raj A, 2021, LANDSC ECOL ENG, V17, P387, DOI 10.1007/s11355-021-00450-1
   Samal B, 2022, ECOL ENG, V175, DOI 10.1016/j.ecoleng.2021.106490
   Sannigrahi S, 2020, INTEGR ENVIRON ASSES, V16, P773, DOI 10.1002/ieam.4287
   Schwilk DW, 2015, NEW PHYTOL, V206, P486, DOI 10.1111/nph.13372
   Shahi C, 2023, TROP ECOL, V64, P180, DOI 10.1007/s42965-022-00258-6
   Singh K.P., 1979, STRUCTURE FUNCTIONIN, P160
   SINGH L, 1991, ANN BOT-LONDON, V68, P263, DOI 10.1093/oxfordjournals.aob.a088252
   Stephan K, 2010, FIRE ECOL, V6, P95, DOI 10.4996/fireecology.0601095
   Strand EK, 2019, FIRE ECOL, V15, DOI 10.1186/s42408-019-0038-8
   Thakrey M, 2022, LAND DEGRAD DEV, V33, P1810, DOI 10.1002/ldr.4263
   Venkatesh K, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105856
   Verma S, 2017, ECOL PROCESS, V6, DOI 10.1186/s13717-017-0098-0
   Vilén T, 2012, FOREST ECOL MANAG, V286, P203, DOI 10.1016/j.foreco.2012.08.048
   Volkova L, 2021, J ENVIRON MANAGE, V290, DOI 10.1016/j.jenvman.2021.112673
   Wang QK, 2012, FOREST ECOL MANAG, V271, P91, DOI 10.1016/j.foreco.2012.02.006
   Wilson N, 2021, FOREST ECOL MANAG, V481, DOI 10.1016/j.foreco.2020.118701
   Yadav D. K., 2010, BIOMASS NET PRIMARY
   Yadav VS, 2022, ECOL ENG, V176, DOI 10.1016/j.ecoleng.2022.106541
   Zhang CH, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/11/114021
NR 78
TC 3
Z9 3
U1 2
U2 3
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1085-3278
EI 1099-145X
J9 LAND DEGRAD DEV
JI Land Degrad. Dev.
PD JUL 30
PY 2024
VL 35
IS 12
BP 3771
EP 3789
DI 10.1002/ldr.5166
EA MAY 2024
PG 19
WC Environmental Sciences; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Agriculture
GA YY6I8
UT WOS:001226509900001
DA 2025-01-10
ER

PT J
AU Neves, JL
AF Neves, Jose Lourenco
TI Urban planning for flood resilience under technical and financial
   constraints: The role of planners and competence development in building
   a flood-resilient city in Matola, Mozambique
SO CITY AND ENVIRONMENT INTERACTIONS
LA English
DT Article
DE Resilience; Urban planning; Floods; Matola; Mozambique
ID CLIMATE-CHANGE ADAPTATION; VULNERABILITY; VARIABILITY; LESSONS; COUNTY;
   MAPUTO; RISK
AB Today, urban flood resilience constitutes an academic and political discourse as well as a 'proposed state ' to be achieved within urban management, planning, and development. Matola, a major Mozambican coastal city, has witnessed many floods, mainly caused by rainfall, the most devastating of which happened in 2000. This study analyses the actions the urban planners took during that major flood event, what flood mitigation and adaptation strategies and measures for increased flood resilience they have developed since that flood event, and the contribution of urban planning to building flood resilience under financial and technical constraints. The study is based on interviews with 32 urban planners from Matola and observations in the field. In addition to financial limitations, the main challenge in promoting flood resilience in Matola is the deficient and insufficient coordination in mitigation and adaptation actions among urban planners, political elites, and members of low-income urban communities, who use floodplain areas for purposes that contradict resilience -building actions. During the 2000 floods, mitigation actions were carried out by rescuing people and goods and placing them in accommodation centres. After the 2000 floods, gradual adaptation strategies and measures were carried out, such as hiring and training staff, designing a new urban plan, gradual resettlement, opening drainage channels, and allocating water pumping systems in some areas to promote flood resilience. The study concludes that urban planning contributed significantly to the building and promotion of flood resilience in Matola: the strategies and measures taken so far have contributed significantly to reducing the exposure and vulnerability to flooding of the population, their assets, and urban infrastructure, as well as improving the ecosystem in lowlands and coastal protection wetlands. The study brings a contribution from retrospective and prospective resilience thinking to the debate on building and promoting resilience in urban socio-ecological systems, showing the role of urban planners, and planning and management activity since the 2000 floods, and perspectives on the future. The study demonstrates that the development of competences or technical skills to plan and manage strategies and measures to promote resilience is a key factor in promoting socio-ecological resilience.
C1 [Neves, Jose Lourenco] Univ Gothenburg, Dept Econ & Soc, Unit Human Geog, Viktoriagatan 13,4th Floor,POB 625, S-40530 Gothenburg, Sweden.
   [Neves, Jose Lourenco] Univ Pedag Maputo, Fac Ciencias Terra & Ambiente, Av Trabalho 9 2482 Bairro Chamanculo C,Campus Lhan, Maputo, Mozambique.
C3 University of Gothenburg
RP Neves, JL (corresponding author), Univ Gothenburg, Dept Econ & Soc, Unit Human Geog, Viktoriagatan 13,4th Floor,POB 625, S-40530 Gothenburg, Sweden.; Neves, JL (corresponding author), Univ Pedag Maputo, Fac Ciencias Terra & Ambiente, Av Trabalho 9 2482 Bairro Chamanculo C,Campus Lhan, Maputo, Mozambique.
EM jose.lourenco.neves@gu.se
FU University of Gothenburg [Sida-51140073]; UEM [Sida-51140073]
FX This work was supported by the Sida - Mozambique Bilateral Programme,
   which funds the collaboration subprogram between UEM and the University
   of Gothenburg (Grant no. Sida-51140073) .
CR Aldunce P, 2015, GLOBAL ENVIRON CHANG, V30, P1, DOI 10.1016/j.gloenvcha.2014.10.010
   ANDREATTA Verena., 2011, Relatorio sobre as condicoes do Planejamento Urbano, Habitacao e Infraestruturas em Maputo, Mocambique
   [Anonymous], 2005, AVALIACAO DA VULNERABILIDADE AS MUDANCAS CLIMATICAS E ESTRATEGIAS DE ADAPTACAO
   [Anonymous], 2007, Guidance on Flash Flood Management. Recent Experiences from Central and Eastern Europe
   [Anonymous], 2014, Caminhos de Geografia, DOI DOI 10.14393/RCG155126626
   [Anonymous], 2009, Terminology on Disaster Risk Reduction
   Araujo ManuelG., 2003, GEOUSP - Espaco e Tempo, V14, P165, DOI 10.11606/issn.2179-0892.geousp.2003.123846
   Artur L, 2012, GLOBAL ENVIRON CHANG, V22, P529, DOI 10.1016/j.gloenvcha.2011.11.013
   Bacci M., 2014, Climate Change Vulnerability in Southern African Cities: building Knowledge for Adaptation, P143, DOI [10.1007/978-3-319-00672-7_9, DOI 10.1007/978-3-319-00672-7_9]
   Balica SF, 2013, ENVIRON MODELL SOFTW, V41, P84, DOI 10.1016/j.envsoft.2012.11.002
   Bertilsson L, 2019, J HYDROL, V573, P970, DOI 10.1016/j.jhydrol.2018.06.052
   Broto VC, 2015, CURR OPIN ENV SUST, V13, P11, DOI 10.1016/j.cosust.2014.12.005
   Broto VC, 2013, LOCAL ENVIRON, V18, P678, DOI 10.1080/13549839.2013.801573
   Brown K, 2016, Resilience, development and global change, P204
   Bunce M, 2010, ENVIRON SCI POLICY, V13, P485, DOI 10.1016/j.envsci.2010.06.003
   CM, 2013, Plano de contingencia para a epoca chuvosa e de ciclones, 2013-2014
   Cmcm, 2010, Regulamento do Plano de estrutura Urbana da cidade da Matola
   Cutter SL, 2000, ANN ASSOC AM GEOGR, V90, P713, DOI 10.1111/0004-5608.00219
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Douglas I, 2008, ENVIRON URBAN, V20, P187, DOI 10.1177/0956247808089156
   Douglas I, 2018, LANDSCAPE URBAN PLAN, V180, P262, DOI 10.1016/j.landurbplan.2016.09.025
   Eu, 2018, LIFE & Urban resilience
   Ficchi A, 2019, GEOPHYS RES LETT, V46, P8809, DOI 10.1029/2019GL081988
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   George O, 2019, CLIM CHANG MANAG, P487, DOI 10.1007/978-3-030-12974-3_22
   GFDRR; WBG; EU; UNDP & INGC, 2014, Mozambique-Recovery from Recurrent Floods 2000-2013: Recovery Framework Case Study
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Inam, 2022, Avaliacao da epoca chuvosa 2021-2022
   INE, 2008, Estatisticas de Cidade da Matola Distrito
   INE, 2019, Definitive Results. 2017 Census. IV General Population and Housing Census
   Kundzewicz ZW, 2014, HYDROLOG SCI J, V59, P1, DOI 10.1080/02626667.2013.857411
   Laeni N, 2019, CITIES, V90, P157, DOI 10.1016/j.cities.2019.02.002
   Liao KH, 2016, LANDSCAPE URBAN PLAN, V155, P69, DOI 10.1016/j.landurbplan.2016.01.014
   Liao KH, 2014, NAT HAZARDS, V71, P723, DOI 10.1007/s11069-013-0923-4
   Liao KH, 2012, ECOL SOC, V17, DOI 10.5751/ES-05231-170448
   MacKay B, 2013, TECHNOL FORECAST SOC, V80, P673, DOI 10.1016/j.techfore.2012.06.003
   Micoa, 2008, Programa nacional de acao de adaptacao
   Mkhandi SH, 2000, HYDROLOG SCI J, V45, P449, DOI 10.1080/02626660009492341
   Modell S, 2020, ACCOUNT AUDIT ACCOUN, V33, P621, DOI 10.1108/AAAJ-01-2019-3863
   Mugume SN, 2015, WATER RES, V81, P15, DOI 10.1016/j.watres.2015.05.030
   Neves JL, 2023, AFR GEOGR REV, V42, P539, DOI 10.1080/19376812.2022.2076133
   Norizan NZA, 2021, LAND USE POLICY, V102, DOI 10.1016/j.landusepol.2020.105178
   OMS & MH, 2008, Mozambique disasters: health cluster report
   Owusu K, 2021, African Handbook of Climate Change Adaptation, DOI [10.1007/978-3-030-45106-6_249, DOI 10.1007/978-3-030-45106-6_249]
   Pelling Mark., 2009, DISASTER RISK REDUCT
   Petit-Boix A, 2017, J CLEAN PROD, V162, P601, DOI 10.1016/j.jclepro.2017.06.047
   Pollalis YA, 2008, Int J Technol Manag
   Priest SJ, 2016, ECOL SOC, V21, DOI 10.5751/ES-08913-210450
   ReliefWeb, 2000, Maputo, Matola threatened by floods
   Ritchie H., 2020, Natural Disasters
   Rodrigues CU, 2019, INT J URBAN SUSTAIN, V11, P319, DOI 10.1080/19463138.2019.1585859
   Sehested K, 2009, PLAN THEORY PRACT, V10, P245, DOI 10.1080/14649350902884516
   Singh RB, 2014, Trans Inst Indian Geographers, V36
   Smith Keith, 2013, Environmental hazards: assessing risk and reducing disaster, DOI [10.4324/9780203805305, DOI 10.4324/9780203805305]
   Song J, 2019, CITIES, V95, DOI 10.1016/j.cities.2019.06.012
   UFCOP, 2016, Land Use Planning for Urban Flood Risk Management
   UN-Habitat, 2023, SDG 11: Sustainable Cities and Communities
   UN-Habitat, 2018, Profile of the housing sector in Mozambique
   UNDRR, 2017, National Disaster Risk Assessment Words into Action Guidelines Governance System, Methodologies, and Use of Results
   UNDRR, 2019, P RES DIV SAF INCL S
   Van Logchem B, 2012, Respondendo as Mudancas Climaticas em Mocambique: relatorio Sintese
   Vitale C, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2020.104575
   Wamsler C, 2014, SUSTAINABILITY-BASEL, V6, P1359, DOI 10.3390/su6031359
   Zevenbergen C, 2020, PHILOS T R SOC A, V378, DOI 10.1098/rsta.2019.0212
NR 65
TC 0
Z9 0
U1 5
U2 5
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2590-2520
J9 CITY ENVIRON INTERAC
JI City Environ. Interact.
PD APR
PY 2024
VL 22
AR 100147
DI 10.1016/j.cacint.2024.100147
EA MAR 2024
PG 14
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA QM8T9
UT WOS:001221389000001
OA gold
DA 2025-01-10
ER

PT J
AU Wang, C
   Leisz, S
   Li, L
   Shi, XY
   Mao, JF
   Zheng, Y
   Chen, AP
AF Wang, Chao
   Leisz, Stephen
   Li, Li
   Shi, Xiaoying
   Mao, Jiafu
   Zheng, Yi
   Chen, Anping
TI Historical and projected future runoff over the Mekong River basin
SO EARTH SYSTEM DYNAMICS
LA English
DT Article
ID MULTIPLE GLOBAL CLIMATE; EMERGENT CONSTRAINTS; HYDROLOGICAL EXTREMES;
   MODELS; IMPACT; UNCERTAINTY; CMIP5; FLOW; PRECIPITATION; DISCHARGE
AB The Mekong River (MR) crosses the borders and connects six countries, including China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. It provides critical water resources and supports natural and agricultural ecosystems, socioeconomic development, and the livelihoods of the people living in this region. Understanding changes in the runoff of this important international river under projected climate change is critical for water resource management and climate change adaptation planning. However, research on long-term runoff dynamics for the MR and the underlying drivers of runoff variability remains scarce. Here, we analyse historical runoff variations from 1971 to 2020 based on runoff gauge data collected from eight hydrological stations along the MR. With these runoff data, we then evaluate the runoff simulation performance of five global hydrological models (GHMs) forced by four global climate models (GCMs) under the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Furthermore, based on the best simulation combination, we quantify the impact of future climate change on river runoff changes in the MR. The result shows that the annual runoff in the MR has not changed significantly in the past 5 decades, while the establishment of dams and reservoirs in the basin visibly affected the annual runoff distribution. The ensemble-averaged result of the Water Global Assessment and Prognosis version 2 (WaterGAP2; i.e. GHM) forced by four GCMs has the best runoff simulation performance. Under Representative Concentration Pathways (RCPs; i.e. RCP2.6, RCP6.0 and RCP8.5), the runoff of the MR is projected to increase significantly (p<0.05); e.g. 3.81 +/- 3.47 m(3)s(-1)a(-1) (9 +/- 8 % increase in 100 years) at the upper reach under RCP2.6 and 16.36 +/- 12.44 m(3)s(-1)a(-1) (13 +/- 10 % increase in 100 years) at the lower reach under RCP6.0. In particular, under the RCP6.0 scenario, the increase in annual runoff is most pronounced in the middle and lower reaches, due to increased precipitation and snowmelt. Under the RCP8.5 scenario, the runoff distribution in different seasons varies obviously, increasing the risk of flooding in the wet season and drought in the dry season.
C1 [Wang, Chao; Zheng, Yi] Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen 518055, Peoples R China.
   [Leisz, Stephen] Colorado State Univ, Dept Anthropol & Geog, Ft Collins, CO 80523 USA.
   [Leisz, Stephen] VinUniv, VinUnivers, Ocean Pk, Hanoi, Vietnam.
   [Li, Li] Penn State Univ, Dept Civil & Environm Engn, University Pk, PA 16802 USA.
   [Shi, Xiaoying; Mao, Jiafu] Oak Ridge Natl Lab, Environm Sci Div, Oak Ridge, TN 37831 USA.
   [Shi, Xiaoying; Mao, Jiafu] Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37831 USA.
   [Chen, Anping] Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.
   [Chen, Anping] Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA.
C3 Southern University of Science & Technology; Colorado State University;
   VinUniversity; Pennsylvania Commonwealth System of Higher Education
   (PCSHE); Pennsylvania State University; Pennsylvania State University -
   University Park; United States Department of Energy (DOE); Oak Ridge
   National Laboratory; United States Department of Energy (DOE); Oak Ridge
   National Laboratory; Colorado State University; Colorado State
   University
RP Chen, AP (corresponding author), Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.; Chen, AP (corresponding author), Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA.
EM anping.chen@colostate.edu
RI Chen, Anping/H-9960-2014; Shi, Xiaoying/C-4447-2012; Li, Li/A-6077-2008;
   Mao, Jiafu/B-9689-2012
OI Chen, Anping/0000-0003-2085-3863; Shi, Xiaoying/0000-0001-8994-5032; Li,
   Li/0000-0002-1641-3710; Mao, Jiafu/0000-0002-2050-7373
FU National Natural Science Foundation of China; Mekong River Commission
   (MRC)
FX We acknowledge the Mekong River Commission (MRC) for providing the
   observed runoff data and the Inter-Sectoral Impact Model Intercomparison
   Project (ISIMIP) for providing the impact model results.
CR Adamson PT, 2009, AQUAT ECOL-SAN DIEGO, P53, DOI 10.1016/B978-0-12-374026-7.00004-8
   Alcamo J, 2003, HYDROLOG SCI J, V48, P317, DOI 10.1623/hysj.48.3.317.45290
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Arnell NW, 2016, CLIMATIC CHANGE, V134, P387, DOI 10.1007/s10584-014-1084-5
   Arnell NW, 2011, GLOBAL ENVIRON CHANG, V21, P592, DOI 10.1016/j.gloenvcha.2011.01.015
   Baiyinbaoligao Liu, 2020, Flood Prevention and Drought Relief in Mekong River Basin, DOI [10.1007/978-981-15-2006-8_1, DOI 10.1007/978-981-15-2006-8_1]
   Barros V, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, pIX
   Brient F, 2020, ADV ATMOS SCI, V37, P1, DOI 10.1007/s00376-019-9140-8
   Chen H, 2021, SCI TOTAL ENVIRON, V765, DOI 10.1016/j.scitotenv.2020.144494
   Cochrane TA, 2014, HYDROL EARTH SYST SC, V18, P4529, DOI 10.5194/hess-18-4529-2014
   Tran DD, 2018, J ENVIRON MANAGE, V217, P429, DOI 10.1016/j.jenvman.2018.03.116
   Eyler Brian., 2019, Last Days of the Mighty Mekong, DOI 10.5040/9781350221031
   Frieler K, 2017, GEOSCI MODEL DEV, V10, P4321, DOI 10.5194/gmd-10-4321-2017
   Giuntoli I, 2015, EARTH SYST DYNAM, V6, P267, DOI 10.5194/esd-6-267-2015
   Gosling SN, 2011, HYDROL PROCESS, V25, P1129, DOI 10.1002/hyp.7727
   Guan XX, 2021, SCI TOTAL ENVIRON, V798, DOI 10.1016/j.scitotenv.2021.149277
   Hagemann S, 2013, EARTH SYST DYNAM, V4, P129, DOI 10.5194/esd-4-129-2013
   Hall A, 2019, NAT CLIM CHANGE, V9, P269, DOI 10.1038/s41558-019-0436-6
   Hamed KH, 2007, WATER RESOUR RES, V43, DOI 10.1029/2006WR005111
   Hanasaki N, 2018, HYDROL EARTH SYST SC, V22, P789, DOI 10.5194/hess-22-789-2018
   Hoang LP, 2019, SCI TOTAL ENVIRON, V649, P601, DOI 10.1016/j.scitotenv.2018.08.160
   Hoang LP, 2016, HYDROL EARTH SYST SC, V20, P3027, DOI 10.5194/hess-20-3027-2016
   IPCC, 2021, Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI DOI 10.1017/9781009157896
   Johnston R, 2012, WATER RESOUR MANAG, V26, P429, DOI 10.1007/s11269-011-9925-8
   Kingston DG, 2011, HYDROL EARTH SYST SC, V15, P1459, DOI 10.5194/hess-15-1459-2011
   Knutti R, 2017, GEOPHYS RES LETT, V44, P1909, DOI 10.1002/2016GL072012
   Krysanova V, 2018, HYDROLOG SCI J, V63, P696, DOI 10.1080/02626667.2018.1446214
   Lauri H, 2012, HYDROL EARTH SYST SC, V16, P4603, DOI 10.5194/hess-16-4603-2012
   Leng GY, 2015, J ADV MODEL EARTH SY, V7, P1285, DOI 10.1002/2015MS000437
   Li DN, 2017, J HYDROL, V551, P217, DOI 10.1016/j.jhydrol.2017.05.061
   Liu JG, 2022, ENGINEERING-PRC, V13, P144, DOI 10.1016/j.eng.2021.06.026
   Lu XX, 2006, HYDROL EARTH SYST SC, V10, P181, DOI 10.5194/hess-10-181-2006
   Lu XX, 2014, QUATERN INT, V336, P145, DOI 10.1016/j.quaint.2014.02.006
   Lv XZ, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51115-x
   Milly PCD, 2005, NATURE, V438, P347, DOI 10.1038/nature04312
   Müller Schmied H, 2016, HYDROL EARTH SYST SC, V20, P2877, DOI 10.5194/hess-20-2877-2016
   Onoz B., 2003, Turkish Journal of Engineering and Environmental Sciences, V27, P247
   Prudhomme C, 2014, P NATL ACAD SCI USA, V111, P3262, DOI 10.1073/pnas.1222473110
   Ruiz-Barradas A, 2018, J HYDROMETEOROL, V19, P849, DOI 10.1175/JHM-D-17-0195.1
   Schewe J, 2014, P NATL ACAD SCI USA, V111, P3245, DOI 10.1073/pnas.1222460110
   Schlund M, 2020, EARTH SYST DYNAM, V11, P1233, DOI 10.5194/esd-11-1233-2020
   Shiogama H, 2022, NATURE, V602, P612, DOI 10.1038/s41586-021-04310-8
   Sitch S, 2003, GLOBAL CHANGE BIOL, V9, P161, DOI 10.1046/j.1365-2486.2003.00569.x
   Takata K, 2003, GLOBAL PLANET CHANGE, V38, P209, DOI 10.1016/S0921-8181(03)00030-4
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   ul Hasson S, 2016, ATMOS RES, V180, P42, DOI 10.1016/j.atmosres.2016.05.008
   Wang F, 2020, FRONT EARTH SC-SWITZ, V8, DOI 10.3389/feart.2020.00014
   Wang SX, 2021, J HYDROL, V602, DOI 10.1016/j.jhydrol.2021.126778
   Wang W, 2017, GEOPHYS RES LETT, V44, P10378, DOI 10.1002/2017GL075037
   Warszawski L, 2014, P NATL ACAD SCI USA, V111, P3228, DOI 10.1073/pnas.1312330110
   Yang H, 2017, GEOPHYS RES LETT, V44, P5540, DOI 10.1002/2017GL073454
   Yun XB, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2021GL094243
   Yun XB, 2020, J HYDROL, V590, DOI 10.1016/j.jhydrol.2020.125472
NR 53
TC 1
Z9 1
U1 2
U2 8
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 2190-4979
EI 2190-4987
J9 EARTH SYST DYNAM
JI Earth Syst. Dynam.
PD JAN 29
PY 2024
VL 15
IS 1
BP 75
EP 90
DI 10.5194/esd-15-75-2024
PG 16
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA JL2A6
UT WOS:001173244400001
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Wang, Z
   Shi, PJ
   Zhang, Z
   Meng, YC
   Luan, YB
   Wang, JW
AF Wang, Zhu
   Shi, Peijun
   Zhang, Zhao
   Meng, Yongchang
   Luan, Yibo
   Wang, Jiwei
TI Separating out the influence of climatic trend, fluctuations, and
   extreme events on crop yield: a case study in Hunan Province, China
SO CLIMATE DYNAMICS
LA English
DT Article; Proceedings Paper
CT 13th East Asian Climate (EAC) International Workshop
CY MAR 24-25, 2016
CL Beijing, PEOPLES R CHINA
DE Climatic trend; Climatic fluctuations; Extreme events; Rice yield;
   Climate impact
ID RICE YIELDS; CHANGE IMPACTS; TEMPERATURE VARIABILITY; NIGHT TEMPERATURE;
   PADDY RICE; MODELS; CULTIVARS; SYSTEM; GROWTH
AB Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the fluctuation threshold which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented trade-offs among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.
C1 [Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.
   [Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei] Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China.
   [Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei] Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China.
C3 Beijing Normal University; Beijing Normal University; Beijing Normal
   University
RP Shi, PJ (corresponding author), Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.; Shi, PJ (corresponding author), Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China.; Shi, PJ (corresponding author), Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China.
EM spj@bnu.edu.cn
RI 张|Zhang, 朝|Zhao/AAF-8815-2019
OI Shi, Peijun/0000-0002-2968-7331
FU Foundation for Innovative Research Groups of the National Natural
   Science Foundation of China [41321001]; State Key Laboratory of Earth
   Surface Processes and Resource Ecology; Faculty of Geographical Science
   of Beijing Normal University
FX We are thankful for the comments of anonymous reviewers and the editors.
   This study was financially supported by the Foundation for Innovative
   Research Groups of the National Natural Science Foundation of China
   (Grant No. 41321001), the State Key Laboratory of Earth Surface
   Processes and Resource Ecology and the Faculty of Geographical Science
   of Beijing Normal University.
CR Aggarwal PK, 2002, CLIMATIC CHANGE, V52, P331, DOI 10.1023/A:1013714506779
   Akinbile CO, 2015, J WATER CLIM CHANGE, V6, P534, DOI 10.2166/wcc.2015.044
   Akinbile C. O., 2011, Trends in Applied Sciences Research, V6, P1127, DOI 10.3923/tasr.2011.1127.1140
   Amiri E, 2013, COMMUN SOIL SCI PLAN, V44, P1814, DOI 10.1080/00103624.2013.769565
   Angstrom A., 1924, Q J ROY METEOR SOC, V50, P121, DOI DOI 10.1002/QJ.49705021008
   [Anonymous], CHINESE J AGROMETEOR
   [Anonymous], 2014, IJNR
   [Anonymous], 2008, 219852008 GBT
   [Anonymous], 2015, China Statistical Yearbook
   [Anonymous], 2014, INTERGOVERNMENTAL PA, P151, DOI DOI 10.3167/147335304782369122
   [Anonymous], 2012, J GEOPHYS RES ATMOSP
   [Anonymous], 2008, Harmonized world soil database
   [Anonymous], 2012, 279592011 GBT
   [Anonymous], 2009, SL4242008 MIN WAT RE
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Auffhammer M, 2012, CLIMATIC CHANGE, V111, P411, DOI 10.1007/s10584-011-0208-4
   Bai HZ, 2016, CLIMATIC CHANGE, V135, P539, DOI 10.1007/s10584-015-1579-8
   Banerjee S, 2016, MITIG ADAPT STRAT GL, V21, P1
   China Meteorological Administration, 2012, DEFINITION CLASSIFIC
   Conradt S, 2012, 123 SEM FEBR 23 24 2, P23
   Deryng D, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034011
   Dinse K, 2009, MICHIGAN SEA GRANT
   FAOSTAT, 2015, CROPS DOWNL DAT RIC
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   [葛道阔 Ge Daokuo], 2002, [江苏农业学报, Journal of Agricultural Sciences], V18, P1
   Hansen J., 2011, CLIMATE CHANGE EVE 2, P1
   Hatfield JL, 2015, WEATHER CLIM EXTREME, V10, P4, DOI 10.1016/j.wace.2015.08.001
   Hollinger S E., 2009, Illinois Agronomy Handbook, P1
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Kim HY, 2013, GLOBAL CHANGE BIOL, V19, P548, DOI 10.1111/gcb.12047
   Kim M. K., 2009, Journal of Rural Development (Seoul), V32, P17
   Knox J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034032
   Kuwagata Tsuneo, 2011, Journal of Agricultural Meteorology, V67, P297, DOI 10.2480/agrmet.67.4.9
   Larson R., 2006, Elementary statistics, V3rd
   Lenton TM, 2011, NAT CLIM CHANGE, V1, P201, DOI [10.1038/NCLIMATE1143, 10.1038/NCLIMATE143]
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Li YM, 2016, J APPL METEOROL CLIM, V55, P1359, DOI 10.1175/JAMC-D-15-0213.1
   LILLIEFORS HW, 1967, J AM STAT ASSOC, V62, P399, DOI 10.2307/2283970
   Lin ED, 2005, PHILOS T R SOC B, V360, P2149, DOI 10.1098/rstb.2005.1743
   Liu ShengLi Liu ShengLi, 2015, Transactions of the Chinese Society of Agricultural Engineering, V31, P246
   Liu YP, 2014, ENVIRON MONIT ASSESS, V186, P8473, DOI 10.1007/s10661-014-4031-z
   LOAGUE K, 1991, Journal of Contaminant Hydrology, V7, P51, DOI 10.1016/0169-7722(91)90038-3
   Lobell DB, 2007, ENVIRON RES LETT, V2, DOI 10.1088/1748-9326/2/1/014002
   Lobell DB, 2007, AGR FOREST METEOROL, V145, P229, DOI 10.1016/j.agrformet.2007.05.002
   Lobell DB, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa518a
   Lobell DB, 2012, PLANT PHYSIOL, V160, P1686, DOI 10.1104/pp.112.208298
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Lobell DB, 2014, ENVIRON RES LETT, V9, P1
   Lu YQ, 2015, CLIM DYNAM, V45, P3347, DOI 10.1007/s00382-015-2543-z
   Luterbacher J, 2004, SCIENCE, V303, P1499, DOI 10.1126/science.1093877
   Maida Zahid Maida Zahid, 2011, Science International (Lahore), V23, P313
   Mann ME, 2013, GEOPHYS RES LETT, V31, P10
   Mann ME, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034716
   Mastrandrea MD, 2011, CLIMATIC CHANGE, V109, P43, DOI 10.1007/s10584-011-0311-6
   Meehl GA, 2007, CLIMATE CHANGE 2007, P533
   Muller C, 2010, CLIMATE CHANGE IMPAC, V11, P1996
   Nelson GC, 2009, Climate change: Impact on Agriculture and costs of Adaptation, V21, DOI DOI 10.2499/0896295354
   Peng SB, 2004, P NATL ACAD SCI USA, V101, P9971, DOI 10.1073/pnas.0403720101
   Potts R, 2015, J HUM EVOL, V87, P5, DOI 10.1016/j.jhevol.2015.06.014
   Prescott J.A., 1940, T FROYAL SOC, V64, P114, DOI DOI 10.1155/2013/168048
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Qin D., 2015, China national assessment report on risk management and adaptation of climate extremes and disasters
   Ray DK, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms6989
   Rinaldi M, 2003, AGR SYST, V78, P17, DOI 10.1016/S0308-521X(03)00030-1
   ROSENZWEIG C, 1994, NATURE, V367, P133, DOI 10.1038/367133a0
   Roudier P, 2011, GLOBAL ENVIRON CHANG, V21, P1073, DOI 10.1016/j.gloenvcha.2011.04.007
   Russill C, 2009, GLOBAL ENVIRON CHANG, V19, P336, DOI 10.1016/j.gloenvcha.2009.04.001
   Sapkota S., 2011, J SCI TECHNOL, V11, P57
   Sarker MAR, 2012, AGR SYST, V112, P11, DOI 10.1016/j.agsy.2012.06.004
   Shi PJ, 2014, SCI CHINA EARTH SCI, V57, P2676, DOI 10.1007/s11430-014-4889-1
   Shuai JB, 2013, REG ENVIRON CHANGE, V13, P287, DOI 10.1007/s10113-012-0332-3
   Tao FL, 2013, GLOBAL CHANGE BIOL, V19, P3200, DOI 10.1111/gcb.12250
   Tao FL, 2008, CLIM RES, V38, P83, DOI 10.3354/cr00771
   Teixeira EI, 2013, AGR FOREST METEOROL, V170, P206, DOI 10.1016/j.agrformet.2011.09.002
   The World Bank, 2013, TURN HEAT CLIM EXTR, P346
   Tiamiyu SA, 2015, INT LETT NAT SCI, V49, P63, DOI 10.18052/www.scipress.com/ILNS.49.63
   Tian J.-R., 1994, Hybrid Rice Technology: New Developments and Future Prospects, P115
   Timsina J., 2006, International Journal of Agricultural Research, V1, P202
   Timsina J, 2006, AGR SYST, V90, P5, DOI 10.1016/j.agsy.2005.11.007
   VIJAYALAKSHMI C, 1991, J AGRON CROP SCI, V167, P184, DOI 10.1111/j.1439-037X.1991.tb00952.x
   Wang P, 2014, CLIMATIC CHANGE, V124, P777, DOI 10.1007/s10584-014-1136-x
   Wang Z, 2016, STOCH ENV RES RISK A, V30, P2019, DOI 10.1007/s00477-016-1215-9
   Wassmann R, 2009, ADV AGRON, V102, P91, DOI 10.1016/S0065-2113(09)01003-7
   Wheeler TR, 2000, AGR ECOSYST ENVIRON, V82, P159, DOI 10.1016/S0167-8809(00)00224-3
   Wu WX, 2014, CROP PASTURE SCI, V65, P1267, DOI 10.1071/CP14009
   Xiao FJ, 2011, NAT HAZARDS, V58, P1333, DOI 10.1007/s11069-011-9735-6
   Xu CC, 2017, MITIG ADAPT STRAT GL, V22, P565, DOI 10.1007/s11027-015-9688-2
   Yao FM, 2007, CLIMATIC CHANGE, V80, P395, DOI 10.1007/s10584-006-9122-6
   Yi W, 1995, HYBRID RICE, V3, P1
   Yin XY, 1996, ANN BOT-LONDON, V77, P203, DOI 10.1006/anbo.1996.0024
   Zhang H, 2016, FRONT EARTH SCI-PRC, V10, P315, DOI 10.1007/s11707-015-0527-2
   Zhang Z, 2016, THEOR APPL CLIMATOL, V123, P291, DOI 10.1007/s00704-014-1343-4
   Zhao C, 2017, NAT PLANTS, V3, DOI 10.1038/nplants.2016.202
   Zhou MZ, 2013, CLIM DYNAM, V41, P3317, DOI 10.1007/s00382-012-1597-4
NR 94
TC 16
Z9 20
U1 6
U2 91
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0930-7575
EI 1432-0894
J9 CLIM DYNAM
JI Clim. Dyn.
PD DEC
PY 2018
VL 51
IS 11-12
SI SI
BP 4469
EP 4487
DI 10.1007/s00382-017-3831-6
PG 19
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Meteorology & Atmospheric Sciences
GA HC3TN
UT WOS:000451725600033
DA 2025-01-10
ER

PT J
AU M'mboroki, KG
   Wandiga, S
   Oriaso, SO
AF M'mboroki, Kiambi Gilbert
   Wandiga, Shem
   Oriaso, Silas Odongo
TI Climate change impacts detection in dry forested ecosystem as indicated
   by vegetation cover change in -Laikipia, of Kenya
SO ENVIRONMENTAL MONITORING AND ASSESSMENT
LA English
DT Article
DE Detection; Climate change adaptations; Impacts; Dry forested ecosystem;
   Land use; Vegetation cover; Yaaku
ID AGRICULTURE; ADAPTATION; AFRICA
AB The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grass-lands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 degrees C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.
C1 [M'mboroki, Kiambi Gilbert] Minist Agr Livestock Dev & Fisheries, State Dept Livestock, Nairobi, Kenya.
   [Wandiga, Shem; Oriaso, Silas Odongo] Univ Nairobi, Inst Climate Change & Adaptat, Nairobi, Kenya.
C3 University of Nairobi
RP M'mboroki, KG (corresponding author), Minist Agr Livestock Dev & Fisheries, State Dept Livestock, Nairobi, Kenya.
EM mborokikiambi@yahoo.com; wandigas@uonbi.ac.ke; soriazzo@gmail.com
FU Regional Pastoral Livelihood Resilience Project-Kenya
FX The funding on transport and logistics was from Regional Pastoral
   Livelihood Resilience Project-Kenya.
CR [Anonymous], 2017, COUNTY GOVT LAIKIPIA
   [Anonymous], 2011, TECHNICAL BRIEF COMM
   Ayuyo I.O., 2014, INT J SCI REIJSR, V3
   Baldyga Tracy J., 2005, ENHANCED LAND COVER
   Borg W., 2003, Educational research: An introduction
   CARE International, 2015, RES RANG CHANG CHALL
   IIRR Cordaid, 2013, BUILD RES COMM TRAIN
   International Fund for Agricultural Development (IFAD), 2012, Country Technical Note on Indigenous Peoples' Issues: Lao People's Democratic Republic
   Kathuri N.J., 1993, Introduction to education research
   Kuldeep T., 2011, INT J GEOMATICS GEOS, V2
   Laikipia County Government (LCG), 2013, 1 COUNT DEV INT DEV
   Müller C, 2011, P NATL ACAD SCI USA, V108, P4313, DOI 10.1073/pnas.1015078108
   Mugenda OM., 1999, RES METHODS QUANTITA
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Noam L., 1999, Fundamentals of Remote Sensing
   Orville B. J., 1996, PEOPLE CULTURE DOROB
   Sarr B, 2012, ATMOS SCI LETT, V13, P108, DOI 10.1002/asl.368
   Shiraz O.S., 2014, THESIS
   Shunlin L., 2008, ADV LAND REMOTE SENS
   SINGH A, 1989, INT J REMOTE SENS, V10, P989, DOI 10.1080/01431168908903939
   Songok C.K., 2011, INTEGRATION INDIGENO
   Thomas DSG, 2007, CLIMATIC CHANGE, V83, P301, DOI 10.1007/s10584-006-9205-4
NR 22
TC 14
Z9 15
U1 3
U2 28
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0167-6369
EI 1573-2959
J9 ENVIRON MONIT ASSESS
JI Environ. Monit. Assess.
PD APR
PY 2018
VL 190
IS 4
AR 255
DI 10.1007/s10661-018-6630-6
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA GB4TS
UT WOS:000429054600078
PM 29594685
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Rumsey, M
   Fletcher, SM
   Thiessen, J
   Gero, A
   Kuruppu, N
   Daly, J
   Buchan, J
   Willetts, J
AF Rumsey, Michele
   Fletcher, Stephanie M.
   Thiessen, Jodi
   Gero, Anna
   Kuruppu, Natasha
   Daly, John
   Buchan, James
   Willetts, Juliet
TI A qualitative examination of the health workforce needs during climate
   change disaster response in Pacific Island Countries
SO HUMAN RESOURCES FOR HEALTH
LA English
DT Article
DE Climate change; Health workforce governance; Health-care management;
   Health-care capacity; Competencies; Human resources for health;
   Workforce development; Emergency; Disaster response; Pacific Islands
ID PREPAREDNESS; CHALLENGES; RESILIENCE; GOVERNANCE
AB Background: There is a growing body of evidence that the impacts of climate change are affecting population health negatively. The Pacific region is particularly vulnerable to climate change; a strong health-care system is required to respond during times of disaster. This paper examines the capacity of the health sector in Pacific Island Countries to adapt to changing disaster response needs, in terms of: (i) health workforce governance, management, policy and involvement; (ii) health-care capacity and skills; and (iii) human resources for health training and workforce development.
   Methods: Key stakeholder interviews informed the assessment of the capacity of the health sector and disaster response organizations in Pacific Island Countries to adapt to disaster response needs under a changing climate. The research specifically drew upon and examined the adaptive capacity of individual organizations and the broader system of disaster response in four case study countries (Fiji, Cook Islands, Vanuatu and Samoa).
   Results: 'Capacity' including health-care capacity was one of the objective determinants identified as most significant in influencing the adaptive capacity of disaster response systems in the Pacific. The research identified several elements that could support the adaptive capacity of the health sector such as: inclusive involvement in disaster coordination; policies in place for health workforce coordination; belief in their abilities; and strong donor support. Factors constraining adaptive capacity included: weak coordination of international health personnel; lack of policies to address health worker welfare; limited human resources and material resources; shortages of personnel to deal with psychosocial needs; inadequate skills in field triage and counselling; and limited capacity for training.
   Conclusion: Findings from this study can be used to inform the development of human resources for health policies and strategic plans, and to support the development of a coordinated and collaborative approach to disaster response training across the Pacific and other developing contexts. This study also provides an overview of health-care capacity and some of the challenges and strengths that can inform future development work by humanitarian organizations, regional and international donors involved in climate change adaptation, and disaster risk reduction in the Pacific region.
C1 [Rumsey, Michele; Fletcher, Stephanie M.; Thiessen, Jodi; Daly, John; Buchan, James] Univ Technol Sydney, World Hlth Org WHO Collaborating Ctr Nursing Midw, Sydney, NSW 2007, Australia.
   [Gero, Anna; Kuruppu, Natasha; Willetts, Juliet] Univ Technol Sydney, Inst Sustainable Futures, Sydney, NSW 2007, Australia.
C3 University of Technology Sydney; World Health Organization; University
   of Technology Sydney
RP Rumsey, M (corresponding author), Univ Technol Sydney, World Hlth Org WHO Collaborating Ctr Nursing Midw, POB 123,Broadway, Sydney, NSW 2007, Australia.
EM Michele.Rumsey@uts.edu.au
RI Fletcher-Lartey, Stephanie/E-1079-2011; Daly, John/G-2012-2017
OI Fletcher, Stephanie/0000-0002-8897-2351; Gero, Anna/0000-0001-7047-4250;
   , natasha/0000-0001-9018-826X; Willetts, Juliet/0000-0002-3975-9642;
   Thiessen, Jodi/0000-0001-7364-5940
CR Aitken P., 2012, Emerging Health Threats Journal, V5, P18147
   [Anonymous], 2020, Building Capacity on Climate Change and Human Health
   [Anonymous], 2001, IMP AD VULN CONTR WO
   [Anonymous], HUM RES HLTH ACT FRA
   [Anonymous], 2007, 7 M MINISTERS HLTH P
   [Anonymous], 2010, 6 CARB NEUTR COMM
   [Anonymous], 2010, World Development Report 2010: Development and Climate Change
   [Anonymous], 2006, Working Together for Health, The World Health Report, DOI WHO/HTM/MAL/2006.1112
   Anstey MHR, 2013, GLOBALIZATION HEALTH, V9, DOI 10.1186/1744-8603-9-4
   Asia Pacific Emergency Disaster Nursing Network, 2010, SYST WID QUAL IMPR F
   Atkinson RL, 2001, INT J OBESITY, V25, P1, DOI 10.1038/sj.ijo.0801574
   Bar-Dayan Y., 2008, PREHOSP DISASTER MED, V23, P280
   Biermann F, 2007, GLOBAL ENVIRON CHANG, V17, P326, DOI 10.1016/j.gloenvcha.2006.11.010
   Bissell RA, 2004, FAM COMMUNITY HEALTH, V27, P193, DOI 10.1097/00003727-200407000-00006
   Bowen KJ, 2012, INT J ENV RES PUB HE, V9, P55, DOI 10.3390/ijerph9010055
   Bremer Rannveig, 2003, Prehosp Disaster Med, V18, P372
   Brooks N., 2005, ASSESSING ENHANCING
   Buchan J., 2011, Recruiting and retaining health workers in remote areas: Pacific Island case-studies
   Buchan J, 2010, HUM RESOUR HEALTH, V8, DOI 10.1186/1478-4491-8-29
   Challen K, 2012, BMC PUBLIC HEALTH, V12, DOI 10.1186/1471-2458-12-542
   CHARMAZ K, 1990, SOC SCI MED, V30, P1161, DOI 10.1016/0277-9536(90)90256-R
   Coumou D, 2012, NAT CLIM CHANGE, V2, P491, DOI 10.1038/NCLIMATE1452
   Davidson JRT, 2006, J CLIN PSYCHIAT, V67, P9
   Doyle J, 2011, HUMAN RESOURCES HLTH
   Dussault G., 2010, Assessing future health workforce needs
   Dussault Gilles, 2006, Hum Resour Health, V4, P12, DOI 10.1186/1478-4491-4-12
   Ekström M, 2013, GLOBAL ENVIRON CHANG, V23, P115, DOI 10.1016/j.gloenvcha.2012.11.003
   Food and Agricultural Organisation [FAO], 2008, DIS RISK MAN SYST AN
   Gero A, 2013, UNDERSTANDING PACIFI
   Gillespie BM, 2007, J ADV NURS, V59, P427, DOI 10.1111/j.1365-2648.2007.04340.x
   Greet N, 2008, SECUR CHALL, V4, P45
   Griffiths K., 2013, PACIFIC HUMANITARIAN
   Hansen E.C., 2006, Successful qualitative health research: a practical introduction
   Hanvoravongchai P, 2010, BMC PUBLIC HEALTH, V10, DOI 10.1186/1471-2458-10-322
   International Federation of Red Cross and Red Crescent Societies, 2012, COOK ISL INT DIS RES
   International Federation of Red Cross and Red Crescent Societies, 2010, LEG PREP INT DIS RES
   Jones L, 2010, RESPONDING CHANGING
   Kabene Stefane M, 2006, Hum Resour Health, V4, P20, DOI 10.1186/1478-4491-4-20
   Kaplan AD, 2013, HUM RESOUR HEALTH, V11, DOI 10.1186/1478-4491-11-6
   Kelman I., 2009, ECOL ENVIRON ANTHROP, V5
   Knutson TR, 2010, NAT GEOSCI, V3, P157, DOI 10.1038/NGEO779
   Kuruppu N, 2011, GLOBAL ENVIRON CHANG, V21, P657, DOI 10.1016/j.gloenvcha.2010.12.002
   Lim B., 2005, Adaptation policy frameworks for climate change: Developing strategies, policies and measures
   Maclellan Nic, 2011, TURNING TIDE IMPROVI
   McManus S., 2008, Natural Hazards Review, V9, P81, DOI [10.1061/(ASCE)1527-6988(2008)9:2(81), DOI 10.1061/(ASCE)1527-6988(2008)9:2(81)]
   McManus S., 2007, Resilience Management: A Framework for Assessing and Improving the Resilience of Organisations
   Mowafi H, 2007, PREHOSPITAL DISASTER, V22, P351, DOI 10.1017/S1049023X00005057
   Nelson CD, 2008, DISASTER MED PUBLIC, V2, P247, DOI 10.1097/DMP.0b013e31818d84ea
   Norris FH, 2002, PSYCHIATRY, V65, P240, DOI 10.1521/psyc.65.3.240.20169
   Rice P., 1999, QUALITATIVE RES METH
   Robertson AG, 2005, MED J AUSTRALIA, V182, P340, DOI 10.5694/j.1326-5377.2005.tb06732.x
   Tangi T, 2009, DISASTER RISK MANAGE, P17
   Thompson L, 2011, PUBLIC HLTH EMERGENC
   United Nations Development Programme, 2009, CLIM CHANG THREAT HU
   United Nations Development Programme, 2011, SUST EQ BETT FUT ALL
   Urbano M., 2010, CLIMATE CHANGE CHILD
   Walker B, 2004, ECOL SOC, V9
   WHO/SEARO, 2007, CLIM CHANG HUM HLTH
NR 58
TC 19
Z9 21
U1 1
U2 49
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
EI 1478-4491
J9 HUM RESOUR HEALTH
JI Hum. Resour. Health
PD FEB 12
PY 2014
VL 12
AR 9
DI 10.1186/1478-4491-12-9
PG 11
WC Health Policy & Services; Industrial Relations & Labor
WE Social Science Citation Index (SSCI)
SC Health Care Sciences & Services; Business & Economics
GA AD0SP
UT WOS:000332944700001
PM 24521057
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Ramírez-Ojeda, G
   Rodríguez-Pérez, JE
   Rodríguez-Guzmán, E
   Sahagún-Castellanos, J
   Chávez-Servia, JL
   Peralta, IE
   Barrera-Guzmán, LA
AF Ramirez-Ojeda, Gabriela
   Enrique Rodriguez-Perez, Juan
   Rodriguez-Guzman, Eduardo
   Sahagun-Castellanos, Jaime
   Luis Chavez-Servia, Jose
   Peralta, Iris E.
   Angel Barrera-Guzman, Luis
TI Distribution and Climatic Adaptation of Wild Tomato (<i>Solanum
   lycopersicum</i> L.) Populations in Mexico
SO PLANTS-BASEL
LA English
DT Article
DE climatic diversity; wild tomatoes; climatic adaptation; Solanum
   lycopersicum
ID ECOLOGICAL DESCRIPTORS; R-PACKAGE; CULTIVATED TOMATO; NATIVE TOMATOES;
   COLLECTIONS; GERMPLASM; QUALITY; ORIGIN
AB Tomato (Solanum lycopersicum L.) is a vegetable with worldwide importance. Its wild or close related species are reservoirs of genes with potential use for the generation of varieties tolerant or resistant to specific biotic and abiotic factors. The objective was to determine the geographic distribution, ecological descriptors, and patterns of diversity and adaptation of 1296 accessions of native tomato from Mexico. An environmental information system was created with 21 climatic variables with a 1 km(2) spatial resolution. Using multivariate techniques (Principal Component Analysis, PCA; Cluster Analysis, CA) and Geographic Information Systems (GIS), the most relevant variables for accession distribution were identified, as well as the groups formed according to the environmental similarity among these. PCA determined that with the first three PCs (Principal Components), it is possible to explain 84.1% of the total variation. The most relevant information corresponded to seasonal variables of temperature and precipitation. CA revealed five statistically significant clusters. Ecological descriptors were determined and described by classifying accessions in Physiographic Provinces. Temperate climates were the most frequent among tomato accessions. Finally, the potential distribution was determined with the Maxent model with 10 replicates by cross-validation, identifying areas with a high probability of tomato presence. These results constitute a reliable source of useful information for planning accession sites collection and identifying accessions that are vulnerable or susceptible to conservation programs.
C1 [Ramirez-Ojeda, Gabriela] Inst Nacl Invest Forestales Agr & Pecuarias INIFA, Campo Expt Ctr Altos Jalisco, Tepatitlan De Morelos 47600, Mexico.
   [Enrique Rodriguez-Perez, Juan; Sahagun-Castellanos, Jaime] Univ Autonoma Chapingo UACh, Dept Fitotecnia, Chapingo 56230, Mexico.
   [Rodriguez-Guzman, Eduardo] Univ Guadalajara UdG, Ctr Univ Ciencias Biol & Agr, Zapopan 45200, Mexico.
   [Luis Chavez-Servia, Jose] Inst Politecn Nacl IPN, CIIDIR Oaxaca, Xoxocotlan 71230, Oaxaca, Mexico.
   [Peralta, Iris E.] Univ Nacl Cuyo UNCUYO, Fac Ciencias Agr, M5502JMA, Mendoza, Argentina.
   [Peralta, Iris E.] Consejo Nacl Invest Cient & Tecn, Inst Argentino Invest Zonas Aridas, Ctr Cient Tecnol, C1425FQB, Mendoza, Argentina.
   [Angel Barrera-Guzman, Luis] Univ Valle Puebla UVP, Coordinac Educ & Invest, Puebla 72440, Mexico.
C3 University Nacional Cuyo Mendoza; Consejo Nacional de Investigaciones
   Cientificas y Tecnicas (CONICET)
RP Rodríguez-Pérez, JE (corresponding author), Univ Autonoma Chapingo UACh, Dept Fitotecnia, Chapingo 56230, Mexico.
EM gabramirezo@gmail.com; erodriguezx@yahoo.com.mx; edrg@hotmail.com;
   jsahagunc@yahoo.com.mx; jchavers@ipn.mx; iperalta@fca.uncu.edu.ar;
   ptc.investigacion3@uvp.mx
RI Ramírez Ojeda, Gabriela/GPK-6113-2022; Barrera-Guzmán, Luis
   Ángel/AEK-3979-2022; Guzmán, Eduardo/T-9496-2019; CASTELLANOS,
   JAIME/P-7001-2015; Rodríguez-Pérez, Juan/GQH-0051-2022; Rodriguez-Perez,
   Juan Enrique/C-7972-2014
OI Rodriguez Guzman, Eduardo/0000-0002-4640-7610; Barrera Guzman, Luis
   Angel/0000-0001-8057-2583; RAMIREZ OJEDA, GABRIELA/0000-0001-9679-6514;
   Rodriguez-Perez, Juan Enrique/0000-0002-5841-0083
FU Universidad Autonoma Chapingo [D.G.I.P. 20001-C66]
FX This research received funding from Universidad Autonoma Chapingo
   through project: D.G.I.P. 20001-C66.
CR [Anonymous], MAXENT SOFTWARE MODE
   [Anonymous], 2009, User's Guide, V2nd
   [Anonymous], 2007, Adaptation to climate change in agriculture, forestry and fisheries: Perspective, framework and priorities
   [Anonymous], 2005, FESTSCHRIFT WILLIAM
   Flores-Hernández Luis Antonio, 2018, Rev. Chapingo Ser.Hortic, V24, P85, DOI 10.5154/r.rchsh.2017.08.030
   Arellano Rodríguez Luis Javier, 2013, Rev. Mex. Cienc. Agríc, V4, P753
   Ávila Coria Rosaura, 2014, Rev. mex. de cienc. forestales, V5, P92
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Bao BL, 2007, ASIA PAC J CLIN NUTR, V16, P122
   Blanca J, 2015, BMC GENOMICS, V16, DOI 10.1186/s12864-015-1444-1
   Blanca J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0048198
   Bonilla-Barrientos O, 2014, REV FITOTEC MEX, V37, P129
   Brock G, 2008, J STAT SOFTW, V25, P1, DOI 10.18637/jss.v025.i04
   Cerda-Hurtado IM, 2018, ECOL EVOL, V8, P6492, DOI 10.1002/ece3.4106
   Cervantes-Moreno Raquel, 2014, Rev. Chapingo Ser.Hortic, V20, P05, DOI 10.5154/r.rchsh.2012.12.071
   Charrad M, 2014, J STAT SOFTW, V61, P1
   Chavez-Servia J.L., 2011, J INT AM SOC TROP AG, V54, P151
   Comision Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), 2016, PROV BIOG MEX ESC 1
   Crisanto-Juarez A., 2010, M XICO REV FITOTEC M, V33, P7
   Velasco-Alvarado MD, 2017, CHIL J AGR RES, V77, P187, DOI 10.4067/S0718-58392017000300187
   Délices G, 2019, REV BIOL TROP, V67, P1023, DOI 10.15517/RBT.V67I4.33754
   Elith J, 2011, DIVERS DISTRIB, V17, P43, DOI 10.1111/j.1472-4642.2010.00725.x
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Flores-Hernández LA, 2017, REV FITOTEC MEX, V40, P83
   Fourcade Y, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0097122
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Gollin D, 2020, FOOD SECUR, V12, P919, DOI 10.1007/s12571-020-01035-w
   HANLEY JA, 1982, RADIOLOGY, V143, P29, DOI 10.1148/radiology.143.1.7063747
   Hijmans RJ, 2001, AM J BOT, V88, P2101, DOI 10.2307/3558435
   Juárez-López P., 2009, Rev. Chapingo Ser.Hortic, V15, P5
   Kassambara A., 2017, Machine Learning Essential: Practical guide in R: Edition 1
   Ladizinsky Gideon., 1998, PLANT EVOLUTION DOME
   Le S, 2008, J STAT SOFTW, V25, P1, DOI 10.18637/jss.v025.i01
   MALDoNADo-PERALTA R., 2016, Agroproductividad, V9, P68
   Magallanes-López AM, 2020, AGROCIENCIA-MEXICO, V54, P779
   Maria-Montes IM, 2019, AGROCIENCIA-MEXICO, V53, P355
   Metz B, 2007, AR4 CLIMATE CHANGE 2007: MITIGATION OF CLIMATE CHANGE, P1
   Moyle LC, 2008, EVOLUTION, V62, P2995, DOI 10.1111/j.1558-5646.2008.00487.x
   Muller C. H., 1940, Miscellaneous Publications. United States Department of Agriculture
   Nee M, 1986, SOLANACEAE FL VERACR
   Pacheco-Triste I.A., 2014, Rev. Mex. Agroecosist, V1, P28
   Peralta I. E., 2008, Systematic Botany Monographs, V84
   Perrino EV, 2022, BIOLOGY-BASEL, V11, DOI 10.3390/biology11020193
   Perrino EV, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13041682
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Ramirez-Ojeda G., 2014, Revista Mexicana de Ciencias Agricolas, V5, P1885
   Ramirez-Ojeda G, 2021, FRONT GENET, V12, DOI 10.3389/fgene.2021.748979
   Ramírez-Ojeda G, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10050855
   Razifard H, 2020, MOL BIOL EVOL, V37, P1118, DOI 10.1093/molbev/msz297
   REMIB (Red Mundial de Informacion sobre Biodiversidad), COM NAC CON US BIOD
   RICK CM, 1975, B TORREY BOT CLUB, V102, P376, DOI 10.2307/2484764
   RODRIGUEZ-GUZMAN Eduardo, 2009, Naturaleza y Desarrollo, V7, P45
   Rosete F., 2003, GAC ECOL GICA, V68, P43
   Corral JAR, 2008, CROP SCI, V48, P1502, DOI 10.2135/cropsci2007.09.0518
   González JDS, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0192676
   Soberón J, 2011, REV MEX BIODIVERS, V82, P1348
   Spooner DM, 2010, AM J BOT, V97, P2049, DOI 10.3732/ajb.1000277
   Steiner JJ, 1996, CROP SCI, V36, P439, DOI 10.2135/cropsci1996.0011183X003600020037x
   Thomas DR, 2014, MULTIVAR BEHAV RES, V49, P329, DOI 10.1080/00273171.2014.905766
   Trabucco A., 2019, **DATA OBJECT**, DOI 10.6084/m9.figshare.7707605.v3
   Vela-Hinojosa C, 2019, J AM SOC HORTIC SCI, V144, P45, DOI [10.21273/JASHS04525-18, 10.21273/jashs04525-18]
   Vela-Hinojosa C, 2018, NOT BOT HORTI AGROBO, V46, P45, DOI 10.15835/nbha46111001
   Veláquez A, 2001, ENVIRON MANAGE, V27, P655
   Wright Kevin, 2023, CRAN
   Zamir D, 2001, NAT REV GENET, V2, P983, DOI 10.1038/35103590
NR 66
TC 4
Z9 4
U1 1
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 2223-7747
J9 PLANTS-BASEL
JI Plants-Basel
PD AUG
PY 2022
VL 11
IS 15
AR 2007
DI 10.3390/plants11152007
PG 17
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 3R8AE
UT WOS:000839128000001
PM 35956486
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Storbjörk, S
   Hjerpe, M
AF Storbjork, Sofie
   Hjerpe, Mattias
TI Stuck in experimentation: exploring practical experiences and challenges
   of using floating housing to climate-proof waterfront urban development
   in Sweden
SO JOURNAL OF HOUSING AND THE BUILT ENVIRONMENT
LA English
DT Article
DE Climate adaptation; Climate-proofing; Cities; Waterfront development;
   Urban climate experimentation; Floating housing
ID ADAPTATION; MANAGEMENT; CITY; INNOVATION; IMPACTS; CITIES; DESIGN;
   ENERGY
AB With climate change already underway, cities are looking for ways to deal with its effects. To balance urban waterfront development and climate adaptation, floating housing is presented as a promising solution-however it has not been studied sufficiently. This paper explores floating housing as urban climate experimentation, targeting vision/motivation, practice and upscaling in a national context where support mechanisms and traditions are absent. Interviews with innovation entrepreneurs and municipal planners involved with planning and building floating districts show that, with one exception, the Swedish initiatives are at odds with the theoretical assumptions behind urban climate experimentation. Initiatives are neither challenge-led in terms of climate risk nor inclusive and community-based. Rather, the small-scale private entrepreneurs are pioneers in offering unique living on water as one-off innovations. While allowing experimentation, municipal planners are less convinced by the effectiveness and appropriateness of upscaling. Floating housing may contribute to local identity building and place marketing, but are riddled with implementation challenges regarding shoreline protection, privatization/accessibility, limited market interest and urban development fit. While the floating houses themselves withstand flooding, thus safeguarding individual house owners, they do not protect the land-based city with its vulnerable waterfront development patterns. Results thus suggest the limitation of floating houses in shifting development pathways and strengthening urban climate proofing.
C1 [Storbjork, Sofie; Hjerpe, Mattias] Linkoping Univ, Ctr Climate Sci & Policy Res, Dept Themat Studies Environm Change, Linkoping, Sweden.
C3 Linkoping University
RP Storbjörk, S (corresponding author), Linkoping Univ, Ctr Climate Sci & Policy Res, Dept Themat Studies Environm Change, Linkoping, Sweden.
EM sofie.storbjork@liu.se
OI Storbjork, Sofie/0000-0003-0109-2288; Hjerpe,
   Mattias/0000-0002-5500-3300
FU Linkoping University; Swedish research council Formas [942-2015-356]
FX Open access funding provided by Linkoping University. This study was
   funded by the Swedish research council Formas project The role of urban
   experiments in triggering climate transitions, EXPECT (Grant number
   942-2015-356).
CR Ambica A., 2015, INDIAN J SCI TECHNOL, V8, P1, DOI [10.17485/ijst/2015/v8i32/84304, DOI 10.17485/IJST/2015/V8I32/84304]
   Baxter J, 1997, T I BRIT GEOGR, V22, P505, DOI 10.1111/j.0020-2754.1997.00505.x
   Boyd E, 2015, URBAN STUD, V52, P1234, DOI 10.1177/0042098014527483
   Bulkeley H, 2015, URBAN POLITICS OF CLIMATE CHANGE: EXPERIMENTATION AND THE GOVERNING OF SOCIO-TECHNICAL TRANSITIONS, P1
   Bulkeley H, 2013, T I BRIT GEOGR, V38, P361, DOI 10.1111/j.1475-5661.2012.00535.x
   Bulkeley H, 2013, ENVIRON POLIT, V22, P136, DOI 10.1080/09644016.2013.755797
   Burch S, 2014, CLIM POLICY, V14, P467, DOI 10.1080/14693062.2014.876342
   Caprotti F, 2017, URBAN GEOGR, V38, P1441, DOI 10.1080/02723638.2016.1265870
   De Graaf, 2012, ADAPTIVE URBAN DEV S
   De Graf, 2009, THESIS TU DELFT
   Dyckman CS, 2014, OCEAN COAST MANAGE, V102, P212, DOI 10.1016/j.ocecoaman.2014.09.010
   El-Shihy AA, 2019, ALEX ENG J, V58, P507, DOI 10.1016/j.aej.2019.05.003
   Evans J, 2016, ROUT RES SUSTAIN URB, P1
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Francesch-Huidobro M, 2017, PROG PLANN, V114, P1, DOI 10.1016/j.progress.2015.11.001
   Granberg M, 2016, RISK MANAG-UK, V18, P26, DOI 10.1057/rm.2015.21
   Harvey N, 2018, OCEAN COAST MANAGE, V157, P237, DOI 10.1016/j.ocecoaman.2018.03.007
   Huang-Lachmann JT, 2016, CITIES, V54, P36, DOI 10.1016/j.cities.2015.11.001
   ICE, 2010, FAC RIS SEA LEV RETR
   Jeuken A, 2015, J WATER CLIM CHANGE, V6, P711, DOI 10.2166/wcc.2014.141
   Kaji-OGrady S., 2005, J Archit, V10, P443, DOI [DOI 10.1080/13602360500285641, 10.1080/13602360500285641]
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Kim T, 2012, STRUCT ENG INT, V22, P57, DOI 10.2749/101686612X13216060213077
   Kivimaa P, 2017, J CLEAN PROD, V169, P17, DOI 10.1016/j.jclepro.2017.01.027
   Kvale S., 1997, KVALITATIVA FORSKNIN
   Lin YH, 2019, MAR GEORESOUR GEOTEC, V37, P880, DOI 10.1080/1064119X.2018.1503761
   Lu PW, 2013, CITIES, V35, P200, DOI 10.1016/j.cities.2013.06.001
   Madsen SHJ, 2019, EUR PLAN STUD, V27, P282, DOI 10.1080/09654313.2017.1421907
   Markard J, 2012, RES POLICY, V41, P955, DOI 10.1016/j.respol.2012.02.013
   Marvin S, 2016, ROUT RES SUSTAIN URB, P47
   Moon, 2014, INT J SUSTAINABLE BU, V5, P125
   Moon Chang-Ho, 2015, [JOURNAL OF THE KOREAN HOUSING ASSOCIATION, 한국주거학회논문집], V26, P97, DOI 10.6107/JKHA.2015.26.5.097
   Naber R, 2017, ENERG POLICY, V110, P342, DOI 10.1016/j.enpol.2017.07.056
   Nicholls RJ, 2011, OCEANOGRAPHY, V24, P144, DOI 10.5670/oceanog.2011.34
   O'Shaughnessy KA, 2020, URBAN ECOSYST, V23, P431, DOI 10.1007/s11252-019-00924-z
   Penning-Rowsell E, 2020, LANDSCAPE RES, V45, P395, DOI 10.1080/01426397.2019.1694881
   Rulleau B, 2017, ENVIRON SCI POLICY, V72, P12, DOI 10.1016/j.envsci.2017.01.009
   Ryghaug M, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11205771
   Schot J, 2008, TECHNOL ANAL STRATEG, V20, P537, DOI 10.1080/09537320802292651
   Sengers F, 2019, TECHNOL FORECAST SOC, V145, P153, DOI 10.1016/j.techfore.2016.08.031
   Sengers F, 2016, ROUT RES SUSTAIN URB, P15
   Silverman D., 2001, Interpreting qualitative data
   Storbjörk S, 2021, OCEAN COAST MANAGE, V210, DOI 10.1016/j.ocecoaman.2021.105732
   Storbjörk S, 2015, REG ENVIRON CHANGE, V15, P1133, DOI 10.1007/s10113-014-0690-0
   Storbjörk S, 2014, EUR PLAN STUD, V22, P2268, DOI 10.1080/09654313.2013.830697
   Strangfeld P., 2014, WIT T ECOLOGY ENV, V184, P277, DOI DOI 10.2495/FRIAR140231
   van Doren D, 2018, URBAN STUD, V55, P175, DOI 10.1177/0042098016640456
   van Winden W, 2017, J URBAN TECHNOL, V24, P51, DOI 10.1080/10630732.2017.1348884
NR 48
TC 3
Z9 3
U1 1
U2 17
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1566-4910
EI 1573-7772
J9 J HOUS BUILT ENVIRON
JI J. Hous. Built Environ.
PD DEC
PY 2022
VL 37
IS 4
BP 2263
EP 2284
DI 10.1007/s10901-022-09942-4
EA APR 2022
PG 22
WC Environmental Studies; Regional & Urban Planning; Urban Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration; Urban Studies
GA 6I4ZQ
UT WOS:000782704300001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Klemm, W
   Lenzholzer, S
   van den Brink, A
AF Klemm, Wiebke
   Lenzholzer, Sanda
   van den Brink, Adri
TI Developing green infrastructure design guidelines for urban climate
   adaptation
SO JOURNAL OF LANDSCAPE ARCHITECTURE
LA English
DT Article
DE Climate-responsive design; Urban green space; Thermal comfort; Research
   through Design; Participatory approach
AB In the context of global warming and increasing urban climate problems, urban green spaces and elements have been recognized as a strategy for urban climate adaptation. Yet, despite increasing scientific evidence of the positive impacts that urban green infrastructure (UGI) is having on the urban microclimate, this evidence is not being incorporated into urban design practice. This explorative study was executed to create design guidelines for climate-responsive UGI that stem from scientific knowledge and are useful to design practice. A participatory 'Research through Design' (RTD) approach was applied in two design studios to have landscape architects test evidence-based preliminary guidelines. The researchers made observations, plan analyses, and executed questionnaires in the studios to assess the usefulness of the preliminary guidelines and, subsequently, to refine them. This paper presents the revised guidelines for the city, park, and street scale levels and elaborates the knowledge on the microclimate and operational principles needed for implementation. This paper argues that a participatory RTD approach helps to link knowledge from research to practice.
C1 [Klemm, Wiebke; Lenzholzer, Sanda] Wageningen Univ, Wageningen, Netherlands.
   [van den Brink, Adri] Wageningen Univ, Landscape Architecture Dept, Wageningen, Netherlands.
C3 Wageningen University & Research; Wageningen University & Research
RP Klemm, W (corresponding author), Wageningen Univ, Landscape Architecture Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
EM wiebke.klemm@wur.nl; sanda.lenzholzer@wur.nl; adri.vandenbrink@wur.nl
OI Lenzholzer, Sanda/0000-0002-5417-1804
FU Dutch Knowledge for Climate Research Programme
FX This research was carried out as part of a PhD project funded by the
   Dutch Knowledge for Climate Research Programme (theme: Climate-Proof
   Cities). The authors want to thank all of the organizers of the design
   studios at Wageningen University, in particular Rudi van Etteger, and at
   the Aorta Centre of Architectural in Utrecht, in particular Eveline
   Paalvast, for their support. We want to thank all of the participants of
   the design studios for their contributions. Furthermore, we would like
   to thank Rick Lensink for his support, Maarten Jacobs for his valuable
   feedback, Monique Janssen for her support in preparing the online
   questionnaires, and Adrie van't Veer for the creation of the icons. We
   would also like to thank the editors and reviewers of this paper for
   their valuable comments.
CR Andersson E, 2014, AMBIO, V43, P445, DOI 10.1007/s13280-014-0506-y
   [Anonymous], 2009, THESIS
   [Anonymous], CAB REV PERSPECTIVES
   [Anonymous], THESIS
   [Anonymous], IMPACTS ADAPTATION V
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Brown R., 2010, DESIGN MICROCLIMATE
   BROWN R.D., 2017, Research in Landscape Architecture - Methods and Methodology
   Brown RD, 2011, LANDSCAPE URBAN PLAN, V100, P327, DOI 10.1016/j.landurbplan.2011.01.017
   Creswell J. W., 2007, Designing and Conducting Mixed Methods Research
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   DeSchiller S, 1996, ATMOS ENVIRON, V30, P449, DOI 10.1016/1352-2310(94)00139-1
   DESCHILLER S, 1991, ENERG BUILDINGS, V15, P51
   Eliasson I, 2000, LANDSCAPE URBAN PLAN, V48, P31, DOI 10.1016/S0169-2046(00)00034-7
   Eliasson I, 2007, LANDSCAPE URBAN PLAN, V82, P72, DOI 10.1016/j.landurbplan.2007.01.020
   Jamei E, 2016, RENEW SUST ENERG REV, V54, P1002, DOI 10.1016/j.rser.2015.10.104
   James P, 2009, URBAN FOR URBAN GREE, V8, P65, DOI 10.1016/j.ufug.2009.02.001
   Klemm W, 2017, URBAN FOR URBAN GREE, V21, P134, DOI 10.1016/j.ufug.2016.11.004
   Klemm W, 2015, LANDSCAPE URBAN PLAN, V138, P87, DOI 10.1016/j.landurbplan.2015.02.009
   Klemm W, 2015, BUILD ENVIRON, V83, P120, DOI 10.1016/j.buildenv.2014.05.013
   Lafortezza R, 2009, URBAN FOR URBAN GREE, V8, P97, DOI 10.1016/j.ufug.2009.02.003
   Lehmann I, 2014, ECOL INDIC, V42, P58, DOI 10.1016/j.ecolind.2014.02.036
   Lenzholzer S., 2015, Weather in the city: how design shapes the urban climate
   Lenzholzer S, 2018, URBAN CLIM, V23, P231, DOI 10.1016/j.uclim.2016.10.003
   Lenzholzer S, 2013, LANDSCAPE URBAN PLAN, V113, P120, DOI 10.1016/j.landurbplan.2013.02.003
   Lenzholzer Sanda, 2012, J CLEAN PROD, V61, P89
   Lovell ST, 2013, LANDSCAPE ECOL, V28, P1447, DOI 10.1007/s10980-013-9912-y
   Mathey Juliane, 2011, RES CIT CIT AD CLIM
   Nassauer JI, 2008, LANDSCAPE ECOL, V23, P633, DOI 10.1007/s10980-008-9226-7
   Nikolopoulou M, 2003, ENERG BUILDINGS, V35, P95, DOI 10.1016/S0378-7788(02)00084-1
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   Paalvast Eveline, 2014, PROGR GREEN FORC WOR
   Pijpers-van Esch M., 2015, THESIS
   Royal Netherlands Meteorological Institute (KNMI), 2015, CLIMATE SCENARIOS NE
   VAN ETTEGER R., 2014, Course guide Atelier 2014 - Green-blue infrastructure for a resilient and healthy city, LAR-60318 Atelier Landscape Architecture and Planning
NR 35
TC 39
Z9 43
U1 3
U2 29
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1862-6033
J9 J LANDSC ARCHIT
JI J. Landsc. Archit.
PY 2017
VL 12
IS 3
BP 60
EP 71
DI 10.1080/18626033.2017.1425320
PG 12
WC Architecture
WE Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Architecture
GA VI3HA
UT WOS:000471562900006
OA Bronze
DA 2025-01-10
ER

PT J
AU Dalle, D
   Gecho, Y
   Bedeke, SB
AF Dalle, Daniel
   Gecho, Yisak
   Bedeke, Sisay Belay
TI Spatiotemporal Variability and Trends in Rainfall and Temperature in
   South Ethiopia: Implications for Climate Change Adaptations in Rural
   Communities
SO ADVANCES IN METEOROLOGY
LA English
DT Article
ID AGRICULTURE; PATTERNS; MODELS; IMPACT
AB Climate change is an environmental challenge for rural communities that rely heavily on rainwater-based agriculture. The main goal of this study is to investigate spatiotemporal variability and trends in rainfall and temperature in southern Ethiopia. Extreme temperature and rainfall indices were computed using the ClimPACT2 software. The detection and quantification of trends in rainfall and temperature extremes were analyzed using a nonparametric modified Mann-Kendall (MMK) test and Sen's slope estimator. Results indicated that the mean annual rainfall has a declining trend at Boditi School and Mayokote stations with a statistically significant amount at magnitudes of 0.02 mm and 0.04 mm, respectively. The highest average monthly rainfall in the catchment was observed in the months of April, May, June, July, and August up to maximum rainfall of 117.50 mm, 177.43 mm, and 228.84 mm in Bilate Tena, Boditi, and Mayakote stations, respectively. On a seasonal scale, rainfall in Bilate Tena station was highly variable in all months, ranging from 49.54% to 126.92%, and three seasons except spring which showed moderate variation at 40.65%. In addition, the three locations over the catchment exhibited varied drought signs such as severe (1.28 < SRA < 1.65) and extreme drought (SRA > 1.65). The temperature indices, on the other hand, exhibited a warming trend over the catchment which was observed through an increased annual number of warm days (TX90p) and warm nights (TN90p) ranges from 0.274 to 6.03 and 0.274 to 3.16, respectively. The annual maximum value of the daily maximum temperature (TXx) ranges from 30.10 to 33.76degree celsius in the three agroecological zones and showed low, medium, and high values in Dega, Woyna Dega, and Kola agroecologies, while the annual maximum value of the daily minimum temperature (TNx) ranged between 17 and 17.44degree celsius at Dega and Kola, respectively. Therefore, based on trends in rainfall variability and persistent temperature rise, appropriate adaptation strategies should be adopted.
C1 [Dalle, Daniel; Gecho, Yisak; Bedeke, Sisay Belay] Wolaita Sodo Univ, RDAE, POB 138, Wolaita Sodo, Ethiopia.
RP Dalle, D (corresponding author), Wolaita Sodo Univ, RDAE, POB 138, Wolaita Sodo, Ethiopia.
EM danieldalle258@gmail.com; yishakgecho@yahoo.com; belaysisay@gmail.com
FU The authors would like to acknowledge all data providers, namely, MoWIEE
   (Ministry of Water Irrigation and Energy of Ethiopia) and NMAE (National
   Meteorology Agency of Ethiopia), for providing the required data. The
   authors are also thankful to Wolaita Sod; MoWIEE (Ministry of Water
   Irrigation and Energy of Ethiopia); Wolaita Sodo University
FX The authors would like to acknowledge all data providers, namely, MoWIEE
   (Ministry of Water Irrigation and Energy of Ethiopia) and NMAE (National
   Meteorology Agency of Ethiopia), for providing the required data. The
   authors are also thankful to Wolaita Sodo University, who has provided
   all logistical support in conducting the research work.
CR Abbas M, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9110203
   Abiy Gebremichael Abiy Gebremichael, 2014, Journal of Natural Sciences Research, V4, P56
   Ademe D, 2020, WEATHER CLIM EXTREME, V29, DOI 10.1016/j.wace.2020.100263
   Agnew C. T., 1999, GeoJournal, V48, P299, DOI 10.1023/A:1007059403077
   Asmamaw M, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0219393
   Assamnew AD, 2020, THEOR APPL CLIMATOL, V142, P1169, DOI 10.1007/s00704-020-03357-3
   Assefa D., 2021, Natural Resources Management, DOI [10.21203/rs.3.rs-410118/v1, DOI 10.21203/RS.3.RS-410118/V1]
   Babatolu J.S., 2013, Atmos. Clim. Sci., V03, P532, DOI 10.4236/acs.2013.34056
   Bekuma Teka, 2022, IOP Conference Series: Earth and Environmental Science, V1016, DOI 10.1088/1755-1315/1016/1/012032
   Belay Abrham., 2017, Agriculture Food Security, V6, P24, DOI [10.1186/s40066-017-0100-1, DOI 10.1186/S40066-017-0100-1]
   Birkmann J, 2013, NAT HAZARDS, V67, P193, DOI 10.1007/s11069-013-0558-5
   Boltana SM, 2023, COGENT FOOD AGR, V9, DOI 10.1080/23311932.2023.2214428
   Chakraborty S., 2013, Int J Appl Sci Eng Res, V2, P425
   Chang'a L. B., 2017, Atmospheric and Climate Sciences, V7, P525
   Chen F., 2014, Paddy and Water Environment, V10
   Dale A, 2017, EARTHS FUTURE, V5, P337, DOI 10.1002/2017EF000539
   Degefu MA, 2015, GEOGR ANN A, V97, P395, DOI 10.1111/geoa.12080
   Destaw F, 2021, JAMBA-J DISASTER RIS, V13, DOI 10.4102/jamba.v13i1.974
   Esayas B., 2018, Advances in Meteorology, V10, P1, DOI [10.19080/IJESNR.2020.25.556163, DOI 10.19080/IJESNR.2020.25.556163]
   Esayas B, 2019, ADV METEOROL, V2019, DOI 10.1155/2019/7341465
   Etana D, 2020, CLIMATE, V8, DOI 10.3390/cli8110121
   Fernandes R, 2005, REMOTE SENS ENVIRON, V95, P303, DOI 10.1016/j.rse.2005.01.005
   Gebremicheal A., 2014, Insitu moisture conservation View project, V4, P56
   Gedefaw M, 2019, WATER-SUI, V11, DOI 10.3390/w11010161
   Geremew GM, 2020, MODEL EARTH SYST ENV, V6, P1177, DOI 10.1007/s40808-020-00749-2
   Gezie M, 2019, COGENT FOOD AGR, V5, DOI 10.1080/23311932.2019.1613770
   Gitima Ginjo, 2021, Geosfera Indonesia, V6, P96, DOI 10.19184/geosi.v6i1.20718
   Gutu Tesso Gutu Tesso, 2012, African Crop Science Journal, V20, P261
   Hailesilassie W.T., 2021, Environ Earth Sci Res J, V8, P37, DOI [10.18280/eesrj.080104, DOI 10.18280/EESRJ.080104]
   Harka AE, 2021, J HYDROL-REG STUD, V37, DOI 10.1016/j.ejrh.2021.100915
   Hughes DA, 2014, HYDROL RES, V45, P134, DOI 10.2166/nh.2013.027
   Ipcc, 2021, IPCC AR6 WGI, V34, pF0003
   IPCC Summary for Policymakers, 2022, CLIM CHANG 2022 IMP
   Klein R.J., 2015, Climate Change 2014: Impacts, Adaptation. Vulnerability Part A Glob. Sect. Asp.
   Koudahe K., 2017, Atmospheric and Climate Sciences, V7, P401, DOI 10.4236/acs.2017.74030
   Laban O., 2009, Climate Variability and Change in Africa: A Review of Potential Impacts on Terrestrial Water Resources, V334
   Lambe BT., 2021, Arab J Geosci, V14, P1, DOI [10.1007/s12517-021-08962-8, DOI 10.1007/S12517-021-08962-8]
   Leander R, 2007, J HYDROL, V332, P487, DOI 10.1016/j.jhydrol.2006.08.006
   Legesse M., 2022, Southern Ethiopia, V3, P86
   Legesse M., 2023, Natural Hazards, V118
   Ly S, 2011, HYDROL EARTH SYST SC, V15, P2259, DOI 10.5194/hess-15-2259-2011
   McSweeney CF, 2015, CLIM DYNAM, V44, P3237, DOI 10.1007/s00382-014-2418-8
   Mekasha A, 2014, INT J CLIMATOL, V34, P1990, DOI 10.1002/joc.3816
   Mekonen AA, 2021, ECOL PROCESS, V10, DOI 10.1186/s13717-021-00313-5
   Meque A, 2015, CLIM DYNAM, V44, P1881, DOI 10.1007/s00382-014-2143-3
   Mihiretu A, 2020, COGENT FOOD AGR, V6, DOI 10.1080/23311932.2020.1763647
   Mirani KB, 2022, ADV METEOROL, V2022, DOI 10.1155/2022/3336257
   Moges DM, 2021, J WATER CLIM CHANGE, V12, P1229, DOI 10.2166/wcc.2020.058
   Mohammed JA, 2022, WEATHER CLIM EXTREME, V37, DOI 10.1016/j.wace.2022.100468
   Lucas EWM, 2021, WEATHER CLIM EXTREME, V31, DOI 10.1016/j.wace.2021.100306
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Olango TM, 2014, J ETHNOBIOL ETHNOMED, V10, DOI 10.1186/1746-4269-10-41
   Oyerinde G. T., 2017, Over the Ou E M E River Basin
   Perez C, 2015, GLOBAL ENVIRON CHANG, V34, P95, DOI 10.1016/j.gloenvcha.2015.06.003
   Peterson TC, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2002JD002251
   Pierce DW, 2009, P NATL ACAD SCI USA, V106, P8441, DOI 10.1073/pnas.0900094106
   Segele ZT, 2005, METEOROL ATMOS PHYS, V89, P153, DOI 10.1007/s00703-005-0127-x
   Seneviratne SI, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P109
   Soro GE, 2016, CLIMATE, V4, DOI 10.3390/cli4030037
   Stadtbäumer C, 2022, AGR FOOD SECUR, V11, DOI 10.1186/s40066-022-00382-5
   Tefera T., 2016, J SCI RES, V12, P1, DOI DOI 10.9734/JSRR/2016/28667
   The World Bank Group, 2020, Climate Risk Profile: Ethiopia
   Tofu DA, 2023, SCI AFR, V19, DOI 10.1016/j.sciaf.2022.e01448
   Turco M, 2013, CLIMATIC CHANGE, V120, P859, DOI 10.1007/s10584-013-0844-y
   Ukumo TY, 2022, J WATER CLIM CHANGE, V13, P4130, DOI 10.2166/wcc.2022.343
   Ukumo TY, 2022, ADV CIV ENG, V2022, DOI 10.1155/2022/3351375
   Ukumo TY, 2023, WORLD J ENG, V20, P559, DOI 10.1108/WJE-07-2021-0410
   Usaid, 2016, Climate Risk Profile Ethiopia
   Wagaye, 2020, Climatol. Weather Forecast OPEN, V8, P1
   Weldegerima TM, 2018, ADV METEOROL, V2018, DOI 10.1155/2018/5869010
   Wmo, 2021, Global Annual to Decadal Climate Update
   Yishak Gecho Yishak Gecho, 2014, Developing Country Studies, V4, P123
   Zentek R, 2020, GEOSCI MODEL DEV, V13, P1809, DOI 10.5194/gmd-13-1809-2020
NR 73
TC 5
Z9 5
U1 1
U2 2
PU HINDAWI LTD
PI LONDON
PA ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON, W1T 5HF, ENGLAND
SN 1687-9309
EI 1687-9317
J9 ADV METEOROL
JI Adv. Meteorol.
PD SEP 25
PY 2023
VL 2023
AR 1939528
DI 10.1155/2023/1939528
PG 21
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA T7FI1
UT WOS:001079597700001
OA gold
DA 2025-01-10
ER

PT J
AU Liu, MZY
   Liu, H
AF Liu, Muziyun
   Liu, Hui
TI Influence of Climate Change on Carbon Emissions during Grain Production
   and Its Mechanism
SO SUSTAINABILITY
LA English
DT Article
DE climate change; carbon emissions during grain production; green
   technology progress; farmland scale; fertilizer use; multiple cropping
   index
ID GREENHOUSE-GAS EMISSIONS; CO2 EMISSIONS; AGRICULTURE; ENERGY;
   ADAPTATION; MANAGEMENT; YIELDS; RISK
AB Abnormal climatic changes and related disasters are increasing in prevalence, with many negative impacts on ecosystems and agricultural production. The area of land in China is vast, including diverse terrain and climate types, and a substantial area is used to grow food crops. Therefore, climate change is having a huge impact on China's grain production. Currently, the relationship between climate change and carbon emissions during grain production and the underlying mechanism have not been fully clarified. Therefore, this study used an ordinary least squares regression (OLS) model and the system generalized method of moments (SYS-GMM) to examine the influence of climatic change and carbon emissions during grain production, and we constructed mediation effect models to explore the mechanism of influence between them by utilizing panel data in China from 2000 to 2020. In addition, we also examined the adjustment effect of green technology progress and farmland scale. The study found that China's carbon emissions during grain production increased from 2000 to 2015 and then presented a decreasing trend after 2015. We found that the annual average temperature has a prominent positive effect on carbon emissions during grain production, while the annual average rainfall has a negative effect. Among them, temperature changes mainly lead to the increase in carbon emissions during grain production through the increase in "fertilizer use" and "multiple cropping index", but the mechanism of rainfall changes' impact on carbon emissions during grain production is still unclear. In addition, green technology progress and farmland scale play adjustment roles in the impact of climate change on carbon emissions during grain production, and they could significantly suppress carbon emissions. On the basis of the conclusions in this paper, we propose that strengthening climate change adaptation is an important prerequisite for reducing carbon emissions during grain production. Furthermore, China should continue to reduce fertilizer use, facilitate the application of agriculture green technology, and expand the scale of farmland to achieve agricultural carbon emission reduction.
C1 [Liu, Muziyun; Liu, Hui] Hunan Agr Univ, Sch Econ, Changsha 410128, Peoples R China.
C3 Hunan Agricultural University
RP Liu, MZY; Liu, H (corresponding author), Hunan Agr Univ, Sch Econ, Changsha 410128, Peoples R China.
EM lmuziyun@163.com; liuh1220@163.com
FU Key Science Fund Project of Hunan Provincial Philosophy and Social
   Science Fund Project [21YBA079]
FX This research was funded by the Key Science Fund Project of Hunan
   Provincial Philosophy and Social Science Fund Project, grant number
   21YBA079.
CR Andrews HM, 2022, AGR ECOSYST ENVIRON, V332, DOI 10.1016/j.agee.2022.107944
   Ani KJ, 2022, INT J CLIM CHANG STR, V14, P148, DOI 10.1108/IJCCSM-11-2020-0119
   [Anonymous], 2011, China Popul. Resour. Environ, DOI [10.3969/j.issn.1002-2104.2011.08.013, DOI 10.3969/J.ISSN.1002-2104.2011.08.013]
   Baloch ZA, 2022, ENVIRON SCI POLLUT R, V29, P57306, DOI 10.1007/s11356-022-19895-4
   Ben Jebli M, 2017, ECOL INDIC, V74, P295, DOI 10.1016/j.ecolind.2016.11.032
   Bennetzen EH, 2016, GLOBAL CHANGE BIOL, V22, P763, DOI 10.1111/gcb.13120
   Bhattacharyya SS, 2022, SCI TOTAL ENVIRON, V826, DOI 10.1016/j.scitotenv.2022.154161
   Birthal PS, 2021, LAND USE POLICY, V109, DOI 10.1016/j.landusepol.2021.105652
   Bond SR., 2002, PORT ECON J, V1, P141, DOI [10.1007/s10258-002-0009-9, DOI 10.1007/S10258-002-0009-9]
   Chen S, 2021, J DEV ECON, V148, DOI 10.1016/j.jdeveco.2020.102557
   Cui XM, 2022, AM J AGR ECON, V104, P249, DOI 10.1111/ajae.12227
   Dalgaard T, 2011, ENVIRON POLLUT, V159, P3193, DOI 10.1016/j.envpol.2011.02.024
   Feiziene D, 2008, ZEMDIRBYSTE, V95, P29
   Fu J, 2023, NAT FOOD, V4, P416, DOI 10.1038/s43016-023-00753-6
   He PP, 2021, J ENVIRON MANAGE, V293, DOI 10.1016/j.jenvman.2021.112837
   Hochman Z, 2017, GLOBAL CHANGE BIOL, V23, P2071, DOI 10.1111/gcb.13604
   Hu-Cheng Wang, 2021, IOP Conference Series: Earth and Environmental Science, V705, DOI 10.1088/1755-1315/705/1/012026
   Huang JX, 2013, J FOOD AGRIC ENVIRON, V11, P1506
   Huang JK, 2015, AM J AGR ECON, V97, P602, DOI 10.1093/ajae/aav005
   Huang WY, 2022, ENERG ECON, V110, DOI 10.1016/j.eneco.2022.106049
   Larson DW, 2004, FOOD POLICY, V29, P257, DOI 10.1016/j.foodpol.2004.05.001
   Li JK, 2022, LAND-BASEL, V11, DOI 10.3390/land11060816
   Li JD, 2023, FRONT PLANT SCI, V14, DOI 10.3389/fpls.2023.1107970
   Liang DJ, 2021, SCI DATA, V8, DOI 10.1038/s41597-021-00960-5
   Liang ZR, 2023, PNAS NEXUS, V2, DOI 10.1093/pnasnexus/pgad057
   Liu DD, 2021, J CLEAN PROD, V278, DOI 10.1016/j.jclepro.2020.123692
   Lobell DB, 2010, AGR FOREST METEOROL, V150, P1443, DOI 10.1016/j.agrformet.2010.07.008
   Maya KA, 2019, CLIM CHANG ECON, V10, DOI 10.1142/S201000781950012X
   Minoli S, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-34411-5
   Najafi E, 2019, SCI TOTAL ENVIRON, V662, P361, DOI 10.1016/j.scitotenv.2019.01.172
   Ortiz-Bobea A, 2021, NAT CLIM CHANGE, V11, P306, DOI 10.1038/s41558-021-01000-1
   Pant K. P., 2009, Journal of Agriculture and Environment, V10, P72
   Qian C, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19148702
   Qiu WW, 2021, CHINESE GEOGR SCI, V31, P571, DOI 10.1007/s11769-021-1200-1
   Rankoana SA, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8080672
   Saud S, 2022, FRONT MICROBIOL, V13, DOI 10.3389/fmicb.2022.926059
   Shahzad MF, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132111702
   Sirag A, 2018, J ENVIRON ECON POLIC, V7, P145, DOI 10.1080/21606544.2017.1382395
   Solomon R., 2021, American Journal of Climate Change, V10, P32, DOI DOI 10.4236/AJCC.2021.101003
   Song SX, 2023, AGRICULTURE-BASEL, V13, DOI 10.3390/agriculture13050919
   Sun MY, 2020, PHYS CHEM EARTH, V116, DOI 10.1016/j.pce.2020.102837
   Tang LL, 2018, INT J LIFE CYCLE ASS, V23, P2288, DOI 10.1007/s11367-015-0965-9
   Tian Y, 2014, J INTEGR AGR, V13, P1393, DOI 10.1016/S2095-3119(13)60624-3
   Wang WK, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17196976
   Welch JR, 2010, P NATL ACAD SCI USA, V107, P14562, DOI 10.1073/pnas.1001222107
   Wojewodzki M, 2023, J CLEAN PROD, V385, DOI 10.1016/j.jclepro.2022.135697
   Wu HX, 2021, LAND-BASEL, V10, DOI 10.3390/land10020111
   Xiao SX, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19169876
   Xiong CH, 2020, GROWTH CHANGE, V51, P1401, DOI 10.1111/grow.12384
   Xu B, 2017, ENERG POLICY, V104, P404, DOI 10.1016/j.enpol.2017.02.011
   Xu XC, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16203932
   Yang TF, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192114508
   Yang ZM, 2021, URBAN CLIM, V37, DOI 10.1016/j.uclim.2021.100812
   Yu XM, 2023, J ENVIRON MANAGE, V325, DOI 10.1016/j.jenvman.2022.116347
   Zhang Q, 2017, INT J BIOMETEOROL, V61, P1445, DOI 10.1007/s00484-017-1322-4
   Zheng XQ, 2020, P NATL ACAD SCI USA, V117, P29, DOI 10.1073/pnas.1908513117
   Zhong RX, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19116488
   Zornoza R, 2016, GEODERMA, V263, P70, DOI 10.1016/j.geoderma.2015.09.003
NR 58
TC 0
Z9 0
U1 8
U2 40
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JUL
PY 2023
VL 15
IS 13
AR 10237
DI 10.3390/su151310237
PG 15
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA M2OF8
UT WOS:001028619300001
OA gold
DA 2025-01-10
ER

PT J
AU Mandic, MV
   Vimic, AV
   Aksic, MF
   Meland, M
AF Mandic, Mirjam Vujadinovic
   Vimic, Ana Vukovic
   Aksic, Milica Fotiric
   Meland, Mekjell
TI Climate Potential for Apple Growing in Norway-Part 2: Assessment of
   Suitability of Heat Conditions under Future Climate Change
SO ATMOSPHERE
LA English
DT Article
DE climate change; apple varieties; heat requirements; growing degree days;
   zoning
ID IMPACT; TREES
AB The commercial apple production in Norway is limited to the small regions along the fjords in the southwest part of the country and around lakes or near the sea in the southeast with favorable climate. Due to the rapid rate of climate change over the recent decades, it is expected that suitable heat conditions for apple growing will expand to the areas that were previously too cold. This study analyses the heat suitability of future climate (2021-2100) under the RCP8.5 scenario for 6 common apple varieties in Norway: Discovery, Gravenstein, Summerred, Aroma, Rubinstep and Elstar. Previously established heat requirement criteria (based on the temperature threshold for the full blooming and growing degree days sum between the full bloom and harvest) are applied to the temperature outputs of the regional climate models downscaled to 1 km resolution. The assessment indicates that as temperature rises, heat conditions suitable for cultivation of all 6 apple varieties will expand. According to the ensemble median value, areas with the favorable heat conditions for growing at least one of the considered apple varieties will increase 25 times in the period 2021-2040 and 60 times in the period 2041-2060, compared to the referent period 1971-2000. At the same time, areas suitable for all 6 apple varieties will increase 3 times in the first, and 3.8 times in the latter period. The favorable areas will advance from south and southeast northwards and inland in the eastern region, along the west and northwestern coastline towards higher latitudes, and along continental parts of fjords. The fastest expansion of heat suitable conditions is expected for Discovery and Gravenstein. The findings of this study are relevant for zoning apple production future potential and for strategical planning of climate change adaptation measures within the sector. Weather-related risks, such as risks from winter low temperatures, spring frost, drought and extreme precipitation were not considered.
C1 [Mandic, Mirjam Vujadinovic; Vimic, Ana Vukovic; Aksic, Milica Fotiric] Univ Belgrade, Fac Agr, Nemanjina 6, Belgrade 11080, Serbia.
   [Meland, Mekjell] Norwegian Inst Bioecon Res, Dept Hort, NIBIO Ullensvang, Ullensvangvegen 1005, N-5781 Lofthus, Norway.
C3 University of Belgrade; Norwegian Institute of Bioeconomy Research
RP Meland, M (corresponding author), Norwegian Inst Bioecon Res, Dept Hort, NIBIO Ullensvang, Ullensvangvegen 1005, N-5781 Lofthus, Norway.
EM mirjam@agrif.bg.ac.rs; anavuk@agrif.bg.ac.rs; fotiric@agrif.bg.ac.rs;
   mekjell.meland@nibio.no
OI Vukovic Vimic, Ana/0000-0003-2528-3169; Vujadinovic Mandic,
   Mirjam/0000-0001-9583-5067; Fotiric Aksic, MIlica/0000-0001-9086-9145;
   Meland, Mekjell/0000-0003-3355-8775
FU Norwegian Agriculture Agency [2020/72550, Agros 138323]
FX This research was funded by the Norwegian Agriculture Agency, grant
   number 2020/72550, Agros 138323.
CR [Anonymous], 2013, CLIM CHANG AD NORW, P107
   Arundhati, 2020, J PHARMACOGN PHYTOCH, V9, P1219
   Ashworth Edward N., 1992, Horticultural Reviews, V13, P215, DOI 10.1002/9780470650509.ch6
   Baldos ULC, 2014, AUST J AGR RESOUR EC, V58, P554, DOI 10.1111/1467-8489.12048
   Belliveau S., 2007, Farming in a changing climate: agricultural adaptation in Canada, P157
   Burgess MG, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abcdd2
   Caprio JM, 1999, CAN J PLANT SCI, V79, P129, DOI 10.4141/P98-028
   Eccel E, 2009, INT J BIOMETEOROL, V53, P273, DOI 10.1007/s00484-009-0213-8
   Fraga H, 2021, FRONT PLANT SCI, V12, DOI 10.3389/fpls.2021.689121
   Gitea MA, 2019, ENVIRON SCI POLLUT R, V26, P9908, DOI 10.1007/s11356-019-04214-1
   Hanssen-Bauer I., 2017, CLIMATE NORWAY 2100, P47, DOI [10.1002/2015jc011277, DOI 10.1002/2015JC011277]
   IPCC, 2022, SYNTH REP 6 ASS REP, P85
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Kaukoranta T, 2010, AGR FOOD SCI, V19, P144, DOI 10.2137/145960610791542352
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Li MR, 2020, THEOR APPL CLIMATOL, V139, P191, DOI 10.1007/s00704-019-02965-y
   Lindén L, 2001, CAN J PLANT SCI, V81, P479, DOI 10.4141/P00-142
   Luedeling E, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0020155
   NMCE, 2021, NORW 1 AD COMM UNFCC, P46
   Nordli O, 2008, INT J BIOMETEOROL, V52, P625, DOI 10.1007/s00484-008-0156-5
   Pan HH, 2007, SCI HORTIC-AMSTERDAM, V112, P290, DOI 10.1016/j.scienta.2006.12.046
   Pfleiderer P, 2019, CLIMATIC CHANGE, V157, P515, DOI 10.1007/s10584-019-02570-y
   Pielke R, 2021, ENERGY RES SOC SCI, V72, DOI 10.1016/j.erss.2020.101890
   Pramanick K, 2017, ENV ECOLOGY RES, V5, P325, DOI [10.13189/eer.2017.050501, DOI 10.13189/EER.2017.050501]
   Ramírez F, 2013, SCI HORTIC-AMSTERDAM, V162, P188, DOI 10.1016/j.scienta.2013.08.007
   Rivero R, 2017, ACTA AGR SCAND B-S P, V67, P292, DOI 10.1080/09064710.2016.1267256
   Rochette P, 2004, CAN J PLANT SCI, V84, P1113, DOI 10.4141/P03-177
   Roen D, 1998, ACTA HORTIC, P153, DOI 10.17660/ActaHortic.1998.484.24
   ssb, 2023, STAT NORW
   Sugiura T, 2004, J JPN SOC HORTIC SCI, V73, P72, DOI 10.2503/jjshs.73.72
   Sugiura T, 2013, SCI REP-UK, V3, DOI 10.1038/srep02418
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Verma K.S., 2013, CLIMATE RESILIENT HO, P89
   Vukovic Vimic A., 2023, ATMOSPHERE-BASEL
   Winkler JA, 2002, J GREAT LAKES RES, V28, P608, DOI 10.1016/S0380-1330(02)70609-6
   WMO, 2009, GUID AN EXTR CHANG C, P52
   Wong W.K., 2016, 592016 NVE NORW WAT, P25
NR 37
TC 6
Z9 6
U1 1
U2 10
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD JUN
PY 2023
VL 14
IS 6
AR 937
DI 10.3390/atmos14060937
PG 13
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA K5PE9
UT WOS:001016951600001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Hashem, K
   Sushama, L
   Sasmito, AP
   Hassani, F
   Kumral, M
AF Hashem, Khalil
   Sushama, Laxmi
   Sasmito, Agus P.
   Hassani, Ferri
   Kumral, Mustafa
TI Climate-mine life cycle interactions for northern Canadian regions
SO COLD REGIONS SCIENCE AND TECHNOLOGY
LA English
DT Article
DE Climate change; Northern mines; Regional climate modelling;
   Quantification of impacts
ID BOUNDARY-LAYER; PARAMETERIZATION; PERFORMANCE; STABILITY; ONTARIO;
   ENERGY; WASTE; LAND
AB This study quantifies the impacts of climate change on the mine life cycle (development, operation and closure phases) of 30 mines located in the northern regions of Canada. To this end, climate projections based on a five -member transient climate change simulation ensemble, performed using a state-of-the art regional climate model, spanning the 1991-2050 period, corresponding to the Representative Concentration Pathway 8.5 emis-sion scenario are used. A reanalysis-driven simulation for the 1991-2010 period compared against available observations confirm suitability of the model for application in climate change simulations. Assessment of projected changes to mine-relevant climate variables that are important from structural integrity and operation perspectives reveal potential vulnerabilities and opportunities. Active layer thickness increases in the 0.3-2 m range in permafrost regions, coupled with increases in flood probability, as reflected in snow-melt rate increases in the 0.14-6.77% range and increases in the 100-year return levels of daily maximum rainfall in the 5-50% range, suggest potential impacts on the structural integrity of mine infrastructure, such as slope instability and foundation settlement of tailings dams, and supporting infrastructure such as ice/all-season roads. Increases in soil moisture, projected in the 0-11% range, at a few mines, suggest potential impacts on material handling systems, such as increases in the traction factor of the muck-haul and tire rolling resistance, that can lead to low productivity. Projected increases to wind speeds in the 5-10% range for the northernmost regions suggest po-tential impacts on the tailings management facility in terms of increases in tailings resuspension. Overall, this study identified northernmost and northeastern mines to be more vulnerable, with air/soil temperature, pre-cipitation and wind speed being the most influential climate variables. This systematic study, for the first time, has identified potential vulnerabilities of northern Canadian mines, which can inform future high-resolution climate modelling and detailed at-site climate-mine interaction studies that is required for climate-change adaptation related decision-making.
C1 [Hashem, Khalil; Sushama, Laxmi] McGill Univ, Dept Civil Engn, Montreal, PQ, Canada.
   [Hashem, Khalil; Sushama, Laxmi; Sasmito, Agus P.; Hassani, Ferri; Kumral, Mustafa] McGill Univ, Trottier Inst Sustainabil Engn & Design, Montreal, PQ, Canada.
   [Sasmito, Agus P.; Hassani, Ferri; Kumral, Mustafa] McGill Univ, Dept Min & Mat Engn, Montreal, PQ, Canada.
C3 McGill University; McGill University; McGill University
RP Hashem, K (corresponding author), McGill Univ, Dept Civil Engn, Montreal, PQ, Canada.
EM khalil.hashem@mail.mcgill.ca
RI Sasmito, Agus/S-9439-2019
OI Kumral, Mustafa/0000-0003-1370-7446
FU FRQNT Development Durable du Secteur Minier-II [2020-MN-284402];
   ArcelorMittal Canada
FX The GEM simulations used in this study were performed on supercomputers
   managed by Calcul Quebec and Compute Canada. The authors acknowledge
   funding from the FRQNT Development Durable du Secteur Minier-II
   (2020-MN-284402) and ArcelorMittal Canada.
CR Agnico-Eagle, 2022, LARONDE COMPL COMP L
   Alzoubi MA, 2021, COLD REG SCI TECHNOL, V192, DOI 10.1016/j.coldregions.2021.103401
   Andersland O. B., 2003, FROZEN GROUND ENG
   [Anonymous], 2002, Belt Conveyors for Bulk Materials
   [Anonymous], 2015, NATL BUILDING CODE C
   Arsie I, 2005, Proceedings of the ASME Power Conference 2005, Pts A and B, P987
   Atkinson LC, 2010, MINE WATER ENVIRON, V29, P99, DOI 10.1007/s10230-010-0109-1
   Awuah-Offei K, 2016, J CLEAN PROD, V117, P89, DOI 10.1016/j.jclepro.2016.01.035
   Barker AB, 2005, SPACE WEATHER, V3, DOI 10.1029/2004SW000118
   Bélair S, 2005, MON WEATHER REV, V133, P1938, DOI 10.1175/MWR2958.1
   BENOIT R, 1989, MON WEATHER REV, V117, P1726, DOI 10.1175/1520-0493(1989)117<1726:IOATBL>2.0.CO;2
   Bensassi S., 2016, ELEMENTA-SCI ANTHROP, V4
   Boulanger-Martel V, 2021, CAN GEOTECH J, V58, P427, DOI 10.1139/cgj-2019-0616
   Brown J., 2002, CIRCUMARCTIC MAP PER
   Brown J., 2000, Polar Geography, V3, P165
   Clemente JS, 2019, ENVIRON REV, V27, P478, DOI 10.1139/er-2017-0092
   Csavina J, 2014, SCI TOTAL ENVIRON, V487, P82, DOI 10.1016/j.scitotenv.2014.03.138
   DeBeers-Group, 2015, BUILD ICE ROAD VICT
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Delage Y, 1997, BOUND-LAY METEOROL, V82, P23, DOI 10.1023/A:1000132524077
   Diro GT, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10080430
   Dukhan T, 2021, BUILD ENVIRON, V196, DOI 10.1016/j.buildenv.2021.107800
   Elberling B, 2004, CRYOSOLS: PERMAFROST-AFFECTED SOILS, P677
   Falmagne V., 2019, PROC 9 INT S GROUND, P139
   Ford JD, 2018, CLIMATIC CHANGE, V151, P189, DOI 10.1007/s10584-018-2304-1
   Glencore-Canada, 2018, RAGL MIN OP ITS 2 WI
   Gokhale B.V., 2010, Rotary drilling and blasting in large surface mines
   Gruber S, 2007, J GEOPHYS RES-EARTH, V112, DOI 10.1029/2006JF000547
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Harris I, 2014, INT J CLIMATOL, V34, P623, DOI 10.1002/joc.3711
   Harris S.A., 2017, GEOCRYOLOGY CHARACTE, DOI DOI 10.4324/9781315166988
   Heginbottom J.A., 1987, PERMAFROST GROUND IC
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Ho K, 2017, Slope safety preparedness for impact of climate change, DOI [10.1201/9781315387789, DOI 10.1201/9781315387789]
   Hori Y, 2017, THEOR APPL CLIMATOL, V129, P1309, DOI 10.1007/s00704-016-1855-1
   Hosking J.R.M., 1997, Regional Frequency Analysis: An Approach Based on L-Moments, DOI [10.1017/CBO9780511529443, DOI 10.1017/CBO9780511529443]
   Hydro-Quebec, 2021, UND EL WIND POW OTH
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Jakubec J., 2018, P 4 INT S BLOCK SUBL
   Jamasmie C, 2016, PEREGRINE DIAMONDS F
   KAIN JS, 1992, METEOROL ATMOS PHYS, V49, P93, DOI 10.1007/BF01025402
   Kawalec W, 2020, ENERGIES, V13, DOI 10.3390/en13195214
   Kivinen S, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9101705
   Knutsson R, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-018-7465-8
   Kyhn C, 2001, COLD REG SCI TECHNOL, V32, P133, DOI 10.1016/S0165-232X(00)00024-0
   MAC, 2019, FACTS FIG REP STAT C
   MAGER D., 2009, The International Journal of Marine and Coastal Law Diethard Mager, v, V24, DOI DOI 10.1163/157180809X421798
   Masloboev VA, 2016, P INT MIN PROC C 201, P11
   Mensah K, 2015, J MECH SCI TECHNOL, V29, P5507, DOI 10.1007/s12206-015-1152-4
   Mian MH, 2003, ADV ENVIRON RES, V7, P745, DOI 10.1016/S1093-0191(02)00027-8
   Mironov D, 2010, BOREAL ENVIRON RES, V15, P218
   Mullan D, 2017, THEOR APPL CLIMATOL, V129, P1089, DOI 10.1007/s00704-016-1830-x
   Mutlu-Pakdil B, 2018, ASTROPHYS J, V863, DOI 10.3847/1538-4357/aacd0e
   MVLWB, 2013, MACK VALL LAND WAT B
   NCCC, 2012, ENG CHALL TAIL MAN F
   Palko K., 2017, CLIMATE RISKS ADAPTA, P2016
   Pearce TD, 2011, MITIG ADAPT STRAT GL, V16, P347, DOI 10.1007/s11027-010-9269-3
   Petryshen C., 2018, P 4 INT S BLOCK SUBL
   Prein AF, 2015, REV GEOPHYS, V53, P323, DOI 10.1002/2014RG000475
   Prowse TD, 2009, AMBIO, V38, P272, DOI 10.1579/0044-7447-38.5.272
   Roworth MeganRose., 2013, Understanding the effect of freezing on rock mass behaviour as applied to the Cigar Lake mining method
   Rummukainen M, 2010, WIRES CLIM CHANGE, V1, P82, DOI 10.1002/wcc.8
   Rykaart M., 2018, P TAILINGS MINE WAST
   Scales M, 2006, CAN MIN J, V127, P5
   Schuur EAG, 2015, NATURE, V520, P171, DOI 10.1038/nature14338
   Shahriar K., 2007, 7 TH INT SCI C SGEM2
   Shahriar K., 2007, INT SCI C
   Simard S., 2017, RENEW ENERGY POWER Q, V1
   Slater AG, 2013, J CLIMATE, V26, P5608, DOI 10.1175/JCLI-D-12-00341.1
   SUNDQVIST H, 1989, MON WEATHER REV, V117, P1641, DOI 10.1175/1520-0493(1989)117<1641:CACPSW>2.0.CO;2
   Swinderman T., 2016, FDN CONVEYOR SAFETY
   Szczepinski J, 2019, WATER-SUI, V11, DOI 10.3390/w11040848
   Teufel B, 2022, CLIM DYNAM, V59, P3135, DOI 10.1007/s00382-022-06265-6
   Teufel B, 2019, NAT CLIM CHANGE, V9, P858, DOI 10.1038/s41558-019-0614-6
   Teufel B, 2019, CLIM DYNAM, V52, P373, DOI 10.1007/s00382-018-4142-2
   Thornton P., 2016, GEOGRAPHIC AREA S 51
   Verseghy D., 2009, CLASS-The Canadian Land Surface Scheme (Version 3.4), P180
   Wang SH, 2016, GEOMECH ENG, V10, P225, DOI 10.12989/gae.2016.10.2.225
   Whittington P, 2013, HYDROL PROCESS, V27, P1845, DOI 10.1002/hyp.9858
   Wind-Turbine-Models, 2021, EN E 82 E4 3 000
   Yakovlev VL, 2018, J MIN SCI+, V54, P979, DOI 10.1134/S1062739118065131
   Yarmuch J.L., 2020, OPTIMUM RAMP DESIGN, V115
   Zadra A., 2012, Recent changes to the orographic blocking parametrization
   Zhao YJ, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11040418
   Zhao YX, 2020, APPL SYST INNOV, V3, DOI 10.3390/asi3030036
   Zhongming Z., 2020, WHAT EVERY MINING CE
   Zueter AF, 2021, COLD REG SCI TECHNOL, V189, DOI 10.1016/j.coldregions.2021.103313
NR 87
TC 1
Z9 1
U1 1
U2 15
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0165-232X
EI 1872-7441
J9 COLD REG SCI TECHNOL
JI Cold Reg. Sci. Tech.
PD APR
PY 2023
VL 208
AR 103782
DI 10.1016/j.coldregions.2023.103782
EA JAN 2023
PG 21
WC Engineering, Environmental; Engineering, Civil; Geosciences,
   Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology
GA 8M4PF
UT WOS:000924448300001
DA 2025-01-10
ER

PT J
AU Ototo, EN
   Ogutu, JO
   Githeko, A
   Said, MY
   Kamau, L
   Namanya, D
   Simiyu, S
   Mutimba, S
AF Ototo, Ednah N.
   Ogutu, Joseph O.
   Githeko, Andrew
   Said, Mohammed Y.
   Kamau, Lucy
   Namanya, Didacus
   Simiyu, Stella
   Mutimba, Stephen
TI Forecasting the Potential Effects of Climate Change on Malaria in the
   Lake Victoria Basin Using Regionalized Climate Projections
SO ACTA PARASITOLOGICA
LA English
DT Article
DE Climate change; Malaria; Regionalized climate projections
ID EL-NINO; TRANSMISSION; HIGHLANDS; TEMPERATURE; VARIABILITY; RESURGENCE;
   IMPACT; EPIDEMICS; DISEASES; HEALTH
AB Background Malaria epidemics are increasing in East Africa since the 1980s, coincident with rising temperature and widening climate variability. A projected 1-3.5 degrees C rise in average global temperatures by 2100 could exacerbate the epidemics by modifying disease transmission thresholds. Future malaria scenarios for the Lake Victoria Basin (LVB) are quantified for projected climate scenarios spanning 2006-2100. Methods Regression relationships are established between historical (1995-2010) clinical malaria and anaemia cases and rainfall and temperature for four East African malaria hotspots. The vector autoregressive moving average processes model, VARMAX (p,q,s), is then used to forecast malaria and anaemia responses to rainfall and temperatures projected with an ensemble of eight General Circulation Models (GCMs) for climate change scenarios defined by three Representative Concentration Pathways (RCPs 2.6, 4.5 and 8.5). Results Maximum temperatures in the long rainy (March-May) and dry (June-September) seasons will likely increase by over 2.0 degrees C by 2070, relative to 1971-2000, under RCPs 4.5 and 8.5. Minimum temperatures (June-September) will likely increase by over 1.5-3.0 degrees C under RCPs 2.6, 4.5 and 8.5. The short rains (OND) will likely increase more than the long rains (MAM) by the 2050s and 2070s under RCPs 4.5 and 8.5. Historical malaria cases are positively and linearly related to the 3-6-month running means of monthly rainfall and maximum temperature. Marked variation characterizes the patterns projected for each of the three scenarios across the eight General Circulation Models, reaffirming the importance of using an ensemble of models for projections. Conclusions The short rains (OND), wet season (MAM) temperatures and clinical malaria cases will likely increase in the Lake Victoria Basin. Climate change adaptation and mitigation strategies, including malaria control interventions could reduce the projected epidemics and cases. Interventions should reduce emerging risks, human vulnerability and environmental suitability for malaria transmission.
C1 [Ototo, Ednah N.; Kamau, Lucy] Kenyatta Univ, POB 43844, Nairobi, Kenya.
   [Ototo, Ednah N.; Githeko, Andrew] Kenya Govt Med Res Ctr, Ctr Global Hlth Res, Climate & Human Hlth Res Unit, POB 1578, Kisumu, Kenya.
   [Ogutu, Joseph O.] Univ Hohenheim, Inst Crop Sci 340, D-70599 Stuttgart, Germany.
   [Said, Mohammed Y.; Simiyu, Stella; Mutimba, Stephen] C&E Advisory Kenya, POB 76406-00508, Nairobi, Kenya.
   [Namanya, Didacus] Uganda Minist Hlth, POB 7272, Kampala, Uganda.
   [Said, Mohammed Y.] Univ Nairobi, Inst Climate Change & Adaptat, POB 30197, Nairobi 00100, Kenya.
C3 Kenyatta University; Kenya Medical Research Institute; University
   Hohenheim; University of Nairobi
RP Ogutu, JO (corresponding author), Univ Hohenheim, Inst Crop Sci 340, D-70599 Stuttgart, Germany.
EM ednaototo@gmail.com; jogutu2007@gmail.com; githeko@yahoo.com;
   msaid362@gmail.com; kamau.lucym@ku.ac.ke; namanyabd2@gmail.com;
   stella.wattimah@eclimateadvisory.com;
   stephen.mutimba@eclimateadvisory.com
OI Namanya, Didacus/0000-0001-6906-4617; Ogutu, Joseph
   O/0000-0002-7379-0387
FU Projekt DEAL; International Development Research Center/Department for
   International Development IDRC/DFID (CCAA) [104707-001]; German Research
   Foundation (DFG Grant) [257734638]; USAID/Kenya and East Africa Planning
   for Resilience in East Africa through Policy, Adaptation, Research and
   Economic Development (PREPARED); European Union [641918]
FX Open Access funding enabled and organized by Projekt DEAL. Ednah Ototo
   was supported by a grant to AK Githeko by International Development
   Research Center/Department for International Development IDRC/DFID
   (CCAA, Project ID: 104707-001). Joseph O. Ogutu was supported by a grant
   from the German Research Foundation (DFG Grant #257734638). This
   research was supported with funds from USAID/Kenya and East Africa
   Planning for Resilience in East Africa through Policy, Adaptation,
   Research and Economic Development (PREPARED). This project has received
   funding from the European Union's Horizon 2020 research and innovation
   programme under Grant Agreement No. 641918.
CR [Anonymous], 2011, GLOB MAL ACT PLAN
   Bentsen M, 2013, GEOSCI MODEL DEV, V6, P687, DOI 10.5194/gmd-6-687-2013
   Bousema T, 2012, PLOS MED, V9, DOI 10.1371/journal.pmed.1001165
   Bousema T, 2010, J INFECT DIS, V201, P1764, DOI 10.1086/652456
   Burnham K. P., 2002, Model selection and inference: a practical informationtheoretic approach, VSecond edition
   Chen H, 2006, MALARIA J, V5, DOI 10.1186/1475-2875-5-17
   Dasgupta S, 2018, INT J HYG ENVIR HEAL, V221, P782, DOI 10.1016/j.ijheh.2018.04.003
   Ebi KL, 2005, CLIMATIC CHANGE, V73, P375, DOI 10.1007/s10584-005-6875-2
   Endris HS, 2013, J CLIMATE, V26, P8453, DOI 10.1175/JCLI-D-12-00708.1
   Engle R, 2002, J BUS ECON STAT, V20, P339, DOI 10.1198/073500102288618487
   ENGLE RF, 1987, ECONOMETRICA, V55, P251, DOI 10.2307/1913236
   Giorgetta MA, 2013, J ADV MODEL EARTH SY, V5, P572, DOI 10.1002/jame.20038
   Giorgi F, 2006, J PHYS IV, V139, P101, DOI 10.1051/jp4:2006139008
   Githeko A., 2001, GLOBAL CHANGE HUMAN, V2, P54, DOI DOI 10.1023/A:1011943131643
   Githeko AK, 2012, ACTA TROP, V121, P19, DOI 10.1016/j.actatropica.2011.10.002
   Githeko AK, 2000, B WORLD HEALTH ORGAN, V78, P1136
   Githeko AK, 2014, MALARIA J, V13, DOI 10.1186/1475-2875-13-329
   Hay SI, 2002, TRENDS PARASITOL, V18, P530, DOI 10.1016/S1471-4922(02)02374-7
   Hay SI, 2002, NATURE, V415, P905, DOI 10.1038/415905a
   Himeidan YE, 2012, FRONT PHYSIOL, V3, DOI 10.3389/fphys.2012.00315
   HOSKING JRM, 1980, J AM STAT ASSOC, V75, P602, DOI 10.2307/2287656
   IPCC, 2018, GLOB WARM 1 5C SUMM
   IPCC (Intergovernmental Panel on Climate Change), 2014, TECHN SUMM CLIM CHAN
   Johansen S., 1995, LIKELIHOOD BASED INF
   Jones AE, 2007, MALARIA J, V6, DOI 10.1186/1475-2875-6-162
   Jones CD, 2011, GEOSCI MODEL DEV, V4, P543, DOI 10.5194/gmd-4-543-2011
   Kinung'hi SM, 2010, BMC PUBLIC HEALTH, V10, DOI 10.1186/1471-2458-10-395
   Lindblade KA, 1999, T ROY SOC TROP MED H, V93, P480, DOI 10.1016/S0035-9203(99)90344-9
   Lindblade KA, 2006, J MED ENTOMOL, V43, P428, DOI 10.1093/jmedent/43.2.428
   Malakooti MA, 1998, EMERG INFECT DIS, V4, P671, DOI 10.3201/eid0404.980422
   McMichael AJ, 2006, LANCET, V367, P859, DOI 10.1016/S0140-6736(06)68079-3
   Mordecai EA, 2013, ECOL LETT, V16, P22, DOI 10.1111/ele.12015
   Newton CRJC, 1997, TROP MED INT HEALTH, V2, P165, DOI 10.1046/j.1365-3156.1997.d01-238.x
   Nolan P, 2020, EC EARTH GLOBAL CLIM
   Ochomo Eric O, 2013, Malar J, V12, P368, DOI 10.1186/1475-2875-12-368
   Okumu FO, 2011, MALARIA J, V10, DOI 10.1186/1475-2875-10-208
   Olago D, 2007, AMBIO, V36, P350, DOI 10.1579/0044-7447(2007)36[350:CSAHFA]2.0.CO;2
   Olayemi I., 2008, AFR J BIOSCI, V1, P84
   Ototo EN, 2015, MALARIA J, V14, DOI 10.1186/s12936-015-0763-7
   Ototo EN, 2011, PARASITE VECTOR, V4, DOI 10.1186/1756-3305-4-144
   Paaijmans KP, 2010, P NATL ACAD SCI USA, V107, P15135, DOI 10.1073/pnas.1006422107
   Pascual M, 2006, P NATL ACAD SCI USA, V103, P5829, DOI 10.1073/pnas.0508929103
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Polgreen PM, 2018, CLIN INFECT DIS, V66, P815, DOI 10.1093/cid/cix1105
   Ryan SJ, 2015, VECTOR-BORNE ZOONOT, V15, P718, DOI 10.1089/vbz.2015.1822
   Siderius C, 2018, EARTHS FUTURE, V6, P2, DOI [10.1002/2017EF000680, 10.1002/2017]
   SNOW RW, 1994, ACTA TROP, V57, P289, DOI 10.1016/0001-706X(94)90074-4
   Talisuna AO, 2015, MALARIA J, V14, DOI 10.1186/s12936-015-0677-4
   Thomas CJ, 2004, TRENDS PARASITOL, V20, P216, DOI 10.1016/j.pt.2004.03.001
   Trenberth KE, 1996, GEOPHYS RES LETT, V23, P57, DOI 10.1029/95GL03602
   van Meijgaard E, 2012, AGU FALL M ABSTRACTS
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Wandiga SO, 2010, CLIMATIC CHANGE, V99, P473, DOI 10.1007/s10584-009-9670-7
   Wanjala CL, 2011, PARASITE VECTOR, V4, DOI 10.1186/1756-3305-4-81
   Watanabe M, 2010, J CLIMATE, V23, P6312, DOI 10.1175/2010JCLI3679.1
   WHO, 2011, WORLD MALARIA REPORT 2011, P1
   World Health Organisation, 2013, METH ACH UN COV LONG
   Yé Y, 2007, BMC PUBLIC HEALTH, V7, DOI 10.1186/1471-2458-7-101
   Zhou G, 2004, P NATL ACAD SCI USA, V101, P2375, DOI 10.1073/pnas.0308714100
   Zhou GF, 2005, TRENDS PARASITOL, V21, P54, DOI 10.1016/j.pt.2004.11.002
   Zhou GF, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0020318
NR 61
TC 8
Z9 8
U1 0
U2 18
PU SPRINGER INT PUBL AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 1230-2821
EI 1896-1851
J9 ACTA PARASITOL
JI Acta Parasitolog.
PD DEC
PY 2022
VL 67
IS 4
BP 1535
EP 1563
DI 10.1007/s11686-022-00588-4
EA AUG 2022
PG 29
WC Parasitology; Veterinary Sciences; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Parasitology; Veterinary Sciences; Zoology
GA 6N9FY
UT WOS:000840021100002
PM 35962265
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Paprocki, K
AF Paprocki, Kasia
TI On viability: Climate change and the science of possible futures
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE viability; co-production; political ecology; science and technology
   studies; climate change adaptation; agrarian change
ID BRAHMAPUTRA-MEGHNA DELTA; SOIL-SALINITY; COASTAL BANGLADESH; ECOSYSTEM
   SERVICES; SHRIMP; IMPACTS; MODEL; SUBSIDENCE; MANAGEMENT; INTRUSION
AB Growing attention to the impacts of climate change around the world has been accompanied by the profusion of discourses about the lives, livelihoods, and geographies that are "viable" and those that are not in the time of climate change. These discourses of viability often invoke concrete physical limits and tipping points suggesting a transcendent natural order. Conversely, I demonstrate how viability is co-produced through political economic structures that exercise power at multiple scales in shaping the environment and understandings of how it is changing. I describe three dialectics of this co-production: epistemic/material (between ideas about viability and their biophysical and political economic conditions), epistemic/normative (between how the world is understood to be and ideas about how we should live in it), and inter-scalar (between geographic scales, where action at one scale shapes both ecologies and understandings of possible action at another). Each of these dialectics shapes the knowledge regimes that govern the ambiguous social and biophysical process of disappearance and foreclosure of livelihood possibilities in the time of climate change. I examine these discourses of viability through narratives of unviable agrarian livelihoods in coastal Bangladesh, as a lens through which to examine the dialectics of viability more broadly. I situate these discourses concretely in relation to an analysis of interdisciplinary social and natural scientific research on ecological and agrarian viability in coastal Bangladesh now and in the future. Across a broad interdisciplinary spectrum, I find that scientific attention to political economy shapes the politics of possibility. Finally, I demonstrate how discourses of viability limit alternative possible economic and ecological futures. I do this through a concrete examination of the co-production of viable agrarian futures within communities in coastal Bangladesh. These alternative visions indicate that the viability of agriculture is shaped by historical and ongoing decisions in the present about cultivation, water management, and development intervention.
C1 [Paprocki, Kasia] London Sch Econ & Polit Sci, Dept Geog & Environm, Houghton St, London WC2A 2AE, England.
C3 University of London; London School Economics & Political Science
RP Paprocki, K (corresponding author), London Sch Econ & Polit Sci, Dept Geog & Environm, Houghton St, London WC2A 2AE, England.
EM k.paprocki@lse.ac.uk
RI Paprocki, Kasia/AFN-4975-2022
OI Paprocki, Kasia/0000-0001-5202-351X
FU National Science Foundation [DGE1144153, 1459009]; Social Science
   Research Council; Fulbright-Hays Program; Division Of Behavioral and
   Cognitive Sci; Direct For Social, Behav & Economic Scie [1459009]
   Funding Source: National Science Foundation
FX Research contributing to this article was generously supported by
   funding from the National Science Foundation (under Grant Nos.
   DGE1144153 and 1459009), the Social Science Research Council, the
   Fulbright-Hays Program.
CR Adnan S, 2013, J PEASANT STUD, V40, P87, DOI 10.1080/03066150.2012.753058
   Adnan Shapan., 2009, Water, Sovereignty and Borders in Asia and Oceania, P104
   Advisory Group on Development of Deltaic Areas, 1966, APPR SOM ASP COAST E
   Afroz S, 2017, DEV CHANGE, V48, P692, DOI 10.1111/dech.12310
   Afroz S, 2016, HUM ECOL, V44, P17, DOI 10.1007/s10745-016-9809-x
   Ahmed N, 2015, OCEAN COAST MANAGE, V114, P42, DOI 10.1016/j.ocecoaman.2015.06.008
   Akter J, 2016, J COASTAL RES, V32, P1212, DOI 10.2112/JCOASTRES-D-14-00232.1
   Alam M, 2003, SEDIMENT GEOL, V155, P179, DOI 10.1016/S0037-0738(02)00180-X
   Ali AMS, 2006, LAND USE POLICY, V23, P421, DOI 10.1016/j.landusepol.2005.02.001
   Allison MA, 1998, J COASTAL RES, V14, P1269
   Asayama S, 2021, CLIMATIC CHANGE, V167, DOI 10.1007/s10584-021-03185-y
   Auerbach LW, 2015, NAT CLIM CHANGE, V5, P153, DOI [10.1038/NCLIMATE2472, 10.1038/nclimate2472]
   Blaikie P., 1985, The political economy of soil erosion in developing countries.
   Bomer EJ, 2020, CATENA, V187, DOI 10.1016/j.catena.2019.104312
   Brammer H., 2009, Economic and Political Weekly, V44, P87
   Brammer H, 2014, CLIM RISK MANAG, V1, P51, DOI 10.1016/j.crm.2013.10.001
   Brown S, 2015, SCI TOTAL ENVIRON, V527, P362, DOI 10.1016/j.scitotenv.2015.04.124
   Chen J, 2018, NAT CLIM CHANGE, V8, P981, DOI 10.1038/s41558-018-0313-8
   Clarke D, 2015, ENVIRON SCI-PROC IMP, V17, P1127, DOI [10.1039/c4em00682h, 10.1039/C4EM00682H]
   Cohen DA, 2021, ENVIRON POLIT, V30, P687, DOI 10.1080/09644016.2020.1816380
   Comaroff Joshua., 2014, Harvard Design Magazine
   Cote M, 2012, PROG HUM GEOG, V36, P475, DOI 10.1177/0309132511425708
   Darby S.E., 2018, ECOSYSTEM SERVICES W, P277, DOI 10.1007/978-3-319-71093-8_15
   Dasgupta S., 2015, Let's Talk Development
   Dasgupta S, 2015, AMBIO, V44, P815, DOI 10.1007/s13280-015-0681-5
   Datta DK, 2010, MANAGEMENT AND SUSTAINABLE DEVELOPMENT OF COASTAL ZONE ENVIRONMENTS, P227, DOI 10.1007/978-90-481-3068-9_15
   Dearing J, 2018, ROU STUD ECOSYS SERV, P55
   Deb AK, 1998, OCEAN COAST MANAGE, V41, P63, DOI 10.1016/S0964-5691(98)00074-X
   Dedekorkut-Howes A, 2020, J ENVIRON PLANN MAN, V63, P2102, DOI 10.1080/09640568.2019.1708709
   Didar-Ul Islam SM, 2016, AQUACULT INT, V24, P1163, DOI 10.1007/s10499-016-9978-z
   Elliott Rebecca., 2021, Underwater: Loss, Flood Insurance, and the Moral Economy of Climate Change in the United States
   Forsyth Tim., 2002, CRITICAL POLITICAL E
   Fraser N, 2021, NEW LEFT REV, P94
   Goodbred SL, 2000, SEDIMENT GEOL, V133, P227, DOI 10.1016/S0037-0738(00)00041-5
   Guhathakurta M., 2008, Development (London), V51, P212, DOI 10.1057/dev.2008.15
   Haider MZ, 2013, J SOIL SCI PLANT NUT, V13, P417, DOI 10.4067/S0718-95162013005000033
   Hossain MS, 2013, REV ENVIRON SCI BIO, V12, P313, DOI 10.1007/s11157-013-9311-5
   Hossain MS, 2017, INT J SUST DEV WORLD, V24, P120, DOI 10.1080/13504509.2016.1182087
   Hossain MS, 2016, REG ENVIRON CHANGE, V16, P429, DOI 10.1007/s10113-014-0748-z
   International Bank for Reconstruction and Development, 1972, WAT LAND WAT RES SEC
   International Bank for Reconstruction and Development, 1972, REG DEV POT CONSTR L
   Islam MA, 2019, ENVIRON MANAGE, V64, P640, DOI 10.1007/s00267-019-01220-4
   Islam MA, 2020, SCI TOTAL ENVIRON, V727, DOI 10.1016/j.scitotenv.2020.138674
   Islam MS, 2009, SOC NATUR RESOUR, V22, P66, DOI 10.1080/08941920801942255
   Jasanoff S., 2004, STATES KNOWLEDGE COP
   Jasanoff S, 2010, THEOR CULT SOC, V27, P233, DOI 10.1177/0263276409361497
   Johnson FA, 2016, SUSTAIN SCI, V11, P423, DOI 10.1007/s11625-016-0356-6
   Kirkpatrick LO, 2015, J URBAN HIST, V41, P261, DOI 10.1177/0096144214563503
   Koslov L., 2019, City, V23, P658, DOI DOI 10.1080/13604813.2019.1690337
   Lamb Zachary., 2020, Louisiana's Response to Extreme Weather, P65
   Lave R., 2018, The Palgrave Handbook of Critical Physical Geography, P3, DOI [10.1007/978-3-319-71461-5_1, DOI 10.1007/978-3-319-71461-5_1, 10.1007/978-3-319-75620-2]
   Lázár AN, 2015, ENVIRON SCI-PROC IMP, V17, P1018, DOI [10.1039/c4em00600c, 10.1039/C4EM00600C]
   Mathews AS, 2016, J ROY ANTHROPOL INST, V22, P9, DOI 10.1111/1467-9655.12391
   Milkoreit M, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaaa75
   Nandy S., 1991, SOCIOECONOMIC DEMOGR
   Nicholls RJ, 2016, ESTUAR COAST SHELF S, V183, P370, DOI 10.1016/j.ecss.2016.08.017
   Nicholls R.J., 2004, 5 INT C ASIAN MARINE
   Paprocki K., 2021, Threatening dystopias: The global politics of climate change adaptation in Bangladesh, DOI 10.7591/cornell/9781501759154.001.0001
   Paprocki K, 2019, ANTIPODE, V51, P295, DOI 10.1111/anti.12421
   Paprocki K, 2014, J PEASANT STUD, V41, P1109, DOI 10.1080/03066150.2014.937709
   Paul BG, 2011, OCEAN COAST MANAGE, V54, P201, DOI 10.1016/j.ocecoaman.2010.12.001
   Payo A, 2017, EARTHS FUTURE, V5, P495, DOI 10.1002/2016EF000530
   Perry KK, 2021, GEOFORUM, V126, P361, DOI 10.1016/j.geoforum.2021.09.003
   Poncelet A., 2010, HOMMES MIGRATIONS, P16
   Poncelet A, 2010, ENVIRONMENT, FORCED MIGRATION AND SOCIAL VULNERABILITY, P211, DOI 10.1007/978-3-642-12416-7_16
   Prodhan S., 2016, INT J ENV AGR RES, V2, P33
   Qureshi AS, 2015, WATER RESOUR MANAG, V29, P4269, DOI 10.1007/s11269-015-1059-y
   Rahman AF, 2011, REMOTE SENS ENVIRON, V115, P3121, DOI 10.1016/j.rse.2011.06.019
   Rahman MM, 2000, ENVIRON GEOL, V40, P31, DOI 10.1007/s002540000152
   Rahman R., 2013, DISASTER RISK REDUCT, P65, DOI [10.1007/978-4-431-54252-0_4, 10.1007/978-4-431-54252-04, DOI 10.1007/978-4-431-54252-0_4]
   Rangan H, 2009, PROG HUM GEOG, V33, P28, DOI 10.1177/0309132508090215
   Riofrancos TN, 2017, PERSPECT POLIT, V15, P678, DOI 10.1017/S1537592717000901
   Rogers KG, 2017, ELEMENTA-SCI ANTHROP, V5, DOI 10.1525/elementa.250
   Safransky S, 2014, GEOFORUM, V56, P237, DOI 10.1016/j.geoforum.2014.06.003
   Salehin M., 2018, Ecosystem Services for Well-Being in Deltas, P333
   Sayre Nathan., 2015, The Routledge Handbook of Political Ecology, V1st, P504
   Schmidt CW, 2015, ENVIRON HEALTH PERSP, V123, pA204, DOI 10.1289/ehp.123-A204
   Schneider-Mayerson Matthew, 2017, RESILIENCE-ABINGDON, V4, P166
   Shampa M.I. M. P., 2012, INT J SCI TECHNOLOGY, V1, P1
   Sherin VR, 2020, CONT SHELF RES, V202, DOI 10.1016/j.csr.2020.104142
   Sousa D., 2019, PREPRINT
   Thomas J.W., 1972, Public Policy in the Reconstruction and Development of Rural Bangladesh
   Thomas KA, 2017, WATER POLICY, V19, P724, DOI 10.2166/wp.2017.109
   van Staveren MF, 2017, WATER POLICY, V19, P147, DOI 10.2166/wp.2016.029
   Wakefield S, 2022, URBAN STUD, V59, P917, DOI 10.1177/00420980211045523
   Watts M., 1997, GEOGRAPHIES EC, P71
   Watts M., 1983, INTERPRETATION CALAM, P23
   Watts M.J., 2015, ROUTLEDGE HDB POLITI, P19
   Whitington J., 2018, ANTHROPOGENIC RIVERS
   Whitington J, 2013, ANTHROPOL THEOR, V13, P308, DOI 10.1177/1463499613509992
   World Bank, 2016, CLIM CHANG POS URG T
   World Bank, 2013, BANGL 1 PHAS COAST E
   Zeiderman A, 2016, PUBLIC CULTURE, V28, P389, DOI 10.1215/08992363-3427499
   Zimmerer KarlS., 2003, Political Ecology: An Integrative Approach to Geography and Environment-Development Studies
NR 94
TC 13
Z9 14
U1 3
U2 17
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD MAR
PY 2022
VL 73
AR 102487
DI 10.1016/j.gloenvcha.2022.102487
EA FEB 2022
PG 10
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 1D3XV
UT WOS:000793737900010
OA Green Accepted, hybrid
DA 2025-01-10
ER

PT J
AU Ausseil, AGE
   Law, RM
   Parker, AK
   Teixeira, EI
   Sood, A
AF Ausseil, Anne-Gaelle E.
   Law, Richard M.
   Parker, Amber K.
   Teixeira, Edmar, I
   Sood, Abha
TI Projected Wine Grape Cultivar Shifts Due to Climate Change in New
   Zealand
SO FRONTIERS IN PLANT SCIENCE
LA English
DT Article
DE adaptation; cumulative thermal time; climate change; cultivar; wine
   grape; phenology
ID VITIS-VINIFERA L.; PHENOLOGICAL DEVELOPMENT; YIELD COMPONENTS; FROST
   DAMAGE; MODEL; TEMPERATURE; VARIABILITY; VITICULTURE; RESPONSES;
   SIMULATE
AB Climate change has already been affecting the regional suitability of grapevines with significant advances in phenology being observed globally in the last few decades. This has significant implications for New Zealand, where the wine industry represents a major share of the horticultural industry revenue. We modeled key crop phenological stages to better understand temporal and spatial shifts in three important regions of New Zealand (Marlborough, Hawke's Bay, Central Otago) for three dominant cultivars (Merlot, Pinot noir, and Sauvignon blanc) and one potential new and later ripening cultivar (Grenache). Simulations show an overall advance in flowering, veraison, and sugar ripeness by mid-century with more pronounced advance by the end of the century. Results show the magnitude of changes depends on the combination of greenhouse gas emission pathway, grape cultivar, and region. By mid-century, in the Marlborough region for instance, the four cultivars would flower 3 to 7 days earlier and reach sugar ripeness 7 to 15 days earlier depending on the greenhouse gas emission pathway. For growers to maintain the same timing of key phenological stages would require shifting planting of cultivars to more Southern parts of the country or implement adaptation strategies. Results also show the compression of time between flowering and veraison for all three dominant cultivars is due to a proportionally greater advance in veraison, particularly for Merlot in the Hawke's Bay and Pinot noir in Central Otago. Cross-regional analysis also raises the likelihood of the different regional cultivars ripening within a smaller window of time, complicating harvesting schedules across the country. However, considering New Zealand primarily accommodates cool climate viticulture cultivars, our results suggest that late ripening cultivars or extended ripening window in cooler regions may be advantageous in the face of climate change. These insights can inform New Zealand winegrowers with climate change adaptation options for their cultivar choices.
C1 [Ausseil, Anne-Gaelle E.] Manaaki Whenua Landcare Res, Wellington, New Zealand.
   [Law, Richard M.] Manaaki Whenua Landcare Res, Palmerston North, New Zealand.
   [Parker, Amber K.] Lincoln Univ, Fac Agr & Life Sci, Lincoln, New Zealand.
   [Teixeira, Edmar, I] Plant & Food Res, Lincoln, New Zealand.
   [Sood, Abha] Natl Inst Water & Atmospher Res, Wellington, New Zealand.
C3 Landcare Research - New Zealand; Landcare Research - New Zealand;
   Lincoln University - New Zealand; New Zealand Institute for Plant & Food
   Research Ltd; National Institute of Water & Atmospheric Research (NIWA)
   - New Zealand
RP Ausseil, AGE (corresponding author), Manaaki Whenua Landcare Res, Wellington, New Zealand.
EM ausseila@landcareresearch.co.nz
RI Ausseil, Anne-Gaelle/C-2195-2011; Law, Richard/KBQ-3437-2024; Parker,
   Amber/F-3431-2018
OI Law, Richard/0000-0002-7400-2530; Sood, Abha/0000-0002-0231-5757;
   Parker, Amber/0000-0002-3601-0951
FU Manaaki Whenua - Landcare Research Strategic Science Investment Funding
   for Crown Research Institutes; New Zealand Ministry for Business,
   Innovation and Employment's Our Land and Water National Science
   Challenge (Toitu te Whenua, Toiora te Wai); Deep South Challenge, as
   part of the Incorporating Climate change impacts in Land-use suitability
   programme [C10X1507]
FX This work was co-funded by Manaaki Whenua - Landcare Research Strategic
   Science Investment Funding for Crown Research Institutes and the New
   Zealand Ministry for Business, Innovation and Employment's Our Land and
   Water National Science Challenge (Toitu te Whenua, Toiora te Wai) and
   Deep South Challenge, contract C10X1507, as part of the Incorporating
   Climate change impacts in Land-use suitability programme.
CR Anderson K., 2013, Which Winegrape Varieties are Grown Where?, A global empirical picture
   Belliveau S, 2006, GLOBAL ENVIRON CHANG, V16, P364, DOI 10.1016/j.gloenvcha.2006.03.003
   Berkes F., 1994, LINKING SOCIAL ECOLO, P1
   Bindi M, 2001, EUR J AGRON, V14, P145, DOI 10.1016/S1161-0301(00)00093-9
   Chuine I, 2004, NATURE, V432, P289, DOI 10.1038/432289a
   Cook BI, 2016, NAT CLIM CHANGE, V6, P715, DOI [10.1038/NCLIMATE2960, 10.1038/nclimate2960]
   Cradock-Henry NA, 2019, ENVIRON SCI POLICY, V94, P182, DOI 10.1016/j.envsci.2019.01.015
   Cuccia C, 2014, J INT SCI VIGNE VIN, V48, P169
   de Cortázar-Atauri IG, 2010, HOLOCENE, V20, P599, DOI 10.1177/0959683609356585
   de Rességuier L, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.00515
   Duchêne E, 2005, AGRON SUSTAIN DEV, V25, P93, DOI 10.1051/agro:2004057
   Duchêne E, 2010, CLIM RES, V41, P193, DOI 10.3354/cr00850
   Ewert F., 2015, Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (Ag- MIP) Integrated Crop and Economic Assessments, P261
   Fleming Aysha, 2015, Journal of Wine Research, V26, P99, DOI 10.1080/09571264.2015.1031883
   Friend AP, 2007, AUST J GRAPE WINE R, V13, P157, DOI 10.1111/j.1755-0238.2007.tb00246.x
   Hochberg U, 2015, INT J MOL SCI, V16, P24276, DOI 10.3390/ijms161024276
   Hunter JJ, 2011, S AFR J ENOL VITIC, V32, P137
   Ioannou Leonidas G, 2017, Temperature (Austin), V4, P330, DOI 10.1080/23328940.2017.1338210
   Jones G. V., 2005, XIV International GESCO Viticulture Congress, Geisenheim, Germany, 23-27 August, 2005, P54
   Jones GV, 2005, CLIMATIC CHANGE, V73, P319, DOI 10.1007/s10584-005-4704-2
   Jones Norman K., 2012, Journal of Wine Research, V23, P103, DOI 10.1080/09571264.2012.678933
   KLIEWER WM, 1977, AM J ENOL VITICULT, V28, P215
   Le Roux R., 2016, 11 INT TERR C WILL V
   Manaaki Whenua-Landcare Research, 2004, NZ LANDC DAT LCDB VE
   Manaaki Whenua-Landcare Research, 2018, NZ LAND RES INV NZLR
   Martinez-Lüscher J, 2016, FRONT ENV SCI-SWITZ, V4, DOI 10.3389/fenvs.2016.00048
   Ministry for Primary Industries, 2021, SITUATION OUTLOOK PR
   Ministry for the Environment, 2018, CLIM CHANG PROJ NZ A
   Molitor D, 2014, AUST J GRAPE WINE R, V20, P160, DOI 10.1111/ajgw.12059
   Molitor D, 2020, AGR FOREST METEOROL, V291, DOI 10.1016/j.agrformet.2020.108024
   Molitor D, 2014, AM J ENOL VITICULT, V65, P72, DOI 10.5344/ajev.2013.13066
   Morales-Castilla I, 2020, P NATL ACAD SCI USA, V117, P2864, DOI 10.1073/pnas.1906731117
   Moran M, 2019, AM J ENOL VITICULT, V70, P9, DOI 10.5344/ajev.2018.18031
   Mosedale JR, 2016, GLOBAL CHANGE BIOL, V22, P3814, DOI 10.1111/gcb.13406
   Mosedale JR, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0141218
   New Zealand Winegrowers, 2020, VIN REG REP 2019 202
   Parker A., 2014, P 10 INT TERR C TOK, V2, P105
   Parker AK, 2011, AUST J GRAPE WINE R, V17, P206, DOI 10.1111/j.1755-0238.2011.00140.x
   Parker A. K., 2015, 19 INT S GROUP INT E, P271
   Parker A, 2013, AGR FOREST METEOROL, V180, P249, DOI 10.1016/j.agrformet.2013.06.005
   Parker AK, 2020, OENO ONE, V54, P955, DOI 10.20870/oeno-one.2020.54.4.3861
   Parker AK, 2020, AGR FOREST METEOROL, V285, DOI 10.1016/j.agrformet.2020.107902
   Petrie PR, 2008, AUST J GRAPE WINE R, V14, P33, DOI 10.1111/j.1755-0238.2008.00005.x
   Petrie PR, 2017, AUST J GRAPE WINE R, V23, P378, DOI 10.1111/ajgw.12303
   Ramos MC, 2020, EUR J AGRON, V115, DOI 10.1016/j.eja.2020.126014
   Reineke A, 2016, J PEST SCI, V89, P313, DOI 10.1007/s10340-016-0761-8
   Rosenzweig C, 2013, AGR FOREST METEOROL, V170, P166, DOI 10.1016/j.agrformet.2012.09.011
   Salinger MJ, 2020, CLIMATIC CHANGE, V162, P485, DOI 10.1007/s10584-020-02730-5
   Salinger MJ, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab012a
   Santos JA, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10093092
   Schultz HR, 2010, AUST J GRAPE WINE R, V16, P4, DOI 10.1111/j.1755-0238.2009.00074.x
   Schultze SR, 2019, J APPL METEOROL CLIM, V58, P1141, DOI 10.1175/JAMC-D-18-0183.1
   Sgubin G, 2018, AGR FOREST METEOROL, V250, P226, DOI 10.1016/j.agrformet.2017.12.253
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Sturman A, 2017, OENO ONE, V51, P99, DOI 10.20870/oeno-one.2016.0.0.1538
   Tait A, 2016, UPDATED CLIMATE CHAN
   Tait A, 2006, INT J CLIMATOL, V26, P2097, DOI 10.1002/joc.1350
   Prats-Llinàs MT, 2020, SCI HORTIC-AMSTERDAM, V262, DOI 10.1016/j.scienta.2019.109065
   Trought MCT, 2015, ACTA HORTIC, V1082, P397, DOI 10.17660/ActaHortic.2015.1082.55
   Trought MCT, 2011, AUST J GRAPE WINE R, V17, P72, DOI 10.1111/j.1755-0238.2010.00120.x
   Van Leeuwen Cornelis, 2006, Journal of Wine Research, V17, P1, DOI 10.1080/09571260600633135
   van Leeuwen C, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9090514
   van Leeuwen C, 2016, J WINE ECON, V11, P150, DOI 10.1017/jwe.2015.21
   Verdugo-Vásquez N, 2020, PRECIS AGRIC, V21, P107, DOI 10.1007/s11119-019-09657-7
   Wang EL, 1998, AGR SYST, V58, P1, DOI 10.1016/S0308-521X(98)00028-6
   Wang XQ, 2020, OENO ONE, V54, P637, DOI 10.20870/oeno-one.2020.54.3.3195
   Webb LB, 2007, AUST J GRAPE WINE R, V13, P165, DOI 10.1111/j.1755-0238.2007.tb00247.x
   Wine Marlborough, 2019, WIN MARLB WEBS
   Wolkovich E., 2019, Wine and Viticulture Journal, V34, P48
NR 69
TC 26
Z9 27
U1 0
U2 42
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 1664-462X
J9 FRONT PLANT SCI
JI Front. Plant Sci.
PD APR 21
PY 2021
VL 12
AR 618039
DI 10.3389/fpls.2021.618039
PG 14
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA RX1SX
UT WOS:000647002100001
PM 33968094
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Laudari, HK
   Aryal, K
   Bhusal, S
   Maraseni, T
AF Laudari, Hari Krishna
   Aryal, Kishor
   Bhusal, Shreejana
   Maraseni, Tek
TI What lessons do the first Nationally Determined Contribution (NDC)
   formulation process and implementation outcome provide to the
   enhanced/updated NDC? A reality check from Nepal
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Adaptation; Mitigation; Climate action; Discourse;
   Discursive institutionalism
ID CLIMATE-CHANGE ADAPTATION; DISCURSIVE INSTITUTIONALISM; PARIS AGREEMENT;
   ECOSYSTEM SERVICES; POLICY; DISCOURSE; PARTICIPATION; VALUES; IDEAS;
   COMMUNITIES
AB Nationally Determined Contributions (NDCs) are the foundation of the Paris Agreement. So far, 190 Parties have submitted their NDCs. But how the NDC can be made comprehensive, unanimous and implementable so that the Paris climate goals can be achieved has been a matter of growing concern among policymakers, academics, and practitioners. Aiming to bridge the knowledge gap about institutional deliberation of NDCs, we assessed the formulation process and implementation outcome of Nepal's first NDC by employing qualitative research methods. We undertook semi-structured interviews (n = 10) with all experts and bureaucrats engaged in the NDC formulation process. Moreover, we conducted group discussions (n = 18) with nine stakeholder groups and key informant surveys (n = 12) with four stakeholder groups representing cross-sectoral ministries, private-sector, (retired) bureaucrats, and media people. We also reviewed contemporary literature and progress report of sectoral governments and other related institutions. The collected data were then analyzed by applying the discursive institutional framework. As NDC is a national political plan of climate action and demands support and commitment from a wide spectrum of society, our results, however, revealed that Nepal's first NDC was formulated without engaging politicians and the other major state and non-state actors. Moreover, the country's NDC was framed and articulated only for fulfilling international obligation (or commitment) and getting international fund, but not as a determined national climate plan of action for expediting climate action at (sub) national level. Our analysis further found that very few institutions including policies, programmes, and budgets were arranged for translating targets of the NDC into action. Because of these shortcomings, Nepal's first NDC could not achieve most of its stipulated targets. Based on the analysis and results of our study, we have discussed and recommended some pathways that are critical for the formulation and implementation of enhanced/updated NDCs in Nepal and the other countries. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Laudari, Hari Krishna; Bhusal, Shreejana] Minist Forests & Environm, Kathmandu, Nepal.
   [Aryal, Kishor] Minist Ind Tourism Forests & Environm, Dhangadhi, Sudoorpaschim P, Nepal.
   [Maraseni, Tek] Univ Southern Queensland, Toowoomba, Qld 4350, Australia.
   [Maraseni, Tek] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China.
C3 University of Southern Queensland; Chinese Academy of Sciences
RP Laudari, HK (corresponding author), Minist Forests & Environm, Kathmandu, Nepal.
EM hklaudari@gmail.com
RI Laudari, Hari Krishna/GNM-9819-2022
OI Maraseni, Tek/0000-0001-9361-1983; Laudari, Hari
   Krishna/0000-0002-4094-0721; Aryal, Kishor/0000-0001-6766-7123
CR ADB, 2013, SOL WAST MAN NEP CUR
   Adger WN, 2005, ECOL SOC, V10
   AEPC, 2019, PROGR GLANC YEAR REV
   Agarwal B, 2001, WORLD DEV, V29, P1623, DOI 10.1016/S0305-750X(01)00066-3
   [Anonymous], [No title captured]
   [Anonymous], 2018, INT FOREST REV
   Arts B, 2009, FOREST POLICY ECON, V11, P340, DOI 10.1016/j.forpol.2008.10.004
   Aryal K, 2020, INT J SUST DEV WORLD, V27, P28, DOI 10.1080/13504509.2019.1627681
   Averchenkova A., 2016, Beyond the Targets: Assessing the Political Credibility of Pledges for the Paris Agreement
   Ayers J, 2011, IDS BULL-I DEV STUD, V42, P70, DOI 10.1111/j.1759-5436.2011.00224.x
   Baral S, 2018, FOREST POLICY ECON, V91, P19, DOI 10.1016/j.forpol.2017.10.007
   Bhatta Laxmi D., 2015, International Journal of Biodiversity Science Ecosystem Services & Management, V11, P145, DOI 10.1080/21513732.2015.1027793
   Buijs A, 2014, LAND USE POLICY, V38, P676, DOI 10.1016/j.landusepol.2014.01.010
   Burton P, 2013, URBAN POLICY RES, V31, P399, DOI 10.1080/08111146.2013.778196
   Busico G, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11247166
   Cannon T, 2010, NAT HAZARDS, V55, P621, DOI 10.1007/s11069-010-9499-4
   Carstensen MB, 2016, J EUR PUBLIC POLICY, V23, P318, DOI 10.1080/13501763.2015.1115534
   Castelló I, 2011, J BUS ETHICS, V100, P11, DOI 10.1007/s10551-011-0770-8
   De Pinto A, 2018, CLIM POLICY, V18, P612, DOI 10.1080/14693062.2017.1321521
   den Besten JW, 2014, ENVIRON SCI POLICY, V35, P40, DOI 10.1016/j.envsci.2013.03.009
   Devkota D.C., 2012, CLIMATE CHANGE UNFCC, P29
   DFRS, 2015, State of Nepal's forest
   Dryzek JS, 2008, AM POLIT SCI REV, V102, P481, DOI 10.1017/S0003055408080325
   Fuji Shizuoka Airport, 2020, BUS REP 15 FISC YEAR
   Gentle P, 2012, ENVIRON SCI POLICY, V21, P24, DOI 10.1016/j.envsci.2012.03.007
   GGGI, 2018, NAT ACT PLAN EL MOB
   Grant D., 2001, INT STUD MANAG ORG, V31, P5, DOI DOI 10.1080/00208825.2001.11656818
   Hajer M., 1993, ARGUMENTATIVE TURN P, P43
   Hajer M.A., 2003, POLITICS ENV DISCOUR, DOI [DOI 10.1093/019829333X.001.0001, 10.1093/019829333X.001.0001]
   Haque AKE, 2019, CLIMATIC CHANGE, V155, P237, DOI 10.1007/s10584-019-02417-6
   Höhne N, 2018, CLIM POLICY, V18, P425, DOI 10.1080/14693062.2017.1294046
   Hsu A, 2020, CLIM POLICY, V20, P443, DOI 10.1080/14693062.2019.1624252
   IPCC, 2018, GLOBAL WARMING 15 C, V1st, DOI [10.1017/9781009157940, DOI 10.1017/9781009157940]
   Jernnäs M, 2019, GLOBAL ENVIRON CHANG, V55, P73, DOI 10.1016/j.gloenvcha.2019.01.006
   Kangas OE, 2014, EUR POLIT SCI REV, V6, P73, DOI 10.1017/S1755773912000306
   Kingdon JohnW., 2011, Longman classics in political science updated, V2nd
   Kishor Sharma Kishor Sharma, 2006, Journal of International Development, V18, P553, DOI 10.1002/jid.1252
   Klein RJT, 2005, ENVIRON SCI POLICY, V8, P579, DOI 10.1016/j.envsci.2005.06.010
   Laudari HK, 2020, LAND USE POLICY, V91, DOI 10.1016/j.landusepol.2019.104338
   Lee TM, 2015, NAT CLIM CHANGE, V5, P1014, DOI 10.1038/NCLIMATE2728
   Lovric M, 2018, J NAT CONSERV, V43, P46, DOI 10.1016/j.jnc.2018.02.005
   Lovric N, 2018, LAND USE POLICY, V79, P30, DOI 10.1016/j.landusepol.2018.07.038
   Lovric N, 2018, FOREST POLICY ECON, V87, P20, DOI 10.1016/j.forpol.2017.11.003
   Maraseni TN, 2020, J ENVIRON MANAGE, V269, DOI 10.1016/j.jenvman.2020.110763
   Mbeva K., 2016, SELF DIFFERENTIATION
   Metz J.J., 1995, GEO J, V35, P175, DOI [DOI 10.1007/BF00814063, 10.1007/BF00814063]
   Miller CA, 2000, ENVIRON VALUE, V9, P211, DOI 10.3197/096327100129342047
   MoF, 2019, EC SURVEY
   MoF, 2018, EC SURVEY
   MoF, 2019, BUDGET SPEECH
   MoF, 2018, BUDGET SPEECH
   MoFALD, 2016, COMP BEST PRACT ENV
   MoFE, 2020, E VEH FEAS ASS
   MoFE, 2020, YEARL DEV PROGR FISC
   MoFE, 2020, PREP NEP STAT PAP NE
   MoFE, 2020, REP PRES STAT FOR SE
   MoFE, 2019, NAT CLIM CHANG POL 2
   MoFSC, 2016, FOR SECT STRAT 2016
   MoPE, 2016, Intended Nationally Determined Contributions
   MoSTE, 2014, 2 NAT COMM UN FRAM C
   Nakarmi AM, 2020, AIR QUAL ATMOS HLTH, V13, P361, DOI 10.1007/s11869-020-00799-6
   NMA, 2007, Climate Change National Adaptation Programme of Action (NAPA) of Ethiopia
   NPC, 2019, MED TERM EXP REP 201
   Ojha HR, 2016, CLIM POLICY, V16, P415, DOI 10.1080/14693062.2014.1003775
   Oldekop JA, 2019, NAT SUSTAIN, V2, P421, DOI 10.1038/s41893-019-0277-3
   Pandey A., 2019, CLIMATE RESILIENT PA
   Panizza F, 2013, POLIT STUD-LONDON, V61, P301, DOI 10.1111/j.1467-9248.2012.00967.x
   Pauw WP, 2020, CLIM POLICY, V20, P468, DOI 10.1080/14693062.2019.1635874
   Pauw WP, 2018, CLIMATIC CHANGE, V147, P23, DOI 10.1007/s10584-017-2122-x
   Polk E, 2020, FRONT COMMUN, V5, DOI 10.3389/fcomm.2020.00006
   Poudyal BH, 2020, ENVIRON SCI POLICY, V106, P111, DOI 10.1016/j.envsci.2020.01.022
   Pradhan BB, 2017, ENRGY PROCED, V138, P470, DOI 10.1016/j.egypro.2017.10.227
   Prinn R, 1999, CLIMATIC CHANGE, V41, P469, DOI 10.1023/A:1005326126726
   Rajamani L, 2016, INT COMP LAW Q, V65, P493, DOI 10.1017/S0020589316000130
   REDD IC, 2020, REDD IC ANN REP FISC
   Regmi B.R., 2013, Journal of Forest and Livelihood, V11, P43, DOI DOI 10.3126/JFL.V11I1.8612
   Röser F, 2020, CLIM POLICY, V20, P415, DOI 10.1080/14693062.2019.1708697
   Rogelj J, 2016, NATURE, V534, P631, DOI 10.1038/nature18307
   Ruseva T, 2019, POLICY STUD J, V47, pS66, DOI 10.1111/psj.12317
   Rutt RL, 2015, FOREST POLICY ECON, V60, P50, DOI 10.1016/j.forpol.2014.06.005
   Sartohadi J., 2014, J ENV PROTECTION, V05, P772, DOI [10.4236/jep.2014.59079, DOI 10.4236/JEP.2014.59079]
   Schmidt VA, 2008, ANNU REV POLIT SCI, V11, P303, DOI 10.1146/annurev.polisci.11.060606.135342
   Schmidt VA, 2011, CRIT POLICY STUD, V5, P106, DOI 10.1080/19460171.2011.576520
   Schmidt VA, 2010, EUR POLIT SCI REV, V2, P1, DOI 10.1017/S175577390999021X
   Shukla P.R., 2019, Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, P41
   Singh P.M., 2019, POLICY GAPS NEEDS AN
   Sodari K.B., 2018, J. Inst. Eng., V14, P151
   Tobin P, 2018, GLOBAL ENVIRON CHANG, V48, P11, DOI 10.1016/j.gloenvcha.2017.11.002
   UNFCCC, 2016, NDC CYCL PAR AGR
   Urwin K, 2008, GLOBAL ENVIRON CHANG, V18, P180, DOI 10.1016/j.gloenvcha.2007.08.002
   van Oort B, 2015, ECOSYST SERV, V13, P70, DOI 10.1016/j.ecoser.2014.11.004
   van Soest HL, 2017, CLIMATIC CHANGE, V144, P165, DOI 10.1007/s10584-017-2027-8
   Wagley P., 2019, NEPAL PARIS AGREEMEN
   Wahlström N, 2018, J EDUC POLICY, V33, P163, DOI 10.1080/02680939.2017.1344879
   WTTC, 2018, Travel tourism economic impact
   Zhang BB, 2018, NAT CLIM CHANGE, V8, P370, DOI 10.1038/s41558-018-0122-0
NR 96
TC 26
Z9 27
U1 3
U2 20
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD MAR 10
PY 2021
VL 759
AR 143509
DI 10.1016/j.scitotenv.2020.143509
EA JAN 2021
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA PP3JZ
UT WOS:000605764100066
PM 33198995
DA 2025-01-10
ER

PT J
AU Schernewski, G
   Schumacher, J
   Weisner, E
   Donges, L
AF Schernewski, Gerald
   Schumacher, Johanna
   Weisner, Eva
   Donges, Larissa
TI A combined coastal protection, realignment and wetland restoration
   scheme in the southern Baltic: planning process, public information and
   participation
SO JOURNAL OF COASTAL CONSERVATION
LA English
DT Article; Proceedings Paper
CT Conference on Changing Littoral - Anticipation and Adaptation to Climate
   Change (Littoral)
CY 2016
CL Biarritz, FRANCE
SP EUCC France, Coastal & Marine Union
DE Hutelmoor; Climate change adaptation; Public perception; Systems
   approach framework; Integrated coastal zone management; Sea level rise;
   Erosion; Brackish moors
ID MANAGED REALIGNMENT; CLIMATE-CHANGE; PERCEPTIONS; EUROPE
AB Markgrafenheide-Hutelmoor covers a total area of 1000 ha (about 490 ha are coastal moor) and a coastline of about 6 km. This touristy area belongs to the city of Rostock in Germany. As response to sea level rise and heavy coastal erosion, the small seaside resort Markgrafenheide received a comprehensive storm surge protection until 2006. Subsequently, the adjacent Hutelmoor was flooded with the aim to restore it as a brackish coastal moor. Coastal protection measures at the Baltic Sea coastline were abandoned to enable natural dynamics, a coastal realignment and salt water intrusions. The entire process until full implementation took 14 years and was associated with very problematic public participation and a strong local polarization. Based on a literature and media review, two surveys, and expert interviews we retrospectively document and analyse the planning process with focus on public information, perception and participation. The local population and holidaymakers did not perceive coastal changes and if, did not associate them with climate change. Interviewees remembered single storm surges, but felt save from it and sea level rise was not perceived as a threat. 89% said that they feel insufficiently informed about the combined coastal protection wetland restoration measure, but did not use the offered information possibilities. 81% had their information from newspapers and freely distributed advertisers. It seems that insufficient information was the major reason for the problems with local acceptance and public participation. The media played a dominating role. The decline of traditional newspapers and the growths of free advertisers seemed to have a negative impact on quality of information and favoured a polarization. Additionally, we discuss local specifics like the cultural background (GDR history), traditions, frustration and the relatively old population and their role in public participation. We strongly promote a pro-active and long-term information and public relation strategy.
C1 [Schernewski, Gerald; Schumacher, Johanna; Weisner, Eva; Donges, Larissa] Leibniz Inst Baltic Sea Res Warnemunde, Coastal Res & Management Grp, Seestr 15, D-18119 Rostock, Germany.
   [Schernewski, Gerald] Klaipeda Univ, Marine Sci & Technol Ctr, Herkus Mantas G 84, LT-92294 Klaipeda, Lithuania.
C3 Leibniz Institut fur Ostseeforschung Warnemunde; Klaipeda University
RP Schernewski, G (corresponding author), Leibniz Inst Baltic Sea Res Warnemunde, Coastal Res & Management Grp, Seestr 15, D-18119 Rostock, Germany.; Schernewski, G (corresponding author), Klaipeda Univ, Marine Sci & Technol Ctr, Herkus Mantas G 84, LT-92294 Klaipeda, Lithuania.
EM gerald.schernewski@io-warnemuende.de
OI Schumacher, Johanna/0000-0003-4881-7776; Schernewski,
   Gerald/0000-0002-4036-7646
FU BONUS BaltCoast project; BONUS from the European Union's Seventh
   Programme for research, technological development and demonstration
   [185]; Baltic Sea national funding institutions
FX The work was part-funded by the BONUS BaltCoast project. BONUS BaltCoast
   has received funding from BONUS (Art 185) funded jointly from the
   European Union's Seventh Programme for research, technological
   development and demonstration, and from Baltic Sea national funding
   institutions. We would also like to express special thanks to the StALU
   MM (Staatliches Amt fur Landwirtschaft und Umwelt Mittleres
   Mecklenburg), especially Dr. Sonja Leipe, for providing background
   information, documents and expertise as well as to all interview
   partners and survey respondents.
CR [Anonymous], STAT JB 2016
   [Anonymous], KUSTENSCHUTZ OSTSEEK
   [Anonymous], NORDOESTLICHE HEIDE
   [Anonymous], P INT C COAST CONS M
   [Anonymous], 2013, ESTUARINE COASTAL MA
   [Anonymous], 2009, REG KUST MECKL VORP
   [Anonymous], ANZEIGENBLATTER GRAT
   Church JA, 2011, SURV GEOPHYS, V32, P585, DOI 10.1007/s10712-011-9119-1
   Esteves LS, 2014, J COASTAL RES, P407, DOI 10.2112/SI70-069.1
   Esteves LS, 2013, J COASTAL RES, P933, DOI 10.2112/SI65-158.1
   Gudowsky N., 2013, Journal of Public Deliberation, V9, DOI DOI 10.16997/JDD.152
   Gumiero B, 2013, ECOL ENG, V56, P36, DOI 10.1016/j.ecoleng.2012.12.103
   Hahn J, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0140657
   Hopkins TS, 2012, ECOL SOC, V17, DOI 10.5751/ES-05266-170339
   Innes J. E., 2004, Planning Theory & Practice, V5, P419, DOI DOI 10.1080/1464935042000293170
   Klötzli F, 2001, RESTOR ECOL, V9, P209, DOI 10.1046/j.1526-100x.2001.009002209.x
   Koebsch F, 2013, J GEOPHYS RES-BIOGEO, V118, P940, DOI 10.1002/jgrg.20069
   Miegel K, 2016, HYDROL WASSERBEWIRTS, V60, P242, DOI 10.5675/HyWa_2016.4_1
   Milligan J, 2007, COAST MANAGE, V35, P499, DOI 10.1080/08920750701525800
   Myatt LB, 2003, J ENVIRON MANAGE, V68, P173, DOI 10.1016/S0301-4797(03)00065-3
   O'Faircheallaigh C, 2010, ENVIRON IMPACT ASSES, V30, P19, DOI 10.1016/j.eiar.2009.05.001
   Piwowarczyk J, 2012, AMBIO, V41, P645, DOI 10.1007/s13280-012-0327-9
   Reed MS, 2009, J ENVIRON MANAGE, V90, P1933, DOI 10.1016/j.jenvman.2009.01.001
   Richter A, 2012, PHYS CHEM EARTH, V53-54, P43, DOI 10.1016/j.pce.2011.04.011
   Roca E, 2012, OCEAN COAST MANAGE, V60, P38, DOI 10.1016/j.ocecoaman.2012.01.002
   Rouillard JJ, 2014, LAND USE POLICY, V38, P637, DOI 10.1016/j.landusepol.2014.01.011
   Rupp-Armstrong S, 2007, J COASTAL RES, V23, P1418, DOI 10.2112/04-0426.1
   Schernewski G, 2017, J COASTAL CONSERVATI, P1
   Turner RK, 2007, GLOBAL ENVIRON CHANG, V17, P397, DOI 10.1016/j.gloenvcha.2007.05.006
   Upham P., 2009, Public A6tudes to environmental change: A selective review of theory and practice
   Wachinger G, 2013, RISK ANAL, V33, P1049, DOI 10.1111/j.1539-6924.2012.01942.x
   Weber EU, 2010, WIRES CLIM CHANGE, V1, P332, DOI 10.1002/wcc.41
   Weisner E, 2013, J COASTAL RES, P1963
NR 33
TC 24
Z9 25
U1 2
U2 58
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1400-0350
EI 1874-7841
J9 J COAST CONSERV
JI J. Coast. Conserv.
PD JUN
PY 2018
VL 22
IS 3
SI SI
BP 533
EP 547
DI 10.1007/s11852-017-0542-4
PG 15
WC Biodiversity Conservation; Environmental Sciences; Marine & Freshwater
   Biology; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Science (CPCI-S)
SC Biodiversity & Conservation; Environmental Sciences & Ecology; Marine &
   Freshwater Biology; Water Resources
GA GI0NA
UT WOS:000434065500007
OA Bronze
DA 2025-01-10
ER

PT J
AU Huang, QY
   Sauer, JR
   Dubayah, RO
AF Huang, Qiongyu
   Sauer, John R.
   Dubayah, Ralph O.
TI Multidirectional abundance shifts among North American birds and the
   relative influence of multifaceted climate factors
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE abundance shift; bird; breeding bird survey; climate change fingerprint;
   climate change metrics; climate change velocity; density shift;
   multidirectional distribution shift
ID SPECIES DISTRIBUTION; POLEWARD SHIFTS; POPULATION-CHANGE; RANGE SHIFTS;
   DISTRIBUTIONS; TEMPERATURE; RESPONSES; IMPACTS; PRECIPITATION;
   FINGERPRINT
AB Shifts in species distributions are major fingerprint of climate change. Examining changes in species abundance structures at a continental scale enables robust evaluation of climate change influences, but few studies have conducted these evaluations due to limited data and methodological constraints. In this study, we estimate temporal changes in abundance from North American Breeding Bird Survey data at the scale of physiographic strata to examine the relative influence of different components of climatic factors and evaluate the hypothesis that shifting species distributions are multidirectional in resident bird species in North America. We quantify the direction and velocity of the abundance shifts of 57 permanent resident birds over 44 years using a centroid analysis. For species with significant abundance shifts in the centroid analysis, we conduct a more intensive correlative analysis to identify climate components most strongly associated with composite change of abundance within strata. Our analysis focus on two contrasts: the relative importance of climate extremes vs. averages, and of temperature vs. precipitation in strength of association with abundance change. Our study shows that 36 species had significant abundance shifts over the study period. The average velocity of the centroid is 5.89 km.yr(-1). The shifted distance on average covers 259 km, 9% of range extent. Our results strongly suggest that the climate change fingerprint in studied avian distributions is multidirectional. Among 6 directions with significant abundance shifts, the northwestward shift was observed in the largest number of species (n = 13). The temperature/average climate model consistently has greater predictive ability than the precipitation/extreme climate model in explaining strata-level abundance change. Our study shows heterogeneous avian responses to recent environmental changes. It highlights needs for more species-specific approaches to examine contributing factors to recent distributional changes and for comprehensive conservation planning for climate change adaptation.
C1 [Huang, Qiongyu] Smithsonian Conservat Biol Inst, Front Royal, VA 22630 USA.
   [Huang, Qiongyu; Dubayah, Ralph O.] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.
   [Sauer, John R.] US Geol Survey, Patuxent Wildlife Res Ctr, Laurel, MD USA.
C3 Smithsonian Institution; Smithsonian National Zoological Park &
   Conservation Biology Institute; University System of Maryland;
   University of Maryland College Park; United States Department of the
   Interior; United States Geological Survey
RP Huang, QY (corresponding author), Smithsonian Conservat Biol Inst, Front Royal, VA 22630 USA.
EM qiongqionghuang@gmail.com
OI Huang, Qiongyu/0000-0002-1450-3587
FU Smithsonian Fellowship
FX Smithsonian Fellowship
CR [Anonymous], 2015, dismo: Species distribution modeling. R package version 1.0-12
   [Anonymous], 2003, The Structure and Dynamics of Geographic Ranges
   Araújo MB, 2007, GLOBAL ECOL BIOGEOGR, V16, P743, DOI 10.1111/j.1466-8238.2007.00359.x
   Baker DJ, 2016, GLOBAL CHANGE BIOL, V22, P2392, DOI 10.1111/gcb.13273
   Barbet-Massin M, 2014, DIVERS DISTRIB, V20, P1285, DOI 10.1111/ddi.12229
   Biau G, 2012, J MACH LEARN RES, V13, P1063
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Brown JL, 2015, ECOL EVOL, V5, P1131, DOI 10.1002/ece3.1418
   Brown JH, 1996, ANNU REV ECOL SYST, V27, P597, DOI 10.1146/annurev.ecolsys.27.1.597
   Cavanaugh KC, 2015, GLOBAL CHANGE BIOL, V21, P1928, DOI 10.1111/gcb.12843
   Cavanaugh KC, 2014, P NATL ACAD SCI USA, V111, P723, DOI 10.1073/pnas.1315800111
   Chan WP, 2016, SCIENCE, V351, P1437, DOI 10.1126/science.aab4119
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Coristine LE, 2015, ECOL EVOL, V5, P5162, DOI 10.1002/ece3.1683
   Crozier L, 2003, OECOLOGIA, V135, P648, DOI 10.1007/s00442-003-1219-2
   Currie DJ, 2017, GLOBAL ECOL BIOGEOGR, V26, P333, DOI 10.1111/geb.12538
   Deblauwe V, 2016, GLOBAL ECOL BIOGEOGR, V25, P443, DOI 10.1111/geb.12426
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Franklin J, 2013, GLOBAL CHANGE BIOL, V19, P473, DOI 10.1111/gcb.12051
   Gaüzère P, 2017, GLOBAL CHANGE BIOL, V23, P2218, DOI 10.1111/gcb.13500
   Gillings S, 2015, GLOBAL CHANGE BIOL, V21, P2155, DOI 10.1111/gcb.12823
   Goetz SJ, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034013
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Hickling R, 2006, GLOBAL CHANGE BIOL, V12, P450, DOI 10.1111/j.1365-2486.2006.01116.x
   Hitch AT, 2007, CONSERV BIOL, V21, P534, DOI 10.1111/j.1523-1739.2006.00609.x
   Huang QY, 2016, ECOGRAPHY, V39, P54, DOI 10.1111/ecog.01447
   Huang QY, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103236
   Illán JG, 2014, GLOBAL CHANGE BIOL, V20, P3351, DOI 10.1111/gcb.12642
   JEFFREE EP, 1994, FUNCT ECOL, V8, P640, DOI 10.2307/2389927
   Karl TR, 1999, CLIMATIC CHANGE, V42, P3, DOI 10.1023/A:1005491526870
   Kumar S., 2009, J ECOL NAT ENV, P94
   La Sorte FA, 2007, ECOLOGY, V88, P1803, DOI 10.1890/06-1072.1
   Lenoir J, 2013, GLOBAL CHANGE BIOL, V19, P1470, DOI 10.1111/gcb.12129
   Link WA, 2002, ECOLOGY, V83, P2832, DOI 10.2307/3072019
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Maclean IMD, 2008, GLOBAL CHANGE BIOL, V14, P2489, DOI 10.1111/j.1365-2486.2008.01666.x
   Massimino D, 2015, BIRD STUDY, V62, P523, DOI 10.1080/00063657.2015.1089835
   Menne MJ, 2009, B AM METEOROL SOC, V90, P993, DOI 10.1175/2008BAMS2613.1
   Midgley GF, 2006, DIVERS DISTRIB, V12, P555, DOI 10.1111/j.1366-9516.2006.00273.x
   Nix H., 1986, ATLAS ELAPID SNAKES, P15
   North American Bird Conservation Initiative, 2014, STAT BIRDS US 2014
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Parmesan C, 1999, NATURE, V399, P579, DOI 10.1038/21181
   Parmesan C, 2000, B AM METEOROL SOC, V81, P443, DOI 10.1175/1520-0477(2000)081<0443:IOEWAC>2.3.CO;2
   Pournelle G. H., 1953, Journal of Mammalogy, V34, P133
   Rapacciuolo G, 2014, GLOBAL CHANGE BIOL, V20, P2841, DOI 10.1111/gcb.12638
   Rittenhouse CD, 2012, CONSERV BIOL, V26, P821, DOI 10.1111/j.1523-1739.2012.01867.x
   Rittenhouse CD, 2010, GLOBAL CHANGE BIOL, V16, P905, DOI 10.1111/j.1365-2486.2009.02101.x
   Rödder D, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0007843
   ROOT T, 1988, J BIOGEOGR, V15, P489, DOI 10.2307/2845278
   Root TL, 2003, NATURE, V421, P57, DOI 10.1038/nature01333
   ROOTS EF, 1989, CLIMATIC CHANGE, V15, P223, DOI 10.1007/BF00138853
   Sagarin RD, 2006, TRENDS ECOL EVOL, V21, P524, DOI 10.1016/j.tree.2006.06.008
   Sauer J.R., 2013, N AM BREEDING BIRD S
   Sauer J.R., 2014, N AM BREEDING BIRD S
   Sauer JR, 2011, AUK, V128, P87, DOI 10.1525/auk.2010.09220
   Sauer JR, 2003, J WILDLIFE MANAGE, V67, P372, DOI 10.2307/3802778
   Sauer JR, 2002, ECOLOGY, V83, P1743, DOI 10.1890/0012-9658(2002)083[1743:HMOPSA]2.0.CO;2
   Serreze MC, 2000, CLIMATIC CHANGE, V46, P159, DOI 10.1023/A:1005504031923
   Sillmann J, 2008, CLIMATIC CHANGE, V86, P83, DOI 10.1007/s10584-007-9308-6
   Sillmann J, 2013, J GEOPHYS RES-ATMOS, V118, P1716, DOI 10.1002/jgrd.50203
   Songer Melissa, 2012, International Journal of Ecology, P1
   Stephens PA, 2016, SCIENCE, V352, P84, DOI 10.1126/science.aac4858
   Stralberg D, 2015, ECOL APPL, V25, P52, DOI 10.1890/13-2289.1
   Synes NW, 2011, GLOBAL ECOL BIOGEOGR, V20, P904, DOI 10.1111/j.1466-8238.2010.00635.x
   Taheri S., 2016, Climate Change Responses, V3, P5, DOI 10.1186/s40665-016-0020-5
   Thomas CD, 1999, NATURE, V399, P213, DOI 10.1038/20335
   Thuiller W, 2006, GLOBAL CHANGE BIOL, V12, P424, DOI 10.1111/j.1365-2486.2006.01115.x
   Thuiller W, 2004, NATURE, V430, DOI 10.1038/nature02716
   Tingley MW, 2009, P NATL ACAD SCI USA, V106, P19637, DOI 10.1073/pnas.0901562106
   Václavík T, 2012, J BIOGEOGR, V39, P42, DOI 10.1111/j.1365-2699.2011.02589.x
   VanDerWal J, 2013, NAT CLIM CHANGE, V3, P239, DOI [10.1038/NCLIMATE1688, 10.1038/nclimate1688]
   Vasseur DA, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.2612
   Virkkala R, 2014, GLOBAL CHANGE BIOL, V20, P2995, DOI [10.1111/gcb.12573, 10.1111/gcb.1]
   Vitousek PM, 1997, SCIENCE, V277, P494, DOI 10.1126/science.277.5325.494
   Walther GR, 2002, NATURE, V416, P389, DOI 10.1038/416389a
   Webber BL, 2011, DIVERS DISTRIB, V17, P978, DOI 10.1111/j.1472-4642.2011.00811.x
   Williams C.N., 2006, US HIST CLIMATOLOGY
   WILLIAMSON K, 1975, BIRD STUDY, V22, P143, DOI 10.1080/00063657509476459
NR 79
TC 31
Z9 36
U1 3
U2 80
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD SEP
PY 2017
VL 23
IS 9
BP 3610
EP 3622
DI 10.1111/gcb.13683
PG 13
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA FC4LU
UT WOS:000406812100017
PM 28295885
DA 2025-01-10
ER

PT J
AU Soundharajan, BS
   Adeloye, AJ
   Remesan, R
AF Soundharajan, Bankaru-Swamy
   Adeloye, Adebayo J.
   Remesan, Renji
TI Evaluating the variability in surface water reservoir planning
   characteristics during climate change impacts assessment
SO JOURNAL OF HYDROLOGY
LA English
DT Article
DE Reservoir performance; Climate change; Uncertainty analysis; Pong
   reservoir; India
ID UNCERTAINTY; PERFORMANCE; RELIABILITY; GENERATION; YIELD; MODEL
AB This study employed a Monte-Carlo simulation approach to characterise the uncertainties in climate change induced variations in storage requirements and performance (reliability (time- and volume based), resilience, vulnerability and sustainability) of surface water reservoirs. Using a calibrated rainfall-runoff(R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change-perturbed future runoff scenarios. The resulting runoff ensembles were used to force simulation models of the behaviour of the reservoir to produce 'populations' of required reservoir storage capacity to meet demands, and the performance. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the variability in the impacts. The methodology was applied to the Pong reservoir on the Beas River in northern India. The reservoir serves irrigation and hydropower needs and the hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall, both of which are predicted to change due to climate change. The results show that required reservoir capacity is highly variable with a coefficient of variation (CV) as high as 0.3 as the future climate becomes drier. Of the performance indices, the vulnerability recorded the highest variability (CV up to 0.5) while the volume-based reliability was the least variable. Such variabilities or uncertainties will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of their sheer magnitudes as obtained in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir. (C) 2016 The Author(s). Published by Elsevier B.V.
C1 [Soundharajan, Bankaru-Swamy; Adeloye, Adebayo J.] Heriot Watt Univ, Inst Infrastruct & Environm, Edinburgh EH14 4AS, Midlothian, Scotland.
   [Remesan, Renji] Cranfield Univ, Cranfield Water Sci Inst, Bedford, England.
C3 Heriot Watt University; Cranfield University
RP Adeloye, AJ (corresponding author), Heriot Watt Univ, Inst Infrastruct & Environm, Edinburgh EH14 4AS, Midlothian, Scotland.
EM a.j.adeloye@hw.ac.uk
RI Remesan, Renji/H-6614-2013
OI Adeloye, Adebayo/0000-0002-2820-4596; Soundharajan, Bankaru
   Swamy/0000-0001-6143-9293
FU UK-NERC [NE/I022337/1]; NERC [NE/N016394/1, NE/I022337/1] Funding
   Source: UKRI
FX The work reported here was funded by the UK-NERC (Project NE/I022337/1)
   - Mitigating Climate Change impacts on India Agriculture through
   Improved Irrigation Water Management (MICCI) - as part of the UK-India
   Changing Water Cycle (CWC South Asia) thematic Programme.
CR Adeloye AJ, 2016, WATER RESOUR MANAG, V30, P445, DOI 10.1007/s11269-015-1171-z
   Adeloye Adebayo J., 2013, Climate Change Modeling, Mitigation and Adaptation, P299
   Adeloye AJ, 2001, WATER RESOUR RES, V37, P73, DOI 10.1029/2000WR900237
   Anandhi A, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009104
   [Anonymous], GUIDE USING HYSIM VE
   [Anonymous], 2013, CLIM CHANG 2013 PHYS
   [Anonymous], 2012, ENCY LAKERESERVOIR
   [Anonymous], 1964, Osnovy Rascheta Regulirovaniia Rechnogo Stoka Metodom Monte-Karlo [Fundamentals for Computing Regulation of Runoff by the Monte Carlo Method]
   Arnell NW, 2003, J HYDROL, V270, P195, DOI 10.1016/S0022-1694(02)00288-3
   Burges S.J., 1971, J HYDRAUL DIV, V97, P977
   Burn DH, 1996, WATER RESOUR MANAG, V10, P463, DOI 10.1007/BF00422550
   Chiamsathit C, 2014, P I CIVIL ENG-WAT M, V167, P551, DOI 10.1680/wama.13.00059
   FIERING MB, 1982, WATER RESOUR RES, V18, P41, DOI 10.1029/WR018i001p00041
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1547, DOI 10.1002/joc.1556
   Fowler HJ, 2003, WATER RESOUR RES, V39, DOI 10.1029/2002WR001778
   HASHIMOTO T, 1982, WATER RESOUR RES, V18, P14, DOI 10.1029/WR018i001p00014
   Jain S.K., 2007, HYDROL WATER RESOUR, V57, P997
   Kumar V, 2007, HYDROLOG SCI J, V52, P376, DOI 10.1623/hysj.52.2.376
   Kuria F, 2015, J HYDROL, V529, P257, DOI 10.1016/j.jhydrol.2015.07.025
   Li LH, 2010, WATER RESOUR MANAG, V24, P83, DOI 10.1007/s11269-009-9438-x
   Lopez A, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR007499
   McKibben B, 2007, NEW YORK REV BOOKS, V54, P44
   McMahon T.A., 1986, River and Reservoir Yield
   McMahon T.A., 2005, Water Resources Yield
   McMahon TA, 2006, J HYDROL, V324, P359, DOI 10.1016/j.jhydrol.2005.09.030
   Murphy C, 2006, AREA, V38, P65, DOI 10.1111/j.1475-4762.2006.00656.x
   Nawaz NR, 2006, CLIMATIC CHANGE, V78, P257, DOI 10.1007/s10584-005-9043-9
   Peel M., 2014, Hydrology and Earth System Sciences Discussions, V11, P4579
   Pilling C, 1999, HYDROL PROCESS, V13, P2877, DOI 10.1002/(SICI)1099-1085(19991215)13:17<2877::AID-HYP904>3.0.CO;2-G
   Pilling CG, 2002, HYDROL PROCESS, V16, P1201, DOI 10.1002/hyp.1057
   Pretto PB, 1997, WATER RESOUR RES, V33, P703, DOI 10.1029/96WR03284
   Raje D, 2010, ADV WATER RESOUR, V33, P312, DOI 10.1016/j.advwatres.2009.12.008
   Rippl W., 1883, Proc. Inst. Civil Eng, VLXXI, P270
   Sandoval-Solis S, 2011, J WATER RES PLAN MAN, V137, P381, DOI 10.1061/(ASCE)WR.1943-5452.0000134
   SAVIC DA, 1989, WATER RESOUR BULL, V25, P977
   Silva AT, 2013, J HYDROL ENG, V18, P567, DOI 10.1061/(ASCE)HE.1943-5584.0000650
   SRIKANTHAN R, 1982, J HYDR ENG DIV-ASCE, V108, P419
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Thomas H., 1962, DESIGN WATER RESOURC
   VALENCIA D, 1973, WATER RESOUR RES, V9, P580
   Vicuña S, 2012, J WATER RES PLAN MAN, V138, P431, DOI 10.1061/(ASCE)WR.1943-5452.0000202
   Wilby RL, 2005, HYDROL PROCESS, V19, P3201, DOI 10.1002/hyp.5819
NR 42
TC 48
Z9 56
U1 2
U2 45
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0022-1694
EI 1879-2707
J9 J HYDROL
JI J. Hydrol.
PD JUL
PY 2016
VL 538
BP 625
EP 639
DI 10.1016/j.jhydrol.2016.04.051
PG 15
WC Engineering, Civil; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA DP2YX
UT WOS:000378360600050
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Walsh, CL
   Blenkinsop, S
   Fowler, HJ
   Burton, A
   Dawson, RJ
   Glenis, V
   Manning, LJ
   Jahanshahi, G
   Kilsby, CG
AF Walsh, Claire L.
   Blenkinsop, Stephen
   Fowler, Hayley J.
   Burton, Aidan
   Dawson, Richard J.
   Glenis, Vassilis
   Manning, Lucy J.
   Jahanshahi, Golnaz
   Kilsby, Chris G.
TI Adaptation of water resource systems to an uncertain future
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID TRANSIENT CLIMATE-CHANGE; WEATHER GENERATOR; REGIONAL DROUGHT; CHANGE
   IMPACTS; URBAN AREAS; MODEL; RISK; FRAMEWORK; PROJECTIONS; ROBUSTNESS
AB Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth, and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local-scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames Basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth, the median number of drought order occurrences may increase 5-fold by the 2050s. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. A decrease in per capita demand of 3.75% reduces the median frequency of drought order measures by 50% by the 2020s. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30% reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence, a portfolio of measures is required.
C1 [Walsh, Claire L.; Blenkinsop, Stephen; Fowler, Hayley J.; Burton, Aidan; Dawson, Richard J.; Glenis, Vassilis; Manning, Lucy J.; Jahanshahi, Golnaz; Kilsby, Chris G.] Newcastle Univ, Sch Civil Engn & Geosci, Ctr Earth Syst Engn Res, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England.
C3 Newcastle University - UK
RP Walsh, CL (corresponding author), Newcastle Univ, Sch Civil Engn & Geosci, Ctr Earth Syst Engn Res, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England.
EM claire.walsh@newcastle.ac.uk
RI WALSH, CLAIRE/B-7932-2008; Dawson, Richard/D-6933-2011; Fowler,
   Hayley/A-9591-2013; Glenis, Vassilis/U-4374-2017
OI Glenis, Vassilis/0000-0001-6037-9508; Dawson,
   Richard/0000-0003-3158-5868; Walsh, Claire/0000-0002-4047-1216; Fowler,
   Hayley/0000-0001-8848-3606; kilsby, chris/0000-0003-3422-294X;
   Blenkinsop, Stephen/0000-0003-0790-6545
FU Engineering and Physical Sciences Research Council (EPSRC)
   [EP/F037422/1]; EPSRC Fellowship [EP/H003630/1]; NERC Postdoctoral
   Fellowship award [NE/D009588/1]; Wolfson Foundation; Royal Society as a
   Royal Society Wolfson Research Merit Award [WM140025]; EPSRC
   [EP/G013403/1, EP/H003630/1, EP/F037422/1] Funding Source: UKRI; NERC
   [NE/D009588/1] Funding Source: UKRI
FX This work was undertaken as part of the SWERVE project which was funded
   by the Engineering and Physical Sciences Research Council (EPSRC)
   project no. EP/F037422/1. Richard Dawson was supported by an EPSRC
   Fellowship EP/H003630/1, and Hayley Fowler was supported by a NERC
   Postdoctoral Fellowship award (NE/D009588/1). Hayley Fowler is funded by
   the Wolfson Foundation and the Royal Society as a Royal Society Wolfson
   Research Merit Award (WM140025) holder. We would like to thank the
   reviewers for their valuable suggestions and comments.
CR [Anonymous], THAM CATCHM ABSTR LI
   Beh EHY, 2015, WATER RESOUR RES, V51, P1529, DOI 10.1002/2014WR016254
   Beh EHY, 2015, ENVIRON MODELL SOFTW, V68, P181, DOI 10.1016/j.envsoft.2015.02.006
   Blanc J, 2012, J FLOOD RISK MANAG, V5, P143, DOI 10.1111/j.1753-318X.2012.01135.x
   Blenkinsop S, 2007, J HYDROL, V342, P50, DOI 10.1016/j.jhydrol.2007.05.003
   Blenkinsop S, 2013, CLIM RES, V57, P95, DOI 10.3354/cr01170
   Borgomeo E, 2014, WATER RESOUR RES, V50, P6850, DOI 10.1002/2014WR015558
   Brown C., 2012, EOS T AM GEOPHYS UN, V93, P401, DOI DOI 10.1029/2012EO410001
   Brown Casey, 2012, WATER RESOURCES RESEARCH, V48, DOI DOI 10.1029/2011WR011212
   Burke EJ, 2010, J HYDROL, V394, P471, DOI 10.1016/j.jhydrol.2010.10.003
   Burton A, 2008, ENVIRON MODELL SOFTW, V23, P1356, DOI 10.1016/j.envsoft.2008.04.003
   Burton A, 2013, ENVIRON MODELL SOFTW, V49, P22, DOI 10.1016/j.envsoft.2013.06.001
   Burton A, 2010, WATER RESOUR RES, V46, DOI 10.1029/2009WR008884
   Burton A, 2010, J HYDROL, V381, P18, DOI 10.1016/j.jhydrol.2009.10.031
   Christensen NS, 2007, HYDROL EARTH SYST SC, V11, P1417, DOI 10.5194/hess-11-1417-2007
   Cloke HL, 2013, Q J ROY METEOR SOC, V139, P282, DOI 10.1002/qj.1998
   Coulthard TJ, 2012, HYDROL EARTH SYST SC, V16, P4401, DOI 10.5194/hess-16-4401-2012
   COWPERTWAIT PSP, 1995, P R SOC-MATH PHYS SC, V450, P163, DOI 10.1098/rspa.1995.0077
   Darch G., 2011, 510399373DG035 ATK
   Davis R. J., 2001, 0004 ENV AG
   Dawson R, 2007, PHILOS T R SOC A, V365, P3085, DOI 10.1098/rsta.2007.0008
   Defra, 2008, CM7319 DEFRA TSO
   Dessai S, 2007, GLOBAL ENVIRON CHANG, V17, P59, DOI 10.1016/j.gloenvcha.2006.11.005
   Environment Agency, 2007, WAT FUT MAN WAT RES
   Environment Agency, 2007, WAT NEUTR THAM GAT S
   Environmental Agency, 2008, SC070010 ENV AG
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   GLA (Greater London Authority), 2011, SEC LOND WAT FUT MAY
   Goderniaux P, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR010082
   Groves DG, 2007, GLOBAL ENVIRON CHANG, V17, P73, DOI 10.1016/j.gloenvcha.2006.11.006
   Groves DG, 2008, WATER RESOUR RES, V44, DOI 10.1029/2008WR006964
   Haasnoot M, 2014, ENVIRON MODELL SOFTW, V60, P99, DOI 10.1016/j.envsoft.2014.05.020
   Hall JW, 2012, WATER ENVIRON J, V26, P118, DOI 10.1111/j.1747-6593.2011.00271.x
   Hall J, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2012.0407
   Hall JimW., 2009, Engineering Cities: How Can Cities Grow Whilst Reducing Emissions and Vulnerability?
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Hallett S., 2013, COMMUNITY RESILIENCE
   Harris CNP, 2013, CLIMATIC CHANGE, V121, P317, DOI 10.1007/s10584-013-0871-8
   Heidrich O, 2013, CLIMATIC CHANGE, V120, P771, DOI 10.1007/s10584-013-0846-9
   Hewitt C, 2012, NAT CLIM CHANGE, V2, P831, DOI 10.1038/nclimate1745
   Jenkins DP, 2014, RENEW ENERG, V61, P7, DOI 10.1016/j.renene.2012.04.035
   Jones P., 2009, UK CLIMATE PROJECTIO
   Jones RN, 2000, CLIMATIC CHANGE, V45, P403, DOI 10.1023/A:1005551626280
   Kay AL, 2012, INT J CLIMATOL, V32, P489, DOI 10.1002/joc.2288
   Kilsby CG, 2007, ENVIRON MODELL SOFTW, V22, P1705, DOI 10.1016/j.envsoft.2007.02.005
   Lee SE, 2013, BUILD SERV ENG RES T, V34, P203, DOI 10.1177/0143624412439485
   Lempert RJ, 2010, TECHNOL FORECAST SOC, V77, P960, DOI 10.1016/j.techfore.2010.04.007
   Lopez A, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR007499
   Manning LJ, 2009, WATER RESOUR RES, V45, DOI 10.1029/2007WR006674
   Marsh Terry, 2007, Weather, V62, P191, DOI 10.1002/wea.99
   Matrosov ES, 2013, J HYDROL, V494, P43, DOI 10.1016/j.jhydrol.2013.03.006
   McDonald A. T., 2007, ROYAL SOC CHEM REPOR
   Murphy J.M., 2009, UK Climate Projections Science Report: Climate change projections
   New M, 2007, PHILOS T R SOC A, V365, P2117, DOI 10.1098/rsta.2007.2080
   Oxford Scientific Software Ltd, 2004, A GUID TO AQUATOR
   Parker JM, 2013, WATER RESOUR MANAG, V27, P981, DOI 10.1007/s11269-012-0190-2
   Patidar S, 2014, RENEW ENERG, V61, P23, DOI 10.1016/j.renene.2012.04.027
   Paton FL, 2014, WATER RESOUR RES, V50, P6285, DOI 10.1002/2013WR015195
   Perry M, 2005, INT J CLIMATOL, V25, P1023, DOI 10.1002/joc.1160
   Perry M, 2005, INT J CLIMATOL, V25, P1041, DOI 10.1002/joc.1161
   Rahiz M, 2014, INT J CLIMATOL, V34, P2853, DOI 10.1002/joc.3879
   Steinschneider S, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000536
   Thames Water, 2014, FIN WAT RES MAN PLAN
   Thompson JR, 2012, HYDROL RES, V43, P507, DOI 10.2166/nh.2012.105
   Vidal JP, 2009, INT J CLIMATOL, V29, P2056, DOI 10.1002/joc.1843
   von Christierson B, 2012, J HYDROL, V424, P48, DOI 10.1016/j.jhydrol.2011.12.020
   Walsh CL, 2011, PROC INST CIV ENG-U, V164, P75, DOI 10.1680/udap.2011.164.2.75
   Warren AJ, 2012, WATER ENVIRON J, V26, P361, DOI 10.1111/j.1747-6593.2011.00296.x
   Whateley S, 2014, WATER RESOUR RES, V50, P8944, DOI 10.1002/2014WR015956
   Whitehead PG, 2006, SCI TOTAL ENVIRON, V365, P260, DOI 10.1016/j.scitotenv.2006.02.040
   WILBY R, 1994, J HYDROL, V153, P265, DOI 10.1016/0022-1694(94)90195-3
   Wilby RL, 2005, HYDROL PROCESS, V19, P3201, DOI 10.1002/hyp.5819
   Wilby RL, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004065
   Wilby RL., 2004, GUIDELINES USE CLIMA
   Zeff HB, 2014, WATER RESOUR RES, V50, P4906, DOI 10.1002/2013WR015126
NR 75
TC 18
Z9 18
U1 0
U2 30
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1027-5606
EI 1607-7938
J9 HYDROL EARTH SYST SC
JI Hydrol. Earth Syst. Sci.
PY 2016
VL 20
IS 5
BP 1869
EP 1884
DI 10.5194/hess-20-1869-2016
PG 16
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA DO5ZX
UT WOS:000377862900013
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Essl, F
   Dullinger, S
   Moser, D
   Rabitsch, W
   Kleinbauer, I
AF Essl, Franz
   Dullinger, Stefan
   Moser, Dietmar
   Rabitsch, Wolfgang
   Kleinbauer, Ingrid
TI Vulnerability of mires under climate change: implications for nature
   conservation and climate change adaptation
SO BIODIVERSITY AND CONSERVATION
LA English
DT Article
DE Biodiversity; BIOMOD; Carbon sequestration; Climate scenarios;
   Ecosystems; Habitat loss; Habitat models; Mitigation; Peatland
ID PLANT DIVERSITY; CARBON LOSSES; DISTRIBUTIONS; BIODIVERSITY; DISPERSAL;
   PEAT; TEMPERATURE; ENSEMBLE; CAPACITY; TRENDS
AB Wetlands in general and mires in particular belong to the most important terrestrial carbon stocks globally. Mires (i.e. bogs, transition bogs and fens) are assumed to be especially vulnerable to climate change because they depend on specific, namely cool and humid, climatic conditions. In this paper, we use distribution data of the nine mire types to be found in Austria and habitat distribution models for four IPCC scenarios to evaluate climate change induced risks for mire ecosystems within the 21st century. We found that climatic factors substantially contribute to explain the current distribution of all nine Austrian mire ecosystem types. Summer temperature proved to be the most important predictor for the majority of mire ecosystems. Precipitation-mostly spring and summer precipitation sums-was influential for some mire ecosystem types which depend partly or entirely on ground water supply (e.g. fens). We found severe climate change induced risks for all mire ecosystems, with rain-fed bog ecosystems being most threatened. Differences between scenarios are moderate for the mid-21st century, but become more pronounced towards the end of the 21st century, with near total loss of climate space projected for some ecosystem types (bogs, quagmires) under severe climate change. Our results imply that even under minimum expected, i.e. inevitable climate change, climatic risks for mires in Austria will be considerable. Nevertheless, the pronounced differences in projected habitat loss between moderate and severe climate change scenarios indicate that limiting future warming will likely contribute to enhance long-term survival of mire ecosystems, and to reduce future greenhouse gas emissions from decomposing peat. Effectively stopping and reversing the deterioration of mire ecosystems caused by conventional threats can be regarded as a contribution to climate change mitigation. Because hydrologically intact mires are more resilient to climatic changes, this would also maintain the nature conservation value of mires, and help to reduce the severe climatic risks to which most Austrian mire ecosystems may be exposed in the 2nd half of the 21st century according to IPCC scenarios.
C1 [Essl, Franz; Moser, Dietmar; Rabitsch, Wolfgang] Environm Agcy Austria, A-1090 Vienna, Austria.
   [Dullinger, Stefan] Univ Vienna, Dept Conservat Biol Vegetat & Landscape Ecol, A-1030 Vienna, Austria.
   [Dullinger, Stefan; Moser, Dietmar; Kleinbauer, Ingrid] Vienna Inst Nat Conservat & Anal, A-1090 Vienna, Austria.
C3 University of Vienna
RP Essl, F (corresponding author), Environm Agcy Austria, Spittelauer Lande 5, A-1090 Vienna, Austria.
EM franz.essl@umweltbundesamt.at
RI Rabitsch, Wolfgang/G-4562-2011; Essl, Franz/ABE-7064-2020
OI Essl, Franz/0000-0001-8253-2112; Dullinger, Stefan/0000-0003-3919-0887;
   Rabitsch, Wolfgang/0000-0002-3811-6071
FU Austrian Forests (OBf); Upper Austrian Federal Government
FX This analysis has been jointly financed by the Austrian Forests (OBf)
   and the Upper Austrian Federal Government. We are indebted to G.M.
   Steiner and P. Weiss for comments and helpful discussions, and to two
   anonymous reviewers whose suggestions significantly improved the
   manuscript.
CR Allison I., 2009, COPENHAGEN DIAGNOSIS
   [Anonymous], E ALPS PLEISTOCENE
   [Anonymous], NATUR LAND
   [Anonymous], ADR GEB WOHN 2 AGWR2
   [Anonymous], CLC 2000 AUSTRIA UPG
   [Anonymous], 2007, SAGA ENTWURF FUNKTIO
   [Anonymous], 2005, ECOSYSTEMS HUMAN WEL
   [Anonymous], 2009, GLOBAL PEATLAND CO2
   [Anonymous], 1999, Rote Listen gefahrdeter Pflanzen Osterreichs. Grune Reihe des Bundesministeriums fur Umwelt, Jugend und Familie
   [Anonymous], 0730 BAFU
   [Anonymous], BRYOPHYTE ECOLOGY CL
   [Anonymous], NAT INF SYST AUSTR N
   [Anonymous], 1990, Generalized additive models
   [Anonymous], 2009, Pathways to a Low-Carbon Economy Version 2 of the Global Greenhouse Gas Abatement Cost Curve
   [Anonymous], LIM GLOB CLIM CHANG
   [Anonymous], 2004, 55 TYND CTR UEA
   [Anonymous], 2001, Machine Learning
   [Anonymous], 2008, CLIMATIC RISK ATLAS
   [Anonymous], 2007, Interpretation manual of European Union Habitats
   [Anonymous], OSTERREICHISCHER MOO
   [Anonymous], 2009, Nat Landsch
   [Anonymous], REV VALDOTAINE DHIST
   Araújo MB, 2006, J BIOGEOGR, V33, P1712, DOI 10.1111/j.1365-2699.2006.01482.x
   Araújo MB, 2007, TRENDS ECOL EVOL, V22, P42, DOI 10.1016/j.tree.2006.09.010
   Bellamy PH, 2005, NATURE, V437, P245, DOI 10.1038/nature04038
   Bergamini A, 2009, PERSPECT PLANT ECOL, V11, P65, DOI 10.1016/j.ppees.2008.10.001
   Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI DOI 10.1080/02626667909491834
   Bobbink R, 2010, ECOL APPL, V20, P30, DOI 10.1890/08-1140.1
   Bobbink R, 1998, J ECOL, V86, P717, DOI 10.1046/j.1365-2745.1998.8650717.x
   Bohner J., 2006, Collection Gottinger geographische Abhandlungen, V115, P1
   Bortoluzzi E, 2006, NEW PHYTOL, V172, P708, DOI 10.1111/j.1469-8137.2006.01859.x
   Bragazza L, 2008, GLOBAL CHANGE BIOL, V14, P2688, DOI 10.1111/j.1365-2486.2008.01699.x
   Brooker RW, 2006, NEW PHYTOL, V171, P271, DOI 10.1111/j.1469-8137.2006.01752.x
   Byrne K.A., 2004, EU PEATLANDS CURRENT
   Carroll MJ, 2011, GLOBAL CHANGE BIOL, V17, P2991, DOI 10.1111/j.1365-2486.2011.02416.x
   Clark JM, 2010, CLIM RES, V45, P131, DOI 10.3354/cr00929
   Couwenberg J, 2011, HYDROBIOLOGIA, V674, P67, DOI 10.1007/s10750-011-0729-x
   Dise NB, 2009, SCIENCE, V326, P810, DOI 10.1126/science.1174268
   Dullinger S, 2004, J ECOL, V92, P241, DOI 10.1111/j.0022-0477.2004.00872.x
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Engler R, 2009, ECOGRAPHY, V32, P34, DOI 10.1111/j.1600-0587.2009.05789.x
   Essl F, 2010, LEBENSRAUMVIELFALT O
   Ferrier S, 2006, J APPL ECOL, V43, P393, DOI 10.1111/j.1365-2664.2006.01149.x
   Friedman JH, 2001, ANN STAT, V29, P1189, DOI 10.1214/aos/1013203451
   FRIEDMAN JH, 1991, ANN STAT, V19, P1, DOI 10.1214/aos/1176347963
   Fronzek S, 2006, CLIM RES, V32, P1, DOI 10.3354/cr032001
   Fronzek S, 2012, GLOBAL ECOL BIOGEOGR, V21, P19, DOI 10.1111/j.1466-8238.2011.00695.x
   Fronzek S, 2010, CLIMATIC CHANGE, V99, P515, DOI 10.1007/s10584-009-9679-y
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Hobbs RJ, 2009, TRENDS ECOL EVOL, V24, P599, DOI 10.1016/j.tree.2009.05.012
   Hobbs RJ, 2006, GLOBAL ECOL BIOGEOGR, V15, P1, DOI 10.1111/j.1466-822x.2006.00212.x
   HOGG EH, 1992, ECOL APPL, V2, P298, DOI 10.2307/1941863
   Le Quéré C, 2009, NAT GEOSCI, V2, P831, DOI 10.1038/ngeo689
   Lindsay R., 2010, PEATBOGS CARBON CRIT
   McCullagh P., 1989, Generalized Linear Models, VSecond
   Nakicenovic N., 2000, IPCC Special Report on Emissions Scenarios (SRES)
   New M, 2002, CLIMATE RES, V21, P1, DOI 10.3354/cr021001
   Ovando P, 2009, ENERG POLICY, V37, P992, DOI 10.1016/j.enpol.2008.10.041
   Ozinga WA, 2009, ECOL LETT, V12, P66, DOI 10.1111/j.1461-0248.2008.01261.x
   Parish F., 2008, ASSESSMENT PEATLANDS
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Parviainen M, 2007, GEOGR ANN A, V89A, P137, DOI 10.1111/j.1468-0459.2007.00314.x
   Pearson RG, 2006, TRENDS ECOL EVOL, V21, P111, DOI 10.1016/j.tree.2005.11.022
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Rickebusch S, 2008, BIOL LETTERS, V4, P556, DOI 10.1098/rsbl.2008.0105
   Sala OE, 2000, SCIENCE, V287, P1770, DOI 10.1126/science.287.5459.1770
   Schmidli J, 2005, INT J CLIMATOL, V25, P753, DOI 10.1002/joc.1179
   Schweiger O, 2008, ECOLOGY, V89, P3472, DOI 10.1890/07-1748.1
   Schweiger O, 2012, GLOBAL ECOL BIOGEOGR, V21, P88, DOI 10.1111/j.1466-8238.2010.00607.x
   Smart SM, 2010, CLIM RES, V45, P163, DOI 10.3354/cr00969
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Succow M., 2001, LANDSCHAFTSOKOLOGISC
   SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Thuiller W, 2005, P NATL ACAD SCI USA, V102, P8245, DOI 10.1073/pnas.0409902102
   Thuiller W, 2009, ECOGRAPHY, V32, P369, DOI 10.1111/j.1600-0587.2008.05742.x
   Tuittila ES, 2004, RESTOR ECOL, V12, P483, DOI 10.1111/j.1061-2971.2004.00280.x
   Williams JW, 2007, P NATL ACAD SCI USA, V104, P5738, DOI 10.1073/pnas.0606292104
   Zhang BC, 2016, J BASIC MICROB, V56, P670, DOI 10.1002/jobm.201500751
NR 80
TC 52
Z9 57
U1 2
U2 118
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0960-3115
EI 1572-9710
J9 BIODIVERS CONSERV
JI Biodivers. Conserv.
PD MAR
PY 2012
VL 21
IS 3
BP 655
EP 669
DI 10.1007/s10531-011-0206-x
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 891WW
UT WOS:000300248500004
DA 2025-01-10
ER

PT S
AU Tsujii, H
   Gültekin, U
AF Tsujii, Hiroshi
   Gultekin, Ufuk
BE Watanabe, T
   Kapur, S
   Aydin, M
   Kanber, R
   Akca, E
TI An Econometric and Agro-meteorological Study on Rain-fed Wheat and
   Barley in Turkey Under Climate Change
SO CLIMATE CHANGE IMPACTS ON BASIN AGRO-ECOSYSTEMS
SE Anthropocene-Politik Economics Society Science
LA English
DT Article; Book Chapter
DE Wheat and barley; Rain-fed production; Climate change impact;
   Econometric approach
AB The objective of our study is to project the impacts of climate change on rain-fed wheat and barley production in Turkey for 2070-2079 and identify their policy implications. We first estimate the wheat and barley yield and area sown functions for the Konya and Adana provinces, which have been representative wheat and barley production areas in Turkey. Most of the wheat and barley in Turkey have been produced in rain- fed conditions. Rain-fed arable land in Turkey is either planted to wheat or barley, leading Turkish farmers to make planting decisions according to the relative price of these crops. The relative price reflects the previous year's Turkish demand for and supply of both crops, and of animal products produced by using barley as feed. As expected from the rain-fed, traditional and low input wheat and barley production in Turkey, most of the estimated yield and area sown functions for these crops have statistically significant correlation coefficients to spring heat-damage variables and drought-damage variables, as well as to the cumulative monthly rainfall variables. Iterative estimation methods were used for selecting the best correlation coefficients of these variables. These coefficients not only appropriately reflect the severe fragility in the rain-fed wheat and barley production on the rain- fed arable land in Konya and Adana, but also provide a good basis for estimating the 2070s' wheat and barley production using the monthly temperature and rainfall projected by a regional circulation model (RCM) in our study for that period. We think that the impact of climate change on crop yield and area sown in the real world is determined not only by the crop responses, but also by farmers' adaptations and agricultural experiment stations' research adaptations to climate change. This is affected by the changes in demand for and supply of wheat, bread, barley and animal products, reflected in the relative price between wheat and barley in the previous year, as well as by policy and institutional changes. Our model incorporates most of these aspects explicitly and implicitly. Thus, we can conclude that the process to assess the impacts of climate change on wheat and barley production in Turkey using our model better emulates the real world process than the physiological plant growth model that focuses the impacts of climatic change on mainly the growth of wheat and barley. Consequently, we insert the 2070-2079 monthly rainfall and temperature data projected by the RCM into the estimated yield and area sown functions in order to project wheat and barley production for that period. Then, adding the FACE 2 * CO2 fertilisation effect of 13% to the projected yields, the final change rates in the wheat and barley production projected for the 2070-2079 period are -14% for wheat and -28% for barley in Konya, and -0.46% for barley and +3.5% for wheat in Adana. The projected impacts of climate change on wheat and barley production in Turkey can be calculated as weighted averages of these impacts with production weights for Central Anatolia and its peripheral region, where the regions of Konya and Adana are the typical representative areas. The impact of climate change on wheat production in Turkey is -12.06% of current production. For barley this impact is -14.39%. Given the self-sufficient wheat and barley market of Turkey, these impacts may cause a food crisis in the case of wheat, and severe shortage of feed and livestock products in the case of barley in Turkey.
   We suggest the development and use of new wheat and barley varieties that are resistant to spring heat damage and drought and preparation of the economic and political capabilities to import the needed wheat and barley that have been staple foods for Turkish people for thousands of years.
C1 [Tsujii, Hiroshi] Univ Illinois, Chicago, IL 60680 USA.
   [Tsujii, Hiroshi] Kyoto Univ, Agr Econ, Fushimi Ku, 104-1 Higashianshincho, Kyoto 6120832, Japan.
   [Gultekin, Ufuk] Cukurova Univ, Dept Agr Econ, Adana, Turkey.
C3 University of Illinois System; University of Illinois Chicago;
   University of Illinois Chicago Hospital; Kyoto University; Cukurova
   University
RP Tsujii, H (corresponding author), Univ Illinois, Chicago, IL 60680 USA.; Tsujii, H (corresponding author), Kyoto Univ, Agr Econ, Fushimi Ku, 104-1 Higashianshincho, Kyoto 6120832, Japan.
EM tsujii1809press@yahoo.co.jp; ugultekin@gmail.com
FU RIHN (Research Institute for Humanity and Nature) in Japan; TUBITAK (The
   Scientific and Technical Research Council of Turkey) in Turkey
FX This study is a part of the economic research sub-project of the ICCAP
   (Impact of Climate Change on Agricultural Production System in Arid
   Area). It is a collaborative research between Japanese and Turkish
   researchers in many disciplines. This project was supported by the RIHN
   (Research Institute for Humanity and Nature) in Japan and TUBITAK (The
   Scientific and Technical Research Council of Turkey) in Turkey.
CR [Anonymous], 2017, FAOSTAT
   Belaid A, 1992, 9102 CIMMYT, P23
   Lobell DB, 2012, PLANT PHYSIOL, V160, P1686, DOI 10.1104/pp.112.208298
   Long SP, 2006, SCIENCE, V312, P1918, DOI 10.1126/science.1114722
   NORDHAUS WD, 1993, J ECON PERSPECT, V7, P11, DOI 10.1257/jep.7.4.11
   Parry M, 1990, CLIMATIC CHANGE WORL, P24
   Sato T, 2007, J HYDROL, V333, P144, DOI 10.1016/j.jhydrol.2006.07.023
   Taub RD, 2010, NATURE ED KNOWLEDGE, V3, P21
   Tsujii H., 1986, CROP INSURANCE AGR D, P143
   Tsujii H, 1977, CLIMATIC CHANGE FOOD, P167
   Tsujii H, 1987, IMPACT CLIMATIC VARI, V1
   Tsujii H, 1988, IMPACT CLIMATIC VARI, V1, P725
   Tsujii H, 2005, INTERIM REPORT SOCIO
   Uchijima Z, 1987, IMPACT CLIMATIC VARI, V1
   USDA, 2012, GRAIN REP, P3
NR 15
TC 0
Z9 0
U1 1
U2 4
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2367-4024
EI 2367-4032
BN 978-3-030-01036-2; 978-3-030-01035-5
J9 ANTHROP POL ECON SOC
PY 2019
VL 18
BP 343
EP 374
DI 10.1007/978-3-030-01036-2_16
D2 10.1007/978-3-030-01036-2
PG 32
WC Agronomy; Environmental Sciences; Water Resources
WE Book Citation Index – Science (BKCI-S)
SC Agriculture; Environmental Sciences & Ecology; Water Resources
GA BS4AT
UT WOS:000717135200020
DA 2025-01-10
ER

PT J
AU Teneva, L
   Free, CM
   Hume, A
   Agostini, VN
   Klein, CJ
   Watson, RA
   Gaines, SD
AF Teneva, Lida
   Free, Christopher M.
   Hume, Andrew
   Agostini, Vera N.
   Klein, Carissa J.
   Watson, Reg A.
   Gaines, Steven D.
TI Small island nations can achieve food security benefits through
   climate-adaptive blue food governance by 2050
SO MARINE POLICY
LA English
DT Article
DE Blue food; Island food security; Climate-smart fisheries; Future seafood
ID PACIFIC ISLANDS; FISHERIES; VULNERABILITY; IMPACTS; FUTURE; FISH
AB Small island nations are highly dependent on food from aquatic environments, or blue food, and vulnerable to climate change and global food market price volatility. By 2050, rising populations will demand more food through various protein sources, including from the sea. This study identifies which small island nations can improve food self-sufficiency from the sea by implementing tailored climate-adaptive fisheries governance strategies that adapt to shifting marine resources. We combined projections of seafood demand and local catch under different future scenarios of global carbon emissions and local adaptive fisheries management to estimate potential seafood surpluses or deficits from by 2050 for 31 small island nations worldwide. We find that adapting fisheries management every 10 years could mitigate even worst-case projections of climate change impacts on locally available seafood, building a seafood surplus by 2050 in the Seychelles, Maldives, Cabo Verde, Bahamas, Antigua and Barbuda, Kiribati, PNG, Fiji, FSM, Tuvalu, and Marshall Islands. Strategic financial and capacity investments by the international community could help realize the full potential of food security from the sea for those nations. However, we project deficits in locally caught seafood by 2050 in Comoros, Sao Tome and Principe, Mauritius, Barbados, Dominican Republic, Cuba, Dominica, Jamaica, Grenada, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago, Haiti, Palau, Samoa, Nauru, and the Solomon Islands, regardless of adapting fisheries management. For those nations, we recommend international collaboration that strengthens food security from sources other than the sea coupled with investments in locally sustainable aquaculture. Overall, we find that climate-adaptive fisheries management can benefit a range of the studied small island nations, by supporting both food security goals as well as economic goals of productive fisheries for international trade
C1 [Teneva, Lida] World Wildlife Fund, Washington, DC USA.
   [Free, Christopher M.; Gaines, Steven D.] Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA USA.
   [Free, Christopher M.] Univ Calif Santa Barbara, Marine Sci Inst, Santa Barbara, CA USA.
   [Hume, Andrew] Stanford Univ, Woods Inst Environm, Stanford, CA USA.
   [Agostini, Vera N.] United Nations Food & Agr Org, Rome, Italy.
   [Klein, Carissa J.] Univ Queensland, Ctr Biodivers & Conservat Sci, Sch Earth & Environm Sci, Brisbane, Qld, Australia.
   [Watson, Reg A.] Univ Tasmania, Inst Marine & Antarctic Studies, Hobart, Tas, Australia.
   [Teneva, Lida] 500 23rd St NW,Apt B407, Washington, DC 20037 USA.
C3 World Wildlife Fund; University of California System; University of
   California Santa Barbara; University of California System; University of
   California Santa Barbara; Stanford University; Food & Agriculture
   Organization of the United Nations (FAO); University of Queensland;
   University of Tasmania
RP Teneva, L (corresponding author), 500 23rd St NW,Apt B407, Washington, DC 20037 USA.
EM lida.teneva@gmail.com
RI Gaines, Steven/Y-3234-2019; Free, Christopher/N-2813-2013; Teneva,
   Lida/G-5772-2013; Klein, Carissa/F-1632-2011
OI Teneva, Lida/0000-0002-8854-5464; Gaines, Steven/0000-0002-7604-3483
FU Australian Research Council Future Fellowship;  [200100314]
FX Carissa Klein was funded by an Australian Research Council Future
   Fellowship (200100314) .
CR Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   [Anonymous], 2008, An introduction to the basic concepts of food security
   [Anonymous], 2015, World Population Prospects: The 2015 Revision, Key Findings and Advance Tables
   [Anonymous], 2018, STATE WORLD FISHERIE, DOI [10.1126/science.aaw5824, DOI 10.18356/8D6-A4B6-EN]
   [Anonymous], 2015, Transforming our world: the 2030 agenda for sustainable development
   [Anonymous], 2016, State of World Fisheries and Aquaculture 2016. Contributing to Food Security and Nutrition for All
   Aqorau T., 2009, International Journal of Marine and Coastal Law, V24, P557, DOI 10.1163/157180809X455647
   Aqorau T, 2018, SCIENCE, V361, P1208, DOI 10.1126/science.aav2051
   Asche F, 2015, WORLD DEV, V67, P151, DOI 10.1016/j.worlddev.2014.10.013
   Ayers AL, 2014, GLOBAL ENVIRON CHANG, V28, P251, DOI 10.1016/j.gloenvcha.2014.07.006
   Bahri T., 2021, ADAPTIVE MANAGEMENT, DOI [10.4060/cb3095-n, DOI 10.4060/CB3095-N]
   Belhabib D, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118351
   Bell J.D., 2011, VULNERABILITY TROP P, P17
   Bell JD, 2021, NAT SUSTAIN, V4, P900, DOI 10.1038/s41893-021-00745-z
   Bell JD, 2015, MAR POLICY, V51, P584, DOI 10.1016/j.marpol.2014.10.005
   Bell JD, 2009, MAR POLICY, V33, P64, DOI 10.1016/j.marpol.2008.04.002
   Belton B, 2014, GLOB FOOD SECUR-AGR, V3, P59, DOI 10.1016/j.gfs.2013.10.001
   Bennett NJ, 2020, COAST MANAGE, V48, P336, DOI 10.1080/08920753.2020.1766937
   Berkes F, 2010, ENVIRON CONSERV, V37, P489, DOI 10.1017/S037689291000072X
   Charlton KE, 2016, BMC PUBLIC HEALTH, V16, DOI 10.1186/s12889-016-2953-9
   Cheung WWL, 2013, NATURE, V497, P365, DOI 10.1038/nature12156
   Cinner J., 2012, ADAPTING CHANGING EN
   Cinner JE, 2012, GLOBAL ENVIRON CHANG, V22, P12, DOI 10.1016/j.gloenvcha.2011.09.018
   Cinner JE, 2016, NATURE, V535, P416, DOI 10.1038/nature18607
   Cinner JE, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0074321
   Clapp J, 2017, FOOD POLICY, V66, P88, DOI 10.1016/j.foodpol.2016.12.001
   Connell J., 2020, Food Security in Small Island States, P1, DOI 10.1007/978-981-13-8256-7_1
   Costello C, 2020, NATURE, V588, P95, DOI 10.1038/s41586-020-2616-y
   Daw T., 2009, CLIMATE CHANGE IMPLI, P107
   Daw TM, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0031460
   Free CM, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0224347
   Friedlander AM, 2013, PAC SCI, V67, P441, DOI 10.2984/67.3.10
   Gaines SD, 2010, P NATL ACAD SCI USA, V107, P18286, DOI 10.1073/pnas.0906473107
   Garlock T, 2022, GLOB FOOD SECUR-AGR, V32, DOI 10.1016/j.gfs.2022.100620
   Golden C, 2016, NATURE, V534, P317, DOI 10.1038/534317a
   Golden CD, 2021, NATURE, V598, P315, DOI 10.1038/s41586-021-03917-1
   Goodman C, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.1046018
   Hanich Q, 2018, MAR POLICY, V88, P279, DOI 10.1016/j.marpol.2017.11.011
   Klein CJ, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac97ab
   Kroodsma DA, 2018, SCIENCE, V359, P904, DOI 10.1126/science.aao5646
   Lam VWY, 2016, SCI REP-UK, V6, DOI 10.1038/srep32607
   Martins IM, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00481
   McClanahan T, 2015, FISH FISH, V16, P78, DOI 10.1111/faf.12045
   Molinos JG, 2016, NAT CLIM CHANGE, V6, P83, DOI 10.1038/NCLIMATE2769
   National Marine Fisheries Service, 2011, US GUID NAT COAST ST
   Naylor RL, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-25516-4
   Pentz B, 2018, MAR POLICY, V92, P13, DOI 10.1016/j.marpol.2018.01.011
   Quimby B, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-020-01730-6
   Santos JA, 2019, PUBLIC HEALTH NUTR, V22, P1858, DOI 10.1017/S1368980018003609
   Soffiantini G, 2020, GLOB FOOD SECUR-AGR, V26, DOI 10.1016/j.gfs.2020.100400
   Swartz W, 2010, MAR POLICY, V34, P1366, DOI 10.1016/j.marpol.2010.06.011
   Teneva LT, 2018, MAR POLICY, V94, P28, DOI 10.1016/j.marpol.2018.04.025
   Thiault L, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaw9976
   Tigchelaar M, 2022, GLOB FOOD SECUR-AGR, V33, DOI 10.1016/j.gfs.2022.100637
   Tigchelaar M, 2021, NAT FOOD, V2, P673, DOI 10.1038/s43016-021-00368-9
   Titley MA, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2011204118
   UN, Small Island Developing States
   Valin H, 2014, AGR ECON-BLACKWELL, V45, P51, DOI 10.1111/agec.12089
   Watson RA, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.39
   Watson RA, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8365
   Webster MS, 2017, TRENDS ECOL EVOL, V32, P167, DOI 10.1016/j.tree.2016.12.007
   White ER, 2021, FISH FISH, V22, P232, DOI 10.1111/faf.12525
   Worm B., 2010, REBUILDING GLOBAL FI, V578, DOI [10.1126/science.1173146, DOI 10.1126/SCIENCE.1173146]
   ,, 2020, The state of food security and nutrition in the world 2020: transforming food systems for affordable healthy diets, DOI 10.4060/ca9692en
NR 64
TC 8
Z9 8
U1 4
U2 18
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0308-597X
EI 1872-9460
J9 MAR POLICY
JI Mar. Pol.
PD MAY
PY 2023
VL 151
AR 105577
DI 10.1016/j.marpol.2023.105577
EA MAR 2023
PG 8
WC Environmental Studies; International Relations
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; International Relations
GA Q1MZ5
UT WOS:001055242000001
DA 2025-01-10
ER

PT J
AU Clark, PW
   D'Amato, AW
   Evans, KS
   Schaberg, PG
   Woodall, CW
AF Clark, Peter W.
   D'Amato, Anthony W.
   Evans, Kevin S.
   Schaberg, Paul G.
   Woodall, Christopher W.
TI Ecological memory and regional context influence performance of
   adaptation plantings in northeastern US temperate forests
SO JOURNAL OF APPLIED ECOLOGY
LA English
DT Article
DE assisted migration; climate change; forestry; reforestation;
   regeneration; seedlings; silviculture; survival
ID CLIMATE-CHANGE; ASSISTED MIGRATION; DISTURBANCE REGIMES; AMERICAN
   CHESTNUT; NORTH-AMERICA; RED SPRUCE; TREE; GROWTH; TOLERANCE; MODELS
AB Species distribution models predict shifts in forest habitat in response to warming temperatures associated with climate change, yet tree migration rates lag climate change, leading to misalignment of current species assemblages with future climate conditions. Forest adaptation strategies have been proposed to deliberately adjust species composition by planting climate-suitable species. Practical evaluations of adaptation plantings are limited, especially in the context of ecological memory or extreme climate events. In this study, we examined the 3-year survival and growth response of future climate-adapted seedling transplants within operational-scale silvicultural trials across temperate forests in the northeastern US. Nine species were selected for evaluation based on projected future importance under climate change and potential functional redundancy with species currently found in these ecosystems. We investigated how adaptation planting type ('population enrichment' vs. 'assisted range expansion') and local site conditions reinforce interference interactions with existing vegetation at filtering adaptation strategies focused on transitioning forest composition. Our results show the performance of seedling transplants is based on species (e.g. functional attributes and size), the strength of local competition (e.g. ecological memory) and adaptation planting type, a proxy for source distance. These findings were consistent across regional forests but modified by site-specific conditions such as browse pressure and extreme climate events, namely drought and spring frost events. Synthesis and applications. Our results highlight that managing forests for shifts in future composition represents a promising adaptation strategy for incorporating new species and functional traits into contemporary forests. Yet, important barriers remain for the establishment of future climate-adapted forests that will most likely require management intervention. Nonetheless, the broader applicability of our findings demonstrates the potential for adaptation plantings to serve as strategic source nodes for the establishment of future climate-adapted species across functionally connected landscapes.
C1 [Clark, Peter W.; D'Amato, Anthony W.] Univ Vermont, Rubenstein Sch Environm & Nat Resources, Burlington, VT 05405 USA.
   [Evans, Kevin S.] Dartmouth Coll Woodlands, Milan, NH USA.
   [Schaberg, Paul G.] US Forest Serv, Northern Res Stn, USDA, Burlington, VT USA.
   [Woodall, Christopher W.] US Forest Serv, Northern Res Stn, USDA, Durham, NH USA.
C3 University of Vermont; United States Department of Agriculture (USDA);
   United States Forest Service; United States Department of Agriculture
   (USDA); United States Forest Service
RP Clark, PW (corresponding author), Univ Vermont, Rubenstein Sch Environm & Nat Resources, Burlington, VT 05405 USA.
EM peter.clark@uvm.edu
RI Woodall, Christopher/D-7757-2012; D'Amato, Anthony/AAV-3245-2021
OI Clark, Peter W./0000-0001-8931-7271; Woodall,
   Christopher/0000-0001-8076-6214
FU National Science Foundation [1920908]; U.S. Forest Service, Northern
   Research Station [16JV11242307-075]; USDA National Institute of Food and
   Agriculture McIntire-Stennis Cooperative Forestry Research Program;
   Northeast Climate Adaptation Science Center; Office of Integrative
   Activities; Office Of The Director [1920908] Funding Source: National
   Science Foundation
FX National Science Foundation, Grant/Award Number: 1920908; U.S. Forest
   Service, Northern Research Station, Grant/Award Number:
   16JV11242307-075; USDA National Institute of Food and Agriculture
   McIntire-Stennis Cooperative Forestry Research Program; Northeast
   Climate Adaptation Science Center
CR Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   [Anonymous], 2021, The PLANTS Database
   Aubin I, 2011, FOREST CHRON, V87, P755, DOI 10.5558/tfc2011-092
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Bellingham PJ, 2000, OIKOS, V89, P409, DOI 10.1034/j.1600-0706.2000.890224.x
   Bengtsson J, 2003, AMBIO, V32, P389, DOI 10.1639/0044-7447(2003)032[0389:RRADL]2.0.CO;2
   Bolker BM, 2009, TRENDS ECOL EVOL, V24, P127, DOI 10.1016/j.tree.2008.10.008
   Bonner F.T., 2008, The Woody Plant Seed Manual. Agriculture Handbook 727
   Brice MH, 2020, GLOBAL CHANGE BIOL, V26, P4418, DOI 10.1111/gcb.15143
   Brice MH, 2019, GLOBAL ECOL BIOGEOGR, V28, P1668, DOI 10.1111/geb.12971
   Brooks ME, 2017, R J, V9, P378, DOI 10.32614/RJ-2017-066
   Burnham K. P., 2002, Model selection and inference: a practical informationtheoretic approach, VSecond edition
   Canadell JG, 2008, SCIENCE, V320, P1456, DOI 10.1126/science.1155458
   Canham CD, 1999, OECOLOGIA, V121, P1, DOI 10.1007/s004420050900
   Canham CD, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1424
   Champagne E, 2021, FOREST ECOL MANAG, V498, DOI 10.1016/j.foreco.2021.119576
   Clark P.W., 2021, DRYAD DIGITAL REPOSI, DOI 10.5061/dryad.brv15dvb1
   Closset-Kopp D, 2007, FOREST ECOL MANAG, V247, P120, DOI 10.1016/j.foreco.2007.04.023
   COX DR, 1972, J R STAT SOC B, V34, P187
   D'Amato AW, 2021, CAN J FOREST RES, V51, P172, DOI 10.1139/cjfr-2020-0306
   Domkea GM, 2020, P NATL ACAD SCI USA, V117, P24649, DOI 10.1073/pnas.2010840117
   Dumais D, 2007, FOREST CHRON, V83, P378, DOI 10.5558/tfc83378-3
   Duveneck MJ, 2015, ECOL APPL, V25, P1653, DOI 10.1890/14-0738.1
   Dyderski MK, 2019, NEOBIOTA, P91, DOI 10.3897/neobiota.41.31908
   Etterson JR, 2020, ECOL APPL, V30, DOI 10.1002/eap.2092
   Fargione J, 2021, FRONT FOR GLOB CHANG, V4, DOI 10.3389/ffgc.2021.629198
   Federal-Register, 2020, EX ORD EST ON TRILL
   George LO, 1999, ECOLOGY, V80, P846, DOI 10.1890/0012-9658(1999)080[0846:TFUAAE]2.0.CO;2
   Gray LK, 2011, ECOL APPL, V21, P1591, DOI 10.1890/10-1054.1
   Griffith G.E., 2009, ECOREGIONS NEW ENGLA
   Gurney KM, 2011, RESTOR ECOL, V19, P55, DOI 10.1111/j.1526-100X.2009.00544.x
   Haase D.L., 2008, Tree Planter's Notes, V52, P24
   Hanson JJ, 2007, ECOL APPL, V17, P1325, DOI 10.1890/06-1067.1
   HIBBS DE, 1982, CAN J BOT, V60, P2046, DOI 10.1139/b82-252
   Hunt R, 1997, NEW PHYTOL, V135, P395, DOI 10.1046/j.1469-8137.1997.00671.x
   Iverson LR, 2019, FORESTS, V10, DOI 10.3390/f10110989
   Jacobs DF, 2005, FOREST ECOL MANAG, V214, P28, DOI 10.1016/j.foreco.2005.03.053
   JANOWIAK M. K, 2018, US FOR SERV GEN TECH, V173, P1
   Johnstone JF, 2016, FRONT ECOL ENVIRON, V14, P369, DOI 10.1002/fee.1311
   Keeley JE, 2011, TRENDS PLANT SCI, V16, P406, DOI 10.1016/j.tplants.2011.04.002
   Kenefic LS, 2021, CAN J FOREST RES, V51, P921, DOI 10.1139/cjfr-2020-0410
   Kobe RK, 1997, OIKOS, V80, P226, DOI 10.2307/3546590
   Kuehne C, 2014, TREE PHYSIOL, V34, P184, DOI 10.1093/treephys/tpt124
   Löf M, 2019, NEW FOREST, V50, P139, DOI 10.1007/s11056-019-09713-0
   Lyons J., 1997, USGS Bedrock geology of New Hampshire
   MacFarlane DW, 2006, CAN J FOREST RES, V36, P1695, DOI 10.1139/X06-054
   MANLEY SAM, 1979, CAN J BOT, V57, P305, DOI 10.1139/b79-042
   Martinussen T., 2006, STAT BIOL HEALTH
   McDowell NG, 2020, SCIENCE, V368, P964, DOI 10.1126/science.aaz9463
   Messier C, 2019, FOR ECOSYST, V6, DOI 10.1186/s40663-019-0166-2
   Miles P.D., 2009, USDA For. Serv. Res. Note NRS-RN-38, P35, DOI DOI 10.2737/NRS-RN-38
   Millar CI, 2007, ECOL APPL, V17, P2145, DOI 10.1890/06-1715.1
   Muller JJ, 2019, FOREST ECOL MANAG, V451, DOI 10.1016/j.foreco.2019.117539
   Nagel LM, 2017, J FOREST, V115, P167, DOI 10.5849/jof.16-039
   NCDC, 2020, NAT OC ATM ADM NAT C
   Niinemets Ü, 2006, ECOL MONOGR, V76, P521, DOI 10.1890/0012-9615(2006)076[0521:TTSDAW]2.0.CO;2
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Paquette A, 2011, GLOBAL ECOL BIOGEOGR, V20, P170, DOI 10.1111/j.1466-8238.2010.00592.x
   Park A, 2018, BIOSCIENCE, V68, P251, DOI 10.1093/biosci/biy001
   Park A, 2014, CRIT REV PLANT SCI, V33, P251, DOI 10.1080/07352689.2014.858956
   Pedlar JH, 2012, BIOSCIENCE, V62, P835, DOI 10.1525/bio.2012.62.9.10
   Peters M.P., 2020, Climate change tree atlas
   Plotkin AB, 2013, ECOLOGY, V94, P414, DOI 10.1890/12-0487.1
   R Core Team, 2019, R LANG ENV STAT COMP
   Ratcliffe N., 2011, USGS Bedrock geology of Vermont
   Raymond P, 2018, FOREST ECOL MANAG, V430, P21, DOI 10.1016/j.foreco.2018.07.054
   Rietveld W. J., 1989, Northern Journal of Applied Forestry, V6, P99
   Royo AA, 2006, CAN J FOREST RES, V36, P1345, DOI 10.1139/X06-025
   SAS-Institute-Inc, 2013, SAS ACCESS
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   Seymour RS, 2002, FOREST ECOL MANAG, V155, P357, DOI 10.1016/S0378-1127(01)00572-2
   Sittaro F, 2017, GLOBAL CHANGE BIOL, V23, P3292, DOI 10.1111/gcb.13622
   Spies TA, 2010, LANDSCAPE ECOL, V25, P1185, DOI 10.1007/s10980-010-9483-0
   Steiner KC, 2017, NEW FOREST, V48, P317, DOI 10.1007/s11056-016-9561-5
   STRUVE DK, 1992, CAN J FOREST RES, V22, P1441, DOI 10.1139/x92-194
   Swanston C., 2016, NRS872 GTP, P120
   Tepe TL, 2011, RESTOR ECOL, V19, P295, DOI 10.1111/j.1526-100X.2010.00748.x
   Thomas SC, 1996, EVOL ECOL, V10, P517, DOI 10.1007/BF01237882
   Thompson E., 2019, Wetland, Woodland, Wildland: A Guide to the Natural Communities of Vermont, V2nd
   Vilmorin D., 1862, Memoires Soc. Imp. Cent. Agric. Fr, P297
   Webster CR, 2018, FOREST ECOL MANAG, V421, P98, DOI 10.1016/j.foreco.2018.01.010
   Williams MI, 2013, J FOREST, V111, P287, DOI 10.5849/jof.13-016
   Woodall CW, 2011, NRS-GTR-88, P30, DOI [DOI 10.2737/NRS-GTR-88, 10.2737/nrs-gtr-88]
NR 83
TC 20
Z9 25
U1 1
U2 38
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0021-8901
EI 1365-2664
J9 J APPL ECOL
JI J. Appl. Ecol.
PD JAN
PY 2022
VL 59
IS 1
BP 314
EP 329
DI 10.1111/1365-2664.14056
EA OCT 2021
PG 16
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA YB9BC
UT WOS:000710103600001
DA 2025-01-10
ER

PT J
AU Mai, T
   Mushtaq, S
   Tong, YD
   Nguyen-Huy, T
   Richards, R
   Marcussen, T
AF Mai, Thanh
   Mushtaq, Shahbaz
   Tong, Yen Dan
   Nguyen-Huy, Thong
   Richards, Russell
   Marcussen, Torben
TI Harnessing a systems approach for sustainable adaptation in vulnerable
   mega-deltas: A case study of the dyke heightening program in the
   Vietnamese Mekong Delta's floodplains
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
ID ENVIRONMENTAL-CHANGE; GANGES-BRAHMAPUTRA; CLIMATE ADAPTATION; DYNAMICS;
   RESILIENCE; THINKING; IMPACTS; LESSONS; FUTURE; RISK
C1 [Mai, Thanh; Mushtaq, Shahbaz; Nguyen-Huy, Thong; Marcussen, Torben] Univ Southern Queensland, Ctr Appl Climate Sci, 487-535 West St, Toowoomba, Qld 4350, Australia.
   [Tong, Yen Dan] La Trobe Univ, La Trobe Business Sch, Melbourne, Vic 3086, Australia.
   [Tong, Yen Dan] Can Tho Univ, Sch Econ, Can Tho, Vietnam.
   [Nguyen-Huy, Thong] Vietnam Acad Sci & Technol, Ho Chi Minh City Space Technol Applicat Ctr, Vietnam Natl Space Ctr, Ho Chi Minh City, Vietnam.
   [Richards, Russell] Univ Queensland, Fac Business Econ & Laws, Brisbane, Qld 4067, Australia.
C3 University of Southern Queensland; La Trobe University; Can Tho
   University; Vietnam Academy of Science & Technology (VAST); University
   of Queensland
RP Mai, T (corresponding author), Univ Southern Queensland, Ctr Appl Climate Sci, 487-535 West St, Toowoomba, Qld 4350, Australia.
EM thanh.mai@usq.edu.au
FU Federal Ministry for Economic Affairs and Climate Action (BMWK); Federal
   Ministry for the Environment, Nature Conservation, Nuclear Safety, and
   Consumer Protection (BMUV); Federal Foreign Office (AA) through the
   International Climate Initiative (IKI)
FX This work was supported by the Federal Ministry for Economic Affairs and
   Climate Action (BMWK) in close cooperation with the Federal Ministry for
   the Environment, Nature Conservation, Nuclear Safety, and Consumer
   Protection (BMUV) , and the Federal Foreign Office (AA) through the
   International Climate Initiative (IKI) .
CR Almar R, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-24008-9
   [Anonymous], 2022, International Journal of Engineering Education
   [Anonymous], 2000, Business Dynamics: Systems Thinking and Modeling for a Complex World
   Arnold RD, 2015, PROCEDIA COMPUT SCI, V44, P669, DOI 10.1016/j.procs.2015.03.050
   Arto I, 2019, SCI TOTAL ENVIRON, V648, P1284, DOI 10.1016/j.scitotenv.2018.08.139
   Berrang-Ford L, 2021, NAT CLIM CHANGE, V11, P989, DOI 10.1038/s41558-021-01170-y
   Berry HL, 2018, NAT CLIM CHANGE, V8, P282, DOI 10.1038/s41558-018-0102-4
   Bishop MJ, 2017, J EXP MAR BIOL ECOL, V492, P7, DOI 10.1016/j.jembe.2017.01.021
   Lebbe TB, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.740602
   Bosch OJH, 2013, SYST RES BEHAV SCI, V30, P116, DOI 10.1002/sres.2171
   Braun W., 2002, SYSTEM ARCHETYPES
   Chapman A, 2016, SCI TOTAL ENVIRON, V559, P326, DOI 10.1016/j.scitotenv.2016.02.162
   Craig R.K., 2019, SSRN Electron. J., DOI [10.2139/ssrn.3401301, DOI 10.2139/SSRN.3401301]
   Day JW, 2016, ESTUAR COAST SHELF S, V183, P275, DOI 10.1016/j.ecss.2016.06.018
   Tran DD, 2019, AGR WATER MANAGE, V223, DOI 10.1016/j.agwat.2019.105703
   Tran DD, 2018, HYDROL EARTH SYST SC, V22, P1875, DOI 10.5194/hess-22-1875-2018
   Duy V. T., 2021, International Journal of Sustainable Development Research, V7, P28, DOI [10.11648/j.ijsdr.20210702.11, DOI 10.11648/J.IJSDR.20210702.11, https://doi.org/10.11648/j.ijsdr.20210702.11]
   Edmonds DA, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18531-4
   Esteban M, 2019, OCEAN COAST MANAGE, V168, P35, DOI 10.1016/j.ocecoaman.2018.10.031
   Gain AK, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01692-9
   Giosan L, 2014, NATURE, V516, P31, DOI 10.1038/516031a
   Gracia A, 2018, OCEAN COAST MANAGE, V156, P277, DOI 10.1016/j.ocecoaman.2017.07.009
   Hagenlocher M, 2018, SCI TOTAL ENVIRON, V631-632, P71, DOI 10.1016/j.scitotenv.2018.03.013
   Hinkel J, 2018, NAT CLIM CHANGE, V8, P570, DOI 10.1038/s41558-018-0176-z
   Hutton CW, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13105534
   Hutton CW, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041108
   Jankowski KL, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14792
   Jeuken A, 2015, J WATER CLIM CHANGE, V6, P711, DOI 10.2166/wcc.2014.141
   Jones B, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/8/084003
   Kelly RA, 2013, ENVIRON MODELL SOFTW, V47, P159, DOI 10.1016/j.envsoft.2013.05.005
   Kirezci E, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67736-6
   Kuenzer C, 2012, ENVIRON SCI ENG, P7, DOI 10.1007/978-94-007-3962-8_2
   Laimon M., 2022, International Journal of Thermofluids, p, P100161, DOI [10.1016/j.ijft.2022.100161, DOI 10.1016/J.IJFT.2022.100161]
   Loucks DP, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4165
   Lwasa S, 2015, REG ENVIRON CHANGE, V15, P815, DOI 10.1007/s10113-014-0715-8
   Maani K.E., 2007, Systems thinking, system dynamics: Managing change and complexity
   Maedows D., 1999, LEVERAGE POINTS PLAC
   Mai T, 2015, J SUSTAIN TOUR, V23, P1504, DOI 10.1080/09669582.2015.1045514
   McLean S, 2019, FRONT SPORTS ACT LIV, V1, DOI 10.3389/fspor.2019.00049
   Meadows DH, 2008, THINKING SYSTEMS PRI
   Minderhoud PSJ, 2020, ENVIRON RES COMMUN, V2, DOI 10.1088/2515-7620/ab5e21
   Minderhoud PSJ, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-11602-1
   Triet NVK, 2017, HYDROL EARTH SYST SC, V21, P3991, DOI 10.5194/hess-21-3991-2017
   Nicholls RJ, 2016, ESTUAR COAST SHELF S, V183, P370, DOI 10.1016/j.ecss.2016.08.017
   Nicholls R.J., 2020, Deltas in the Anthropocene, P282, DOI [10.1007/978-3-030-23517-8, DOI 10.1007/978-3-030-23517-8]
   Nicholls RJ, 2021, NAT CLIM CHANGE, V11, P338, DOI 10.1038/s41558-021-00993-z
   Perry J, 2015, LANDSCAPE URBAN PLAN, V133, P1, DOI 10.1016/j.landurbplan.2014.08.013
   Perry W.H., 2022, Bulletin of the Atomic Scientists
   Pham NTT, 2020, WEST PAC SURVEILL RE, V11, DOI 10.5365/wpsar.2018.9.2.012
   Portner H.-O., 2019, IPCC SPECIAL REPORT, DOI [10.1017/9781009157964, DOI 10.1017/9781009157964]
   Renaud F, 2016, SUSTAIN SCI, V11, P519, DOI 10.1007/s11625-016-0380-6
   Rich KM, 2018, AGR SYST, V160, P110, DOI 10.1016/j.agsy.2016.09.022
   Ross H, 2015, CLIMATIC CHANGE, V129, P27, DOI 10.1007/s10584-014-1318-6
   Royal HaskoningDHV, 2013, Mekong Delta Plan: Long-Term Vision and Strategy for a Safe, Prosperous and Sustainable Delta
   Sahin O, 2020, SYSTEMS-BASEL, V8, DOI 10.3390/systems8020020
   Schelfaut K, 2011, ENVIRON SCI POLICY, V14, P825, DOI 10.1016/j.envsci.2011.02.009
   Seo BK, 2021, PUBLIC HEALTH NUTR, V24, P4339, DOI 10.1017/S1368980021001002
   Smajgl A, 2015, NAT CLIM CHANGE, V5, P167, DOI [10.1038/NCLIMATE2469, 10.1038/nclimate2469]
   Sutton-Grier AE, 2015, ENVIRON SCI POLICY, V51, P137, DOI 10.1016/j.envsci.2015.04.006
   Szabo S, 2016, SUSTAIN SCI, V11, P539, DOI 10.1007/s11625-016-0372-6
   Szabo S, 2016, ENVIRONMENT, V58, P24, DOI 10.1080/00139157.2016.1209016
   Termeer CJAM, 2016, LANDSCAPE URBAN PLAN, V154, P11, DOI 10.1016/j.landurbplan.2016.01.007
   Tessler ZD, 2015, SCIENCE, V349, P638, DOI 10.1126/science.aab3574
   Mai T, 2020, INT J DISAST RISK RE, V47, DOI 10.1016/j.ijdrr.2020.101550
   Tran TA, 2021, SCI TOTAL ENVIRON, V770, DOI 10.1016/j.scitotenv.2021.145125
   Tong YD, 2020, J ASIA PAC ECON, V25, P124, DOI 10.1080/13547860.2019.1636605
   TRAN T., 2017, Water Resour. Rural. Dev, V9, P67, DOI [https://doi.org/10.1016/j.wrr.2017.04.002, DOI 10.1016/J.WRR.2017.04.002, 10.1016/j.wrr.2017.04.002]
   van der Most Herman., 2009, Towards Sustainable Development of Deltas, Estuaries and Coastal Zones: Description of Eight Selected Deltas
   VnExpress International, 2024, Cambodia's Funan Techo canal could upset Mekong Delta ecosystem experts: Cambodia's Funan Techo canal could upset Mekong Delta ecosystem: experts-VnExpress International
   Thanh VQ, 2020, HYDROL EARTH SYST SC, V24, P189, DOI 10.5194/hess-24-189-2020
   Xuan NV, 2022, WATER SUPPLY, V22, P7945, DOI 10.2166/ws.2022.333
NR 71
TC 0
Z9 0
U1 1
U2 1
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD DEC 1
PY 2024
VL 954
AR 176501
DI 10.1016/j.scitotenv.2024.176501
EA SEP 2024
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA I3V6B
UT WOS:001329569600001
PM 39326749
OA hybrid
DA 2025-01-10
ER

PT J
AU Flachowsky, H
   Töpfer, R
AF Flachowsky, Henryk
   Toepfer, Reinhard
TI Fruit and grapevine breeding in time lapse
SO JOURNAL FUR KULTURPFLANZEN
LA English
DT Article
DE fruit breeding; grapevine breeding; durable resistance; scab; powdery
   mildew; black rot; botrytis; climate adaptation
ID LIGHT-SEPARATION; APPLE; RESISTANCE; GENE
AB Since not many people outlive 100 years, it appears that time stands still during the 20 to 30 years, which is required to develop a new variety in fruit and grapevine breeding. However, a time-lapse will reveal considerable breeding progress with the development of many new cultivars. Although breeding requirements and objectives of recent times are described in different vocabulary, not much has changed from times past. For example, problems of combating harmful organisms (food security, lack of plant protection products) are just as much a focus today (loss of active ingredients and sustainability) as in the past. In addition, breeding for climatic adaptation in the past (for earlier maturity, for example) is same as today, only (at least for grapevine) the goal is reversed for late maturity traits.In the wake of the 'Green Deal' with its 'Farm to Fork Strategy', the EU has set ambitious goals and long overdue targets for achieving 'green agriculture' with minimization of negative impacts on the natural environment. The ambitious goal of halving the use of pesticides requires adaptation of all farming systems, especially for pesticide-intensive crops such as orchards and vineyards. These crops also represent in a special way a cultural landscape with high economic power through local recreation and tourism.Ambitious goals can only be achieved by implementing innovations. However, given the transformation goals towards sustainability, individual entrepreneurial innovation is not enough to achieve the ambitious goals. Thus, a systemic approach to innovation is required. In a system that has previously experienced huge success, there are sometimes tendencies to not innovate. Nevertheless, the current and future challenge is clear: climate change is forcing breeding for climatic adaptation that will ultimately lead to variety change. This situation presents an opportunity for new robust varieties.
C1 [Flachowsky, Henryk] Julius Kuhn Inst JKI, Inst Zuchtungsforsch Obst, Bundesforsch Inst Kulturpflanzen, Dresden, Germany.
   [Toepfer, Reinhard] Julius Kuhn Inst JKI, Inst Rebenzuchtung, Bundesforsch Inst Kulturpflanzen, Siebeldingen, Germany.
   [Flachowsky, Henryk] Julius Kuhn Inst JKI, Inst Zuchtungs Forsch Obst, Bundesforsch Inst Kulturpflanzen, Pillnitzer Pl 3a, D-01326 Dresden, Germany.
C3 Julius Kuhn-Institut; Julius Kuhn-Institut; Julius Kuhn-Institut
RP Flachowsky, H (corresponding author), Julius Kuhn Inst JKI, Inst Zuchtungs Forsch Obst, Bundesforsch Inst Kulturpflanzen, Pillnitzer Pl 3a, D-01326 Dresden, Germany.
EM henryk.flachowsky@julius-kuehn.de
RI Flachowsky, Henryk/B-6828-2018
CR Barré P, 2019, COMPUT ELECTRON AGR, V156, P263, DOI 10.1016/j.compag.2018.11.012
   Broggini GAL, 2014, PLANT BIOTECHNOL J, V12, P728, DOI 10.1111/pbi.12177
   Giacomelli L, 2019, ACTA HORTIC, V1248, P195, DOI 10.17660/ActaHortic.2019.1248.28
   Hanke MV., 2020, BIOTECHNOLOGY FRUIT, VEd 2, P440, DOI 10.1079/9781780648279.0440
   Haucke T, 2021, VITIS, V60, P1, DOI 10.5073/vitis.2021.60.1-10
   Herzog K, 2015, SENSORS-BASEL, V15, P12498, DOI 10.3390/s150612498
   Pessina S, 2017, MOL BREEDING, V37, DOI 10.1007/s11032-016-0610-8
   Pessina S, 2016, PLANT BIOTECHNOL J, V14, P2033, DOI 10.1111/pbi.12562
   Richter R, 2020, THEOR APPL GENET, V133, P3249, DOI 10.1007/s00122-020-03667-0
   Rist F, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11242953
   Rossmann S, 2020, PLANT J, V101, P1234, DOI 10.1111/tpj.14588
   Schouten HJ, 2014, TREE GENET GENOMES, V10, P251, DOI 10.1007/s11295-013-0678-9
   Tpfer R., 2011, Fruit Veg. Cereal Sci. Biotechnol, V5, P79
   Vanblaere T, 2011, J BIOTECHNOL, V154, P304, DOI 10.1016/j.jbiotec.2011.05.013
NR 14
TC 2
Z9 2
U1 0
U2 3
PU Julius Kuhn Inst - JKI
PI Quedlinburg
PA Erwin-Baur-Str. 27, Quedlinburg, GERMANY
SN 1867-0911
EI 1867-0938
J9 J KULT
JI J. Kult.
PY 2021
VL 73
IS 7-8
BP 197
EP 203
DI 10.5073/JfK.2021.07-08.03
PG 7
WC Agronomy; Plant Sciences
WE Emerging Sources Citation Index (ESCI)
SC Agriculture; Plant Sciences
GA S6BE0
UT WOS:001071988200004
DA 2025-01-10
ER

PT J
AU Derkzen, ML
   van Teeffelen, AJA
   Verburg, PH
AF Derkzen, Marthe L.
   van Teeffelen, Astrid J. A.
   Verburg, Peter H.
TI Green infrastructure for urban climate adaptation: How do residents'
   views on climate impacts and green infrastructure shape adaptation
   preferences?
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Ecosystem services; Nature-based solutions; Urban flooding; Urban heat;
   Urban planning; Willingness to pay
ID ECOSYSTEM SERVICES; CITIES; VALUES; PERCEPTION; MORTALITY; FRAMEWORK;
   BENEFITS; SPACES; SCALE; CITY
AB Cities are particularly prone to the effects of climate change. One way for cities to adapt is by enhancing their green infrastructure (GI) to mitigate the impacts of heat waves and flooding. While alternative GI design options exist, there are many unknoWns regarding public support for the various options. This study aims to fill this gap by performing a socio-cultural valuation of urban GI for climate adaptation that encompasses multiple dimensions: people's notion of and concerns about climate impacts, the degree to which people acknowledge the benefits of GI to alleviate such impacts, and people's preferences for different GI measures, including their willingness to pay (WTP). Data were collected through photo-assisted face-to-face surveys (n=200.) with residents in Rotterdam, the Netherlands, and linked to GI GIS data. Respondents had a notion of and concerns about climate impacts, but did not necessarily acknowledge that GI may help tackle these issues. Yet, when residents were informed about the adaptation capacity of different GI measures, their preferences shifted towards the most effective options. There was no information effect, however, on people's WTP for GI, which was mostly related to income and ethnicity. Our study shows that economic valuation alone would miss nuances that socio-cultural valuation as applied in this paper can reveal. The method revealed preferences for particular adaptation designs, and assists in detecting why policy for climate adaptation may be hampered. Understanding people's views on climate impacts and adaptation options is crucial for prioritizing effective policy responses in the face of climate change. (C) 2016 Elsevier B.V. All rights reserved.
C1 [Derkzen, Marthe L.; van Teeffelen, Astrid J. A.; Verburg, Peter H.] Vrije Univ Amsterdam, Environm Geog Grp, Dept Earth Sci, Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands.
C3 Vrije Universiteit Amsterdam
RP Derkzen, ML (corresponding author), Vrije Univ Amsterdam, Environm Geog Grp, Dept Earth Sci, Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands.
EM marthe.derkzen@vu.nl; astrid.van.teeffelen@vu.nl; peter.verburg@vu.nl
RI Van Teeffelen, Astrid/L-1320-2013; Verburg, Peter/Z-1582-2019; Verburg,
   Peter/A-8469-2010
OI Derkzen, Marthe/0000-0003-2545-8045; Verburg, Peter/0000-0002-6977-7104
FU European Union [282834 "TURAS", 308393 "OPERAs"]
FX We like to thank Annemarijn Plukaard for fieldwork assistance. This
   research was financially supported by the European Union's Seventh
   Framework Programme (FP7/2007-2013) under grant agreement no. 282834
   "TURAS" and no. 308393 "OPERAs".
CR Andersson E, 2015, ECOSYST SERV, V12, P157, DOI 10.1016/j.ecoser.2014.08.001
   Anguelovski I, 2014, GLOBAL ENVIRON CHANG, V27, P156, DOI 10.1016/j.gloenvcha.2014.05.010
   [Anonymous], 2012, URBAN ADAPTATION CLI
   Baptiste AK, 2015, LANDSCAPE URBAN PLAN, V136, P1, DOI 10.1016/j.landurbplan.2014.11.012
   Barona CO, 2015, J ENVIRON MANAGE, V164, P215, DOI 10.1016/j.jenvman.2015.09.004
   Berghofer Augustin., 2011, The Economics of Ecosystems and Biodiversity
   Broto VC, 2015, CURR OPIN ENV SUST, V13, P11, DOI 10.1016/j.cosust.2014.12.005
   Buijs AE, 2009, LANDSCAPE URBAN PLAN, V91, P113, DOI 10.1016/j.landurbplan.2008.12.003
   Burger J, 2015, URBAN ECOSYST, V18, P553, DOI 10.1007/s11252-014-0412-x
   Byrne JA, 2015, LANDSCAPE URBAN PLAN, V138, P132, DOI 10.1016/j.landurbplan.2015.02.013
   Carter JG, 2015, PROG PLANN, V95, P1, DOI 10.1016/j.progress.2013.08.001
   Castro AJ, 2011, J ARID ENVIRON, V75, P1201, DOI 10.1016/j.jaridenv.2011.05.013
   Church SP, 2015, LANDSCAPE URBAN PLAN, V134, P229, DOI 10.1016/j.landurbplan.2014.10.021
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   Derkzen ML, 2015, J APPL ECOL, V52, P1020, DOI 10.1111/1365-2664.12469
   Gao JH, 2015, SCI TOTAL ENVIRON, V505, P535, DOI 10.1016/j.scitotenv.2014.10.028
   Hansen R, 2014, AMBIO, V43, P516, DOI 10.1007/s13280-014-0510-2
   Headache classification Committee of the International Headache Society (IHS), 2018, Cephalalgia, V38, P1, DOI [10.1177/0333102417738202, DOI 10.1177/0333102417738202, DOI 10.2833/9937]
   Hunter MCR, 2012, LANDSCAPE URBAN PLAN, V105, P407, DOI 10.1016/j.landurbplan.2012.01.013
   Jim CY, 2013, CITIES, V31, P123, DOI 10.1016/j.cities.2012.06.017
   Klemm W, 2015, LANDSCAPE URBAN PLAN, V138, P87, DOI 10.1016/j.landurbplan.2015.02.009
   Klemm W, 2015, BUILD ENVIRON, V83, P120, DOI 10.1016/j.buildenv.2014.05.013
   Lo AY, 2010, URBAN FOR URBAN GREE, V9, P113, DOI 10.1016/j.ufug.2010.01.001
   Lo AYH, 2012, LAND USE POLICY, V29, P577, DOI 10.1016/j.landusepol.2011.09.011
   Madureira H, 2015, URBAN FOR URBAN GREE, V14, P56, DOI 10.1016/j.ufug.2014.11.008
   Matthews T, 2015, LANDSCAPE URBAN PLAN, V138, P155, DOI 10.1016/j.landurbplan.2015.02.010
   Muratet A, 2015, LANDSCAPE URBAN PLAN, V137, P95, DOI 10.1016/j.landurbplan.2015.01.003
   Ng WY, 2015, URBAN FOR URBAN GREE, V14, P30, DOI 10.1016/j.ufug.2014.11.002
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   Priego C., 2008, Landscape Online
   Rosenthal JK, 2014, HEALTH PLACE, V30, P45, DOI 10.1016/j.healthplace.2014.07.014
   Shackleton S, 2015, LANDSCAPE URBAN PLAN, V136, P76, DOI 10.1016/j.landurbplan.2014.12.004
   Silvertown J, 2015, TRENDS ECOL EVOL, V30, P641, DOI 10.1016/j.tree.2015.08.007
   Sussams LW, 2015, J ENVIRON MANAGE, V147, P184, DOI 10.1016/j.jenvman.2014.09.003
   UN-HABITAT, 2011, GLOB REP HUM SETTL 2
   Uren HV, 2015, LANDSCAPE URBAN PLAN, V137, P76, DOI 10.1016/j.landurbplan.2014.12.008
   Visscher RS, 2014, LANDSCAPE URBAN PLAN, V132, P37, DOI 10.1016/j.landurbplan.2014.08.004
   Vollmer D, 2015, LANDSCAPE URBAN PLAN, V138, P144, DOI 10.1016/j.landurbplan.2015.02.011
NR 38
TC 218
Z9 243
U1 34
U2 469
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0169-2046
EI 1872-6062
J9 LANDSCAPE URBAN PLAN
JI Landsc. Urban Plan.
PD JAN
PY 2017
VL 157
BP 106
EP 130
DI 10.1016/j.landurbplan.2016.05.027
PG 25
WC Ecology; Environmental Studies; Geography; Geography, Physical; Regional
   & Urban Planning; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography; Physical Geography; Public
   Administration; Urban Studies
GA EF2VI
UT WOS:000390183300011
OA Green Published
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Kori, DS
AF Kori, Dumisani Shoko
TI A typology of climate adaptation costs for a smallholder maize farming
   system
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Adaptation; Challenges; Dangers; Mis-implementation; Unintended
   consequences; Smallholder farmers
ID SEA-LEVEL; FARMERS; VULNERABILITY; DISTRICT; AGRICULTURE; POVERTY
AB Understanding adaptation costs among smallholder farmers is essential in developing more tar-geted policy frameworks. This study was carried out to develop a typology of adaptation costs for a smallholder maize farming system. An exploratory sequential mixed methods research design was adopted. Semi-structured interviews with smallholder maize farmers were conducted to gather qualitative data on adaptation costs. Qualitative data on adaptation costs was transformed into quantitative binary data and subjected to Agglomerative Hierarchical Clustering using the Squared Euclidean Distance and Between-Groups Linkage methods. This led to the development of a typology of adaptation costs with twenty-one homogenous clusters and six distinct categories out of the 119 climate adaptation costs established. The typology developed encompasses the intangible, indirect, non-economic and non-market costs. It simplifies the complexity associated with adaptation costs in general, can be useful as a management tool and could be essential in facilitating adaptation cost inventories. It is recommended that national governments should develop capacity building programmes aimed at raising awareness of adaptation costs among smallholder farmers. Training and mentorship programs aimed at enhancing proper imple-mentation of adaptation measures among smallholder farmers are also pertinent to reduce mis-implementation and maladaptive practices that increase the cost of adaptation among small-holder farmers.
C1 [Kori, Dumisani Shoko] Univ Johannesburg, Fac Sci, Dept Geog Environm Management & Energy Studies, Auckland Pk, ZA-2093 Johannesburg, South Africa.
C3 University of Johannesburg
RP Kori, DS (corresponding author), Univ Johannesburg, Fac Sci, Dept Geog Environm Management & Energy Studies, Auckland Pk, ZA-2093 Johannesburg, South Africa.
EM d_shoko@yahoo.com
OI Shoko Kori, Dumisani/0000-0002-2046-4385
CR Adeagbo OA, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e06231
   Adelman S, 2016, J HUM RIGHTS ENVIRON, V7, P32, DOI 10.4337/jhre.2016.01.02
   Agrawala S., 2008, Economic Aspects of Adaptation to Climate Change
   Agrawala S, 2011, INT REV ENVIRON RESO, V5, P245, DOI 10.1561/101.00000043
   Amjath-Babu TS, 2019, CLIM POLICY, V19, P283, DOI 10.1080/14693062.2018.1501329
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P5045, DOI 10.1007/s10668-019-00414-4
   Asplund T, 2020, LOCAL ENVIRON, V25, P114, DOI 10.1080/13549839.2020.1712340
   Asugeni J, 2015, AUSTRALAS PSYCHIATRY, V23, P22, DOI 10.1177/1039856215609767
   Atteridge A., 2018, WIRES COMPUT STAT, V9, P500
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Biesbroek GR, 2013, REG ENVIRON CHANGE, V13, P1119, DOI 10.1007/s10113-013-0421-y
   Brady SP, 2019, EVOL APPL, V12, P1229, DOI 10.1111/eva.12844
   Butler CD, 2010, POSTGRAD MED J, V86, P230, DOI 10.1136/pgmj.2009.082727
   Carey M, 2012, J HIST GEOGR, V38, P181, DOI 10.1016/j.jhg.2011.12.002
   Chambwera M, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P945
   Chapagain D, 2020, CLIM DEV, V12, P934, DOI 10.1080/17565529.2020.1711698
   Chiba Y., 2019, APN SCI B
   Chikodzi D., 2013, Journal of Sustainable Development in Africa, V15, P104
   Chiweshe M. K., 2014, Occasional Papers on Green Economy and Sustainable Development - United Nations Research Institute for Social Development
   Clayton S, 2020, J ANXIETY DISORD, V74, DOI 10.1016/j.janxdis.2020.102263
   Clayton S, 2020, J ENVIRON PSYCHOL, V69, DOI 10.1016/j.jenvp.2020.101434
   Creswell J. W., 2007, Designing and Conducting Mixed Methods Research
   Dasgupta P., 2016, ASSESSING COSTS BENE
   Dasgupta S, 2022, WORLD DEV, V150, DOI 10.1016/j.worlddev.2021.105707
   Dawson D, 2016, J TRANSP GEOGR, V51, P97, DOI 10.1016/j.jtrangeo.2015.11.009
   De Nijs P.J., 2014, SCI REPORTS, V4, P1
   Diaz D, 2017, NAT CLIM CHANGE, V7, P774, DOI [10.1038/nclimate3411, 10.1038/NCLIMATE3411]
   Donatti CI, 2019, CLIM DEV, V11, P264, DOI 10.1080/17565529.2018.1442796
   Dube T., 2018, WILL ADAPTATION CARR
   Dube Thulani, 2018, Journal of Human Ecology, V61, P20, DOI 10.1080/09709274.2018.1452866
   Eisenack K, 2014, NAT CLIM CHANGE, V4, P867, DOI 10.1038/NCLIMATE2350
   Eriksen SH, 2007, CLIM POLICY, V7, P337, DOI 10.1080/14693062.2007.9685660
   Etikan I., 2016, American Journal of Theoretical and Applied Statistics, V5, P1, DOI DOI 10.11648/J.AJTAS.20160501.11
   Fankhauser S., 1998, COSTS ADAPTING CLIMA
   Fankhauser S, 2011, CLIM DEV, V3, P94, DOI 10.1080/17565529.2011.582267
   Fankhauser S, 2010, WIRES CLIM CHANGE, V1, P23, DOI 10.1002/wcc.14
   Fattouh Bassam, 2019, Energy Transitions, V3, P45, DOI 10.1007/s41825-019-00013-x
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Friese S., 2016, CAQDAS GROUNDED THEO
   Gibson K, 2019, TRANSCULT PSYCHIATRY, V56, P667, DOI 10.1177/1363461519847057
   Gifford R, 2011, AM PSYCHOL, V66, P290, DOI 10.1037/a0023566
   Glover L, 2021, CLIMATE, V9, DOI 10.3390/cli9050069
   Halcomb EJ, 2006, APPL NURS RES, V19, P38, DOI 10.1016/j.apnr.2005.06.001
   Harvey C. A., 2018, Agriculture & Food Security, V7, P57, DOI 10.1186/s40066-018-0209-x
   Holland MB, 2017, CLIMATIC CHANGE, V141, P139, DOI 10.1007/s10584-016-1810-2
   Iizumi T, 2020, CLIM RES, V80, P203, DOI 10.3354/cr01605
   Iizumi T, 2019, ADAPTATION TO CLIMATE CHANGE IN AGRICULTURE: RESEARCH AND PRACTICES, P3, DOI 10.1007/978-981-13-9235-1_1
   Insarov GE, 2022, Climate change 2022: impacts, adaptation, and vulnerability. Contribution of working group II to the sixth assessment report of the intergovernmental panel on climate change
   Jamshidi O, 2019, CLIM RISK MANAG, V23, P146, DOI 10.1016/j.crm.2018.06.002
   Juhola S, 2016, ENVIRON SCI POLICY, V55, P135, DOI 10.1016/j.envsci.2015.09.014
   Kallio H, 2016, J ADV NURS, V72, P2954, DOI 10.1111/jan.13031
   Karlsson M, 2020, CLIM POLICY, V20, P292, DOI 10.1080/14693062.2020.1724070
   Kaufman Leonard, 2009, FINDING GROUPS DATA
   Kori D.S., 2021, AFRICAN HDB CLIMATE
   Kori DS, 2020, J RURAL STUD, V79, P145, DOI 10.1016/j.jrurstud.2020.08.012
   Lani J., 2010, CONDUCT INTERPRET CL
   Liang YT, 2017, HABITAT INT, V59, P21, DOI 10.1016/j.habitatint.2016.11.008
   Luis S, 2018, J ENVIRON MANAGE, V223, P165, DOI 10.1016/j.jenvman.2018.06.020
   Macia L, 2015, QUAL REP, V20, P1083
   MacLean LM, 2004, QUAL HEALTH RES, V14, P113, DOI 10.1177/1049732303259804
   Magnan A., 2014, S.A.P.I.EN.S, V7
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Makate C, 2019, J ENVIRON MANAGE, V231, P858, DOI 10.1016/j.jenvman.2018.10.069
   Mccarl B.A., 2007, REPORT UNFCCC SECRET
   McCarthy N., 2011, Mitigation of Climate Change in Agriculture Working Paper, V3, P1
   McMichael C, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb398
   Mugandani R., 2012, African Crop Science Journal, V20, P361
   Mujeyi A., 2020, AFRICAN HDB CLIM CHA, P1, DOI [10.1007/978-3-030-42091-817-1, DOI 10.1007/978-3-030-42091-817-1]
   Mundial B., 2006, J SPORT SCI
   Nayar S, 2012, J OCCUP SCI, V19, P76, DOI 10.1080/14427591.2011.581626
   Nhodo L., 2013, RUSS J AGR SOC EC SC, V16
   Njaya T., 2014, ASIAN DEV POLICY REV, V2, P1, DOI 10.18488/journal.107.2014.21.1.19
   Omerkhil N, 2020, ECOL INDIC, V118, DOI 10.1016/j.ecolind.2020.106781
   Ovincent V., 1960, AGR SURVEY SO RHODES
   Palinkas LA, 2020, CURR OPIN PSYCHOL, V32, P12, DOI 10.1016/j.copsyc.2019.06.023
   Peterson JS, 2019, GIFTED CHILD QUART, V63, P147, DOI 10.1177/0016986219844789
   Raworth K., 2007, OXFAM
   Rusinamhodzi L, 2015, FIELD CROP RES, V170, P66, DOI 10.1016/j.fcr.2014.10.006
   Schaeffer M., 2013, AMCEN, UNEP and climate analytics Tech Rep, P44
   Serdeczny O, 2019, CLIM RISK MANAGE POL, P205, DOI 10.1007/978-3-319-72026-5_8
   Serdeczny OM, 2018, CLIM DEV, V10, P97, DOI 10.1080/17565529.2017.1372268
   Simba F. M., 2017, Journal of Earth Science & Climatic Change, V8, P392, DOI 10.4172/2157-7617.1000392
   Stern N., 2006, Stern Review: The economics of climate change
   Sussman F, 2014, CLIM POLICY, V14, P242, DOI 10.1080/14693062.2013.777604
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   Truelove HB, 2015, GLOBAL ENVIRON CHANG, V31, P85, DOI 10.1016/j.gloenvcha.2014.12.010
   United Nations Development Programme, 2002, UNDP INTERIM MISSION
   Ward PS, 2016, WORLD DEV, V78, P541, DOI 10.1016/j.worlddev.2015.10.022
   Watkins K., 2007, Fighting climate change: Human solidarity in a divided world Human Development Report 2007/2008
   Yim O, 2015, QUANT METH PSYCHOL, V11, P8, DOI 10.20982/tqmp.11.1.p008
   Zeleke T, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13042162
NR 91
TC 2
Z9 2
U1 1
U2 4
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2023
VL 40
AR 100517
DI 10.1016/j.crm.2023.100517
EA APR 2023
PG 16
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA G7BH9
UT WOS:000990664500001
OA gold
DA 2025-01-10
ER

PT J
AU Gibbs, MT
AF Gibbs, Mark T.
TI Consistency in coastal climate adaption planning in Australia and the
   importance of understanding local political barriers to implementation
SO OCEAN & COASTAL MANAGEMENT
LA English
DT Article
DE Coastal erosion; Sea level rise; Planned retreat; Climate change
ID SEA-LEVEL RISE; CHANGE ADAPTATION; SEAWALLS
AB The discipline of coastal climate adaptation in Australia has been increasingly practiced as communities become more aware of the likely future impacts of sea level rise. As a result, a number of coastal adaptation plans, strategies and guidelines and have been developed for coastal urban communities around the Australian coastline over the last decade. Given that a number of plans have been developed for different communities facing the same issues, it is timely to compare and contrast these plans. To this end a set of these coastal adaptation plans developed for Australian communities were compared in order to consider the variability in the recommended adaptation responses and general consistency of the plans. The adaptation responses proposed in the plans were also assessed for their ability to be implemented. Despite the similarity in the cities and towns considered in the analysis and the commonality of risk arising from sea level rise, no consistent set of adaptation recommendations arose that was common across the communities. This lack of consistency suggests a lack of understanding of the effectiveness and implement-ability of many of the proposed adaptation responses. This lack of consistency is explored here and it appears that many, if not most of the plans considered contained adaptation recommendations which will be difficult to implement.
C1 [Gibbs, Mark T.] Queensland Univ Technol, Inst Future Environm, Brisbane, Qld, Australia.
C3 Queensland University of Technology (QUT)
RP Gibbs, MT (corresponding author), Queensland Univ Technol, Inst Future Environm, Brisbane, Qld, Australia.
EM Mt.Gibbs@qut.edu.au
OI Gibbs, Mark/0000-0002-9632-1567
CR Adger WN, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/6/060201
   AECOM, 2012, 60223572 AECOM
   Araos M, 2016, ENVIRON SCI POLICY, V66, P375, DOI 10.1016/j.envsci.2016.06.009
   Barnett J., 2013, Barriers to adaptation to sealevel rise: the legal, institutional and cultural barriers to adaptation to sea-level rise in Australia
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Bijlsma L., 1996, Climate Change 1995-Impacts, P289
   BMT, 2016, ESP COAST HAZ AD STR
   Butler WH, 2016, J PLAN EDUC RES, V36, P319, DOI 10.1177/0739456X16647161
   Carmin JoAnn., 2012, Progress and Challenges in Urban Climate Adaptation Planning: Results of a Global Survey
   Carson M, 2016, CLIMATIC CHANGE, V134, P269, DOI 10.1007/s10584-015-1520-1
   Eakin HC, 2011, WIRES CLIM CHANGE, V2, P141, DOI 10.1002/wcc.100
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   FANKHAUSER S, 1995, ENVIRON PLANN A, V27, P299, DOI 10.1068/a270299
   Few R, 2007, CLIM POLICY, V7, P46, DOI 10.1080/14693062.2007.9685637
   Ford JD, 2015, NAT CLIM CHANGE, V5, P967, DOI 10.1038/nclimate2744
   GHD, 2012, 4124609 GHD
   Gibbs MT, 2016, OCEAN COAST MANAGE, V130, P107, DOI 10.1016/j.ocecoaman.2016.06.002
   Gibbs MT, 2015, CLIM RISK MANAG, V8, P1, DOI 10.1016/j.crm.2015.05.001
   Gibbs MT, 2013, OCEAN COAST MANAGE, V85, P119, DOI 10.1016/j.ocecoaman.2013.09.001
   Gibbs MT, 2013, OCEAN COAST MANAGE, V80, P73, DOI 10.1016/j.ocecoaman.2013.04.002
   Graham S, 2013, ENVIRON IMPACT ASSES, V41, P45, DOI 10.1016/j.eiar.2013.02.002
   Hurlimann A, 2014, LANDSCAPE URBAN PLAN, V126, P84, DOI 10.1016/j.landurbplan.2013.12.013
   Jamero ML, 2017, NAT CLIM CHANGE, V7, P581, DOI [10.1038/nclimate3344, 10.1038/NCLIMATE3344]
   Jin D, 2015, OCEAN COAST MANAGE, V114, P185, DOI 10.1016/j.ocecoaman.2015.06.025
   Kowalski K, 2009, EUR J OPER RES, V197, P1063, DOI 10.1016/j.ejor.2007.12.049
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Merilä J, 2014, EVOL APPL, V7, P1, DOI 10.1111/eva.12137
   Moyne Shire Council, 2016, PORT FAIR COAST CLIM
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Paterson SK, 2017, GEOFORUM, V81, P109, DOI 10.1016/j.geoforum.2017.02.014
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Rulleau B, 2017, ENVIRON SCI POLICY, V72, P12, DOI 10.1016/j.envsci.2017.01.009
   Sovacool BK, 2015, NAT CLIM CHANGE, V5, P616, DOI 10.1038/nclimate2665
   Spalding MD, 2014, OCEAN COAST MANAGE, V90, P50, DOI 10.1016/j.ocecoaman.2013.09.007
   Stafford-Smith Mark, 2017, Sustain Sci, V12, P911, DOI 10.1007/s11625-016-0383-3
   Svara JH, 1999, PUBLIC ADMIN REV, V59, P44, DOI 10.2307/977478
   URPS, 2016, AD W W AD REG CLIM A
   van den Honert RC, 2011, WATER-SUI, V3, P1149, DOI 10.3390/w3041149
   Vella K, 2016, J PLAN EDUC RES, V36, P363, DOI 10.1177/0739456X16659700
   Wdowinski S, 2016, OCEAN COAST MANAGE, V126, P1, DOI 10.1016/j.ocecoaman.2016.03.002
NR 41
TC 16
Z9 16
U1 0
U2 23
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0964-5691
EI 1873-524X
J9 OCEAN COAST MANAGE
JI Ocean Coastal Manage.
PD MAY 1
PY 2019
VL 173
BP 131
EP 138
DI 10.1016/j.ocecoaman.2019.03.006
PG 8
WC Oceanography; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Oceanography; Water Resources
GA HU1UJ
UT WOS:000465057000013
DA 2025-01-10
ER

PT J
AU Perney, MEP
   D'Angelo, G
AF Perney, Marion Eva Pauline
   D'Angelo, Gigliola
TI Local Governance Support Tools for Disaster Risk Reduction and Climate
   Adaptation Strategies: The EU Contribution in the Case Study of the
   Municipality of Naples
SO SUSTAINABILITY
LA English
DT Article
DE governance; induced risk; soft-resilience tools; living labs
ID MITIGATION; CITIES; DESIGN
AB Today's global context poses ongoing challenges that can be addressed by implementing a systemic and strategic approach directed toward climate-resilient cities. During times of energy and digital transition, managing climate risks involves analysing sector-specific impacts and fostering a shared commitment at the national and international levels; in this sense, European programs promote the dissemination of good practices and implementation of projects and tools to improve the resilience of communities to climate challenges. This paper examines the Naples municipality as a case study within the SEACAP 4 SDG capitalization project in the implementation of innovative governance support tools for hazard and climate adaptation, mitigation, and energy rehabilitation to enhance local governance, planning, and design strategies towards a sustainable and low-emission future. Within the creation of a living lab, tools were selected as part of the project, and training sessions were held targeting key stakeholders. The training aimed to form and inform key players about the tools' potential, leading to their incorporation into the municipality's strategic action plan for future implementation. This case study has a high repeatability and stands as a starting point for the implementation of this approach in numerous other local municipalities.
C1 [Perney, Marion Eva Pauline] Univ Naples Federico II, Dept Architecture DiARC, UNINA, I-80125 Naples, Italy.
   [D'Angelo, Gigliola] Univ Naples Federico II, Dept Civil Bldg & Environm Engn DICEA, UNINA, I-80125 Naples, Italy.
   [D'Angelo, Gigliola] Naples Agcy Energy & Environm ANEA, I-80134 Naples, Italy.
C3 University of Naples Federico II; University of Naples Federico II
RP Perney, MEP (corresponding author), Univ Naples Federico II, Dept Architecture DiARC, UNINA, I-80125 Naples, Italy.
EM marion.perney@unina.it; gigliola.dangelo@unina.it
RI D'Angelo, Gigliola/ABC-3744-2022
OI D'angelo, Gigliola/0000-0002-3243-9080; Perney,
   Marion/0009-0001-0110-9943
CR [Anonymous], 2021, Urban sustainability in Europe - Avenues for change
   [Anonymous], 2019, COMMISSION RECOMMEND, P34
   Behnam M, 2023, EUR SPORT MANAG Q, V23, P789, DOI 10.1080/16184742.2021.1929375
   Bernardini C., 2022, J TECHNOL ARCHIT ENV, V23, P78, DOI [10.36253/techne-12153, DOI 10.36253/TECHNE-12153]
   Commission Staff Working Document, 2016, SWD2016205 EUR COMM
   Cramer W., 2020, Climate and Environmental Change in the Mediterranean BasinCurrent Situation and Risks for the Future. First Mediterranean Assessment Report, P11, DOI [10.5281/zenodo.5513887, DOI 10.5281/ZENODO.5513887]
   D'Angelo G., 2022, PARAMETRIC SUSTAINAB
   Edenhofer O, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, pIX
   European Commission, 2019, COMMUNICATION COMMIS
   European Commission Secretariat-General, 2021, COM202182 EUR COMM S
   Fortelli A, 2021, APPL SCI-BASEL, V11, DOI 10.3390/app112311460
   Grafakos S., 2018, Climate Change and Cities eds, P101, DOI DOI 10.1017/9781316563878.011
   Landauer M, 2019, J ENVIRON PLANN MAN, V62, P741, DOI 10.1080/09640568.2018.1430022
   Lapietra I, 2023, WATER-SUI, V15, DOI 10.3390/w15061175
   Leone M.F., 2020, ADAPTING CHANGING CL, V1st, P77
   Leone MF, 2018, TECHNE, V15, P299, DOI 10.13128/Techne-22076
   Parliament E., 2018, Official Journal of the European Union, DOI DOI 10.1007/3-540-47891-4_10
   Portner HO, 2022, IPCC, 2022: summary for policymakers
   Rama H.-O., 2022, CLIMATE CHANGE 2022, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Reckien D, 2018, J CLEAN PROD, V191, P207, DOI 10.1016/j.jclepro.2018.03.220
   Rocco R., 2021, UFM STRATEGIC URBAN, P11
   SEACAP 4, SEACAP 4 SDG ID MAIN
   Solecki W, 2011, CURR OPIN ENV SUST, V3, P135, DOI 10.1016/j.cosust.2011.03.001
   Stavrakakis GM, 2023, ENERGIES, V16, DOI 10.3390/en16083352
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   UNDRR, 2022, Technical guidance on comprehensive risk assessment and planning in the context of climate change
   UNDRR, 2021, PROM SYN AL CLIM CHA
   UNISDR (United Nations International Strategy for Disaster Reduction), 2015, Sendai Framework for Disaster Risk Reduction 2015-2030
   Visconti C, 2023, HABITAT INT, V135, DOI 10.1016/j.habitatint.2023.102748
   Zuccaro G, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.693319
NR 30
TC 2
Z9 2
U1 3
U2 4
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD AUG
PY 2023
VL 15
IS 15
AR 11716
DI 10.3390/su151511716
PG 19
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA O7RH5
UT WOS:001045734000001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Nimac, I
   Herceg-Bulic, I
   Zuvela-Aloise, M
AF Nimac, Irena
   Herceg-Bulic, Ivana
   Zuvela-Aloise, Maja
TI The contribution of urbanisation and climate conditions to increased
   urban heat load in Zagreb (Croatia) since the 1960s
SO URBAN CLIMATE
LA English
DT Article
DE Urban climate; Climate change; Climate variability; Urbanisation;
   Land-use; land-cover alteration
ID LAND-USE; ISLAND; IMPACTS; CITY; FREQUENT; WAVES
AB Urban climate is affected by weather, global climate change and urban development. However, climate change and urbanisation take place simultaneously with intertwined impacts. To analyse their relative contribution to the heat load of Zagreb, a modelling approach is applied to two land-use/land-cover (LULC) situations and corresponding climate conditions. The results indicate that the change in total heat load is dominantly affected by climate change (-88%) with an average increase in the summer days for 35 days. LULC alterations have a weaker impact (-12%), but they strongly affect heat load spatial variability. The sign of LULC related heat load change de-pends on the type of the change (e.g. an increase is detected in areas that have turned from green into built-up classes). Generally, LULC effect is limited to the area with the modification, however it can spread to adjacent areas due to the processes like advection and evapotranspiration. In areas with considerable LULC alterations, their impact on the heat load is comparable to that of climate change. These results highlight the potential of change in the city infrastructure for climate adaptation, as well as emphasise the importance of considering future climate conditions when assessing efficiency of climate adaptation measures.
C1 [Nimac, Irena] Meteorol & Hydrol Serv Croatia, Zagreb, Croatia.
   [Nimac, Irena] Karl Franzens Univ Graz, Wegener Ctr Klima & Globalen Wandel, Graz, Austria.
   [Herceg-Bulic, Ivana] Univ Zagreb, Fac Sci, Dept Geophys, Zagreb, Croatia.
   [Zuvela-Aloise, Maja] Zentralanstalt Meteorol & Geodynam, Vienna, Austria.
C3 University of Graz; University of Zagreb
RP Herceg-Bulic, I (corresponding author), Univ Zagreb, Fac Sci, Dept Geophys, Zagreb, Croatia.
EM ivana.herceg.bulic@gfz.hr
RI Nimac, Irena/GWQ-8075-2022
OI Herceg Bulic, Ivana/0000-0002-0429-1584
FU Croatian Science Foundation;  [UIP-2017-05-6396]
FX Funding This research has been fully supported by Croatian Science
   Foundation under the project UIP-2017-05-6396 (CroClimGoGreen) .
   Availability of data and material Meteorological data from station
   Zagreb-Maksimir are the property of Croatian Meteorological and
   Hydrological service. Terms of the use, data availability and contact
   can be found at: https://klima.hr/razno/katalog_i_cjenikDHMZ.pdf
   (accessed May 28th 2021) .
CR Alexander LV, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006290
   [Anonymous], 2019, POPULATION DIVISION, DOI DOI 10.4054/DEMRES.2005.12.9
   Argüeso D, 2014, CLIM DYNAM, V42, P2183, DOI 10.1007/s00382-013-1789-6
   Bauer TJ, 2020, J APPL METEOROL CLIM, V59, P477, DOI 10.1175/JAMC-D-19-0061.1
   Bokwa A, 2015, THEOR APPL CLIMATOL, V122, P365, DOI 10.1007/s00704-015-1577-9
   Bounoua L, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/084010
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Dumitrescu A, 2015, THEOR APPL CLIMATOL, V122, P111, DOI 10.1007/s00704-014-1290-0
   Founda D, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-11407-6
   Früh B, 2011, J APPL METEOROL CLIM, V50, P167, DOI 10.1175/2010JAMC2377.1
   Fu P, 2018, THEOR APPL CLIMATOL, V133, P123, DOI 10.1007/s00704-017-2160-3
   Gál T, 2021, COMPUT ENVIRON URBAN, V87, DOI 10.1016/j.compenvurbsys.2021.101600
   Geletic J, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2020.100588
   Geletic J, 2019, CLIMATIC CHANGE, V152, P487, DOI 10.1007/s10584-018-2353-5
   Giorgi F, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL025734
   Grigoras G, 2019, INT J APPL EARTH OBS, V80, P115, DOI 10.1016/j.jag.2019.03.009
   Hammond MJ, 2015, URBAN WATER J, V12, P14, DOI 10.1080/1573062X.2013.857421
   Harmay NSM, 2021, SUSTAIN CITIES SOC, V69, DOI 10.1016/j.scs.2021.102861
   Holec J, 2020, THEOR APPL CLIMATOL, V141, P979, DOI 10.1007/s00704-020-03197-1
   Jia G., 2019, CLIMATE CHANGE LAND, P131
   Kalnay E, 2003, NATURE, V423, P528, DOI 10.1038/nature01675
   Klaic ZB, 2002, METEOROL ATMOS PHYS, V79, P1, DOI 10.1007/s703-002-8225-z
   Klaic ZB, 2014, J APPL METEOROL CLIM, V53, P1121, DOI 10.1175/JAMC-D-13-0163.1
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Markusic S, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13061095
   Meehl GA, 2004, SCIENCE, V305, P994, DOI 10.1126/science.1098704
   Nimac I, 2022, INT J CLIMATOL, V42, P4850, DOI 10.1002/joc.7507
   Nimac I, 2022, NAT HAZARDS, V112, P873, DOI 10.1007/s11069-022-05210-4
   Nimac I, 2021, THEOR APPL CLIMATOL, V146, P429, DOI 10.1007/s00704-021-03689-8
   Nitis T, 2010, INT J ENVIRON POLLUT, V40, P123, DOI 10.1504/IJEP.2010.030888
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Oleson KW, 2015, CLIMATIC CHANGE, V129, P525, DOI 10.1007/s10584-013-0936-8
   Oswald SM, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2020.100582
   Pauleit S, 2005, LANDSCAPE URBAN PLAN, V71, P295, DOI 10.1016/j.landurbplan.2004.03.009
   Podolszki L, 2022, SENSORS-BASEL, V22, DOI 10.3390/s22010177
   Prtenjak MT, 2018, ATMOS RES, V214, P213, DOI 10.1016/j.atmosres.2018.08.001
   Schau-Noppel H, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100614
   SIEBERT J, 1992, BOUND-LAY METEOROL, V59, P1, DOI 10.1007/BF00120684
   Sievers U., 1983, Contributions to Atmospheric Physics, V56, P58
   Sievers U., 1995, Meteorologische Zeitschrift, V4, P3
   Spinoni J, 2018, INT J CLIMATOL, V38, P1718, DOI 10.1002/joc.5291
   Steeneveld GJ, 2014, LANDSCAPE URBAN PLAN, V121, P92, DOI 10.1016/j.landurbplan.2013.09.001
   Vicente-Serrano SM, 2018, EARTH SYST DYNAM, V9, P915, DOI 10.5194/esd-9-915-2018
   Wilks DS, 2019, STATISTICAL METHODS IN THE ATMOSPHERIC SCIENCES, 4TH EDITION, P1, DOI 10.1016/C2017-0-03921-6
   Winguth AME, 2013, J APPL METEOROL CLIM, V52, P2418, DOI 10.1175/JAMC-D-12-0195.1
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-25296-w
   Zaninovic K., 2008, KLIMATSKI ATLAS HRVA
   Zhang ZT, 2019, J CLIMATE, V32, P7421, DOI 10.1175/JCLI-D-18-0691.1
   Zhao L, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa9f73
   Zhou B, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-04242-2
   Zuvela-Aloise M, 2017, INT J BIOMETEOROL, V61, P527, DOI 10.1007/s00484-016-1230-z
   Zuvela-Aloise M, 2016, CLIMATIC CHANGE, V135, P425, DOI 10.1007/s10584-016-1596-2
   Zuvela-Aloise M, 2014, URBAN CLIM, V10, P490, DOI 10.1016/j.uclim.2014.04.002
NR 54
TC 13
Z9 13
U1 2
U2 12
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0955
J9 URBAN CLIM
JI Urban CLim.
PD DEC
PY 2022
VL 46
AR 101343
DI 10.1016/j.uclim.2022.101343
EA NOV 2022
PG 15
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 6O7WM
UT WOS:000890451000002
OA hybrid
DA 2025-01-10
ER

PT J
AU Alexandra, J
AF Alexandra, Jason
TI Climate adaptation options for the 2026 MDB Plan: opportunities for
   managing climate risk
SO AUSTRALASIAN JOURNAL OF WATER RESOURCES
LA English
DT Article
DE Water planning; water allocation regimes; adaptive policy; climate
   risks; MDB
ID MURRAY-DARLING BASIN; WATER GOVERNANCE; AUSTRALIA; MANAGEMENT; SCIENCE;
   POLICY; COMPLEXITY; RESOURCES; POLITICS; WORLD
AB How water resources are defined, both conceptually and legally, is central to their efficient and equitable allocation. With climate change introducing significant uncertainties to water resources management, flexible allocation frameworks are needed that can adapt to changing conditions. This paper explores options for climate-adaptive water allocation in Australia's Murray Darling Basin. The 2026 revision of the Basin Plan may provide significant opportunities for proactive climate risk mitigation, but this depends on rigorous evaluation of policy options. The Water Act requires that the Plan's revisions use the best available science to inform strategies that minimise the impact of climate risks. The Act also enables the use of ratios and formulas as alternatives to using long-term averages as the basis of the Plan. However, there have been limited investigations into using these alternatives. Achieving more adaptive policies depends on rigorously assessing climate risk management options. Given the far-reaching consequences of climate change, rigorous investigations are needed into reforms to the established approaches to water resources planning and to existing water entitlements and allocation regimes. At minimum, this means reassessing the total resource pool and all subsidiary targets and investigating allocation frameworks that equitably share risks between extractive users and the environment.
C1 [Alexandra, Jason] Alexandra & Associates, Pyrmont, Australia.
   [Alexandra, Jason] ANU Inst Water Futures & Climate Energy & Disaste, Canberra, ACT, Australia.
C3 Australian National University
RP Alexandra, J (corresponding author), Alexandra & Associates, Pyrmont, Australia.; Alexandra, J (corresponding author), ANU Inst Water Futures & Climate Energy & Disaste, Canberra, ACT, Australia.
EM jason@alexandra-consulting.com
RI Alexandra, Jason/AFK-6039-2022
OI Alexandra, Jason/0000-0002-9624-1698
CR Abel N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08422-210223
   Alexandra J., 2012, WATER CLIMATE POLICY, P494
   Alexandra J, 2021, WATER ALTERN, V14, P773
   Alexandra J, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-03036-w
   Alexandra J, 2020, ENVIRON SCI POLICY, V112, P17, DOI 10.1016/j.envsci.2020.05.022
   Alexandra J, 2020, AUSTRALAS J WAT RESO, V24, P9, DOI 10.1080/13241583.2020.1717694
   Alexandra J, 2019, AUSTRALAS J WAT RESO, V23, P99, DOI 10.1080/13241583.2019.1586066
   Allan C, 2013, CURR OPIN ENV SUST, V5, P625, DOI 10.1016/j.cosust.2013.09.004
   Allouche J., 2019, The water-food-energy nexus: power, politics and justice
   [Anonymous], 2021, State of Global Climate 2021 WMO Provisional Report
   [Anonymous], 2007, WAT ACT 2007
   [Anonymous], 2012, SEACI PHAS 2 SYNTH R
   [Anonymous], 2008, Water Availability in the Murrumbidgee: a Report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project
   [Anonymous], 2015, OECD Studies on Water, DOI DOI 10.1787/9789264229631-EN
   Australian Academy of Science, 2019, REP MASS FISH KILLS
   Bell S, 2022, WATER ALTERN, V15, P129
   Bender I, 2023, AUSTRALAS J WAT RESO, V27, P132, DOI 10.1080/13241583.2022.2077685
   Boyd E, 2015, AMBIO, V44, pS149, DOI 10.1007/s13280-014-0604-x
   Cai WJ, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL033390
   Chaffin BC, 2014, ECOL SOC, V19, DOI 10.5751/ES-06824-190356
   Chiew F., 2009, ADVICE DEFINING CLIM
   Chipperfield and Alexandra, AUSTRALAS J WAT RESO
   Cleaver F, 2018, ECOL SOC, V23, DOI 10.5751/ES-10212-230249
   Colloff MJ, 2021, AUSTRALAS J WAT RESO, V25, P121, DOI 10.1080/13241583.2021.1917097
   Colloff MJ, 2019, AUSTRALAS J WAT RESO, V23, P88, DOI 10.1080/13241583.2019.1664878
   Commonwealth of Australia, 2012, BAS PLAN 2012 2012 B
   Cosens BA, 2018, ECOL SOC, V23, DOI 10.5751/ES-09524-230104
   CSIRO, 2010, CLIMATE CHANGE VARIA
   Dankel DJ, 2017, FUTURES, V91, P1, DOI 10.1016/j.futures.2017.05.009
   Donohue RJ, 2013, GEOPHYS RES LETT, V40, P3031, DOI 10.1002/grl.50563
   Donohue RJ, 2011, J HYDROL, V406, P234, DOI 10.1016/j.jhydrol.2011.07.003
   Dore J, 2012, J HYDROL, V466, P23, DOI 10.1016/j.jhydrol.2012.07.023
   Dupuis J., 2018, CRITICAL APPROACH IN, P177
   Erik y SWYNGEDOUW., 2018, Water justice, P115, DOI DOI 10.1017/9781316831847.008
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   Frederick KD, 1997, CLIMATIC CHANGE, V37, P7, DOI 10.1023/A:1005336924908
   Gallant AJE, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009832
   GLEICK PH, 1987, CLIMATIC CHANGE, V10, P137, DOI 10.1007/BF00140252
   Godden L, 2011, WATER RESOUR MANAG, V25, P3971, DOI 10.1007/s11269-011-9902-2
   Grafton RQ, 2020, INT J WATER RESOUR D, V36, P484, DOI 10.1080/07900627.2019.1674132
   Grafton RQ, 2019, NAT SUSTAIN, V2, P907, DOI 10.1038/s41893-019-0376-1
   Grafton RQ, 2018, ANNU REV RESOUR ECON, V10, P487, DOI 10.1146/annurev-resource-100517-023039
   Grafton RQ, 2014, AMBIO, V43, P1082, DOI 10.1007/s13280-014-0495-x
   Grafton RQ, 2014, AGR WATER MANAGE, V145, P61, DOI 10.1016/j.agwat.2013.12.001
   Grafton RQ, 2019, AUST J AGR RESOUR EC, V63, P116, DOI 10.1111/1467-8489.12288
   Hatton T, 2011, AUST J PUBL ADMIN, V70, P298, DOI 10.1111/j.1467-8500.2011.00730.x
   Huntjens P, 2010, REG ENVIRON CHANGE, V10, P263, DOI 10.1007/s10113-009-0108-6
   Ison R, 2018, SUSTAIN SCI, V13, P1209, DOI 10.1007/s11625-018-0570-5
   Jackson S, 2020, GEOFORUM, V109, P44, DOI 10.1016/j.geoforum.2019.12.020
   JARMAN A, 1994, TECHNOL FORECAST SOC, V45, P119, DOI 10.1016/0040-1625(94)90089-2
   Juhola S, 2011, ENVIRON POLIT, V20, P445, DOI 10.1080/09644016.2011.589571
   Kaune A, 2020, HYDROL EARTH SYST SC, V24, P3851, DOI 10.5194/hess-24-3851-2020
   Kiem AS, 2013, AUSTRALAS J WAT RESO, V17, P126, DOI 10.7158/W13-015.2013.17.2
   Konig N, 2017, FUTURES, V91, P12, DOI 10.1016/j.futures.2016.12.004
   Lacey J, 2018, NAT CLIM CHANGE, V8, P22, DOI 10.1038/s41558-017-0010-z
   Laerhoven Frank., 2007, INT J COMMONS, V1, P3, DOI [DOI 10.18352/IJC.76, https://doi.org/10.18352/ijc.76]
   Lane SN, 2014, HYDROL EARTH SYST SC, V18, P927, DOI 10.5194/hess-18-927-2014
   Linton J., 2010, What is water? The history of a modern abstraction
   Lukasiewicz A, 2016, REG ENVIRON CHANGE, V16, P487, DOI 10.1007/s10113-015-0765-6
   Marlow D., 2020, P ROY SOC QUEENSL, V124, P27
   Marshall GR, 2013, INT J WATER GOV, V1, P197, DOI 10.7564/13-IJWG17
   Mastrotheodoros T, 2020, NAT CLIM CHANGE, V10, P155, DOI 10.1038/s41558-019-0676-5
   MDBA, 2019, CLIM CHANG MURR DARL
   MDBMC Ministerial Council, 2004, PROSP FUT DET FLOW M
   Meijerink S, 2010, ECOL SOC, V15
   Miller KA, 1997, CLIMATIC CHANGE, V35, P157, DOI 10.1023/A:1005300529862
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Mollinga PP, 2019, WATER ALTERN, V12, P788
   Neave I., 2015, Water J. Aust. Water Assoc, V42, P102
   Nightingale AJ, 2017, GEOFORUM, V84, P11, DOI 10.1016/j.geoforum.2017.05.011
   NORTH DC, 1991, J ECON PERSPECT, V5, P97, DOI 10.1257/jep.5.1.97
   O'Donnell E, 2020, NAT SUSTAIN, V3, P675, DOI 10.1038/s41893-020-0541-6
   O'Donnell T, 2019, LAND USE POLICY, V88, DOI 10.1016/j.landusepol.2019.104145
   Olsson P, 2006, ECOL SOC, V11, DOI 10.5751/ES-01595-110118
   Pahl-Wostl C, 2007, WATER RESOUR MANAG, V21, P49, DOI 10.1007/s11269-006-9040-4
   Pahl-Wostl C, 2012, ENVIRON SCI POLICY, V23, P24, DOI 10.1016/j.envsci.2012.07.014
   Palmer MA, 2008, FRONT ECOL ENVIRON, V6, P81, DOI 10.1890/060148
   PC Productivity Commission, 2021, PRODUCTIVITY COMMISS
   Pittock J., 2015, WATER-SUI, V42, P28, DOI [DOI 10.3316/INFORMIT.603377005698763, 10.3316/informit.603377005698763]
   Pittock J, 2011, MAR FRESHWATER RES, V62, P232, DOI 10.1071/MF09319
   Prosser IP, 2021, WATER-SUI, V13, DOI 10.3390/w13182504
   Raadgever GT, 2008, ECOL SOC, V13
   RIEBSAME WE, 1988, CLIMATIC CHANGE, V13, P69, DOI 10.1007/BF00140162
   Ross MRV, 2015, ANNU REV ENV RESOUR, V40, P419, DOI 10.1146/annurev-environ-121012-100957
   Sarewitz D, 2004, ENVIRON SCI POLICY, V7, P385, DOI 10.1016/j.envsci.2004.06.001
   Schmidt JeremyJ., 2017, Water: Abundance, Scarcity, and Security in the Age of Humanity
   Schoeman J, 2014, INT J WATER RESOUR D, V30, P377, DOI 10.1080/07900627.2014.907087
   Stewardson MJ, 2021, AUSTRALAS J WAT RESO, V25, P141, DOI 10.1080/13241583.2021.1996681
   Sylla MB, 2018, CLIMATIC CHANGE, V151, P247, DOI 10.1007/s10584-018-2308-x
   Taylor M, 2014, GLOBAL WARMING AND CLIMATE CHANGE: WHAT AUSTRALIA KNEW AND BURIED - THEN FRAMED A NEW REALITY FOR THE PUBLIC, P1
   Tilleard S, 2016, CLIMATIC CHANGE, V137, P575, DOI 10.1007/s10584-016-1699-9
   Ukkola AM, 2016, NAT CLIM CHANGE, V6, P75, DOI [10.1038/nclimate2831, 10.1038/NCLIMATE2831]
   Urban F, 2018, INT J WATER RESOUR D, V34, P747, DOI 10.1080/07900627.2017.1329138
   van Dijk AIJM, 2013, WATER RESOUR RES, V49, P1040, DOI 10.1002/wrcr.20123
   Walker B, 2019, REPORT S AUSTR MDB R
   Wallis PJ, 2011, WATER RESOUR MANAG, V25, P4081, DOI 10.1007/s11269-011-9885-z
   Wentworth Group of Concerned Scientists, 2020, ASS RIV FLOWS MURR D
   Whaley L, 2022, WATER ALTERN, V15, P218
   Wheeler SA, 2020, CLIMATIC CHANGE, V158, P551, DOI 10.1007/s10584-019-02601-8
   Whetton P., 2021, Murray-Darling Basin, Australia, P253, DOI DOI 10.1016/B978-0-12-818152-2.00012-7
   Whetton Penny H., 2016, Climate Services, V2-3, P1, DOI 10.1016/j.cliser.2016.06.001
   Wilkinson M., 2020, The Carbon Club: How a Network of Influential Climate Sceptics, Politicians and Business Leaders Fought to Control Australia's Climate Policy
   Williams John, 2017, Journal and Proceedings of the Royal Society of New South Wales, V150, P68
   Wyborn C, 2015, GLOBAL ENVIRON CHANG, V30, P56, DOI 10.1016/j.gloenvcha.2014.10.009
   Xu JC, 2009, CONSERV BIOL, V23, P520, DOI 10.1111/j.1523-1739.2009.01237.x
   Young B., 2011, REPORT SCI LEADERS F
   Young M.D., 2003, AUSTR EC REV, V36, P225, DOI [DOI 10.1111/1467-8462.00282, 10.1111/1467-8462.00282]
   Young M. J., 2008, FUTURE PROOFED BASIN
   Young MD, 2014, AGR WATER MANAGE, V145, P32, DOI 10.1016/j.agwat.2013.12.002
NR 109
TC 6
Z9 6
U1 2
U2 8
PU TAYLOR & FRANCIS AS
PI OSLO
PA KARL JOHANS GATE 5, NO-0154 OSLO, NORWAY
SN 1324-1583
EI 2204-227X
J9 AUSTRALAS J WAT RESO
JI Australas. J. Water Resour.
PD JUL 3
PY 2023
VL 27
IS 2
SI SI
BP 257
EP 270
DI 10.1080/13241583.2022.2133643
EA OCT 2022
PG 14
WC Water Resources
WE Emerging Sources Citation Index (ESCI)
SC Water Resources
GA AA4Y6
UT WOS:000876146400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Shirsat, TS
   Kulkarni, AV
   Momblanch, A
   Randhawa, SS
   Holman, IP
AF Shirsat, Tejal S.
   Kulkarni, Anil, V
   Momblanch, Andrea
   Randhawa, S. S.
   Holman, Ian P.
TI Towards climate-adaptive development of small hydropower projects in
   Himalaya: A multi-model assessment in upper Beas basin
SO JOURNAL OF HYDROLOGY-REGIONAL STUDIES
LA English
DT Article
DE Glaciers; Indus; Snowmelt; Climate change; Modelling; WEAP
AB Study Region: Allain catchment, a sub-basin of Beas basin, Western Himalaya.
   Study Focus: This study aims to assess future glacio-hydrological changes in a small basin and their impacts on the operation of two Small Hydropower Projects (SHP) with contrasting hydrological requirements. The Water Evaluation and Planning (WEAP) model is used to integrate cryosphere, hydrology and hydropower production modelling in the 21st century using climate changes projected by the ensembles of five global climate models under RCP 4.5 and 8.5.
   New Hydrological Insights for the Region: The total streamflow in the future is projected to have widespread uncertainty in the magnitude but shows noticeable changes in the seasonality. Of the two SHPs, the one utilizing high flows with low hydraulic head shows a power generation behaviour similar to streamflow projections. Its annual hydropower production is projected to change by 2 to 21% (RCP4.5) and -5 to 40% (RCP8.5) by the end of the century. The other plant that uses lesser flows but high head maintains its designed power production consistently throughout the century. The study indicates that the design of hydropower plants strongly influences their sensitivity to future climate and thus provides important insights into the climate-adaptive designs and planning of future hydropower projects in Himalaya.
C1 [Shirsat, Tejal S.; Kulkarni, Anil, V] Indian Inst Sci, Divecha Ctr Climate Change, Bangalore 560012, Karnataka, India.
   [Momblanch, Andrea; Holman, Ian P.] Cranfield Univ, Coll Rd, Cranfield MK43 0AL, Beds, England.
   [Randhawa, S. S.] Himachal Pradesh Council Sci Technol & Environm, Shimla 171001, India.
C3 Indian Institute of Science (IISC) - Bangalore; Cranfield University
RP Shirsat, TS (corresponding author), Indian Inst Sci, Divecha Ctr Climate Change, Bangalore 560012, Karnataka, India.
EM shirsat.tejal@gmail.com
RI ; Momblanch, Andrea/J-1848-2016; Holman, Ian/A-7108-2010
OI /0000-0001-9906-9240; Momblanch, Andrea/0000-0003-3165-4691; Holman,
   Ian/0000-0002-5263-7746
FU Science & Engineering Research Board (SERB) of Department of Science and
   Technology, Government of India [DSTO1952]; UK Natural Environment
   Research Council [NE/N015541/1]; NERC [NE/N015541/1] Funding Source:
   UKRI
FX The authors would like to thank Divecha Centre for Climate Change (DCCC)
   at the Indian Institute of Science (IISc) for providing facilities to
   carry out this research. This research was supported by Science &
   Engineering Research Board (SERB) of Department of Science and
   Technology, Government of India, under grant DSTO1952 and UK Natural
   Environment Research Council grant NE/N015541/1. We are thankful to
   ADHPL, Manali and Bhakra Beas Management Board for providing in-situ
   discharge measurements at Allain barrage and meteorological data at
   Bhuntar station. We also thank Ms. Veena Prasad (DCCC) for the help in
   future projections of glacier area. Various satellite datasets employed
   in the study can be accessed from the sources given in the Table 2 in
   the Section 2. Projections of GCMs were acquired from KNMI Climate
   Explorer data portal at https://climexp.knmi.nl.Details of the power
   projects were obtained from the database of UNFCC's Clean Development
   Mechanism at https://cdm.unfccc.int/Projects/projsearch.html.The authors
   affirm that no new data was used or generated in the study.
CR Ali SA, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-30489-4
   Anandhi A, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009104
   Azam MF, 2019, J HYDROL, V574, P760, DOI 10.1016/j.jhydrol.2019.04.075
   Azam MF, 2018, J GLACIOL, V64, P61, DOI 10.1017/jog.2017.86
   Azmat M., 2015, WATER RESOURCES AVAI, DOI [10.6092/polito/porto/2594956, DOI 10.6092/POLITO/PORTO/2594956]
   Bolch T, 2012, SCIENCE, V336, P310, DOI 10.1126/science.1215828
   Bookhagen B, 2010, J GEOPHYS RES-EARTH, V115, DOI 10.1029/2009JF001426
   CEA, 2020, STAT HYDR POT DEV
   Hussain A, 2019, RENEW SUST ENERG REV, V107, P446, DOI 10.1016/j.rser.2019.03.010
   Immerzeel WW, 2020, NATURE, V577, P364, DOI 10.1038/s41586-019-1822-y
   Immerzeel WW, 2012, CLIMATIC CHANGE, V110, P721, DOI 10.1007/s10584-011-0143-4
   Jain SK, 2010, WATER RESOUR MANAG, V24, P1763, DOI 10.1007/s11269-009-9523-1
   Kulkarni A. V., 2002, J INDIAN SOC REMOTE, V30, P221
   Kumar D, 2014, RENEW SUST ENERG REV, V39, P87, DOI 10.1016/j.rser.2014.07.052
   Kumar V, 2007, HYDROLOG SCI J, V52, P376, DOI 10.1623/hysj.52.2.376
   Li H, 2015, J HYDROL, V527, P656, DOI 10.1016/j.jhydrol.2015.05.017
   Li L, 2019, HYDROL EARTH SYST SC, V23, P1483, DOI 10.5194/hess-23-1483-2019
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Marzeion B, 2012, CRYOSPHERE, V6, P1295, DOI 10.5194/tc-6-1295-2012
   Maurer JM, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aav7266
   Maurya AS, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-018-7849-9
   Mishra SK, 2020, FRONT ENV SCI-SWITZ, V8, DOI 10.3389/fenvs.2020.00026
   Momblanch A, 2019, WATER-SUI, V11, DOI 10.3390/w11061303
   Momblanch A, 2019, SCI TOTAL ENVIRON, V655, P35, DOI 10.1016/j.scitotenv.2018.11.045
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Muhammad S, 2020, EARTH SYST SCI DATA, V12, P345, DOI 10.5194/essd-12-345-2020
   Mukherjee K, 2018, CLIMATIC CHANGE, V148, P219, DOI 10.1007/s10584-018-2185-3
   Negi HS, 2018, CURR SCI INDIA, V114, P760, DOI 10.18520/cs/v114/i04/760-770
   NEP, 2018, NAT EL PLAN
   Prasad V, 2019, CURR SCI INDIA, V116, P1721, DOI 10.18520/cs/v116/i10/1721-1730
   Pritchard HD, 2019, NATURE, V569, P649, DOI 10.1038/s41586-019-1240-1
   Ragettli S, 2015, ADV WATER RESOUR, V78, P94, DOI 10.1016/j.advwatres.2015.01.013
   Ragettli S, 2014, HYDROL PROCESS, V28, P5674, DOI 10.1002/hyp.10055
   Rathore B.P., 2011, J. Geosci., V5, P53
   Sharma V, 2013, J MT SCI-ENGL, V10, P574, DOI 10.1007/s11629-013-2667-8
   Sieber J., 2015, WATER EVALUATION PLA
   Su F, 2016, GLOBAL PLANET CHANGE, V136, P82, DOI 10.1016/j.gloplacha.2015.10.012
   Tahir AA, 2015, SCI TOTAL ENVIRON, V505, P748, DOI 10.1016/j.scitotenv.2014.10.065
   Tawde SA, 2019, ENVIRON RES COMMUN, V1, DOI 10.1088/2515-7620/ab1d6d
   Tawde SA, 2017, ANN GLACIOL, V58, P99, DOI 10.1017/aog.2017.18
   Yang RPJ, 2006, INT J INTERCULT REL, V30, P487, DOI 10.1016/j.ijintrel.2005.11.010
   Yates D, 2005, WATER INT, V30, P487, DOI 10.1080/02508060508691893
NR 42
TC 12
Z9 12
U1 1
U2 15
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
EI 2214-5818
J9 J HYDROL-REG STUD
JI J. Hydrol.-Reg. Stud.
PD APR
PY 2021
VL 34
AR 100797
DI 10.1016/j.ejrh.2021.100797
EA MAR 2021
PG 13
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA RF9TM
UT WOS:000635180700023
OA gold, Green Accepted, Green Published
DA 2025-01-10
ER

PT J
AU Ebeling, SK
   Stöcklin, J
   Hensen, I
   Auge, H
AF Ebeling, Susan K.
   Stoecklin, Juerg
   Hensen, Isabell
   Auge, Harald
TI Multiple common garden experiments suggest lack of local adaptation in
   an invasive ornamental plant
SO JOURNAL OF PLANT ECOLOGY
LA English
DT Article
DE Buddleja davidii; reciprocal transplantation; biological invasion;
   geographic clines; climatic conditions
ID LATITUDINAL POPULATION DIFFERENTIATION; POPPIES
   ESCHSCHOLZIA-CALIFORNICA; GENERAL-PURPOSE GENOTYPES; INTRODUCED
   POPULATIONS; GENETIC DIFFERENTIATION; RAPID EVOLUTION; LIFE-HISTORY;
   PHENOTYPIC PLASTICITY; INVADING POPULATIONS; HYPERICUM-PERFORATUM
AB Aims
   Adaptive evolution along geographic gradients of climatic conditions is suggested to facilitate the spread of invasive plant species, leading to clinal variation among populations in the introduced range. We investigated whether adaptation to climate is also involved in the invasive spread of an ornamental shrub, Buddleja davidii, across western and central Europe.
   Methods
   dWe combined a common garden experiment, replicated in three climatically different central European regions, with reciprocal transplantation to quantify genetic differentiation in growth and reproductive traits of 20 invasive B. davidii populations. Additionally, we compared compensatory regrowth among populations after clipping of stems to simulate mechanical damage.
   Important Findings
   Our results do not provide evidence for clinal variation among invasive B. davidii populations: populations responded similarly to the different environments, and trait values were not correlated to climatic conditions or geographic coordinates of their home sites. Moreover, we did not detect differences in the compensatory ability of populations.
   We suppose that the invasive spread of B. davidii has been facilitated by phenotypic plasticity rather than by adaptation to climate and that continent-wide shuffling of cultivars due to horticultural trade may have limited local adaptation so far.
C1 [Ebeling, Susan K.; Auge, Harald] UFZ Helmholtz Ctr Environm Res, UFZ, Dept Community Ecol, D-06120 Halle, Germany.
   [Ebeling, Susan K.; Hensen, Isabell] Univ Halle Wittenberg, Inst Geobot & Bot Garden, D-06108 Halle, Germany.
   [Stoecklin, Juerg] Univ Basel, Inst Bot, CH-4056 Basel, Switzerland.
C3 Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); Martin Luther University Halle Wittenberg; University of Basel
RP Ebeling, SK (corresponding author), UFZ Helmholtz Ctr Environm Res, UFZ, Dept Community Ecol, Theodor Lieser Str 4, D-06120 Halle, Germany.
EM susan.ebeling@alumni.uni-halle.de
RI Stöcklin, Jürg/F-5029-2012; Ebeling, Susan/KHC-9380-2024; Auge,
   Harald/D-4802-2015
OI Auge, Harald/0000-0001-7432-8453
FU Deutsche Bundesstiftung Umwelt [20004/705]
FX Deutsche Bundesstiftung Umwelt (20004/705 to S.K.E.).
CR Agrawal AA, 2004, ECOL LETT, V7, P1199, DOI 10.1111/j.1461-0248.2004.00680.x
   Albrecht HJ, 2004, GARTENPRAXIS, V1, P30
   Allendorf FW, 2003, CONSERV BIOL, V17, P24, DOI 10.1046/j.1523-1739.2003.02365.x
   Anderson JE, 1996, AUST J PLANT PHYSIOL, V23, P311, DOI 10.1071/PP9960311
   Armitage A. M., 1995, Journal of Environmental Horticulture, V13, P176
   Auer C, 2008, CRIT REV PLANT SCI, V27, P255, DOI 10.1080/07352680802237162
   Baker H. G., 1975, Annual Review of Ecology and Systematics, V5, P1, DOI 10.1146/annurev.es.05.110174.000245
   Becker U, 2006, OECOLOGIA, V150, P506, DOI 10.1007/s00442-006-0534-9
   Bischoff A, 2006, J ECOL, V94, P1130, DOI 10.1111/j.1365-2745.2006.01174.x
   Bone E, 2001, GENETICA, V112, P165, DOI 10.1023/A:1013378014069
   Bossdorf O, 2005, OECOLOGIA, V144, P1, DOI 10.1007/s00442-005-0070-z
   Bridle JR, 2007, TRENDS ECOL EVOL, V22, P140, DOI 10.1016/j.tree.2006.11.002
   BROWN K, 1990, THESIS VICTORIA U WE
   CABI, 2009, INV SPEC COMP
   Cabin R., 2000, B ECOL SOC AM, V81, P246, DOI DOI 10.2307/20168454
   CAMPBELL DJ, 1984, NEW ZEAL J BOT, V22, P223, DOI 10.1080/0028825X.1984.10425254
   Clarke MM, 2006, BIOL INVASIONS, V8, P149, DOI 10.1007/s10530-004-2424-6
   Clausen J., 1940, EXPT STUDIES NATURE, V520
   Colautti RI, 2010, P ROY SOC B-BIOL SCI, V277, P1799, DOI 10.1098/rspb.2009.2231
   Colautti RI, 2009, EVOL APPL, V2, P187, DOI 10.1111/j.1752-4571.2008.00053.x
   Csurshes S., 1998, POTENTIAL ENV WEEDS
   Culley TM, 2007, BIOSCIENCE, V57, P956, DOI 10.1641/B571108
   DAVISON AW, 1995, NEW PHYTOL, V131, P337, DOI 10.1111/j.1469-8137.1995.tb03069.x
   Dehnen-Schmutz K, 2007, CONSERV BIOL, V21, P224, DOI 10.1111/j.1523-1739.2006.00538.x
   Dlugosch KM, 2008, ECOL LETT, V11, P701, DOI 10.1111/j.1461-0248.2008.01181.x
   Ebeling SK, 2008, ECOGRAPHY, V31, P709, DOI 10.1111/j.1600-0587.2008.05470.x
   Ebeling SK, 2008, DIVERS DISTRIB, V14, P225, DOI 10.1111/j.1472-4642.2007.00422.x
   Ellstrand NC, 2000, P NATL ACAD SCI USA, V97, P7043, DOI [10.1073/pnas.97.13.7043, 10.1007/s10681-006-5939-3]
   ESLER AE, 1988, NEW ZEAL J BOT, V26, P345, DOI 10.1080/0028825X.1988.10410640
   Falconer D.S., 1966, INTRO QUANTITATIVE G
   Fraser A, 1965, GENETICS COLONIZING
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hutchison DW, 1999, EVOLUTION, V53, P1898, DOI 10.1111/j.1558-5646.1999.tb04571.x
   Joshi J, 2001, ECOL LETT, V4, P536, DOI 10.1046/j.1461-0248.2001.00262.x
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Keller SR, 2009, NEW PHYTOL, V183, P678, DOI 10.1111/j.1469-8137.2009.02892.x
   Kitajima K, 2006, BIOL INVASIONS, V8, P1471, DOI 10.1007/s10530-005-5839-9
   Kollmann J, 2004, DIVERS DISTRIB, V10, P377, DOI 10.1111/j.1366-9516.2004.00126.x
   Kreh W, 1952, AUS HEIMAT NATURWISS, V60, P20
   Kunick W, 1970, BERLINER NATURSCHUTZ, V14, P407
   Lambdon PW, 2008, PRESLIA, V80, P101
   Leeuwenberg AJM, 1979, LOGANIACEAE AFRICA
   Leger EA, 2007, J EVOLUTION BIOL, V20, P1090, DOI 10.1111/j.1420-9101.2006.01292.x
   Leger EA, 2003, ECOL LETT, V6, P257, DOI 10.1046/j.1461-0248.2003.00423.x
   Lenormand T, 2002, TRENDS ECOL EVOL, V17, P183, DOI 10.1016/S0169-5347(02)02497-7
   Linhart YB, 1996, ANNU REV ECOL SYST, V27, P237, DOI 10.1146/annurev.ecolsys.27.1.237
   Littell R.C., 1996, SAS SYSTEMS MIXED MO
   Maron JL, 2004, ECOLOGY, V85, P3243, DOI 10.1890/04-0297
   Maron JL, 2004, ECOL MONOGR, V74, P261, DOI 10.1890/03-4027
   Maron JL, 2007, EVOLUTION, V61, P1912, DOI 10.1111/j.1558-5646.2007.00153.x
   Merilä J, 2001, J EVOLUTION BIOL, V14, P892, DOI 10.1046/j.1420-9101.2001.00348.x
   Metzger MJ, 2005, GLOBAL ECOL BIOGEOGR, V14, P549, DOI 10.1111/j.1466-822x.2005.00190.x
   Miller A., 1984, THESIS OXFORD POLYTE
   Mitchell TD, 2004, 55 U E ANGL TYND CTR
   Montague JL, 2008, J EVOLUTION BIOL, V21, P234, DOI 10.1111/j.1420-9101.2007.01456.x
   Monty A, 2009, OECOLOGIA, V159, P305, DOI 10.1007/s00442-008-1228-2
   Mooney HA, 2001, P NATL ACAD SCI USA, V98, P5446, DOI 10.1073/pnas.091093398
   New M, 2000, J CLIMATE, V13, P2217, DOI 10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2
   NOVAK SJ, 1993, HEREDITY, V71, P167, DOI 10.1038/hdy.1993.121
   Olsson K, 2002, J EVOLUTION BIOL, V15, P983, DOI 10.1046/j.1420-9101.2002.00457.x
   Parker IM, 2003, CONSERV BIOL, V17, P59, DOI 10.1046/j.1523-1739.2003.02019.x
   Randall JM, 1996, HDB 21 CENTURY GARDE
   Ream J., 2006, Production and invasion of Butterfly bush (Buddleja davidii) in Oregon
   Reichard SH, 2001, BIOSCIENCE, V51, P103, DOI 10.1641/0006-3568(2001)051[0103:HAAPOI]2.0.CO;2
   Reichard SH, 1997, CONSERV BIOL, V11, P193, DOI 10.1046/j.1523-1739.1997.95473.x
   RICE KJ, 1991, OECOLOGIA, V88, P91, DOI 10.1007/BF00328408
   Richards CL, 2006, ECOL LETT, V9, P981, DOI 10.1111/j.1461-0248.2006.00950.x
   Ridley CE, 2010, EVOL APPL, V3, P64, DOI 10.1111/j.1752-4571.2009.00099.x
   ROACH DA, 1987, ANNU REV ECOL SYST, V18, P209, DOI 10.1146/annurev.es.18.110187.001233
   Ross CA, 2008, PLANT SYST EVOL, V275, P219, DOI 10.1007/s00606-008-0066-3
   Ross CA, 2009, BIOL INVASIONS, V11, P441, DOI 10.1007/s10530-008-9261-y
   Rossiter MC, 1996, ANNU REV ECOL SYST, V27, P451, DOI 10.1146/annurev.ecolsys.27.1.451
   ROTHMALER W, 2002, EXKURSIONSFLORA DTSC
   Sakai AK, 2001, ANNU REV ECOL SYST, V32, P305, DOI 10.1146/annurev.ecolsys.32.081501.114037
   Santamaría L, 2003, ECOLOGY, V84, P2454, DOI 10.1890/02-0431
   SCHLICHTING CD, 1986, ANNU REV ECOL SYST, V17, P667, DOI 10.1146/annurev.es.17.110186.003315
   Schreiter S, 2011, AM J BOT, V98, pE39, DOI 10.3732/ajb.1000417
   SHAW RG, 1993, ECOLOGY, V74, P1638, DOI 10.2307/1939922
   SMALE MC, 1990, NEW ZEAL J ECOL, V14, P1
   Strauss SY, 1999, TRENDS ECOL EVOL, V14, P179, DOI 10.1016/S0169-5347(98)01576-6
   Stuart D. D., 2006, PLANT COLLECTOR GUID
   Thompson JN, 1998, TRENDS ECOL EVOL, V13, P329, DOI 10.1016/S0169-5347(98)01378-0
   Tutin TG, 1972, FLORA EUROPAEA, P202
   Verhoeven KJF, 2005, OIKOS, V108, P643, DOI 10.1111/j.0030-1299.2005.13727.x
   Webb C.J., 1988, Flora of New Zealand. Volume IV, Naturalised Pteridophytes, Gymnosperms, VIV
   Weber E, 1998, AM J BOT, V85, P1110, DOI 10.2307/2446344
   Williams JL, 2008, OECOLOGIA, V157, P239, DOI 10.1007/s00442-008-1075-1
   Wilson SB, 2004, HORTTECHNOLOGY, V14, P605, DOI 10.21273/HORTTECH.14.4.0605
   Wu ZY, 1996, PANAX GINSENG
NR 89
TC 38
Z9 49
U1 1
U2 85
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 1752-9921
J9 J PLANT ECOL-UK
JI J. Plant Ecol.
PD DEC
PY 2011
VL 4
IS 4
BP 209
EP 220
DI 10.1093/jpe/rtr007
PG 12
WC Plant Sciences; Ecology; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences; Environmental Sciences & Ecology; Forestry
GA 861SH
UT WOS:000298039000003
OA Bronze, Green Accepted
DA 2025-01-10
ER

PT S
AU Dunnett, N
AF Dunnett, Nigel
BE Sutton, RK
TI Ruderal Green Roofs
SO GREEN ROOF ECOSYSTEMS
SE Ecological Studies-Analysis and Synthesis
LA English
DT Article; Book Chapter
DE Bio-diverse roofs; Community dynamics; Functional ecology; Stress;
   Disturbance; Competition; Colonization
ID MEADOW; ECOSYSTEMS; MANAGEMENT; VEGETATION
AB An awareness of the ecological theory relating to the colonization, early successional stages and persistence of ruderal communities and their role within a matrix of other plant communities and plant types on green roofs provides an important basis for increased understanding of the long-term resilience of dynamic green roof vegetation assemblages. This chapter discusses the concept of the ruderal green roof, with its highly dynamic nature and inclusion of colonization, succession and change as core functioning elements. The theoretical background of a trait-based or functional type approach to working with green roof vegetation will be explored, and the wider role of 'ruderal' or disturbance-tolerant plant species in creating resilient and climate-adapted green roofs will be reviewed. Dynamic colonization processes have wide applications across typical extensive, semi-intensive and intensive green roof types where designers and users desire greater biodiversity, a more sustainable approach to long-term management, increased local distinctiveness, climate adaptation, and greater aesthetic and visual interest.
C1 [Dunnett, Nigel] Univ Sheffield, Dept Landscape, Western Bank, Sheffield S10 2TN, S Yorkshire, England.
C3 University of Sheffield
RP Dunnett, N (corresponding author), Univ Sheffield, Dept Landscape, Western Bank, Arts Tower, Sheffield S10 2TN, S Yorkshire, England.
EM n.dunnett@sheffield.ac.uk
CR [Anonymous], 2001, Plant strategies, Vegetation Process and Ecosystem Properties
   [Anonymous], 2012, EVOLUTIONARY STRATEG, DOI [DOI 10.1002/9781118223246, 10.1002/9781118223246]
   Baumann Nathalie, 2006, Urban Habitats, V4, P37
   Brenneisen Stephan, 2006, Urban Habitats, V4, P27
   Collins JP, 2000, AM SCI, V88, P416
   CONNELL JH, 1978, SCIENCE, V199, P1302, DOI 10.1126/science.199.4335.1302
   Del Tredici P., 2010, WILD URBAN PLANTS NE
   Dickinson G., 1998, ECOSYSTEMS
   Dunnett N., 2008, Planting green roofs and living walls
   Dunnett N, 2006, P GREEN ROOFT SUST C
   Dunnett Nigel, 2008, Urban Ecosystems, V11, P373, DOI 10.1007/s11252-007-0042-7
   Fischer LK, 2013, BIOL CONSERV, V159, P119, DOI 10.1016/j.biocon.2012.11.028
   Gallagher FJ, 2011, ENVIRON POLLUT, V159, P1159, DOI 10.1016/j.envpol.2011.02.007
   Gedge D, 2011, SMALL GREEN ROOFS
   Gedge D, 2003, P 1 N AM GREEN ROOFS
   Gilbert O.L., 1991, ECOLOGY URBAN HABITA
   Grant G., 2006, URB HABITAT, V4, P51
   GRIME JP, 1977, AM NAT, V111, P1169, DOI 10.1086/283244
   Hobbs RJ, 2006, GLOBAL ECOL BIOGEOGR, V15, P1, DOI 10.1111/j.1466-822x.2006.00212.x
   Holling C.S., 1996, Engineering resilience versus ecological resilience
   Kircher W, 2004, ACTA HORTIC, P301, DOI 10.17660/ActaHortic.2004.643.39
   KöppIer MR, 2014, LANDSCAPE URBAN PLAN, V126, P1, DOI 10.1016/j.landurbplan.2014.03.001
   Kohler M., 2006, URBAN HABITATS, V4, P3
   Kowarik I, 2011, ENVIRON POLLUT, V159, P1974, DOI 10.1016/j.envpol.2011.02.022
   Kreh W, 1945, PFLANZENWELT UNSERER, V97-101, P199
   Lachmund J, 2013, INSIDE TECHNOL, P1
   Loder A, 2014, LANDSCAPE URBAN PLAN, V126, P94, DOI 10.1016/j.landurbplan.2014.01.008
   MacIvor JS, 2011, ANN BOT-LONDON, V107, P671, DOI 10.1093/aob/mcr007
   Molineux CJ, 2009, ECOL ENG, V35, P1507, DOI 10.1016/j.ecoleng.2009.06.010
   Nagase A, 2011, LANDSCAPE URBAN PLAN, V112, P50
   Nagase A, 2013, LANDSCAPE URBAN PLAN, V112, P50, DOI 10.1016/j.landurbplan.2012.12.007
   Nassauer JoanIverson., 1995, Landscape Journal, V14, P161, DOI [10.3368/lj.14.2.161, DOI 10.3368/LJ.14.2.161]
   Scheffer M, 2001, NATURE, V413, P591, DOI 10.1038/35098000
   Schröder A, 2005, OIKOS, V110, P3, DOI 10.1111/j.0030-1299.2005.13962.x
   Smith RS, 1996, GRASS FORAGE SCI, V51, P278, DOI 10.1111/j.1365-2494.1996.tb02063.x
   Sukopp H, 2003, FLORA VEGETATION REF
   Sukopp H., 1979, Nature in cities: the natural environment in the design and development of urban green space, P115
   Sutton R, 2014, J LIVING ARCHIT, P22
   Wieditz I, 2003, GREEN ROOFS INFRASTR, V5, P8
NR 39
TC 15
Z9 17
U1 1
U2 16
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 0070-8356
BN 978-3-319-14983-7; 978-3-319-14982-0
J9 ECOL STUD-ANAL SYNTH
JI Ecol. Stud.
PY 2015
VL 223
BP 233
EP 255
DI 10.1007/978-3-319-14983-7_10
D2 10.1007/978-3-319-14983-7
PG 23
WC Ecology; Horticulture
WE Book Citation Index – Science (BKCI-S)
SC Environmental Sciences & Ecology; Agriculture
GA BE1LW
UT WOS:000368109000011
DA 2025-01-10
ER

PT J
AU Grant, R
   Roy, SS
   Zablah, CJ
   Aquino, P
   Simpson, M
   Viala, P
AF Grant, Richard
   Roy, Shouraseni Sen
   Zablah, Camilla Jimenez
   Aquino, Perla
   Simpson, Madisyn
   Viala, Paula
TI Climate adaptation and resilience indices for the Caribbean region: an
   assessment of four leading indices
SO CLIMATE AND DEVELOPMENT
LA English
DT Article; Early Access
DE Caribbean; climate adaptation index; performance; data limitations;
   Global Climate Risk Index; Good Life Index; ND-GAIN; Yale Environmental
   Performance Index
ID VULNERABILITY; RISK; PATTERNS; TRENDS
AB Countries of the Caribbean region share a common vulnerability and risk of disappearing if the dangers of climate change and global warming are not addressed collectively and urgently. Over the last decade, four open-source international indices, the Global Climate Risk Index (GCRI), Good Life Index (GLI), Norte Dame Global Adaptation Initiative (ND-GAIN), Yale Environmental Performance Index (EPI), have been developed and employed in research and policy as a measurement tool to aggregate data and examine risks exacerbated by climate change. Countries are ranked internationally based on their level of vulnerability and readiness to implement adaptation solutions. No index is explicitly developed for the Caribbean. However, there is an imperative to bridge community and national adaptation planning, which remains to be better integrated into climate policy and adaptation. Thus, we provide a timely assessment of the four most widely employed indices, reviewing individual country performances, 2010-2020. The results show some similarities regarding the best and worst performers, but significant variation is observed in the rate of improvement and degree of inertia. Each index has strengths and weaknesses. ND-GAIN is the index with the region's most transparent methodology and comprehensive coverage.
C1 [Grant, Richard; Roy, Shouraseni Sen; Zablah, Camilla Jimenez; Aquino, Perla; Simpson, Madisyn; Viala, Paula] Univ Miami, Dept Geog & Sustainable Dev, 1300 Campo Sano Bldg,115R, Coral Gables, FL 33124 USA.
C3 University of Miami
RP Grant, R (corresponding author), Univ Miami, Dept Geog & Sustainable Dev, 1300 Campo Sano Bldg,115R, Coral Gables, FL 33124 USA.
EM rgrant@miami.edu
RI Roy, Shouraseni/ABF-5185-2021
OI Roy, Shouraseni/0000-0003-4158-7082
CR Abson DJ, 2012, APPL GEOGR, V35, P515, DOI 10.1016/j.apgeog.2012.08.004
   Alleyne T., 2017, Unleashing growth and strengthening resilience in the Caribbean
   [Anonymous], 2022, DataBank
   Arnott Rob., 2016, Research Affiliates
   Bahadur A., 2021, Resilience Reset: Creating Resilient Cities in the Global South
   Berrang-Ford L, 2021, NAT CLIM CHANGE, V11, P989, DOI 10.1038/s41558-021-01170-y
   Burford G, 2013, SUSTAINABILITY-BASEL, V5, P3035, DOI 10.3390/su5073035
   Cevik S., 2021, Journal of Globalization and Development, V12, P47, DOI [https://doi.org/10.1515/jgd-2020-0015, DOI 10.1515/JGD-2020-0015]
   Cevik S, 2022, J ENVIRON ECON POLIC, V11, P420, DOI 10.1080/21606544.2022.2049372
   Chao SR, 2021, APPL GEOGR, V128, DOI 10.1016/j.apgeog.2021.102413
   Chen C., 2015, Country Index Technical Report
   Christiansen L., 2018, Adaptation metrics: Perspectives on measuring, aggregating and comparing adaptation results
   Corporacion Andina de Fomento, 2014, Vulnerability index to climate change in the Latin American and Caribbean Region
   Cutter SL, 2018, ENVIRONMENT, V60, P16, DOI 10.1080/00139157.2018.1517518
   de Sherbinin A, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.600
   de Souza JN, 2017, CORAL REEFS, V36, P701, DOI 10.1007/s00338-017-1562-0
   De Souza R. M., 2015, Re-framing island nations as champions of resilience in the face of climate change and disaster risk
   Dupuis J, 2013, GLOBAL ENVIRON CHANG, V23, P1476, DOI 10.1016/j.gloenvcha.2013.07.022
   Eckstein D., 2021, Global Climate Risk Index 2021: Who Suffers Most from Extreme Weather Events? Weather-Related Loss Events in 2019 and 20002019
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Fussel Hans-Martin., 2010, Review and Quantitative Analysis of Indices of Climate Change Exposure, Adaptive Capacity, Sensitivity, and Impacts
   Garschagen M, 2021, CLIM RISK MANAG, V34, DOI 10.1016/j.crm.2021.100357
   Garschagen M., 2016, Landeranalyse zum Katastrophenund Risikomanagement
   Garschagen M, 2021, CLIMATIC CHANGE, V169, DOI 10.1007/s10584-021-03209-7
   Goldman DaraE., 2008, OUT BOUNDS ISLANDS D
   Haberland T., 2008, Analysis of the Yale Environmental Performance Index (EPI)
   Hammill MO, 2014, ICES J MAR SCI, V71, P1332, DOI 10.1093/icesjms/fsu123
   Herron H., 2014, Climate change data and risk assessment methodologies for the Caribbean
   Hinkel J, 2011, GLOBAL ENVIRON CHANG, V21, P198, DOI 10.1016/j.gloenvcha.2010.08.002
   InterAmerican Development Bank, 2015, The Caribbean to improve its climate resilience with a US$10.49 million program supported by the PPCR through the IDB
   Klöck C, 2019, J ENVIRON DEV, V28, P196, DOI 10.1177/1070496519835895
   Leiter T., 2019, Adaptation Metrics. Current Landscape and Evolving Practices
   Li C, 2023, REMOTE SENS APPL, V32, DOI 10.1016/j.rsase.2023.101000
   Lo AY, 2015, CLIMATIC CHANGE, V131, P335, DOI 10.1007/s10584-015-1378-2
   Miola A., 2014, Concepts and metrics for climate change risk and development-towards an index for climate resilient development
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   O'Neill DW, 2018, NAT SUSTAIN, V1, P88, DOI 10.1038/s41893-018-0021-4
   Pelling M, 2002, INT DEV PLANN REV, V24, P59, DOI 10.3828/idpr.24.1.4
   Price A., 2022, Institute of Development Studies, DOI [https://doi.org/10.19088/K4D.2022.050, DOI 10.19088/K4D.2022.050]
   Raworth K., 2017, Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist
   Remling E, 2015, CLIM DEV, V7, P16, DOI 10.1080/17565529.2014.886992
   Rhiney K, 2015, GEOGR COMPASS, V9, P97, DOI 10.1111/gec3.12199
   Robinson SA, 2020, GEOGR TIDSSKR-DEN, V120, P79, DOI 10.1080/00167223.2020.1733432
   Robinson SA, 2018, ISL STUD J, V13, P79, DOI 10.24043/isj.59
   Robinson SA, 2019, CLIM DEV, V11, P47, DOI 10.1080/17565529.2017.1410086
   Robinson SA, 2017, MITIG ADAPT STRAT GL, V22, P669, DOI 10.1007/s11027-015-9693-5
   Singh B., 2014, CLIMATE CHANGE RESIL
   Stennett-Brown RK, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0219250
   Thomas A, 2019, REG ENVIRON CHANGE, V19, P2013, DOI 10.1007/s10113-019-01540-5
   UNDP/UN Environment, 2018, Climate impact vulnerability index: Lessons learned and systematization of the IVACC design and application process in the dominican republic
   United Nations Framework for Convention on Climate Change (UNFCC), 2016, The Paris agreemen t
   Ward PJ, 2020, NAT HAZARD EARTH SYS, V20, P1069, DOI 10.5194/nhess-20-1069-2020
NR 53
TC 2
Z9 2
U1 3
U2 5
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1756-5529
EI 1756-5537
J9 CLIM DEV
JI Clim. Dev.
PD 2023 NOV 28
PY 2023
DI 10.1080/17565529.2023.2282482
EA NOV 2023
PG 11
WC Development Studies; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology
GA GJ4L3
UT WOS:001152287400001
DA 2025-01-10
ER

PT J
AU Jhong, BC
   Tachikawa, Y
   Tanaka, T
   Udmale, P
   Tung, CP
AF Jhong, Bing-Chen
   Tachikawa, Yasuto
   Tanaka, Tomohiro
   Udmale, Parmeshwar
   Tung, Ching-Pin
TI A Generalized Framework for Assessing Flood Risk and Suitable Strategies
   under Various Vulnerability and Adaptation Scenarios: A Case Study for
   Residents of Kyoto City in Japan
SO WATER
LA English
DT Article
DE climate adaptation strategy; climate risk map; flood; exposure;
   vulnerability; metropolitan city
ID CLIMATE-CHANGE; CHANGE IMPACTS; VARIABILITY; INSURANCE; CITIES; INDEX
AB This study proposes a generalized framework for the assessment of flood risk and potential strategies to mitigate flood under various vulnerability and adaptation scenarios. The possible causes of hazard, exposure and vulnerability in flood disaster were clearly identified by using a climate risk template. Then, levels of exposure and vulnerability with adaptive capacity and sensitivity were further defined by a quantification approach, and the climate risk maps were consequently provided. The potential possible climate adaptation strategies were investigated through the comparison of climate risk maps with diverse adaptation options. The framework was demonstrated in the Kyoto City in Japan with residents as a target population to reduce the flood risk. The results indicate that the government should pay attention to reducing the population in flood-prone areas and adopt diverse adaptation strategies to reduce the flood risk to the residents. Rainwater storage and green roofs as adaptation strategies as short-term planning options are recommended. The construction of detention ponds has been suggested to prevent flood risks in future as a part of the long-term planning process. In conclusion, the proposed framework is expected to be a suitable tool for supporting climate risk analysis in the context of flood disasters.
C1 [Jhong, Bing-Chen] Natl Taiwan Univ Sci & Technol, Dept Civil & Construct Engn, Taipei 10607, Taiwan.
   [Tachikawa, Yasuto] Kyoto Univ, Grad Sch Engn, Dept Civil & Earth Resources Engn, Kyoto 6158540, Japan.
   [Tanaka, Tomohiro] Kyoto Univ, Grad Sch Global Environm Studies, Kyoto 6158540, Japan.
   [Udmale, Parmeshwar] Asian Inst Technol, Sch Environm Resources & Dev, Dept Dev & Sustainabil, Pathum Thani 12120, Thailand.
   [Tung, Ching-Pin] Natl Taiwan Univ, Dept Bioenvironm Syst Engn, Taipei 10617, Taiwan.
C3 National Taiwan University of Science & Technology; Kyoto University;
   Kyoto University; Asian Institute of Technology; National Taiwan
   University
RP Jhong, BC (corresponding author), Natl Taiwan Univ Sci & Technol, Dept Civil & Construct Engn, Taipei 10607, Taiwan.
EM jhongbc0516@gmail.com; tachikawa@hywr.kuciv.kyoto-u.ac.jp;
   tanaka.tomohiro.7c@kyoto-u.ac.jp; udmale@ait.ac.th; cptung@ntu.edu.tw
RI Udmale, Parmeshwar/ABF-3433-2020; Tachikawa, Yasuto/HHS-8494-2022
OI Tanaka, Tomohiro/0000-0002-8884-9089; Tachikawa,
   Yasuto/0000-0002-1647-8899; Jhong, Bing-Chen/0000-0003-3817-3946
FU Ministry of Science and Technology, Taiwan [109-2621-M-002 -005 -]
FX This research was funded by Ministry of Science and Technology, Taiwan,
   grant number 109-2621-M-002 -005 -. The APC was funded by Ching-Pin
   Tung.
CR Acharya A, 2019, ENVIRON DEV, V31, P55, DOI 10.1016/j.envdev.2018.12.003
   Adelekan IO, 2011, NAT HAZARDS, V56, P215, DOI 10.1007/s11069-010-9564-z
   Akter T, 2018, ENVIRON SCI POLICY, V89, P163, DOI 10.1016/j.envsci.2018.07.002
   [Anonymous], 2014, PROSIDING SEMINAR NA
   Arrighi C, 2017, HYDROL EARTH SYST SC, V21, P515, DOI 10.5194/hess-21-515-2017
   Australian Institute for Disaster Resilience (AIDR), 2017, AUSTR DIS RES GUID 7
   Balica SF, 2012, NAT HAZARDS, V64, P73, DOI 10.1007/s11069-012-0234-1
   Costabile P, 2020, J HYDROL, V580, DOI 10.1016/j.jhydrol.2019.124231
   Crichton D, 2008, GENEVA PAP R I-ISS P, V33, P117, DOI 10.1057/palgrave.gpp.2510151
   Dankers R, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009719
   de Moel H, 2009, NAT HAZARD EARTH SYS, V9, P289, DOI 10.5194/nhess-9-289-2009
   Dilling L, 2015, WIRES CLIM CHANGE, V6, P413, DOI 10.1002/wcc.341
   Fassman EA, 2010, J HYDROL ENG, V15, P475, DOI 10.1061/(ASCE)HE.1943-5584.0000238
   Fekete A, 2017, NAT HAZARDS, V86, P151, DOI 10.1007/s11069-016-2720-3
   Grahn T, 2017, INT J DISAST RISK RE, V21, P367, DOI 10.1016/j.ijdrr.2017.01.016
   Guo YP, 2007, J HYDROL ENG, V12, P197, DOI 10.1061/(ASCE)1084-0699(2007)12:2(197)
   Huong HTL, 2013, HYDROL EARTH SYST SC, V17, P379, DOI 10.5194/hess-17-379-2013
   Jhong BC, 2019, WATER RESOUR MANAG, V33, P3377, DOI 10.1007/s11269-019-02306-8
   Joakim EP, 2015, ENVIRON HAZARDS-UK, V14, P137, DOI 10.1080/17477891.2014.1003777
   Jurgilevich A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5508
   Kunreuther H, 2006, ANN AM ACAD POLIT SS, V604, P208, DOI 10.1177/0002716205285685
   Lee DR, 2014, GLOBAL ENVIRON CHANG, V29, P78, DOI 10.1016/j.gloenvcha.2014.08.002
   Mansur AV, 2016, SUSTAIN SCI, V11, P625, DOI 10.1007/s11625-016-0355-7
   Martínez-Gomariz E, 2018, J FLOOD RISK MANAG, V11, pS817, DOI 10.1111/jfr3.12262
   Meng M, 2019, ENVIRON SCI POLICY, V96, P95, DOI 10.1016/j.envsci.2019.03.006
   Milanesi L, 2018, WATER RESOUR RES, V54, P7177, DOI 10.1029/2018WR022577
   Nasiri H, 2019, INT J ENVIRON SCI TE, V16, P2249, DOI 10.1007/s13762-018-1797-5
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Shinde P.S., 2002, THESIS
   Shrestha Sangam, 2017, International Journal of Sustainable Built Environment, V6, P285, DOI 10.1016/j.ijsbe.2016.09.006
   Song J, 2019, SCI TOTAL ENVIRON, V696, DOI 10.1016/j.scitotenv.2019.133764
   Tripathi P., 2015, Interdisciplinary Journal of Contemporary Research, V2, P91
   Tung CP, 2019, WATER-SUI, V11, DOI 10.3390/w11030497
   Velasco M, 2018, J FLOOD RISK MANAG, V11, pS55, DOI 10.1111/jfr3.12247
   Vijayaraghavan K, 2014, WATER RES, V63, P94, DOI 10.1016/j.watres.2014.06.012
   WATANABE S, 1995, WATER SCI TECHNOL, V32, P25, DOI 10.2166/wst.1995.0007
   Wu JB, 2019, SCI TOTAL ENVIRON, V694, DOI 10.1016/j.scitotenv.2019.133586
   Zhai G., 2003, J. Nat. Disaster Sci., V25, P23
NR 38
TC 9
Z9 9
U1 4
U2 19
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD SEP
PY 2020
VL 12
IS 9
AR 2508
DI 10.3390/w12092508
PG 23
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA OG7EB
UT WOS:000582041600001
OA gold
DA 2025-01-10
ER

PT J
AU Jessee, N
AF Jessee, Nathan
TI Reshaping Louisiana's coastal frontier: managed retreat as colonial
   decontextualization
SO JOURNAL OF POLITICAL ECOLOGY
LA English
DT Article
DE Community resettlement; managed retreat; racial capitalism;
   environmental change; native American and Indigenous Studies
ID SOCIAL-JUSTICE; ADAPTATION; PROPERTY; MOBILITY; RACE
AB This article describes social encounters produced by climate adaptation policy experimentation focused on managed retreat-a concept increasingly used by academics and planning professionals to describe various kinds of relocation from areas exposed to environmental hazards. Building on scholarship that examines the political ecology of resettlement and adaptation, I draw on five years of ethnographic work conducted alongside Isle de Jean Charles Biloxi-Chitimacha-Choctaw Tribal leaders as their longstanding Tribal resettlement was transformed by government investment. I describe how Louisiana's Office of Community Development relied on Tribal planning to garner federal funds, used those funds to reduce the scope of the resettlement, and systematically erased the initial resettlement rationales and aims of Indigenous leaders. I liken the state's approach to Dina Gilio-Whitaker's notion of decontextualization as a colonial strategy, and argue that state efforts to transform the resettlement from what Tribal leaders viewed as "an act of cultural survival" to a scalable model for managed retreat policy threatens to reproduce a frontier dynamic whereby colonial and capitalist futures are once again rested upon the erasure of Indigenous peoples. State tools for decontextualization included published constructions of risk, community, and timelines; liberal planning conventions; and evocations of legal barriers. Ethnographic accounts of such processes can inform future resistance to ecocolonial schemes within climate adaptation.
C1 [Jessee, Nathan] Princeton Univ, High Meadows Environm Inst, Princeton, NJ 08544 USA.
C3 Princeton University
RP Jessee, N (corresponding author), Princeton Univ, High Meadows Environm Inst, Princeton, NJ 08544 USA.
EM nathanjessee@princeton.edu
FU Wenner-Gren Foundation; Tulane University's Center for the Gulf South;
   Temple University's Graduate School
FX The research for this article was funded by Wenner-Gren Foundation,
   Tulane University's Center for the Gulf South, and Temple University's
   Graduate School.
CR Acevedo E, 2020, CBS 60 MINUTES OVERT
   Ajibade I, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102187
   Ajibade Idowu Jola., 2021, Global Views on Climate Relocation and Social Justice: Navigating Retreat
   Alaska Institute for Justice, 2020, RIGHTS IND PEOPL ADD
   [Anonymous], 2014, Mohawk interruptions: Political life across the borders of settler states
   Arvin Maile., 2013, FEMINIST FORMATIONS, V25, P8, DOI DOI 10.1353/FF.2013.0006
   Barker Joanne., 2011, NATIVE ACTS LAW RECO
   Barra MP, 2021, ANN AM ASSOC GEOGR, V111, P266, DOI 10.1080/24694452.2020.1766411
   Barry J.M., 1998, RISING TIDE GREAT MI
   Blackhawk Ned., 2006, VIOLENCE LAND INDIAN
   Bronen R., 2011, NYU Review of Law and Social Change, V35, P357
   Burden-Stelly C, 2020, MON REV, V72, P8, DOI 10.14452/MR-072-03-2020-07_2
   Callison C., 2017, OXF RES ENCY CLIM SC, DOI [10.1093/acrefore/9780190228620.013.411, DOI 10.1093/ACREFORE/9780190228620.013.411]
   CIRD, 2017, ISL JEAN CHARL WORKS
   Clipp A., 2017, 2017 Coastal Master Plan: Appendix B: People and the Landscape
   Colten CE, 2018, REG ENVIRON CHANGE, V18, P371, DOI 10.1007/s10113-017-1115-7
   Colten CE, 2017, J COASTAL RES, V33, P699, DOI 10.2112/JCOASTRES-D-16-00008.1
   Colten Craig.E., 2015, Transplanting Communities Facing Environmental Change: An Annotated Bibliography on Resettlement
   Comardelle C, 2020, NONPROFIT Q
   Dalbom C., 2014, Community resettlement prospects in southeast Louisiana: A multidisciplinary exploration of legal, cultural, and demographic aspects of moving individuals and communities
   Darlington J.D., 2006, RELATIONSHIP COASTAL
   Davenport C., 2016, New York Times
   de Vries D.H., 2012, International Journal of Mass Emergencies Disasters, V30, P1, DOI [DOI 10.1017/CBO9781107415324.004, 10.1017/CBO9781107415324.004]
   Deloria, 1988, Custer Died for Your Sins: An Indian Manifesto
   Denetdale Jennifer., 2008, The Long Walk: The Forced Navajo Exile
   Dermansky J, 2019, DESMOG          0111
   DeSantis John., 2016, THIBODAUX MASSACRE R
   Dunbar-Ortiz R., 2014, An indigenous peoples' history of the United States
   Elliott J. R., 2020, SOCIUS, V6, DOI 10.1177%2F2378023120905439
   Estes Nick., 2019, OUR HIST IS FUTURE S
   Forbes Pat, 2019, COMMUNICATION 0507
   Fullilove MindyThompson., 2005, Root Shock: How Tearing up City Neighborhoods Hurts America, and What We Can Do about It
   Gass Henry., 2017, Christian Science Monitor
   Gaventa John., 1993, VOICES CHANGE PARTIC
   Gilio-Whitaker Dina., 2019, LONG GRASS GROWS IND
   Gilmore R.W., 2007, Golden Gulag
   Government Accountability Office, 2020, CLIM MIGR PIL PROGR
   Grove K, 2020, GEOFORUM, V117, P134, DOI 10.1016/j.geoforum.2020.09.014
   Hardy RD, 2017, GEOFORUM, V87, P62, DOI 10.1016/j.geoforum.2017.10.005
   Hardy S, 2019, ADVOCATE
   HARRIS CI, 1993, HARVARD LAW REV, V106, P1707, DOI 10.2307/1341787
   Hino M, 2017, NAT CLIM CHANGE, V7, P364, DOI [10.1038/NCLIMATE3252, 10.1038/nclimate3252]
   Hudson PJ., 2018, Boston Review
   IDJC, 2009, TRIB PROT PLAN
   Isacoff R., 2021, GLOBAL VIEWS CLIMATE
   James E, 2003, HOUMA COURIER 1003
   Jenkins Destin., 2021, Histories of Racial Capitalism (2021)
   Jessee N., 2020, Louisiana's Response to Extreme Weather, P147
   Jessee N, 2021, DESMOG 0723
   Jessee N., 2020, ANTHROPOCENE CURRICU
   Jessee Nathan., 2015, American Anthropologist, V117, P808
   Keenan JM, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabb32
   Kelley R, 2017, MON LABOR REV
   Kindon S, 2007, ROUTL STUD HUM GEOGR, V22, P9
   King N, 2010, HOUMA TODAY 1110
   Koslov L, 2016, PUBLIC CULTURE, V28, P359, DOI 10.1215/08992363-3427487
   Lajimodiere DeniseK., 2019, Stringing Rosaries: The History, the Unforgivable, and the Healing of Northern Plains American Indian Boarding School Survivors
   Laughland O, 2021, GUARDIAN 0912
   LDOA, 2019, OUR LAND WAT REG APP
   Li TM, 1996, DEV CHANGE, V27, P501, DOI 10.1111/j.1467-7660.1996.tb00601.x
   Louisiana Budget Project, 2018, POV INC IN CONT PLAG
   Louisiana Department of Administration (LDOA), 2017, NDR ACT PLAN APPR 20
   Louisiana Department of Administration (LDOA), 2015, RES RES STRAT CAS IS
   Louisiana Department of Administration (LDOA), 2018, ISL JEAN CHARL IDJC
   Louisiana Department of Administration (LDOA), 2017, LA SAFE LOUIS STRAT
   Louisiana Department of Administration (LDOA), NAT DIS RES COMP PHA
   Louisiana Department of Administration (LDOA), 2017, RES ISL JEAN CHARL R
   Louisiana Department of Administration (LDOA), 2019, SUBST AM 5 INTR NEW
   Louisiana Department of Administration (LDOA), 2009, COMM RES PIL PROGR
   Louisiana Housing Corporation, 2019, LOUIS HOUS NEEDS ASS
   Louisiana Land Trust, 2020, RFP RFQ SFO BID DOC
   Louisiana Trustee Implementation Group (LTIG), 2018, FIN REST PLAN ENV AS
   Luke N, 2020, AM QUART, V72, P603, DOI 10.1353/aq.2020.0037
   Maldonado J. K., 2020, EOS T AM GEOPHYS UN, V101, DOI 10.1029/2020EO150527
   Maldonado J. K., 2018, SEEK JUST EN SACR ZO
   Maldonado J, 2021, J ENVIRON STUD SCI, V11, P294, DOI 10.1007/s13412-021-00695-0
   Maldonado Julie K., 2015, Disasters Impact on Livelihood and Cultural Survival, P239
   Maldonado JK, 2013, CLIMATIC CHANGE, V120, P601, DOI 10.1007/s10584-013-0746-z
   Maldonado JK, 2014, J POLIT ECOL, V21, P61, DOI 10.2458/v21i1.21125
   Manning-Broome C., 2015, View from the Coast: Local Perspectives and Policy Recommendations on Flood-Risk Reduction in South Louisiana
   Marino E, 2015, FIERCE CLIMATE SACRED GROUND: AN ETHNOGRAPHY OF CLIMATE CHANGE IN SHISHMAREF, ALASKA, P1
   Marshall B., 2017, LENS
   McClintock A, 2014, PMLA, V129, P819, DOI 10.1632/pmla.2014.129.4.819
   McPhee John., 1989, The Control of Nature
   Morris Christopher., 2012, BIG MUDDY ENV HIST M
   Naquin A., 2019, Preserving Our Place: A Community Field Guide to Engagement, Resilience, and Resettlement: Community regeneration in the face of environmental and developmental pressures
   O'Neill KarenM., 2006, RIVERS DESIGN STATE
   Office of Governor John Bel Edwards, 2019, FED EN REG COMM AUTH
   Palmer MA, 2020, ENVIRON PLANN D, V38, P793, DOI 10.1177/0263775820922233
   Park K, 2021, CONQUEST SLAVERY FDN
   Pelot-Hobbs L., 2019, THESIS CITY U NY
   Porter L., 2016, Unlearning the colonial cultures of planning
   Randolph Ned., 2018, Lateral
   Reilly A, 2016, E NEWS
   Reuss Martin., 2004, DESIGNING BAYOUS CON, DOI DOI 10.2307/27649250
   Robinson CedricJ., 2021, Black Marxism, Revised and Updated Third Edition: The Making of the Black Radical Tradition
   Safransky S, 2014, GEOFORUM, V56, P237, DOI 10.1016/j.geoforum.2014.06.003
   Sanders M, 2018, DONT LABEL THEM CLIM
   Sell, 2008, HIST OFFSHORE OIL GA
   Shearer C, 2012, J POLIT ECOL, V19, P174, DOI 10.2458/v19i1.21725
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   Silvernail John., 1967, New Orleans Geological Society Oil and Gas Fields of Southeast Louisiana, Volume, V2, P78
   Simms JRZ, 2021, J ENVIRON STUD SCI, V11, P316, DOI 10.1007/s13412-021-00682-5
   Smith LindaTuhiwai., 2012, Decolonizing Methodologies: Research and Indigenous Peoples, V2nd
   Smith N., 1992, POSTMODERNISM SOCIAL, P57, DOI [10.1007/978-1-349-22183-7_4, DOI 10.1007/978-1-349-22183-7_4]
   Solet K., 2006, THESIS U NEW ORLEANS
   Spencer Robyn., 1994, Journal of Negro History, V79, P170
   Sultana F, 2007, ACME, V6, P374
   Taylor KY, 2019, JUST POWER POLIT, P1
   Toews, 2018, STOLEN CITY RACIAL C
   Tsing AL, 2015, MUSHROOM AT THE END OF THE WORLD: ON THE POSSIBILITY OF LIFE IN CAPITALIST RUINS, P1, DOI 10.1515/9781400873548
   Tuck E, 2012, DECOLONIZATION, V1, P1
   Turner RE, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0207717
   United States Army Corps of Engineers (USACE), 2013, REV PROGR ENV IMP ST
   United States Bureau of Indian Affairs, 2008, SUMM CRIT EV AM PROP
   United States Department of Housing and Urban Development (HUD), 2016, NAT DIS RES COMP GRA
   United States Department of Housing and Urban Development (HUD), 2014, NAT DIS RES COMP PHA
   United States Department of Labor, 2018, LOUIS EC GLANC
   United States Geological Survey, TERR BAS SUMM COAST
   Via Catharine Ashley., 2005, Acadia Plantation Records Mss
   Vimalassery M., 2016, THEORY EVENT, V19
   Whyte K., 2017, Humanities for the Environment: Integrating Knowledges, Forging New Constellations of Practice, P88
   Whyte K, 2019, MOBILITIES-UK, V14, P319, DOI 10.1080/17450101.2019.1611015
   Wildcat D., 2009, Red alert! Saving the planet with indigenous knowledge
   Wolfe P, 2006, J GENOCIDE RES, V8, P387, DOI 10.1080/14623520601056240
   Woods ClydeAdrian., 1998, Development Arrested: The Blues and Plantation Power in the Mississippi Delta
NR 126
TC 16
Z9 20
U1 1
U2 11
PU UNIV ARIZONA LIBRARIES
PI TUCSON
PA UNIV ARIZONA LIBRARIES, TUCSON, AZ 85721 USA
SN 1073-0451
J9 J POLIT ECOL
JI J. Polit. Ecol.
PY 2022
VL 29
BP 277
EP 301
PG 25
WC Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA 1K4UX
UT WOS:000798598900001
DA 2025-01-10
ER

PT J
AU Shabib, D
   Khan, S
AF Shabib, Dalia
   Khan, Shusmita
TI Gender-sensitive adaptation policy-making in Bangladesh: status and ways
   forward for improved mainstreaming
SO CLIMATE AND DEVELOPMENT
LA English
DT Article
DE gender; mainstreaming; adaptation; climate change; climate policy
ID CLIMATE-CHANGE; FEMINIZATION; POVERTY
AB Bangladesh is particularly vulnerable to the impacts of climate change such as flooding, cyclones and drought. Women in Bangladesh are disproportionately affected by these impacts due to the nature of their livelihoods, their social obligations and confines, and their unique nutritional and health requirements, particularly during pregnancy and breastfeeding. Climate change policy in Bangladesh seeks to replicate adaptation policies under the United Nations Framework Convention on Climate Change. This paper will briefly review the policy response to climate change in Bangladesh. As climate adaptation requires a multi-sectoral response, relevant policy concerned with climate, adaptation, poverty, gender and health will be studied. This assessment will determine whether gender issues related to adaptation are addressed in key policy pieces in Bangladesh. Key interventions related to climate change will also be assessed to determine whether gender is integrated in operational activity. Finally, the role of women in the development of adaptation policy will be assessed by outlining their participation in adaptation discourse. Findings indicate that gender-sensitive policies are quite limited. Policies may acknowledge the particular vulnerabilities of women, but operational planning to address these is absent. Whilst some operational responses superficially acknowledge vulnerability and may include women in planning processes, few address the unique impacts of climate change on women.
RP Shabib, D (corresponding author), Mohammad El Zayyat St,Blg 948, Tyr, Lebanon.
EM dalia.shabib@gmail.com
CR Adger W. N., 2003, Progress in Development Studies, V3, P179, DOI 10.1191/1464993403ps060oa
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   [Anonymous], 2013, UNFCCC BANGL EXP NAP
   [Anonymous], 2011, GEND CLIM CHANG HLTH
   [Anonymous], 2013, UNESCAP CRIT EV POL
   [Anonymous], NUTR STRAT
   [Anonymous], CHILD MOTH NUTR SURV
   [Anonymous], 2011, BANGL DEM HLTH SURV
   Arora-Jonsson S, 2011, GLOBAL ENVIRON CHANG, V21, P744, DOI 10.1016/j.gloenvcha.2011.01.005
   Booram N., 1993, CTR GENDER DEV STUDI, V1, P5
   Cagatay N., 1998, SOCIAL DEV POVERTY E
   Cannon T., 2009, PRACTICAL ACTION PUB
   CARE, 2013, RED VULN CLIM CHANG
   Fukuda-Parr S, 1999, FEM ECON, V5, P99, DOI 10.1080/135457099337996
   Government of Bangladesh, 2008, COMPR DIS MAN PROGR
   Independent Commission for Aid Impact, 2011, DEP INT DEV CLIM CHA
   International Federation of Red Cross and Red Crescent Societies, 2005, WORLD DIS REP 2005
   International Monetary Fund, 2013, 1363 IMF
   Klein RJT, 2007, CLIMATIC CHANGE, V84, P23, DOI 10.1007/s10584-007-9268-x
   Konate A. M., 2003, MAINSTREAMING ADAPTA
   Micronutrient Initiative, 2013, STAT HLTH DEV BANGL
   Ministry of Disaster Management and Relief, 2008, COMPR DIS MAN PROGR
   Ministry of Environment and Forest, 2005, NAT AD PROGR ACT NAP
   Ministry of Environment and Forest, 1995, NAT ENV MAN ACT PLAN, VII
   Nelson V., 2002, Gender and Development, V10, P51, DOI 10.1080/13552070215911
   Network for Information Response and Preparedness Activities in Disaster, 2011, COLL
   PEARCE D, 1978, URBAN SOC CHANGE REV, V11, P28
   Rahman AA, 2007, UNDP HUMAN DEV REPOR
   Reid H., 2009, Participatory Learning and Action, V60, P11
   Thomalla F., 2005, INT I ENV DEV, V176, P668
   UNFPA & WEDO, 2009, MAK NAPAS WORK WOM
   United Nations Development Project, 2010, AD FUND EXPL GEND DI
   World Health Organization, 2011, SOC DIM CLIM CHANG
NR 33
TC 16
Z9 19
U1 1
U2 42
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1756-5529
EI 1756-5537
J9 CLIM DEV
JI Clim. Dev.
PD OCT 2
PY 2014
VL 6
IS 4
SI SI
BP 329
EP 335
DI 10.1080/17565529.2014.951017
PG 7
WC Development Studies; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology
GA AS7YF
UT WOS:000344467100005
OA Bronze
DA 2025-01-10
ER

PT J
AU Bretschger, L
   Valente, S
AF Bretschger, Lucas
   Valente, Simone
TI Climate Change and Uneven Development
SO SCANDINAVIAN JOURNAL OF ECONOMICS
LA English
DT Article
DE Climate adaptation; climate change; endogenous growth; pollution; uneven
   development
ID ENDOGENOUS GROWTH; RESOURCE; POLLUTION
AB In this paper, using a theoretical model with endogenous capital depreciation, we study the effects of climate change and adaptation on long-run development. We show that climate change affects economic growth depending on climate exposure and adaptation efficiency, which are asymmetric between different countries. Poor countries are likely to be hurt more, because of the negative effects of climate change on the rate of depreciation of the assets that represent the engine of growth. These asymmetries generally induce growth deficits and unsustainability traps in less-developed economies.
C1 [Bretschger, Lucas; Valente, Simone] Swiss Fed Inst Technol, Ctr Econ Res, CH-8032 Zurich, Switzerland.
C3 Swiss Federal Institutes of Technology Domain; ETH Zurich
RP Bretschger, L (corresponding author), Swiss Fed Inst Technol, Ctr Econ Res, CH-8032 Zurich, Switzerland.
EM lbretschger@ethz.ch; svalente@ethz.ch
CR [Anonymous], 2006, Avoiding dangerous climate change
   [Anonymous], 2010, COST DEV COUNTR AD C
   [Anonymous], 2009, ASSESSING COSTS ADAP
   [Anonymous], 2006, HDB ENV EC
   [Anonymous], 2010, World Development Report 2010: Development and Climate Change
   Barbier EB, 1999, ENVIRON RESOUR ECON, V14, P51, DOI 10.1023/A:1008389422019
   BOVENBERG AL, 1995, J PUBLIC ECON, V57, P369
   Bretschger L, 2007, ENVIRON RESOUR ECON, V36, P1, DOI 10.1007/s10640-006-9043-x
   Brock WA, 2005, HANDB ECON, V22, P1749
   Brock WA, 2010, J ECON GROWTH, V15, P127, DOI 10.1007/s10887-010-9051-0
   Collier P., 2008, OXFORD REV ECON POL, V24, P211
   DASGUPTA P, 1974, REV ECON STUD, P3
   Daubanes J, 2010, ENVIRON RESOUR ECON, V47, P567, DOI 10.1007/s10640-010-9393-2
   Dell M, 2009, AM ECON REV, V99, P198, DOI 10.1257/aer.99.2.198
   Egli H, 2007, ENVIRON RESOUR ECON, V36, P15, DOI 10.1007/s10640-006-9044-9
   Fankhauser S, 2005, RESOUR ENERGY ECON, V27, P1, DOI 10.1016/j.reseneeco.2004.03.003
   Fankhauser S, 2010, WIRES CLIM CHANGE, V1, P23, DOI 10.1002/wcc.14
   Füssel HM, 2010, WIRES CLIM CHANGE, V1, P288, DOI 10.1002/wcc.40
   Grimaud A., 2007, 0704225 LERNA
   Groth C, 2007, J ENVIRON ECON MANAG, V53, P80, DOI 10.1016/j.jeem.2006.07.004
   Manne AS, 2005, GERAD 25TH ANNIV SER, V3, P175
   Mendelsohn R., 2010, 2010 WORLD C ENV RES
   Michel P., 1995, Environment and Resource Economics, V6, P279
   Peretto PF, 2009, J ENVIRON ECON MANAG, V57, P269, DOI 10.1016/j.jeem.2008.07.007
   Pindyck RS, 2000, RESOUR ENERGY ECON, V22, P233, DOI 10.1016/S0928-7655(00)00033-6
   SCHELLING TC, 1995, ENERG POLICY, V23, P395, DOI 10.1016/0301-4215(95)90164-3
   Scholz CM, 1999, ENVIRON RESOUR ECON, V13, P169, DOI 10.1023/A:1008201811142
   Smulders Sjak., 1996, EUR J POLIT ECON, V12, P505
   SOLOW RM, 1974, REV ECON STUD, P29
   STIGLITZ J, 1974, REV ECON STUD, P123
   Stokey NL, 1998, INT ECON REV, V39, P1, DOI 10.2307/2527228
   Tahvonen O., 1995, ENVIRON RESOUR ECON, V5, P9, DOI [https://doi.org/10.1007/BF00691907, DOI 10.1007/BF00691907]
   Tol RSJ, 2009, J ECON PERSPECT, V23, P29, DOI 10.1257/jep.23.2.29
   van der Ploeg Frederick., 1991, Environmental and Resource Economics, V1, P215, DOI [10.1007/BF00310019, DOI 10.1007/BF00310019]
   WITHAGEN C, 1994, RESOUR ENERGY ECON, V16, P235, DOI 10.1016/0928-7655(94)90007-8
   Withagen C., 1995, ENVIRON RESOUR ECON, V5, P1
NR 36
TC 30
Z9 31
U1 0
U2 19
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0347-0520
EI 1467-9442
J9 SCAND J ECON
JI Scand. J. Econ.
PY 2011
VL 113
IS 4
SI SI
BP 825
EP 845
DI 10.1111/j.1467-9442.2011.01676.x
PG 21
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA 863MT
UT WOS:000298169200005
DA 2025-01-10
ER

PT J
AU Van Daele, F
   Honnay, O
   De Kort, H
AF Van Daele, Frederik
   Honnay, Olivier
   De Kort, Hanne
TI Genomic analyses point to a low evolutionary potential of prospective
   source populations for assisted migration in a forest herb
SO EVOLUTIONARY APPLICATIONS
LA English
DT Article
DE assisted migration; climate change; forest herb; genetic offset;
   landscape genomics; local adaptation
ID LOCAL ADAPTATION; CLIMATE-CHANGE; HABITAT FRAGMENTATION; DISPERSAL
   LIMITATION; TEMPERATURE RESPONSE; FAGUS-SYLVATICA; CANDIDATE GENES; R
   PACKAGE; LANDSCAPE; SCALE
AB Climate change is increasingly impacting temperate forest ecosystems and many forest herbs might be unable to track the changing climate due to dispersal limitation. Forest herbs with a low adaptive capacity may therefore benefit from conservation strategies that mitigate dispersal limitation and evolutionary constraints, such as assisted migration. However, assisted migration strategies rarely consider evolutionary constraints of potential source populations that may jeopardize their success. In cases where climate adaptation is overshadowed by competing evolutionary processes, assisted migration is unlikely to support adaptation to future climates. Using a combination of population and landscape genomic analyses, we disentangled local adaptation drivers and quantified the adaptability and vulnerability to climate change of the self-incompatible deciduous forest herb Primula elatior. Southern populations displayed a sharp genetic turnover and a considerable amount of local adaptation under diversifying selection was discovered. However, most of the outlier loci could not be linked to climate variables (71%) and were likely related to other local adaptation drivers, such as photoperiodism. Furthermore, specific adaptations to climate extremes, such as drought stress, could not be detected. This is in line with the typical occurrence of forest herbs in buffered climatic conditions, which can be expected to reduce selection pressures imposed by climate. Finally, populations in the south of the distribution area had increased sensitivity to climate change due to a reduced adaptive capacity and a moderate genetic offset, while central European populations were sensitive due to a high genetic offset. We conclude that assisted migration from southern source populations could bear significant risk due to nonclimatic maladaptation and a low adaptive capacity. Regional admixture and restoration of ecological connectivity to increase the adaptive capacity, and assisted range expansion to suitable habitat in the north might be more appropriate mitigation strategies.
C1 [Van Daele, Frederik; Honnay, Olivier; De Kort, Hanne] Katholieke Univ Leuven, Dept Biol Plant Conservat & Populat Biol, Kasteelpk Arenberg 31, B-3001 Leuven, Belgium.
C3 KU Leuven
RP Van Daele, F (corresponding author), Katholieke Univ Leuven, Dept Biol Plant Conservat & Populat Biol, Kasteelpk Arenberg 31, B-3001 Leuven, Belgium.
EM frederik.vandaele@kuleuven.be
RI Honnay, Olivier/AAH-8625-2019; Van Daele, Frederik/L-9450-2019; De Kort,
   Hanne/AAI-9063-2021
OI De Kort, Hanne/0000-0003-2516-0134; Van Daele,
   Frederik/0000-0001-5827-722X; Honnay, Olivier/0000-0002-4287-8511
FU Fonds Wetenschappelijk Onderzoek [G091419N]
FX Fonds Wetenschappelijk Onderzoek, Grant/Award Number: G091419N
CR Ågren J, 2013, P NATL ACAD SCI USA, V110, P21077, DOI 10.1073/pnas.1316773110
   Aitken SN, 2013, ANNU REV ECOL EVOL S, V44, P367, DOI 10.1146/annurev-ecolsys-110512-135747
   Akerman A, 2014, J MATH BIOL, V68, P1135, DOI 10.1007/s00285-013-0660-z
   Alexa A., 2020, topGO: Enrichment Analysis for Gene Ontology
   Alexa A, 2006, BIOINFORMATICS, V22, P1600, DOI 10.1093/bioinformatics/btl140
   Alsos IG, 2012, P ROY SOC B-BIOL SCI, V279, P2042, DOI 10.1098/rspb.2011.2363
   Baeten L, 2015, PLANT ECOL EVOL, V148, P283, DOI 10.5091/plecevo.2015.1089
   Bauman D, 2018, ECOGRAPHY, V41, P1638, DOI 10.1111/ecog.03380
   Bauman D, 2018, ECOLOGY, V99, P2159, DOI 10.1002/ecy.2469
   Beaumont MA, 2004, MOL ECOL, V13, P969, DOI 10.1111/j.1365-294X.2004.02125.x
   Blanquart F, 2013, ECOL LETT, V16, P1195, DOI 10.1111/ele.12150
   BORCARD D, 1992, ECOLOGY, V73, P1045, DOI 10.2307/1940179
   Breed MF, 2018, BIOSCIENCE, V68, P510, DOI 10.1093/biosci/biy050
   Breed MF, 2013, CONSERV GENET, V14, P1, DOI 10.1007/s10592-012-0425-z
   Broadhurst LM, 2008, EVOL APPL, V1, P587, DOI 10.1111/j.1752-4571.2008.00045.x
   Bussotti F, 2015, ENVIRON EXP BOT, V111, P91, DOI 10.1016/j.envexpbot.2014.11.006
   Butchart SHM, 2010, SCIENCE, V328, P1164, DOI 10.1126/science.1187512
   Camon EB, 2005, BMC BIOINFORMATICS, V6, DOI 10.1186/1471-2105-6-S1-S17
   Capblancq T, 2020, ANNU REV ECOL EVOL S, V51, P245, DOI 10.1146/annurev-ecolsys-020720-042553
   Cingolani P, 2012, FLY, V6, P80, DOI 10.4161/fly.19695
   Copernicus Atmosphere Monitoring Service, 2020, MONTHL YEARL AV DIR
   Crusoe Michael R, 2015, F1000Res, V4, P900, DOI 10.12688/f1000research.6924.1
   Csilléry K, 2014, MOL ECOL, V23, P4696, DOI 10.1111/mec.12902
   De Frenne P, 2019, NAT ECOL EVOL, V3, P744, DOI 10.1038/s41559-019-0842-1
   De Frenne P, 2011, GLOBAL CHANGE BIOL, V17, P3240, DOI 10.1111/j.1365-2486.2011.02449.x
   De Kort H, 2020, J ECOL, V108, P1465, DOI 10.1111/1365-2745.13365
   Dray S, 2020, adespatial: multivariate multiscale spatial analysis Online
   Dray S, 2011, GEOGR ANAL, V43, P127, DOI 10.1111/j.1538-4632.2011.00811.x
   Dullinger S, 2015, DIVERS DISTRIB, V21, P1375, DOI 10.1111/ddi.12370
   European Environment Agency, 2021, GLOB EUR TEMP IND
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Fitzpatrick MC, 2021, MOL ECOL RESOUR, V21, P2749, DOI 10.1111/1755-0998.13374
   Fitzpatrick MC, 2015, ECOL LETT, V18, P1, DOI 10.1111/ele.12376
   Flynn DFB, 2018, NEW PHYTOL, V219, P1353, DOI 10.1111/nph.15232
   Foll M, 2008, GENETICS, V180, P977, DOI 10.1534/genetics.108.092221
   Frankham R, 2011, CONSERV BIOL, V25, P465, DOI 10.1111/j.1523-1739.2011.01662.x
   Franks SJ, 2014, EVOL APPL, V7, P123, DOI 10.1111/eva.12112
   Frichot E, 2015, METHODS ECOL EVOL, V6, P925, DOI 10.1111/2041-210X.12382
   Frichot E, 2014, GENETICS, V196, P973, DOI 10.1534/genetics.113.160572
   Garrido JL, 2012, PLANT ECOL, V213, P1555, DOI 10.1007/s11258-012-0111-8
   Garrison E., 2012, GENOMICS
   Gray SB, 2016, DEV BIOL, V419, P64, DOI 10.1016/j.ydbio.2016.07.023
   Grillakis MG, 2019, SCI TOTAL ENVIRON, V660, P1245, DOI 10.1016/j.scitotenv.2019.01.001
   Grossmann S, 2007, BIOINFORMATICS, V23, P3024, DOI 10.1093/bioinformatics/btm440
   Herrera CM, 2017, AM J BOT, V104, P1195, DOI 10.3732/ajb.1700162
   Hewitt GM, 1999, BIOL J LINN SOC, V68, P87, DOI 10.1111/j.1095-8312.1999.tb01160.x
   Hoban S, 2016, AM NAT, V188, P379, DOI 10.1086/688018
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   Holderegger R, 2006, LANDSCAPE ECOL, V21, P793, DOI 10.1007/s10980-005-6058-6
   Honnay O, 2002, ECOL LETT, V5, P525, DOI 10.1046/j.1461-0248.2002.00346.x
   Illumina, 2013, BCL2FASTQ
   Jia KH, 2020, EVOL APPL, V13, P665, DOI 10.1111/eva.12891
   Jones P, 2014, BIOINFORMATICS, V30, P1236, DOI 10.1093/bioinformatics/btu031
   Keller B, 2016, ECOL EVOL, V6, P6223, DOI 10.1002/ece3.2293
   Kubisch A, 2013, ECOGRAPHY, V36, P873, DOI 10.1111/j.1600-0587.2012.00062.x
   Láruson AJ, 2022, EVOL APPL, V15, P403, DOI 10.1111/eva.13354
   Lenth R., 2018, PACKAGE EMMEANS
   Leroy T, 2020, NEW PHYTOL, V226, P1171, DOI 10.1111/nph.16095
   Leuschner C., 2017, Ecology of central European forests
   Li H., 2013, GENOMICS, DOI [10.48550/arXiv.1303.3997, DOI 10.48550/ARXIV.1303.3997]
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Liu YC, 2013, BIOINFORMATICS, V29, P308, DOI [10.1093/bioinformatics/btt688, 10.1093/bioinformatics/bts690]
   López-Goldar X, 2021, TRENDS PLANT SCI, V26, P796, DOI 10.1016/j.tplants.2021.03.006
   Lotterhos KE, 2018, GENOME BIOL, V19, DOI 10.1186/s13059-018-1545-7
   Lotterhos KE, 2014, MOL ECOL, V23, P2178, DOI 10.1111/mec.12725
   Luu K, 2017, MOL ECOL RESOUR, V17, P67, DOI 10.1111/1755-0998.12592
   Mahony CR, 2020, EVOL APPL, V13, P116, DOI 10.1111/eva.12871
   Martins K, 2018, EVOL APPL, V11, P1842, DOI 10.1111/eva.12684
   Mastretta-Yanes A, 2015, MOL ECOL RESOUR, V15, P28, DOI 10.1111/1755-0998.12291
   Moore RD, 2005, J AM WATER RESOUR AS, V41, P813, DOI 10.1111/j.1752-1688.2005.tb04465.x
   Naaf T, 2021, LANDSCAPE ECOL, V36, P2831, DOI 10.1007/s10980-021-01292-w
   Norgen Biotek, 2015, PLANT FUNG DNA IS KI
   O'Leary SJ, 2018, MOL ECOL, V27, P3193, DOI 10.1111/mec.14792
   Oksanen J., 2013, Vegan: Community Ecology Package
   Orsini L, 2013, MOL ECOL, V22, P5983, DOI 10.1111/mec.12561
   Pluess AR, 2016, NEW PHYTOL, V210, P589, DOI 10.1111/nph.13809
   Poorter H, 2009, NEW PHYTOL, V182, P565, DOI 10.1111/j.1469-8137.2009.02830.x
   Qiagen, 2021, CLC GENOMICS WORKBEN
   Razgour O, 2019, P NATL ACAD SCI USA, V116, P10418, DOI 10.1073/pnas.1820663116
   Reich PB, 2003, INT J PLANT SCI, V164, pS143, DOI 10.1086/374368
   Rellstab C, 2017, HEREDITY, V118, P193, DOI 10.1038/hdy.2016.82
   Rellstab C, 2021, EVOL APPL, V14, P1202, DOI 10.1111/eva.13205
   Rellstab C, 2016, MOL ECOL, V25, P5907, DOI 10.1111/mec.13889
   Rothstein DE, 2001, FUNCT ECOL, V15, P722, DOI 10.1046/j.0269-8463.2001.00584.x
   Savolainen O, 2013, NAT REV GENET, V14, P807, DOI 10.1038/nrg3522
   Sommer RS, 2009, J BIOGEOGR, V36, P2013, DOI 10.1111/j.1365-2699.2009.02187.x
   Stanke M, 2008, BIOINFORMATICS, V24, P637, DOI 10.1093/bioinformatics/btn013
   Svenning JC, 2008, ECOGRAPHY, V31, P316, DOI 10.1111/j.0906-7590.2008.05206.x
   Taylor K, 2008, J ECOL, V96, P1098, DOI 10.1111/j.1365-2745.2008.01418.x
   Thiel D, 2014, EUR J FOREST RES, V133, P247, DOI 10.1007/s10342-013-0750-x
   Thuiller W, 2005, P NATL ACAD SCI USA, V102, P8245, DOI 10.1073/pnas.0409902102
   Van Daele F., 2022, DRYAD, DOI 10.5061/dryad.b5mkkwhg0
   Van Daele F, 2021, DIVERS DISTRIB, V27, P1775, DOI 10.1111/ddi.13367
   Van Rossum F, 2011, OECOLOGIA, V165, P663, DOI 10.1007/s00442-010-1745-7
   van Strien MJ, 2015, HEREDITY, V114, P27, DOI 10.1038/hdy.2014.62
   Vandepitte K, 2010, EVOL ECOL, V24, P1353, DOI 10.1007/s10682-010-9395-0
   Vanhove M, 2021, J EVOLUTION BIOL, V34, P910, DOI 10.1111/jeb.13765
   VanWallendael A, 2019, ANNU REV PLANT BIOL, V70, P559, DOI 10.1146/annurev-arplant-050718-100114
   Ver Hoef JM, 2018, ECOL MONOGR, V88, P36, DOI 10.1002/ecm.1283
   Vergeer P, 2004, CONSERV BIOL, V18, P812, DOI 10.1111/j.1523-1739.2004.00562.x
   Verheyen K, 2003, J ECOL, V91, P563, DOI 10.1046/j.1365-2745.2003.00789.x
   Vranken S, 2021, MOL ECOL, V30, P3730, DOI 10.1111/mec.15993
   Wadgymar SM, 2017, CONSERV BIOL, V31, P547, DOI 10.1111/cobi.12877
   Wessinger CA, 2018, MOL ECOL RESOUR, V18, P1402, DOI 10.1111/1755-0998.12930
   West-Eberhard Mary Jane, 2003, pi
   WHALE DM, 1983, OECOLOGIA, V58, P272, DOI 10.1007/BF00399231
   Wingler A, 2015, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00794
   Yamori W, 2014, PHOTOSYNTH RES, V119, P101, DOI 10.1007/s11120-013-9874-6
   Zellweger F, 2020, SCIENCE, V368, P772, DOI 10.1126/science.aba6880
   Zhang D, 2021, R SQUARED RELATED ME
NR 110
TC 4
Z9 5
U1 4
U2 26
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1752-4571
J9 EVOL APPL
JI Evol. Appl.
PD NOV
PY 2022
VL 15
IS 11
BP 1859
EP 1874
DI 10.1111/eva.13485
EA OCT 2022
PG 16
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA 6L5NN
UT WOS:000862910900001
PM 36426124
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU French, B
   Prior, LD
   Bowman, DMJS
AF French, Ben J.
   Prior, Lynda D.
   Bowman, David M. J. S.
TI Transplanting interventions could help conserve the living fossil
   <i>Athrotaxis cupressoides</i> under fire regimes induced by climate
   change
SO FRONTIERS IN CONSERVATION SCIENCE
LA English
DT Article
DE <italic>Athrotaxis</italic>; paleoendemic species; Gondwanan relict;
   climate change adaptation; active restoration; Tasmanian Central Plateau
ID D DON TAXODIACEAE; RAIN-FOREST; RESTORATION; REVEGETATION; REGENERATION;
   VEGETATION; ECOLOGY; PLANTS; RECRUITMENT; POPULATIONS
AB Introduction Pencil pine (Athrotaxis cupressoides) is an iconic, paleoendemic tree restricted to historic fire refugia in Tasmania's western mountains. Anthropogenic climate change is increasingly exposing these areas to wildfire. Given that pencil pines have little capacity to recover from fire, and show scarce natural recruitment across their core range, they will be lost from many areas without interventions to restore population viability to burnt stands.Methods We conducted a large-scale field study targeting pencil pine stands burnt in recent (2016) and historic (1960) fires. Using small (0.5 m2) experimental plots distributed across a range of topography and vegetation, we trialled three interventions: i) protecting groups of naturally germinated seedlings from herbivores in situ (35 plots); ii) introducing seeds via multiple sowing methods (300 plots); and iii) transplanting tube stock propagated from seed or cutting material, with and without herbivore protection (1007 plots).Results We found that protecting natural germinants from herbivores did not prevent seedling mortality over 2.5 years, and sowing interventions largely failed. Most transplants exposed to herbivores failed to establish after 1.5 years, but establishment rates were high with herbivore exclusion, indicating strong predation by native macropod herbivores. Transplant establishment also varied with fine-scale topography, with the best outcomes in well-drained and Sphagnum dominated positions, and the worst outcomes in poorly-drained positions, suggesting young pencil pines are sensitive to waterlogging. Transplant establishment rates varied little between recently and historically burnt sites, and were insensitive to how plants were propagated.Discussion In summary, transplanting tube stock with herbivore protection is a promising method for restoring burnt pencil pine stands, and establishment rates can be improved by selecting favourable planting positions at fine scales. Our findings suggest pencil pine stands burnt decades previously are suitable for restoration. Managers seeking to conserve pencil pines may begin restoring both historically and recently burnt stands, alongside protecting unburned stands from fire. Interventions should be refined through adaptive management, including re-surveys of this long-term trial.
C1 [French, Ben J.; Prior, Lynda D.; Bowman, David M. J. S.] Univ Tasmania, Fire Ctr, Hobart, Tas, Australia.
C3 University of Tasmania
RP French, B (corresponding author), Univ Tasmania, Fire Ctr, Hobart, Tas, Australia.
EM Ben.French@utas.edu.au
FU Department of Natural Resources and Environment Tasmania; Australian
   Government; Westpac Scholars Trust
FX The author(s) declare financial support was received for the research,
   authorship, and/or publication of this article. This project was funded
   by the Department of Natural Resources and Environment Tasmania, as part
   of the Lake Mackenzie Alpine Restoration Project. BF was supported by a
   Research Training Program (RTP) scholarship from the Australian
   Government and a Future Leaders Scholarship from the Westpac Scholars
   Trust.
CR Ashmore SE, 2011, IN VITRO CELL DEV-PL, V47, P99, DOI 10.1007/s11627-010-9320-9
   Ashton PMS, 1997, J APPL ECOL, V34, P915, DOI 10.2307/2405282
   Bailey TG, 2021, ECOL MANAG RESTOR, V22, P106, DOI 10.1111/emr.12498
   Bailey TG, 2021, ECOL MANAG RESTOR, V22, P92, DOI 10.1111/emr.12474
   Bailey TG, 2012, FOREST ECOL MANAG, V269, P229, DOI 10.1016/j.foreco.2011.12.021
   Banks M., 1972, Papers and Proceedings of the Royal Society of Tasmania, P55
   Bassett OD, 2015, FOREST ECOL MANAG, V342, P39, DOI 10.1016/j.foreco.2015.01.008
   Beltran RS, 2014, RESTOR ECOL, V22, P790, DOI 10.1111/rec.12144
   Bergstrom DM, 2021, GLOBAL CHANGE BIOL, V27, P1692, DOI 10.1111/gcb.15539
   Bliss A, 2021, AUST J BOT, V69, P162, DOI 10.1071/BT20117
   Bowman DMJS, 2022, FIRE-BASEL, V5, DOI 10.3390/fire5020033
   Bowman DMJS, 2021, ECOL STUD-ANAL SYNTH, V241, P133, DOI 10.1007/978-3-030-71330-0_6
   Bowman DMJS, 2019, AUSTRAL ECOL, V44, P1322, DOI 10.1111/aec.12789
   Bowman DMJS, 2017, RESTOR ECOL, V25, P674, DOI 10.1111/rec.12560
   Breed MF, 2018, BIOSCIENCE, V68, P510, DOI 10.1093/biosci/biy050
   Breed MF, 2013, CONSERV GENET, V14, P1, DOI 10.1007/s10592-012-0425-z
   Broadhurst L, 2017, ECOL MANAG RESTOR, V18, P205, DOI 10.1111/emr.12275
   Broadhurst LM, 2008, EVOL APPL, V1, P587, DOI 10.1111/j.1752-4571.2008.00045.x
   Bureau of Meteorology, 2022, Climate data online
   Cogoni D, 2013, ORYX, V47, P203, DOI 10.1017/S003060531200169X
   Cox AC, 2004, NAT AREA J, V24, P4
   Palma AC, 2015, APPL VEG SCI, V18, P561, DOI 10.1111/avsc.12173
   Cubit S., 1996, Aust. Geogr. Stud, V34, P216, DOI [10.1111/j.1467-8470.1996.tb00117.x, DOI 10.1111/J.1467-8470.1996.TB00117.X]
   CULLEN PJ, 1987, J BIOGEOGR, V14, P39, DOI 10.2307/2844785
   CULLEN PJ, 1988, AUST J BOT, V36, P547, DOI 10.1071/BT9880547
   CULLEN PJ, 1988, AUST J BOT, V36, P561, DOI 10.1071/BT9880561
   Dalrymple SE., 2012, PLANT REINTRODUCTION, P31, DOI [DOI 10.5822/978-1-61091-183-2_3, 10.5822/978-1-61091-183-2_3/FIGURES/3, DOI 10.5822/978-1-61091-183-2_3/FIGURES/3]
   De Steven D, 2006, RESTOR ECOL, V14, P452, DOI 10.1111/j.1526-100X.2006.00153.x
   Dodson JR, 2001, HOLOCENE, V11, P111, DOI 10.1191/095968301670253295
   Douterlungne D, 2015, RESTOR ECOL, V23, P861, DOI 10.1111/rec.12247
   Dunwiddie P. W., 1980, Australian Forestry, V43, P124
   Dunwiddie PW, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0150417
   Engelbrecht BMJ, 2003, OECOLOGIA, V136, P383, DOI 10.1007/s00442-003-1290-8
   Fletcher MS, 2018, QUATERNARY SCI REV, V182, P37, DOI 10.1016/j.quascirev.2017.12.023
   Gaitán-Espitia JD, 2021, GLOBAL CHANGE BIOL, V27, P475, DOI 10.1111/gcb.15359
   Godefroid S, 2011, BIOL CONSERV, V144, P672, DOI 10.1016/j.biocon.2010.10.003
   Grossnickle S C., 2017, Reforesta, V4, P94, DOI [10.21750/REFOR.4.07.46, DOI 10.21750/REFOR.4.07.46, 10.21750/refor.4.07.46]
   Hallett LM, 2014, ECOL MANAG RESTOR, V15, P140, DOI 10.1111/emr.12110
   Halsey SJ, 2017, ECOL RESTOR, V35, P52, DOI 10.3368/er.35.1.52
   Hannah L, 2008, ANN NY ACAD SCI, V1134, P201, DOI 10.1196/annals.1439.009
   Harris RMB, 2018, NAT CLIM CHANGE, V8, P579, DOI 10.1038/s41558-018-0187-9
   Heywood VH, 2019, PLANT DIVERSITY, V41, P36, DOI 10.1016/j.pld.2018.10.001
   Holl KD, 2011, FOREST ECOL MANAG, V261, P1558, DOI 10.1016/j.foreco.2010.07.004
   Holz A, 2015, GLOBAL CHANGE BIOL, V21, P445, DOI 10.1111/gcb.12674
   Ibanez T, 2020, APPL VEG SCI, V23, P197, DOI 10.1111/avsc.12478
   Jackson W., 1972, Papers Proc. R. Soc. Tasmania, P61, DOI [10.26749/rstpp.106.1.61, DOI 10.26749/RSTPP.106.1.61]
   Johnson K., 2002, Papers Proc. R. Soc. Tasmania, V136, P145, DOI [10.26749/SFCE4919, DOI 10.26749/SFCE4919, 10.26749/rstpp.136.145]
   Jordan GJ, 2016, GLOBAL ECOL BIOGEOGR, V25, P127, DOI 10.1111/geb.12389
   Jusaitis M., 2007, Australasian Plant Conservation: Journal of the Australian Network for Plant Conserv, V16, P23
   Keppel G, 2015, FRONT ECOL ENVIRON, V13, P106, DOI 10.1890/140055
   Keppel G, 2012, GLOBAL ECOL BIOGEOGR, V21, P393, DOI 10.1111/j.1466-8238.2011.00686.x
   Klaus VH, 2018, RESTOR ECOL, V26, pS114, DOI 10.1111/rec.12626
   Larkin Daniel, 2006, P142
   Li YY, 2012, BIOL CONSERV, V150, P1, DOI 10.1016/j.biocon.2012.02.020
   Linabury MC, 2019, RESTOR ECOL, V27, P1300, DOI 10.1111/rec.13004
   Lorite J, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-95739-4
   Mariani M, 2019, GLOBAL CHANGE BIOL, V25, P2030, DOI 10.1111/gcb.14609
   Marquis B, 2021, NEW FOREST, V52, P1079, DOI 10.1007/s11056-021-09840-7
   Marris E, 2016, NATURE, V530, P137, DOI 10.1038/nature.2016.19308
   Menges Eric S., 2016, Plant Diversity, V38, P238, DOI 10.1016/j.pld.2016.09.004
   Miandrimanana C, 2019, PLANT DIVERSITY, V41, P118, DOI 10.1016/j.pld.2018.09.005
   Mortlock BW., 2000, Ecol Manag Restor, V1, P93, DOI DOI 10.1046/J.1442-8903.2000.00029.X
   Morton A., 2016, Like losing the thylacine': fire burns Tasmanian wilderness world heritage area
   Muñoz-Rojas M, 2016, SOIL-GERMANY, V2, P287, DOI 10.5194/soil-2-287-2016
   Nilar H, 2019, FOREST ECOL MANAG, V435, P18, DOI 10.1016/j.foreco.2018.12.041
   Ogden J., 1978, Tree-Ring Bulletin, V38, P1
   Overdyck E, 2013, RESTOR ECOL, V21, P763, DOI 10.1111/j.1526-100X.2012.00933.x
   Padilla FM, 2006, FRONT ECOL ENVIRON, V4, P196, DOI 10.1890/1540-9295(2006)004[0196:TRONPI]2.0.CO;2
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Porfirio LL, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0113749
   Prior L., 2023, TWWHA Bushfire Recovery Lake Mackenzie Sphagnum and Pencil Pine Rehabilitation Trials Final Report
   Prior LD, 2020, FIRE-BASEL, V3, DOI 10.3390/fire3020015
   Prior LD, 2018, AUST J BOT, V66, P511, DOI 10.1071/BT18124
   Prober SM, 2019, ECOL MONOGR, V89, DOI 10.1002/ecm.1333
   Prober SM, 2015, FRONT ECOL EVOL, V3, DOI 10.3389/fevo.2015.00065
   Pyke DA, 2010, RESTOR ECOL, V18, P274, DOI 10.1111/j.1526-100X.2010.00658.x
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Raulings Elisa J., 2007, Wetlands Ecology and Management, V15, P175, DOI 10.1007/s11273-006-9022-6
   RAY GJ, 1995, RESTOR ECOL, V3, P86, DOI 10.1111/j.1526-100X.1995.tb00081.x
   READ J, 1989, Papers and Proceedings of the Royal Society of Tasmania, V123, P211
   Richards SA, 2008, J APPL ECOL, V45, P218, DOI 10.1111/j.1365-2664.2007.01377.x
   SAKAI A, 1981, ECOLOGY, V62, P563, DOI 10.2307/1937722
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Siles G, 2010, ACTA OECOL, V36, P357, DOI 10.1016/j.actao.2010.03.002
   Styger J, 2018, FIRE-BASEL, V1, DOI 10.3390/fire1030038
   The IUCN Red List of Threatened Species, 2023, Pencil Pine
   Tongway David J., 1994, Pacific Conservation Biology, V1, P201
   Volis S, 2019, PLANT DIVERSITY, V41, P50, DOI 10.1016/j.pld.2019.01.002
   Wahlquist C., 2020, The Guardian
   Wang TL, 2010, ECOL APPL, V20, P153, DOI 10.1890/08-2257.1
   Whinam J., 1994, Papers and Proceedings of the Royal Society of Tasmania, V128, P63
   Worth JRP, 2016, SCI REP-UK, V6, DOI 10.1038/srep33930
   Zahawi RA, 2014, RESTOR ECOL, V22, P284, DOI 10.1111/rec.12098
   Zahawi RA, 2009, RESTOR ECOL, V17, P854, DOI 10.1111/j.1526-100X.2008.00423.x
NR 94
TC 0
Z9 0
U1 1
U2 1
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2673-611X
J9 FRONT CONSERV SCI
JI Front. Conserv. Sci.
PD NOV 28
PY 2024
VL 5
AR 1491062
DI 10.3389/fcosc.2024.1491062
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Emerging Sources Citation Index (ESCI)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA P0S6W
UT WOS:001375121400001
OA gold
DA 2025-01-10
ER

PT J
AU Usman, M
   Ali, A
   Bashir, MK
   Radulescu, M
   Mushtaq, K
   Wudil, AH
   Baig, SA
   Akram, R
AF Usman, Muhammad
   Ali, Asghar
   Bashir, Muhammad Khalid
   Radulescu, Magdalena
   Mushtaq, Khalid
   Wudil, Abdulazeez Hudu
   Baig, Sajjad Ahmad
   Akram, Rimsha
TI Do farmers' risk perception, adaptation strategies, and their
   determinants benefit towards climate change? Implications for
   agriculture sector of Punjab, Pakistan
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE Climate change; Perceived impacts; Adaptation strategies; Determinants;
   Benefits; Pakistan
ID SMALLHOLDER FARMERS; CHANGE IMPACTS; FOOD SECURITY; PRODUCTIVITY;
   INCOME; LEVEL; VULNERABILITY; PERSPECTIVES; COMMUNITIES; VARIABILITY
AB Due to global and regional climatic dynamics for a couple of decades, agricultural productivity, rural livelihood, and food security have been badly affected in Pakistan. This study was conducted in Punjab, Pakistan, to explore the farmers' understanding of the impacts of climate change, adaptation strategies, determinants, and benefits on agriculture using data from 1080 respondents. Perceived risks by the farmers in the rice-wheat cropping system and the cotton-wheat cropping system were weed infestation, seed rate augmented, low-quality seeds, infestation of crop diseases and pests, change of cropping pattern, increase of input use, decrease of cropping intensity and productivity, decreasing soil fertility, increasing irrigation frequency, and increase of harvesting time. To alleviate the adverse influences of climate change, the adaptation strategies used by farmers were management of crop and variety, soil and irrigation water, diversification of agriculture production systems and livelihood sources, management of fertilizer and farm operations time, spatial adaptation, access to risk reduction measures and financial assets, adoption of new technologies, institutional support, and indigenous knowledge. Moreover, the results of Binary Logistic Regression indicate that adaptation strategies are affected by different factors like age, education, household family size, off-farm income, remittances, credit access, information on climatic and natural hazards, information on weather forecasting, land acreage, the experience of growing crops and rearing of livestock, tenancy status, tube well ownership, livestock inventory, access to market information, agricultural extension services, and distance from agricultural input/output market. There is a significant difference between adapters and nonadapters. The risk management system may be created to protect crops against failures caused by extreme weather events. There is a need to develop crop varieties that are both high yielding and resistant to climate change. Moreover, cropping patterns should be revised to combat the effects of climate change. To enhance farmers' standard of living, it is necessary to provide adequate extension services and a more significant number of investment facilities. These measures will assist farmers in maintaining their standard of living and food security over the long term to adapt to the effects of climate change based on various cropping zones.
C1 [Usman, Muhammad; Ali, Asghar; Bashir, Muhammad Khalid; Mushtaq, Khalid; Wudil, Abdulazeez Hudu] Univ Agr Faisalabad, Inst Agr & Resource Econ, Faisalabad, Pakistan.
   [Radulescu, Magdalena] Univ Pitesti, Dept Finance Accounting & Econ, Pitesti, Romania.
   [Radulescu, Magdalena] Univ Lucian Blaga, Inst Doctoral & Postdoctoral Studies, Bd Victoriei 10, Sibiu 550024, Romania.
   [Baig, Sajjad Ahmad] Natl Text Univ, Faisalabad Business Sch, Faisalabad, Pakistan.
   [Akram, Rimsha] Univ Agr Faisalabad, Dept Bot, Faisalabad, Pakistan.
C3 University of Agriculture Faisalabad; National University of Science &
   Technology POLITEHNICA Bucharest; University of Pitesti; Lucian Blaga
   University of Sibiu; National Textile University - Pakistan; University
   of Agriculture Faisalabad
RP Ali, A (corresponding author), Univ Agr Faisalabad, Inst Agr & Resource Econ, Faisalabad, Pakistan.
EM usmanghani99@hotmail.com; asghar.ali@uaf.edu.pk; Khalid450@uaf.edu.pk;
   magdalena.radulescu@upit.ro; khalidmushtaq@uaf.edu.pk;
   azeezhud4real@gmail.com; sajjad.baig@hotmail.com;
   rimshausman99@hotmail.com
RI baig, sajjad/X-8065-2018; Bashir, Muhammad Khalid/H-9729-2014
OI , Dr. Asghar Ali/0009-0003-0750-3807
CR Abbas G, 2017, AGR FOREST METEOROL, V247, P42, DOI 10.1016/j.agrformet.2017.07.012
   Abid M, 2015, EARTH SYST DYNAM, V6, P225, DOI 10.5194/esd-6-225-2015
   Abid M, 2020, CLIM RISK MANAG, V27, DOI 10.1016/j.crm.2019.100200
   Abid M, 2017, CLIMATE, V5, DOI 10.3390/cli5040085
   Abid M, 2016, J RURAL STUD, V47, P254, DOI 10.1016/j.jrurstud.2016.08.005
   Abid M, 2016, SCI TOTAL ENVIRON, V547, P447, DOI 10.1016/j.scitotenv.2015.11.125
   Acquah H. de G., 2011, AGRIS On-line Papers in Economics and Informatics, P31
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P75, DOI 10.1016/j.gloenvcha.2005.03.001
   Ahmad D, 2020, ENVIRON SCI POLLUT R, V27, P15375, DOI 10.1007/s11356-020-08057-z
   Ahmad M., 2014, Impact of climate change on wheat productivity in Pakistan: A district level analysis, DOI 10.13140/2.1.1192.0167
   Ahmed MN, 2011, BUS ECON HORIZ, V4, P1
   Ahmed MN, 2015, INT J GLOBAL WARM, V8, P231, DOI 10.1504/IJGW.2015.071954
   Alam GMM, 2016, ECOL ECON, V130, P243, DOI 10.1016/j.ecolecon.2016.07.012
   Alauddin M, 2014, ECOL ECON, V106, P204, DOI 10.1016/j.ecolecon.2014.07.025
   Alemayehu A, 2017, ENVIRON DEV, V24, P77, DOI 10.1016/j.envdev.2017.06.006
   Alhassan H, 2020, HELIYON, V6, DOI 10.1016/j.heliyon.2020.e04167
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Ali MF, 2021, ENVIRON SCI POLLUT R, V28, P14844, DOI 10.1007/s11356-020-11472-x
   Ali S, 2021, J CLEAN PROD, V291, DOI 10.1016/j.jclepro.2020.125250
   Ali S, 2017, FOODS, V6, DOI 10.3390/foods6060039
   Amare ZY., 2018, AGR FOOD SECUR, V7, P1, DOI [10.1186/s40066-018-0188-y, DOI 10.1186/S40066-018-0188-Y]
   Amir S, 2020, ARAB J GEOSCI, V13, DOI 10.1007/s12517-020-06019-w
   Anjum S.A., 2012, Pak J Sci, V64, P138
   [Anonymous], 2013, MESSESTANDORT BASEL
   [Anonymous], 2018, J Ecosyst Ecography, DOI [DOI 10.4172/2157-7625.1000251, 10.4172/2157-7625.251]
   Anser MK, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17072522
   Arshad M, 2017, INT J SUST DEV WORLD, V24, P532, DOI 10.1080/13504509.2016.1254689
   Aryal JP, 2020, ENVIRON DEV SUSTAIN, V22, P5045, DOI 10.1007/s10668-019-00414-4
   Aslam AQ, 2017, SCI TOTAL ENVIRON, V580, P468, DOI 10.1016/j.scitotenv.2016.11.155
   Atta-ur-Rahman, 2011, NAT HAZARDS, V59, P1239, DOI 10.1007/s11069-011-9830-8
   Rahut DB, 2017, INT J DISAST RISK RE, V24, P515, DOI 10.1016/j.ijdrr.2017.05.006
   Baig A., 2014, PAKISTAN BUS REV, V15, P600
   Bakhsh K, 2019, INT J COMMONS, V13, P833, DOI 10.5334/ijc.887
   Bate BG, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11071921
   Belaineh L., 2013, Asian Journal of Empirical Research, V3, P251
   Belay Abrham., 2017, Agriculture Food Security, V6, P24, DOI [10.1186/s40066-017-0100-1, DOI 10.1186/S40066-017-0100-1]
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Croppenstedt A., 2003, Review of Development Economics, V7, P58, DOI [DOI 10.1111/1467-9361.00175, 10.1111/1467-9361.00175]
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Deressa TT., 2010, FACTORS AFFECTING CH, P1032
   Dumenu WK, 2016, ENVIRON SCI POLICY, V55, P208, DOI 10.1016/j.envsci.2015.10.010
   Elahi E., 2015, International Journal of Agriculture Innovations and Research, V3, P1470
   Elahi E, 2022, TECHNOVATION, V117, DOI 10.1016/j.technovation.2021.102255
   Fadina AMR, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5010015
   FAO, 2004, FERT US CROP PAK
   Farooqi A., 2005, Pakistan J. Meteorol, V2, P11
   Fernihough A, 2011, UCD CTR EC RES WORKI, VWP11/22
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fosu-Mensah B. Y., 2012, Environment Development and Sustainability, V14, P495, DOI 10.1007/s10668-012-9339-7
   Ghazali EM, 2020, IND MANAGE DATA SYST, V120, P2319, DOI 10.1108/IMDS-10-2019-0576
   Gorst A, 2015, 189 GRANTH RES I
   Gorst A, 2018, ENVIRON DEV ECON, V23, P679, DOI 10.1017/S1355770X18000232
   Government of Pakistan, 2021, PAKISTAN EC SURVEY 2
   Gul Farhana, 2019, Sarhad Journal of Agriculture, V35, P442, DOI 10.17582/journal.sja/2019/35.2.442.448
   Haider S, 2021, ASIA-PAC J ATMOS SCI, V57, P757, DOI 10.1007/s13143-021-00231-8
   Hair J. F., 2010, Multivariate data analysis
   Hanif U., 2010, The Pakistan Development Review, P771, DOI DOI 10.30541/V49I4IIPP.771-798
   Henseler J, 2016, IND MANAGE DATA SYST, V116, P2, DOI 10.1108/IMDS-09-2015-0382
   Hosmer DW., 1989, Applied Logistic Regression
   Hussain A, 2016, FOOD SECUR, V8, P921, DOI 10.1007/s12571-016-0607-5
   Hussain M, 2018, J CLEAN PROD, V200, P791, DOI 10.1016/j.jclepro.2018.07.272
   Iheke OR, 2016, SCI PAP-SER MANAG EC, V16, P213
   Imran M, 2020, ENVIRON DEV SUSTAIN, V22, P2121, DOI 10.1007/s10668-018-0280-2
   IPCC CC., 2014, SYNTHESIS REPORT, P151
   Iqbal MA, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12239895
   Javed SA., 2015, PERCEPTIONS ADAPTATI
   Kassie M, 2013, TECHNOL FORECAST SOC, V80, P525, DOI 10.1016/j.techfore.2012.08.007
   Kato E, 2011, AGR ECON-BLACKWELL, V42, P593, DOI 10.1111/j.1574-0862.2011.00539.x
   Kayani AS, 2018, J ANIM PLANT SCI, V28, P584
   Khan AA, 2022, ENVIRON SCI POLLUT R, V29, P7352, DOI 10.1007/s11356-021-16179-1
   Khan I, 2021, ENVIRON SCI POLLUT R, V28, P29720, DOI 10.1007/s11356-021-12801-4
   Khan I, 2020, LAND USE POLICY, V91, DOI 10.1016/j.landusepol.2019.104395
   Khan I, 2019, ENVIRON SCI POLLUT R, V26, P33076, DOI 10.1007/s11356-019-06448-5
   Khan MA, 2018, 30 INT C AGR EC VANC
   Khan NA, 2021, ENVIRON SCI POLLUT R, V28, P4229, DOI 10.1007/s11356-020-10758-4
   Khan NA, 2020, ENVIRON SCI POLLUT R, V27, P20292, DOI 10.1007/s11356-020-08341-y
   Khatri-Chhetri A, 2017, AGR SYST, V151, P184, DOI 10.1016/j.agsy.2016.10.005
   Kurukulasuriya P., 2007, RICARDIAN ANAL IMPAC, DOI [10.1596/1813-9450-4305, DOI 10.1596/1813-9450-4305]
   Lohmoller J., 1989, Latent variable path modeling with partial least squares
   Mabe FN, 2014, DETERMINANTS CHOICE
   Maddison DavidJ., 2007, PERCEPTION ADAPTATIO, DOI 10.1596/1813-9450-4308
   Masud MM, 2017, J CLEAN PROD, V156, P698, DOI 10.1016/j.jclepro.2017.04.060
   Mateos-Aparicio G, 2011, COMMUN STAT-THEOR M, V40, P2305, DOI 10.1080/03610921003778225
   Memon M.A., 2020, J APPL STRUCTURAL EQ, V4, P1, DOI [DOI 10.47263/JASEM.4(2)01, 10.47263/jasem.4(2)01, 10.47263/JASEM.4, DOI 10.47263/JASEM.4]
   Mertz O, 2009, ENVIRON MANAGE, V43, P804, DOI 10.1007/s00267-008-9197-0
   Moyo M., 2012, African Crop Science Journal, V20, P317
   Mulwa C, 2017, CLIM RISK MANAG, V16, P208, DOI 10.1016/j.crm.2017.01.002
   Myeni L, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11113003
   Nabikolo D., 2012, African Crop Science Journal, V20, P203
   Nazir A, 2018, J ANIM PLANT SCI-PAK, V28, P1163
   Ndamani F, 2016, SCI AGR, V73, P201
   Nhemachena C., 2007, INT FOOD POLICY RES
   Niles MT, 2015, AGR ECOSYST ENVIRON, V200, P178, DOI 10.1016/j.agee.2014.11.010
   Norris P. E., 1987, Southern Journal of Agricultural Economics, V19, P79
   Pakistan bureau of statistics government of pakistan, 2020, CROPS COUNT DAT
   Parry M., 2009, ASSESSING COSTS ADAP
   Peng CYJ, 2002, J EDUC RES, V96, P3, DOI 10.1080/00220670209598786
   PMD, 2020, ABOUT US
   PMD, 2017, CLIM CHANG SCEN DAT
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Rahman MHU, 2018, AGR FOREST METEOROL, V253, P94, DOI 10.1016/j.agrformet.2018.02.008
   Sarstedt M., 2011, Schmalenbach Business Review, V63, P34
   Savo V, 2016, NAT CLIM CHANGE, V6, P462, DOI [10.1038/NCLIMATE2958, 10.1038/nclimate2958]
   Schilling J, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01597-7
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   Seo SN, 2008, ECOL ECON, V67, P109, DOI 10.1016/j.ecolecon.2007.12.007
   Seo SN, 2009, ENVIRON RESOUR ECON, V43, P313, DOI 10.1007/s10640-009-9270-z
   Shaffril HAM, 2018, SCI TOTAL ENVIRON, V644, P683, DOI 10.1016/j.scitotenv.2018.06.349
   Shahid F., 2021, PAKISTAN SOC SCI REV, V5, P223, DOI DOI 10.35484/PSSR.2021(5-II)18
   Shahzad M. F., 2019, 2019 AGR APPL EC ASS
   Shahzad MF, 2020, AGR SYST, V180, DOI 10.1016/j.agsy.2019.102772
   Sheikh M. J., 2019, Pakistan Journal of Agriculture, Agricultural Engineering, Veterinary Sciences, V35, P113
   Siddiqui R., 2012, Pakistan Development Review, V4, DOI [10.30541/v51i4iipp.261-276, DOI 10.30541/V51I4IIPP.261-276]
   Stephenson B., 2008, Binary response and logistic regression analysis
   Stocker, 2014, CLIMATE CHANGE 2013
   Tessema YA., 2013, Agricultural and Food Economics, V1, P1, DOI [10.1186/2193-7532-1-13, DOI 10.1186/2193-7532-1-13]
   Thapa S, 2021, CLIM DEV, V13, P713, DOI 10.1080/17565529.2020.1855099
   Ullah W., 2016, International Journal of Environmental Protection and Policy, V4, P126, DOI [10.11648/j.ijepp.20160405.13, DOI 10.11648/J.IJEPP.20160405.13]
   Wang J, 2018, CLIMATE, V6, DOI 10.3390/cli6020041
   Ward PJ, 2013, ENVIRON POLIT, V22, P518, DOI 10.1080/09644016.2012.683155
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   Weber EU, 2016, WIRES CLIM CHANGE, V7, P125, DOI 10.1002/wcc.377
   Wetende E, 2018, ENVIRON DEV, V27, P14, DOI 10.1016/j.envdev.2018.08.001
   WOLD H, 1974, EUR ECON REV, V5, P67, DOI 10.1016/0014-2921(74)90008-7
   Wold H., 1982, Systems under indirect observations: causality, structure, prediction, part 2, P1
   Wold HOA., 1985, PARTIAL LEAST SQUARE, P220
   Yamane T., 1967, Statistics: An introductory analysis, V2nd ed
   Zahid KB, 2018, J Econ Lib, V5, P85
NR 128
TC 9
Z9 10
U1 3
U2 18
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0944-1344
EI 1614-7499
J9 ENVIRON SCI POLLUT R
JI Environ. Sci. Pollut. Res.
PD JUL
PY 2023
VL 30
IS 33
BP 79861
EP 79882
DI 10.1007/s11356-023-27759-8
EA JUN 2023
PG 22
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA L5XE7
UT WOS:001004546200011
PM 37291341
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Sinha, A
   Basu, D
   Priyadarshi, P
   Ghosh, A
   Sohane, RK
AF Sinha, Aditya
   Basu, Debabrata
   Priyadarshi, Prashant
   Ghosh, Amitava
   Sohane, Ravindra Kumar
TI Farm Typology for Targeting Extension Interventions Among Smallholders
   in Tribal Villages in Jharkhand State of India
SO FRONTIERS IN ENVIRONMENTAL SCIENCE
LA English
DT Article
DE farm typology; extension; tribal; smallholders; classification
ID CLIMATE-CHANGE ADAPTATION; FOOD SECURITY; SYSTEMS; MANAGEMENT; POLICY;
   AGRICULTURE; DIVERSITY; DIVERSIFICATION; HETEROGENEITY; AGROFORESTRY
AB The highly heterogeneous and complex farm holdings operated by the smallholders in developing countries are often deprived of optimum production and profitability. The farming systems in the state of Jharkhand, India, are heterogeneous due to biophysical (e.g., climatic conditions, fertilizer status, elevation, etc.) and socio-economic (investment potential, production goals, income preferences) factors. The extension interventions to reach the smallholders often face the one-size-fits-all approach making farming less attractive with diminished potential. There is a need to understand the diversity of the farms to classify them into different homogenous groups after studying the nature and characteristics of the farm and operators on the farms. In the current study, twenty-one different variables related to socio-economic,biophysical and geospatial features of the farms from 394 farm households were used for the analysis using Principal Component Analysis to identify six principal components explaining 73.07% of the total variability in the dataset. The first six factors were further analyzed using Euclidean Distance as distance measure and Ward's technique as agglomerative clustering to form four clusters that were found to represent the farm households in the three villages. The four farm types identified were, Type 1. Large farm household with a diversification of crops and intensification of labour (22%), Type 2. Small farm households with major income from livestock (9%), Type 3. Small farm households with diversified cropping system and income from other sources (17%), and Type 4. Small farm households with monocropping dominated by senior farmers with an additional source of income (51%). The validation of the clusters was undertaken through qualitative methods such as focused group discussions and participatory workshops. The findings back up previous research that showed a positive association between farmer categorization and mathematical classification. The study offers a verifiable scientific methodology that could help scale agricultural technologies by forming a specific cluster of farmers based on their characteristics. The technologies applied to various farm types would be helpful to the extension system to target the interventions among the precise members of the identified farm types. Thus, the study suggests the farming system typology based on socio-economic, biophysical and geospatial factors for targeted farming systems interventions among smallholders.
C1 [Sinha, Aditya] Bihar Agr Univ, Dept Extens Educ, Bhagalpur, India.
   [Basu, Debabrata] Bidhan Chandra Krishi Viswavidyalaya, Dept Agr Extens, Nadia, India.
   [Priyadarshi, Prashant] Natl Inst Technol, Dept Comp Sci & Engn, Patna, India.
   [Ghosh, Amitava] Cent Agr Univ Imphal, Coll Fisheries, Dept Extens & Social Sci, Agartala, India.
   [Sohane, Ravindra Kumar] Bihar Agr Univ, Director Extens Educ, Bhagalpur, India.
C3 Bidhan Chandra Agricultural University; National Institute of Technology
   (NIT System); National Institute of Technology Patna
RP Sinha, A (corresponding author), Bihar Agr Univ, Dept Extens Educ, Bhagalpur, India.
EM inc.aditya@gmail.com
RI Sinha, Aditya/AFC-2629-2022; Priyadarshi, Prashant/HNB-3817-2023
OI Priyadarshi, Prashant/0000-0002-8205-1383; Sinha,
   Aditya/0000-0002-5193-9048; SOHANE, RAVINDRA KUMAR/0000-0002-3522-0703
CR Adu-Baffour F, 2019, FOOD POLICY, V84, P133, DOI 10.1016/j.foodpol.2019.03.007
   Amadu FO, 2020, WORLD DEV, V126, DOI 10.1016/j.worlddev.2019.104692
   Amare D, 2019, SMALL-SCALE FOR, V18, P39, DOI 10.1007/s11842-018-9405-6
   Anderzén J, 2020, J RURAL STUD, V77, P33, DOI 10.1016/j.jrurstud.2020.04.001
   [Anonymous], 1987, MULTIVARIATE DATA AN
   Antony AP, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093750
   Anugwa IQ, 2022, CLIM POLICY, V22, P112, DOI 10.1080/14693062.2021.1953435
   Anyimah FO, 2021, Environ Challenges, V4, DOI [10.1016/j.envc.2021.100087, DOI 10.1016/J.ENVC.2021.100087]
   Bhuvan Geoportal of ISRO, 2019, IND SPAC RES ORG BHU
   Bisht IS, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093751
   Bozeman B, 2000, RES POLICY, V29, P627, DOI 10.1016/S0048-7333(99)00093-1
   Brooks K, 2018, AGREKON, V57, P181, DOI 10.1080/03031853.2018.1538002
   Chatterjee S, 2015, J AGR SCI TECH-IRAN, V17, P1127
   Corp I.M, 2016, IBM SPSS STAT
   Courault D, 2020, IEEE J-STARS, V13, P5027, DOI 10.1109/JSTARS.2020.3018881
   D'Aquino P, 2003, JASSS-J ARTIF SOC S, V6
   Daskalopoulou I, 2002, J RURAL STUD, V18, P95, DOI 10.1016/S0743-0167(01)00027-4
   Dray S, 2007, J STAT SOFTW, V22, P1, DOI 10.18637/jss.v022.i04
   Elahi E., 2021, TECHNOVATION, P102255, DOI [10.1016/j.technovation.2021.102255, DOI 10.1016/J.TECHNOVATION.2021.102255]
   Elahi E, 2021, LAND USE POLICY, V102, DOI 10.1016/j.landusepol.2020.105250
   Escobar N., 2019, TYPOLOGY SMALL PRODU
   Fernandez-Cornejo J., 2005, Journal of Agricultural and Applied Economics, V37, P549
   Flenniken J.M., 2020, QUANTUM GIS QGIS INT, P7
   Gebauer R. H., 1987, European Review of Agricultural Economics, V14, P261, DOI 10.1093/erae/14.3.261
   Geological Survey (U.S.) and EROS Data Center, 2019, EARTHEXPLORER
   Gorton M, 2008, J RURAL STUD, V24, P322, DOI 10.1016/j.jrurstud.2007.10.001
   Goswami R., 2014, Agricultural and Food Economics, V2, P5, DOI [DOI 10.1186/S40100-014-0005-2, 10.1186/s40100-014-0005-2]
   Guèye EF, 2002, WORLD POULTRY SCI J, V58, P541, DOI 10.1079/WPS20020039
   Gupta R, 2020, EASJEHL, V3, P548, DOI [10.36349/easjehl.2020.v03i12.001, DOI 10.36349/EASJEHL.2020.V03I12.001]
   Gyau A, 2015, AGROFOREST SYST, V89, P149, DOI 10.1007/s10457-014-9750-1
   Hameleers M, 2018, INT J COMMUN-US, V12, P2171
   Hammond J, 2020, AGR SYST, V183, DOI 10.1016/j.agsy.2020.102857
   Head E, 2009, INT J SOC RES METHOD, V12, P335, DOI 10.1080/13645570802246724
   Innazent A, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-021-04148-0
   Ioki K, 2019, J NAT CONSERV, V52, DOI 10.1016/j.jnc.2019.125740
   Jolliffe IT, 2016, PHILOS T R SOC A, V374, DOI 10.1098/rsta.2015.0202
   Kadiyala S, 2018, TRIALS, V19, DOI 10.1186/s13063-018-2521-y
   Kansiime MK, 2021, FOOD ENERGY SECUR, V10, DOI 10.1002/fes3.254
   Kapalanga T.S., 2008, A review of land degradation assessment methods, VVolume 2011, P68
   Kaur J, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-00372-w
   Kessler JJ, 1998, LAND DEGRAD DEV, V9, P95, DOI 10.1002/(SICI)1099-145X(199803/04)9:2<95::AID-LDR289>3.0.CO;2-Y
   Kilwinger F, 2021, OUTLOOK AGR, V50, P441, DOI 10.1177/00307270211045408
   Kmoch L, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103719
   Köbrich C, 2003, AGR SYST, V76, P141, DOI 10.1016/S0308-521X(02)00013-6
   Krueger RA, 2014, Focus Groups: A Practical Guide for Applied Research
   Kuivanen KS, 2016, NJAS-WAGEN J LIFE SC, V78, P153, DOI 10.1016/j.njas.2016.04.003
   Kuivanen KS, 2016, J RURAL STUD, V45, P184, DOI 10.1016/j.jrurstud.2016.03.015
   Kuria AW, 2019, GEODERMA REG, V16, DOI 10.1016/j.geodrs.2018.e00199
   Le Ngoc H., 2018, International Association of Agricultural Economists, DOI [10.22004/ag.econ.277409, DOI 10.22004/AG.ECON.277409]
   Lopez-Ridaura S, 2018, AGR SYST, V159, P57, DOI 10.1016/j.agsy.2017.09.007
   Mariyono J., 2018, International Journal of Vegetable Science, V24, P274, DOI 10.1080/19315260.2017.1413698
   McDonald CK, 2019, AGR SYST, V176, DOI 10.1016/j.agsy.2019.102659
   Mujeyi A, 2022, CLIM DEV, V14, P399, DOI 10.1080/17565529.2021.1930507
   Murgue C, 2015, LAND USE POLICY, V45, P52, DOI 10.1016/j.landusepol.2015.01.011
   Musafiri CM, 2020, SCI AFR, V8, DOI 10.1016/j.sciaf.2020.e00458
   Mwai D., 2016, Public Health Res, V6, P83, DOI DOI 10.5923/J.PHR.20160603.02
   Nyambo Devotha G, 2019, ScientificWorldJournal, V2019, P6121467, DOI 10.1155/2019/6121467
   Paula CJM, 2005, J ECONOMETRICS, V126, P525, DOI 10.1016/j.jeconom.2004.05.012
   Priegnitz U, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00068
   Priyadarshini P, 2020, LAND USE POLICY, V96, DOI 10.1016/j.landusepol.2020.104718
   Rahman S, 2018, AGRICULTURE-BASEL, V8, DOI 10.3390/agriculture8010012
   Righi E, 2011, AGR ECOSYST ENVIRON, V142, P63, DOI 10.1016/j.agee.2010.07.011
   Ritchie J., 2013, Qualitative research practice: A guide for social science students and researchers
   Robert M, 2017, WATER-SUI, V9, DOI 10.3390/w9010051
   Ruben R, 2004, FOOD POLICY, V29, P303, DOI 10.1016/j.foodpol.2004.07.004
   Sankalpa JKS, 2021, J RUBBER RES, V24, P719, DOI 10.1007/s42464-021-00127-2
   Sarker MR, 2021, FOOD ENERGY SECUR, V10, DOI 10.1002/fes3.287
   Scoones I., 2009, FARMER 1 REVISITED
   Sharma N. K., 2020, J REMOTE SENSING GIS, V11, P1
   Shukla R, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-56931-9
   Siddique MNEA, 2022, GEODERMA REG, V28, DOI 10.1016/j.geodrs.2021.e00460
   Sinha A, 2022, NATL ACAD SCI LETT, V45, P1, DOI 10.1007/s40009-021-01071-w
   Som S., 2018, J COMMUNITY MOBILIZ, V13, P385
   Sutherland LA, 2011, LANDSCAPE URBAN PLAN, V100, P1, DOI 10.1016/j.landurbplan.2010.10.005
   Tavenner K, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00010
   Thar SP, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11060516
   Tittonell P, 2007, AGR SYST, V94, P376, DOI 10.1016/j.agsy.2006.10.012
   Toorop RA, 2020, EUR J AGRON, V121, DOI 10.1016/j.eja.2020.126157
   Villarreal E.A.Z., 2020, TROP SUBTROPICAL AGR, V23, P1
   Zhang JY, 2021, SCI TOTAL ENVIRON, V760, DOI 10.1016/j.scitotenv.2020.143326
   Zoma-Traoré B, 2020, TROP ANIM HEALTH PRO, V52, P2179, DOI 10.1007/s11250-020-02241-6
NR 81
TC 11
Z9 12
U1 0
U2 9
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-665X
J9 FRONT ENV SCI-SWITZ
JI Front. Environ. Sci.
PD MAR 18
PY 2022
VL 10
AR 823338
DI 10.3389/fenvs.2022.823338
PG 18
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 0Z9JM
UT WOS:000791385700001
OA gold
DA 2025-01-10
ER

PT J
AU Yoshimoto, M
   Fukuoka, M
   Tsujimoto, Y
   Matsui, T
   Kobayasi, K
   Saito, K
   van Oort, PAJ
   Inusah, BIY
   Vijayalakshmi, C
   Vijayalakshmi, D
   Weerakoon, WMW
   Silva, LC
   Myint, TT
   Phyo, ZC
   Tian, XH
   Lur, HS
   Yang, CM
   Tarpley, L
   Manigbas, NL
   Hasegawa, T
AF Yoshimoto, Mayumi
   Fukuoka, Minehiko
   Tsujimoto, Yasuhiro
   Matsui, Tsutomu
   Kobayasi, Kazuhiro
   Saito, Kazuki
   van Oort, Pepijn A. J.
   Inusah, Baba I. Y.
   Vijayalakshmi, Chenniappan
   Vijayalakshmi, Dhashnamurthi
   Weerakoon, W. M. W.
   Silva, L. C.
   Myint, Tin Tin
   Phyo, Zar Chi
   Tian, Xiaohai
   Lur, Huu-Sheng
   Yang, Chwen-Ming
   Tarpley, Lee
   Manigbas, Norvie L.
   Hasegawa, Toshihiro
TI Monitoring canopy micrometeorology in diverse climates to improve the
   prediction of heat-induced spikelet sterility in rice under climate
   change
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Canopy microclimate; Evaporative cooling; Heat-induced spikelet
   sterility; Oasis effect; Oryza sativa L.; Panicle temperature
ID TEMPERATURE-INDUCED STERILITY; MORNING FLOWERING TRAIT; PHENOTYPIC
   PLASTICITY; ORYZA-OFFICINALIS; WILD-RICE; STRESS; SIMULATION; TIME;
   DIFFERENCE; FERTILITY
AB Rice is well adapted to a wide range of climates, but is highly susceptible to heat during flowering. However, there are uncertainties in assessing the occurrence of heat-induced spikelet sterility (HISS) and the impact of climate change. One reason is the gap between the ambient air temperature and the panicle temperature, which determines the magnitude of HISS in field studies. To improve our understanding of this gap, we established a multi-site monitoring network (MINCERnet) to measure canopy micrometeorology and heat stress in the major rice growing regions (Sub-Saharan Africa; South, Southeast, and East Asia; and the USA). MINCERnet assessed the processes that determine panicle temperature and the resulting HISS in open fields using the same cultivars ('IR64', 'N22', and 'IR52') and a standard system (MINCER) for micrometeorological monitoring under diverse climates. By using the MINCERnet data in the canopy heat-balance model (IM(2)PACT), we confirmed that the canopy and panicle transpiration and the resulting evaporative cooling strongly affected the gap between the ambient air temperature and the panicle temperature, and that the HISS rate in open fields could be predicted accurately in diverse climates by using the mean panicle temperature during the flowering hours. The "oasis effect" in the broad sense, that is, evaporative cooling and the increase of relative humidity, which is nested at the various levels along the continuum from the landscape to the panicle, formed temperature and relative humidity gradients along the continuum in response to different climatic conditions.
   The heat-balance characteristics (i.e., a stronger evaporative cooling under drier climate conditions) suggested that the risk of HISS caused by global warming will increase more in wetter climates, where panicle temperatures tended to increase. Thus, accurate relative humidity data as well as air temperature will be required, along with spatial downscaling, to permit accurate prediction of rice heat stress and yield. HISS prediction using an approach based on the panicle temperature as input for models and monitoring of canopy micrometeorology will reduce uncertainties in rice yield prediction and the response of yield to various climate change adaptation measures.
C1 [Yoshimoto, Mayumi; Fukuoka, Minehiko; Hasegawa, Toshihiro] Natl Agr & Food Res Org, Inst Agroenvironm Sci, 3-1-3 Kannondai, Tsukuba, Ibaraki 3058604, Japan.
   [Tsujimoto, Yasuhiro] Japan Int Res Ctr Agr Sci, 1-1 Ohwashi, Tsukuba, Ibaraki 3058686, Japan.
   [Matsui, Tsutomu] Gifu Univ, Fac Appl Biol Sci, 1-1 Yanagido, Gifu 5011193, Japan.
   [Kobayasi, Kazuhiro] Shimane Univ, Fac Life & Environm Sci, 1060 Nishikawatsu Thou, Matsue, Shimane 6908504, Japan.
   [Saito, Kazuki] Africa Rice Ctr AfricaRice, 01 BP 2551, Bouake 01, Cote Ivoire.
   [van Oort, Pepijn A. J.] Wageningen Plant Res WPR, Business Unit Agrosyst Res, POB 16, NL-6700 AA Wageningen, Netherlands.
   [Inusah, Baba I. Y.] CSIR, Savanna Agr Res Inst, POB 52, Tamale, Ghana.
   [Vijayalakshmi, Chenniappan; Vijayalakshmi, Dhashnamurthi] Tamil Nadu Agr Univ, Dept Crop Physiol, Coimbatore 641003, Tamil Nadu, India.
   [Weerakoon, W. M. W.] Dept Agr, Batalagoda, Ibbagamuwa, Sri Lanka.
   [Silva, L. C.] Rice Res & Dev Inst, Dept Agr, Batalagoda, Ibbagamuwa, Sri Lanka.
   [Myint, Tin Tin; Phyo, Zar Chi] Dept Agr Res, Rice & Other Cereal Crops Div, Yezin, Nay Pyi Taw, Myanmar.
   [Tian, Xiaohai] Yangtze Univ, Fac Agr, Jingzhou 434025, Hubei, Peoples R China.
   [Lur, Huu-Sheng] Natl Taiwan Univ, Dept Agron, Taipei 10616, Taiwan.
   [Yang, Chwen-Ming] Agr Res Inst Taiwan, Crop Sci Div, Taichung 41362, Taiwan.
   [Tarpley, Lee] Texas A&M AgriLife Res Ctr, Beaumont, TX 77713 USA.
   [Manigbas, Norvie L.] Philippine Rice Res Inst, Plant Breeding & Biotechnol Div, Science City Of Munoz, Nueva Ecija, Philippines.
C3 National Agriculture & Food Research Organization - Japan; Japan
   International Research Center for Agricultural Sciences; Gifu
   University; Shimane University; CGIAR; Africa Rice Center; Wageningen
   University & Research; Tamil Nadu Agricultural University; Yangtze
   University; National Taiwan University; Agricultural Research Institute
   of Taiwan; Philippine Rice Research Institute
RP Yoshimoto, M (corresponding author), Natl Agr & Food Res Org, Inst Agroenvironm Sci, 3-1-3 Kannondai, Tsukuba, Ibaraki 3058604, Japan.
EM yoshimot@affrc.go.jp
RI Manigbas, Norvie/HKE-9157-2023; tian, xiaohai/R-8717-2019; 辻本,
   泰弘/AAU-1459-2020; Hasegawa, Toshihiro/H-8211-2019
OI Hasegawa, Toshihiro/0000-0001-8501-5612
FU Global Environmental Research Coordination System from Ministry of the
   Environment of Japan [MAFF1531, MAFF1842]; Japan Society for the
   Promotion of Science KAKENHI [JP15H02650]
FX Our research was financially supported by the Global Environmental
   Research Coordination System from Ministry of the Environment of Japan
   (MAFF1531 and MAFF1842), and by a Japan Society for the Promotion of
   Science KAKENHI Grant Number JP15H02650.
CR Berger S., CLIMATE CHANGE 2021
   Bouman B.A.M., 2001, ORYZA2000 MODELLING
   Fukuoka M, 2012, PLANT PROD SCI, V15, P258, DOI 10.1626/pps.15.258
   Fukuoka Minehiko, 2012, Journal of Agricultural Meteorology, V68, P135, DOI 10.2480/agrmet.68.2.1
   Hasegawa Toshihiro, 2011, Journal of Agricultural Meteorology, V67, P225, DOI 10.2480/agrmet.67.4.3
   Hayase H., 1969, JPN J CROP SCI, V38, P706, DOI [10.1626/jcs.38.706, DOI 10.1626/JCS.38.706]
   Hirabayashi H, 2015, J EXP BOT, V66, P1227, DOI 10.1093/jxb/eru474
   Horie T., 1993, Journal of Agricultural Meteorology, V48, P567, DOI [10.2480/agrmet.48.567, DOI 10.2480/AGRMET.48.567, 10.2480/ agrmet.48.567.]
   Horie T, 2019, P JPN ACAD B-PHYS, V95, P211, DOI 10.2183/pjab.95.016
   IPCC, 2021, Masson-Delmotte, P195
   Ishimaru T, 2010, ANN BOT-LONDON, V106, P515, DOI 10.1093/aob/mcq124
   Jagadish SVK, 2007, J EXP BOT, V58, P1627, DOI 10.1093/jxb/erm003
   Jagadish SVK, 2010, J EXP BOT, V61, P143, DOI 10.1093/jxb/erp289
   Julia C, 2013, EUR J AGRON, V49, P50, DOI 10.1016/j.eja.2013.03.006
   Julia C, 2012, EUR J AGRON, V43, P166, DOI 10.1016/j.eja.2012.06.007
   Khan S, 2019, PLANTS-BASEL, V8, DOI 10.3390/plants8110508
   Kobata T, 2010, PLANT PROD SCI, V13, P289, DOI 10.1626/pps.13.289
   Kobayasi K, 2010, PLANT PROD SCI, V13, P21, DOI 10.1626/pps.13.21
   Kumar U, 2017, FIELD CROP RES, V202, P94, DOI 10.1016/j.fcr.2016.04.037
   Kumar U, 2016, FIELD CROP RES, V193, P164, DOI 10.1016/j.fcr.2016.04.036
   Kuwagata T, 2014, SOLA, V10, P45, DOI 10.2151/sola.2014-010
   Lubis I, 2003, PLANT PROD SCI, V6, P119, DOI 10.1626/pps.6.119
   MACKILL DJ, 1982, CROP SCI, V22, P730, DOI 10.2135/cropsci1982.0011183X002200040008x
   Maruyama A, 2013, J AGRON CROP SCI, V199, P416, DOI 10.1111/jac.12028
   Matsui T, 1999, ANN BOT-LONDON, V84, P501, DOI 10.1006/anbo.1999.0943
   Matsui T, 2001, PLANT PROD SCI, V4, P90, DOI 10.1626/pps.4.90
   Matsui T, 2007, PLANT PROD SCI, V10, P57, DOI 10.1626/pps.10.57
   Matsui T, 2014, PLANT PROD SCI, V17, P245, DOI 10.1626/pps.17.245
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Prasad PVV, 2006, FIELD CROP RES, V95, P398, DOI 10.1016/j.fcr.2005.04.008
   SATAKE T, 1978, JPN J CROP SCI, V47, P6, DOI 10.1626/jcs.47.6
   Satake T., 1980, J AGRIC METEOROL, V35, P251, DOI [10.2480/agrmet.35.251, DOI 10.2480/AGRMET.35.251]
   Tian XH, 2010, PLANT PROD SCI, V13, P243, DOI 10.1626/pps.13.243
   van Oort PAJ, 2021, FIELD CROP RES, V263, DOI 10.1016/j.fcr.2021.108074
   van Oort PAJ, 2014, FIELD CROP RES, V156, P303, DOI 10.1016/j.fcr.2013.11.007
   van Oort PAJ, 2018, GLOBAL CHANGE BIOL, V24, P1029, DOI 10.1111/gcb.13967
   van Oort PAJ, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118114
   Webber H, 2016, ENVIRON MODELL SOFTW, V77, P143, DOI 10.1016/j.envsoft.2015.12.003
   Weerakoon WMW, 2008, J AGRON CROP SCI, V194, P135, DOI 10.1111/j.1439-037X.2008.00293.x
   Yoshida H, 2010, FIELD CROP RES, V117, P122, DOI 10.1016/j.fcr.2010.02.007
   Yoshida S., 1981, Fundamentals of rice crop science.
   Yoshimoto M, 2005, AGR FOREST METEOROL, V133, P226, DOI 10.1016/j.agrformet.2005.09.010
   Yoshimoto M., 2005, J. Agric. Meteorol., V60, P597, DOI [10.2480/agrmet.597, DOI 10.2480/AGRMET.597]
   Yoshimoto Mayumi, 2012, Journal of Agricultural Meteorology, V68, P149, DOI 10.2480/agrmet.68.2.2
   Yoshimoto Mayumi, 2011, Journal of Agricultural Meteorology, V67, P233, DOI 10.2480/agrmet.67.4.8
NR 45
TC 12
Z9 12
U1 7
U2 29
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0168-1923
EI 1873-2240
J9 AGR FOREST METEOROL
JI Agric. For. Meteorol.
PD APR 1
PY 2022
VL 316
AR 108860
DI 10.1016/j.agrformet.2022.108860
EA FEB 2022
PG 19
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA 2S6KQ
UT WOS:000821899400001
DA 2025-01-10
ER

PT J
AU Autio, A
   Johansson, T
   Motaroki, L
   Minoia, P
   Pellikka, P
AF Autio, Antti
   Johansson, Tino
   Motaroki, Lilian
   Minoia, Paola
   Pellikka, Petri
TI Constraints for adopting climate-smart agricultural practices among
   smallholder farmers in Southeast Kenya
SO AGRICULTURAL SYSTEMS
LA English
DT Article
DE Agriculture; Smallholder; Climate smart; Adaptation; Gender; Kenya
ID ADAPTATION; FRAMEWORK; LESSONS; LAND; RESILIENCE; STRATEGIES; SOIL
AB CONTEXT: Climate uncertainty challenges the livelihoods of smallholder farmers in sub-Saharan Africa. Awareness of climate-smart agricultural (CSA) practices and access to climate-smart technologies are key factors in determining the utilization of farm and land management practices that may simultaneously decrease greenhouse gas emissions, increase the adaptive capacity of farmers, and improve food security. OBJECTIVE: Understanding how biophysical and socio-economic constraints affect the adoption of CSA practices and technologies plays an essential role in policy and intervention planning. Our objective was to identify these constraints among smallholder farmers in Taita Taveta County of Southeast Kenya across varying agro-ecological zones. METHODS: We conducted a Climate-Smart Agriculture Rapid Appraisal that consisted of four mostly genderdisaggregated smallholder farmer workshops (102 participants), a household survey (65 participants), key informant interviews (16 informants), and four transect walks. RESULTS AND CONCLUSIONS: Our results indicate a dissonance in the perceived awareness of CSA practices and utilization of CSA technologies between state actors and farmers. State actors emphasize lack of awareness as a barrier to adoption, while farmers express knowledgeability regarding environmental change and climate-smart practices but are confined by limitations and restrictions posed by e.g. market mechanisms, land tenure issues,and lack of resources. These restrictions include e.g. uncertainty in product prices, lack of land ownership, scarcity of arable land, and simply lack of capital or willingness to invest. Farmers are further challenged by the emergence of new pests and human-wildlife conflicts. Our research findings are based on the contextual settings of Taita Taveta County, but the results indicate that adopting CSA practices and utilizing technologies, especially in sub-Saharan regions that are heavily based on subsistence agriculture with heterogenous agro-ecological zones, require localized and gender-responsive solutions in policy formation and planning of both agricultural extension services and development interventions that take into account the agency of the farmers. SIGNIFICANCE: This study contributes to existing climate change adaptation research by increasing our un- derstanding of how physical and socio-economic constraints can affect the adoption of new farm and land management practices, and how CSA-based intervention strategies could be restructured by local stakeholders to be more inclusive.
C1 [Autio, Antti; Johansson, Tino; Pellikka, Petri] Univ Helsinki, Dept Geosci & Geog, Gustaf Hallstromin Katu 2, FI-00014 Helsinki, Finland.
   [Motaroki, Lilian] African Ctr Technol Studies ACTS, POB 45917, Nairobi 00100, Kenya.
   [Minoia, Paola] Univ Helsinki, Global Dev Studies, Unioninkatu 35, FI-00014 Helsinki, Finland.
   [Motaroki, Lilian] Int Inst Environm & Dev IIED, 1 Bomughloch Sq, Edinburgh EH8 9NJ, Midlothian, Scotland.
C3 University of Helsinki; University of Helsinki
RP Autio, A (corresponding author), Univ Helsinki, Dept Geosci & Geog, Gustaf Hallstromin Katu 2, FI-00014 Helsinki, Finland.
EM antti.j.autio@helsinki.fi
RI ; Minoia, Paola/AAF-9215-2020
OI Pellikka, Petri/0000-0002-5996-9268; Minoia, Paola/0000-0003-0760-5785;
   Johansson, Tino Petri/0000-0002-2381-5144; Autio,
   Antti/0000-0002-2054-4940
FU Academy of Finland [318645]
FX This research is part of the SMARTLAND-project (Environmental sensing of
   ecosystem services for developing climate-smart landscape framework to
   improve food security in East Africa) , funded by the Academy of Finland
   (grant no. 318645) . The funding source had no further involvement in
   conducting the research or in preparing the article. Besides the funding
   instrument, the research team acknowledges Taita Taveta University for
   collaboration, the County Government of Taita Taveta and its agencies
   for co-operation, the Natural Museum of Kenya and the National
   Commission for Science, Technology and Innovation (NACOSTI) of Kenya for
   the research permit (no. P/18/97336/26355) , and Taita Research Station
   of the University of Helsinki for facilitating the research. Fieldwork
   by Mwadime Mjomba, Darius Kimuzi, Emmah Owidi, and Elizabeth Mbinga is
   gratefully acknowl-edged. We thank Dr. Janne Heiskanen and Dr. Mika
   Siljander for assis-tance with the satellite imagery and the language
   revision services at the University of Helsinki for the proof reading of
   the manuscript. Thecorresponding author is also grateful for advice from
   Dr. Matti Radsadnen and Sheila Wachiye in the research work.
CR Abegunde VO, 2019, CLIMATE, V7, DOI 10.3390/cli7110132
   Amare A., 2017, Agric. Food Secur, V6, P64, DOI DOI 10.1186/S40066-017-0144-2
   Andrieu N, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00037
   Aryal JP, 2018, NAT RESOUR FORUM, V42, P141, DOI 10.1111/1477-8947.12152
   Belay Abrham., 2017, Agriculture Food Security, V6, P24, DOI [10.1186/s40066-017-0100-1, DOI 10.1186/S40066-017-0100-1]
   Bindoff N. L., 2019, IPCC SPECIAL REPORT, P447
   Boitt M., 2014, Geosciences J, V2, P172, DOI [10.13189/ujg.2014.020602, DOI 10.13189/UJG.2014.020602]
   Brandt P, 2017, AGR SYST, V151, P234, DOI 10.1016/j.agsy.2015.12.011
   Capitani C, 2019, SUSTAIN SCI, V14, P191, DOI 10.1007/s11625-018-0622-x
   Chaudhury AS, 2016, MITIG ADAPT STRAT GL, V21, P301, DOI 10.1007/s11027-014-9600-5
   Clay N, 2019, WORLD DEV, V116, P1, DOI 10.1016/j.worlddev.2018.11.022
   County Government of Taita Taveta, 2018, COUNT GOV TAIT TAV I
   De Groote H, 2020, AGR ECOSYST ENVIRON, V292, DOI 10.1016/j.agee.2019.106804
   De Pinto A, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0231764
   Dhanya P, 2016, J INTEGR ENVIRON SCI, V13, P1, DOI 10.1080/1943815X.2015.1062031
   Elum ZA, 2017, CLIM RISK MANAG, V16, P246, DOI 10.1016/j.crm.2016.11.001
   Eshetu G, 2021, CLIM DEV, V13, P318, DOI 10.1080/17565529.2020.1772706
   FAO, 2014, SUCC STOR CLIM SMART
   FAO, 2017, Climate smart agriculture sourcebook, V2
   FAO and Care, 2019, GOOD PRACT INT GEND
   Ge M., 2020, 4 charts explain greenhouse gas emissions by countries and sectors
   Hohenthal J, 2018, J POLIT ECOL, V25, P1
   Hohenthal J, 2017, PROF GEOGR, V69, P383, DOI 10.1080/00330124.2016.1237294
   Holden ST, 2018, LAND USE POLICY, V76, P113, DOI 10.1016/j.landusepol.2018.04.048
   Holt Lucy., 2013, Climate-smart agriculture success stories from farming communities around the world
   Jaetzold R., 2012, FARM MANAGEMENT HDB, VII, P46
   Kenya National Bureau of Statistics, 2018, KEN INT HOUS BUDG SU
   Kenya National Bureau of Statistics, 2019 KEN POP HOUS CE, VII
   Kenya National Bureau of Statistics, 2019, 2019 KEN POP HOUS CE, VI
   Khatri-Chhetri A, 2020, CLIMATIC CHANGE, V158, P29, DOI 10.1007/s10584-018-2350-8
   Kirui V., 2018, J. Small Bus. Enterp. Dev, V6, P59, DOI [https://doi.org/10.15640/jsbed.v5n2a6, 10.15640/jsbed.v5n2a6, DOI 10.15640/JSBED.V5N2A6]
   Klytchnikova IrinaI., 2015, Future of food: shaping a climate-smart global food system (English)
   Kpadonou RAB, 2017, LAND USE POLICY, V61, P196, DOI 10.1016/j.landusepol.2016.10.050
   Lan L, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0207700
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Little J, 2002, PROG HUM GEOG, V26, P665, DOI 10.1191/0309132502ph394pr
   MacGregor S., 2010, J INDIAN OCEAN REG, V6, P223, DOI [DOI 10.1080/19480881.2010.536669, 10.1080/19480881.2010.536669]
   Maeda EE, 2011, J ENVIRON MANAGE, V92, P982, DOI 10.1016/j.jenvman.2010.11.005
   Maeda EE, 2010, GEOMORPHOLOGY, V123, P279, DOI 10.1016/j.geomorph.2010.07.019
   Makate C, 2019, J ENVIRON MANAGE, V231, P858, DOI 10.1016/j.jenvman.2018.10.069
   MoALF, 2016, CLIM RISK PROF TAIT
   Mwongera C., 2015, Climate-smart agriculture rapid appraisal (CSA-RA): A prioritization tool for outscaling CSA
   Mwongera C, 2017, AGR SYST, V151, P192, DOI 10.1016/j.agsy.2016.05.009
   Notenbaert A, 2017, AGR SYST, V151, P153, DOI 10.1016/j.agsy.2016.05.017
   Ogallo L., 2019, Report on historical climate baseline statistics for Taita Taveta, V1
   Pellikka P.K., 2013, DEV EARTH SURFACE PR
   Pellikka PKE, 2018, APPL GEOGR, V94, P178, DOI 10.1016/j.apgeog.2018.03.017
   Ravera F, 2016, AMBIO, V45, pS235, DOI 10.1007/s13280-016-0842-1
   Saj S, 2017, AGR ECOSYST ENVIRON, V250, P20, DOI 10.1016/j.agee.2017.09.003
   Taylor M, 2018, J PEASANT STUD, V45, P89, DOI 10.1080/03066150.2017.1312355
   Thornton PK, 2018, AGR SYST, V167, P161, DOI 10.1016/j.agsy.2018.09.009
   Thurston Anne., 1987, SMALLHOLDER AGR COLO
   Tsige M, 2020, SCI AFR, V7, DOI 10.1016/j.sciaf.2019.e00250
   Wachiye S, 2020, BIOGEOSCIENCES, V17, P2149, DOI 10.5194/bg-17-2149-2020
   Waswa F, 2002, J AGR TROP SUBTROP, V103, P107
   Wekesa B. M., 2018, Agriculture & Food Security, V7, P80, DOI 10.1186/s40066-018-0230-0
   Wiebe K, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/085010
   World Bank Group FAO IFAD, 2015, GEND CLIM SMART AGR
NR 58
TC 53
Z9 54
U1 9
U2 60
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0308-521X
EI 1873-2267
J9 AGR SYST
JI Agric. Syst.
PD DEC
PY 2021
VL 194
AR 103284
DI 10.1016/j.agsy.2021.103284
EA OCT 2021
PG 13
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture
GA WG4OV
UT WOS:000706975200002
OA hybrid
DA 2025-01-10
ER

PT J
AU Frank, A
   Sperisen, C
   Howe, GT
   Brang, P
   Walthert, L
   St Clair, JB
   Heiri, C
AF Frank, Aline
   Sperisen, Christoph
   Howe, Glenn Thomas
   Brang, Peter
   Walthert, Lorenz
   St Clair, John Bradley
   Heiri, Caroline
TI Distinct genecological patterns in seedlings of Norway spruce and silver
   fir from a mountainous landscape
SO ECOLOGY
LA English
DT Article
DE Abies alba; adaptive genetic variation; Central Europe; climate change;
   common garden; conifers; evolutionary adaptation; genecology;
   phenotype-environment associations; Picea abies; quantitative genetics;
   soils
ID FOREST GENETIC-RESOURCES; CLIMATE-CHANGE; PICEA-ABIES; DOUGLAS-FIR;
   CONIFEROUS FORESTS; ADAPTIVE RESPONSES; LOCAL ADAPTATION; EUROPEAN
   FORESTS; SEED TRANSFER; GROWTH
AB Understanding the genecology of forest trees is critical for gene conservation, for predicting the effects of climate change and climate change adaptation, and for successful reforestation. Although common genecological patterns have emerged, species-specific details are also important. Which species are most vulnerable to climate change? Which are the most important adaptive traits and environmental drivers of natural selection? Even though species have been classified as adaptive specialists vs. adaptive generalists, large-scale studies comparing different species in the same experiment are rare. We studied the genecology of Norway spruce (Picea abies) and silver fir (Abies alba), two co-occurring but ecologically distinct European conifers in Central Europe. For each species, we collected seed from more than 90 populations across Switzerland, established a seedling common-garden test, and developed genecological models that associate population variation in seedling growth and phenology to climate, soil properties, and site water balance. Population differentiation and associations between seedling traits and environmental variables were much stronger for Norway spruce than for silver fir, and stronger for seedling height growth than for bud phenology. In Norway spruce, height growth and second flushing were strongly associated with temperature and elevation, with seedlings from the lowlands being taller and more prone to second flush than seedlings from the Alps. In silver fir, height growth was more weakly associated with temperature and elevation, but also associated with water availability. Soil characteristics explained little population variation in both species. We conclude that Norway spruce has become an adaptive specialist because trade-offs between rapid juvenile growth and frost avoidance have subjected it to strong diversifying natural selection based on temperature. In contrast, because silver fir has a more conservative growth habit, it has evolved to become an adaptive generalist. This study demonstrates that co-occurring tree species can develop very different adaptive strategies under identical environmental conditions, and suggests that Norway spruce might be more vulnerable to future maladaptation due to rapid climate change than silver fir.
C1 [Frank, Aline; Sperisen, Christoph; Brang, Peter; Walthert, Lorenz; Heiri, Caroline] Swiss Fed Inst Forest Snow & Landscape Res, WSL, CH-8903 Birmensdorf, Switzerland.
   [Sperisen, Christoph] Oregon State Univ, Dept Forest Ecosyst & Soc, 321 Richardson Hall, Corvallis, OR 97331 USA.
   [St Clair, John Bradley] US Forest Serv, Pacific Northwest Res Stn, USDA, 3200 SW Jefferson Way, Corvallis, OR 97331 USA.
C3 Swiss Federal Institutes of Technology Domain; Swiss Federal Institute
   for Forest, Snow & Landscape Research; Oregon State University; United
   States Department of Agriculture (USDA); United States Forest Service
RP Frank, A (corresponding author), Swiss Fed Inst Forest Snow & Landscape Res, WSL, CH-8903 Birmensdorf, Switzerland.
EM aline.frank@alumni.ethz.ch
RI Heiri, Caroline/S-5836-2016; Brang, Peter/C-8238-2009; Sperisen,
   Christoph/S-1383-2019
OI Frank, Aline/0000-0001-7008-3866; Sperisen,
   Christoph/0000-0003-1241-5636
FU research program "Forests and Climate Change" of FOEN; WSL
FX The authors thank the large team of field workers for seed harvest, soil
   profile analyses, chemical analyses of soil characteristics, plantation
   of seedlings, trait assessments, and site maintenance. A special thank
   goes to A. Burkart and his team of gardeners at WSL for support during
   seed harvest, seedling management, and common garden procedures. The
   authors further thank G. Schneiter, P. Jakob and P. Waldner for
   technical support, and D. Steiner and B. Buttler for providing the
   experimental site at Brunnersberg and their helping hands. In addition,
   the authors are grateful for the statistical advice provided by J.
   Wunder (WSL), J. Zell (WSL), A.R. Pluess (WSL), and M. Tanadini
   (statistic consulting ETH Zurich). Thanks also to the Swiss Long-term
   Forest Ecosystem Research Programme (LWF) for providing soil data of one
   seed source. This work was funded by the research program "Forests and
   Climate Change" of FOEN and WSL.
CR Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   Aitken SN, 2013, ANNU REV ECOL EVOL S, V44, P367, DOI 10.1146/annurev-ecolsys-110512-135747
   Aitken SN, 2001, TREE PHYSIOL SER, V1, P23
   Alberto FJ, 2013, GLOBAL CHANGE BIOL, V19, P1645, DOI 10.1111/gcb.12181
   Alfaro RI, 2014, FOREST ECOL MANAG, V333, P76, DOI 10.1016/j.foreco.2014.04.006
   [Anonymous], 1993, P IUFRO S2 2 11 S LA
   [Anonymous], SWISS NAT FOR INV NF
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Beaulieu J, 2004, CAN J FOREST RES, V34, P531, DOI 10.1139/X03-224
   Blanquart F, 2013, ECOL LETT, V16, P1195, DOI 10.1111/ele.12150
   Boisbunon A, 2014, INT STAT REV, V82, P422, DOI 10.1111/insr.12052
   Bossel F., 1983, Schweizerische Zeitschrift fur Forstwesen, V134, P339
   Bower AD, 2008, AM J BOT, V95, P66, DOI 10.3732/ajb.95.1.66
   Bräutigam K, 2013, ECOL EVOL, V3, P399, DOI 10.1002/ece3.461
   Brandli U.-B., 1998, BER EIDG FORSCH ANST, V342, P279
   Burley J., 2004, Encyclopedia of forest sciences, P197, DOI DOI 10.1016/B0-12-145160-7/00086-7
   Bussotti F, 2015, ENVIRON EXP BOT, V111, P91, DOI 10.1016/j.envexpbot.2014.11.006
   CAMPBELL RK, 1991, FOREST SCI, V37, P973
   Chen J, 2012, GENETICS, V191, P865, DOI 10.1534/genetics.112.140749
   Chmura DJ, 2006, NEW FOREST, V32, P21, DOI 10.1007/s11056-005-3390-2
   Clapham D, 2001, TREE PHYSIOL SER, V1, P187
   Cline MG, 2007, CAN J FOREST RES, V37, P74, DOI 10.1139/X06-218
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   Dolnicki A., 2003, Acta Agraria et Silvestria. Series Silvestris, V41, P3
   Ellenberg H., 2009, VEGETATION ECOLOGY C, P191
   Emerson J.D., 1983, Understanding robust and exploratory data analysis, P58
   Engler A, 1905, MITT SCHWEIZ ANST FO, V8, P81
   FAIRBAIRN WA, 1970, FORESTRY, V43, P57, DOI 10.1093/forestry/43.1.57
   Finkeldey Reiner, 2000, Forest Snow and Landscape Research, V75, P137
   Fouvy P., 1997, Schweizerische Zeitschrift fur Forstwesen, V148, P103
   Frampton J, 2013, TREE GENET GENOMES, V9, P53, DOI 10.1007/s11295-012-0529-0
   GILMOUR AR, 1985, BIOMETRIKA, V72, P593, DOI 10.1093/biomet/72.3.593
   Gonseth Y., 2001, Die biogeographischen Regionen der Schweiz. Erlauterungen und Einteilungsstandard, Umwelt-Materialien
   Grassi G, 2001, TREE PHYSIOL, V21, P959, DOI 10.1093/treephys/21.12-13.959
   Green DS, 2005, CAN J FOREST RES, V35, P910, DOI [10.1139/x05-015, 10.1139/X05-015]
   GRIER CC, 1977, ECOLOGY, V58, P893, DOI 10.2307/1936225
   Hannerz M, 1999, CAN J FOREST RES, V29, P768, DOI 10.1139/cjfr-29-6-768
   Herzog M., 1990, Schweizerische Zeitschrift fur Forstwesen, V141, P989
   HOULE D, 1992, GENETICS, V130, P195
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Huguenin-Landl, 2014, KLIMADATEN WALDMODEL
   Kapeller S, 2012, FOREST ECOL MANAG, V271, P46, DOI 10.1016/j.foreco.2012.01.039
   King GM, 2013, OECOLOGIA, V173, P1587, DOI 10.1007/s00442-013-2696-6
   Kramer K, 2014, FOREST ECOL MANAG, V331, P116, DOI 10.1016/j.foreco.2014.08.002
   Kremer A, 2012, ECOL LETT, V15, P378, DOI 10.1111/j.1461-0248.2012.01746.x
   LAGERCRANTZ U, 1990, EVOLUTION, V44, P38, DOI [10.2307/2409523, 10.1111/j.1558-5646.1990.tb04278.x]
   LARSEN JB, 1991, SILVAE GENET, V40, P188
   Lebourgeois F, 2010, J VEG SCI, V21, P364, DOI 10.1111/j.1654-1103.2009.01148.x
   Leinonen T, 2008, J EVOLUTION BIOL, V21, P1, DOI 10.1111/j.1420-9101.2007.01445.x
   Lenormand T, 2002, TRENDS ECOL EVOL, V17, P183, DOI 10.1016/S0169-5347(02)02497-7
   Lesser MR, 2004, CAN J FOREST RES, V34, P1119, DOI [10.1139/x03-286, 10.1139/X03-286]
   Lindner M, 2014, J ENVIRON MANAGE, V146, P69, DOI 10.1016/j.jenvman.2014.07.030
   MALLOWS CL, 1973, TECHNOMETRICS, V15, P661, DOI 10.2307/1267380
   Matyas C, 1996, EUPHYTICA, V92, P45, DOI 10.1007/BF00022827
   McKay JK, 2002, TRENDS ECOL EVOL, V17, P285, DOI 10.1016/S0169-5347(02)02478-3
   Motta R, 2003, FOREST ECOL MANAG, V181, P139, DOI 10.1016/S0378-1127(03)00128-2
   Nicotra AB, 2010, TRENDS PLANT SCI, V15, P684, DOI 10.1016/j.tplants.2010.09.008
   Petit RJ, 2006, ANNU REV ECOL EVOL S, V37, P187, DOI 10.1146/annurev.ecolsys.37.091305.110215
   Rehfeldt GE, 1999, ECOL MONOGR, V69, P375, DOI 10.1890/0012-9615(1999)069[0375:GRTCIP]2.0.CO;2
   Rehfeldt GE, 2002, GLOBAL CHANGE BIOL, V8, P912, DOI 10.1046/j.1365-2486.2002.00516.x
   Rehfeldt GE, 1994, INTERIOR CEDAR-HEMLOCK-WHITE PINE FORESTS: ECOLOGY AND MANAGEMENT, SYMPOSIUM PROCEEDINGS, P91
   Rehfeldt GE, 2010, MITIG ADAPT STRAT GL, V15, P283, DOI 10.1007/s11027-010-9217-2
   Remund J., 2011, SCHATZUNG STANDORTSP, P56
   Sagnard F, 2002, FOREST ECOL MANAG, V157, P175, DOI 10.1016/S0378-1127(00)00664-2
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   Schueler S, 2013, BIODIVERS CONSERV, V22, P1151, DOI 10.1007/s10531-012-0313-3
   SKROPPA T, 1993, SILVAE GENET, V42, P111
   St Clair JB, 2007, GLOBAL CHANGE BIOL, V13, P1441, DOI 10.1111/j.1365-2486.2007.01385.x
   St Clair JB, 2005, ANN BOT-LONDON, V96, P1199, DOI 10.1093/aob/mci278
   St Clair JB, 2011, TURK J BOT, V35, P403, DOI 10.3906/bot-1012-98
   Stöcklin J, 2009, BOT HELV, V119, P125, DOI 10.1007/s00035-009-0065-1
   Team RC, 2014, R: A Language and Environment for Statistical Computing
   Teepe R, 2003, J PLANT NUTR SOIL SC, V166, P111, DOI 10.1002/jpln.200390001
   Vitasse Y, 2013, OECOLOGIA, V171, P663, DOI 10.1007/s00442-012-2580-9
   Vitasse Y, 2009, CAN J FOREST RES, V39, P1259, DOI 10.1139/X09-054
   Walthert L, 2013, FOREST ECOL MANAG, V297, P94, DOI 10.1016/j.foreco.2013.02.008
   Wang T, 2006, GLOBAL CHANGE BIOL, V12, P2404, DOI 10.1111/j.1365-2486.2006.01271.x
   Zang C, 2014, GLOBAL CHANGE BIOL, V20, P3767, DOI 10.1111/gcb.12637
   Zelenka A., 1992, IEASHCP9D1, P261
NR 79
TC 30
Z9 34
U1 1
U2 35
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0012-9658
EI 1939-9170
J9 ECOLOGY
JI Ecology
PD JAN
PY 2017
VL 98
IS 1
BP 211
EP 227
DI 10.1002/ecy.1632
PG 17
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EH6DM
UT WOS:000391862900018
PM 28052396
OA Green Published
DA 2025-01-10
ER

PT J
AU Garrity, DP
   Akinnifesi, FK
   Ajayi, OC
   Weldesemayat, SG
   Mowo, JG
   Kalinganire, A
   Larwanou, M
   Bayala, J
AF Garrity, Dennis Philip
   Akinnifesi, Festus K.
   Ajayi, Oluyede C.
   Weldesemayat, Sileshi G.
   Mowo, Jeremias G.
   Kalinganire, Antoine
   Larwanou, Mahamane
   Bayala, Jules
TI Evergreen Agriculture: a robust approach to sustainable food security in
   Africa
SO FOOD SECURITY
LA English
DT Article
DE Agroforestry; Burkina faso; Climate change adaptation and mitigation;
   Conservation farming; Evergreen Agriculture; Faidherbia albida;
   Fertilizer trees; Malawi; Niger; Soil carbon; Zambia
ID MAIZE INTERCROPPING SYSTEM; GLIRICIDIA-SEPIUM; CROPPING SYSTEMS;
   ACACIA-ALBIDA; SOIL; AGROFORESTRY; MANAGEMENT; HUNGER; YIELDS
AB Producing more food for a growing population in the coming decades, while at the same time combating poverty and hunger, is a huge challenge facing African agriculture. The risks that come with climate change make this task more daunting. However, hundreds of thousands of rain fed smallholder farmers in Zambia, Malawi, Niger, and Burkina Faso have been shifting to farming systems that are restoring exhausted soils and are increasing food crop yields, household food security, and incomes. This article reviews these experiences, and their broader implications for African food security, as manifestations of Evergreen Agriculture, a fresh approach to achieving food security and environmental resilience. Evergreen Agriculture is defined as the integration of particular tree species into annual food crop systems. The intercropped trees sustain a green cover on the land throughout the year to maintain vegetative soil cover, bolster nutrient supply through nitrogen fixation and nutrient cycling, generate greater quantities of organic matter in soil surface residues, improve soil structure and water infiltration, increase greater direct production of food, fodder, fuel, fiber and income from products produced by the intercropped trees, enhance carbon storage both above-ground and below-ground, and induce more effective conservation of above-and below-ground biodiversity. Four national cases are reviewed where farmers are observed to be applying these principles on a major scale. The first case involves the experience of Zambia, where conservation farming programmes include the cultivation of food crops within an agroforest of the fertilizer tree Faidherbia albida. The second case is that of the Malawi Agroforestry Food Security Programme, which is integrating fertilizer, fodder, fruit, fuel wood, and timber tree production with food crops on small farms on a national scale. The third case is the dramatic expansion of Faidherbia albida agroforests in millet and sorghum production systems throughout Niger via assisted natural regeneration. The fourth case is the development of a unique type of planting pit technology (zai) along with farmer-managed natural regeneration of trees on a substantial scale in Burkina Faso. Lastly, we examine the current outlook for Evergreen Agriculture to be further adapted and scaled-up across the African continent.
C1 [Garrity, Dennis Philip; Mowo, Jeremias G.] World Agroforestry Ctr, Nairobi, Kenya.
   [Akinnifesi, Festus K.; Ajayi, Oluyede C.; Weldesemayat, Sileshi G.] World Agroforestry Ctr, Lilongwe, Malawi.
   [Kalinganire, Antoine; Bayala, Jules] World Agroforestry Ctr, Bamako, Mali.
   [Larwanou, Mahamane] World Agroforestry Ctr ICRAF, AFF, Nairobi, Kenya.
C3 CGIAR; World Agroforestry (ICRAF); CGIAR; World Agroforestry (ICRAF)
RP Garrity, DP (corresponding author), World Agroforestry Ctr, POB 30677-00100, Nairobi, Kenya.
EM d.garrity@cgiar.org
OI Akinnifesi, Festus Kehinde/0009-0003-1293-6818
FU Governments of Malawi; Governments of Zambia; Government of Niger and
   Burkina; Government of Australia; Government of Canada; Government of
   Denmark; Government of Finland; Government of Germany; Government of
   Ireland; Government of Japan; Government of Norway; Government of
   Sweden; Government of United Kingdom; Government of United State;
   International Fund for Agricultural Development; Rock-efeller; Bill and
   Melinda Gates Foundation
FX The authors gratefully acknowledge the financial and in-kind support
   provided for this work by the Governments of Malawi, Zambia, Niger and
   Burkina Faso, the Governments of Australia, Canada, Denmark, Finland,
   Germany, Ireland, Japan, Norway, Sweden, United Kingdom, and the United
   States, by the International Fund for Agricultural Development, and by
   the Rock-efeller and Bill and Melinda Gates Foundation.
CR AAGARD P, 2009, COMMUNICATION
   ABDULAI A, 2004, 5 IFPRI DEV STRAT GO
   Adam T, 2006, PLUS GENS PLUS ARBRE
   Ajayi CO, 2009, AGREKON, V48, P246
   Ajayi OC, 2007, INTERNATIONAL RESEARCH ON NATURAL RESOURCE MANAGEMENT: ADVANCES IN IMPACT ASSESSMENT, P147, DOI 10.1079/9781845932831.0147
   Ajayi O. C., 2005, IMPACT FERTILIZER TR, P28
   Akinnifesi F. K., 2009, Agricultural Journal, V4, P260
   Akinnifesi F. K., 2008, Agricultural Journal, V3, P58
   Akinnifesi FK, 2007, PLANT SOIL, V294, P203, DOI 10.1007/s11104-007-9247-z
   AKINNIFESI FK, 2010, J SUSTAIN DEV, DOI DOI 10.1051/AGRON/2009058
   [Anonymous], 2004, WORLD POP 2300
   [Anonymous], 2007, STAT FOOD AGR, DOI DOI 10.4060/CB4476EN
   [Anonymous], 2006, Etude de la Regeneration Naturelle Assistee dans la Region de Zinder (Niger)
   [Anonymous], 1983, EVOLUTION LUTTE ANTI
   [Anonymous], 1983, TRANSFORMATIE MOSSI
   [Anonymous], 2006, UN ACC WAT MILL DEV
   [Anonymous], ROOTS RES GROW WEALT
   [Anonymous], 2010, IFPRI DISCUSSION PAP
   [Anonymous], 142 INT FOOD POL RES
   [Anonymous], 2003, TROPICAL FORESTRY PA
   Arnold J.E.M., 1995, TREE MANAGEMENT FARM
   Barro Albert, 2005, Cahiers Agricultures, V14, P549
   BOFFA JM, 1999, 34 FAO
   Carr S. J., 1997, African Crop Science Journal, V5, P93
   Chirwa PW, 2007, AGROFOREST SYST, V69, P29, DOI 10.1007/s10457-006-9016-7
   Denning G, 2009, PLOS BIOL, V7, P2, DOI 10.1371/journal.pbio.1000023
   Devereux S., 2001, FOOD SECURITY SUBSAH
   Devereux S, 2009, FOOD SECUR, V1, P25, DOI 10.1007/s12571-008-0005-8
   DRAME YA, 2008, TROPICULTURA, V26, P141
   *FAM EARL WARN SYS, 2007, MONTHL REP 2005 2007
   *FAO, 2008, FAOSTAT DAT PROD CRO
   Frankenberger T., 2007, Discussion Paper No. 43
   Funk CC, 2009, FOOD SECUR, V1, P271, DOI 10.1007/s12571-009-0026-y
   GARRITY D, 2008, M CHALLENGES CLIMATE, P8
   Garrity DP, 2004, AGROFOREST SYST, V61-2, P5, DOI 10.1023/B:AGFO.0000028986.37502.7c
   GARRITY DP, 2010, OUR PLANET       MAY, P28
   *GEF, 2003, WHAT KIND WORLD CHAL, P4
   Hadgu KM, 2008, Temporal and spatial changes in land use patterns and biodiversity in relation to farm productivity at multiple scales in Tigray, Ethiopia
   Haggblade S., 2003, 108 EPTD INT FOOD PO
   Jones PG, 2003, GLOBAL ENVIRON CHANG, V13, P51, DOI 10.1016/S0959-3780(02)00090-0
   KABORE D, 2004, 114 INT FOOD POL RES
   KANDJI ST, 2006, CLIMATE CHANGE VARIA, P36
   Kaonga ML, 2009, AGROFOREST SYST, V76, P37, DOI 10.1007/s10457-008-9185-7
   Katanga R, 2007, J AGRIC EDUC EXT, V13, P117, DOI 10.1080/13892240701289544
   KUMAR BM, 2006, TROPICAL HOMEGARDENS, P377
   KWESIGA, 2005, 130 EPTD INT FOOD PO
   Kwesiga F, 2003, AGROFOREST SYST, V59, P173, DOI 10.1023/B:AGFO.0000005222.68054.38
   KWESIGA F, 1994, FOREST ECOL MANAG, V64, P161, DOI 10.1016/0378-1127(94)90290-9
   Lal R, 2009, FOOD SECUR, V1, P45, DOI 10.1007/s12571-009-0009-z
   Lal R, 2010, FOOD SECUR, V2, P169, DOI 10.1007/s12571-010-0060-9
   Lamb RL, 2000, AGR ECON-BLACKWELL, V22, P271, DOI 10.1111/j.1574-0862.2000.tb00075.x
   LARWANOU M, 2008, 11 U A MOUM NIAM NIG
   Mafongoya P L., 2006, Biological approaches to sustainable soil systems, P273, DOI DOI 10.1201/9781420017113.CH19
   Makumba W, 2007, AGR ECOSYST ENVIRON, V118, P237, DOI 10.1016/j.agee.2006.05.011
   Makumba W, 2006, AGR ECOSYST ENVIRON, V116, P85, DOI 10.1016/j.agee.2006.03.012
   MATLON P J, 1990, Food Research Institute Studies (Stanford), V22, P1
   MATLON PJ, 1984, AM J AGR ECON, V66, P671, DOI 10.2307/1240976
   MONIMART M, 1989, FEMMES SAHEL DESERTI, P263
   PHOMBEYA H, 2009, COMMUNICATION
   Phombeya H. S. K, 1999, THESIS U LONDON THESIS U LONDON
   PYESMITH C, 2008, FARMING TREES BANISH, P27
   Reij, 2009, TRANSFORMATION SILEN
   REIJ C, 2003, DEV RURAL ENV BURKIN
   RHOADES C, 1995, AGROFOREST SYST, V29, P133, DOI 10.1007/BF00704882
   SAKA AR, 1994, FOREST ECOL MANAG, V64, P217, DOI 10.1016/0378-1127(94)90296-8
   Sanchez PA, 2005, SCIENCE, V307, P357, DOI 10.1126/science.1109057
   Sanchez PA, 2002, SCIENCE, V295, P2019, DOI 10.1126/science.1065256
   SANCHEZ PA, 1994, 15TH WORLD CONGRESS OF SOIL SCIENCE, VOL 1, TRANSACTIONS, P65
   Sangiga N, 2009, INTEGRATED SOIL FERT, P263
   SCHERR S, 2009, FARMING NATURE SCI P, P473
   Schmidhuber J, 2007, P NATL ACAD SCI USA, V104, P19703, DOI 10.1073/pnas.0701976104
   Scoones I., 1999, Policies for soil fertility in Africa
   Shepherd KD, 2007, J NEAR INFRARED SPEC, V15, P1, DOI 10.1255/jnirs.716
   Sileshi G, 2006, AGR ECOSYST ENVIRON, V115, P69, DOI 10.1016/j.agee.2005.12.010
   Sileshi G., 2006, Zambian J. Agric. Sci., V8, P6
   Sileshi G, 2008, PLANT SOIL, V307, P1, DOI 10.1007/s11104-008-9547-y
   Sileshi G, 2010, FIELD CROP RES, V116, P1, DOI 10.1016/j.fcr.2009.11.014
   Snapp SS, 1998, AGR ECOSYST ENVIRON, V71, P185, DOI 10.1016/S0167-8809(98)00140-6
   Swift M J., 2007, Saving Africa's Soils
   Syampungani S., 2010, Agricultural Journal, V5, P80
   Tougiani A, 2009, GEOJOURNAL, V74, P377, DOI 10.1007/s10708-008-9228-7
   Tripp R., 2005, International Journal of Agricultural Sustainability, V3, P143, DOI 10.1080/14735903.2005.9684752
   *UNEP ISRIC, 1991, WORLD MAP STAT HUM I
   Zomer R. J., 2009, 89 ICRAF WORLD AGR C
   2008, MALAWI POVERTY VULNE, V2
NR 85
TC 323
Z9 364
U1 7
U2 317
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 1876-4517
EI 1876-4525
J9 FOOD SECUR
JI Food Secur.
PD SEP
PY 2010
VL 2
IS 3
BP 197
EP 214
DI 10.1007/s12571-010-0070-7
PG 18
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA 675WV
UT WOS:000283872600002
DA 2025-01-10
ER

PT J
AU Gissi, E
   Schiebinger, L
   Hadly, EA
   Crowder, LB
   Santoleri, R
   Micheli, F
AF Gissi, Elena
   Schiebinger, Londa
   Hadly, Elizabeth A.
   Crowder, Larry B.
   Santoleri, Rosalia
   Micheli, Fiorenza
TI Exploring climate-induced sex-based differences in aquatic and
   terrestrial ecosystems to mitigate biodiversity loss
SO NATURE COMMUNICATIONS
LA English
DT Article
ID RATIO
AB The response of aquatic and terrestrial organisms to climate change can depend on biological sex. A key challenge is to unravel the interactive effects of sex and climate change at the individual and population levels and the cascading effects on communities. This new understanding is essential to improve climate adaptation and mitigation strategies.
C1 [Gissi, Elena; Crowder, Larry B.; Micheli, Fiorenza] Stanford Univ, Oceans Dept, Hopkins Marine Stn, 120 Ocean View Blvd, Pacific Grove, CA 93950 USA.
   [Gissi, Elena; Santoleri, Rosalia] Inst Marine Sci, Natl Res Council, CNR ISMAR, Tesa 104 Castello 2737-F, I-30122 Venice, Italy.
   [Gissi, Elena] Natl Biodivers Future Ctr, I-90133 Palermo, Italy.
   [Schiebinger, Londa] Stanford Univ, Hist Sci Gendered Innovat Sci Hlth & Med, Engn & Environm, Stanford, CA 94305 USA.
   [Hadly, Elizabeth A.] Stanford Univ, Dept Biol, Stanford, CA 94305 USA.
   [Hadly, Elizabeth A.; Crowder, Larry B.; Micheli, Fiorenza] Stanford Univ, Stanford Woods Inst Environm, Stanford, CA 94305 USA.
   [Hadly, Elizabeth A.] Stanford Univ, Ctr Innovat Global Hlth, Stanford, CA 94305 USA.
   [Micheli, Fiorenza] Stanford Ctr Ocean Solut, 120 Ocean View Blvd, Pacific Grove, CA 93950 USA.
C3 Stanford University; Consiglio Nazionale delle Ricerche (CNR); Istituto
   di Scienze Marine (ISMAR-CNR); Stanford University; Stanford University;
   Stanford University; Stanford University
RP Gissi, E (corresponding author), Stanford Univ, Oceans Dept, Hopkins Marine Stn, 120 Ocean View Blvd, Pacific Grove, CA 93950 USA.; Gissi, E (corresponding author), Inst Marine Sci, Natl Res Council, CNR ISMAR, Tesa 104 Castello 2737-F, I-30122 Venice, Italy.; Gissi, E (corresponding author), Natl Biodivers Future Ctr, I-90133 Palermo, Italy.
EM elena.gissi@cnr.it
RI Hay, Elizabeth/HKF-8621-2023; Santoleri, Rosalia/JNT-1470-2023; GISSI,
   ELENA/T-1108-2019
OI Micheli, Fiorenza/0000-0002-6865-1438; Schiebinger,
   Londa/0000-0003-3438-3081; GISSI, ELENA/0000-0002-1666-8772
FU EU Horizon 2020 research and innovation program under the Marie
   Sklodowska-Curie grant [893614]; US National Science Foundation
   [2108566]; Marie Curie Actions (MSCA) [893614] Funding Source: Marie
   Curie Actions (MSCA)
FX Funding was provided by the EU Horizon 2020 research and innovation
   program under the Marie Sklodowska-Curie grant agreement #893614. F.M.
   acknowledges US National Science Foundation support (2108566). This
   study reflects only the views of the authors. The Research Executive
   Agency and the European Commission are not responsible for any use that
   may be made of the information it contains.
CR AMAP, 2018, AMAP ASS 2018 ARC OC
   Avery DE, 2008, LIMNOL OCEANOGR, V53, P2627, DOI 10.4319/lo.2008.53.6.2627
   DFO (Fisheries and Oceans Canada), 2006, DFO CAN SCI ADV SEC
   Dong JS, 2022, FOOD WEBS, V33, DOI 10.1016/j.fooweb.2022.e00253
   Eberhart-Phillips LJ, 2017, P NATL ACAD SCI USA, V114, pE5474, DOI 10.1073/pnas.1620043114
   Ellis RP, 2017, BIOL LETTERS, V13, DOI 10.1098/rsbl.2016.0761
   Gianuca D, 2019, J ANIM ECOL, V88, P1366, DOI 10.1111/1365-2656.13009
   Gissi E, 2023, FRONT ECOL ENVIRON, V21, P324, DOI 10.1002/fee.2652
   Gunderson AR, 2021, FUNCT ECOL, V35, P2618, DOI 10.1111/1365-2435.13959
   Hoye TT, 2009, BIOL LETTERS, V5, P542, DOI 10.1098/rsbl.2009.0169
   Jay CV, 2017, J MAMMAL, V98, P386, DOI 10.1093/jmammal/gyw195
   Jay CV, 2011, POLAR BIOL, V34, P1065, DOI 10.1007/s00300-011-0967-4
   Jensen MP, 2018, CURR BIOL, V28, P154, DOI 10.1016/j.cub.2017.11.057
   Kappeler PM, 2023, BIOL REV, V98, P462, DOI 10.1111/brv.12915
   Kiorboe T, 2006, OECOLOGIA, V148, P40, DOI 10.1007/s00442-005-0346-3
   Main Martin B., 2005, P148
   Mitchell NJ, 2008, P ROY SOC B-BIOL SCI, V275, P2185, DOI 10.1098/rspb.2008.0438
   Noren SR, 2016, PHYSIOL BIOCHEM ZOOL, V89, P93, DOI 10.1086/685454
   Petry WK, 2016, SCIENCE, V353, P69, DOI 10.1126/science.aaf2588
   Pottier P, 2021, FUNCT ECOL, V35, P2663, DOI 10.1111/1365-2435.13899
   Queensland Department of Agriculture and Fisheries, 2021, Queensland Sea Cucumber Fishery Harvest Strategy: 2021-2026
   Sales K, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-07273-z
   Sasaki M, 2019, ROY SOC OPEN SCI, V6, DOI 10.1098/rsos.182115
   Shaw AK, 2018, J ANIM ECOL, V87, P36, DOI 10.1111/1365-2656.12658
   Soldatini C, 2019, POPUL ECOL, V61, P227, DOI 10.1002/1438-390X.1024
   Titley MA, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0189577
   Urbach D, 2012, FISH RES, V134, P104, DOI 10.1016/j.fishres.2012.08.008
   Welbergen JA, 2008, P ROY SOC B-BIOL SCI, V275, P419, DOI 10.1098/rspb.2007.1385
   Wilson EO, 2017, NAT ECOL EVOL, V1, P1590, DOI 10.1038/s41559-017-0360-y
   Woitowich NC, 2020, ELIFE, V9, DOI 10.7554/eLife.56344
NR 30
TC 8
Z9 8
U1 1
U2 15
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
EI 2041-1723
J9 NAT COMMUN
JI Nat. Commun.
PD AUG 16
PY 2023
VL 14
IS 1
AR 4787
DI 10.1038/s41467-023-40316-8
PG 6
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA P5LT3
UT WOS:001051097300005
PM 37587108
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Van Buuren, A
   Vink, M
   Warner, J
AF Van Buuren, Arwin
   Vink, Martinus
   Warner, Jeroen
TI Constructing Authoritative Answers to a Latent Crisis? Strategies of
   Puzzling, Powering and Framing in Dutch Climate Adaptation Practices
   Compared
SO JOURNAL OF COMPARATIVE POLICY ANALYSIS
LA English
DT Article
DE governance; framing; crisis; legitimacy; puzzling; powering; climate
   adaptation
ID POLICY; POLITICS
AB While adaptation tends to be approached as an issue for policy analysis, framing and powering strongly interact with policy analysis (puzzling) and are at least as important for adequate outcomes in such an ambiguous context. The present contribution compares and analyzes two Dutch adaptation strategies in the Central Netherlands: (1) realizing a flood bypass channel near the town of Kampen and (2) exploring possibilities to raise the water level of Lake IJssel, enhancing the country's freshwater storage capacity. The article concludes that in both trajectories there is an important role for policy analysis (puzzling) but the cases differ strongly in the way actors frame the intervention, their corresponding powering strategies and the policy outcomes.
C1 [Van Buuren, Arwin] Erasmus Univ, Fac Social Sci, Dept Publ Adm, Room T17-13,POB 1738, NL-3000 DR Rotterdam, Netherlands.
   [Vink, Martinus] Wageningen UR, Publ Adm & Policy Grp, Wageningen, Netherlands.
   [Warner, Jeroen] Wageningen UR, Rural Dev Sociol, Wageningen, Netherlands.
C3 Erasmus University Rotterdam; Erasmus University Rotterdam - Excl
   Erasmus MC; Wageningen University & Research; Wageningen University &
   Research
RP Van Buuren, A (corresponding author), Erasmus Univ, Fac Social Sci, Dept Publ Adm, Room T17-13,POB 1738, NL-3000 DR Rotterdam, Netherlands.
EM vanbuuren@fsw.eur.nl
RI van Buuren, Arwin/I-6240-2013
OI van Buuren, Arwin/0000-0002-8504-0495
CR [Anonymous], GRONDSLAG ONDER BYPA
   [Anonymous], DELT 2012 PROBL IJSS
   [Anonymous], DILEMMAS GEN THEORY
   [Anonymous], ACT OND VEIL BYP KAM
   [Anonymous], 196 CPB CENTR PLANB
   [Anonymous], AANV BEOORD PROJ IJS
   [Anonymous], REGIONS AND POWERS
   [Anonymous], SAM PLAN VAN AANP
   [Anonymous], SEMISOVEREIGN PEOPLE
   [Anonymous], KAMPEN IJSELDELTA AM
   [Anonymous], GROEN LICHT BYP
   [Anonymous], REGIONAL EN IN PRESS
   [Anonymous], ENV PLANNING C
   [Anonymous], 2008, WORK TOG WAT LIV LAN
   [Anonymous], 1993, ARGUMENTATIVE TURN P
   Arts B, 2004, POLICY SCI, V37, P339, DOI 10.1007/s11077-005-0156-9
   BACHRACH P, 1962, AM POLIT SCI REV, V56, P947, DOI 10.2307/1952796
   Baumgartner F. R., 2001, Policy Dynamics Introduction: Positive and Negative Feedback in Politics
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Biesbroek GR, 2010, GLOBAL ENVIRON CHANG, V20, P440, DOI 10.1016/j.gloenvcha.2010.03.005
   Boezeman D, 2013, ENVIRON SCI POLICY, V27, P162, DOI 10.1016/j.envsci.2012.12.016
   Boin A., 2005, POLITICS CRISIS MANA, DOI 10.1017/CBO9780511490880
   Buzan B., 1997, Security: a new framework for analysis
   Cobb R.W., 1972, PARTICIPATION AM POL
   Culpepper PD, 2002, J EUR PUBLIC POLICY, V9, P774, DOI 10.1080/13501760210162357
   de Bruin K, 2009, CLIMATIC CHANGE, V95, P23, DOI 10.1007/s10584-009-9576-4
   Dewulf A, 2013, WIRES CLIM CHANGE, V4, P321, DOI 10.1002/wcc.227
   Dunn WilliamN., 2003, Public Policy Analysis; an Introductoin (Analisis Kebijakan Publik)
   Few R, 2007, CLIM POLICY, V7, P46, DOI 10.1080/14693062.2007.9685637
   Ford JD, 2011, ADV GLOB CHANGE RES, V42, P3, DOI 10.1007/978-94-007-0567-8_1
   Giddens A, 2015, POLICY POLIT, V43, P155, DOI 10.1332/030557315X14290856538163
   Gusfield JosephR., 1981, CULTURE PUBLIC PROBL
   HALL PA, 1993, COMP POLIT, V25, P275, DOI 10.2307/422246
   Heclo H., 1974, MODERN SOCIAL POLITI
   Hegerl G.C., 2007, CLIMATE CHANGE 2007
   Henstra D, 2012, J COMP POLICY ANAL, V14, P175, DOI 10.1080/13876988.2012.665215
   Hoppe R, 2010, GOVERNANCE OF PROBLEMS: PUZZLING, POWERING, PARTICIPATION, P1
   Hulme M, 2009, WHY WE DISAGREE ABOUT CLIMATE CHANGE: UNDERSTANDING CONTROVERSY, INACTION AND OPPORTUNITY, P1
   Intergov Panel Clim Chg, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P1, DOI 10.1017/CBO9781139177245
   Karafoulidis T, 2012, CLIMATE CHANGE HUMAN, P259
   Lahsen M, 2005, SCI TECHNOL HUM VAL, V30, P137, DOI 10.1177/0162243904270710
   Laswell H.D., 1936, Politics: Who Gets What, When, How
   Lazarus RJ, 2009, CORNELL LAW REV, V94, P1153
   Majone G., 1996, A New Handbook of Political Science
   Pralle SB, 2009, ENVIRON POLIT, V18, P781, DOI 10.1080/09644010903157115
   Repetto R., 2008, The Climate Crisis and the Adaptation Myth
   Runhaar H, 2012, REG ENVIRON CHANGE, V12, P777, DOI 10.1007/s10113-012-0292-7
   Schon D.A.M. Rein., 1994, FRAME REFLECTION RES
   STONE DA, 1989, POLIT SCI QUART, V104, P281, DOI 10.2307/2151585
   Termeer Catrien., 2013, Climate Change Governance, Climate Change Management, DOI 10.1007/978-3-642-29831-8_3
   Turnpenny J, 2009, ENVIRON SCI POLICY, V12, P347, DOI 10.1016/j.envsci.2009.01.004
   Uittenbroek CJ, 2013, REG ENVIRON CHANGE, V13, P399, DOI 10.1007/s10113-012-0348-8
   Van Buuren A, 2010, ENVIRON IMPACT ASSES, V30, P127, DOI 10.1016/j.eiar.2009.05.007
   Verduijn S. H., 2012, Water Alternatives, V5, P469
   Vink M.J., 2013, Evaluatie Lerend Proces Delta Programma IJsselmeergebied
   Vink MJ, 2013, ENVIRON SCI POLICY, V30, P90, DOI 10.1016/j.envsci.2012.10.010
   Visser Jelle., 1997, DUTCH MIRACLE JOB GR
   von Benda-Beckmann K., 1981, Journal of Legal Pluralism, V19, P117, DOI DOI 10.1080/07329113.1981.10756260
   Warner J, 2011, INT REV ADM SCI, V77, P779, DOI 10.1177/0020852311419387
   Warner Jeroen., 2011, Flood Planning. The Politics of River Interventions, DOI [10.5040/9780755620449, DOI 10.5040/9780755620449]
   Warner JF, 2013, MAKING SPACE FOR THE RIVER: GOVERNANCE EXPERIENCES WITH MULTIFUNCTIONAL RIVER FLOOD MANAGEMENT IN THE US AND EUROPE, P1
   Wolf J, 2011, ADV GLOB CHANGE RES, V42, P21, DOI 10.1007/978-94-007-0567-8_2
NR 62
TC 18
Z9 18
U1 0
U2 9
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1387-6988
EI 1572-5448
J9 J COMP POLICY ANAL
JI J. Comp. Policy Anal.
PD JAN 1
PY 2016
VL 18
IS 1
BP 70
EP 87
DI 10.1080/13876988.2013.877675
PG 18
WC Public Administration
WE Social Science Citation Index (SSCI)
SC Public Administration
GA DG5LO
UT WOS:000372119900005
DA 2025-01-10
ER

PT J
AU Zafeiriou, E
   Galatsidas, S
   Moulogianni, C
   Sofios, S
   Arabatzis, G
AF Zafeiriou, Eleni
   Galatsidas, Spyros
   Moulogianni, Christina
   Sofios, Spyridon
   Arabatzis, Garyfallos
TI Evaluating Enteric Fermentation-Driven Environmental Kuznets Curve
   Dynamics: A Bayesian Vector Autoregression Comparative Study of the EU
   and Least Developed Countries
SO AGRICULTURE-BASEL
LA English
DT Article
DE enteric fermentation; Kuznets; livestock; the European Union (EU); least
   developed countries (LDCs); Bayesian vector autoregression models (BVAR
   models)
ID CO2 EMISSIONS; AGRICULTURE; HYPOTHESIS; ENERGY; IMPACT
AB Global warming and climate change, primarily driven by human activities, with agriculture playing a significant role, have become central topics of scientific research. Livestock production, especially enteric fermentation, is a major source of greenhouse gas emissions, making it a focal point for both climate change adaptation and mitigation strategies. Both the European Union (EU) and Least Developed Countries (LDCs) are highly dependent on agriculture, particularly livestock, which plays a key role in their economic growth. In developing countries, livestock systems are evolving rapidly due to various factors, while in the EU, the livestock sector remains economically and socially significant, representing 36% of total agricultural activity. This study explores the environmental impact of enteric fermentation in livestock production, alongside the economic value it generates in both the EU and LDCs. The analysis utilizes a Bayesian Vector Autoregression (BVAR) methodology, which provides a more robust performance compared to traditional models like Vector Autoregression (VAR) and the Vector-error Correction Model (VECM). This research identifies significant relationships between the variables studied, with structural breaks quantified to reflect the impact of initiatives undertaken in both regions. Interestingly, the results challenge the environmental Kuznets curve, which hypothesizes an inverted U-shaped relationship between economic growth and environmental degradation, as proposed by Stern. This suggests that stronger economic incentives may be necessary to enhance policy effectiveness and promote eco-efficiency. The distinctive characteristics of livestock production in the EU and LDCs should be carefully considered when shaping agricultural policies, with a strong emphasis on farmer education as a critical factor for success. Additionally, corporate management practices must be tailored to address the unique needs, strengths, and challenges of livestock businesses in these two diverse regions.
C1 [Zafeiriou, Eleni] Democritus Univ Thrace, Fac Agr & Forestry Sci, Sch Agr Dev, Orestiada 68200, Greece.
   [Galatsidas, Spyros; Arabatzis, Garyfallos] Democritus Univ Thrace, Fac Agr & Forestry Sci, Sch Forestry & Management Environm & Nat Resources, Orestiada 68200, Greece.
   [Moulogianni, Christina] Aristotle Univ Thessaloniki, Dept Agr Econ, Thessaloniki 54124, Greece.
   [Sofios, Spyridon] Independent Author Publ Revenue, Thessaloniki 54110, Greece.
C3 Democritus University of Thrace; Democritus University of Thrace;
   Aristotle University of Thessaloniki
RP Galatsidas, S (corresponding author), Democritus Univ Thrace, Fac Agr & Forestry Sci, Sch Forestry & Management Environm & Nat Resources, Orestiada 68200, Greece.
EM ezafeir@agro.duth.gr; sgalatsi@fmenr.duth.gr; kristin@agro.auth.gr;
   spyrossofios@gmail.com; garamp@fmenr.duth.gr
RI Moulogianni, Christina/ADH-6896-2022
OI Zafeiriou, Eleni/0000-0002-2892-0293
CR den Toorn SIA, 2021, J CLEAN PROD, V304, DOI 10.1016/j.jclepro.2021.127138
   Ali G, 2017, ENVIRON SCI POLICY, V77, P166, DOI 10.1016/j.envsci.2017.08.019
   [Anonymous], 2014, Agriculture, forestry and other land use emissions by sources and removal by sinks: 1990- 2011 analysis
   [Anonymous], 2019, Annual european union greenhouse gas inventory 1990-2017 and inventory report 2019
   [Anonymous], 2022, UNEP Annual Report 2022
   [Anonymous], 2019, Air Quality in Europe2019 Report. EEA Technical Report 10/2019, DOI DOI 10.2800/822355
   ARELLANO M, 1991, REV ECON STUD, V58, P277, DOI 10.2307/2297968
   Brahmasrene T, 2014, ENERG ECON, V44, P407, DOI 10.1016/j.eneco.2014.05.011
   Dogan E, 2020, ENVIRON SCI POLLUT R, V27, P12717, DOI 10.1007/s11356-020-07878-2
   Dogan N, 2019, PANOECONOMICUS, V66, P257, DOI 10.2298/PAN160504030D
   EEA, 2020, EU Emissions of Ammonia
   European Environment Agency (EEA), 2021, Agriculture and Climate ChangeNitrous Oxide Emissions
   FAO, About us
   FAOSTAT, 2021, US
   Fischer A, 2020, J DAIRY SCI, V103, P4408, DOI 10.3168/jds.2019-17654
   Food and Agriculture Organization of the United Nations, 2019, About us
   Food and Agriculture Organization of the United Nations, 2022, Methane Emissions in Livestock and Rice Systems
   Gerber PJ, 2013, Tackling climate change through livestock-A global assessment of emissions and mitigation opportunities
   Giannone D, 2006, J ECONOMETRICS, V132, P257, DOI 10.1016/j.jeconom.2005.01.030
   Goldstein J, 2018, SCI CULT-UK, V27, P74, DOI 10.1080/09505431.2017.1346598
   Gorodnichenko Y, 2020, J BUS ECON STAT, V38, P921, DOI 10.1080/07350015.2019.1610661
   Gurbuz IB, 2021, ENVIRON SCI POLLUT R, V28, P23099, DOI 10.1007/s11356-020-12228-3
   Harsanyi E, 2021, ENERGIES, V14, DOI 10.3390/en14206495
   Ibidhi R, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13169133
   IFAD, 2021, Rural Development Report 2021|Transforming Food Systems for Rural Prosperity
   IPCC, 2014, Climate Change 2014: Mitigation of Climate Change
   IPCC, 2019, Refinements to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories
   Ivanov V, 2005, STUD NONLINEAR DYN E, V9
   Jakada AH, 2022, ENV HEALTH ENG MANAG, V9, P223, DOI 10.34172/EHEM.2022.23
   Kang SH, 2019, STRUCT CHANGE ECON D, V50, P90, DOI 10.1016/j.strueco.2019.05.006
   Kleftodimos G, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14010411
   Kleftodimos G, 2021, LAND USE POLICY, V107, DOI 10.1016/j.landusepol.2021.105462
   Leip A., 2010, Evaluation of the livestock sector's contribution to the EU greenhouse gas emissions (GGELS) - final report
   Liu X, 2017, J CLEAN PROD, V164, P1239, DOI 10.1016/j.jclepro.2017.07.086
   Ltkepohl H., 2013, Handbook of Research Methods and Applications in Empirical Macroeconomics
   Lütkepohl H, 2009, MACROECONOMETRICS AND TIME SERIES ANALYSIS, P369
   Mielcarek-Bochenska P, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12111396
   Mosnier C, 2009, ECOL ECON, V68, P1408, DOI 10.1016/j.ecolecon.2008.10.001
   Murawska A, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031035
   Ngwabie NM, 2011, ATMOS ENVIRON, V45, P6760, DOI 10.1016/j.atmosenv.2011.08.027
   Ocko IB, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abf9c8
   Orzuna-Orzuna JF, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13137410
   Pesaran HH, 1998, ECON LETT, V58, P17, DOI 10.1016/S0165-1765(97)00214-0
   Prastiyo SE, 2020, ENVIRON SCI POLLUT R, V27, P42092, DOI 10.1007/s11356-020-10148-w
   Sarkodie SA, 2020, RENEW SUST ENERG REV, V117, DOI 10.1016/j.rser.2019.109481
   Sarkodie SA, 2019, SCI TOTAL ENVIRON, V649, P128, DOI 10.1016/j.scitotenv.2018.08.276
   Selcuk M, 2021, ENVIRON SCI POLLUT R, V28, P55623, DOI 10.1007/s11356-021-14825-2
   Steinfeld H., 2006, Renewable Resources Journal, V24, P15
   Sun CW, 2017, J CLEAN PROD, V161, P153, DOI 10.1016/j.jclepro.2017.05.119
   Tagarakis A.C., 2021, Eng. Proc, V9, P10, DOI [10.3390/engproc2021009010, DOI 10.3390/ENGPROC2021009010]
   Tienhaara K, 2018, TRANSNATL ENVIRON LA, V7, P229, DOI 10.1017/S2047102517000309
   Tongwane MI, 2021, ENVIRON RES, V195, DOI 10.1016/j.envres.2021.110833
   Tongwane MI, 2020, J CLEAN PROD, V265, DOI 10.1016/j.jclepro.2020.121931
   Turkish Statistics Institute, Greenhouse Gas Emissions Statistics, 1990-2022
   Zafeiriou E, 2017, ECOL INDIC, V81, P104, DOI 10.1016/j.ecolind.2017.05.039
   Zafeiriou E, 2017, ENVIRON SCI POLLUT R, V24, P15510, DOI 10.1007/s11356-017-9090-6
NR 56
TC 0
Z9 0
U1 0
U2 0
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2077-0472
J9 AGRICULTURE-BASEL
JI Agriculture-Basel
PD NOV
PY 2024
VL 14
IS 11
AR 2036
DI 10.3390/agriculture14112036
PG 16
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA N3U4Z
UT WOS:001363628600001
OA gold
DA 2025-01-10
ER

PT J
AU Mousavisangdehi, A
   Oladi, R
   Pourtahmasi, K
   Etemad, V
   Koprowski, M
   Tumajer, J
AF Mousavisangdehi, Atiehsadat
   Oladi, Reza
   Pourtahmasi, Kambiz
   Etemad, Vahi
   Koprowski, Marcin
   Tumajer, Jan
TI Higher temperatures promote intra-annual radial growth of Oriental beech
   (<i>Fagus orientalis</i> Lipsky) in the humid Hyrcanian forests
SO TREES-STRUCTURE AND FUNCTION
LA English
DT Article
DE Xylogenesis; Wood formation; Growth pattern; Bud break; Cambium
   phenology; Oriental beech
ID WOOD FORMATION; SYLVATICA L.; CLIMATE SENSITIVITY; EUROPEAN BEECH;
   VESSEL FORMATION; XYLEM FORMATION; LEAF PHENOLOGY; DIFFERENTIATION;
   PRECIPITATION; XYLOGENESIS
AB Key message Oriental beech trees in Hyrcanian forests may exhibit a bimodal growth pattern. While water availability does not limit growth, these trees benefit from warmer weather. Abstract Climate projections for the Hyrcanian forests predict higher temperatures and reduced rainfall. However, the impact of these changes on beech tree growth is still debated. This study investigates the intra-annual growth patterns of Oriental beech (Fagus orientalis Lipsky) and their responses to climatic variation within the Hyrcanian forests of northern Iran. We collected micro-cores from six healthy trees in the Sangdeh forest every week from March to September 2022. Microsections were prepared from each core, and the width of the developing tree ring was measured under an optical microscope. We fitted a generalized additive model (GAM) to the measured radial growth increments to model growth and derive daily growth rates. We then used correlations between daily tree growth rates and climatic variables considering different time lags. The results show variable growth patterns within the beech trees, including both unimodal and bimodal growth dynamics during the growing season. Analysis of climatic data indicates a significant positive correlation between temperature and growth rate, particularly with a 15-day lag, while rainfall and humidity exhibit weaker, negative correlations with growth. Surprisingly, sufficient rainfall in the study area may hinder growth due to associated cloud cover, which limits sunshine and photosynthesis. A comparison of variations in radial growth and temperature shows their tight synchronization over the growing season. In conclusion, this study offers insights into the complex interactions between climatic factors and tree growth, with implications for regional forest management and climate change adaptation strategies.
C1 [Mousavisangdehi, Atiehsadat; Oladi, Reza; Pourtahmasi, Kambiz] Univ Tehran, Univ Coll Agr & Nat Resources, Fac Nat Resources, Dept Wood & Paper Sci & Technol, Karaj, Iran.
   [Etemad, Vahi] Univ Tehran, Univ Coll Agr & Nat Resources, Fac Nat Resources, Dept Forestry & Forest Econ, Karaj, Iran.
   [Koprowski, Marcin] Nicolaus Copernicus Univ, Fac Biol & Vet Sci, Dept Ecol & Biogeog, Ul Lwowska 1, PL-87100 Torun, Poland.
   [Tumajer, Jan] Charles Univ Prague, Fac Sci, Dept Phys Geog & Geoecol, Prague, Czech Republic.
C3 University of Tehran; University of Tehran; Nicolaus Copernicus
   University; Charles University Prague
RP Oladi, R (corresponding author), Univ Tehran, Univ Coll Agr & Nat Resources, Fac Nat Resources, Dept Wood & Paper Sci & Technol, Karaj, Iran.
EM oladi@ut.ac.ir
RI Pourtahmasi, Kambiz/ABG-6814-2021; Tumajer, Jan/I-2053-2019; Tumajer,
   Jan/S-3397-2016; Oladi, Reza/F-6725-2017; Koprowski, Marcin/A-2863-2014
OI Tumajer, Jan/0000-0002-7773-7081; Oladi, Reza/0000-0002-8522-7321;
   Pourtahmasi, Kambiz/0000-0002-1858-7765; etemad,
   vahid/0000-0001-6560-7653; Koprowski, Marcin/0000-0002-0583-4165
FU College of Agriculture Natural Resources, University of Tehran
   [24-11757S]; Czech Science Foundation [PRIMUS/24/SCI/004]; Charles
   University [CZ.02.01.01/00/22_008/0004605]; Programme JAC; Erasmus+
   Programme; Nicolaus Copernicus University, Poland
FX We acknowledge the personal support from the Czech Science Foundation
   [24-11757S], Charles University [PRIMUS/24/SCI/004], and Programme JAC
   [CZ.02.01.01/00/22_008/0004605]. We also thank the Erasmus+ Programme
   for funding a 3-month stay of the first author at the Nicolaus
   Copernicus University, Poland. The logistic assistance of FarimWood
   Logging Company is appreciated.
CR Abdi O, 2018, LAND DEGRAD DEV, V29, P2525, DOI 10.1002/ldr.3025
   ALONI R, 1983, DIFFERENTIATION, V24, P203, DOI 10.1111/j.1432-0436.1983.tb01320.x
   Aloni R, 2015, TREES-STRUCT FUNCT, V29, P1, DOI 10.1007/s00468-014-1070-6
   Balapour S., 2011, WATERSHED MANAG RES, V23, P1
   Bayat M, 2022, FORESTS, V13, DOI 10.3390/f13111816
   Bektas Ibrahim, 2002, Turkish Journal of Agriculture and Forestry, V26, P147
   Campelo F, 2018, DENDROCHRONOLOGIA, V49, P77, DOI 10.1016/j.dendro.2018.03.001
   Chen TT, 2023, J ENVIRON MANAGE, V347, DOI 10.1016/j.jenvman.2023.119253
   Cuny HE, 2013, J EXP BOT, V64, P1983, DOI 10.1093/jxb/ert057
   D'Andrea E, 2020, PLANT CELL ENVIRON, V43, P2365, DOI 10.1111/pce.13858
   De Luis M, 2007, IAWA J, V28, P389, DOI 10.1163/22941932-90001651
   Deslauriers A, 2016, PLANT PHYSIOL, V170, P2072, DOI 10.1104/pp.15.01525
   Ding YX, 2020, INT J APPL EARTH OBS, V92, DOI 10.1016/j.jag.2020.102179
   Dittmar Christoph, 2007, Dendrochronologia, V25, P37, DOI 10.1016/j.dendro.2007.01.003
   Dittmar C, 2006, EUR J FOREST RES, V125, P249, DOI 10.1007/s10342-005-0098-y
   Dorado-Liñán I, 2016, CLIM DYNAM, V47, P937, DOI 10.1007/s00382-015-2881-x
   Elzami E, 2018, THESIS FAU ERLANGEN
   Fang JY, 2006, J BIOGEOGR, V33, P1804, DOI 10.1111/j.1365-2699.2006.01533.x
   Gao JN, 2021, AGR FOREST METEOROL, V308, DOI 10.1016/j.agrformet.2021.108572
   Garcia-Forner N, 2019, TREE PHYSIOL, V39, P2008, DOI 10.1093/treephys/tpz099
   Gholizadeh H, 2020, APPL VEG SCI, V23, P107, DOI 10.1111/avsc.12469
   Girard F, 2012, EUR J FOREST RES, V131, P919, DOI 10.1007/s10342-011-0565-6
   Golbabaei F., 2004, IRAN J WOOD PAP SCI, V19, P175
   Grossiord C, 2022, J ECOL, V110, P1575, DOI 10.1111/1365-2745.13892
   Gutiérrez E, 2011, TREES-STRUCT FUNCT, V25, P637, DOI 10.1007/s00468-011-0540-3
   Hafner P, 2014, CLIM DYNAM, V43, P971, DOI 10.1007/s00382-013-1864-z
   Haghshenas M, 2016, FOR SCI TECHNOL, V12, P176, DOI 10.1080/21580103.2016.1144542
   Hamidi SK, 2023, BIODIVERS CONSERV, V32, P3791, DOI 10.1007/s10531-022-02470-1
   Hoshino Y, 2008, J WOOD SCI, V54, P183, DOI 10.1007/s10086-007-0935-3
   Houston DT., 2016, EUROPEAN ATLAS FORES
   Huang JG, 2014, NEW PHYTOL, V203, P831, DOI 10.1111/nph.12859
   Jevsenak J, 2022, ECOGRAPHY, V2022, DOI 10.1111/ecog.06030
   Camarero JJ, 2010, NEW PHYTOL, V185, P471, DOI 10.1111/j.1469-8137.2009.03073.x
   Kolár T, 2017, AGR FOREST METEOROL, V239, P24, DOI 10.1016/j.agrformet.2017.02.028
   Köse N, 2012, TURK J AGRIC FOR, V36, P501, DOI 10.3906/tar-1109-4
   Larysch E, 2021, FORESTS, V12, DOI 10.3390/f12010075
   Levanic T, 2023, PLANTS-BASEL, V12, DOI 10.3390/plants12132427
   Liang EY, 2009, THEOR APPL CLIMATOL, V98, P9, DOI 10.1007/s00704-008-0085-6
   Limaki MK, 2021, ECOL MODEL, V455, DOI 10.1016/j.ecolmodel.2021.109637
   Liu HX, 2021, GLOB ECOL CONSERV, V30, DOI 10.1016/j.gecco.2021.e01751
   Mansouri Daneshvar MR., 2019, Environ. Syst. Res., V8, P1, DOI [10.1186/s40068-019-0135-3, DOI 10.1186/S40068-019-0135-3]
   Marchand LJ, 2021, TREE PHYSIOL, V41, P1161, DOI 10.1093/treephys/tpaa171
   del Castillo EM, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00370
   Martinez-Sancho E, 2021, FORESTS, V12, DOI 10.3390/f12121746
   Mellert KH, 2022, IFOREST, V15, P417, DOI [10.103832/ifor4077015, 10.3832/ifor4077-015]
   Michelot A, 2012, TREE PHYSIOL, V32, P1033, DOI 10.1093/treephys/tps052
   MITRAKOS K, 1980, ACTA OECOL-OEC PLANT, V1, P245
   Muffler L, 2024, ECOL EVOL, V14, DOI 10.1002/ece3.70028
   Myskow E, 2021, FORESTS, V12, DOI 10.3390/f12111537
   Nabais C, 2014, FORESTRY, V87, P598, DOI 10.1093/forestry/cpu021
   O'Donnell AJ, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0249959
   Oladi R., 2012, Notulae Scientia Biologicae, V4, P136
   OLADI R, 2011, IRAN TREES, V25, P425, DOI DOI 10.1007/S00468-010-0517-7
   Oladi R., 2022, IRAN J IJFPR, V14, P185, DOI [10.22034/ijf.2022.310532.1806, DOI 10.22034/IJF.2022.310532.1806]
   Oladi R, 2017, EUR J FOREST RES, V136, P345, DOI 10.1007/s10342-017-1036-5
   Oladi R, 2014, TREES-STRUCT FUNCT, V28, P493, DOI 10.1007/s00468-013-0966-x
   Oribe Y, 2003, TREES-STRUCT FUNCT, V17, P185, DOI 10.1007/s00468-002-0231-1
   Pacheco A, 2018, SCI TOTAL ENVIRON, V615, P1518, DOI 10.1016/j.scitotenv.2017.09.133
   Parhizkar P., 2023, IRAN J POPLAR RES IJ, V31, P87
   Parhizkar P, 2021, FORESTRY, V94, P691, DOI 10.1093/forestry/cpab019
   Pödör Z, 2014, ADV INTELL SYST, V282, P353, DOI 10.1007/978-3-319-06569-4_26
   Pompa-García M, 2023, J FORESTRY RES, V34, P51, DOI 10.1007/s11676-022-01484-3
   Prislan P, 2019, CLIMATIC CHANGE, V153, P181, DOI 10.1007/s10584-019-02374-0
   Prislan P, 2018, TREE PHYSIOL, V38, P186, DOI 10.1093/treephys/tpx167
   Prislan P, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01923
   Prislan P, 2013, AGR FOREST METEOROL, V180, P142, DOI 10.1016/j.agrformet.2013.06.001
   R Core Team, 2023, R LANG ENV STAT COMP
   Rahimi J, 2019, THEOR APPL CLIMATOL, V135, P545, DOI 10.1007/s00704-018-2395-7
   Ramezani E, 2023, REV PALAEOBOT PALYNO, V312, DOI 10.1016/j.revpalbo.2023.104871
   Rezaei Sangdehi S. M., 2020, J. Wood For. Sci. Technol, V27, P1, DOI [10.22069/jwfst.2019.16794.1817, DOI 10.22069/JWFST.2019.16794.1817]
   Rossi S, 2006, NEW PHYTOL, V170, P301, DOI 10.1111/j.1469-8137.2006.01660.x
   Rossi S, 2006, IAWA J, V27, P89, DOI 10.1163/22941932-90000139
   Salomón RL, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-021-27579-9
   Savage JA, 2021, NEW PHYTOL, V230, P1700, DOI 10.1111/nph.17289
   Shi SY, 2021, ECOL INDIC, V133, DOI 10.1016/j.ecolind.2021.108446
   Sundberg B, 2000, EXPTL BIOL REV, P169
   Suzuki M, 1996, IAWA J, V17, P431, DOI 10.1163/22941932-90000641
   Takahashi S, 2013, ECOL RES, V28, P615, DOI 10.1007/s11284-013-1053-x
   Talebi KS, 2014, PLANT VEG, V10, P1, DOI 10.1007/978-94-007-7371-4
   Touchan R, 2012, BIOGEOSCIENCES, V9, P965, DOI 10.5194/bg-9-965-2012
   Trifkovic V, 2022, AGR FOREST METEOROL, V327, DOI 10.1016/j.agrformet.2022.109195
   Tumajer J, 2022, AGR FOREST METEOROL, V327, DOI 10.1016/j.agrformet.2022.109234
   Tumajer J, 2021, AGR FOREST METEOROL, V311, DOI 10.1016/j.agrformet.2021.108685
   Vaganov EA, 2009, OECOLOGIA, V161, P729, DOI 10.1007/s00442-009-1421-y
   van der Maaten E, 2018, TREE PHYSIOL, V38, P1820, DOI 10.1093/treephys/tpy042
   van der Maaten E, 2012, TREES-STRUCT FUNCT, V26, P777, DOI 10.1007/s00468-011-0645-8
   Vander Mijnsbrugge K, 2021, FORESTS, V12, DOI 10.3390/f12111604
   Vitasse Y, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00541
   Wang M, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14215580
   Wood SN, 2011, J ROY STAT SOC B, V73, P3, DOI 10.1111/j.1467-9868.2010.00749.x
   Xu SX, 2023, J HYDROL, V627, DOI 10.1016/j.jhydrol.2023.130455
   Ziaco E, 2018, PLANT CELL ENVIRON, V41, P823, DOI 10.1111/pce.13152
   Ziaco E, 2016, TREE PHYSIOL, V36, P818, DOI 10.1093/treephys/tpw006
NR 93
TC 0
Z9 0
U1 4
U2 4
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0931-1890
EI 1432-2285
J9 TREES-STRUCT FUNCT
JI Trees-Struct. Funct.
PD DEC
PY 2024
VL 38
IS 6
BP 1569
EP 1580
DI 10.1007/s00468-024-02574-x
EA OCT 2024
PG 12
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA N0K2N
UT WOS:001334007200001
DA 2025-01-10
ER

PT J
AU Komelo, CK
   Fotso-Nguemo, TC
   Ngavom, Z
   Dessacka, AK
   Taguela, TN
   Yepdo, ZD
   Nghonda, JP
   Diedhiou, A
   Monkam, D
   Tchawoua, C
AF Komelo, Crepin K.
   Fotso-Nguemo, Thierry C.
   Ngavom, Zakariahou
   Dessacka, Abdon K.
   Taguela, Thierry N.
   Yepdo, Zephirin D.
   Nghonda, Jean P.
   Diedhiou, Arona
   Monkam, David
   Tchawoua, Clement
TI Evaluation of extreme precipitation events as simulated by CMIP6 models
   over Central Africa: Spatial patterns
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
ID EARTH SYSTEM MODEL; RESOLUTION VERSION; PROJECTED CHANGES; CLIMATE;
   RAINFALL; TEMPERATURE; MONSOON; FUTURE; REMO
AB Extreme precipitation events have substantial implications for water resources, ecosystems, and human populations in Central Africa (CA). Consequently, understanding the spatial variability of these events is crucial for effective climate change adaptation and water management strategies. In this study, we assess the performance of the state-of-the-art global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating extreme precipitation events over CA. By considering three observational datasets, we evaluated the ability of sixteen CMIP6 models as well their multi-model ensemble (MME), to capture the patterns of extreme precipitation events. We then focus on key metrics such as duration and intensity, based on a total of ten indices of extreme precipitation events, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The results showed that the individual models as well as the MME exhibited acceptable performance in reproducing the patterns of extreme precipitation events, especially when dealing with wet-day amount, frequency, dry spell duration and persistence of extreme precipitation over the two northern CA subregions (i.e., Sudano-Sahelian and Northern Equatorial). Moreover, the analyses revealed that CMIP6 models generally lack the ability of in simulating not only the wet spell duration, but also heavy precipitation indices, particularly over the central and southeastern CA subregions (i.e., Equatorial East and Southern Equatorial, respectively). These results highlight the remaining challenges in reproducing local-scale processes governing precipitation variability and extreme precipitation events over the region. The results of this study provide an understanding of both the strengths and limitations of the CMIP6 models over CA, which would help to improve regional climate projections and strengthen the ability of decision makers to assess the future risks associated with extreme precipitation events in the region.
C1 [Komelo, Crepin K.; Ngavom, Zakariahou; Dessacka, Abdon K.; Taguela, Thierry N.] Univ Yaounde I, Fac Sci, Dept Phys, Lab Environm Modelling & Atmospher Phys LEMAP, POB 812, Yaounde, Cameroon.
   [Komelo, Crepin K.; Dessacka, Abdon K.] Univ Bangui, Fac Sci, Dept Phys, Lab Energet Carnot LEC, POB 908, Bangui, Cent Afr Republ.
   [Fotso-Nguemo, Thierry C.; Yepdo, Zephirin D.; Nghonda, Jean P.] Natl Inst Cartog, Climate Change Res Lab CCRL, POB 157, Yaounde, Cameroon.
   [Fotso-Nguemo, Thierry C.; Ngavom, Zakariahou; Diedhiou, Arona] Univ Felix Houphou & Boigny, Eau Agr & Energie Afr & Dev Serv Climat LMI NEXUS, Lab Mixte Int Nexus Interrelat Climat, POB 463, Abidjan, Cote Ivoire.
   [Taguela, Thierry N.] Univ Illinois, Dept Earth & Environm Sci, Chicago, IL USA.
   [Nghonda, Jean P.] Univ Maroua, Higher Teacher Training Coll, Dept Geog, POB 55, Maroua, Cameroon.
   [Diedhiou, Arona] Univ Grenoble Alpes, IRD, CNRS, Grenoble INP,IGE, F-38000 Grenoble, France.
   [Monkam, David] Univ Douala, Fac Sci, Dept Phys, POB 24157, Douala, Cameroon.
   [Tchawoua, Clement] Univ Yaounde I, Fac Sci, Dept Phys, Lab Mech, POB 812, Yaounde, Cameroon.
C3 University of Yaounde I; Universite Felix Houphouet-Boigny; University
   of Illinois System; University of Illinois Chicago; University of
   Illinois Chicago Hospital; Communaute Universite Grenoble Alpes;
   Universite Grenoble Alpes (UGA); Institut National Polytechnique de
   Grenoble; Centre National de la Recherche Scientifique (CNRS); Institut
   de Recherche pour le Developpement (IRD); University of Yaounde I
RP Komelo, CK (corresponding author), Univ Yaounde I, Fac Sci, Dept Phys, Lab Environm Modelling & Atmospher Phys LEMAP, POB 812, Yaounde, Cameroon.; Komelo, CK (corresponding author), Univ Bangui, Fac Sci, Dept Phys, Lab Energet Carnot LEC, POB 908, Bangui, Cent Afr Republ.
EM crepinjuniorkomelo14@gmail.com
RI DIEDHIOU, Arona/D-2719-2009
OI Fotso-Nguemo, Thierry C./0000-0002-7321-9236; DESSACKA,
   Abdon/0009-0006-1591-339X; Ngavom, Zakariahou/0009-0003-1005-1338;
   DIEDHIOU, Arona/0000-0003-3841-1027; Taguela,
   Thierry/0000-0001-8140-125X; Nghonda, Jean-Pierre/0000-0002-0405-3906
FU Abdus Salam International Centre for Theoretical Physics (ICTP) through
   the Associates Programme
FX We would also like to thank the climate modelling groups listed in Table
   1 for producing and making their model output freely available through
   the Earth System Grid Federation's (ESGF) platforms. We gratefully
   appreciate the efforts of the LMI-NEXUS along with that of the National
   Computing Center of Cote d'Ivoire (CNCCI) during the realisation of this
   work. Thierry C. Fotso-Nguemo would like to acknowledge support from the
   Abdus Salam International Centre for Theoretical Physics (ICTP) through
   the Associates Programme (2020-2025). We are also grateful to the two
   anonymous reviewers whose comments helped to improve the quality of this
   document.
CR Agyekum J, 2022, SCI AFR, V16, DOI 10.1016/j.sciaf.2022.e01181
   Akinsanola AA, 2021, ATMOS RES, V254, DOI 10.1016/j.atmosres.2021.105509
   Ayugi B, 2021, INT J CLIMATOL, V41, P6474, DOI 10.1002/joc.7207
   Ayugi BO, 2024, ENVIRON RES LETT, V19, DOI 10.1088/1748-9326/ad416b
   Bentsen M., 2019, Ncc noresm2-mm model output prepared for cmip6 scenariomip ssp585
   Bi DH, 2020, J SO HEMISPH EARTH, V70, P225, DOI 10.1071/ES19040
   Boucher O, 2020, J ADV MODEL EARTH SY, V12, DOI 10.1029/2019MS002010
   Camberlin P, 2019, Q J ROY METEOR SOC, V145, P2115, DOI 10.1002/qj.3547
   Danabasoglu G., 2019, NCAR CESM2 model output prepared for CMIP6 LUMIP
   Diba I, 2022, ENVIRON RES COMMUN, V4, DOI 10.1088/2515-7620/ac9aa7
   Diedhiou A, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac3e5
   Dinku T, 2018, Q J ROY METEOR SOC, V144, P292, DOI 10.1002/qj.3244
   Döscher R, 2022, GEOSCI MODEL DEV, V15, P2973, DOI 10.5194/gmd-15-2973-2022
   Dosio A, 2021, EARTH SPACE SCI, V8, DOI 10.1029/2020EA001466
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Faye A, 2022, CLIM DYNAM, V58, P925, DOI 10.1007/s00382-021-05942-2
   Fita ED., 2024, J WATER RESOUR PROT, V16, P569, DOI [10.4236/jwarp.2024.168032, DOI 10.4236/JWARP.2024.168032]
   Fotso-Kamga G, 2020, INT J CLIMATOL, V40, P2891, DOI 10.1002/joc.6372
   Fotso-Nguemo TC, 2019, CLIMATIC CHANGE, V155, P339, DOI 10.1007/s10584-019-02492-9
   Fotso-Nguemo TC, 2018, ATMOS SCI LETT, V19, DOI 10.1002/asl.803
   Fotso-Nguemo TC, 2017, CLIM DYNAM, V48, P3685, DOI 10.1007/s00382-016-3294-1
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Gelaro R, 2017, J CLIMATE, V30, P5419, DOI 10.1175/JCLI-D-16-0758.1
   Golaz JC, 2022, J ADV MODEL EARTH SY, V14, DOI 10.1029/2022MS003156
   Haensler A, 2013, CLIMATIC CHANGE, V121, P349, DOI 10.1007/s10584-013-0863-8
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Horowitz LW, 2018, NOAA GFDL GFDL ESM4
   Kamsu-Tamo PH, 2014, CLIM DYNAM, V43, P3377, DOI 10.1007/s00382-014-2111-y
   Kenfack K, 2024, INT J CLIMATOL, V44, P1778, DOI 10.1002/joc.8410
   Klutse NAB, 2021, EARTH SYST ENVIRON, V5, P25, DOI 10.1007/s41748-021-00203-y
   Klutse NAB, 2016, THEOR APPL CLIMATOL, V123, P369, DOI 10.1007/s00704-014-1352-3
   Mbienda AJK, 2022, CLIM DYNAM, V58, P691, DOI 10.1007/s00382-021-05928-0
   Kuete G, 2023, CLIM DYNAM, V60, P2907, DOI 10.1007/s00382-022-06467-y
   Kuete G, 2020, CLIM DYNAM, V54, P1539, DOI 10.1007/s00382-019-05072-w
   Kundzewicz ZW, 2014, HYDROLOG SCI J, V59, P1, DOI 10.1080/02626667.2013.857411
   Mba WP, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab048
   Mboka JJM, 2021, WEATHER, V76, P347, DOI 10.1002/wea.3867
   Meehl GA, 2007, B AM METEOROL SOC, V88, P1383, DOI 10.1175/BAMS-88-9-1383
   Mishra BK, 2021, WATER-SUI, V13, DOI 10.3390/w13040490
   Moihamette F, 2024, CLIM DYNAM, V62, P25, DOI 10.1007/s00382-024-07251-w
   Moihamette F, 2022, INT J CLIMATOL, V42, P5255, DOI 10.1002/joc.7531
   Moise AF, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009250
   Müller WA, 2018, J ADV MODEL EARTH SY, V10, P1383, DOI 10.1029/2017MS001217
   Nana HN, 2024, CLIM DYNAM, V62, P1, DOI 10.1007/s00382-023-06892-7
   Ngavom Z, 2024, MODEL EARTH SYST ENV, DOI 10.1007/s40808-024-02091-3
   Novella NS, 2013, J APPL METEOROL CLIM, V52, P588, DOI 10.1175/JAMC-D-11-0238.1
   Oluwagbemi OO, 2022, APPL SCI-BASEL, V12, DOI 10.3390/app12147107
   Patricola CM, 2010, CLIM DYNAM, V35, P193, DOI 10.1007/s00382-009-0623-7
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Roehrig R, 2013, J CLIMATE, V26, P6471, DOI 10.1175/JCLI-D-12-00505.1
   Skinner CB, 2013, J GEOPHYS RES-ATMOS, V118, P3590, DOI 10.1002/jgrd.50363
   Sonkoué D, 2019, THEOR APPL CLIMATOL, V137, P2167, DOI 10.1007/s00704-018-2729-5
   Sonwa DJ., 2014, FORESTS CONGO BASIN, P99
   Taguela TN, 2024, CLIM DYNAM, V62, P8333, DOI 10.1007/s00382-022-06411-0
   Taguela TN, 2020, J GEOPHYS RES-ATMOS, V125, DOI 10.1029/2019JD031607
   Tamoffo AT, 2023, METEOROL APPL, V30, DOI 10.1002/met.2119
   Tamoffo AT, 2019, THEOR APPL CLIMATOL, V137, P2351, DOI 10.1007/s00704-018-2745-5
   Tanessong RS, 2024, METEOROL ATMOS PHYS, V136, DOI 10.1007/s00703-024-01018-y
   Tanessong RS, 2020, THEOR APPL CLIMATOL, V140, P1515, DOI 10.1007/s00704-020-03176-6
   Tang BH, 2019, NPJ CLIM ATMOS SCI, V2, DOI 10.1038/s41612-019-0103-7
   Tang Y., 2019, MOHC UKESM1. 0-LL model output prepared for CMIP6 CMIP
   Tarnavsky E, 2014, J APPL METEOROL CLIM, V53, P2805, DOI 10.1175/JAMC-D-14-0016.1
   Tatebe H, 2019, GEOSCI MODEL DEV, V12, P2727, DOI 10.5194/gmd-12-2727-2019
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Taylor KE, 2001, J GEOPHYS RES-ATMOS, V106, P7183, DOI 10.1029/2000JD900719
   Tchinda CW, 2023, SCI REP-UK, V13, DOI 10.1038/s41598-023-46346-y
   Volodin E, 2019, IPCC DDC INM INM CM5, DOI [10.26050/WDCC/AR6.C6SPINIC0-370, DOI 10.26050/WDCC/AR6.C6SPINIC0-370]
   Vondou DA, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13126803
   Wilfried PM, 2014, J CLIMATE, V27, P4245, DOI 10.1175/JCLI-D-13-00490.1
   Wu TW, 2021, GEOSCI MODEL DEV, V14, P2977, DOI 10.5194/gmd-14-2977-2021
   Yukimoto S., 2019, MRI MRI-ESM2. 0 model output prepared for CMIP6 CMIP
   Zebaze S, 2022, ACTA GEOPHYS, V70, P943, DOI 10.1007/s11600-022-00754-2
   Zebaze S, 2019, ATMOS SCI LETT, V20, DOI 10.1002/asl.926
   Zhang XB, 2011, WIRES CLIM CHANGE, V2, P851, DOI 10.1002/wcc.147
NR 75
TC 0
Z9 0
U1 1
U2 1
PU SPRINGER WIEN
PI Vienna
PA Prinz-Eugen-Strasse 8-10, A-1040 Vienna, AUSTRIA
SN 0177-798X
EI 1434-4483
J9 THEOR APPL CLIMATOL
JI Theor. Appl. Climatol.
PD NOV
PY 2024
VL 155
IS 11
BP 9579
EP 9599
DI 10.1007/s00704-024-05198-w
EA OCT 2024
PG 21
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA K5T9H
UT WOS:001325735300001
DA 2025-01-10
ER

PT J
AU Mazumder, AK
   Yadav, R
   Kumar, M
   Babu, P
   Kumar, N
   Singh, SK
   Solanke, AU
   Wani, SH
   Alalawy, AI
   Alasmari, A
   Gaikwad, KB
AF Mazumder, Amit Kumar
   Yadav, Rajbir
   Kumar, Manjeet
   Babu, Prashanth
   Kumar, Naresh
   Singh, Sanjay Kumar
   Solanke, Amolkumar U.
   Wani, Shabir H.
   Alalawy, Adel I.
   Alasmari, Abdulrahman
   Gaikwad, Kiran B.
TI Discovering novel genomic regions explaining adaptation of bread wheat
   to conservation agriculture through GWAS
SO SCIENTIFIC REPORTS
LA English
DT Article
DE Genome-wide association studies (GWAS); Conservation agriculture;
   Physiological adaptations; Chlorophyll fluorescence; Wheat
ID CANOPY TEMPERATURE DEPRESSION; CLIMATE-CHANGE ADAPTATION; GRAIN-YIELD;
   TRANSCRIPTION FACTOR; TRITICUM-AESTIVUM; PHYSIOLOGICAL TRAITS; DROUGHT
   RESISTANCE; BREEDING WHEAT; RICE; ARABIDOPSIS
AB To sustainably increase wheat yield to meet the growing world population's food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.
C1 [Mazumder, Amit Kumar; Yadav, Rajbir; Kumar, Manjeet; Babu, Prashanth; Kumar, Naresh; Singh, Sanjay Kumar; Gaikwad, Kiran B.] ICAR Indian Agr Res Inst, Div Genet, New Delhi 110012, India.
   [Solanke, Amolkumar U.] Natl Inst Plant Biotechnol, New Delhi 110012, India.
   [Wani, Shabir H.] Mt Res Ctr Field Crops, Khudwani 192101, India.
   [Wani, Shabir H.] Sher E Kashmir Univ Agr Sci & Technol Kashmir SKUA, Shalimar, Jammu Kashmir, India.
   [Alalawy, Adel I.] Univ Tabuk, Fac Sci, Dept Biochem, Tabuk, Saudi Arabia.
   [Alasmari, Abdulrahman] Univ Tabuk, Fac Sci, Dept Biol, Tabuk, Saudi Arabia.
C3 Indian Council of Agricultural Research (ICAR); ICAR - Indian
   Agricultural Research Institute; Indian Council of Agricultural Research
   (ICAR); ICAR - National Institute For Plant Biotechnology (NIPB);
   Sher-e-Kashmir University of Agricultural Sciences & Technology of
   Kashmir (SKUAST Kashmir); University of Tabuk; University of Tabuk
RP Gaikwad, KB (corresponding author), ICAR Indian Agr Res Inst, Div Genet, New Delhi 110012, India.
EM gaikwadkb@gmail.com
RI Wani, Shabir/B-4599-2014; Alasmari, Abdulrahman/HSG-4726-2023; singh,
   sanjay/F-1870-2016; ALALAWY, ADEL/HSE-5556-2023; Gaikwad,
   Kiran/AAX-4963-2021
OI kumar, Manjeet/0000-0002-9253-7766
FU Bill and Melinda Gates Foundation; ICAR-Indian Agricultural Research
   Institute, New Delhi
FX The authors would like to thank ICAR-Indian Agricultural Research
   Institute, New Delhi for providing the resources to conduct the
   experiments.
CR Ahmad S, 2021, BIOMOLECULES, V11, DOI 10.3390/biom11060771
   Alptekin B, 2021, THEOR APPL GENET, V134, P351, DOI 10.1007/s00122-020-03701-1
   Alvarado G, 2020, CROP J, V8, P745, DOI 10.1016/j.cj.2020.03.010
   Aravind J, 2023, **DATA OBJECT**, DOI 10.5281/ZENODO.8015094
   Arias-Gaguancela O, 2022, PLANT DIRECT, V6, DOI 10.1002/pld3.421
   Arora R, 2007, BMC GENOMICS, V8, DOI 10.1186/1471-2164-8-242
   Aryal JP, 2016, AGR ECOSYST ENVIRON, V233, P325, DOI 10.1016/j.agee.2016.09.013
   Asseng S, 2015, NAT CLIM CHANGE, V5, P143, DOI [10.1038/nclimate2470, 10.1038/NCLIMATE2470]
   Baader WJ, 1996, J PHOTOCH PHOTOBIO A, V101, P49, DOI 10.1016/S1010-6030(96)04424-3
   Baud Sebastien, 2008, Arabidopsis Book, V6, pe0113, DOI 10.1199/tab.0113
   Baye A, 2020, COGENT FOOD AGR, V6, DOI 10.1080/23311932.2020.1752603
   Bhatia A., 2022, Conservation Agriculture in India, P223, DOI [10.4324/9781003292487-14, DOI 10.4324/9781003292487-14]
   Bhattacharyya R, 2015, EUR J AGRON, V70, P11, DOI 10.1016/j.eja.2015.06.006
   Bradbury PJ, 2007, BIOINFORMATICS, V23, P2633, DOI 10.1093/bioinformatics/btm308
   Byrne SL, 2009, PLANT GROWTH REGUL, V59, P215, DOI 10.1007/s10725-009-9407-7
   Castelán-Muñoz N, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00853
   Chen J, 2003, PLANT MOL BIOL, V52, P579, DOI 10.1023/A:1024854101965
   Chen JP, 2018, BMC PLANT BIOL, V18, DOI [10.1186/s12870-018-1330-5, 10.1186/s12913-018-3288-2, 10.1186/s12887-018-1203-y, 10.1186/s12870-018-1228-2, 10.1186/s12879-018-3216-4]
   Cheng YQ, 2019, TREE GENET GENOMES, V15, DOI 10.1007/s11295-019-1328-7
   Chu SS, 2018, INT J MOL SCI, V19, DOI 10.3390/ijms19061688
   Craufurd PQ, 2009, J EXP BOT, V60, P2529, DOI 10.1093/jxb/erp196
   Cui YW, 2022, PLANT COMMUN, V3, DOI 10.1016/j.xplc.2021.100273
   Dai N, 1999, PLANT CELL, V11, P1253, DOI 10.1105/tpc.11.7.1253
   Datta K, 2012, PLANT BIOTECHNOL J, V10, P579, DOI 10.1111/j.1467-7652.2012.00688.x
   Devkota M, 2021, EXP AGR, V57, P126, DOI 10.1017/S0014479721000107
   Ding W, 2023, BIOTECHNOL BIOF BIOP, V16, DOI 10.1186/s13068-023-02352-w
   Erenstein Olaf, 2022, Wheat improvement: food security in a changing climate, P47, DOI 10.1007/978-3-030-90673-3_4
   Evanno G, 2005, MOL ECOL, V14, P2611, DOI 10.1111/j.1365-294X.2005.02553.x
   Fan MH, 2022, AQUACULTURE, V557, DOI 10.1016/j.aquaculture.2022.738344
   Finegan C, 2022, FRONT PLANT SCI, V12, DOI 10.3389/fpls.2021.800326
   Flint-Garcia SA, 2003, ANNU REV PLANT BIOL, V54, P357, DOI 10.1146/annurev.arplant.54.031902.134907
   Gaikwad KB., 2022, New Horizons in Wheat and Barley Research
   Gaikwad KB, 2023, INDIAN J GENET PL BR, V83, P32, DOI 10.31742/ISGPB.83.1.5
   Gao MJ, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8243
   Gao YT, 2021, EUPHYTICA, V217, DOI 10.1007/s10681-021-02795-y
   Gao ZX, 2020, IRRIGATION SCI, V38, P365, DOI 10.1007/s00271-020-00678-z
   Gill HS, 2022, THEOR APPL GENET, V135, P2953, DOI 10.1007/s00122-022-04160-6
   Gilmore AM, 1996, PHOTOCHEM PHOTOBIOL, V64, P552, DOI 10.1111/j.1751-1097.1996.tb03105.x
   Gorfer LM, 2022, ACTA HORTIC, V1353, P9, DOI 10.17660/ActaHortic.2022.1353.2
   Guidi L, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00174
   Guo ZF, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-31977-3
   Gupta PK., 2019, Association Mapping in Plants in the Post-GWAS Genomics Era, DOI [10.1016/bs.adgen.2018.12.001, DOI 10.1016/BS.ADGEN.2018.12.001]
   Gupta R, 2017, CLIMATIC CHANGE, V140, P593, DOI 10.1007/s10584-016-1878-8
   Han X, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.1065766
   Herrera JM, 2013, CROP SCI, V53, P1845, DOI 10.2135/cropsci2013.01.0071
   Holland JB, 2002, PL BRED RE, V22, P9
   Hu HH, 2006, P NATL ACAD SCI USA, V103, P12987, DOI 10.1073/pnas.0604882103
   Huang JQ, 2018, RICE, V11, DOI 10.1186/s12284-018-0235-0
   Huang M, 2019, GIGASCIENCE, V8, DOI 10.1093/gigascience/giy154
   Huang ZH, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.931063
   Huseynova IM, 2009, BIOCHEMISTRY-MOSCOW+, V74, P903, DOI 10.1134/S0006297909080124
   Hussain Q, 2021, BIOMOLECULES, V11, DOI 10.3390/biom11081159
   Jagadish SVK, 2008, CROP SCI, V48, P1140, DOI 10.2135/cropsci2007.10.0559
   Jaskune K, 2022, CROP J, V10, P508, DOI 10.1016/j.cj.2021.07.005
   Jat RK, 2014, FIELD CROP RES, V164, P199, DOI 10.1016/j.fcr.2014.04.015
   Jeena GS, 2019, PLANT MOL BIOL, V100, P351, DOI 10.1007/s11103-019-00872-4
   Jeong JS, 2013, PLANT BIOTECHNOL J, V11, P101, DOI 10.1111/pbi.12011
   Jiang Q, 2014, PLANT SCI, V215, P172, DOI 10.1016/j.plantsci.2013.11.003
   Kang JY, 2002, PLANT CELL, V14, P343, DOI 10.1105/tpc.010362
   Khan A, 2020, PAK J BOT, V52, P1981, DOI 10.30848/RT132020-6(30)
   Khan H, 2022, FRONT GENET, V13, DOI 10.3389/fgene.2022.982589
   Kim JY, 2021, PLANT PHYSIOL, V187, P1893, DOI 10.1093/plphys/kiab228
   Kim SR, 2013, MOL CELLS, V35, P402
   Ko SS, 2021, J EXP BOT, V72, P4888, DOI 10.1093/jxb/erab190
   Krishnappa G, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-15992-z
   Kromdijk J, 2020, J EXP BOT, V71, P318, DOI 10.1093/jxb/erz442
   Kuhlgert S, 2016, ROY SOC OPEN SCI, V3, DOI 10.1098/rsos.160592
   Kumar A, 2018, INDIAN J GENET PL BR, V78, P309, DOI 10.31742/IJGPB.78.3.1
   Kumar K, 2021, 3 BIOTECH, V11, DOI 10.1007/s13205-020-02605-7
   Kumar S, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.549743
   Li L, 2021, INT J MOL SCI, V22, DOI 10.3390/ijms22094885
   Li LH, 2023, J PLANT GROWTH REGUL, V42, P2212, DOI 10.1007/s00344-022-10694-2
   Li L, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0119425
   Liu J, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01584
   Liu L, 2021, SMALL STRUCT, V2, DOI 10.1002/sstr.202000125
   Liu MT, 2022, DNA CELL BIOL, V41, P564, DOI 10.1089/dna.2021.1144
   Liu YH, 2023, HORTIC PLANT J, V9, P293, DOI 10.1016/j.hpj.2022.04.002
   Lloret A, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-00471-7
   Lohani N, 2021, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.622748
   Ma LQ, 2021, INT J MOL SCI, V22, DOI 10.3390/ijms22115849
   Ma WW, 2022, PLANTS-BASEL, V11, DOI 10.3390/plants11172206
   Misra AN, 2014, NITRIC OXIDE-BIOL CH, V39, P35, DOI 10.1016/j.niox.2014.04.003
   Mittal S., 2022, New Horizons in Wheat and Barley Research
   Mohan D, 2022, INDIAN J GENET PL BR, V82, P31, DOI 10.31742/IJGPB.82.1.5
   Müller B, 2015, CURR BIOL, V25, P3126, DOI 10.1016/j.cub.2015.10.038
   Murphy CD, 2017, LIMNOL OCEANOGR-METH, V15, P54, DOI 10.1002/lom3.10142
   Narendra MC, 2021, CZECH J GENET PLANT, V57, P43, DOI 10.17221/63/2020-CJGPB
   Nazari M, 2020, J PLANT INTERACT, V15, P180, DOI 10.1080/17429145.2020.1758812
   Ogawa M, 2009, PLANT CELL, V21, P216, DOI 10.1105/tpc.108.063768
   Ortiz R, 2008, AGR ECOSYST ENVIRON, V126, P46, DOI 10.1016/j.agee.2008.01.019
   Pankaj YK, 2024, PLANT MOL BIOL REP, V42, P369, DOI 10.1007/s11105-022-01357-3
   Pankaj YK, 2022, CEREAL RES COMMUN, DOI 10.1007/s42976-021-00234-1
   Parrotta L, 2023, INT J MOL SCI, V24, DOI 10.3390/ijms241512413
   Paul P, 2020, GENES-BASEL, V11, DOI 10.3390/genes11060650
   Peng XJ, 2015, BMC GENOMICS, V16, DOI 10.1186/s12864-015-2047-6
   Pradhan A, 2018, AGR SYST, V163, P27, DOI 10.1016/j.agsy.2017.01.002
   Pradhan S, 2020, BMC GENOMICS, V21, DOI 10.1186/s12864-020-6717-7
   Prasad PVV, 2008, CROP SCI, V48, P2372, DOI 10.2135/cropsci2007.12.0717
   Pritchard JK, 2000, GENETICS, V155, P945
   Qian M, 2016, INT J MOL SCI, V17, DOI 10.3390/ijms17111933
   Qu JZ, 2021, MOL GENET GENOMICS, V296, P615, DOI 10.1007/s00438-021-01761-6
   Rahman MA., 2009, BANGLADESH J AGR RES, V34, P360, DOI [10.3329/bjar.v34i3.3961, DOI 10.3329/BJAR.V34I3.3961]
   Ranjan R, 2021, INDIAN J GENET PL BR, V81, P24, DOI 10.31742/IJGPB.81.1.2
   Rasheed A, 2014, BMC PLANT BIOL, V14, DOI 10.1186/1471-2229-14-128
   Redillas MCFR, 2012, PLANT BIOTECHNOL J, V10, P792, DOI 10.1111/j.1467-7652.2012.00697.x
   Richards RA, 2006, AGR WATER MANAGE, V80, P197, DOI 10.1016/j.agwat.2005.07.013
   Riou C, 2002, PLANT PHYSIOL BIOCH, V40, P431, DOI 10.1016/S0981-9428(02)01390-6
   Robson JK, 2023, J EXP BOT, V74, P5181, DOI 10.1093/jxb/erad239
   Rojas CA, 2009, PLANT MOL BIOL, V71, P307, DOI 10.1007/s11103-009-9525-7
   Roy C, 2021, CZECH J GENET PLANT, V57, P140, DOI 10.17221/45/2021-CJGPB
   Sahu TK, 2023, bioRxiv, DOI [10.1101/2023.02.25.530014, 10.1101/2023.02.25.530014, DOI 10.1101/2023.02.25.530014]
   Sapkota TB, 2015, J INTEGR AGR, V14, P1524, DOI 10.1016/S2095-3119(15)61093-0
   Sattar A, 2023, FRONT PLANT SCI, V14, DOI 10.3389/fpls.2023.1224334
   Saxena D. C., 2014, Indian Journal of Plant Physiology, V19, P43, DOI 10.1007/s40502-014-0071-1
   Sendhil R., 2022, New Horizons in Wheat and Barley Research
   Shailendra Singh Shailendra Singh, 2005, Indian Journal of Weed Science, V37, P51
   Shamloo-Dashtpagerdi R, 2018, MOL BIOL REP, V45, P1111, DOI 10.1007/s11033-018-4262-0
   Shi XY, 2021, BIOCHEM BIOPH RES CO, V548, P189, DOI 10.1016/j.bbrc.2021.02.047
   Shin JH., 2006, J. Stat. Softw, DOI [10.1863/jss.v016.c03, DOI 10.1863/JSS.V016.C03]
   Shirvani F, 2023, ACTA ECOL SINICA, V43, P810, DOI 10.1016/j.chnaes.2022.10.009
   Silva-Pérez V, 2020, J EXP BOT, V71, P2299, DOI 10.1093/jxb/erz439
   Singh A, 2014, SOIL TILL RES, V140, P98, DOI 10.1016/j.still.2014.03.002
   Singh BK, 2023, PLANTS-BASEL, V12, DOI 10.3390/plants12081697
   Strejcková B, 2023, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.1106164
   Süssenbacher I, 2019, PHOTOSYNTH RES, V142, P69, DOI 10.1007/s11120-019-00649-2
   Sukumaran S, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.00081
   Tahmasebi S, 2017, GENOME, V60, P26, DOI 10.1139/gen-2016-0017
   Tamang BG, 2015, INT J MOL SCI, V16, P30164, DOI 10.3390/ijms161226226
   Tanabata T, 2012, PLANT PHYSIOL, V160, P1871, DOI 10.1104/pp.112.205120
   Teaster ND, 2012, FRONT PLANT SCI, V3, DOI 10.3389/fpls.2012.00032
   Teo ZWN, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.01474
   Tesfaye K, 2017, THEOR APPL CLIMATOL, V130, P959, DOI 10.1007/s00704-016-1931-6
   Thakur A, 2015, PLANT SIGNAL BEHAV, V10, DOI 10.1080/15592324.2015.1030100
   Thapa S, 2018, FIELD CROP RES, V217, P11, DOI 10.1016/j.fcr.2017.12.005
   Trethowan RM, 2012, FIELD CROP RES, V132, P76, DOI 10.1016/j.fcr.2011.10.015
   Wang JB, 2021, GENOM PROTEOM BIOINF, V19, P629, DOI 10.1016/j.gpb.2021.08.005
   Wang JC, 2013, J EXP BOT, V64, P3453, DOI 10.1093/jxb/ert187
   Wei T, 2021, R package 'corrplot': visualization of a correlation matrix (Version 0.92)
   Wheeler TR, 2000, AGR ECOSYST ENVIRON, V82, P159, DOI 10.1016/S0167-8809(00)00224-3
   Xu ZY, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.983650
   Xu ZP, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-12903-5
   Yadav R, 2017, INDIAN J GENET PL BR, V77, P185, DOI 10.5958/0975-6906.2017.00026.8
   Yang ZK, 2014, ENVIRON MICROBIOL, V16, P1793, DOI 10.1111/1462-2920.12411
   Ye JL, 2020, PLANTA, V252, DOI 10.1007/s00425-020-03435-w
   Yu Q, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.882655
   ZADOKS JC, 1974, WEED RES, V14, P415, DOI 10.1111/j.1365-3180.1974.tb01084.x
   Zeng DY, 2022, INT J MOL SCI, V23, DOI 10.3390/ijms23063390
   Zhang J, 2017, J EXP BOT, V68, P5615, DOI 10.1093/jxb/erx360
   Zhang XH, 2022, SCI HORTIC-AMSTERDAM, V297, DOI 10.1016/j.scienta.2022.110962
   Zhang Y, 2021, REMOTE SENS ENVIRON, V267, DOI 10.1016/j.rse.2021.112724
   Zhang ZL, 2011, P NATL ACAD SCI USA, V108, P2160, DOI 10.1073/pnas.1012232108
   Zhao M, 2023, INT J MOL SCI, V24, DOI 10.3390/ijms24010798
   Zheng SY, 2021, BMC PLANT BIOL, V21, DOI 10.1186/s12870-021-03343-5
   Zhu YH, 2016, J BIOL CHEM, V291, P18689, DOI 10.1074/jbc.M116.721175
NR 154
TC 0
Z9 0
U1 0
U2 0
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD JUL 16
PY 2024
VL 14
IS 1
AR 16351
DI 10.1038/s41598-024-66903-3
PG 21
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA J5E8Q
UT WOS:001337302400077
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Congedo, PM
   Albanese, PM
   D'Agostino, D
   Baglivo, C
AF Congedo, Paolo Maria
   Albanese, Paola Maria
   D'Agostino, Delia
   Baglivo, Cristina
TI The role of total solar energy transmittance for normal incidence of the
   glazed system in climate change adaptation under Italy energy efficiency
   policies
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Glass; Solar Factor; Climate Change; Building Resilience; Energy
   efficiency Policy; Thermal Performance Index
ID BUILDINGS; DESIGN; IMPACT; COMFORT
AB This study investigates the effectiveness of envelope regulations in mitigating climate change impact on building energy demand in different locations and Representative Concentration Pathway (RCP) scenarios. It aims to assess the building thermal performance (EPtot,nd) in compliance with main Italian energy policies (issued in 2005, 2015, 2020). It specifically examines how variations in total solar energy transmittance of glazed systems (ggl,n) impact heat regulation and overall energy efficiency. Results are variable depending on the national climate zone (from A to F) and related standards. Whereas climate zone E does not show significant gains from ggl,n modifications, in zone A reducing ggl,n (from 0.67 to 0.50) enhances resilience in buildings adhering to 2005 regulation (L.D. 192/2005). In climate zone C, ggl,n reduction benefits all standards, while in zone B this adjustment affects buildings following 2020 regulation (M.D. 06/08/2020), particularly under RCP 8.5. In climate zone F, decreasing ggl,n results in higher EPtot,nd, thereby compromising resilience. It is observed that buildings designed in accordance with L.D. 192/2005, compared to other regulations, show a smaller variation of EPtot,nd over time. In particular, moving from 2020 to 2070, climate zone BSh (Koppen climate classification) is the climate zone that sees the largest EPtot,nd increases over the years, while Cfc is the only zone that shows EPtot, nd decreases in all scenarios. For the other zones, a mixed behaviour is observed, with heterogeneous variations and results. Due to climate change, increased insulation in warm areas has contributed to an increase in overall annual consumption. Effective regulatory planning requires a comprehensive future climate assessment to optimize building energy performance.
C1 [Congedo, Paolo Maria; Albanese, Paola Maria; Baglivo, Cristina] Univ Salento, Dept Engn Innovat, I-73100 Lecce, Italy.
   [D'Agostino, Delia] European Commiss, Joint Res Ctr JRC, Ispra, VA, Italy.
C3 University of Salento; European Commission Joint Research Centre; EC JRC
   ISPRA Site
RP Baglivo, C (corresponding author), Univ Salento, Dept Engn Innovat, I-73100 Lecce, Italy.
EM cristina.baglivo@unisalento.it
RI Baglivo, Cristina/N-2822-2019; Congedo, Paolo Maria/N-8307-2015
OI Congedo, Paolo Maria/0000-0002-7271-8586; Baglivo,
   Cristina/0000-0001-9553-6382; Albanese, Paola Maria/0009-0002-7147-3801
CR 'Agostino D, 2024, ENERGY, V288, DOI 10.1016/j.energy.2023.129886
   [Anonymous], Koppen-Geiger Explorer
   [Anonymous], 2020, DM 6/8/2020, Italian Ministerial Decree, Requisiti tecnici per l'accesso alle detrazioni fiscali per la riqualificazione energetica degli edifici - cd Ecobonus
   [Anonymous], 2006, Directive 2006/32/EC of the European Parliament and of the Council of 5 April 2006 on energy end-use efficiency and energy services and repealing Council Directive 93/76/EEC
   [Anonymous], 2012, Meteonorm - Global Meteorological Database
   [Anonymous], 2023, Directive (EU) 2023/1791 of the European Parliament and of the Council of 13 September 2023 on energy efficiency and amending Regulation (EU) 2023/955
   [Anonymous], 2015, M.D. 26/06/2015, Italian Ministerial Decree, "Applicazione delle metodologie di calcolo delle prestazioni energetiche e definizione delle prescrizioni e dei requisiti minimi degli edifici
   [Anonymous], 2010, L.D. 192/2005, Italian Legislative Decree, Attuazione della direttiva (UE) 2018/ 844, che modifica la direttiva 2010/31/UE sulla prestazione energetica nell'edilizia e la direttiva 2012/27/UE sull'efficienza energetica, della direttiva 2010/31/UE, sulla prestazione energetica nell'edilizia, e della direttiva 2002/91/ CE relativa al rendimento energetico nell'edilizia, (In Italian
   [Anonymous], 2014, Technology Roadmap Energy Efficient Building Envelopes
   [Anonymous], 2009, Directive 2009/125/EC of the European Parliament and of the Council of 21 October 2009 establishing a framework for the setting of ecodesign requirements for energy -related products
   Ascione F, 2022, ENERG BUILDINGS, V262, DOI 10.1016/j.enbuild.2022.112004
   Baglivo C, 2023, J CLEAN PROD, V411, DOI 10.1016/j.jclepro.2023.137345
   Baglivo C, 2022, ENERGY, V238, DOI 10.1016/j.energy.2021.121641
   Baglivo C, 2021, APPL SCI-BASEL, V11, DOI 10.3390/app11146664
   Baglivo C, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116375
   Beck HE, 2023, SCI DATA, V10, DOI 10.1038/s41597-023-02549-6
   Chan KT, 1998, APPL ENERG, V60, P21, DOI 10.1016/S0306-2619(98)00021-X
   Ciancio V, 2020, SUSTAIN CITIES SOC, V60, DOI 10.1016/j.scs.2020.102213
   cmcc, Report CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici) Analisi del Rischio, I cambiamenti climatici in Italia
   Congedo PM, 2023, ENERG CONVERS MANAGE, V276, DOI 10.1016/j.enconman.2022.116554
   Congedo PM, 2021, J BUILD ENG, V42, DOI 10.1016/j.jobe.2021.103057
   Cristina Baglivo, 2023, Woodhead Publishing Series in Civil and structural engineering, adapting the built environment for climate change, P229, DOI [10.1016/B978-0-323-95336-8.00003-2, DOI 10.1016/B978-0-323-95336-8.00003-2]
   Cuce E, 2015, RENEW SUST ENERG REV, V41, P695, DOI 10.1016/j.rser.2014.08.084
   D'Agostino D, 2022, ENERGY, V240, DOI 10.1016/j.energy.2021.122479
   D'Agostino D, 2023, SUSTAIN CITIES SOC, V92, DOI 10.1016/j.scs.2023.104461
   D'Agostino D, 2017, ENERGIES, V10, DOI 10.3390/en10050658
   D'Amico A, 2019, APPL ENERG, V242, P1285, DOI 10.1016/j.apenergy.2019.03.167
   De Luca G, 2022, ENERGY REP, V8, P7349, DOI 10.1016/j.egyr.2022.05.120
   De Masi RF, 2023, ENERG BUILDINGS, V292, DOI 10.1016/j.enbuild.2023.113177
   Díaz-López C, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103223
   Economidou M, 2020, ENERG BUILDINGS, V225, DOI 10.1016/j.enbuild.2020.110322
   European Commission, 2023, Directive 2012/27/EU of the European parliament and of the council of 25 october 2012 on energy efficiency, amending directives 2009/ 125/EC and 2010/30/EU and repealing directives 2004/8/EC and 2006/32/EC
   Gercek M, 2019, SUSTAIN CITIES SOC, V48, DOI 10.1016/j.scs.2019.101580
   Goia F, 2018, SOL ENERGY, V166, P458, DOI 10.1016/j.solener.2018.03.058
   Hawila AA, 2019, BUILD ENVIRON, V157, P47, DOI 10.1016/j.buildenv.2019.04.027
   Jafarpur P, 2021, J BUILD ENG, V42, DOI 10.1016/j.jobe.2021.102725
   Kini PG, 2022, ENERGY REP, V8, P616, DOI 10.1016/j.egyr.2022.10.182
   Koengkan M, 2022, ENERGY, V241, DOI 10.1016/j.energy.2021.122895
   Kumar D, 2022, CLEAN ENG TECHNOL, V11, DOI 10.1016/j.clet.2022.100555
   Malvoni M, 2016, ENERGY, V111, P430, DOI 10.1016/j.energy.2016.06.002
   Marinoski DL, 2012, BUILD ENVIRON, V47, P232, DOI 10.1016/j.buildenv.2011.07.017
   Matera N, 2022, ENERGIES, V15, DOI 10.3390/en15249546
   Nejat P, 2015, RENEW SUST ENERG REV, V43, P843, DOI 10.1016/j.rser.2014.11.066
   Oliveti G, 2011, ENERG BUILDINGS, V43, P269, DOI 10.1016/j.enbuild.2010.11.009
   Pachauri RK., 2015, CLIMATE CHANGE 2014, P151
   Poirazis H, 2008, ENERG BUILDINGS, V40, P1161, DOI 10.1016/j.enbuild.2007.10.011
   Russo MA, 2022, SUSTAIN ENERGY TECHN, V52, DOI 10.1016/j.seta.2022.102283
   Salata F, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103518
   Skillington K, 2022, ENERG POLICY, V168, DOI 10.1016/j.enpol.2022.112920
   Thalfeldt M, 2013, ENERG BUILDINGS, V67, P309, DOI 10.1016/j.enbuild.2013.08.027
   UNI EN ISO, 2008, UNI EN ISO 15927-6
   UNI/TS, 2014, UNI/TS 11300-1
   Vanhoutteghem L, 2015, ENERG BUILDINGS, V102, P149, DOI 10.1016/j.enbuild.2015.05.018
   Yang YC, 2021, APPL ENERG, V298, DOI 10.1016/j.apenergy.2021.117246
   Yildiz Y, 2011, ENERGY, V36, P4287, DOI 10.1016/j.energy.2011.04.013
   Zomorodian ZS, 2017, ENERG BUILDINGS, V134, P80, DOI 10.1016/j.enbuild.2016.10.018
NR 56
TC 1
Z9 1
U1 2
U2 2
PU ELSEVIER SCIENCE SA
PI LAUSANNE
PA PO BOX 564, 1001 LAUSANNE, SWITZERLAND
SN 0378-7788
EI 1872-6178
J9 ENERG BUILDINGS
JI Energy Build.
PD MAR 15
PY 2024
VL 307
AR 113944
DI 10.1016/j.enbuild.2024.113944
EA FEB 2024
PG 20
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA KB3M2
UT WOS:001177461600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Cascone, S
   Leuzzo, A
AF Cascone, Stefano
   Leuzzo, Alessia
TI Thermal Comfort in the Built Environment: A Digital Workflow for the
   Comparison of Different Green Infrastructure Strategies
SO ATMOSPHERE
LA English
DT Article
DE early-stage design; parametric model; climate change adaptation; human
   wellbeing; greenspaces; UTCI
ID URBAN; DESIGN; VEGETATION; BUILDINGS; ECOSYSTEM; DAYLIGHT; HEALTH;
   IMPACT
AB The green transformation of the built environment is aimed at improving sustainability and can be supported by digitalization, which has become a significant tool to support the supply, integration, and management of information throughout the construction life cycle. In addition, climate change highly affects human comfort in the built environment and different strategies should be evaluated for adapting cities. This paper developed a digital workflow by integrating existing tools (i.e., Grasshopper, Ladybug, Honeybee, and Dragonfly) to evaluate how different green infrastructure strategies affected the thermal comfort by reducing the UTCI. The workflow was applied to a typical historical urban context (Catania, South of Italy), consisting of a square surrounded by three-floor buildings. Three basic scenarios were created that depended on the pavement material used in the built environment: a black stone pavement (reference material from Mount Etna), a permeable pavement, and grass. These three scenarios were combined with different green infrastructure strategies: tree pattern on the square, green walls and green roofs on the surrounding buildings, and the integrations of all these above-mentioned strategies. The results demonstrated that the integration of different green strategies (a grass square instead of pavement, with trees, and green walls and green roofs) increased the thermal comfort by reducing the UTCI by more than 8 degrees C compared to the existing urban context (black stone pavement and building envelope). However, this temperature reduction was highly affected by the location of the human body into the urban context and by the evaporation rates from vegetation. The workflow developed will be useful for designers to evaluate the effectiveness of different green strategies during the early-design stage in mitigating and adapting cities to climate change.
C1 [Cascone, Stefano; Leuzzo, Alessia] Mediterranea Univ Reggio Calabria, Dept Architecture & Terr, Via Univ 25, I-89124 Reggio Di Calabria, Italy.
C3 Universita Mediterranea di Reggio Calabria
RP Cascone, S (corresponding author), Mediterranea Univ Reggio Calabria, Dept Architecture & Terr, Via Univ 25, I-89124 Reggio Di Calabria, Italy.
EM stefano.cascone@unirc.it
RI Cascone, Stefano/J-1927-2019
OI Cascone, Stefano/0000-0002-6854-937X
CR Afshari A, 2017, ENERG BUILDINGS, V157, P204, DOI 10.1016/j.enbuild.2017.01.008
   Alavipanah S, 2015, SUSTAINABILITY-BASEL, V7, P4689, DOI 10.3390/su7044689
   Blau ML, 2018, LAND-BASEL, V7, DOI 10.3390/land7040141
   Blazejczyk K, 2012, INT J BIOMETEOROL, V56, P515, DOI 10.1007/s00484-011-0453-2
   Cascone Santi Maria, 2020, Sustainability in Energy and Buildings. Proceedings of SEB 2019. Smart Innovation, Systems and Technologies (SIST 163), P309, DOI 10.1007/978-981-32-9868-2_26
   Cascone S, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15065548
   Cascone S, 2022, J CLEAN PROD, V380, DOI 10.1016/j.jclepro.2022.135032
   Cascone S, 2022, ENERG BUILDINGS, V273, DOI 10.1016/j.enbuild.2022.112427
   De Carvalho RM, 2019, ENVIRON POLLUT, V245, P844, DOI 10.1016/j.envpol.2018.10.114
   Dong J, 2022, SCI TOTAL ENVIRON, V834, DOI 10.1016/j.scitotenv.2022.155307
   Fahmy M, 2019, CLIMATE, V7, DOI 10.3390/cli7010001
   Faivre N, 2017, ENVIRON RES, V159, P509, DOI 10.1016/j.envres.2017.08.032
   Farrell C, 2022, URBAN FOR URBAN GREE, V76, DOI 10.1016/j.ufug.2022.127732
   Gholami M, 2022, LAND-BASEL, V11, DOI 10.3390/land11111917
   González J, 2015, BUILDINGS, V5, P560, DOI 10.3390/buildings5020560
   Gu H, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13122016
   Hamdan DMA, 2019, ENERG BUILDINGS, V200, P86, DOI 10.1016/j.enbuild.2019.07.028
   Heaviside Clare, 2017, Curr Environ Health Rep, V4, P296, DOI 10.1007/s40572-017-0150-3
   Ibrahim Y, 2021, ENERGIES, V14, DOI 10.3390/en14134026
   Jamei E, 2020, RENEW SUST ENERG REV, V134, DOI 10.1016/j.rser.2020.110362
   Johansson E, 2014, URBAN CLIM, V10, P346, DOI 10.1016/j.uclim.2013.12.002
   Kandya A, 2018, ENERG BUILDINGS, V164, P266, DOI 10.1016/j.enbuild.2018.01.014
   Khidmat Rendy Perdana, 2021, IOP Conference Series: Earth and Environmental Science, DOI 10.1088/1755-1315/830/1/012008
   Lin HK, 2023, J ASIAN ARCHIT BUILD, V22, P1317, DOI 10.1080/13467581.2022.2081574
   Lobaccaro G, 2018, ENERG BUILDINGS, V175, P235, DOI 10.1016/j.enbuild.2018.06.066
   Milosevic DD, 2017, URBAN FOR URBAN GREE, V23, P113, DOI 10.1016/j.ufug.2017.03.011
   Motamedi S, 2017, ENERG BUILDINGS, V138, P655, DOI 10.1016/j.enbuild.2016.12.045
   Ouldboukhitine SE, 2011, BUILD ENVIRON, V46, P2624, DOI 10.1016/j.buildenv.2011.06.021
   Perini K, 2017, ENERG BUILDINGS, V152, P373, DOI 10.1016/j.enbuild.2017.07.061
   Pisello AL, 2017, SOL ENERGY, V144, P660, DOI 10.1016/j.solener.2017.01.068
   Rosso F, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13052881
   Santiago-Ramos J, 2022, APPL SPAT ANAL POLIC, V15, P1115, DOI 10.1007/s12061-022-09441-7
   Schibuola L, 2022, ENERG BUILDINGS, V273, DOI 10.1016/j.enbuild.2022.112368
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   van den Bosch M, 2017, ENVIRON RES, V158, P373, DOI 10.1016/j.envres.2017.05.040
   Wang JY, 2023, ENVIRON TECHNOL INNO, V29, DOI 10.1016/j.eti.2022.102965
   Wei D, 2022, SUSTAIN CITIES SOC, V77, DOI 10.1016/j.scs.2021.103535
   Yang B, 2013, INT J ENV RES PUB HE, V10, P5433, DOI 10.3390/ijerph10115433
   Zamani Z, 2018, RENEW SUST ENERG REV, V93, P580, DOI 10.1016/j.rser.2018.05.055
   Zhang LW, 2016, SOL ENERGY, V132, P38, DOI 10.1016/j.solener.2016.02.053
   Zhao QS, 2018, URBAN FOR URBAN GREE, V32, P81, DOI 10.1016/j.ufug.2018.03.022
   Zölch T, 2016, URBAN FOR URBAN GREE, V20, P305, DOI 10.1016/j.ufug.2016.09.011
NR 42
TC 10
Z9 10
U1 6
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD APR
PY 2023
VL 14
IS 4
AR 685
DI 10.3390/atmos14040685
PG 17
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA E8UP4
UT WOS:000978230400001
OA gold
DA 2025-01-10
ER

PT J
AU Gordu, F
   Nachabe, MH
AF Gordu, Fatih
   Nachabe, Mahmood H.
TI Inferences of Groundwater Response to Projected Hydroclimatic Changes in
   North Florida
SO JOURNAL OF HYDROLOGIC ENGINEERING
LA English
DT Article
DE Groundwater levels; Statistical modeling; Climate change; Global climate
   models (GCM); North Florida
ID CLIMATE-CHANGE IMPACTS; HYDROLOGICAL DROUGHT; RIVER-BASIN; MODELS;
   UNCERTAINTY; DYNAMICS; RECHARGE
AB Discerning anthropogenic stressors on groundwater is critical for climate change adaptation to reduce risks and increase resiliency. Long-term groundwater level trends are forecasted and examined at three sites in North Florida using a large ensemble of Global Climate Model (GCM) projections under low and medium emission scenarios. The forecasts indicate groundwater levels are likely to decline from 2020 to 2099. However, the declines are expected to accelerate after 2040s, reaching critical levels by the end of this century. Pumping impact constitutes 10% to 45% of future declines but is amplified by enhanced drought. Examination of distinct influence of rainfall, evapotranspiration (ET), and groundwater pumping on future trends shows highly divergent groundwater response to projected hydroclimatic changes. The future long-term rainfall trend may lead to rising groundwater levels, which may be overshadowed by heightened ET loss driven by climate change and increased groundwater pumping, causing steep declines. This study also reveals poor performance of predictions driven by GCM projections in replicating the timing of high and low levels at the sites influenced by Florida's peninsular climate due to the limitation of downscaling and bias-correction to capture oscillations in climate cycles driving hydrologic memory. However, groundwater levels are predicted well by a few GCMs at one site influenced primarily by continental climate. Additionally, a multidecadal harmonic analysis exposes presence of centennial periodicity in groundwater levels, which opens a new perspective in the understanding of climate change impacts on groundwater resources. Further investigation is needed to better understand the effect of centennial cycles on future groundwater levels and how these cycles can be incorporated into the downscaling methods. Hence, GCM-based forecasts are recommended to be cautiously utilized for groundwater resource planning when they significantly depart from historical long-term cyclic patterns.
C1 [Gordu, Fatih] St Johns River Water Management Dist, Palatka, FL 32177 USA.
   [Nachabe, Mahmood H.] Univ S Florida, Dept Civil & Environm Engn, Tampa, FL 33620 USA.
C3 State University System of Florida; University of South Florida
RP Gordu, F (corresponding author), St Johns River Water Management Dist, Palatka, FL 32177 USA.
EM fgordu@sjrwmd.com; nachabe@usf.edu
OI Gordu, Fatih/0000-0003-0649-7161
CR Allen DM, 2010, WATER RESOUR RES, V46, DOI 10.1029/2009WR008932
   Amanambu AC, 2020, J HYDROL, V589, DOI 10.1016/j.jhydrol.2020.125163
   [Anonymous], 2013, Downscaled CMIP3 and CMIP5 climate projections: Release of downscaled CMIP5 climate projections, comparison with preceding information, and summary of user needs
   Bellino J. C., 2018, 20185030 USGS
   Chang S, 2018, HYDROL EARTH SYST SC, V22, P4793, DOI 10.5194/hess-22-4793-2018
   Crosbie RS, 2012, HYDROGEOL J, V20, P245, DOI 10.1007/s10040-011-0804-4
   Cuthbert MO, 2019, NAT CLIM CHANGE, V9, P137, DOI 10.1038/s41558-018-0386-4
   Dams J, 2012, HYDROL EARTH SYST SC, V16, P1517, DOI 10.5194/hess-16-1517-2012
   DAUBECHIES I, 1990, IEEE T INFORM THEORY, V36, P961, DOI 10.1109/18.57199
   Durden D., 2019, SJ201901 ST JOHNS RI
   Flato G., 2013, CLIMATE CHANGE 2013, P741, DOI DOI 10.1017/CBO9781107415324.020
   Florida Climate Center, 2022, AN BEG END LENGTH ST
   Garner G, 2017, PROG PHYS GEOG, V41, P154, DOI 10.1177/0309133316679082
   Gettelman A., 2016, Demystifying Climate Models, V2, DOI [10.1007/978-3-662-48959-8, DOI 10.1007/978-3-662-48959-8]
   GFDL (Geophysical Fluid Dynamics Laboratory), 2022, CLIM MOD
   Gordu F, 2021, HYDROL PROCESS, V35, DOI 10.1002/hyp.14308
   Green TR, 2011, J HYDROL, V405, P532, DOI 10.1016/j.jhydrol.2011.05.002
   Harley GL, 2017, J HYDROL, V544, P438, DOI 10.1016/j.jhydrol.2016.11.020
   Holman IP, 2012, HYDROGEOL J, V20, P1, DOI 10.1007/s10040-011-0805-3
   Hu W, 2019, J HYDROL, V578, DOI 10.1016/j.jhydrol.2019.124042
   Infanti JM, 2020, EARTH SPACE SCI, V7, DOI 10.1029/2019EA000725
   Jackson CR, 2011, J HYDROL, V399, P12, DOI 10.1016/j.jhydrol.2010.12.028
   Jeihouni E, 2019, ENVIRON EARTH SCI, V78, DOI 10.1007/s12665-019-8283-3
   Jyrkama MI, 2007, J HYDROL, V338, P237, DOI 10.1016/j.jhydrol.2007.02.036
   Kinzelbach W., 2011, HYDROL EARTH SYST SC, V8, P7621, DOI [10.5194/hessd-8-7621-2011, DOI 10.5194/HESSD]
   Klove B, 2014, J HYDROL, V518, P250, DOI 10.1016/j.jhydrol.2013.06.037
   Maurer EP, 2010, HYDROL EARTH SYST SC, V14, P1125, DOI 10.5194/hess-14-1125-2010
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Moriasi DN, 2015, T ASABE, V58, P1763
   Mustafa SMT, 2019, HYDROL EARTH SYST SC, V23, P2279, DOI 10.5194/hess-23-2279-2019
   Neukum C, 2012, HYDROGEOL J, V20, P547, DOI 10.1007/s10040-011-0827-x
   Niraula R, 2017, GEOPHYS RES LETT, V44, P10407, DOI 10.1002/2017GL075421
   Nkhonjera GK, 2017, GLOBAL PLANET CHANGE, V158, P72, DOI 10.1016/j.gloplacha.2017.09.011
   NOAA (National Oceanic and Atmospheric Administration), 2021, CLIMATE MODELS
   Opie S, 2020, EARTH SYST DYNAM, V11, P775, DOI 10.5194/esd-11-775-2020
   Ou GX, 2018, CLIMATIC CHANGE, V151, P303, DOI 10.1007/s10584-018-2278-z
   Panaou T, 2018, J WATER RES PLAN MAN, V144, DOI [10.1061/(ASCE)WR.1943-5452.0000910, 10.1061/(asce)wr.1943-5452.0000910]
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Sanderson BM, 2017, GEOSCI MODEL DEV, V10, P2379, DOI 10.5194/gmd-10-2379-2017
   Scibek J, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004742
   Serrat-Capdevila A, 2007, J HYDROL, V347, P48, DOI 10.1016/j.jhydrol.2007.08.028
   Stocker, 2015, CEUR WORKSHOP PROC, V1542, P33, DOI [10.1017/CBO9781107415324, DOI 10.1017/CBO9781107415324]
   Stute M, 2001, P NATL ACAD SCI USA, V98, P10529, DOI 10.1073/pnas.191366098
   Taylor RG, 2013, NAT CLIM CHANGE, V3, P322, DOI [10.1038/nclimate1744, 10.1038/NCLIMATE1744]
   Torrence C, 1998, B AM METEOROL SOC, V79, P61, DOI 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
   Van Lanen HAJ, 2013, HYDROL EARTH SYST SC, V17, P1715, DOI 10.5194/hess-17-1715-2013
   Van Lanen HAJ, 2006, IAHS-AISH P, V308, P122
   Van Loon AF, 2014, J GEOPHYS RES-ATMOS, V119, P4640, DOI 10.1002/2013JD020383
   Van Loon AF, 2015, WIRES WATER, V2, P359, DOI 10.1002/wat2.1085
   Wada Y, 2016, NAT CLIM CHANGE, V6, P777, DOI [10.1038/NCLIMATE3001, 10.1038/nclimate3001]
   Wootten A, 2017, J APPL METEOROL CLIM, V56, P3245, DOI 10.1175/JAMC-D-17-0087.1
   Wootten A., 2014, 20141190 USGS
   Wu WY, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-17581-y
NR 53
TC 1
Z9 1
U1 0
U2 6
PU ASCE-AMER SOC CIVIL ENGINEERS
PI RESTON
PA 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
SN 1084-0699
EI 1943-5584
J9 J HYDROL ENG
JI J. Hydrol. Eng.
PD APR 1
PY 2023
VL 28
IS 4
AR 04023001
DI 10.1061/JHYEFF.HEENG-5827
PG 13
WC Engineering, Civil; Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Environmental Sciences & Ecology; Water Resources
GA 8Z8YY
UT WOS:000933658400016
DA 2025-01-10
ER

PT J
AU Muzammil, M
   Zahid, A
   Farooq, U
   Saddique, N
   Breuer, L
AF Muzammil, Muhammad
   Zahid, Azlan
   Farooq, Umar
   Saddique, Naeem
   Breuer, Lutz
TI Climate change adaptation strategies for sustainable water management in
   the Indus basin of Pakistan
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Water security; Climate change; Indus basin; Water management
   strategies; Improved irrigation technologies; Sustainable development
ID CHANGE IMPACTS; IRRIGATION; FOOD; AGRICULTURE; PROJECTIONS; EFFICIENCY;
   SCARCITY; OPTIONS; MODEL; SOIL
AB Pakistan's agriculture faces water security challenges owing to insecure water supply and bad governance. The increas-ing food demand of the growing population and climate change vulnerability are future key threats to water sustain-ability. In this study, the current and future water demands as well as management strategies are evaluated for two climate change Representative Concentration Pathways (RCP2.6 and RCP8.5) for the Punjab and Sindh provinces in the Indus basin of Pakistan. The RCPs are assessed for the regional climate model REMO2015, which was found to be the best-fitting model for the current situation in a preceding model comparison using Taylor diagrams. The status quo water consumption (CWRarea) is estimated to 184 km3 yr-1, consisting of 76 % blue water (freshwater from sur -face water and groundwater), 16 % green water (precipitation), and 8 % grey water (required to leach out the salts from the root zone). The results of the future CWRareaindicates that RCP2.6 is more vulnerable than RCP8.5 in view of water consumption as the vegetation period of crops is reduced under RCP8.5. For both pathways (RCP2.6 and RCP8.5), CWRarea increases gradually in the midterm (2031-2070) and becomes extreme at the end of the long term (2061-2090). The future CWRarea increases up to +73 % under the RCP2.6 and up to +68 % in the RCP8.5 com-pared to the status quo. However, the increase in CWRarea could be restrained up to -3 % compared to the status quo through the adaptation of alternative cropping patterns. The results further show that the future CWRarea under climate change could be even decreased by up to -19 % through the collective implementation of improved irrigation tech-nologies and optimized cropping patterns.
C1 [Muzammil, Muhammad; Breuer, Lutz] Justus Liebig Univ Giessen, Inst Landscape Ecol & Resources Management ILR, Res Ctr Biosyst Land Use & Nutr IFZ, D-35392 Giessen, Germany.
   [Zahid, Azlan] Texas A&M Univ Syst, Texas A&M AgriLife Res, Dallas, TX 75252 USA.
   [Farooq, Umar] Washington State Univ, Dept Civil & Environm Engn, Pullman, WA USA.
   [Muzammil, Muhammad; Saddique, Naeem] Univ Agr Faisalabad, Dept Irrigat & Drainage, Faisalabad, Pakistan.
   [Breuer, Lutz] Justus Liebig Univ Giessen, Ctr Int Dev & Environm Res ZEU, D-35390 Giessen, Germany.
C3 Justus Liebig University Giessen; Texas A&M University System; Texas A&M
   University College Station; Texas A&M AgriLife Research; Washington
   State University; University of Agriculture Faisalabad; Justus Liebig
   University Giessen
RP Muzammil, M (corresponding author), Justus Liebig Univ Giessen, Inst Landscape Ecol & Resources Management ILR, Res Ctr Biosyst Land Use & Nutr IFZ, D-35392 Giessen, Germany.; Muzammil, M (corresponding author), Univ Agr Faisalabad, Dept Irrigat & Drainage, Faisalabad, Pakistan.
EM muhammad.muzammil@umwelt.uni-giessen.de
RI Zahid, A/E-8947-2019; Farooq, Umar/JFA-0090-2023; Saddique,
   Naeem/AAH-8733-2021; Muzammil, Muhammad/AAY-9501-2020; Breuer,
   Lutz/C-6652-2013
OI Farooq, Umar/0000-0001-6164-1889; Breuer, Lutz/0000-0001-9720-1076;
   Muzammil, Muhammad/0000-0003-0314-8601
CR Abbas G, 2017, AGR FOREST METEOROL, V247, P42, DOI 10.1016/j.agrformet.2017.07.012
   Ahmad MJ, 2021, J WATER CLIM CHANGE, V12, P1184, DOI 10.2166/wcc.2020.009
   Ahmed E, 2020, WATER-SUI, V12, DOI 10.3390/w12071902
   Ahmed N, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13168695
   Allen R.G., 1998, FAO Irrig. Drain. Pap., V56, P300, DOI DOI 10.1016/S0141-1187(05)80058-6
   [Anonymous], NATL WATER POLICY 20
   Arshad A, 2021, SCI TOTAL ENVIRON, V784, DOI 10.1016/j.scitotenv.2021.147140
   Arshad M., 2009, Pakistan Journal of Agricultural Sciences, V46, P280
   Ayers R.S., 1985, Water quality for agriculture. FAO Irrigation and drainage paper 29 Rev. 1
   Banihashemi SM, 2021, INT J PLANT PROD, V15, P45, DOI 10.1007/s42106-020-00118-0
   Basharat M, 2019, INDUS RIVER BASIN: WATER SECURITY AND SUSTAINABILITY, P375, DOI 10.1016/B978-0-12-812782-7.00017-5
   Bekele B, 2022, WATER CONSERV SCI EN, V7, P119, DOI 10.1007/s41101-022-00129-0
   Bhattacharjee A, 2022, I SYMPOS LOW POWER E, DOI [10.1145/3531437.3539729, 10.1007/978-981-16-9037-2_1]
   Boazar M, 2020, J ENVIRON PLANN MAN, V63, P2484, DOI 10.1080/09640568.2020.1729705
   Brouwer C., 1985, IRRIGATION WATER MAN
   Cheema MJM, 2014, GROUNDWATER, V52, P25, DOI 10.1111/gwat.12027
   Chouchane H, 2020, HYDROL EARTH SYST SC, V24, P3015, DOI 10.5194/hess-24-3015-2020
   Cui XM, 2020, J ENVIRON ECON MANAG, V101, DOI 10.1016/j.jeem.2020.102306
   Deihimfard R, 2022, SCI TOTAL ENVIRON, V807, DOI 10.1016/j.scitotenv.2021.150991
   Doulgeris C, 2015, IRRIGATION SCI, V33, P469, DOI 10.1007/s00271-015-0482-4
   Du PP, 2021, PEERJ, V9, DOI 10.7717/peerj.12201
   Enayati M, 2021, J WATER CLIM CHANGE, V12, P401, DOI 10.2166/wcc.2020.261
   Frisvold G, 2016, J CONTEMP WAT RES ED, V158, P62, DOI 10.1111/j.1936-704X.2016.03219.x
   Ghaffar A., 2022, Improvement of Plant Production in the Era of Climate Change, P1
   Govere S, 2020, SCI TOTAL ENVIRON, V742, DOI 10.1016/j.scitotenv.2020.140473
   Gul A, 2022, ENVIRON SCI POLLUT R, V29, P26660, DOI 10.1007/s11356-021-17579-z
   Habib Z., 2021, FOOD AGR ORG
   Hamududu BH, 2020, ENVIRON DEV SUSTAIN, V22, P2817, DOI 10.1007/s10668-019-00320-9
   Hussain M, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-019-7956-4
   Jia LZ, 2019, CATENA, V175, P18, DOI 10.1016/j.catena.2018.12.012
   Kader M.A., 2019, Bulletin of the National Research Centre, V43, P1, DOI [DOI 10.1186/S42269-019-0186-7, 10.1186/s42269-019-0186-7]
   Kahlown M.A., 2007, AGR WATER MANAGE, V7
   Kawakita S, 2020, AGR FOREST METEOROL, V290, DOI 10.1016/j.agrformet.2020.107998
   Khelifa R, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-86383-z
   Kirby M, 2017, AGR WATER MANAGE, V179, P34, DOI 10.1016/j.agwat.2016.06.001
   Ko A, 2019, WATER RESOUR RES, V55, P1129, DOI [10.1029/2018wr023521, 10.1029/2018WR023521]
   Kukal MS, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-25212-2
   Lovelli S, 2010, AGR WATER MANAGE, V97, P1287, DOI 10.1016/j.agwat.2010.03.005
   Malhi GS, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031318
   Mani M., 2018, S ASIAS HOTSPOTS, P125
   Mian M.A., 2019, TROP 2019 KASS GERM, P1
   Millán S, 2020, SENSORS-BASEL, V20, DOI 10.3390/s20092526
   Minkoff-Zern LA, 2014, GEOFORUM, V57, P91, DOI 10.1016/j.geoforum.2014.08.017
   Mishra A, 2013, SCI TOTAL ENVIRON, V468, pS132, DOI 10.1016/j.scitotenv.2013.05.080
   Multsch S, 2017, J HYDROL-REG STUD, V12, P315, DOI 10.1016/j.ejrh.2017.04.007
   Multsch S, 2017, INT J WATER RESOUR D, V33, P292, DOI 10.1080/07900627.2016.1168286
   Multsch S, 2013, GEOSCI MODEL DEV, V6, P1043, DOI 10.5194/gmd-6-1043-2013
   Multsch S., 2015, REDUCTION PREDICTIVE, DOI [10.22029/jlupub-8562, DOI 10.22029/JLUPUB-8562]
   Multsch S, 2020, HYDROL EARTH SYST SC, V24, P307, DOI 10.5194/hess-24-307-2020
   Multsch S, 2016, REG ENVIRON CHANGE, V16, P2419, DOI 10.1007/s10113-016-0968-5
   Muzammil M, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-02913-9
   Muzammil M, 2020, WATER-SUI, V12, DOI 10.3390/w12051429
   Myint SW, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12081080
   Nikolaou G, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10081120
   Nouri H, 2019, SCI TOTAL ENVIRON, V653, P241, DOI 10.1016/j.scitotenv.2018.10.311
   Parc, About us
   Pastén-Zapata E, 2020, J HYDROL, V584, DOI 10.1016/j.jhydrol.2020.124653
   pbs, About us
   Perez-Lopez D., 2018, Water scarcity and sustainable agriculture in semiarid environment: tools, strategies, and challenges for woody crops, P247
   Qureshi AS, 2008, AGR WATER MANAGE, V95, P1, DOI 10.1016/j.agwat.2007.09.014
   Qureshi AS, 2010, WATER RESOUR MANAG, V24, P1551, DOI 10.1007/s11269-009-9513-3
   Rahimi-Moghaddam S, 2021, AGR WATER MANAGE, V243, DOI 10.1016/j.agwat.2020.106487
   Raja M.U., 2018, CLIMATE CHANGE ITS I, P2617
   Rizov M, 2013, J AGR ECON, V64, P537, DOI 10.1111/1477-9552.12030
   Rodrigues G., 2012, APPL MAIZE SO BRAZIL
   Rodriguez Pleguezuelo C. R., 2018, Water scarcity and sustainable agriculture in semiarid environment: tools, strategies, and challenges for woody crops, P299
   Saddique N, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13081280
   Saifullah M., 2022, TEMPERATURE BASED AG, DOI [10.5772/intechopen.105590, DOI 10.5772/INTECHOPEN.105590]
   Shaheen N., 2020, APN SCI B, DOI [10.30852/sb.2020.1221, DOI 10.30852/SB.2020.1221]
   Sharma C.P., 2016, OVERDRAFT INDIAS WAT
   Singh A, 2018, ECOL INDIC, V90, P184, DOI 10.1016/j.ecolind.2018.03.014
   Supit I, 2010, AGR FOREST METEOROL, V150, P77, DOI 10.1016/j.agrformet.2009.09.002
   Tariq M, 2021, INT J PLANT PROD, V15, P291, DOI 10.1007/s42106-020-00124-2
   Taylor KE, 2001, J GEOPHYS RES-ATMOS, V106, P7183, DOI 10.1029/2000JD900719
   Wang X, 2017, J INTEGR AGR, V16, P2709, DOI 10.1016/S2095-3119(17)61786-6
   Xiao DP, 2020, AGR WATER MANAGE, V238, DOI 10.1016/j.agwat.2020.106238
   Zhou GL, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-28392-z
   Zhu TJ, 2013, WATER INT, V38, P651, DOI 10.1080/02508060.2013.830682
NR 78
TC 4
Z9 4
U1 0
U2 12
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD JUN 20
PY 2023
VL 878
AR 163143
DI 10.1016/j.scitotenv.2023.163143
EA MAR 2023
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA E3GR2
UT WOS:000974466300001
PM 36996978
DA 2025-01-10
ER

PT J
AU Castro, B
   Sen, R
AF Castro, Brianna
   Sen, Raka
TI Everyday Adaptation: Theorizing climate change adaptation in daily life
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Adaptation; Climate Change; Vulnerability; Adaptive Capacity; Everyday
   Action
ID PROTECTION; RESILIENCE; FRAMEWORK; POLITICS; HEALTHY; LESSONS; SCIENCE
AB Climate science to date demonstrates that natural and human systems must urgently adapt. Adaptation refers to changes in societies and ecological systems as they respond to both actual and anticipated impacts of the changing climate. While adaptation is not limited to the level of planning and policy, existing adaptation practice privileges institutional action. We argue that the definition of adaptation should be broadened to include the small, incremental changes made in our daily lives to accommodate the shifting ecologies in which we live. Drawing on critical adaptation research and our own ethnographic fieldwork in the Global South, we define everyday adaptation as the shifted ways a person works, eats, lives and thinks in response to climate realities, rather than the hardening of coastlines or the relocation of vulnerable structures. We integrate and build on existing scholarship on adaptation and the everyday to theorize the logics of everyday, hyperlocal adaptation. This hyperlocal scale is a critical component of any definition of adaptation and a useful lens for studying the way much of the global population adapts and will continue to adapt their lives to climate change. We offer two theoretical components of adaptation revealed by the everyday - adaptation labor and value adaptation - as lenses to see changes in everyday action. Through considering hyperlocal action, we then identify and explore four logics of everyday adaptation actions: lifestyle stability, socio-ecological reactivity, livelihood flexibility, and community capacity. Everyday adaptations are limited by individuals' capacity to adapt and thereby determine the longevity, livability, and quality of life of places on the frontlines of climate change. We argue for understanding the aggregate effects of everyday adaptation in order to better align the actions of those living with climate change in their everyday lives and the large-scale adaptation projects aiming to protect them.
C1 [Castro, Brianna] Harvard Univ, Dept Sociol, Cambridge, MA USA.
   [Sen, Raka] Univ Penn, Dept Sociol, Philadelphia, PA USA.
   [Castro, Brianna] 33 Kirkland St, Cambridge, MA 02138 USA.
C3 Harvard University; University of Pennsylvania
RP Castro, B (corresponding author), 33 Kirkland St, Cambridge, MA 02138 USA.
EM briannacastro@g.harvard.edu
RI Castro, Brianna/KMA-4001-2024
OI Sen, Raka/0000-0002-6197-5691; Castro, Brianna/0000-0002-8246-4487
FU National Science Foundation; Weatherhead Center for International
   Affairs; Gertrude and Otto Pollak Fellowship; Foreign Language and Area
   Studies Fellowship; Center for Advanced Study of India; David
   Rockefeller Center for Latin American Studies
FX We thank Eric Klinenberg and the Social Consequences of Climate Change
   working group at the Institute for Public Knowledge for facili-tating
   this research. We also thank Liz Koslov, Malcolm Araos, and Danielle
   Falzon for their comments on earlier versions of this paper. This
   research was made possible by the generous funding support of the
   National Science Foundation, the Weatherhead Center for International
   Affairs, the Gertrude and Otto Pollak Fellowship, the Foreign Language
   and Area Studies Fellowship, the Center for Advanced Study of India, and
   the David Rockefeller Center for Latin American Studies.
CR Abid M, 2017, CLIMATE, V5, DOI 10.3390/cli5040085
   Adger N., 2003, CLIMATE CHANGE ADAPT, P29, DOI DOI 10.1142/9781860945816_0003
   Adger W.N., 2006, Fairness in adaptation to climate change, P1
   Adger WN, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P755
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P75, DOI 10.1016/j.gloenvcha.2005.03.001
   Adger WN, 2003, ECON GEOGR, V79, P387
   Agrawal A, 2008, NEW FRONT SOC POLICY
   Agrawal A, 2015, NAT CLIM CHANGE, V5, P185, DOI 10.1038/nclimate2501
   Anand Nikhil., 2017, HYDRAULIC CITY WATER
   [Anonymous], 2010, I INT EC POLICY WORK
   [Anonymous], WEAPONS WEAK EVERYDA
   [Anonymous], 2017, ARTS LIVING DAMAGED
   Appadurai A, 2003, PRODUCTION LOCALITY, P208
   Artur L, 2012, GLOBAL ENVIRON CHANG, V22, P529, DOI 10.1016/j.gloenvcha.2011.11.013
   Ayers J, 2009, ENVIRONMENT, V51, P22, DOI 10.3200/ENV.51.4.22-31
   Black R, 2011, GLOBAL ENVIRON CHANG, V21, pS3, DOI 10.1016/j.gloenvcha.2011.10.001
   Cadena Marisol de la., 2015, Earth Beings: Ecologies of Practice across Andean Worlds
   Caniglia B.S., 2015, CLIMATE CHANGE SOC S
   Carman JP, 2020, GLOBAL ENVIRON CHANG, V61, DOI 10.1016/j.gloenvcha.2020.102062
   Carmin JoAnn., 2015, Climate Change and Society: Sociological Perspectives, P164
   Castro B, 2019, CURR DIR WATER SCARC, V2, P77, DOI 10.1016/B978-0-12-814820-4.00006-7
   Davies M, 2008, IDS BULL-I DEV STUD, V39, P105
   Davies M, 2013, DEV POLICY REV, V31, P27, DOI 10.1111/j.1467-7679.2013.00600.x
   Dodman D, 2013, J INT DEV, V25, P640, DOI 10.1002/jid.1772
   Dow K, 2013, NAT CLIM CHANGE, V3, P305, DOI 10.1038/nclimate1847
   Dzebo A, 2015, GLOBAL ENVIRON CHANG, V35, P423, DOI 10.1016/j.gloenvcha.2015.10.006
   Ellis F, 2000, J AGR ECON, V51, P289, DOI 10.1111/j.1477-9552.2000.tb01229.x
   Ellis F., 2000, RURAL LIVELIHOODS DI, DOI DOI 10.1093/OSO/9780198296959.001.0001
   Ensor J, 2015, WIRES CLIM CHANGE, V6, P509, DOI 10.1002/wcc.348
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   FREUDENBURG WR, 1995, SOCIOL FORUM, V10, P361, DOI 10.1007/BF02095827
   Funder M, 2019, GLOBAL ENVIRON CHANG, V55, P130, DOI 10.1016/j.gloenvcha.2019.02.007
   Geertz C., 1983, LOCAL KNOWLEDGE FURT
   Govindrajan Radhika., 2018, ANIMAL INTIMACIES
   Huq S, 2004, CLIM POLICY, V4, P25
   Intergovernmental Panel on Climate Change, 2018, Global warming of 1.5 C
   Jackson RC, 2018, GLOBAL ENVIRON CHANG, V52, P58, DOI 10.1016/j.gloenvcha.2018.05.006
   Johansson A, 2016, CRIT SOCIOL, V42, P417, DOI 10.1177/0896920514524604
   Kates RW, 2000, CLIMATIC CHANGE, V45, P5, DOI 10.1023/A:1005672413880
   Kim BF, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2019.05.010
   Klinenberg E., 2015, Heat Wave: A Social Autopsy of Disaster in Chicago
   Koslov L, 2019, ANN AM ASSOC GEOGR, V109, P568, DOI 10.1080/24694452.2018.1549472
   Lemos M.C., 2013, Climate Science for Serving Society: Research, Modeling and Prediction Priorities, P437, DOI DOI 10.1007/978-94-007-6692-1_16
   Lemos MC, 2016, GLOBAL ENVIRON CHANG, V39, P170, DOI 10.1016/j.gloenvcha.2016.05.001
   Li TM, 2010, ANTIPODE, V41, P66, DOI 10.1111/j.1467-8330.2009.00717.x
   Li TaniaMurray., 2014, LANDS END CAPITALIST, DOI DOI 10.1515/9780822376460
   Lyons K. M., 2020, Vital Decomposition: Soil Practitioners + Life Politics, DOI DOI 10.2307/J.CTV11CW3T1
   Masuda YJ, 2019, GLOBAL ENVIRON CHANG, V56, P29, DOI 10.1016/j.gloenvcha.2019.03.005
   Mendelsohn R, 2007, CLIMATIC CHANGE, V81, P101, DOI 10.1007/s10584-005-9010-5
   Mimura N, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P869
   Moore DonaldS., 2005, Suffering for Territory: Race, Place, and Power in Zimbabwe
   Mortimore MJ, 2001, GLOBAL ENVIRON CHANG, V11, P49, DOI 10.1016/S0959-3780(00)00044-3
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Nalau J, 2015, ENVIRON SCI POLICY, V48, P89, DOI 10.1016/j.envsci.2014.12.011
   Niamir M., 1995, The cultural dimension of development: indigenous knowledge systems., P245
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   Olsson P, 2014, ECOL SOC, V19, DOI 10.5751/ES-06799-190401
   Owen G, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102071
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Paganini Z, 2019, GEOFORUM, V104, P25, DOI 10.1016/j.geoforum.2019.06.003
   Patt A, 2002, GLOBAL ENVIRON CHANG, V12, P185, DOI 10.1016/S0959-3780(02)00013-4
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Pelling M, 2015, CLIMATIC CHANGE, V133, P113, DOI 10.1007/s10584-014-1303-0
   Pelling M, 2011, ECOL SOC, V16
   Pelling M, 2010, PROG HUM GEOG, V34, P21, DOI 10.1177/0309132509105004
   Phillips J., 2003, Coping with Climate Variability, P110
   Portner H.-O., IN PRESS
   Raffles H, 1999, CULT ANTHROPOL, V14, P323, DOI 10.1525/can.1999.14.3.323
   Rahman HMT, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00002
   Rao ND, 2018, GLOBAL ENVIRON CHANG, V49, P154, DOI 10.1016/j.gloenvcha.2018.02.013
   Rosengren D., 2018, ETHNOS, V83, P607, DOI [DOI 10.1080/00141844.2016.1213760, 10.1080/00141844.2016.1213760]
   Ross Kristin., 1996, PARALLAX, V2, P67
   Scott JamesC., 2011, ART NOT BEING GOVERN
   Start D., 2001, Development Policy Review, V19, P491, DOI 10.1111/1467-7679.00147
   Stoetzer B, 2018, CULT ANTHROPOL, V33, P295, DOI 10.14506/ca33.2.09
   Tang S, 2012, WEATHER CLIM SOC, V4, P300, DOI 10.1175/WCAS-D-12-00028.1
   Thomas DS., 2006, Fairness in adaptation to climate change, P223
   Tran TA, 2020, CLIM DEV, V12, P610, DOI 10.1080/17565529.2019.1664974
   Timmer C.P., 2009, A World without Agriculture: The Structural Transformation in Historical Perspective
   Vogel B, 2015, GLOBAL ENVIRON CHANG, V31, P110, DOI 10.1016/j.gloenvcha.2015.01.001
   Wamsler C, 2016, CLIMATIC CHANGE, V137, P71, DOI 10.1007/s10584-016-1660-y
   Zickgraf C, 2019, SOC SCI-BASEL, V8, DOI 10.3390/socsci8080228
NR 82
TC 25
Z9 31
U1 6
U2 38
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD JUL
PY 2022
VL 75
AR 102555
DI 10.1016/j.gloenvcha.2022.102555
EA JUL 2022
PG 9
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 3A4ZP
UT WOS:000827270100009
OA Bronze
DA 2025-01-10
ER

PT J
AU Johnston, JD
   Greenler, SM
   Miller, BA
   Reilly, MJ
   Lindsay, AA
   Dunn, CJ
AF Johnston, James D.
   Greenler, Skye M.
   Miller, Becky A.
   Reilly, Matthew J.
   Lindsay, Amanda A.
   Dunn, Christopher J.
TI Diameter limits impede restoration of historical conditions in dry
   mixed-conifer forests of eastern Oregon, USA
SO ECOSPHERE
LA English
DT Article
DE 21&#8208; inch rule; climate change adaptation; co&#8208; production of
   research; diameter limits; Douglas&#8208; fir; eastside screens; grand
   fir; ponderosa pine; restoration; shade&#8208; intolerant; shade&#8208;
   tolerant; simulations; thinning; western larch; western white pine
ID CLIMATE-CHANGE; PACIFIC-NORTHWEST; ECOLOGICAL RESTORATION; TREE
   MORTALITY; PONDEROSA PINE; WESTERN; GROWTH; VEGETATION; PRODUCTIVITY;
   LANDSCAPES
AB The U.S. Forest Service is reconsidering policies that limit the size of trees that can be removed in the course of restoration treatments in dry forests of eastern Oregon. To evaluate the effects of diameter limits on the ability of managers to meet restoration objectives, we used an existing network of long-term research plots to summarize historical and contemporary structure and composition of mixed-conifer forests within a one million-ha study area in eastern Oregon. Then, we used a novel thinning simulation procedure to quantify the degree to which thinning using different diameter limits restored stands to historical conditions. Contemporary mixed-conifer forests within the study area are significantly denser, have more basal area, and have a greater proportion of shade-tolerant species than historical conditions. Our simulations of thinning under current policy that prohibits cutting of trees >= 53 cm show that a quarter of mixed-conifer stands cannot be restored to within the historical range of basal area or density. Those stands that could be restored to within historical basal area ranges still had a substantially higher component of shade-tolerant trees than historical stands. Permitting larger shade-tolerant trees to be removed allowed restoration of all or most of stands to within historical structural and compositional ranges. Forest conditions in the late 1800s may not necessarily provide the best template for management because climate and disturbance projections suggest that eastern Oregon forests will be less well suited to shade-tolerant species in the future. Adapting stands to future conditions will require robust monitoring of forest structural and compositional response to restoration treatments.
C1 [Johnston, James D.; Greenler, Skye M.; Dunn, Christopher J.] Oregon State Univ, Coll Forestry, 140 Peavy Hall,3100 SW Jefferson Way, Corvallis, OR 97333 USA.
   [Miller, Becky A.] Parks Canada Agcy, 2220 Harbour Rd, Sidney, BC V8L 2P6, Canada.
   [Reilly, Matthew J.] US Forest Serv, USDA, Pacif Northwest Res Stn, Western Wildland Environm Threat Assessment Ctr, Corvallis, OR 97331 USA.
   [Lindsay, Amanda A.] US Forest Serv, USDA, Malheur Natl Forest, 431 Patterson Bridge Rd, John Day, OR 97845 USA.
C3 Oregon State University; Parks Canada; United States Department of
   Agriculture (USDA); United States Forest Service; United States
   Department of Agriculture (USDA); United States Forest Service
RP Johnston, JD (corresponding author), Oregon State Univ, Coll Forestry, 140 Peavy Hall,3100 SW Jefferson Way, Corvallis, OR 97333 USA.
EM james.johnston@oregonstate.edu
OI Greenler, Skye/0000-0002-4454-8970
FU USFS; Blue Mountains Forest Partners
FX Fieldwork for this study was made possible with the assistance of the
   Blue Mountains Forest Partners, Ochoco Forest Restoration Collaborative,
   Harney County Restoration Collaborative, the Ochoco National Forest, and
   the Malheur National Forest. The authors wish to extend special thanks
   to Steve Beverlin, Boyd Britton, Susan Jane Brown, Elise Delgado,
   Vernita Ediger, Dave Halemeier, Dave Hannibal, Pam Hardy, Ben Holliday,
   Glen Johnston, Rick Minster, Trent Seager, Brenda Smith, Jack
   Southworth, Mark Webb, King Williams, and Zach Williams. We are grateful
   to field and laboratory technicians: Amanda Bintliff, Clark Chesshir,
   Tatiana Dolgushina, Kayla Gunther, Will Hendricks, Hana Maaiah, Jamie
   Martenson, Alex Martinez-Held, Kevin Mason, Lexa McAllister, Tyler
   Mesberg, Kylie Meyer, Claire Moreland-Ochoa, Leigh Anna Morgan, Kat
   Morici, Brett Morrissette, Julia Olszewski, Courtnay Pogainis, Joel
   Riggs, Lizzie Schattle, Sonya Templeton, Tatum VanDam, Kate Wellons,
   Kate Williams, and Jordan Woodcock. Funding was provided by the USFS and
   the Blue Mountains Forest Partners. We thank two anonymous reviewers
   whose comments significantly improved a draft manuscript.
CR Abella SR, 2006, J FOREST, V104, P407
   Ager AA, 2007, LANDSCAPE URBAN PLAN, V80, P292, DOI 10.1016/j.landurbplan.2006.10.009
   Blicharska M, 2014, CONSERV BIOL, V28, P1558, DOI 10.1111/cobi.12341
   Bradford JB, 2017, FRONT ECOL ENVIRON, V15, P11, DOI 10.1002/fee.1445
   Butler WH, 2015, ENVIRON MANAGE, V55, P564, DOI 10.1007/s00267-014-0430-8
   Coops NC, 2005, ECOL MODEL, V183, P107, DOI 10.1016/j.ecolmodel.2004.08.002
   Fettig CJ, 2007, FOREST ECOL MANAG, V238, P24, DOI 10.1016/j.foreco.2006.10.011
   Finney MA, 2007, INT J WILDLAND FIRE, V16, P712, DOI 10.1071/WF06064
   Franklin J.F., 2018, ECOLOGICAL FOREST MA
   Franklin JF, 2014, LANDSCAPE ECOL, V29, P1645, DOI 10.1007/s10980-014-0077-0
   Gersonde RF, 2005, FOREST ECOL MANAG, V219, P95, DOI 10.1016/j.foreco.2005.09.002
   Hagmann RK, 2014, FOREST ECOL MANAG, V330, P158, DOI [10.1016/j.foreco.2014.0, 10.1016/j.foreco.2014.06.044]
   Halofsky JE, 2020, FIRE ECOL, V16, DOI 10.1186/s42408-019-0062-8
   Jackson ST, 2009, SCIENCE, V325, P567, DOI 10.1126/science.1172977
   Jain TB, 2004, CAN J FOREST RES, V34, P2187, DOI 10.1139/X04-094
   Johnson C.G., 1992, R6 ERW T 036 92
   Johnston JD, 2019, FOREST ECOL MANAG, V433, P690, DOI 10.1016/j.foreco.2018.11.047
   Johnston JD, 2017, FIRE ECOL, V13, P18, DOI 10.4996/fireecology.130257453
   Johnston JD, 2017, FOREST ECOL MANAG, V392, P45, DOI 10.1016/j.foreco.2017.02.050
   Johnston JD, 2018, ECOSPHERE, V9, DOI 10.1002/ecs2.2400
   Keane RE, 2009, FOREST ECOL MANAG, V258, P1025, DOI 10.1016/j.foreco.2009.05.035
   Keeler BL, 2017, BIOSCIENCE, V67, P591, DOI 10.1093/biosci/bix051
   Kerns BK, 2020, FOREST ECOL MANAG, V463, DOI 10.1016/j.foreco.2020.117985
   Kerns BK, 2018, CLIM SERV, V10, P33, DOI 10.1016/j.cliser.2017.07.002
   Langille H.D, 1906, REPORT PROPOSED BLUE
   Lindsay A.A., 2020, US FOR SERV GEN TECH, P23, DOI DOI 10.2737/NRS-GTR-P-193-paper4
   Littell JS, 2018, EARTHS FUTURE, V6, P1097, DOI 10.1029/2018EF000878
   Littell JS, 2009, ECOL APPL, V19, P1003, DOI 10.1890/07-1183.1
   Loehman RA, 2011, FORESTS, V2, P832, DOI 10.3390/f2040832
   Long CJ, 2011, QUATERNARY RES, V75, P151, DOI 10.1016/j.yqres.2010.08.010
   LOPUSHINSKY W, 1974, FOREST SCI, V20, P181
   LOPUSHINSKY W, 1969, BOT GAZ, V130, P258, DOI 10.1086/336501
   McDowell NG, 2015, NAT CLIM CHANGE, V5, P669, DOI [10.1038/nclimate2641, 10.1038/NCLIMATE2641]
   Merschel A, 2019, J FOREST, V117, P128, DOI 10.1093/jofore/fvy085
   Merschel AG, 2014, ECOL APPL, V24, P1670, DOI 10.1890/13-1585.1
   Millar CI, 2015, SCIENCE, V349, P823, DOI 10.1126/science.aaa9933
   Mote PW, 2010, CLIMATIC CHANGE, V102, P29, DOI 10.1007/s10584-010-9848-z
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Reilly MJ, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.1695
   Reilly MJ, 2016, FOREST ECOL MANAG, V374, P102, DOI 10.1016/j.foreco.2016.05.002
   Safford H.D., 2012, Historical Environmental Variation in Conservation and Natural Resource Management, P46, DOI DOI 10.1002/9781118329726.CH4
   Simpson M., 2007, TECHNICAL PAPER R6 N
   Sohn JA, 2016, FOREST ECOL MANAG, V380, P261, DOI 10.1016/j.foreco.2016.07.046
   Spies TA., 2018, Synthesis of Science to Inform Land Management within the Northwest Forest Plan Area, DOI [DOI 10.2737/PNW-GTR-966, 10.2737/pnw-gtr-966]
   Stine P., 2014, GEN TECHNICAL REPORT
   Tepley AJ, 2020, ECOL APPL, V30, DOI 10.1002/eap.2188
   Urgenson LS, 2017, ENVIRON MANAGE, V59, P338, DOI 10.1007/s00267-016-0791-2
   USDA [U.S. Department of Agriculture], 1995, APPENDIX BREVISED IN
   USDA [U.S. Department of Agriculture], 2020, FOREST PLANS AMENDME
   USDA [U.S. Department of Agriculture], 2018, RAGGED RUBY PROJECT
   van Mantgem PJ, 2009, SCIENCE, V323, P521, DOI 10.1126/science.1165000
   Vernon MJ, 2018, FOREST ECOL MANAG, V422, P190, DOI 10.1016/j.foreco.2018.03.043
   Voelker SL, 2019, GLOBAL CHANGE BIOL, V25, P1247, DOI 10.1111/gcb.14543
   Westlind DJ, 2021, FOREST ECOL MANAG, V480, DOI 10.1016/j.foreco.2020.118645
   Whitlock C, 2011, QUATERNARY RES, V75, P114, DOI 10.1016/j.yqres.2010.08.013
NR 55
TC 5
Z9 5
U1 0
U2 5
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2150-8925
J9 ECOSPHERE
JI Ecosphere
PD MAR
PY 2021
VL 12
IS 3
AR e03394
DI 10.1002/ecs2.3394
PG 13
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA RH6HW
UT WOS:000636318200016
OA gold
DA 2025-01-10
ER

PT C
AU Awad, J
   Abd-Rabo, L
AF Awad, Jihad
   Abd-Rabo, Lamia
BE Lagaros, ND
   Abdalla, KM
   Marano, GC
   Phocas, MC
   AlRousan, R
TI Daylight and Energy Performance Optimization in Hot - Arid Regions:
   application and adaptation guide for designers in the UAE
SO 1ST INTERNATIONAL CONFERENCE ON OPTIMIZATION-DRIVEN ARCHITECTURAL DESIGN
   (OPTARCH 2019)
SE Procedia Manufacturing
LA English
DT Proceedings Paper
CT 1st International Conference on Optimization-Driven Architectural Design
   (OPTARCH)
CY NOV 05-07, 2019
CL Amman, JORDAN
SP Natl Tech Univ Athens, Jordan Univ Sci & Technol, Politecnico Torino, Univ Cyprus, McGill Univ, Fuzhou Univ
DE daylighting; thermal comfort; International Style; energy efficiency;
   parametric algorithm
AB In addition to the thermal comfort, the quality of daylight in the buildings are of exceptional importance in the early stages of the project. The building envelope therefore plays an important mediator, whether as climate change perceived or as cultural patrimony intangible, between the building and its surrounding conditions.
   Nowadays, the countries of the hot desert are introducing policy based on completely glazed constructions with neglecting their climate change as applied for the United Arab Emirates (UAE). This results in poor building efficiency and identity crises. Therefore, any attempt seeks to decrease excess sun exposure and make efficient sunlight availability. This leads to climate change adaptation and the happiness of the inhabitants as a sustainable development technique, decreasing buildings ' energy consumption, which is an effective way to eliminate emissions of carbon dioxide (CO2).
   In this context, this paper presents the assessment principles for daylight performance in the case-study. This lays out approaches for optimizing daylight and energy efficiency in hot-arid climates by comparing different scenarios for building with international style at Ajman University - UAE, in order to reach to the best solution, that through the best use of performance simulation analysis and parametric generic algorithm software (Revit - Insight 360 plugin). Three phases of the methodology are taken: (1) the daylight and energy efficiency are analyzed for the case-study, (2) the results are assessed and compared to the hotarid climate, (3) the optimum solutions and recommendations are determined. The study provides a new building performance optimization method, which can enable architects to predict the optimal energy performance and daylight strategies by creating suitable climatic design options and to recognize the connection between design demands and daylight efficiency metrics, which are estimated to improve the entire environment. (C) 2020 The Authors. Published by Elsevier B.V.
C1 [Awad, Jihad] Ajman Univ, Dept Architecture, Coll Architecture Art & Design, Ajman, Egypt.
   [Abd-Rabo, Lamia] Ajman Univ, Dept Architecture, Fac Engn, Alexandria 21544, Egypt.
RP Abd-Rabo, L (corresponding author), Ajman Univ, Dept Architecture, Fac Engn, Alexandria 21544, Egypt.
EM j.awad@ajman.ac.ae; englamiaa_lamiaa@yahoo.com
RI Awad, Jihad/AAH-9722-2021
OI Awad, Jihad/0000-0001-9270-9241; Abd-Rabo, Lamiaa/0000-0002-5392-0332
CR Al-Temmamy M., 2019, IOP C SERIES MAT SCI, V609
   BRANZ, 2007, DES QUAL LEARN SPAC
   Heiselberg P., 2007, Integrated building design
   Hu A. M. A. Jianxin, 2014, 43 ANN NATL SOLAR C
   Lee E. S., 1998, OFFICE WORKER RESPON
   Mardaljevic J., 2013, OURNAL SUSTAINABLE D, V1
   McMullin P.W., 2016, Introduction to Structures
   Roche P. L., 2017, CARBON NEUTRAL ARCHI, V2
   Twinn Chris., 2003, The Arup Journal, P10
   U. G. B. C. GBC, 2014, LEED REFERENCE GUIDE
   Wagdy A, 2015, J BUILD ENG, V3, P155, DOI 10.1016/j.jobe.2015.07.007
   Wienold J., 2009, 11 INT IBPSA C
NR 12
TC 9
Z9 9
U1 1
U2 7
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 2351-9789
J9 PROCEDIA MANUF
PY 2020
VL 44
BP 237
EP 244
DI 10.1016/j.promfg.2020.02.227
PG 8
WC Computer Science, Hardware & Architecture; Engineering, Manufacturing
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science; Engineering
GA BT9YG
UT WOS:000865915900030
OA gold
DA 2025-01-10
ER

PT J
AU Biemans, H
   Siderius, C
   Lutz, AF
   Nepal, S
   Ahmad, B
   Hassan, T
   von Bloh, W
   Wijngaard, RR
   Wester, P
   Shrestha, AB
   Immerzeel, WW
AF Biemans, H.
   Siderius, C.
   Lutz, A. F.
   Nepal, S.
   Ahmad, B.
   Hassan, T.
   von Bloh, W.
   Wijngaard, R. R.
   Wester, P.
   Shrestha, A. B.
   Immerzeel, W. W.
TI Importance of snow and glacier meltwater for agriculture on the
   Indo-Gangetic Plain
SO NATURE SUSTAINABILITY
LA English
DT Article
ID CLIMATE-CHANGE; WATER AVAILABILITY; SOUTH-ASIA; FOOD; IRRIGATION;
   DISCHARGE; PRECIPITATION; VULNERABILITY; CHALLENGE; SECURITY
AB Densely populated floodplains downstream of Asia's mountain ranges depend heavily on mountain water resources, in particular for irrigation. An intensive and complex multi-cropping irrigated agricultural system has developed here to optimize the use of these mountain water resources in conjunction with monsoonal rainfall. Snow and glacier melt thereby modulate the seasonal pattern of river flows and, together with groundwater, provide water when rainfall is scarce. Climate change is expected to weaken this modulating effect, with potentially strong effects on food production in one of the world's breadbaskets. Here we quantify the space-, time-and crop-specific dependence of agriculture in the Indo-Gangetic Plains on mountain water resources, using a coupled state-of-the-art, high-resolution, cryosphere-hydrology-crop model. We show that dependence varies strongly in space and time and is highest in the Indus basin, where in the pre-monsoon season up to 60% of the total irrigation withdrawals originate from mountain snow and glacier melt, and that it contributes an additional 11% to total crop production. Although dependence in the floodplains of the Ganges is comparatively lower, meltwater is still essential during the dry season, in particular for crops such as sugar cane. The dependency on meltwater in the Brahmaputra is negligible. In total, 129 million farmers in the Indus and Ganges substantially depend on snow and glacier melt for their livelihoods. Snow and glacier melt provides enough water to grow food crops to sustain a balanced diet for 38 million people. These findings provide important information for agricultural and climate change adaptation policies in a climate change hot spot where shifts in water availability and demand are projected as a result of climate change and socio-economic growth.
C1 [Biemans, H.; Siderius, C.] Wageningen Univ & Res, Wageningen, Netherlands.
   [Biemans, H.; Nepal, S.; Wester, P.; Shrestha, A. B.] Int Ctr Integrated Mt Dev, Kathmandu, Nepal.
   [Siderius, C.] London Sch Econ, London, England.
   [Lutz, A. F.; Wijngaard, R. R.] FutureWater, Wageningen, Netherlands.
   [Lutz, A. F.; Wijngaard, R. R.; Immerzeel, W. W.] Univ Utrecht, Utrecht, Netherlands.
   [Ahmad, B.] Pakistan Agr Res Council, Islamabad, Pakistan.
   [Hassan, T.] Bangladesh Ctr Adv Studies, Dhaka, Bangladesh.
   [von Bloh, W.] Potsdam Inst Climate Impact Res, Potsdam, Germany.
C3 Wageningen University & Research; University of London; London School
   Economics & Political Science; Utrecht University; National Agricultural
   Research Council - Pakistan; Potsdam Institut fur Klimafolgenforschung
RP Biemans, H (corresponding author), Wageningen Univ & Res, Wageningen, Netherlands.; Biemans, H (corresponding author), Int Ctr Integrated Mt Dev, Kathmandu, Nepal.
EM hester.biemans@wur.nl
RI Hassan, Tarek/T-9225-2019; Immerzeel, Walter/E-2489-2012; Wester,
   Philippus/B-7186-2008
OI Hassan, S. M. Tanvir/0000-0001-9340-6226; Lutz,
   Arthur/0000-0002-6327-1487; Wester, Philippus/0000-0002-0126-7853;
   Siderius, christian/0000-0002-2201-9728; Wijngaard,
   Rene/0000-0002-2131-9761; Shrestha, Arun Bhakta/0000-0002-1757-6589;
   Biemans, Hester/0000-0001-8750-2553
FU UK Government's Department for International Development; International
   Development Research Centre, Ottawa, Canada; ICIMOD by the government of
   Afghanistan; ICIMOD by the government of Australia; ICIMOD by the
   government of Austria; ICIMOD by the government of Bangladesh; ICIMOD by
   the government of Bhutan; ICIMOD by the government of China; ICIMOD by
   the government of India; ICIMOD by the government of Myanmar; ICIMOD by
   the government of Nepal; ICIMOD by the government of Norway; ICIMOD by
   the government of Pakistan; ICIMOD by the government of Switzerland;
   ICIMOD by the government of United Kingdom; European Research Council
   under the European Union [676819]; research programme VIDI - Netherlands
   Organisation for Scientific Research [016.161.308]; European Research
   Council (ERC) [676819] Funding Source: European Research Council (ERC)
FX This work was carried out by the Himalayan Adaptation, Water and
   Resilience consortium under the Collaborative Adaptation Research
   Initiative in Africa and Asia with financial support from the UK
   Government's Department for International Development and the
   International Development Research Centre, Ottawa, Canada.This work was
   also partially supported by core funds from ICIMOD contributed by the
   governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan,
   China, India, Myanmar, Nepal, Norway, Pakistan, Switzerland and the
   United Kingdom. W.W.I. has been supported by the European Research
   Council under the European Union's Horizon 2020 research and innovation
   programme (grant agreement no. 676819) and by the research programme
   VIDI (project no. 016.161.308), which is financed by the Netherlands
   Organisation for Scientific Research.
CR Aggarwal PK, 2004, ENVIRON SCI POLICY, V7, P487, DOI 10.1016/j.envsci.2004.07.006
   Andermann C, 2012, NAT GEOSCI, V5, P127, DOI [10.1038/NGEO1356, 10.1038/ngeo1356]
   Bagla P, 2014, SCIENCE, V345, P128, DOI 10.1126/science.345.6193.128
   Biemans H, 2011, WATER RESOUR RES, V47, DOI 10.1029/2009WR008929
   Biemans H, 2016, HYDROL EARTH SYST SC, V20, P1971, DOI 10.5194/hess-20-1971-2016
   Bliss A, 2014, J GEOPHYS RES-EARTH, V119, P717, DOI 10.1002/2013JF002931
   Bondeau A, 2007, GLOBAL CHANGE BIOL, V13, P679, DOI 10.1111/j.1365-2486.2006.01305.x
   Cai YY, 2016, ENVIRON MODELL SOFTW, V75, P459, DOI 10.1016/j.envsoft.2015.10.024
   Cheema MJM, 2010, AGR WATER MANAGE, V97, P1541, DOI 10.1016/j.agwat.2010.05.009
   De Souza K, 2015, REG ENVIRON CHANGE, V15, P747, DOI 10.1007/s10113-015-0755-8
   Fader M, 2010, J HYDROL, V384, P218, DOI 10.1016/j.jhydrol.2009.12.011
   Gerten D, 2011, J HYDROMETEOROL, V12, P885, DOI 10.1175/2011JHM1328.1
   Godfray HCJ, 2010, SCIENCE, V327, P812, DOI 10.1126/science.1185383
   Goldewijk KK, 2010, HOLOCENE, V20, P565, DOI 10.1177/0959683609356587
   Govt. of India, 2018, AGR STAT GLANC
   Hanasz P, 2017, WATER ALTERN, V10, P459
   Huss M, 2018, NAT CLIM CHANGE, V8, P135, DOI 10.1038/s41558-017-0049-x
   Immerzeel WW, 2015, HYDROL EARTH SYST SC, V19, P4673, DOI 10.5194/hess-19-4673-2015
   Immerzeel WW, 2010, SCIENCE, V328, P1382, DOI 10.1126/science.1183188
   Immerzeel WW, 2012, MT RES DEV, V32, P30, DOI 10.1659/MRD-JOURNAL-D-11-00097.1
   Jägermeyr J, 2015, HYDROL EARTH SYST SC, V19, P3073, DOI 10.5194/hess-19-3073-2015
   Kaser G, 2010, P NATL ACAD SCI USA, V107, P20223, DOI 10.1073/pnas.1008162107
   Kirby M, 2017, AGR WATER MANAGE, V179, P34, DOI 10.1016/j.agwat.2016.06.001
   Knox J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034032
   Kraaijenbrink PDA, 2017, NATURE, V549, P257, DOI 10.1038/nature23878
   Kummu M, 2014, HYDROL EARTH SYST SC, V18, P447, DOI 10.5194/hess-18-447-2014
   Loo YY, 2015, GEOSCI FRONT, V6, P817, DOI 10.1016/j.gsf.2014.02.009
   Lutz AF, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0165630
   Lutz AF, 2014, NAT CLIM CHANGE, V4, P587, DOI [10.1038/nclimate2237, 10.1038/NCLIMATE2237]
   Munia HA, 2018, HYDROL EARTH SYST SC, V22, P2795, DOI 10.5194/hess-22-2795-2018
   O'Brien K, 2004, GLOBAL ENVIRON CHANG, V14, P303, DOI 10.1016/j.gloenvcha.2004.01.001
   Pastor AV, 2014, HYDROL EARTH SYST SC, V18, P5041, DOI 10.5194/hess-18-5041-2014
   Portmann FT, 2010, GLOBAL BIOGEOCHEM CY, V24, DOI 10.1029/2008GB003435
   Pritchard HD, 2019, NATURE, V569, P649, DOI 10.1038/s41586-019-1240-1
   Rasul G, 2014, ENVIRON SCI POLICY, V39, P35, DOI 10.1016/j.envsci.2014.01.010
   Rockström J, 2007, P NATL ACAD SCI USA, V104, P6253, DOI 10.1073/pnas.0605739104
   Rodell M, 2009, NATURE, V460, P999, DOI 10.1038/nature08238
   Schaphoff S, 2018, GEOSCI MODEL DEV, V11, P1343, DOI 10.5194/gmd-11-1343-2018
   Scott CA, 2009, INT J RIVER BASIN MA, V7, P119, DOI 10.1080/15715124.2009.9635374
   Shah T, 2003, NAT RESOUR FORUM, V27, P130, DOI 10.1111/1477-8947.00048
   Siderius C, 2013, SCI TOTAL ENVIRON, V468, pS93, DOI 10.1016/j.scitotenv.2013.05.084
   Smith T, 2018, SCI ADV, V4, DOI 10.1126/sciadv.1701550
   Terink W, 2015, GEOSCI MODEL DEV, V8, P2009, DOI 10.5194/gmd-8-2009-2015
   Thayyen RJ, 2010, CRYOSPHERE, V4, P115, DOI 10.5194/tc-4-115-2010
   Tiwari VM, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL039401
   van Vliet MTH, 2016, GLOBAL ENVIRON CHANG, V40, P156, DOI 10.1016/j.gloenvcha.2016.07.007
   Von Grebmer K.V., 2012, Global Hunger Index. The Challenge of Hunger: Taming Price Spikes and Excessive Food Price Volatility
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Wijngaard RR, 2018, HYDROL EARTH SYST SC, V22, P6297, DOI 10.5194/hess-22-6297-2018
NR 52
TC 204
Z9 225
U1 18
U2 199
PU NATURE RESEARCH
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2398-9629
J9 NAT SUSTAIN
JI Nat. Sustain.
PD JUL
PY 2019
VL 2
IS 7
BP 594
EP 601
DI 10.1038/s41893-019-0305-3
PG 8
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA IH7LK
UT WOS:000474685000017
DA 2025-01-10
ER

PT J
AU Felzer, B
   Sahagian, D
AF Felzer, Benjamin
   Sahagian, Dork
TI Climate impacts on regional ecosystem services in the United States from
   CMIP3-based multimodel comparisons
SO CLIMATE RESEARCH
LA English
DT Article
DE Inter-model comparison; IPCC scenarios; Regional downscaling;
   Ecohydrology
ID NET PRIMARY PRODUCTION; CARBON SEQUESTRATION; CLOUD FEEDBACK; MODEL;
   UNCERTAINTY; SIMULATIONS; PROJECTIONS; TRENDS; COVER; PRECIPITATION
AB Projections of surface hydrology and local ecosystem responses to expected climate change in the 21st century can inform regional planners and land use managers in the broader context of climate change adaptation at regional scales. We use bias-corrected and downscaled projections for 3 IPCC scenarios (B1, A1B, and A2) to assess projected climate impacts on ecosystem function and services for different regions of the conterminous USA utilizing the Terrestrial Ecosystems Model version Hydro. Significance of model trends is analyzed for each of the 6 US National Climate Assessment megaregions for several climatological, hydrological, and ecological variables based on projections and consistency among the multimodel ensemble from phase 3 of the Coupled Model Intercomparison Project (CMIP3). Our regional analysis reveals that there are some robust and significant trends that can be useful to decision-makers, and that these trends are specific to each region, as each region responds to climate forcing differently in ways that reflect emergent behavior from the interaction of climate, ecosystem, and surface processes. Generally, runoff is simulated to increase in winter and decrease in summer throughout the northern USA, snowpack is reduced everywhere, and net primary productivity and maize yield increase except where limited by moisture. Model reconstructions of magnitudes and directions of some historical regional trends are incorrect, so predicted reversals may be spurious. Some model variables such as precipitation show no significant projected trends, yet in concert, they control the responses of other variables such as soil moisture, in which the trends are projected to be significant. As such, variables whose trends are less observable may be revealed by other variables controlled by them, and can thus be used as proxies to enhance predictive capacity.
C1 [Felzer, Benjamin; Sahagian, Dork] Lehigh Univ, Dept Earth & Environm Sci, Bethlehem, PA 18015 USA.
C3 Lehigh University
RP Felzer, B (corresponding author), Lehigh Univ, Dept Earth & Environm Sci, 1 West Packer Ave, Bethlehem, PA 18015 USA.
EM bsf208@lehigh.edu
RI Felzer, Benjamin/AAB-3456-2021
OI Felzer, Benjamin/0000-0002-3990-3739
FU US Department of Energy subaward from the Massachusetts Institute of
   Technology (MIT); Westwind Foundation
FX This study was funded by the US Department of Energy subaward from the
   Massachusetts Institute of Technology (MIT) for An Integrated Framework
   for Climate Change Assessment and by the Westwind Foundation. We
   acknowledge the modeling groups, the Program for Climate Model Diagnosis
   and Intercomparison, and the WCRP's Working Group on Coupled Modelling
   for their roles in making available the WCRP CMIP3 multimodel dataset.
   Support of this dataset is provided by the Office of Science, US
   Department of Energy. We also acknowledge the Global Land Cover Facility
   dataset. We especially thank Colin Prentice, Chris Forest, John Reilly,
   and Mike MacCracken for insightful comments.
CR ANGELL JK, 1990, J CLIMATE, V3, P296, DOI 10.1175/1520-0442(1990)003<0296:VIUSCA>2.0.CO;2
   [Anonymous], 2013, CONTRIBUTION WORKING
   [Anonymous], 2007, CLIMATE CHANGE 2007
   [Anonymous], 2007, AR4 CLIM CHANG 2007
   [Anonymous], CROP PROD 2013 SUMM
   [Anonymous], P 13 ARM SCI TEAM M
   [Anonymous], UNDERSTANDING EARTH
   [Anonymous], 2009, Global climate change impacts in the Unites States
   [Anonymous], PENNSYLVANIA CLIMATE
   [Anonymous], 2001, CLIM CHANG IMP US PO
   Baldocchi D, 1998, AGR FOREST METEOROL, V90, P1, DOI 10.1016/S0168-1923(97)00072-5
   Baldocchi D, 2000, BOUND-LAY METEOROL, V96, P257, DOI 10.1023/A:1002497616547
   Caspersen JP, 2000, SCIENCE, V290, P1148, DOI 10.1126/science.290.5494.1148
   Curtis PS, 2002, AGR FOREST METEOROL, V113, P3, DOI 10.1016/S0168-1923(02)00099-0
   DALY C, 1994, J APPL METEOROL, V33, P140, DOI 10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2
   Dangal SRS, 2014, J GEOPHYS RES-BIOGEO, V119, P35, DOI 10.1002/2013JG002409
   Defries RS, 2000, GLOBAL CHANGE BIOL, V6, P247, DOI 10.1046/j.1365-2486.2000.00296.x
   Dessler AE, 2010, SCIENCE, V330, P1523, DOI 10.1126/science.1192546
   Diffenbaugh NS, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035075
   Dorigo W, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052988
   Felzer B, 2004, TELLUS B, V56, P230, DOI 10.1111/j.1600-0889.2004.00097.x
   Felzer BS, 2012, ECOL MODEL, V240, P49, DOI 10.1016/j.ecolmodel.2012.05.003
   Felzer BS, 2011, J GEOPHYS RES-BIOGEO, V116, DOI 10.1029/2010JG001621
   Felzer BS, 2009, J GEOPHYS RES-BIOGEO, V114, DOI 10.1029/2008JG000826
   Flanner MG, 2011, NAT GEOSCI, V4, P151, DOI [10.1038/ngeo1062, 10.1038/NGEO1062]
   Forest CE, 2008, TELLUS A, V60, P911, DOI 10.1111/j.1600-0870.2008.00346.x
   Giorgi F, 2002, J CLIMATE, V15, P1141, DOI 10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2
   Giorgi F, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL037593
   Groisman PY, 2000, J CLIMATE, V13, P1858, DOI 10.1175/1520-0442(2000)013<1858:TROCCT>2.0.CO;2
   Hansen MC, 2000, INT J REMOTE SENS, V21, P1331, DOI 10.1080/014311600210209
   Hanson PJ, 2004, ECOL MONOGR, V74, P443, DOI 10.1890/03-4049
   Hayhoe K, 2004, P NATL ACAD SCI USA, V101, P12422, DOI 10.1073/pnas.0404500101
   Hayhoe K, 2008, MITIG ADAPT STRAT GL, V13, P425, DOI 10.1007/s11027-007-9133-2
   Hayhoe K, 2007, CLIM DYNAM, V28, P381, DOI 10.1007/s00382-006-0187-8
   Heath LS, 2003, POTENTIAL OF U.S. FOREST SOILS TO SEQUESTER CARBON AND MITIGATE THE GREENHOUSE EFFECT, P35
   HENDERSON-SELLERS A, 1989, GLOBAL PLANET CHANGE, V75, P175
   Hicke JA, 2002, GLOBAL BIOGEOCHEM CY, V16, DOI [10.1029/2002GB001876, 10.1029/2001GB001550]
   Hicke JA, 2002, GEOPHYS RES LETT, V29, DOI 10.1029/2001GL013578
   Houghton RA, 1999, SCIENCE, V285, P574, DOI 10.1126/science.285.5427.574
   Jung M, 2007, BIOGEOSCIENCES, V4, P647, DOI 10.5194/bg-4-647-2007
   Jung M, 2009, BIOGEOSCIENCES, V6, P2001, DOI 10.5194/bg-6-2001-2009
   Jung M, 2011, J GEOPHYS RES-BIOGEO, V116, DOI 10.1029/2010JG001566
   Katz RW, 2002, CLIM RES, V20, P167, DOI 10.3354/cr020167
   KLEIN SA, 1993, J CLIMATE, V6, P1587, DOI 10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2
   Knutti R, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034932
   Knutti R, 2010, J CLIMATE, V23, P2739, DOI 10.1175/2009JCLI3361.1
   LETTENMAIER DP, 1994, J CLIMATE, V7, P586, DOI 10.1175/1520-0442(1994)007<0586:HCTITC>2.0.CO;2
   Liepert BG, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014006
   Lins HF, 1999, GEOPHYS RES LETT, V26, P227, DOI 10.1029/1998GL900291
   Maurer E.P., 2007, Eos, Transactions, American Geophysical Union, V88, DOI 10.1029/2007EO470006
   Maurer EP, 2007, CLIMATIC CHANGE, V82, P309, DOI 10.1007/s10584-006-9180-9
   Maurer EP, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2004GL021462
   McCabe GJ, 2002, CLIMATE RES, V20, P19, DOI 10.3354/cr020019
   Meehl GA, 2007, B AM METEOROL SOC, V88, P1383, DOI 10.1175/BAMS-88-9-1383
   Melillo JM, 2002, SCIENCE, V298, P2173, DOI 10.1126/science.1074153
   Nemani RR, 2003, SCIENCE, V300, P1560, DOI 10.1126/science.1082750
   Orlowsky B, 2012, CLIMATIC CHANGE, V110, P669, DOI 10.1007/s10584-011-0122-9
   Pacala SW, 2001, SCIENCE, V292, P2316, DOI 10.1126/science.1057320
   Pierce DW, 2009, P NATL ACAD SCI USA, V106, P8441, DOI 10.1073/pnas.0900094106
   Portmann RW, 2009, P NATL ACAD SCI USA, V106, P7324, DOI 10.1073/pnas.0808533106
   RAICH JW, 1991, ECOL APPL, V1, P399, DOI 10.2307/1941899
   Schaefer K, 2008, J GEOPHYS RES-BIOGEO, V113, DOI 10.1029/2007JG000603
   Schimel D, 2000, SCIENCE, V287, P2004, DOI 10.1126/science.287.5460.2004
   Schneider von Deimling T, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL026484
   Sheffield J, 2012, NATURE, V491, P435, DOI 10.1038/nature11575
   Shiogama H, 2011, NAT COMMUN, V2, DOI 10.1038/ncomms1252
   Sokolov AP, 2008, J CLIMATE, V21, P3776, DOI 10.1175/2008JCLI2038.1
   Stephens GL, 2005, J CLIMATE, V18, P237, DOI 10.1175/JCLI-3243.1
   Sun BM, 2001, J CLIMATE, V14, P1864, DOI 10.1175/1520-0442(2001)014<1864:RCICTF>2.0.CO;2
   Walter MT, 2004, J HYDROMETEOROL, V5, P405, DOI 10.1175/1525-7541(2004)005<0405:IEFTCU>2.0.CO;2
   WETHERALD RT, 1988, J ATMOS SCI, V45, P1397, DOI 10.1175/1520-0469(1988)045<1397:CFPIAG>2.0.CO;2
   Williams KD, 2007, CLIM DYNAM, V29, P231, DOI 10.1007/s00382-007-0232-2
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Wood AW, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD000659
   Woodbury PB, 2007, FOREST ECOL MANAG, V241, P14, DOI 10.1016/j.foreco.2006.12.008
   Xiao JF, 2011, AGR FOREST METEOROL, V151, P60, DOI 10.1016/j.agrformet.2010.09.002
   Zhang MH, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2004JD005021
NR 77
TC 4
Z9 7
U1 2
U2 30
PU INTER-RESEARCH
PI OLDENDORF LUHE
PA NORDBUNTE 23, D-21385 OLDENDORF LUHE, GERMANY
SN 0936-577X
EI 1616-1572
J9 CLIM RES
JI Clim. Res.
PD SEP
PY 2014
VL 61
IS 2
BP 133
EP 155
DI 10.3354/cr01249
PG 23
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA AS0JN
UT WOS:000343963700004
OA Bronze
DA 2025-01-10
ER

PT J
AU Lu, PX
   Parker, WH
   Cherry, M
   Colombo, S
   Parker, WC
   Man, RZ
   Roubal, N
AF Lu, Pengxin
   Parker, William H.
   Cherry, Marilyn
   Colombo, Steve
   Parker, William C.
   Man, Rongzhou
   Roubal, Ngaire
TI Survival and growth patterns of white spruce (<i>Picea glauca</i>
   [Moench] Voss) rangewide provenances and their implications for climate
   change adaptation
SO ECOLOGY AND EVOLUTION
LA English
DT Article
DE Assisted migration; genetic conservation; genetic gain; geographic
   genetic variation; local adaptation; universal response function
ID GENETIC-VARIATION; TRANSFER GUIDELINES; LOCAL ADAPTATION; SEED TRANSFER;
   DOUGLAS-FIR; JACK PINE; POPULATIONS; RESISTANCE; PHENOLOGY; TESTS
AB Intraspecific assisted migration (ISAM) through seed transfer during artificial forest regeneration has been suggested as an adaptation strategy to enhance forest resilience and productivity under future climate. In this study, we assessed the risks and benefits of ISAM in white spruce based on long-term and multilocation, rangewide provenance test data. Our results indicate that the adaptive capacity and growth potential of white spruce varied considerably among 245 range-wide provenances sampled across North America; however, the results revealed that local populations could be outperformed by nonlocal ones. Provenances originating from south-central Ontario and southwestern Quebec, Canada, close to the southern edge of the species' natural distribution, demonstrated superior growth in more northerly environments compared with local populations and performed much better than populations from western Canada and Alaska, United States. During the 19-28 years between planting and measurement, the southern provenances have not been more susceptible to freezing damage compared with local populations, indicating they have the potential to be used now for the reforestation of more northerly planting sites; based on changing temperature, these seed sources potentially could maintain or increase white spruce productivity at or above historical levels at northern sites. A universal response function (URF), which uses climatic variables to predict provenance performance across field trials, indicated a relatively weak relationship between provenance performance and the climate at provenance origin. Consequently, the URF from this study did not provide information useful to ISAM. The ecological and economic importance of conserving white spruce genetic resources in south-central Ontario and southwestern Quebec for use in ISAM is discussed.
C1 [Lu, Pengxin; Colombo, Steve; Parker, William C.; Man, Rongzhou; Roubal, Ngaire] Ontario Minist Nat Resources, Ontario Forest Res Inst, Sault Ste Marie, ON P6A 2E5, Canada.
   [Parker, William H.] Lakehead Univ, Fac Forestry & Forest Environm, Thunder Bay, ON P7B 5E1, Canada.
   [Cherry, Marilyn] Oregon State Univ, Coll Forestry, Corvallis, OR 97331 USA.
C3 Ministry of Natural Resources & Forestry; Lakehead University; Oregon
   State University
RP Lu, PX (corresponding author), Ontario Minist Nat Resources, Ontario Forest Res Inst, 1235 Queen St East, Sault Ste Marie, ON P6A 2E5, Canada.
EM pengxin.lu@ontario.ca
FU Government of Ontario Interministerial Climate Change Committee [CC-145]
FX Government of Ontario Interministerial Climate Change Committee under
   the Project CC-145.
CR Aitken S. N., 2000, Journal of Sustainable Forestry, V10, P1
   Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   Anderson LL, 2006, P NATL ACAD SCI USA, V103, P12447, DOI 10.1073/pnas.0605310103
   [Anonymous], SAS STAT 9 2 US GUID
   [Anonymous], 1992, Variance Components
   Bannister P, 2001, TREE PHYSIOL SER, V1, P3
   BLUM BM, 1988, CAN J FOREST RES, V18, P315, DOI 10.1139/x88-048
   CAMPBELL RK, 1979, ECOLOGY, V60, P1036, DOI 10.2307/1936871
   Carter KK, 1996, CAN J FOREST RES, V26, P1089, DOI 10.1139/x26-120
   Cherry M., 2003, 160 ONT MIN NAT RES
   CLEMENTS J R, 1972, Canadian Journal of Forest Research, V2, P62, DOI 10.1139/x72-013
   de Lafontaine G, 2010, J BIOGEOGR, V37, P741, DOI 10.1111/j.1365-2699.2009.02241.x
   EKBERG I, 1994, SCAND J FOREST RES, V9, P25, DOI 10.1080/02827589409382809
   Fournier-Level A, 2011, SCIENCE, V334, P86, DOI 10.1126/science.1209271
   GOELZ JCG, 1992, CAN J FOREST RES, V22, P776, DOI 10.1139/x92-106
   Goldblum D, 2005, CAN J FOREST RES, V35, P2709, DOI 10.1139/X05-185
   Hamann A, 2011, TREE GENET GENOMES, V7, P399, DOI 10.1007/s11295-010-0341-7
   Henderson C. R., 1984, APPL LINEAR MODELS A
   Huang JG, 2010, GLOBAL CHANGE BIOL, V16, P711, DOI 10.1111/j.1365-2486.2009.01990.x
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Johnston M., 2009, Vulnerability of Canada's tree species to climate change and management options for adaptation: an overview for policy makers and practitioners
   KHALIL MAK, 1985, CAN J FOREST RES, V15, P444, DOI 10.1139/x85-071
   Leech SM., 2011, BC J ECOSYSTEMS MANA, V12, P18
   Lesser MR, 2004, CAN J FOREST RES, V34, P1119, DOI [10.1139/x03-286, 10.1139/X03-286]
   LI P, 1993, SILVAE GENET, V42, P52
   Li P, 1997, CAN J FOREST RES, V27, P189, DOI 10.1139/cjfr-27-2-189
   Lynch Michael, 1998
   Man RZ, 2009, FOREST CHRON, V85, P453, DOI 10.5558/tfc85453-3
   MATYAS C, 1992, SILVAE GENET, V41, P370
   MATYAS C, 1994, TREE PHYSIOL, V14, P797, DOI 10.1093/treephys/14.7-8-9.797
   Mckenney DW, 2007, BIOSCIENCE, V57, P939, DOI 10.1641/B571106
   McKenney DW, 1999, ENVIRON MODELL SOFTW, V14, P589, DOI 10.1016/S1364-8152(98)00095-4
   Morgenstern E. K., 1999, STX16 CAN FOR SERV S
   MORGENSTERN EK, 1990, CAN J FOREST RES, V20, P130, DOI 10.1139/x90-019
   Morgenstern K, 2006, FOREST CHRON, V82, P572, DOI 10.5558/tfc82572-4
   Namroud MC, 2008, MOL ECOL, V17, P3599, DOI 10.1111/j.1365-294X.2008.03840.x
   Neinstadt H., 1990, Silvics of North America Vol. 1 Conifers, V1, P204
   Nienstaedt H., 1969, Proc. Eleventh Mtg. Comm. For. Tree Breed. Can, P183
   O'Neill G., 2013, ASSISTED MIGRATION B
   Ontario Ministry of Natural Resources (OMNR), 2006, STAT FOR REP 2006
   OREILLY C, 1982, CAN J FOREST RES, V12, P408, DOI 10.1139/x82-058
   PARKER WH, 1992, CAN J FOREST RES, V22, P267, DOI 10.1139/x92-035
   Partanen J, 1999, SCAND J FOREST RES, V14, P487, DOI 10.1080/02827589908540813
   PASTOR J, 1988, NATURE, V334, P55, DOI 10.1038/334055a0
   Payandeh Bijan, 1995, Northern Journal of Applied Forestry, V12, P57
   Popovich S., 1972, ZX29 CAN FOR SERV LA
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Rahmstorf S, 1999, CLIMATIC CHANGE, V43, P353, DOI 10.1023/A:1005474526406
   Rauscher H. M., 1993, Northern Journal of Applied Forestry, V10, P112
   Rehfeldt GE, 1999, ECOL MONOGR, V69, P375, DOI 10.1890/0012-9615(1999)069[0375:GRTCIP]2.0.CO;2
   REHFELDT GE, 1989, FOREST ECOL MANAG, V28, P203, DOI 10.1016/0378-1127(89)90004-2
   RITCHIE JC, 1986, J BIOGEOGR, V13, P527, DOI 10.2307/2844816
   Rweyyongeza D. M., 2011, ALBERTA SUSTAI RESOU
   SAKAI A, 1983, CAN J BOT, V61, P2323, DOI 10.1139/b83-255
   SAKAI A, 1979, PLANT CELL PHYSIOL, V20, P1381, DOI 10.1093/oxfordjournals.pcp.a075937
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   SCHMIDTLING RC, 1994, TREE PHYSIOL, V14, P805, DOI 10.1093/treephys/14.7-8-9.805
   SIMPSON DG, 1994, CAN J FOREST RES, V24, P1066, DOI 10.1139/x94-140
   Skroppa T., 1982, SILVA FENNICA, V16, P160, DOI DOI 10.14214/SF.A15075
   Sogaard G, 2008, TREE PHYSIOL, V28, P311, DOI 10.1093/treephys/28.2.311
   SORK VL, 1993, AM NAT, V142, P928, DOI 10.1086/285581
   Thomson AM, 2008, CAN J FOREST RES, V38, P157, DOI 10.1139/X07-122
   Wang T, 2006, GLOBAL CHANGE BIOL, V12, P2404, DOI 10.1111/j.1365-2486.2006.01271.x
   Wang TL, 2010, ECOL APPL, V20, P153, DOI 10.1890/08-2257.1
   White T. L., 2007, Forest Genetics
   White T.L., 1989, Predicting Breeding Values with Applications in Forest Tree Improvement
   Wu HX, 2004, FOREST ECOL MANAG, V194, P177, DOI 10.1016/j.foreco.2004.02.017
   Ying CC, 2006, FOREST ECOL MANAG, V227, P1, DOI 10.1016/j.foreco.2006.02.028
   Young AG, 2000, FOREST CONSERVATION
NR 69
TC 50
Z9 54
U1 2
U2 84
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2045-7758
J9 ECOL EVOL
JI Ecol. Evol.
PD JUN
PY 2014
VL 4
IS 12
BP 2360
EP 2374
DI 10.1002/ece3.1100
PG 15
WC Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology
GA AJ5PX
UT WOS:000337738800005
PM 25360273
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Wilby, RL
   Orr, HG
   Hedger, M
   Forrow, D
   Blackmore, M
AF Wilby, R. L.
   Orr, H. G.
   Hedger, M.
   Forrow, D.
   Blackmore, M.
TI Risks posed by climate change to the delivery of Water Framework
   Directive objectives in the UK
SO ENVIRONMENT INTERNATIONAL
LA English
DT Article
DE climate change; probabilistic scenarios; water framework directive;
   risk; hydromorphology; monitoring
ID LONG-TERM CHANGES; ENVIRONMENTAL-CHANGE; POTENTIAL IMPACTS; WEATHER
   PATTERNS; CATCHMENT; QUALITY; SEA; VARIABILITY; VEGETATION; YORKSHIRE
AB The EU Water Framework Directive (WFD) is novel because it integrates water quality, water resources, physical habitat and, to some extent, flooding for all surface and groundwaters and takes forward river basin management. However, the WFD does not explicitly mention risks posed by climate change to the achievement of its environmental objectives. This is despite the fact that the time scale for the implementation process and achieving particular objectives extends into the 2020s, when climate models project changes in average temperature and precipitation. This paper begins by reviewing the latest UK climate change scenarios and the wider policy and science context of the WFD. We then examine the potential risks of climate change to key phases of the River Basin Management Process that underpin the WFD (such as charactelisation of liver basins and their water bodies, risk assessments to identify pressures and impacts, programmes of measures (POMs) options appraisal, monitoring and modelling, policy and management activities). Despite these risks the WFD could link new policy and participative mechanisms (being established for the River Basin Management Plans) to the emerging framework of national and regional climate change adaptation policy. The risks are identified with a view to informing policy opportunities, objective setting, adaptation strategies and the research agenda. Key knowledge gaps have already been identified during the implementation of the WFD, such as the links between hydromorphology and ecosystem status, but the overarching importance of linking climate change to these considerations needs to be highlighted. The next generation of (probabilistic) climate change scenarios will present new opportunities and challenges for risk analysis and policy-making. (c) 2006 Elsevier Ltd. All lights reserved.
C1 Univ Lancaster, Dept Geog, Lancaster LA1 4YW, England.
C3 Lancaster University
EM rob.wilby@environment-agency.gov.uk
RI Orr, Harriet/AAP-2665-2020
OI Orr, Harriet/0000-0001-5021-1074; Wilby, Robert/0000-0002-4662-9344
CR [Anonymous], WHAT WE NEED KNOW DE
   [Anonymous], 2002, CLIMATE CHANGE SCENA
   [Anonymous], 2000, CLIMATE CHANGE ASSES
   ARNELLNW, 2002, EFFECT CLIMATE CHANG
   Beaugrand G, 2003, GLOBAL CHANGE BIOL, V9, P801, DOI 10.1046/j.1365-2486.2003.00632.x
   Bradley DC, 2001, J ANIM ECOL, V70, P987, DOI 10.1046/j.0021-8790.2001.00551.x
   Brewin PA, 1996, ENVIRON POLLUT, V93, P147, DOI 10.1016/0269-7491(96)00028-0
   Brierley GJ, 2000, ENVIRON MANAGE, V25, P661, DOI 10.1007/s002670010052
   BROOKER MP, 1977, J APPL ECOL, V14, P409, DOI 10.2307/2402554
   Brookes A., 1988, CHANNELIZED RIVERS P
   Brovkin V, 2003, CLIMATIC CHANGE, V57, P119, DOI 10.1023/A:1022168609525
   Cammeraat LH, 2002, EARTH SURF PROC LAND, V27, P1201, DOI 10.1002/esp.421
   Charman DJ, 2000, CLIMATIC CHANGE, V47, P45, DOI 10.1023/A:1005673624994
   Clarke RT, 2003, ECOL MODEL, V160, P219, DOI 10.1016/S0304-3800(02)00255-7
   CODLING I, 2003, X1043TR R D ENV AG
   Coulthard TJ, 2000, HYDROL PROCESS, V14, P2031, DOI 10.1002/1099-1085(20000815/30)14:11/12<2031::AID-HYP53>3.0.CO;2-G
   Crane M, 2005, HUM ECOL RISK ASSESS, V11, P289, DOI 10.1080/10807030590925740
   *DEFR, 2005, MAK SPAC WAT, P8
   Dennis IA, 2003, HYDROL PROCESS, V17, P1641, DOI 10.1002/hyp.1206
   Dils RM, 1999, WATER SCI TECHNOL, V39, P55, DOI 10.1016/S0273-1223(99)00318-2
   Dockerty T, 2003, GLOBAL ENVIRON CHANG, V13, P125, DOI 10.1016/S0959-3780(03)00010-4
   DOKULI MT, 2004, CLIM CHANG AQ EC PAS
   Dunn SM, 2003, J ENVIRON MANAGE, V68, P95, DOI 10.1016/S0301-4797(03)00006-9
   Edmunds WM, 2003, SCI TOTAL ENVIRON, V310, P25, DOI 10.1016/S0048-9697(02)00620-4
   Elliott JM, 1997, J APPL ECOL, V34, P1229, DOI 10.2307/2405234
   *ENV AG, 2005, ANTHR INFL TEMP REG
   *ENV AG, 2004, WAT LIF LIV STRAT RI
   Ferrier RC, 2002, SCI TOTAL ENVIRON, V294, P57, DOI 10.1016/S0048-9697(02)00052-9
   GEBREMESKEL S, 2003, THESIS U BRUSSELS BE
   Gerten D, 2000, LIMNOL OCEANOGR, V45, P1058, DOI 10.4319/lo.2000.45.5.1058
   Grimvall A, 2000, ECOL ENG, V14, P363, DOI 10.1016/S0925-8574(99)00061-0
   Harrison P.A., 2001, CLIMATE CHANGE NATUR
   Hawkins SJ, 2003, SCI TOTAL ENVIRON, V310, P245, DOI 10.1016/S0048-9697(02)00645-9
   HEDGER MM, 2005, BRIDGING GAP EMPOWER
   Hendon D, 2004, HOLOCENE, V14, P125, DOI 10.1191/0959683604hl695rp
   Hutjes RWA, 1998, J HYDROL, V212, P1, DOI 10.1016/S0022-1694(98)00255-8
   Irvine K, 2004, AQUAT CONSERV, V14, P107, DOI 10.1002/aqc.622
   Jansson R, 2002, ANNU REV ECOL SYST, V33, P741, DOI 10.1146/annurev.ecolsys.33.010802.150520
   JENKINS G, 2003, HANDLING UNCERTAINIT, V44
   *JOINT RES CTR, 2004, CLIM CHANG EUR WAT D
   LANDRUM PF, 1984, OIL FRESHWATER CHEM, P304
   Limbrick KJ, 2000, SCI TOTAL ENVIRON, V251, P539, DOI 10.1016/S0048-9697(00)00394-6
   Longfield SA, 1999, HYDROL PROCESS, V13, P1051, DOI 10.1002/(SICI)1099-1085(199905)13:7<1051::AID-HYP789>3.0.CO;2-R
   Macklin MG, 2003, J QUATERNARY SCI, V18, P101, DOI 10.1002/jqs.751
   *MAFF, 2001, FLOOD COAST DEF PROJ
   *OJC, 2000, OJ C L, V327, P1
   *OPDM, 2004, PLANN RESP CLIM CHAN
   Orr HG, 2006, RIVER RES APPL, V22, P239, DOI 10.1002/rra.908
   Parr TW, 2003, SCI TOTAL ENVIRON, V310, P1, DOI 10.1016/S0048-9697(03)00257-2
   Pearson RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361, DOI 10.1046/j.1466-822X.2003.00042.x
   Petts GE., 1989, Alternatives in Regulated River Management, P3
   RICKARD S, 2005, YIELDS FARMED SPECIE
   Sear DA, 2003, SCI TOTAL ENVIRON, V310, P17, DOI 10.1016/S0048-9697(02)00619-8
   Sims DW, 2001, P ROY SOC B-BIOL SCI, V268, P2607, DOI 10.1098/rspb.2001.1847
   SMITH RS, 1988, J APPL ECOL, V25, P579, DOI 10.2307/2403846
   Stalnacke P, 2003, J HYDROL, V283, P184, DOI 10.1016/S0022-1694(03)00266-X
   Underwood AJ, 2003, J EXP MAR BIOL ECOL, V296, P49, DOI 10.1016/S0022-0981(03)00304-6
   Van Vliet AJH, 2002, INT J CLIMATOL, V22, P1713, DOI 10.1002/joc.816
   Viles HA, 2003, EARTH-SCI REV, V61, P105, DOI 10.1016/S0012-8252(02)00113-7
   WEBB BW, 2004, CHANGING UK RIVER TE, P177
   Werritty A, 2002, SCI TOTAL ENVIRON, V294, P29, DOI 10.1016/S0048-9697(02)00050-5
   White I., 2003, Journal of Environmental Planning and Management, V46, P621, DOI DOI 10.1080/0964056032000133198
   WHITEHEAD PG, IN PRESS SCI TOTAL E
   Wilby R L., 2005, Weather, V60, P206
   Wilby RL, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004065
   Wilby RL, 1997, EARTH SURF PROC LAND, V22, P353, DOI 10.1002/(SICI)1096-9837(199704)22:4<353::AID-ESP692>3.0.CO;2-G
   WILBY RL, 1993, INT J CLIMATOL, V13, P447, DOI 10.1002/joc.3370130408
   Wilby Robert L., 2004, Ecohydrology & Hydrobiology, V4, P243
NR 68
TC 113
Z9 125
U1 0
U2 82
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0160-4120
EI 1873-6750
J9 ENVIRON INT
JI Environ. Int.
PD DEC
PY 2006
VL 32
IS 8
BP 1043
EP 1055
DI 10.1016/j.envint.2006.06.017
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 115HH
UT WOS:000242724900012
PM 16857260
DA 2025-01-10
ER

PT J
AU Sanz, VM
   Muñoz, SR
   Chaparro, TS
   Gómez, LB
   Herdt, T
AF Sanz, Victor Munoz
   Munoz, Sara Romero
   Chaparro, Teresa Sanchez
   Gomez, Lorena Bello
   Herdt, Tanja
TI Making Green Work: Implementation Strategies in a New Generation of
   Urban Forests
SO URBAN PLANNING
LA English
DT Article
DE climate adaptation; mainstreaming; planning process; urban forestry;
   urban greening
ID SUSTAINABILITY; TOOL; TRANSFORMATION; MANAGEMENT; CLIMATE; ENERGY
AB The concept of "urban forest" (UF) is gaining momentum in urban planning in the context of climate adaptation. Principles from the field of urban forestry are mainstreamed into urban planning, but little is known about effective tools for the successful implementation of new UFs. This article presents explorative research comparing how three cities (Almere, Madrid, and Boston) are dealing with the planning of a UF project, and their alignment with distinct organisational and typological interpretations of a UF. We employed a mixed-methods approach to gain insights into the main goals of the project, their organisational structure, and the employed planning process through the analysis of project documents and expert interviews. Our results point to an effective mainstreaming of environmental questions among stakeholders, but also indicate a poor development of objective criteria for the success of a UF. We note that municipal planners circumvented current internal rigidities and barriers by relying on intermediaries and local academia as providers of external knowledge, or by facilitating experiments. Finally, our results show that there may not be just one UF type to achieve the desired environmental and social goals and overcome implementation barriers. Conversely, each of the governance and organisational models behind the implementation of each type present collaborative and mainstreaming challenges. Therefore, we see an opportunity in further research examining processes and institutions towards the collaborative building of UFs that could bridge gaps between top-down and bottom-up approaches and activate different types of agencies.
C1 [Sanz, Victor Munoz; Herdt, Tanja] Delft Univ Technol, Dept Urbanism, Delft, Netherlands.
   [Munoz, Sara Romero; Chaparro, Teresa Sanchez] Univ Politecn Madrid, Innovat & Technol Human Dev Ctr, Madrid, Spain.
   [Gomez, Lorena Bello] Harvard Univ, Grad Sch Design, Cambridge, MA 02138 USA.
C3 Delft University of Technology; Universidad Politecnica de Madrid;
   Harvard University
RP Sanz, VM (corresponding author), Delft Univ Technol, Dept Urbanism, Delft, Netherlands.
EM v.munozsanz@tudelft.nl
RI Sanchez Chaparro, Teresa/ABE-3798-2021
OI Romero Munoz, Sara/0000-0001-9248-8936; Munoz Sanz,
   Victor/0000-0002-9604-0925; Sanchez-Chaparro,
   Teresa/0000-0003-3444-1501; Herdt, Tanja/0000-0003-2789-0667
CR 1t.org, 2020, PLATF TRILL TREE COM
   Allison Graham., 1999, ESSENCE DECISION, VSecond
   [Anonymous], 2009, MANAGE DECIS, DOI DOI 10.1108/00251740910978322
   [Anonymous], 2020, Communication from the commission on the EU security union strategy
   Antonenko M., 2020, MAKING GREEN CITIES, P180
   Assefa G, 2007, TECHNOL SOC, V29, P63, DOI 10.1016/j.techsoc.2006.10.007
   Barron S, 2016, FORESTS, V7, DOI 10.3390/f7090208
   Berrizbeitia Anita., 2007, Large Parks, P175
   Bulkeley H., 2013, ROUTLEDGE INT HDB SO, P173
   Cariñanos P, 2017, FUTURE CITY, V7, P79, DOI 10.1007/978-3-319-50280-9_9
   Carlsson-Kanyama A, 2008, FUTURES, V40, P34, DOI 10.1016/j.futures.2007.06.001
   Carreiro MM, 2008, SPRINGER SER ENV MAN, P3, DOI 10.1007/978-0-387-71425-7_1
   Cities4Forests, 2019, URB FOR HLTH CIT POL
   Croy O., 2017, Routledge Handb. Urban For., V17
   Davies C., 2017, GUIDELINES URBAN FOR
   De la Sota C, 2019, URBAN FOR URBAN GREE, V40, P145, DOI 10.1016/j.ufug.2018.09.004
   Sanz JLD, 2019, PLAN PERSPECT, V34, P725, DOI 10.1080/02665433.2019.1588154
   Dean J., 2009, METHOD MEAN ING CANA, P236
   EISENHARDT KM, 1989, ACAD MANAGE REV, V14, P532, DOI 10.2307/258557
   Endreny TA, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03622-0
   Ernst L, 2016, J CLEAN PROD, V112, P2988, DOI 10.1016/j.jclepro.2015.10.136
   European Commission, 2021, 3 BILL TREE PLANT PL
   FAO, 2013, SUBM FOOD AGR ORG UN
   Ferguson J, 2002, AM ETHNOL, V29, P981, DOI 10.1525/ae.2002.29.4.981
   Forster A., 2014, THESIS TUM
   Galunic DC, 2001, ACAD MANAGE J, V44, P1229, DOI 10.5465/3069398
   Gupta J., 2010, MAINSTREAMING CLIMAT, P67, DOI DOI 10.1017/CBO9780511712067.004
   Hölscher K, 2019, J ENVIRON MANAGE, V231, P843, DOI 10.1016/j.jenvman.2018.10.043
   Janssen MA, 2006, LANDSCAPE URBAN PLAN, V78, P71, DOI 10.1016/j.landurbplan.2005.05.005
   Jones J., 2017, URBAN FORESTS NATURA
   Karlsson-Vinkhuyzen SI, 2011, INST DIMENS GLOB ENV, P285
   KarlssonVinkhuyzen S., 2014, Mainstreaming biodiversity where it matters most
   Konijnendijk Cecil C., 2006, Urban Forestry & Urban Greening, V4, P93, DOI 10.1016/j.ufug.2005.11.003
   Macnaghten P, 2003, SOCIOL REV, V51, P63, DOI 10.1111/1467-954X.00408
   Mattern Shannon., Places Journal, P2021, DOI [DOI 10.22269/210921, https://doi.org/10.22269/210921]
   McBride JoeR., 2017, The World's Urban Forests: History, Composition, Design, Function and Management
   Meuser M, 2009, RES METHODS SER, P17
   Mieg HaroldA., 2006, EXPERTENINTERVIEWS U, DOI DOI 10.1016/j.futures.2008.09.013
   Mogelgaard K., 2018, From Planning to Action: Mainstreaming Climate Change Adaptation into Development
   Moreno-Serna J, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12020539
   Nye M, 2008, ENVIRON PLANN B, V35, P227, DOI 10.1068/b3379
   Ordóñez C, 2020, ENVIRON SCI POLICY, V104, P136, DOI 10.1016/j.envsci.2019.11.008
   Ordóñez C, 2019, LANDSCAPE URBAN PLAN, V189, P166, DOI 10.1016/j.landurbplan.2019.04.020
   Organisation for Economic Co-operation and Development (OECD), 2014, MAINSTR CROSS CUTT I
   Ottitsch Andreas., 2005, Urban Forests and Trees: A Reference Book, P117, DOI [DOI 10.1007/3-540-27684-X_6, DOI 10.1007/3-540-27684-X6]
   Perkins H, 2015, URBAN FORESTS, TREES, AND GREENSPACE: A POLITICAL ECOLOGY PERSPECTIVE, P19
   Pettigrew AM, 1990, ORGAN SCI, V1, P267, DOI 10.1287/orsc.1.3.267
   Purdon M, 2003, ENVIRON SCI POLICY, V6, P377, DOI 10.1016/S1462-9011(03)00064-9
   Randrup ThomasB., 2005, Urban Forests and Trees, P9
   ROGERS K., 2015, Valuing London'S Urban Forest. Results of the London i-Tree Eco Project. Treeconomics London
   Rogers K, 2017, FUTURE CITY, V7, P283, DOI 10.1007/978-3-319-50280-9_21
   Runhaar H, 2018, REG ENVIRON CHANGE, V18, P1201, DOI 10.1007/s10113-017-1259-5
   Sandberg L.A., 2014, URBAN FORESTS TREES
   Schwab J.C., 2009, Planning the Urban Forest: Ecology, Economy, and Community Development
   Scott A., 2019, ROUTLEDGE COMPANION, P420
   Smith NR, 2014, CITIES, V41, P209, DOI 10.1016/j.cities.2014.01.006
   Teo HC, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abe783
   Tyrvainen L., 2005, URBAN FORESTS TREES, P81
   Vervoort M, 2011, EUR SOCIOL REV, V27, P586, DOI 10.1093/esr/jcq029
   Walker DHT, 2008, CONSTR MANAG ECON, V26, P645, DOI 10.1080/01446190701882390
   White House, 2021, Fact sheet: the American jobs plan
   Wolfram M, 2019, AMBIO, V48, P437, DOI 10.1007/s13280-019-01169-y
   YIN RK, 1992, CURR SOCIOL, V40, P121, DOI 10.1177/001139292040001009
   YIN RK, 1981, KNOWLEDGE, V3, P97, DOI 10.1177/107554708100300106
   Young RF, 2013, URBAN ECOSYST, V16, P703, DOI 10.1007/s11252-013-0287-2
   Zuniga-Teran AA, 2020, J ENVIRON PLANN MAN, V63, P710, DOI 10.1080/09640568.2019.1605890
NR 66
TC 4
Z9 4
U1 4
U2 15
PU COGITATIO PRESS
PI LISBON
PA RUA FIALHO ALMEIDA 14, 2 ESQ, LISBON, 1070-129, PORTUGAL
SN 2183-7635
J9 URBAN PLAN
JI Urban Plan.
PY 2022
VL 7
IS 2
BP 202
EP 213
DI 10.17645/up.v7i2.5039
PG 12
WC Urban Studies
WE Emerging Sources Citation Index (ESCI)
SC Urban Studies
GA 1W5DT
UT WOS:000806794600008
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Roggema, R
   Tillie, N
   Hollanders, M
AF Roggema, Rob
   Tillie, Nico
   Hollanders, Matthijs
TI Designing the Adaptive Landscape: Leapfrogging Stacked Vulnerabilities
SO LAND
LA English
DT Article
DE climate adaptation; long-term planning; holistic future; Groningen;
   food; ecology; sea level rise
ID CLIMATE-CHANGE; LED APPROACH; SCIENCE; CITIES
AB 6 In the Anthropocene, climate impacts are expected to fundamentally change the way we live in, and plan and design for, our cities and landscapes. Long-term change and uncertainty require a long view, while current planning approaches and policy making are mostly short-term oriented and are therefore not well suited to respond adequately. The path-dependency it implies causes an irresolvable dilemma between short-term effect and long-term necessities. The objective of the research is to investigate an alternative planning and design approach which is able to overcome the current constraints and take a holistic long-term perspective. Therefore, the methods used in the study underpin a creative process of future visioning through backcasting and finding a dynamic equilibrium in the past as a primer for long-term climate adaptation. This way, the individual vulnerabilities of current sectoral policies can be leapfrogged and integrated into one intervention. This design-led method is applied to the northern landscape of the Groningen region in The Netherlands. This intervention is positioned as a re-dynamization of the landscape by re-establishing the exchange between the land and the sea. The findings in the study show that a long-term perspective on the future of the regional landscape increases climate adaptation and enriches the opportunities for viable agriculture, increased biodiversity, and a raised land that is not only protected against possible storm surges, but benefits from the sediments the sea brings. The economic analysis shows that a new perspective for farming within saline conditions is profitable on a fraction of the land, the biodiversity can be enriched by more than 75%, and the ground level of the landscape can be raised by one meter or more in the next 50-100 years. Moreover, the study shows how a long-term perspective can be implemented in logic stages that comply with the natural step-changes occurring in climate change.
C1 [Roggema, Rob] Cittaideale, Off Adapt Design & Planning, NL-6706 LC Wageningen, Netherlands.
   [Roggema, Rob] Univ Western Sydney, Inst Culture & Soc, Parramatta, NSW 2124, Australia.
   [Tillie, Nico] Delft Univ Technol, Urban Ecol & Ecoc Lab, Fac Architecture, NL-2628 BL Delft, Netherlands.
   [Hollanders, Matthijs] Delft Univ Technol, Fac Architecture, NL-2628 BL Delft, Netherlands.
C3 Western Sydney University; Delft University of Technology; Delft
   University of Technology
RP Roggema, R (corresponding author), Cittaideale, Off Adapt Design & Planning, NL-6706 LC Wageningen, Netherlands.; Roggema, R (corresponding author), Univ Western Sydney, Inst Culture & Soc, Parramatta, NSW 2124, Australia.
EM rob@cittaideale.eu; n.m.j.d.tillie@tudelft.nl;
   matthijshollanders@urbanisten.nl
RI Roggema, Robert/AFM-3455-2022
OI Roggema, Rob/0000-0003-2492-0779; Hollanders,
   Matthijs/0000-0001-8422-2820; Tillie, Nico/0000-0003-3195-1290
CR Aan de Burgh M., 2020, ZO LEUK IS NATUUR NI
   Alkemade F., 2020, TOEKOMST NEDERLAND K
   Almond R., 2020, Living Planet Report 2020-Bending the Curve of Biodiversity Loss (No. LPR2020)
   [Anonymous], 2019, GLOB COMM AD AD NOW
   [Anonymous], 2008, BUSINESS PLANNING TU
   Balz V., 2019, THESIS DELFT U TECHN
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   CBS PBL RIVM WUR, 2020, CENTR EC PALN CEP 20
   Cohen-Shacham E., 2016, NATURE BASED SOLUTIO, V97, P2016
   Condon PatrickM., 2008, Design Charrettes for Sustainable Communities
   Cornish E., 2004, Futuring: The exploration of the future
   Cross N, 2007, BOARD INT RES DES, P41, DOI 10.1007/978-3-7643-8472-2_3
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   Davy B, 2008, PLAN THEOR, V7, P301, DOI 10.1177/1473095208096885
   De Jong T.M., 1992, Kleine methodologie voor ontwerpend onderzoek
   De Vries S., INCREASING DROUGHT N
   Delta Programme Commissioner, 2019, DELT PROGR 2020 CONT
   Fry T., 2009, Design futuring, P71
   Gaffikin F, 2006, PLAN THEORY PRACT, V7, P159, DOI 10.1080/14649350600673070
   GELDOF GD, 1995, WATER SCI TECHNOL, V32, P7, DOI 10.2166/wst.1995.0004
   Gladwell M., 2000, TIPPING POINT LITTLE
   Glaze-Corcoran S, 2020, ADV AGRON, V162, P199, DOI 10.1016/bs.agron.2020.02.004
   Haasnoot M., 2018, Mogelijke gevolgen van versnelde zeespiegelstijging voor het Deltaprogramma: Een verkenning (11202230-005-0002.)
   Hauberg J., 2011, AE... Revista Lusofona de Arquitectura e Educacao, V5, P46
   Hocking V.T., 2010, Tackling Wicked Problems Through the Transdisciplinary Imagination, P242
   Holmberg J, 2000, INT J SUST DEV WORLD, V7, P291, DOI 10.1080/13504500009470049
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Jones RN, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD016328
   Jones RN, 2017, EARTH SYST DYNAM, V8, P177, DOI 10.5194/esd-8-177-2017
   Kabat P, 2009, NAT GEOSCI, V2, P450, DOI 10.1038/ngeo572
   Lennertz B., 2006, CHARRETTE HDB ESSENT
   Liang L, 2020, SCI TOTAL ENVIRON, V726, DOI 10.1016/j.scitotenv.2020.138339
   LINDBLOM CE, 1959, PUBLIC ADMIN REV, V19, P79, DOI 10.2307/973677
   Lindsey R.L. Dahlman., 2018, Climate Change: Global Temperature
   Merry U., 1995, COPING UNCERTAINTY I
   Milburn LAS, 2003, LANDSCAPE URBAN PLAN, V64, P47, DOI 10.1016/S0169-2046(02)00200-1
   Ministerie van LNV Europese Landbouw-Beleid, 2019, TOEL BET KAD GEM LAN
   Ministerie van Verkeer en Waterstaat, 2007, ALL 2006 ACHT STORMV
   Molotch H, 2000, AM SOCIOL REV, V65, P791, DOI 10.2307/2657514
   Mupedziswa R, 2017, DEV SO AFR, V34, P196, DOI 10.1080/0376835X.2016.1231057
   Ostrom E, 2004, ECOL ECON, V49, P488, DOI 10.1016/j.ecolecon.2004.01.010
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Quist J., 2007, Backcasting for a sustainable future: the impact after 10 years
   Ramirez Rafael., 2016, Strategic Reframing: The Oxford Scenario Planning Approach
   ROBERTS WO, 1976, P AM PHILOS SOC, V120, P230
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Roggema R, 2009, ADAPTATION TO CLIMATE CHANGE: A SPATIAL CHALLENGE, P1, DOI 10.1007/978-1-4020-9359-3
   Roggema R, 2010, WIT TRANS ECOL ENVIR, V127, P161, DOI 10.2495/RAV090141
   Roggema R., 2020, TOUKOMST IS LANG BEG
   Roggema R., 2021, URBAN REG PLAN, V6, P1, DOI [10.11648/j.urp.20210601.11, DOI 10.11648/J.URP.20210601.11]
   Roggema R., 2011, P ANZRSAI C CANB AUS
   Roggema R., 2021, MOEDER ZERNIKE EMBRA
   Roggema R, 2017, URBAN SCI, V1, DOI 10.3390/urbansci1010002
   Roggema Rob., 2013, DESIGN CHARRETTE WAY
   Rosegrant MW, 2003, SCIENCE, V302, P1917, DOI 10.1126/science.1092958
   Rosemann J, 2001, RESEARCH BY DESIGN PROCEEDINGS A, P63
   Rougoor C., 2016, CLM904
   Sala Enric., 2020, The Nature of Nature: Why We Need the Wild
   Santema P. A., 2020, LEEUWARDER COURANT
   Schipper E.L.F., 2009, Adaptation to Climate Change
   SCHOEMAKER PJH, 1995, SLOAN MANAGE REV, V36, P25
   Schubert D, 2019, PLAN PERSPECT, V34, P3, DOI 10.1080/02665433.2018.1541758
   Schwarz P., 1991, The art of the long view in Planning for the Future in an uncertain world
   Shipley R, 1999, ENVIRON PLANN B, V26, P573, DOI 10.1068/b260573
   Swann C, 2002, DES ISSUES, V18, P49, DOI 10.1162/07479360252756287
   Teunissen W.L., 2005, SOVON INFORMATIE 200
   Timmermans W., 2012, SWARMING LANDSCAPES, P43
   Tree I., 2018, Wilding: The return of nature to a British farm
   UNEP, 2020, DEC REST
   Van der Heijden K., 1997, SCENARIOS ART STRATE
   Van der Woud A., 2020, LANDSCHAP MENSEN NED, P445
   van Eekelen E., 2020, BUILDING NATURE CREA
   van Oort PAJ, 2020, EUR J AGRON, V112, DOI 10.1016/j.eja.2019.125936
   Velstra J., 2012, VERZILTING LANDBOUWG
   *WHO, 2006, FOOD SAF RISK AN GUI
   Wiersma J., 2018, GESCHIEDENIS TERPEN, V100, P11
   Willett W, 2019, LANCET, V393, P447, DOI 10.1016/S0140-6736(18)31788-4
   Wilson A., 2012, Catastrophe Theory and Bifurcation (Routledge Revivals): Appli- cations to Urban and Regional Systems
   Wrigley C, 2017, INT J DES CREAT INNO, V5, P235, DOI 10.1080/21650349.2017.1292152
   Yan WL, 2019, URBAN PLAN, V4, P123, DOI 10.17645/up.v4i1.1739
NR 80
TC 7
Z9 7
U1 0
U2 5
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD FEB
PY 2021
VL 10
IS 2
AR 158
DI 10.3390/land10020158
PG 25
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA QN9FF
UT WOS:000622755000001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Shin, S
   Ichihara, M
   Sokourenko, K
   Liao, C
AF Shin, Seongmin
   Ichihara, Mai
   Sokourenko, Kristina
   Liao, Chuan
TI Everyday climate adaptation practices in agriculture contribute to food
   security in Sub-Saharan Africa
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE climate change; dietary diversity; everyday adaptation; food security;
   home gardening; Sub-Saharan Africa; tree management
ID NUTRITION SECURITY; ASSOCIATION; LIVELIHOODS; INDICATORS; HOUSEHOLDS;
   DIVERSITY; DRIVERS; DIETS
AB Sub-Saharan Africa (SSA) faces considerable threats to its food security because of the adverse effects of climate change. Agriculture, which both influences and is influenced by climate change, requires a thorough understanding of how it impacts and is impacted by these changes. Such understanding is essential for guiding everyday adaptation strategies that uphold sustainable practices and food security. This study explores the impact of various climate adaptation strategies, demographic, and economic factors on dietary diversity across SSA by using Household Dietary Diversity Score (HDDS) as an objective and standardized measure. The research integrates everyday adaptation practices such as tree management, home gardening, crop diversity, intercropping, and composting, alongside demographic factors to assess their influence on food security. The findings reveal tree management and home gardening consistently show a positive influence on HDDS, regardless of seasonal variability. Crop diversity and intercropping also positively impact HDDS, although their effectiveness varies across seasons. Meanwhile, irrigation emerges as a critical factor in maintaining dietary diversity during challenging seasons. Female control within households emerges as a significant demographic factor positively associated with HDDS. Moreover, dietary diversity is generally lower in West Africa, particularly during adverse seasons, because of less stable and extreme agricultural conditions. Despite these adaptation practices, the study identifies a significant policy gap, as existing agricultural policies in the region do not fully support the integration of these everyday practices or address gender- specific needs. Therefore, there is a critical need for sustainable, gender-responsive, and region-specific agricultural policies that effectively incorporate these everyday climate adaptation practices to enhance resilience and food security in SSA.
C1 [Shin, Seongmin; Ichihara, Mai; Sokourenko, Kristina; Liao, Chuan] Cornell Univ, Dept Global Dev, Ithaca, NY 14850 USA.
C3 Cornell University
RP Shin, S (corresponding author), Cornell Univ, Dept Global Dev, Ithaca, NY 14850 USA.
FU Cornell University Library
FX We thank John Sipple and Kristie LeBeau for their guidance and support
   throughout the research process. We acknowledge funding from Cornell
   University Library for covering the publication cost.
CR Abafita J., 2014, Journal of Rural Development (Seoul), V37, P129
   African Union Commission, 2021, Africa regional overview of food security and nutrition 2020: transforming food systems for affordable healthy diets
   Angelsen A, 2014, WORLD DEV, V64, pS12, DOI 10.1016/j.worlddev.2014.03.006
   [Anonymous], 2022, World Population Prospects 2022, DOI DOI 10.18356/9789210014380
   [Anonymous], 2000, GLOBAL ECOLOGICAL ZO
   [Anonymous], 2012, Women's Empowerment in Agriculture Index
   Assefa E, 2023, GLOBAL ENVIRON CHANG, V82, DOI 10.1016/j.gloenvcha.2023.102737
   Avuwadah B. Y., 2021, Dissertation
   Azzarri C, 2016, NAT CLIM CHANGE, V6, P115, DOI 10.1038/nclimate2842
   Benson T, 2015, AGREKON, V54, P62, DOI 10.1080/03031853.2015.1084940
   Blakstad MM, 2019, PUBLIC HEALTH NUTR, V22, P1646, DOI 10.1017/S1368980018003798
   Blomme G, 2018, ACTA HORTIC, V1196, P41, DOI 10.17660/ActaHortic.2018.1196.5
   Brugger J, 2013, GLOBAL ENVIRON CHANG, V23, P1830, DOI 10.1016/j.gloenvcha.2013.07.012
   Campbell B. M., 2011, Addressing agriculture in climate change negotiations: a scoping report
   Carletto C., 2016, Statistical tragedy in Africa?, P37
   Cuni-Sanchez A, 2023, ECOL SOC, V27, DOI 10.5751/ES-13622-270432
   Davis KF, 2014, EARTHS FUTURE, V2, P559, DOI 10.1002/2014EF000254
   de Certeau Michel., 1980, The Practice of Everyday Life
   Eggleston H.S., 2006, 2006 IPCC GUIDELINES
   Ferrat M., 2019, Climate change and land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fikire Abebaw Hailu, 2022, ScientificWorldJournal, V2022, P9561063, DOI 10.1155/2022/9561063
   Food and Agriculture Organization (FAO), 2023, Africa-regional overview of food security and nutrition 2023: Statistics and trends
   Food and Agriculture Organization-Euro-Mediterranean Center on Climate Change (FAO-CMCC), 2016, CLIMAFRICA-Climate change predictions in Sub-Saharan Africa: impacts and adaptations
   Franzel S, 2014, CURR OPIN ENV SUST, V6, P98, DOI 10.1016/j.cosust.2013.11.008
   Frelat R, 2016, P NATL ACAD SCI USA, V113, P458, DOI 10.1073/pnas.1518384112
   Griscom BW, 2017, P NATL ACAD SCI USA, V114, P11645, DOI 10.1073/pnas.1710465114
   Hameed A, 2023, APPL SOIL ECOL, V184, DOI 10.1016/j.apsoil.2022.104772
   Islam AMS, 2018, FOOD SECUR, V10, P701, DOI 10.1007/s12571-018-0806-3
   Jima Y, 2022, COGENT ECON FINANC, V10, DOI 10.1080/23322039.2022.2132632
   Johnson K.B., 2015, SURVEY PRACTICE, V8, P1, DOI DOI 10.29115/SP-2015-0016
   Kerr RB, 2019, AGR ECOSYST ENVIRON, V279, P109, DOI 10.1016/j.agee.2019.04.004
   Khoza S, 2022, ECOL SOC, V27, DOI 10.5751/ES-13480-270419
   Kihara J, 2022, AGR SYST, V203, DOI 10.1016/j.agsy.2022.103496
   Koffi CK, 2020, INT FOREST REV, V22, P64, DOI 10.1505/146554820828671490
   Kotu BH, 2022, WORLD DEV, V152, DOI 10.1016/j.worlddev.2021.105789
   Leal W, 2021, SCI TOTAL ENVIRON, V779, DOI 10.1016/j.scitotenv.2021.146414
   Leroux L, 2022, AGR SYST, V196, DOI 10.1016/j.agsy.2021.103312
   Marambe B., 2012, Adaptation to climate change in agro-ecosystems: a case study from homegardens in South Asia
   Maxwell D, 2014, FOOD POLICY, V47, P107, DOI 10.1016/j.foodpol.2014.04.003
   Megbowon ET, 2018, INT J SOC ECON, V45, P2, DOI 10.1108/IJSE-07-2016-0187
   Ngema PZ, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10093307
   Nielsen JN, 2018, MATERN CHILD NUTR, V14, DOI 10.1111/mcn.12573
   Nixon R, 2023, ECOL SOC, V28, DOI 10.5751/ES-14026-280231
   Oladele OI, 2019, INFORM DEV, V35, P639, DOI 10.1177/0266666918779639
   Powell B., 2013, INT C NUTR FAO WHO G
   Prihadyanti D, 2023, BUS STRATEGY DEV, V6, P140, DOI 10.1002/bsd2.229
   Rammohan A, 2019, BMC PUBLIC HEALTH, V19, DOI 10.1186/s12889-019-7440-7
   Rowhani P, 2011, AGR FOREST METEOROL, V151, P449, DOI 10.1016/j.agrformet.2010.12.002
   Ruel Marie T., 2003, Food and Nutrition Bulletin, V24, P231
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   Scott J. C., 1985, Weapons of the Weak: Everyday Forms of Peasant Resistance, DOI DOI 10.12987/9780300153620
   Sibhatu KT, 2018, FOOD POLICY, V77, P1, DOI 10.1016/j.foodpol.2018.04.013
   Smyth I., 2015, Gender Development, V23, P405, DOI DOI 10.1080/13552074.2015.1113769
   StataCorp LLC, 2019, STATA STAT SOFTWARE
   Sultan B, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01262
   Swindale A., 2006, Household dietary diversity score (HDDS) for measurement of household food access: Indicator guide (version 2), DOI DOI 10.1017/CBO9781107415324.004
   Tranchant J.-P., 2021, Impact of conflict- related violence and presence of armed groups on food security: evidence from longitudinal analysis in Mali, DOI [10.2499/p15738coll2.134960, DOI 10.2499/P15738COLL2.134960]
   United Nations Department of Economic and Social Affairs (UN DESA), 2019, Green legacy initiative
   Vaitla B, 2017, FOOD POLICY, V68, P193, DOI 10.1016/j.foodpol.2017.02.006
   van Wijk M, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0388-8
   Wan M, 2011, INT FOREST REV, V13, P369, DOI 10.1505/146554811798293854
   Wang X, 2022, ECOL SOC, V27, DOI 10.5751/ES-13503-270339
   World Health Organization, 2021, The state of food security and nutrition in the world 2021: transforming food systems for food security, improved nutrition and affordable healthy diets for all
   Xie H, 2014, AGR WATER MANAGE, V131, P183, DOI 10.1016/j.agwat.2013.08.011
NR 65
TC 0
Z9 0
U1 0
U2 0
PU Resilience Alliance
PI Dedham
PA 231 Bussey St., Beckwith and Brown, Dedham, Massachusetts, UNITED STATES
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PD NOV
PY 2024
VL 29
IS 4
AR 32
DI 10.5751/ES-15686-290432
PG 20
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA O9Q4X
UT WOS:001374384300005
OA gold
DA 2025-01-10
ER

PT J
AU Becher, O
   Verschuur, J
   Pant, R
   Hall, J
AF Becher, Olivia
   Verschuur, Jasper
   Pant, Raghav
   Hall, Jim
TI Prioritising climate adaptation options to minimise financial and
   distributional impacts of water supply disruptions
SO ENVIRONMENTAL RESEARCH: INFRASTRUCTURE AND SUSTAINABILITY
LA English
DT Article
DE water supply; infrastructure; climate adaptation
ID ROBUST DECISION-MAKING; ECONOMIC-IMPACTS; JAMAICA; RISK; RESOURCES;
   VULNERABILITY; UNCERTAINTY; COUNTRIES; MODEL
AB Climate-related disruptions to water supply infrastructure services incur direct financial losses to utilities (e.g. to repair damaged assets) and externalise a societal cost to domestic customers due to additional costs that they may incur (e.g. to acquire water from alternative sources). The latter often represents an uncompensated social burden, which should be properly accounted for in investment planning. Here we present a new framework for quantifying direct financial risks burdened by utilities and alternative water purchase losses incurred by domestic customers, including those in low-income groups, during flood- and drought-induced utility water supply disruptions. This framework enables the comparison of benefit-cost ratios of a portfolio of flood protection and leakage reduction for water supply systems across the island of Jamaica. A system-level optioneering analysis allows the identification of the optimal adaptation option per system. We estimate that 34% of systems would benefit from flood defences and 53% would benefit from leakage reduction to adaptation to droughts. The benefit that could be achieved by implementing all system optimised adaptation options is estimated to be 720 million Jamaican dollars per year on average, representing a substantial saving for the utility and its customers, including low-income customers. We identify options that offer strong synergies between economic and equity objectives for both types of adaptation option. The proposed framework is established to support the business case for climate adaptation in the water supply sector and to prioritise across flood and drought mitigation options. We take a first step towards mainstreaming equity considerations in water supply sector optioneering frameworks by estimating the contribution of adaptation options towards reducing household costs for low-income customers.
C1 [Becher, Olivia; Verschuur, Jasper; Pant, Raghav; Hall, Jim] Univ Oxford, Environm Change Inst, Oxford, England.
C3 University of Oxford
RP Becher, O (corresponding author), Univ Oxford, Environm Change Inst, Oxford, England.
EM olivia.becher@ouce.ox.ac.uk
RI Hall, Jim/ABF-1407-2020
OI Becher, Olivia/0000-0002-7727-2368
FU Engineering and Physical Sciences Research
   Councilhttp://dx.doi.org/10.13039/501100000266 [EP/T517811/1];
   Engineering and Physical Sciences Research Council (EPSRC)
FX The authors declare no conflict of interest. O B acknowledges funding
   from the Engineering and Physical Sciences Research Council (EPSRC)
   under Grant Number EP/T517811/1.
CR Aerts JCJH, 2018, WATER-SUI, V10, DOI 10.3390/w10111646
   Ahopelto S, 2020, WATER-SUI, V12, DOI 10.3390/w12010195
   ALTAF MA, 1994, THIRD WORLD PLAN REV, V16, P41, DOI 10.3828/twpr.16.1.m1wk8611v47009u3
   Andres L. A., 2021, Troubled tariffs: Revisiting water pricing for affordable and sustainable water services
   [Anonymous], 2018, JAMAICA OBSERVER
   [Anonymous], 2014, GLOBAL TUBERCULOSIS
   Baisa B, 2010, J DEV ECON, V92, P1, DOI 10.1016/j.jdeveco.2008.09.010
   Bakker Karen J., 2010, PRIVATIZING WATER GO, DOI [10.7591/9780801463617, DOI 10.7591/9780801463617]
   Bangladesh Bureau of Statistics, 2020, Bangladesh population and housing census 2011
   Beard VA, 2021, WORLD DEV, V147, DOI 10.1016/j.worlddev.2021.105625
   Becher O, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF002946
   Bharti N, 2020, WATER POLICY, V22, P65, DOI 10.2166/wp.2019.203
   Borgomeo E, 2018, INT J WATER RESOUR D, V34, P900, DOI 10.1080/07900627.2017.1331842
   Borgomeo E, 2018, EARTHS FUTURE, V6, P468, DOI 10.1002/2017EF000730
   Borgomeo E, 2015, WATER RESOUR RES, V51, P8927, DOI 10.1002/2015WR017324
   Brown C, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011212
   Burdescu R., 2020, A Benchmark for the Performance of State-Owned Water Utilities in the Caribbean, A Benchmark for the Performance of State-Owned Water Utilities in the Caribbean, DOI [10.1596/33251, DOI 10.1596/33251]
   Burgess CP, 2015, NAT HAZARDS, V78, P231, DOI 10.1007/s11069-015-1712-z
   Dong X, 2020, RESOUR CONSERV RECY, V161, DOI 10.1016/j.resconrec.2020.104918
   FAO, 2019, National Water Sector Policy and Implementation Plan 2019
   Federal Emergency Management Agency (FEMA), 2020, MULT LOSS EST METH H
   Freire-González J, 2017, ECOL ECON, V132, P196, DOI 10.1016/j.ecolecon.2016.11.005
   Garrick D., 2019, Informal Water Markets in an Urbanising World: Some Unanswered Questions (English) [Text/HTML]
   Glas H, 2015, INT MULTI SCI GEOCO, P643
   Gober P, 2014, HANDB ENVIRON ENG, V15, P411, DOI 10.1007/978-1-62703-595-8_8
   Goyal MK, 2015, J IRRIG DRAIN ENG, V141, DOI 10.1061/(ASCE)IR.1943-4774.0000802
   Grasham CF, 2022, ENVIRON RES-INFRASTR, V2, DOI 10.1088/2634-4505/ac9c8d
   Grasham CF, 2022, FRONT WATER, V3, DOI 10.3389/frwa.2021.799515
   Griffin RC, 2000, AM J AGR ECON, V82, P414, DOI 10.1111/0002-9092.00035
   Guo DL, 2018, J HYDROL, V556, P877, DOI 10.1016/j.jhydrol.2016.03.025
   GWI, 2022, GWI WaterData
   Hall JW, 2012, WATER ENVIRON J, V26, P118, DOI 10.1111/j.1747-6593.2011.00271.x
   Hall J, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2012.0407
   Hallegatte S., 2016, SHOCK WAVES MANAGING, DOI [DOI 10.1596/978-1-4648-0673-5, 10.1596/978-1-4648-0673-5_fm]
   Hallegatte S, 2017, NAT CLIM CHANGE, V7, P250, DOI 10.1038/NCLIMATE3253
   Hallegatte Stephane., 2017, Unbreakable: Building the Resilience of the Poor in the Face of Natural Disasters, DOI DOI 10.1596/978-1-4648-1003-9
   Haughton S., 2015, Jamaica's Water Insecurity
   Heflin C, 2014, EVAL PROGRAM PLANN, V46, P80, DOI 10.1016/j.evalprogplan.2014.05.003
   Herman JD, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000701
   Huskova I, 2016, GLOBAL ENVIRON CHANG, V41, P216, DOI 10.1016/j.gloenvcha.2016.10.007
   Hussien WA, 2016, WATER RESOUR MANAG, V30, P2931, DOI 10.1007/s11269-016-1314-x
   Hutton G., 2016, COSTS M 2030 SUSTAIN, DOI [10.1596/K8543, DOI 10.1596/K8543]
   Jamaica Water Resources Authority, 2020, Water Information System
   Jenkins K, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR027715
   Jensen O, 2016, POLICY SOC, V35, P115, DOI 10.1016/j.polsoc.2016.07.002
   JIS, 2008, Access to Clean Water Essential to Poverty Alleviation
   Jongman B, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04396-1
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Koks E, 2019, INT J DISAST RISK SC, V10, P421, DOI 10.1007/s13753-019-00236-y
   Lambert A., 2001, IWA C SYSTEM APPROAC
   Larson KL, 2015, SUSTAINABILITY-BASEL, V7, P14761, DOI 10.3390/su71114761
   Laucelli D, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000478
   Lester S., 2015, Caribbean Geography, V20, P74
   Libey A, 2020, WORLD DEV, V136, DOI 10.1016/j.worlddev.2020.105155
   Luo TY, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-023-00782-w
   MacDonald M., 2022, Safeguarding England's water future
   Mandal A., 2011, Advances in Geosciences: Volume 23: Hydrological Science (HS), DOI [10.1142/9789814355339_0023, DOI 10.1142/9789814355339_0023]
   Mandal A, 2016, NAT HAZARDS, V83, P1635, DOI 10.1007/s11069-016-2380-3
   Mandal A, 2013, B SOC GEOL FR, V184, P165, DOI 10.2113/gssgfbull.184.1-2.165
   Matrosov ES, 2013, J HYDROL, V494, P43, DOI 10.1016/j.jhydrol.2013.03.006
   Matrosov ES, 2013, WATER RESOUR MANAG, V27, P1123, DOI 10.1007/s11269-012-0118-x
   MEGJC, 2019, National Water Sector Policy and Implementation Plan
   Mirza MMQ, 2003, CLIM POLICY, V3, P233, DOI 10.1016/S1469-3062(03)00052-4
   Mitlin D, 2020, J DEV STUD, V56, P259, DOI 10.1080/00220388.2019.1577383
   Miyamoto, 2019, Report: Supporting Material and Reference Information
   Mott MacDonald, 2018, Appendix 4.1.A-Mott MacDonald flood risk assessment-Wessex Water
   Nagpal T., 2018, Mobilizing Additional Funds for Pro-Poor Water Services
   Nandi A, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-5323-0
   National Spatial Management Branch, 2010, Potable water facilities
   National Water Commission, 2011, Draft WS PPLan-October 12 2011
   National Water Commission, 2020, About
   NWC, 2021, Facilities Logged on FDIMS affected by turbidity and drought conditions
   NWC, 2015, Capital Improvement Plan
   NWC, 2019, Audited Financial Statements as of March 31
   OECD, 2022, Financing a Water Secure Future
   Pant R, 2018, J FLOOD RISK MANAG, V11, P22, DOI 10.1111/jfr3.12288
   Planning Institute of Jamaica, 2011, Poverty Prevalence by Community, 2011/2012
   Porter K., 2015, ENCY EARTHQUAKE ENG, P235, DOI DOI 10.1007/978-3-642-35344-4_256
   Robak A, 2018, WATER INT, V43, P436, DOI 10.1080/02508060.2018.1446613
   Roibas D, 2019, ENVIRON RESOUR ECON, V73, P159, DOI 10.1007/s10640-018-0255-7
   Roman O, 2021, WATER RESOUR RES, V57, DOI 10.1029/2021WR029621
   Rouse M., 2013, Water Intell, V2nd, DOI [10.2166/9781780404516, DOI 10.2166/9781780404516]
   Rozenberg J., 2019, Beyond the Gap: How Countries Can Afford the Infrastructure They Need while Protecting the Planet
   Selelo LR, 2017, SOUTH AFR BUS REV, V21, P480
   Setegn SG, 2014, CATENA, V120, P81, DOI 10.1016/j.catena.2014.04.005
   Sjöstrand K, 2021, WATER-SUI, V13, DOI 10.3390/w13111565
   Sohail M, 2006, P I CIVIL ENG-CIV EN, V159, P16, DOI 10.1680/cien.2006.159.5.16
   Srinivasan V, 2013, GLOBAL ENVIRON CHANG, V23, P229, DOI 10.1016/j.gloenvcha.2012.10.002
   Statistical Institute of Jamaica, 2010, Census of Population and Housing-Jamaica
   Turkelboom F, 2021, AMBIO, V50, P1431, DOI 10.1007/s13280-021-01548-4
   United Nations, 2022, Sustainable development goals
   Velleman Y., 2009, WaterAid publication
   Verschuur J., 2023, The Impacts of Climatic Extremes on Multidimensional Poverty and the Wider Benefits of Climate Adaptation
   Verschuur J, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-022-00656-7
   Winpenny J., 2015, Water: Fit to Finance? Catalyzing National Growth through Investment in Water Security, Report of the High Level Panel on Financing Infrastructure for a Water-Secure World
   World Bank, 2012, Living Standards Measurement Study (LSMS)
   Wutich A, 2016, WORLD DEV, V79, P14, DOI 10.1016/j.worlddev.2015.10.043
   Yoon J, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2020431118
   Zorn C, 2020, ASCE-ASME J RISK U B, V6, DOI 10.1115/1.4046327
   Zozmann H, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su141711029
NR 100
TC 1
Z9 1
U1 3
U2 9
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
EI 2634-4505
J9 ENVIRON RES-INFRASTR
JI Environ. Res.-Infrastruct. Sustain.
PD MAR 1
PY 2024
VL 4
IS 1
AR 015007
DI 10.1088/2634-4505/ad0ff0
PG 18
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA HZ3D7
UT WOS:001163286400001
OA gold
DA 2025-01-10
ER

PT J
AU Roggema, R
   Vermeend, T
   van den Dobbelsteen, A
AF Roggema, Rob
   Vermeend, Tim
   van den Dobbelsteen, Andy
TI Incremental Change, Transition or Transformation? Optimising Change
   Pathways for Climate Adaptation in Spatial Planning
SO SUSTAINABILITY
LA English
DT Article
DE spatial planning; climate adaptation; transition; transformation;
   resilience; complex adaptive systems
ID ADAPTIVE GOVERNANCE; RESILIENCE
AB In order to incorporate climate adaptation in spatial planning change is required, because climate change impacts the way we live. This implies that spatial planning, as the arranger of the spatial organisation and layout needs to be able to support this change. Current spatial planning is not yet well equipped to play this role. In this research article three possible routes to navigate change are explored. Incremental change is seen as a slow process, which modifies the landscape only slightly. Transition is seen as a fluent change towards a new future, which is an improved version of the existing; and transformation is seen as a change towards a future that is fundamentally different from the existing. The three pathways are compared and it is concluded that transformational change offers the best perspective in dealing with uncertain, unexpected and unprecedented futures, such as developing in times of climate change. Therefore, transformation is theoretically further elaborated and it is found that a transformational change to a new system already starts at a time when the existing system still fully operates. The change to a new system (called B in this article) therefore already started and the predecessors of B already existed. These 'B-minuses' of the new system can be found through network analysis, where the most intense and connective nodes are the most likely 'B-minuses'. Alternatively B-minuses can be created through locating the areas where key-nodes and existing infrastructure can be related to existing urban functions. As illustrated in the case-study design, these principles are able to guide the design of a climate proof landscape.
C1 [Roggema, Rob] Swinburne Univ Technol, Inst Social Res, Hawthorn, Vic 3122, Australia.
   [Roggema, Rob; van den Dobbelsteen, Andy] Delft Univ Technol, Fac Architecture, NL-2600 GA Delft, Netherlands.
   [Roggema, Rob] Univ Wageningen & Res Ctr, NL-6700 AA Wageningen, Netherlands.
   [Vermeend, Tim] UC Architects, NL-9712 NX Groningen, Netherlands.
C3 Swinburne University of Technology; Delft University of Technology;
   Wageningen University & Research
RP Roggema, R (corresponding author), Swinburne Univ Technol, Inst Social Res, POB 218, Hawthorn, Vic 3122, Australia.
EM rob@cittaideale.eu; timvermeend@ucarchitects.com;
   a.a.j.f.vandendobbelsteen@tudelft.nl
RI Roggema, Robert/AFM-3455-2022
OI Roggema, Rob/0000-0003-2492-0779
FU Dutch 'Climate Changes Spatial Planning' programme
FX This research was made possible by the contribution of the Dutch
   Ministry of Housing, Spatial Affairs and the Environment and by support
   of the Dutch 'Climate Changes Spatial Planning' programme.
CR [Anonymous], THESIS VAN HALL LARE
   [Anonymous], GROW DIE UNIFYING PR
   [Anonymous], SPATIAL IMPACT ADAPT
   [Anonymous], WICKED PROBLEMS SOCI
   [Anonymous], DUURZAME ENERGIESTRU
   [Anonymous], 2008, BUSINESS PLANNING TU
   [Anonymous], NCCARF SEM MELB AUST
   [Anonymous], CORNELL LAW REV
   [Anonymous], WOLK 777 CRISIS KRIM
   [Anonymous], 2007, Tackling Wicked Problems. A Public Policy Perspective
   [Anonymous], PROV OMG POP 2 TEKST
   [Anonymous], CRISIS VERNIEUWING U
   [Anonymous], 1999, MENTALE WERELD MERKE
   [Anonymous], P 7 M AES THEM GROUP
   [Anonymous], HYP VOORB KLIM ALS S
   [Anonymous], PROV OMG
   [Anonymous], NIETS NIEUWS ONDER Z
   [Anonymous], ORGANISATIEDYNAMICA
   [Anonymous], 2002, Advances Complex Systems, DOI DOI 10.1142/S021952590200047X
   [Anonymous], THESIS U AMSTERDAM A
   [Anonymous], PROV OMG 2009 2013
   [Anonymous], COST BENEFIT DEV COM
   Berkman PA, 2009, SCIENCE, V324, P339, DOI 10.1126/science.1173200
   Bianconi G, 2001, EUROPHYS LETT, V54, P436, DOI 10.1209/epl/i2001-00260-6
   Broder A, 2000, COMPUT NETW, V33, P309, DOI 10.1016/S1389-1286(00)00083-9
   Castells M., 2010, The Rise of the Network Society, DOI [10.1002/9781444319514, DOI 10.1002/9781444319514]
   Chapin FS, 2010, CAN J FOREST RES, V40, P1360, DOI 10.1139/X10-074
   Chapin FS, 2010, TRENDS ECOL EVOL, V25, P241, DOI 10.1016/j.tree.2009.10.008
   Dietz T, 2003, SCIENCE, V302, P1907, DOI 10.1126/science.1091015
   EMERY FE, 1965, HUM RELAT, V18, P21, DOI 10.1177/001872676501800103
   ERDOS P, 1960, B INT STATIST INST, V38, P343
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Folke C, 2010, ECOL SOC, V15, DOI 10.5751/es-03610-150420
   Geels F W., 2006, Flexibility and Stability in the Innovating Economy, P227, DOI DOI 10.1093/0199290474.003.0009
   Geels FW, 2011, ENVIRON INNOV SOC TR, V1, P24, DOI 10.1016/j.eist.2011.02.002
   Geels FW, 2002, RES POLICY, V31, P1257, DOI 10.1016/S0048-7333(02)00062-8
   Geels FW, 2005, TECHNOL FORECAST SOC, V72, P681, DOI 10.1016/j.techfore.2004.08.014
   Ghodeswar BM, 2008, J PROD BRAND MANAG, V17, P4, DOI 10.1108/10610420810856468
   Gladwell M., 2000, TIPPING POINT LITTLE
   Gunderson L.H., 2001, Panarchy: understanding transformations in human and natural systems
   Kemp R, 2001, LEAS ORG MAN SERIES, P269
   Newman ME., 2006, The Structure and Dynamics of Networks
   Olsson P, 2006, ECOL SOC, V11, DOI 10.5751/ES-01595-110118
   Perez Carlota, 2003, Technological revolutions and financial capital. The dynam- ics of bubbles and golden ages
   RITTEL HWJ, 1973, POLICY SCI, V4, P155, DOI 10.1007/BF01405730
   Roberts K., 2006, The lovemarks effect: Winning in the consumer revolution
   Rotmans, 2000, TRANSITIES TRANSITIE
   Scheffer M, 2009, NATURE, V461, P53, DOI 10.1038/nature08227
   Steffen W., 2004, Global change and the earth system: a planet under pressure, DOI [10.1007/b137870, DOI 10.1007/B137870]
   Steffen W, 2007, AMBIO, V36, P614, DOI 10.1579/0044-7447(2007)36[614:TAAHNO]2.0.CO;2
   Walker B, 2009, SCIENCE, V325, P1345, DOI 10.1126/science.1175325
   Watts DJ, 1998, NATURE, V393, P440, DOI 10.1038/30918
NR 52
TC 49
Z9 50
U1 4
U2 71
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD OCT
PY 2012
VL 4
IS 10
BP 2525
EP 2549
DI 10.3390/su4102525
PG 25
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 213GJ
UT WOS:000324043100010
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Liao, XL
   Su, YJ
   Klintenaes, M
   Li, Y
   Sane, S
   Wu, ZH
   Chen, QH
   Zhang, B
   Nilsson, O
   Ding, JH
AF Liao, Xiaoli
   Su, Yunjie
   Klintenaes, Maria
   Li, Yue
   Sane, Shashank
   Wu, Zhihao
   Chen, Qihui
   Zhang, Bo
   Nilsson, Ove
   Ding, Jihua
TI Age- dependent seasonal growth cessation in<i> Populus</i>
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE tree phenology; age-dependency; bud set; bud break; climate adaptation
ID FLOWERING-LOCUS-T; LEAF PHENOLOGY; AMBIENT-TEMPERATURE; BUD DORMANCY;
   TREES; TRANSCRIPTION; GENES; TIME; NORTHERN; SUGGEST
AB In temperate and boreal regions, perennial plants adapt their annual growth cycle to the change of seasons. In natural forests, juvenile seedlings usually display longer growth seasons compared to adult trees to ensure their establishment and survival under canopy shade. However, how trees adjust their annual growth according to their age is not known. In this study, we show that age- dependent seasonal growth cessation is genetically controlled and found that the miR156- SPL3/5 module, a key regulon of vegetative phase change (VPC), also triggers age- dependent growth cessation in Populus trees. We show that miR156promotes shoot elongation during vegetative growth, and its targets SPL3/5s function in the same pathway but as repressors. We find that the miR156-SPL3/5s regulon controls growth cessation in both leaves and shoot apices and through multiple pathways, but with a different mechanism compared to how the miR156-SPL regulon controls VPC in annual plants. Taken together, our results reveal an age- dependent genetic network in mediating seasonal growth cessation, a key phenological process in the climate adaptation of perennial trees.
C1 [Liao, Xiaoli; Su, Yunjie; Klintenaes, Maria; Li, Yue; Wu, Zhihao; Chen, Qihui; Ding, Jihua] Huazhong Agr Univ, Coll Hort & Forestry, Natl Key Lab Germplasm Innovat & Utilizat Hort Cro, Wuhan 430070, Peoples R China.
   [Liao, Xiaoli; Su, Yunjie; Li, Yue; Wu, Zhihao; Chen, Qihui; Ding, Jihua] Hubei Hongshan Lab, Wuhan 430070, Peoples R China.
   [Liao, Xiaoli; Su, Yunjie; Li, Yue; Wu, Zhihao; Chen, Qihui; Ding, Jihua] Huazhong Agr Univ, Coll Hort & Forestry, Hubei Engn Technol Res Ctr Forestry Informat, Wuhan 430070, Peoples R China.
   [Klintenaes, Maria; Sane, Shashank; Zhang, Bo; Nilsson, Ove] Swedish Univ Agr Sci, Umea Plant Sci Ctr, Dept Forest Genet & Plant Physiol, S-90183 Umea, Sweden.
C3 Huazhong Agricultural University; Huazhong Agricultural University; Umea
   University; Swedish University of Agricultural Sciences
RP Ding, JH (corresponding author), Huazhong Agr Univ, Coll Hort & Forestry, Natl Key Lab Germplasm Innovat & Utilizat Hort Cro, Wuhan 430070, Peoples R China.; Ding, JH (corresponding author), Hubei Hongshan Lab, Wuhan 430070, Peoples R China.; Ding, JH (corresponding author), Huazhong Agr Univ, Coll Hort & Forestry, Hubei Engn Technol Res Ctr Forestry Informat, Wuhan 430070, Peoples R China.; Nilsson, O (corresponding author), Swedish Univ Agr Sci, Umea Plant Sci Ctr, Dept Forest Genet & Plant Physiol, S-90183 Umea, Sweden.
EM Ove.Nilsson@slu.se; jihuading@mail.hzau.edu.cn
RI Liao, Xiaoli/L-1654-2013
OI Nilsson, Ove/0000-0002-1033-1909
FU National Natural Science Foundation of China [32271824, 31971676];
   Fundamental Research Funds for the Central Universities [2662019PY007];
   Swedish Research Council; Knut and Alice Wallenberg Foundation; Swedish
   Governmental Agency for Innovation Systems (VINNOVA); National Key
   Laboratory of Crop Genetic Improvement, Huazhong Agricultural University
FX ACKNOWLEDGMENTS.This work was supported bythe National Natural Science
   Foundation of China (32271824 and 31971676) and the Fundamental Research
   Funds for the Central Universities (2662019PY007) to J.D. and by the
   Swedish Research Council, the Knut and Alice Wallenberg Foundation and
   the Swedish Governmental Agency for Innovation Systems (VINNOVA) to O.N.
   The computa-tions in this paper were run on the bioinformatics computing
   platform of the National Key Laboratory of Crop Genetic Improvement,
   Huazhong Agricultural University.
CR Akhter S, 2022, NEW PHYTOL, V236, P1951, DOI 10.1111/nph.18449
   André D, 2022, CURR BIOL, V32, P2988, DOI 10.1016/j.cub.2022.05.023
   André D, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.823019
   Augspurger CK, 2003, TREE PHYSIOL, V23, P517, DOI 10.1093/treephys/23.8.517
   Aukerman MJ, 2003, PLANT CELL, V15, P2730, DOI 10.1105/tpc.016238
   Azeez A, 2014, CURR BIOL, V24, P717, DOI 10.1016/j.cub.2014.02.037
   Böhlenius H, 2006, SCIENCE, V312, P1040, DOI 10.1126/science.1126038
   Chen XB, 2010, J INTEGR PLANT BIOL, V52, P946, DOI 10.1111/j.1744-7909.2010.00987.x
   Cooke JEK, 2012, PLANT CELL ENVIRON, V35, P1707, DOI 10.1111/j.1365-3040.2012.02552.x
   Falavigna VD, 2021, NEW PHYTOL, V232, P2071, DOI 10.1111/nph.17710
   Ding JH, 2021, NEW PHYTOL, V232, P2339, DOI 10.1111/nph.17350
   Ding JH, 2018, NEW PHYTOL, V218, P1491, DOI 10.1111/nph.15087
   Ding JH, 2016, CURR OPIN PLANT BIOL, V29, P73, DOI 10.1016/j.pbi.2015.11.007
   Eriksson ME, 2015, NEW PHYTOL, V205, P1288, DOI 10.1111/nph.13144
   Eriksson ME, 2000, NAT BIOTECHNOL, V18, P784, DOI 10.1038/77355
   Falavigna VDS, 2019, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01990
   Gao J, 2022, NAT PLANTS, V8, P257, DOI 10.1038/s41477-022-01110-4
   Gill DS, 1998, TREE PHYSIOL, V18, P281
   HOWE GT, 1995, PHYSIOL PLANTARUM, V93, P695, DOI 10.1111/j.1399-3054.1995.tb05119.x
   Hsu CY, 2011, P NATL ACAD SCI USA, V108, P10756, DOI 10.1073/pnas.1104713108
   Hyun Y, 2019, SCIENCE, V363, P409, DOI 10.1126/science.aau8197
   Jiménez S, 2009, BMC PLANT BIOL, V9, DOI 10.1186/1471-2229-9-81
   Karlberg A, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1002361
   Kim JJ, 2012, PLANT PHYSIOL, V159, P461, DOI 10.1104/pp.111.192369
   Kozarewa I, 2010, PLANT MOL BIOL, V73, P143, DOI 10.1007/s11103-010-9619-2
   Kuncha SK, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-017-02204-w
   Lawrence EH, 2021, NEW PHYTOL, V231, P351, DOI 10.1111/nph.17316
   Lee JH, 2007, GENE DEV, V21, P397, DOI 10.1101/gad.1518407
   Mathieu J, 2009, PLOS BIOL, V7, DOI 10.1371/journal.pbio.1000148
   Miskolczi P, 2019, P NATL ACAD SCI USA, V116, P10852, DOI 10.1073/pnas.1902199116
   Pei HC, 2023, SCI CHINA LIFE SCI, V66, P819, DOI 10.1007/s11427-022-2202-3
   Ramos-Sánchez JM, 2019, CURR BIOL, V29, P2402, DOI 10.1016/j.cub.2019.06.003
   Sasaki R, 2011, PLANT PHYSIOL, V157, P485, DOI 10.1104/pp.111.181982
   Seiwa K, 1999, TREE PHYSIOL, V19, P793
   Sheng XY, 2023, TREE PHYSIOL, V43, P1042, DOI 10.1093/treephys/tpad027
   Sheng XY, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.805101
   Singh RK, 2019, CURR BIOL, V29, P128, DOI 10.1016/j.cub.2018.11.006
   Thomas H, 2002, MECH AGEING DEV, V123, P747, DOI 10.1016/S0047-6374(01)00420-1
   Tylewicz S, 2018, SCIENCE, V360, P212, DOI 10.1126/science.aan8576
   Tylewicz S, 2015, P NATL ACAD SCI USA, V112, P3140, DOI 10.1073/pnas.1423440112
   Wang JW, 2008, PLANT CELL, V20, P1231, DOI 10.1105/tpc.108.058180
   Wang JW, 2014, J EXP BOT, V65, P4723, DOI 10.1093/jxb/eru246
   Wang JW, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1002012
   Wang JW, 2009, CELL, V138, P738, DOI 10.1016/j.cell.2009.06.014
   Wang J, 2023, FORESTRY RES, V3, DOI 10.48130/FR-2023-0002
   WEIGEL D, 1995, NATURE, V377, P495, DOI 10.1038/377495a0
   Wu G, 2006, DEVELOPMENT, V133, P3539, DOI 10.1242/dev.02521
   Wu G, 2009, CELL, V138, P750, DOI 10.1016/j.cell.2009.06.031
   Wu RM, 2012, J EXP BOT, V63, P797, DOI 10.1093/jxb/err304
   Xu ML, 2016, PLOS GENET, V12, DOI 10.1371/journal.pgen.1006263
   Yang L, 2013, ELIFE, V2, DOI 10.7554/eLife.00260
   Yang L, 2011, DEVELOPMENT, V138, P245, DOI 10.1242/dev.058578
   Yu H, 2002, P NATL ACAD SCI USA, V99, P16336, DOI 10.1073/pnas.212624599
   Yu S, 2015, CURR OPIN PLANT BIOL, V27, P1, DOI 10.1016/j.pbi.2015.05.009
   Yu S, 2013, ELIFE, V2, DOI 10.7554/eLife.00269
NR 55
TC 2
Z9 4
U1 16
U2 60
PU NATL ACAD SCIENCES
PI WASHINGTON
PA 2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA
SN 0027-8424
EI 1091-6490
J9 P NATL ACAD SCI USA
JI Proc. Natl. Acad. Sci. U. S. A.
PD NOV 28
PY 2023
VL 120
IS 48
AR e2311226120
DI 10.1073/pnas.2311226120
PG 10
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA HC8R2
UT WOS:001157389000008
PM 37991940
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Bussey, M
   Carter, RW
   Keys, N
   Carter, J
   Mangoyana, R
   Matthews, J
   Nash, D
   Oliver, J
   Richards, R
   Roiko, A
   Sano, M
   Thomsen, DC
   Weber, E
   Smith, TF
AF Bussey, Marcus
   Carter, R. W. (Bill)
   Keys, Noni
   Carter, Jennifer
   Mangoyana, Robert
   Matthews, Julie
   Nash, Denzil
   Oliver, Jeannette
   Richards, Russell
   Roiko, Anne
   Sano, Marcello
   Thomsen, Dana C.
   Weber, Estelle
   Smith, Timothy F.
TI Framing adaptive capacity through a history-futures lens: Lessons from
   the South East Queensland Climate Adaptation Research Initiative
SO FUTURES
LA English
DT Article
ID COMPLEXITY; SCIENCE; ANGKOR
AB This paper explores how the history-futures interface can inform a set of concrete adaptation options to climate change for stakeholders in South East Queensland, Australia. It is based on research undertaken as part of the Commonwealth funded South East Queensland Climate Adaptation Research Initiative (SEQ-CARI) that profiled 33 historical case studies to identify common themes in the ways societies responded to stress. The case studies are intended to provide a context for thinking about adaptive capacity with stakeholders in the four areas of human settlement and health; energy: agriculture, forestry and fisheries; and ecosystems and biodiversity. The case studies demonstrate that adaptive capacity varies with context and is affected by the complexity, technology, leadership, institutions and imaginative resources inherent to the social system examined. To increase the possibilities for reflection by stakeholders, the case studies were used to create a set of historical scenarios that explore some of the key features of human responses to challenges such as climate change. This paper draws on this work to suggest a set of 'practical' lessons for those engaged with climate change today and into the future. (C) 2011 Elsevier Ltd. All rights reserved.
C1 [Bussey, Marcus; Carter, R. W. (Bill); Keys, Noni; Carter, Jennifer; Mangoyana, Robert; Matthews, Julie; Nash, Denzil; Oliver, Jeannette; Roiko, Anne; Thomsen, Dana C.; Smith, Timothy F.] Univ Sunshine Coast, Sustainabil Res Ctr, Maroochydore, Qld 4558, Australia.
   [Richards, Russell; Sano, Marcello] Griffith Univ, Griffith Ctr Coastal Management, Nathan, Qld 4222, Australia.
   [Weber, Estelle] Univ Queensland, Brisbane, Qld 4072, Australia.
C3 University of the Sunshine Coast; Griffith University; University of
   Queensland
RP Bussey, M (corresponding author), Univ Sunshine Coast, Sustainabil Res Ctr, ML 28, Maroochydore, Qld 4558, Australia.
EM MBussey@usc.edu.au
RI Roiko, Anne/AAU-3221-2021; Carter, Jennifer/AAT-9587-2021; Bussey,
   Marcus/E-8581-2010; Carter, Rodney/T-8996-2019
OI Carter, Jennifer/0000-0002-9585-0627; Bussey,
   Marcus/0000-0002-9686-1854; Matthews, Julie/0000-0002-7571-5778; Smith,
   Timothy/0000-0002-3991-5211; Carter, Rodney/0000-0003-3545-825X;
   Thomsen, Dana C/0000-0002-5913-3225; Roiko, Anne/0000-0003-0395-307X
CR Adger WN, 2011, WIRES CLIM CHANGE, V2, P757, DOI 10.1002/wcc.133
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Agar J., 2003, Constant touch: A global history of the mobile phone
   [Anonymous], 2008, ECONOMIST, V389, P29
   [Anonymous], 2005, Collapse: How Civilizations Choose to Fail and Succeed
   [Anonymous], 2009, SOCIAL CHANGE 2 0 BL
   [Anonymous], SOCIAL EVOLUTION HIS
   [Anonymous], 2005, ORDER THINGS ARCHAEO
   [Anonymous], MEAS INF SOC ICT DEV
   [Anonymous], 1991, Nous n'avons jamais ete modernes
   Arendt Hannah., 2018, The Human Condition
   Artigiani R, 2005, FUTURES, V37, P585, DOI 10.1016/j.futures.2004.11.002
   Bauman Zygmunt, 2000, Liquid Modernity
   Berkes F., 2003, Navigating social and ecological systems: building resilience for complexity and change, DOI DOI 10.1017/CBO9780511541957
   Berkes F, 2009, FUTURES, V41, P6, DOI 10.1016/j.futures.2008.07.003
   Blühdorn I, 2011, ORGAN ENVIRON, V24, P34, DOI 10.1177/1086026611402008
   Bussey M., 2010, SOC RESPONSES SIGNIF
   Bussey M., 2012, CRISIS IS REAL CRISI
   Bussey M, 2009, FORESIGHT, V11, P29, DOI 10.1108/14636680910950138
   Casciaro T, 2005, ADMIN SCI QUART, V50, P167, DOI 10.2189/asqu.2005.50.2.167
   Castoriadis Cornelius., 1997, WORLD FRAGMENTS WRIT
   Chermack TJ, 2004, FUTURES, V36, P295, DOI 10.1016/S0016-3287(03)00156-3
   Christian D, 2003, J WORLD HIST, V14, P437, DOI 10.1353/jwh.2003.0048
   Christian D., 2018, ORIGIN STORY BIG HIS
   Colantonio A, 2006, CITIES, V23, P63, DOI 10.1016/j.cities.2005.10.001
   Collins K., 2009, Environmental Policy and Governance, V19, P351, DOI 10.1002/eet.520
   Crivits M, 2010, FUTURES, V42, P1187, DOI 10.1016/j.futures.2010.07.002
   Curry A, 2008, J FUTURES STUD, V13, P1, DOI 10.1117/1.2837450
   Dator JamesA., 2002, ADV FUTURES FUTURES
   Deleuze G., 1987, A Thousand Plateaus: Capitalism and Schizophrenia
   Deleuze Gilles., 1993, The Fold: Leibniz and the Baroque
   Derrida J., 2002, WRITING DIFFERENCE
   Dunn A., 2011, Fletcher Forum of World Affairs, V35
   Eisler R., 2007, REAL WEALTH NATIONS
   Evans D, 2007, P NATL ACAD SCI USA, V104, P14277, DOI 10.1073/pnas.0702525104
   Ferguson N, 2010, FOREIGN AFF, V89, P18
   Ferguson Niall., 2008, ASCENT MONEY
   Fernandez-Armesto, 2007, WORLD HIST
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   Frye J., 2006, KB J, V2
   Ghosh Pallab., 2009, BBC News
   Gupta J, 2010, ENVIRON SCI POLICY, V13, P459, DOI 10.1016/j.envsci.2010.05.006
   Harman C., 2008, A people's history of the world: From the Stone Age to the new millennium
   Harris EM, 2006, DEMOCRACY AND THE RULE OF LAW IN CLASSICAL ATHENS: ESSAYS ON LAW, SOCIETY, AND POLITICS, P1, DOI 10.1017/CBO9780511497858
   Heifetz RA., 2009, PRACTICE ADAPTIVE LE
   Heimbuch J., 2009, CELL PHONES ARE CHAN
   Hetherington Kevin., 2006, The Badlands of Modernity: Heterotopia and Social Ordering
   Heugens PPMAR, 2001, FUTURES, V33, P861, DOI 10.1016/S0016-3287(01)00023-4
   Higham C., 2003, CIVILIZATION ANGKOR
   Hinkel J, 2011, GLOBAL ENVIRON CHANG, V21, P198, DOI 10.1016/j.gloenvcha.2010.08.002
   Inayatullah S, 2006, FUTURES, V38, P656, DOI 10.1016/j.futures.2005.10.003
   Inayatullah S., 2007, Questioning the Future: Methods and Tools for Organizational and Societal Transformation
   Inayatullah S, 2009, J FUTURES STUD, V13, P75
   Inayatullah S, 2008, FORESIGHT, V10, P4, DOI 10.1108/14636680810855991
   Jones L, 2011, GLOBAL ENVIRON CHANG, V21, P1262, DOI 10.1016/j.gloenvcha.2011.06.002
   Katz J.E., 2002, PERPETUAL CONTACT MO
   Kegan R., 2009, IMMUNITY CHANGE OVER
   Kurzweil R., 2006, SINGULARITY IS REAL
   Lakoff G., 2005, Don't Think of an Elephant!: Know Your Values and Frame the Debate--The Essential Guide for Progressives, V1st
   Landes D., 2007, GLOBAL POLITICS, P23
   Leveque Pierre., 1996, CLEISTHENES ATHENIAN
   McNeill J.R., 2003, The mountains of the Mediterranean world
   Milojevic Ivana., 2005, Educational Futures: Dominant and Contesting Visions
   Nandy Ashis., 2007, Time Treks: The Uncertain Futures of Old and New Despotisms
   O'Keefe M, 2010, FUTURES, V42, P26, DOI 10.1016/j.futures.2009.08.004
   Page SE, 2006, Q J POLIT SCI, V1, P87, DOI 10.1561/100.00000006
   Parkin S., 2010, POSITIVE DEVIANT SUS
   Penny D, 2006, ANTIQUITY, V80, P599, DOI 10.1017/S0003598X00094060
   Ponting Clive., 2007, A New Green History of the World: The Environment and the Collapse of Great Civilizations
   Ravetz JR, 2011, FUTURES, V43, P142, DOI 10.1016/j.futures.2010.10.002
   Rhodes J.P., 2006, SOLON ATHENS NEW HIS
   Richards R., ENV MODELLI IN PRESS
   Roiko A., 2010, SOCIOECONOMIC TRENDS
   Sale K., 1995, Rebels against the future: The Luddites and their war on the Industrial Revolution/lessons for the computer age
   Sanderson S.K., 2005, World societies: the evolution of human social life
   Sano M., CLIMATIC CH IN PRESS
   Schama Simon., 2002, A History of Britain, VIII
   Shapiro M.J., 1992, READING POSTMODERN P
   Slaughter R.A., 2004, Futures in Education
   Smith T.F., 2010, AUSTRALASIAN J DISAS, V14
   Srivastava L, 2005, BEHAV INFORM TECHNOL, V24, P111, DOI 10.1080/01449290512331321910
   Staley D., 2010, HIST FUTURE USING HI
   Stark MT, 2006, ANNU REV ANTHROPOL, V35, P407, DOI 10.1146/annurev.anthro.35.081705.123157
   Tainter J., 1988, The collapse of complex societies
   Tuchman BW, 1985, MARCH FOLLY TROY VIE
   van Drunen MA, 2011, FUTURES, V43, P488, DOI 10.1016/j.futures.2011.01.001
   Vincent K, 2007, GLOBAL ENVIRON CHANG, V17, P12, DOI 10.1016/j.gloenvcha.2006.11.009
   Walsh SP, 2007, J APPL SOC PSYCHOL, V37, P2405, DOI 10.1111/j.1559-1816.2007.00264.x
   Watson Peter., 2006, IDEAS HIST THOUGHT I
   Wilber K., 2001, A theory of everything: An integral vision for business, politics, science, and spirituality
   Wildman P, 1996, FUTURES, V28, P723, DOI 10.1016/0016-3287(96)00031-6
   Wright Ronald., 2006, A Short History of Progress
   Wynne B, 2010, NATURE, V466, P441, DOI 10.1038/466441a
NR 93
TC 29
Z9 32
U1 3
U2 43
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0016-3287
EI 1873-6378
J9 FUTURES
JI Futures
PD MAY
PY 2012
VL 44
IS 4
BP 385
EP 397
DI 10.1016/j.futures.2011.12.002
PG 13
WC Economics; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Business & Economics; Public Administration
GA 927DT
UT WOS:000302887900010
DA 2025-01-10
ER

PT J
AU Asariotis, R
   Monioudi, IN
   Naray, VM
   Velegrakis, AF
   Vousdoukas, MI
   Mentaschi, L
   Feyen, L
AF Asariotis, Regina
   Monioudi, Isavela N.
   Mohos Naray, Viktoria
   Velegrakis, Adonis F.
   Vousdoukas, Michalis I.
   Mentaschi, Lorenzo
   Feyen, Luc
TI Climate change and seaports: hazards, impacts and policies and
   legislation for adaptation
SO ANTHROPOCENE COASTS
LA English
DT Article
DE Seaports; Climate change; Adaptation; Seaport resilience; Policy; Legal
   framework
ID SEA-LEVEL RISE
AB Seaports are critical for global trade and development but are at risk of climate change-driven damages, operational disruptions and delays with extensive related economic losses. The aim of the present contribution is to (a) provide an overview of the main impacts of climate variability and change (CV&C) on ports; (b) present recent research on trends and projections involving the main climatic factors/hazards affecting global ports; (c) provide an analytical overview of emerging international and regional policies and legislation relevant to port risk assessment and resilience-building under climate change; and (d) consider issues and areas for further action. As shown by projections under different climatic scenarios and timelines, many global ports will increasingly be exposed to significantly growing hazards under increasing CV&C, including extreme sea levels (ESLs), waves, and extreme heat events. Depending on scenario (RCP 4.5 and RCP 8.5) by 2050, 55% to 59% of the 3630 global ports considered could face ESLs in excess of 2 m above the baseline mean sea levels (mean of the 1980-2014 period); by 2100, between 71% and 83% of ports could face ESLs of this magnitude. Ports in most tropical/sub-tropical settings will face the baseline (mean of the 1976 - 2005 period) 1-in-100 year extreme heat every 1 - 5 years, whereas with 3 oC global warming, most global ports (except some in higher latitudes) could experience the baseline 1-in-100 years extreme heat event every 1 - 2 years. A range of policy and legal instruments to support climate change adaptation, resilience-building and disaster risk reduction have been agreed internationally as well as at regional levels. At the EU level, relevant legal obligations and related normative technical guidance aimed at ensuring the climate proofing of new infrastructure are already in place as a matter of supra-national law for 27 EU Member States. These could significantly enhance levels of climate-resilience and preparedness for ports within the EU, as well as for EU funded port projects in other countries, and may serve as useful examples of good practices for other countries. However, further action is needed to advance and accelerate the implementation of effective adaptation measures for ports across regions.
C1 [Asariotis, Regina] UN Trade & Dev UNCTAD, Policy & Legislat Sect, DTL, Geneva, Switzerland.
   [Monioudi, Isavela N.; Velegrakis, Adonis F.; Vousdoukas, Michalis I.] Univ Aegean, Dept Marine Sci, Mitilini, Greece.
   [Mohos Naray, Viktoria] United Nations Dev Programme UNDP, Crisis Bur, Disaster Risk Reduct & Recovery Bldg Resilience, Geneva, Switzerland.
   [Mentaschi, Lorenzo] Univ Bologna, Dept Phys & Astron, Bologna, Italy.
   [Feyen, Luc] European Commiss, Joint Res Ctr JRC, Ispra, Italy.
C3 University of Aegean; University of Bologna; European Commission Joint
   Research Centre; EC JRC ISPRA Site
RP Monioudi, IN (corresponding author), Univ Aegean, Dept Marine Sci, Mitilini, Greece.
EM imonioudi@marine.aegean.gr
RI Vousdoukas, Michalis/C-6743-2012; /ABD-2814-2020
FU Green Fund of the Greek Ministry of Environment and Energy
FX The authors would like to thank the experts participating in a number of
   UNCTAD expert meetings for stimulating discussions on the subject. INM
   and AFV also acknowledge support received as part of the ResPorts
   project (Enhancing Resilience for Greek Ports), funded by the Green Fund
   of the Greek Ministry of Environment and Energy.
CR Alfieri L, 2018, CLIMATE, V6, DOI [10.3390/cli6010006, 10.3390/cli6010016]
   [Anonymous], EU (2021b) Regulation (EU) 2021/836 of the European Parliament and of the Council of 20 May 2021 amending Decision 1313/2013/EU on a Union Civil Protection Mechanism
   [Anonymous], 2023, Climate Action Tracker (Gklim Eylem Takipcisi) Country Targets: Turkiye Main Climate Targets. 15
   [Anonymous], 2022, Review of maritime transport
   [Anonymous], 1992, United Nations Framework Convention on Climate Change
   [Anonymous], 1998, AARHUS CONVENTION AC
   [Anonymous], 2014, Official Journal of the European Union, VL257, P135
   [Anonymous], 2014, CLIMATE CHANGE 2014, P1
   [Anonymous], EU (2021c) European Climate Law. Regulation (EU) 2021/1119 30/6/2021 amending Regulations (EC) No 401/2009 and (EU) 2018/1999. O.J.9.7.2021L243/11,
   [Anonymous], 2017, Post-disaster needs assessment hurricane maria september 18, 2017
   [Anonymous], 2002, Coastal Engineering Manual
   [Anonymous], 2016, GOMSG-H-16-001
   [Anonymous], 2022, DIR EU 2022 2557 EUR, P164
   [Anonymous], 2008, Climate Change Act 2008
   Arias P. A., 2021, Climate Change 2021: The Physical Science Basis. Contributionof Working Group I to the Sixth Assessment Report of the IntergovernmentalPanel on Climate Change, P33, DOI [10.1017/9781009157896.002, DOI 10.1017/9781009157896.002, 10.59327/IPCC/AR6-9789291691647, DOI 10.59327/IPCC/AR6-9789291691647]
   Asariotis R, 2023, Protecting maritime operators in a changing regulatory and technological environment, P285
   Asariotis R, 2018, UNCTAD/SER.RP/2017/18/Rev.1
   Asariotis R., 2020, COASTAL MARINE ENV, P253, DOI DOI 10.1201/9780429441004-29
   Asariotis R, 2021, Climate change impacts on seaports: A growing threat to sustainable trade and development
   Becker A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.508
   Becker AH, 2013, CLIMATIC CHANGE, V120, P683, DOI 10.1007/s10584-013-0843-z
   Becker AH, 2015, PROG PLANN, V99, P1, DOI 10.1016/j.progress.2013.11.002
   Bevacqua E, 2020, COMMUN EARTH ENVIRON, V1, DOI 10.1038/s43247-020-00044-z
   Bove G, 2020, SCI TOTAL ENVIRON, V710, DOI 10.1016/j.scitotenv.2019.136162
   Brooke J., 2024, Supporting the business case to adapt existing ports to the changing climate
   Brooke J, 2024, P I CIVIL ENG-CIV EN, V177, P37, DOI 10.1680/jcien.23.00134
   Camus P, 2019, COAST ENG, V147, P12, DOI 10.1016/j.coastaleng.2019.01.007
   Camus P, 2017, EARTHS FUTURE, V5, P918, DOI 10.1002/2017EF000609
   Cao XH, 2018, RELIAB ENG SYST SAFE, V175, P1, DOI 10.1016/j.ress.2018.02.008
   Cheng LJ, 2019, SCIENCE, V363, P128, DOI 10.1126/science.aav7619
   DAuvergne C., 2022, OECS Climate Change Adaptation Strategy and Action Plan 2021-2026  Considerations for seaport resilience building and DRR; Presentation at UNCTAD Multi Year Expert Meeting on Transport, Trade Logistics and Trade Facilitation
   DeConto RM, 2021, NATURE, V593, P83, DOI 10.1038/s41586-021-03427-0
   Dosio A, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab827
   Dottori F, 2018, NAT CLIM CHANGE, V8, P781, DOI 10.1038/s41558-018-0257-z
   ECCLIPSE, 2021, Developed as part of the ECCLIPSE project
   ECFAS, 2023, ABOUT US
   Economist Impact, 2023, Global Maritime Trends 2050
   EDF, 2022, Act Now or Pay Later: The Costs of Climate Inaction for Ports and Shipping
   ESPO, 2022, Environmental Report 2022. EcoPortsinSights 2022
   ESPO, 2023, Environmental Report 2023. EcoPortsinSights 2023
   EU, 2008, Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive)., P19
   EU, 2021, COM:2021/82
   EU, 2022, European Commission. MSFD CIS Guidance Document No. 19
   EU, 2007, Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE)
   EU, 2021, Commission Notice-Technical guidance on the climate proofing of infrastructure in the period 2021-2027 (OJ C 373, 16.9.2021,, P1
   EU, 2016, onsolidated version of the Treaty on the Functioning of the European Union (OJ C 202, 7.6.2016,, P47
   EU, 2014, Directive 2014/52/EU 16/4/2014 amending Directive 2011/92/EU on the assessment of the effects of certain public and private projects on the environment (OJL124, 25.4.2014, P1
   EU, 2007, Directive 2007/60/EC on the assessment and management of flood risks
   EU, 2003, Directive 2003/4/EC of the European Parliament and of the Council of 28 January 2003 on public access to environmental information and repealing Council Directive 90/313/EEC
   EU, 2013, Regulation (EU) No1315/2013 of the European Parliament and of the Council (11/12/2013) on Union guidelines for the development of the trans-European transport network and repealing Decision No661/2010/EU
   EU, 2001, Directive 2001/42/EC on the assessment of the effects of certain plans and programmes on the environment (OJ L 197, P30
   EU, 2016, Action Plan on SFDRR 2015-2030
   EU (European Union), 2023, Commission Delegated Directive (EU) 2023/2775 of 17 October 2023 amending Directive 2013/34/EU of the European Parliament and of the Council as regards the adjustments of the size criteria for micro, small, medium-sized and large undertakings or groups
   European Union, 2022, The Impact of Artificial Intelligence on the Future of Workforces in the EU and the US
   Flegg E.F., 2018, Coasts, Marine Structures and Breakwaters 2017, P297
   Folkman Dylan, 2021, International Journal of Advanced Operations Management, V13, P409, DOI 10.1504/IJAOM.2021.120779
   Giardino A, 2018, REG ENVIRON CHANGE, V18, P2237, DOI 10.1007/s10113-018-1353-3
   Hallegatte S., 2019, Lifelines: The Resilient Infrastructure Opportunity, DOI [10.1596/978-1-4648-1430-3, DOI 10.1596/978-1-4648-1430-3]
   Hanson S., 2012, Maritime transport and the climate change challenge, P243
   Hanson S, 2011, CLIMATIC CHANGE, V104, P89, DOI 10.1007/s10584-010-9977-4
   Hanson SE, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001543
   Hoshino S, 2016, NAT HAZARDS, V80, P539, DOI 10.1007/s11069-015-1983-4
   IDB, 2020, Assessment of the Effects and Impacts of Hurricane Dorian in the Bahamas, DOI [10.18235/0002582, DOI 10.18235/0002582]
   IPCC, 2023, Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [DOI 10.59327/IPCC/AR6-9789291691647, 10.59327/IPCC/AR6-9789291691647.001]
   IPCC, 2018, GLOB WARM 1 5C SUMM
   ISO, 2019, ISO 14090:2019
   ISO, 2021, ISO Standard No. 14091:2021
   Izaguirre C, 2021, NAT CLIM CHANGE, V11, P14, DOI 10.1038/s41558-020-00937-z
   Izaguirre C, 2020, MARIT POLICY MANAG, V47, P544, DOI 10.1080/03088839.2020.1725673
   Jevrejeva S, 2016, P NATL ACAD SCI USA, V113, P13342, DOI 10.1073/pnas.1605312113
   Kalaidjian E, 2022, FRONT SUSTAIN, V3, DOI 10.3389/frsus.2022.963555
   KAnG, 2023, BundesKlimaanpassungsgesetz. BGBl. 2023 I Nr. 393
   Kirezci E, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67736-6
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Kontopyrakis KE, 2024, ANTHROPOCENE COASTS, V7, DOI 10.1007/s44218-023-00035-5
   Lam JSL, 2017, OCEAN COAST MANAGE, V141, P43, DOI 10.1016/j.ocecoaman.2017.02.015
   Lawrence J-M, 2019, 18 ANN C SYST ENG RE
   Lenton T., 2009, MAJOR TIPPING POINTS
   Lenton T.M., 2023, The global tipping points report 2023
   Lenton TM, 2019, NATURE, V575, P592, DOI 10.1038/d41586-019-03595-0
   León-Mateos F, 2021, MAR POLICY, V130, DOI 10.1016/j.marpol.2021.104573
   Li F, 2018, COAST ENG, V142, P52, DOI 10.1016/j.coastaleng.2018.09.007
   Mclean EL, 2020, SUSTAIN SCI, V15, P835, DOI 10.1007/s11625-019-00741-5
   Mentaschi L, 2017, GEOPHYS RES LETT, V44, P2416, DOI 10.1002/2016GL072488
   Mingle J, 2020, NEW YORK REV BOOKS, V67, P49
   Monioudi IN, 2023, FRONT MAR SCI, V10, DOI 10.3389/fmars.2023.1188896
   Monioudi IN, 2018, REG ENVIRON CHANGE, V18, P2211, DOI 10.1007/s10113-018-1360-4
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Moreno E, 2023, Reuters5 Sept
   Morris LL, 2019, ROU ST HAZ DIS RIS C, P179
   Morris LL, 2020, MARIT POLICY MANAG, V47, P953, DOI 10.1080/03088839.2020.1729435
   Muis S, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11969
   Ng AKY, 2018, COAST MANAGE, V46, P148, DOI 10.1080/08920753.2018.1451731
   Ng AKY, 2016, R STUD TRANSP ANAL, P1
   Notteboom T., 2022, Port Economics
   OECD, 2023, Climate finance provided and mobilised by developed countries in 2013-2021, DOI [10.1787/e20d2bc7-en, DOI 10.1787/E20D2BC7-EN]
   OECS, 2021, OECS Climate change adaptation strategy and action plan (CCASAP) 2021-2026
   Panahi R, 2020, TRANSPORT POLICY, V95, P10, DOI 10.1016/j.tranpol.2020.05.010
   PIANC, 2022, PTGCC Technical Note 1
   PIANC, 2024, PTGCC Technical Note No.2
   PIANC, 2020, EnviCom WG 178
   Port Consultants Rotterdam, 2024, Developing a port masterplan
   Rossouw M, 2012, Maritime Transport and the Climate Change Challenge, P286
   Sánchez-Arcilla A, 2016, REG ENVIRON CHANGE, V16, P2471, DOI 10.1007/s10113-016-0972-9
   Smithers RJ, 2023, Assessing climate change risks and vulnerabilities (climate risk assessment). A DIY Manual. Version 1
   Strauss BH, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22838-1
   Sweeney B, 2020, J WATERW PORT COAST, V146, DOI 10.1061/(ASCE)WW.1943-5460.0000583
   Tolman H.L., 2009, NOAA/NWS/NCEP/MMAB Technical note, 276
   Trenberth KE, 2018, EARTHS FUTURE, V6, P730, DOI 10.1029/2018EF000825
   UN Environment/MAP, 2017, Regional Climate Change Adaptation Framework for the Mediterranean Marine and Coastal Areas
   UNCTAD, 2021, The Bridgetown Covenant. TD/541/Add.2. UNCTAD XV Outcome document
   UNCTAD, 2018, UNDA project 1415O
   UNCTAD, 2020, Transport and Trade Facilitation Series, V12
   UNCTAD, 2020, Note by the UNCTAD Secretariat. TD/B/C.I/MEM.7/23
   UNCTAD, 2022, UNCTAD Policy Brief No. 103
   UNDRR and WMO, 2022, Global Status of Multi-Hazard Early Warning Systems, Target G
   UNECE, 2020, Expert Group Report ECE/TRANS/283
   UNECE, 2014, Climate Change Impacts and Adaptation for International Transport Networks
   UNECE, 2015, ECE/TRANS/251
   UNECLAC, 2018, The Magazine of the Caribbean Development and Cooperation Committee, ISSUE 1 / JANUARY-MARCH 2018
   UNEP United Nations Environment Programme, 2023, Adaptation gap report 2023: Underfinanced. Underprepared. Inadequate investment and planning on climate adaptation leaves world exposed
   UNFCCC, 2023, National Adaptation Plans
   UNFCCC, 2020, Technologies for Averting, Minimizing and Addressing Loss and Damage in Coastal Zones
   UNISDR (United Nations International Strategy for Disaster Reduction), 2015, Sendai Framework for Disaster Risk Reduction 2015-2030
   United Nations, 2015, Paris Agreement
   United Nations, 2020, COMMON GUIDANCE HELP
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   United Nations Environment Programme, 2023, Emissions Gap Report 2023: Broken RecordTemperatures Hit New Highs, Yet World Fails to Cut Emissions (Again)
   United Nations Framework Convention on Climate Change (UNFCCC), 2021, Climate action pathway.
   Velegrakis AF, 2021, Deliverable 2.2-ECFAS Project (GA 101004211), DOI [10.5281/zenodo.6538546, DOI 10.5281/ZENODO.6538546]
   Verschuur J, 2023, NAT CLIM CHANGE, V13, P804, DOI 10.1038/s41558-023-01754-w
   Verschuur J, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-022-00656-7
   Vousdoukas MI, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04692-w
   WMO, 2023, El Nio/La Nia Update June 2023, P5
NR 134
TC 2
Z9 2
U1 4
U2 4
PU SPRINGERNATURE
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND
EI 2561-4150
J9 ANTHROPOCENE COASTS
JI Anthropocene Coasts
PD JUN 18
PY 2024
VL 7
IS 1
AR 14
DI 10.1007/s44218-024-00047-9
PG 21
WC Environmental Sciences; Oceanography
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Oceanography
GA UN5E9
UT WOS:001248744400001
OA gold
DA 2025-01-10
ER

PT J
AU Huet, EK
   Adam, M
   Traore, B
   Giller, KE
   Descheemaeker, K
AF Huet, E. K.
   Adam, M.
   Traore, B.
   Giller, K. E.
   Descheemaeker, K.
TI Coping with cereal production risks due to the vagaries of weather,
   labour shortages and input markets through management in southern Mali
SO EUROPEAN JOURNAL OF AGRONOMY
LA English
DT Article
DE Hazard; Maize; Millet; Sorghum; West -Africa; Crop model
ID CLIMATE-CHANGE ADAPTATION; SUB-SAHARAN AFRICA; FARMING SYSTEMS; CROP
   PRODUCTION; SEMIARID AREAS; FERTILIZER USE; FOOD SECURITY; SORGHUM;
   IMPACT; MAIZE
AB Production of cereals (maize, sorghum, millet) in southern Mali is challenged by several hazards that affect yield and yield variability. The research aims to inform decision making towards effective risk management by quantifying cereal yield losses at field level due to production hazards under different management strategies. Five hazards relevant for farmers were analysed: late onset of rains, insufficient total rainfall, dry spells, low fertiliser quality and sudden lack of labour. The frequency and impact on yield of these hazards were assessed by combining a long term weather database (1965-2019) with outputs of the DSSAT crop model (baseline and optimised variety, fertiliser rates and sowing dates), and visualised in a risk matrix. The prevalence of the weather hazards was common, with all of them occurring at least once every five years. Frequency of non -weather hazards were perceived to occur once every five years (labour hazards) and once every ten years (fertiliser hazards). Under baseline conditions maize (3.39 t / ha) outperformed sorghum (1.74 t / ha) and millet (1.33 t / ha), except in cases of fertiliser hazard when sorghum yielded more than maize. Maize responded relatively well to N application, and sorghum performed relatively well without N application. The benefit of millet resided in low yield variability, and lower sensitivity to the weather hazards. Changing management to optimise yields generally involved early sowing (22 days, 2 days and 27 days after onset for maize, sorghum and millet), increased N applications (66 kg N / ha, 27 kg N / ha and 111 kg N / ha for maize, sorghum and millet), and using short duration varieties. For millet the long duration variety was more beneficial. For maize there was opportunity to increase the yield without affecting the risk of yield loss, while for sorghum there was a synergy and for millet a trade-off between yield and risk. The different interactions between hazards and management for the three cereals stress the importance of maintaining farm diversity, as well as operational farm flexibility to respond to production risks.
C1 [Huet, E. K.; Giller, K. E.; Descheemaeker, K.] Wageningen Univ, Plant Prod Syst, Wageningen, Netherlands.
   [Adam, M.] CIRAD, UMR AGAP Inst, Bobo Dioualasso 01, Burkina Faso.
   [Adam, M.] Univ Montpellier, UMR AGAP Inst, Inst Agro, CIRAD, F-34398 Montpellier, France.
   [Adam, M.] Int Crops Res Inst Semi Arid Trop, Sorghum Breeding Program, Samanko 320, Bamako, Mali.
   [Traore, B.] Int Crops Res Inst Semi Arid Trop, Niamey, Niger.
C3 Wageningen University & Research; CIRAD; Universite de Montpellier;
   Institut Agro; CIRAD; CGIAR; International Crops Research Institute for
   the Semi-Arid-Tropics (ICRISAT); CGIAR; International Crops Research
   Institute for the Semi-Arid-Tropics (ICRISAT)
RP Huet, EK (corresponding author), Wageningen Univ, Plant Prod Syst, Wageningen, Netherlands.
EM eva.huet@wur.nl
RI Adam, Myriam/AAE-6299-2019; Giller, Ken/K-2799-2012
OI ADAM, Myriam/0000-0002-8873-6762
FU McKnight Foundation; CGIAR Research Program on Grain Legumes and Dryland
   Cereals (GLDC); Africa RISING project - USAID
FX This research is part of the project 'Pathways to agroecological
   intensification of crop-livestock systems in southern Mali' funded by
   the McKnight Foundation, and received support from the Africa RISING
   project funded by USAID and the CGIAR Research Program on Grain Legumes
   and Dryland Cereals (GLDC). We would like to thank Ousmane Sanogo, Salif
   Doumbia and Salia Coulibaly from IER, Mali (Institut d'Economie Rurale)
   for facilitating the collection and sharing of weather data. An
   additional thank you goes to anonymous reviewer(s) for their useful
   comments that helped to improve the paper.
CR Adam M, 2018, EUR J AGRON, V100, P35, DOI 10.1016/j.eja.2018.04.001
   Adam M, 2020, AGR SYST, V185, DOI 10.1016/j.agsy.2020.102920
   Akponikpè PBI, 2010, EUR J AGRON, V32, P144, DOI 10.1016/j.eja.2009.09.005
   Akumaga U, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9120497
   Amouzou KA, 2019, FIELD CROP RES, V235, P104, DOI 10.1016/j.fcr.2019.02.021
   Andrieu N, 2015, AGR SYST, V136, P125, DOI 10.1016/j.agsy.2015.02.010
   Aune JB, 2008, AGR SYST, V98, P119, DOI 10.1016/j.agsy.2008.05.002
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Bassu S, 2014, GLOBAL CHANGE BIOL, V20, P2301, DOI 10.1111/gcb.12520
   Benjaminsen TA, 2012, J PEACE RES, V49, P97, DOI 10.1177/0022343311427343
   Boansi D, 2019, THEOR APPL CLIMATOL, V135, P355, DOI 10.1007/s00704-018-2384-x
   Bosma RH, 1999, AGR SYST, V62, P1, DOI 10.1016/S0308-521X(99)00038-4
   Brouwer R, 2007, RISK ANAL, V27, P313, DOI 10.1111/j.1539-6924.2007.00884.x
   Bullock JM, 2017, J ECOL, V105, P880, DOI 10.1111/1365-2745.12791
   Challinor AJ, 2018, AGR SYST, V159, P296, DOI 10.1016/j.agsy.2017.07.010
   Cooper PJM, 2008, AGR ECOSYST ENVIRON, V126, P24, DOI 10.1016/j.agee.2008.01.007
   Defrance D, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187585
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Dzotsi KA, 2010, ECOL MODEL, V221, P2839, DOI 10.1016/j.ecolmodel.2010.08.023
   Ewansiha S. U., 2006, Journal of Food Agriculture & Environment, V4, P188
   Ewert F, 2015, ENVIRON MODELL SOFTW, V72, P287, DOI 10.1016/j.envsoft.2014.12.003
   Falconnier GN, 2020, GLOBAL CHANGE BIOL, V26, P5942, DOI 10.1111/gcb.15261
   Falconnier GN, 2016, FIELD CROP RES, V187, P113, DOI 10.1016/j.fcr.2015.12.015
   Falconnier GN, 2015, AGR SYST, V139, P210, DOI 10.1016/j.agsy.2015.07.005
   FAO, 2006, Guidelines for Soil Description, Vfourth
   Faye B, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaab40
   Fleisher DH, 2020, AGRON J, V112, P828, DOI 10.1002/agj2.20070
   Fosu-Mensah BY, 2012, NUTR CYCL AGROECOSYS, V94, P255, DOI 10.1007/s10705-012-9539-4
   Fosu-Mensah B.Y., 2016, Environmental Systems Research, V5, P22, DOI DOI 10.1186/S40068-016-0073-2
   Freduah BS, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9100639
   Frison EA, 2011, SUSTAINABILITY-BASEL, V3, P238, DOI 10.3390/su3010238
   Ganeme A., 2021, International Journal of Innovation and Applied Studies, V31, P836
   Getnet M.D., 2016, Crop intensification options and tradeGoffs with the water balance in the Central Rift Valley of Ethiopia
   Gijsman AJ, 2002, AGRON J, V94, P462, DOI 10.2134/agronj2002.4620
   Gijsman AJ, 2007, COMPUT ELECTRON AGR, V56, P85, DOI 10.1016/j.compag.2007.01.001
   GYGA, 2020, GLOB YIELD GAP WAT P
   Hardaker J. B., 2015, COPING RISK AGR APPL
   Hoogenboom G., 2019, Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.7.5
   Huet EK, 2020, AGR SYST, V184, DOI 10.1016/j.agsy.2020.102905
   Jones J.W., 1986, CERES-Maize: A simulation model of maize growth and development
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Joseph J.E., 2020, CGIAR RES PROGRAM CL
   Kante M, 2019, CROP SCI, V59, P2544, DOI 10.2135/cropsci2019.03.0172
   Kante S., 2001, Tropical resource Manegement Papers, V38
   Khumairoh U, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-32915-z
   Kloos J., 2015, UNUEHS Working Paper, 19
   Komarek AM, 2020, AGR SYST, V178, DOI 10.1016/j.agsy.2019.102738
   Kone? Y., 2020, POLITIQUE REGLEMENTA
   Kone? Y., 2020, MALIAN FARMERS ACCES
   Losch B., 2012, STRUCTURAL TRANSFORM
   Mach KJ, 2019, NATURE, V571, P193, DOI 10.1038/s41586-019-1300-6
   Masvaya EN, 2018, FIELD CROP RES, V228, P110, DOI 10.1016/j.fcr.2018.09.002
   Meuwissen MPM, 2019, AGR SYST, V176, DOI 10.1016/j.agsy.2019.102656
   Milgroom J, 2013, AGR SYST, V118, P91, DOI 10.1016/j.agsy.2013.03.002
   Mubaya CP, 2017, ENVIRON DEV SUSTAIN, V19, P2377, DOI 10.1007/s10668-016-9861-0
   Nissan H, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.579
   Olabisi Laura Schmitt, 2018, Environment Systems & Decisions, V38, P23, DOI 10.1007/s10669-017-9653-6
   OMA, 2016, US
   PIHA MI, 1993, EXP AGR, V29, P405, DOI 10.1017/S0014479700021128
   Ritchie JT, 1998, SYST APPR S, V7, P79
   Roudier P, 2011, GLOBAL ENVIRON CHANG, V21, P1073, DOI 10.1016/j.gloenvcha.2011.04.007
   Salack S, 2011, THEOR APPL CLIMATOL, V106, P1, DOI 10.1007/s00704-011-0414-z
   Schlecht E, 2006, NUTR CYCL AGROECOSYS, V76, P109, DOI 10.1007/s10705-005-1670-z
   Segnon AC, 2021, CLIM DEV, V13, P697, DOI 10.1080/17565529.2020.1855097
   Siart S, 2008, CAH AGRIC, V17, P195
   Singh P, 2017, SCI TOTAL ENVIRON, V601, P1226, DOI 10.1016/j.scitotenv.2017.06.002
   Singh P, 2014, AGR FOREST METEOROL, V185, P37, DOI 10.1016/j.agrformet.2013.10.012
   SIVAKUMAR MVK, 1992, J CLIMATE, V5, P532, DOI 10.1175/1520-0442(1992)005<0532:EAODSF>2.0.CO;2
   Soumare M., 2008, Dynamique et durabilite des systemes agraires a base de coton au Mali
   Sultan B, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-49167-0
   ten Berge HFM, 2019, GLOB FOOD SECUR-AGR, V23, P9, DOI 10.1016/j.gfs.2019.02.001
   The World Bank, 2016, AGR SECT RISK ASS ME
   Traore B, 2017, FIELD CROP RES, V201, P133, DOI 10.1016/j.fcr.2016.11.002
   Traore B, 2015, EXP AGR, V51, P615, DOI 10.1017/S0014479714000507
   Traore B, 2014, FIELD CROP RES, V156, P63, DOI 10.1016/j.fcr.2013.10.014
   Traore B, 2013, EUR J AGRON, V49, P115, DOI 10.1016/j.eja.2013.04.004
   Trisos C., 2022, Climate Change 2022: Impacts, Adaptation and Vulnerability, P172
   Urruty N, 2016, AGRON SUSTAIN DEV, V36, DOI 10.1007/s13593-015-0347-5
   van Dijk H, 2004, ENVIRON POLICY, V39, P173
   Van Wart J, 2015, AGR FOREST METEOROL, V209, P49, DOI 10.1016/j.agrformet.2015.02.020
   Vanlauwe B, 2019, EXP AGR, V55, P84, DOI 10.1017/S0014479716000193
   VANNOORDWIJK M, 1994, NETH J AGR SCI, V42, P249
   Wolf J, 2015, AGR FOREST METEOROL, V214, P208, DOI 10.1016/j.agrformet.2015.08.262
   World Bank, 2020, PPP CONV FACT
   Worou O.N., 2018, HDB CLIMATE CHANGE R, P1
NR 85
TC 5
Z9 6
U1 0
U2 10
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1161-0301
EI 1873-7331
J9 EUR J AGRON
JI Eur. J. Agron.
PD OCT
PY 2022
VL 140
AR 126587
DI 10.1016/j.eja.2022.126587
EA JUL 2022
PG 13
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 4W8SW
UT WOS:000860427200008
OA hybrid
DA 2025-01-10
ER

PT J
AU Wilson, K
   Arreak, A
   Bell, T
   Ljubicic, G
AF Wilson, Katherine
   Arreak, Andrew
   Bell, Trevor
   Ljubicic, Gita
CA Sikumiut Comm
TI The Mittimatalik Siku Asijjipallianinga (Sea Ice Climate Atlas): How
   Inuit Knowledge, Earth Observations, and Sea Ice Charts Can Fill IPCC
   Climate Knowledge Gaps
SO FRONTIERS IN CLIMATE
LA English
DT Article
DE Indigenous knowledge; Inuit Qaujimajatuqangit; decolonizing research;
   research co-production; sea ice; climate change adaptation; Arctic
ID TRADITIONAL KNOWLEDGE; NUNAVUT; VULNERABILITY; LAND; ADAPTATION;
   ULUKHAKTOK; RESCUE; HEALTH
AB The IPCC special report on the ocean and cryosphere in a changing climate (SROCC) highlights with high confidence that declining Arctic sea ice extents and increased ship-based transportation are impacting the livelihoods of Arctic Indigenous peoples. Current IPCC assessments cannot address the local scale impacts and adaptive needs of Arctic Indigenous communities based on the global, top-down model approaches used. Inuit maintain the longest unrecorded climate history of sea ice in Canada, and to support Inuit community needs, a decolonized, Inuit knowledge-based approach was co-developed in the community of Mittimatalik, Nunavut (Canada) to create the Mittimatalik siku asijjipallianinga (sea ice climate atlas) 1997-2019. This paper presents the novel approach used to develop the atlas based on Inuit knowledge, earth observations and Canadian Ice Service (CIS) sea ice charts, and demonstrates its application. The atlas provides an adaptation tool that Mittimatalik can use to share locations of known and changing sea ice conditions to plan for safe sea ice travel. These maps can also be used to support the safety and situational awareness of territorial and national search and rescue partners, often coming from outside the region and having limited knowledge of local sea ice conditions. The atlas demonstrates the scientific merit of Inuit knowledge in environmental assessments for negotiating a proposal to extend the shipping seasons for the nearby Mary River Mine. The timing and rates of sea ice freeze-up (October-December) in Mittimatalik are highly variable. There were no significant trends to indicate that sea ice is freezing up later to support increased shipping opportunities into the fall. The atlas shows that the first 2 weeks of November are critical for landfast ice formation, and icebreaking at this time would compromise the integrity of the sea ice for safe travel, wildlife migration and reproduction into the winter months. There was evidence that sea ice break-up (May-July) and the fracturing of the nearby floe edge have been occurring earlier in the last 10 years (2010-2019). Shipping earlier into the break-up season could accelerate the break-up of an already declining sea ice travel season, that Inuit are struggling to maintain.
C1 [Wilson, Katherine; Bell, Trevor] Mem Univ Newfoundland, Dept Geog, St John, NF, Canada.
   [Arreak, Andrew; Sikumiut Comm] SmartICE Sea Ice Monitoring & Informat Inc, Mittimatalik, NU, Canada.
   [Ljubicic, Gita] McMaster Univ, Sch Earth Environm & Soc, Hamilton, ON, Canada.
C3 Memorial University Newfoundland; McMaster University
RP Wilson, K (corresponding author), Mem Univ Newfoundland, Dept Geog, St John, NF, Canada.
EM katherine.wilson@mun.ca
FU Public Safety Canada's Search and Rescue New Initiatives Fund; Social
   Sciences and Humanities Research Council of Canada; Northern Scientific
   Training Program, ArcticNet, and Polar Knowledge Canada
FX This research was funded in part by the Public Safety Canada's Search
   and Rescue New Initiatives Fund, the Social Sciences and Humanities
   Research Council of Canada, the Northern Scientific Training Program,
   ArcticNet, and Polar Knowledge Canada. This research has received the
   following approvals: Nunavut Research License #02 013 20R-M; Memorial
   University of Newfoundland Interdisciplinary Committee on Ethics in
   Human Research, ethics approval #20190684-AR; and through a joint
   project agreement, Wilson received approvals from the CSA and CIS for
   the use of the archived RADARSAT data in this research (December 21,
   2018).
CR [Anonymous], 2015, Alaskan inuit food security conceptual framework: How to assess the Arctic from an inuit perspective
   [Anonymous], 2016, IN TAP KAN SUBM NAYL
   [Anonymous], 2018, National Inuit Strategy on Research
   [Anonymous], 2005, GOVT NUNAVUT NUNAVUT
   Archer L, 2017, SUSTAIN SCI, V12, P15, DOI 10.1007/s11625-016-0401-5
   Arctic Eider Society, 2020, SIKU IND KNOWL SOC N
   Bell T., 2016, NEWFOUNDLAND Q, V109, P37
   Bell T., 2020, SIKUMIUT PERSPECTIVE
   Bell T, 2014, OCEANS-IEEE
   Bindoff N. L., 2019, IPCC SPECIAL REPORT, P447
   Bohensky EL, 2011, ECOL SOC, V16, DOI 10.5751/ES-04342-160406
   Bourbonnais P., 2016, MARY RIVER PHASE 2 P
   Bravo M. T., 2009, HIGH PLACES CULTURAL, P161
   Brewer C., 2002, COLOUR BREWER
   Brychtova A., 2015, SEQUENTIAL COLOUR SC
   Cameron E, 2015, ANN ASSOC AM GEOGR, V105, P274, DOI 10.1080/00045608.2014.973006
   Clark DG, 2016, PUBLIC HEALTH, V137, P44, DOI 10.1016/j.puhe.2016.06.003
   Clark DG, 2016, SOC SCI MED, V169, P18, DOI 10.1016/j.socscimed.2016.09.026
   Cooley SW, 2020, NAT CLIM CHANGE, V10, P533, DOI 10.1038/s41558-020-0757-5
   CSA, 2019, CAN SPAC AG
   Damas D., 2002, ARCTIC MIGRANTSARCTI, DOI [10.2307/j.ctt809qt, DOI 10.2307/J.CTT809QT]
   Dawson J, 2018, ARCTIC, V71, P15, DOI 10.14430/arctic4698
   DFO, 2019, SCI REV PHAS 2 ADD F
   Driscoll DL, 2016, CLIMATIC CHANGE, V137, P455, DOI 10.1007/s10584-016-1687-0
   Durkalec A, 2015, SOC SCI MED, V136, P17, DOI 10.1016/j.socscimed.2015.04.026
   Durkalec A, 2014, INT J ENV RES PUB HE, V11, P1536, DOI 10.3390/ijerph110201536
   ECCC, 2020, CAN IC SERV
   ECCC, 2005, MAN IC MANICE ENV CL
   ECCC, 2021, CAN IC SERV 30 YEAR
   ESA, 2019, EUROPEAN SPACE AGENC
   Fawcett D, 2018, POLAR REC, V54, P119, DOI 10.1017/S003224741800027X
   Ford JD, 2019, NAT CLIM CHANGE, V9, P335, DOI 10.1038/s41558-019-0435-7
   Ford J, 2007, ARCTIC, V60, P150
   Ford JD, 2013, GLOBAL ENVIRON CHANG, V23, P1317, DOI 10.1016/j.gloenvcha.2013.06.001
   Ford JD, 2013, ANN ASSOC AM GEOGR, V103, P1193, DOI 10.1080/00045608.2013.776880
   Ford JD, 2012, CLIMATIC CHANGE, V113, P201, DOI 10.1007/s10584-011-0350-z
   Fox S., 2004, WEATHER IS UGGIANAQT
   Gearheard S.F., 2013, The Meaning of Ice: People and Sea Ice in Three Arctic Communities
   Gearheard S, 2006, AMBIO, V35, P203, DOI 10.1579/0044-7447(2006)35[203:INTSAC]2.0.CO;2
   GN and NTI, 2005, TERM CLIM CHANG
   Government of Nunavut and Nunavut Department of Education, 2007, IN QAUJ ED FRAM NUN
   Healey GK., 2014, Int J Crit Indigenous Stud, V7, P1, DOI DOI 10.5204/IJCIS.V7I1.117
   Heyes SA, 2011, CAN GEOGR-GEOGR CAN, V55, P69, DOI 10.1111/j.1541-0064.2010.00346.x
   Huntington HP, 2015, MAR POLICY, V51, P119, DOI 10.1016/j.marpol.2014.07.027
   ICC-Canada, 2014, SEA IC NEV STOPS CIR
   ipcc, 2019, Summary for Policy Makers of IPCC Special Report on the Ocean and Cryosphere in a Changing Climate
   Johnson N, 2015, ARCTIC, V68, P28, DOI 10.14430/arctic4447
   Kenny TA, 2018, FOOD POLICY, V80, P39, DOI 10.1016/j.foodpol.2018.08.006
   Kenny TA, 2018, PUBLIC HEALTH NUTR, V21, P1319, DOI 10.1017/S1368980017003810
   Laidler GJ, 2009, CLIMATIC CHANGE, V94, P363, DOI 10.1007/s10584-008-9512-z
   Leduc TB, 2007, CLIMATIC CHANGE, V85, P237, DOI 10.1007/s10584-006-9187-2
   McGrath J.T., 2018, The Qaggiq Model
   MTHO, 2021, MHTO INT PUBL HEAR M
   NASA, 2019, EOSDIS WORLDV
   NIRB, 2021, NUN IMP REV BOARD IN
   NSIDC, 2021, SEA IC IND AN TOOL
   Pearce T, 2015, ARCTIC, V68, P233, DOI 10.14430/arctic4475
   Pearce T, 2011, HUM ECOL, V39, P271, DOI 10.1007/s10745-011-9403-1
   Pearce T, 2010, POLAR REC, V46, P157, DOI 10.1017/S0032247409008602
   Pizzolato L, 2016, GEOPHYS RES LETT, V43, P12146, DOI 10.1002/2016GL071489
   Pizzolato L, 2014, CLIMATIC CHANGE, V123, P161, DOI 10.1007/s10584-013-1038-3
   Polar View, 2019, POL VIEW EARTH OBS P
   QIA, 2014, QIK TRUTH COMM OFF M
   Ramsay B., 1998, Can. J. Remote Sens., V24, P36, DOI DOI 10.1080/07038992.1998.10874689
   Ramsay B. R., 1996, EUROPEAN SPACE AGENC
   Riedlinger D., 2001, POLAR RECORDS, V37, P315, DOI DOI 10.1017/S0032247400017058
   Segal RA, 2020, ANN GLACIOL, V61, P284, DOI 10.1017/aog.2020.48
   Segal RA, 2020, ARCTIC, V73, P461, DOI 10.14430/arctic71567
   Sikumiut, 2021, WRITT SUBM SEA IC BA
   Sinha N.K., 2015, Sea ice: Physics and remote sensing
   Statistics Canada, 2017, POND INL
   Stroeve J, 2018, SEA ICE TRENDS CLIMA
   Tester F., 1997, TAMMARNIIT MISTAKES
   TRC [Truth and Reconciliation Commission of Canada], 2015, Canada's residential schools: The history, part 2, 1939 to 2000: The final report of the Truth and Reconciliation Commission of Canada, VI, DOI [10.2307/j.ctt19rm9wn, DOI 10.2307/J.CTT19RM9WN]
   Wachowich Nancy, 2018, HANDS MEASURE ESSAYS
   [Weyer N.M. IPCC IPCC], 2019, IPCC Special Report on the Ocean and Cryosphere in a Changing Climate
   White G, 2006, ARCTIC, V59, P401
   Willox AC, 2013, EMOT SPACE SOC, V6, P14, DOI 10.1016/j.emospa.2011.08.005
   Wilson KJ, 2020, ARCT SCI, V6, P127, DOI 10.1139/as-2019-0021
   Wilson K. J., 2018, MEMORIAL SIKUMIUT RE
   Wilson K J, IN PRESS
   WMO (World Meteorological Organization), 2017, WMO GUID CALC CLIM N, DOI DOI 10.1186/S12302-021-00458-2
NR 82
TC 10
Z9 10
U1 4
U2 9
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-9553
J9 FRONT CLIM
JI Front. Clim.
PD OCT 26
PY 2021
VL 3
AR 715105
DI 10.3389/fclim.2021.715105
PG 28
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA L2RW6
UT WOS:001021792700001
OA gold
DA 2025-01-10
ER

PT J
AU Wang, YJ
   Wang, Y
   Xu, HM
AF Wang, Yujie
   Wang, Yong
   Xu, Hongmei
TI Impacts of 1.5°C and 2.0°C Global Warming on Runoff of Three Inland
   Rivers in the Hexi Corridor, Northwest China
SO JOURNAL OF METEOROLOGICAL RESEARCH
LA English
DT Article
DE climate change; runoff; Shiyang River (SYR); Heihe River (HHR); Shule
   River (SLR)
ID 2 DEGREES-C; CLIMATE-CHANGE; WATER-RESOURCES; ARID REGION; HYDROLOGICAL
   MODELS; BASIN; EVAPOTRANSPIRATION; PRECIPITATION; STREAMFLOW;
   UNCERTAINTY
AB Basin-scale projections of river runoff at different warming levels provide useful information for climate change adaptation. In this study, we investigated changes in the projected climate and simulated runoff under 1.5 degrees C and 2.0 degrees C global warming of three inland rivers in the Hexi Corridor: the Shiyang River (SYR), the Heihe River (HHR), and the Shule River (SLR). The change in climate was projected based on five global climate models (GCMs) under three representative concentration pathways (RCPs), and the change in runoff was simulated based on the Soil and Water Assessment Tool (SWAT) hydrological model. Furthermore, the uncertainties in projected climate change and simulated runoff constrained by the GCMs and RCPs were quantified. The results indicate that, compared with the baseline period (1976-2005), there is a 1.42-1.54 degrees C increase in annual air temperature and 4%-12% increase in annual mean precipitation in the three river basins under 1.5 degrees C global warming, while there is a 2.09-2.36 degrees C increase in annual air temperature and 5%-11% increase in annual mean precipitation under 2.0 degrees C global warming. The simulated annual runoff of the SYR decreases by 4% under 1.5 degrees C global warming, that of the HHR decreases by 3% and 4%, while that of the SLR increases considerably by 10% and 11% under 1.5 degrees C and 2.0 degrees C global warming, respectively. The additional 0.5 degrees C global warming results in an annual air temperature increase of 0.67-0.82 degrees C, a change of -1% to 1% in annual mean precipitation, and a change of -1% to 5% in simulated runoff. The simulated annual runoff has greater uncertainty. The simulations indicate substantial and consistent warming in autumn and winter in the three basins, relatively drier summer and autumn in the SYR and HHR basins, and a relatively drier autumn in the SLR basin. The simulated monthly runoff shows more complex changes with large uncertainties constrained mainly by the GCMs.
C1 [Wang, Yujie] Nanjing Univ Informat Sci & Technol, Int Joint Res Lab Climate & Environm Change, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Key Lab Meteorol Disaster,Minist Educ, Nanjing 210044, Peoples R China.
   [Wang, Yujie] Nanjing Univ Informat Sci & Technol, Sch Atmospher Sci, Nanjing 210044, Peoples R China.
   [Wang, Yong] Chongqing Meteorol Serv, Chongqing Climate Ctr, Chongqing 401147, Peoples R China.
   [Xu, Hongmei] China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China.
C3 Nanjing University of Information Science & Technology; Nanjing
   University of Information Science & Technology; China Meteorological
   Administration
RP Xu, HM (corresponding author), China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China.
EM xuhm@cma.cn
FU National Key Research and Development Program of China [2018YFA0606302,
   SQ2018YFE010367]; China Meteorological Administration Climate Change
   Project [CCSF201924]
FX Supported by the National Key Research and Development Program of China
   (2018YFA0606302 and SQ2018YFE010367) and China Meteorological
   Administration Climate Change Project (CCSF201924).
CR [Anonymous], 2004, NAT SEED PROD, P1
   [Anonymous], 2008, HARM WORLD SOIL DAT
   [Anonymous], 2015, 3 NATL ASSESSMENT RE, P22
   Arnell NW, 2016, CLIMATIC CHANGE, V134, P343, DOI 10.1007/s10584-016-1600-x
   Arnold JG, 2012, T ASABE, V55, P1491
   Bao C, 2007, ECOL ECON, V62, P508, DOI 10.1016/j.ecolecon.2006.07.013
   Berg A, 2018, J CLIMATE, V31, P4865, DOI 10.1175/JCLI-D-17-0757.1
   Betts RA, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2016.0452
   Chen J, 2017, QUATERN INT, V453, P63, DOI 10.1016/j.quaint.2017.01.017
   Chen XL, 2016, SCI BULL, V61, P1451, DOI 10.1007/s11434-016-1166-z
   [程玉菲 CHENG Yufei], 2007, [冰川冻土, Journal of Glaciology and Geocryology], V29, P406
   Dile YT, 2014, J AM WATER RESOUR AS, V50, P1226, DOI 10.1111/jawr.12182
   Döll P, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab792
   Duan Z, 2016, SCI TOTAL ENVIRON, V573, P1536, DOI 10.1016/j.scitotenv.2016.08.213
   Essou GRC, 2016, J HYDROMETEOROL, V17, P1929, DOI 10.1175/JHM-D-15-0138.1
   Gosling SN, 2017, CLIMATIC CHANGE, V141, P577, DOI 10.1007/s10584-016-1773-3
   Grusson Y, 2017, WATER-SUI, V9, DOI 10.3390/w9010054
   Hao Y, 2018, WATER-SUI, V10, DOI 10.3390/w10121863
   Hargreaves G. H., 1985, Applied Engineering in Agriculture, V1, P96
   Hattermann FF, 2017, CLIMATIC CHANGE, V141, P561, DOI 10.1007/s10584-016-1829-4
   He Y, 2019, SUSTAIN CITIES SOC, V50, DOI 10.1016/j.scs.2019.101703
   Hempel S, 2013, EARTH SYST DYNAM, V4, P219, DOI 10.5194/esd-4-219-2013
   Javanmard S., 2010, Adv. Geosci, V25, P119, DOI [DOI 10.5194/ADGEO-25-119-2010AL, 10.5194/adgeo-25-119-2010, DOI 10.5194/ADGEO-25-119-2010]
   [蓝永超 Lan Yongchao], 2013, [冰川冻土, Journal of Glaciology and Geocryology], V35, P1474
   Li BF, 2012, QUATERN INT, V282, P87, DOI 10.1016/j.quaint.2012.06.005
   Li G, 2017, SCI TOTAL ENVIRON, V596, P256, DOI 10.1016/j.scitotenv.2017.04.080
   Li XL, 2017, AGR WATER MANAGE, V179, P55, DOI 10.1016/j.agwat.2016.07.010
   Li ZX, 2016, GLOBAL PLANET CHANGE, V144, P119, DOI 10.1016/j.gloplacha.2016.06.017
   Li ZX, 2016, GLOBAL PLANET CHANGE, V136, P41, DOI 10.1016/j.gloplacha.2015.12.002
   Liu LL, 2018, WATER-SUI, V10, DOI 10.3390/w10070883
   Liu LL, 2017, CLIMATIC CHANGE, V145, P145, DOI 10.1007/s10584-017-2072-3
   Lu ZX, 2015, PHYS CHEM EARTH, V79-82, P76, DOI 10.1016/j.pce.2014.11.003
   Ma ZM, 2008, J HYDROL, V352, P239, DOI 10.1016/j.jhydrol.2007.12.022
   Matin MA, 2013, J HYDROL, V486, P455, DOI 10.1016/j.jhydrol.2013.02.014
   McSweeney Carol F., 2016, Climate Services, V1, P24, DOI 10.1016/j.cliser.2016.02.001
   Neitsch S. L., 2005, SOIL WATER ASSESSMEN, P379
   Neitsch SL., 2011, THEORETICAL DOCUMENT
   Nilawar AP, 2019, SCI TOTAL ENVIRON, V650, P2685, DOI 10.1016/j.scitotenv.2018.09.334
   Pandey VP, 2019, SCI TOTAL ENVIRON, V650, P365, DOI 10.1016/j.scitotenv.2018.09.053
   Piao SL, 2010, NATURE, V467, P43, DOI 10.1038/nature09364
   Qin J, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-6187-z
   Schewe J, 2014, P NATL ACAD SCI USA, V111, P3245, DOI 10.1073/pnas.1222460110
   Shi YF, 2007, CLIMATIC CHANGE, V80, P379, DOI 10.1007/s10584-006-9121-7
   Su BD, 2017, CLIMATIC CHANGE, V141, P533, DOI 10.1007/s10584-016-1852-5
   Sun QH, 2015, INT J CLIMATOL, V35, P1125, DOI 10.1002/joc.4043
   UNFCCC, 2015, DEC 1 CP 21 AD PAR A
   Vetter T, 2015, EARTH SYST DYNAM, V6, P17, DOI 10.5194/esd-6-17-2015
   Vetter T, 2017, CLIMATIC CHANGE, V141, P419, DOI 10.1007/s10584-016-1794-y
   Wang HJ, 2013, CHINESE GEOGR SCI, V23, P286, DOI 10.1007/s11769-013-0605-x
   Wang JS, 2009, AGR WATER MANAGE, V96, P666, DOI 10.1016/j.agwat.2008.10.008
   Wang L, 2014, INT J CLIMATOL, V34, P2059, DOI 10.1002/joc.3822
   Wang RT, 2019, WATER-SUI, V11, DOI 10.3390/w11020347
   Wang XQ, 2019, QUATERN INT, V519, P32, DOI 10.1016/j.quaint.2018.11.010
   Wang YJ, 2017, ADV CLIM CHANG RES, V8, P268, DOI 10.1016/j.accre.2017.08.004
   Warszawski L, 2014, P NATL ACAD SCI USA, V111, P3228, DOI 10.1073/pnas.1312330110
   Weedon G., 2010, The WATCH forcing data 1958-2001: A meteorological forcing dataset for land surface-and hydrological-models
   Weedon GP, 2011, J HYDROMETEOROL, V12, P823, DOI 10.1175/2011JHM1369.1
   Zeng ZZ, 2018, J CLIMATE, V31, P2633, DOI 10.1175/JCLI-D-17-0236.1
   Zhai R, 2018, EARTH SYST DYNAM, V9, P717, DOI 10.5194/esd-9-717-2018
   Zou MZ, 2020, J HYDROL, V585, DOI 10.1016/j.jhydrol.2019.124323
NR 60
TC 9
Z9 10
U1 2
U2 44
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 2095-6037
EI 2198-0934
J9 J METEOROL RES-PRC
JI J. Meteorol. Res.
PD OCT
PY 2020
VL 34
IS 5
BP 1082
EP 1095
DI 10.1007/s13351-020-9152-4
PG 14
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA OQ4CG
UT WOS:000588732500014
OA hybrid
DA 2025-01-10
ER

PT J
AU Buras, A
   Menzel, A
AF Buras, Allan
   Menzel, Annette
TI Projecting Tree Species Composition Changes of European Forests for
   2061-2090 Under RCP 4.5 and RCP 8.5 Scenarios
SO FRONTIERS IN PLANT SCIENCE
LA English
DT Article
DE tree-species vulnerability; climate-smart forests; forest-management
   adaptation; climate change; CMIP5 climate projections; climate analogs
ID RADIAL GROWTH-PATTERNS; FAGUS-SYLVATICA L.; SCOTS PINE STANDS;
   QUERCUS-ROBUR L.; CLIMATE-CHANGE; DROUGHT TOLERANCE; FUTURE CLIMATE;
   NORWAY SPRUCE; MORTALITY; DECLINE
AB Climate change poses certain threats to the World's forests. That is, tree performance declines if species-specific, climatic thresholds are surpassed. Prominent climatic changes negatively affecting tree performance are mainly associated with so-called hotter droughts. In combination with biotic pathogens, hotter droughts cause a higher tree vulnerability and thus mortality. As a consequence, global forests are expected to undergo vast changes in the course of climate change. Changed climatic conditions may on the one hand locally result in more frequent dieback of a particular tree species but on the other hand allow other-locally yet absent species-to establish themselves, thereby potentially changing local tree-species diversity. Although several studies provide valuable insights into potential risks of prominent European tree species, we yet lack a comprehensive assessment on how and to which extent the composition of European forests may change. To overcome this research gap, we here project future tree-species compositions of European forests. We combine the concept of climate analogs with national forest inventory data to project the tree-species composition for the 26 most important European tree species at any given location in Europe for the period 2061-2090 and the two most relevant CMIP5 scenarios RCP 4.5 and RCP 8.5. Our results indicate significant changes in European forests species compositions. Species richness generally declined in the Mediterranean and Central European lowlands, while Scandinavian and Central European high-elevation forests were projected an increasing diversity. Moreover, 76% (RCP 4.5) and 80% (RCP 8.5) of the investigated locations indicated a decreasing abundance of the locally yet most abundant tree species while 74 and 68% were projected an increasing tree-species diversity. Altogether, our study confirms the expectation of European forests undergoing remarkable changes until the end of the 21st century (i.e., 2061-2090) and provides a scientific basement for climate change adaptation with important implications for forestry and nature conservation.
C1 [Buras, Allan; Menzel, Annette] Tech Univ Munich, Ecoclimatol, Freising Weihenstephan, Germany.
   [Buras, Allan] Tech Univ Munich, Land Surface Atmosphere Interact, Freising Weihenstephan, Germany.
   [Menzel, Annette] Tech Univ Munich, Inst Adv Study, Garching, Germany.
C3 Technical University of Munich; Technical University of Munich;
   Technical University of Munich
RP Buras, A (corresponding author), Tech Univ Munich, Ecoclimatol, Freising Weihenstephan, Germany.; Buras, A (corresponding author), Tech Univ Munich, Land Surface Atmosphere Interact, Freising Weihenstephan, Germany.
EM allan@buras.eu
RI Buras, Allan/B-1412-2012; Menzel, Annette/B-1105-2013
OI Menzel, Annette/0000-0002-7175-2512; Buras, Allan/0000-0003-2179-0681
FU Bavarian State Ministry for Food, Agriculture, and Forestry (StMELF)
   [M029]
FX This study has received funding from the Bavarian State Ministry for
   Food, Agriculture, and Forestry (StMELF, Grant Number M029).
CR Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   [Anonymous], 1967 KLIMADIAGRAMM W
   [Anonymous], 2018, CLIMATIC CHANGE, DOI DOI 10.1007/s10584-017-1972-6
   [Anonymous], 2012, DICT ALGORITHMS DATA
   [Anonymous], 1995, WATER AIR SOIL POLL, DOI DOI 10.1007/BF01182849
   [Anonymous], 2018, Global warming of 1.5 degree. an ipcc special report on the impacts of global warming of 1.5 degree above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development
   Bigler C, 2006, ECOSYSTEMS, V9, P330, DOI 10.1007/s10021-005-0126-2
   Breshears DD, 2005, P NATL ACAD SCI USA, V102, P15144, DOI 10.1073/pnas.0505734102
   Buras A, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa0b4
   Cailleret M, 2017, GLOBAL CHANGE BIOL, V23, P1675, DOI 10.1111/gcb.13535
   Linares JC, 2010, TREE PHYSIOL, V30, P795, DOI 10.1093/treephys/tpq052
   Carnicer J, 2011, P NATL ACAD SCI USA, V108, P1474, DOI 10.1073/pnas.1010070108
   Chen JQ, 1999, BIOSCIENCE, V49, P288, DOI 10.2307/1313612
   CHEN JQ, 1993, AGR FOREST METEOROL, V63, P219, DOI 10.1016/0168-1923(93)90061-L
   Choat B, 2018, NATURE, V558, P531, DOI 10.1038/s41586-018-0240-x
   Dulamsuren C, 2017, TREES-STRUCT FUNCT, V31, P673, DOI 10.1007/s00468-016-1499-x
   Dulamsuren C, 2010, GLOBAL CHANGE BIOL, V16, P3024, DOI 10.1111/j.1365-2486.2009.02147.x
   Eilmann B, 2009, TREE PHYSIOL, V29, P1011, DOI 10.1093/treephys/tpp035
   Fekete I, 2017, GLOBAL CHANGE BIOL, V23, P3154, DOI 10.1111/gcb.13669
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Ford JD, 2010, WIRES CLIM CHANGE, V1, P374, DOI 10.1002/wcc.48
   Galiano L, 2011, NEW PHYTOL, V190, P750, DOI 10.1111/j.1469-8137.2010.03628.x
   Galiano L, 2010, ECOSYSTEMS, V13, P978, DOI 10.1007/s10021-010-9368-8
   Gea-Izquierdo G, 2011, FOREST ECOL MANAG, V262, P1807, DOI 10.1016/j.foreco.2011.07.025
   Geiger R., 1961, Uberarbeitete Neuausgabe von Geiger
   Harris I, 2014, INT J CLIMATOL, V34, P623, DOI 10.1002/joc.3711
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Horton DE, 2015, NATURE, V522, P465, DOI 10.1038/nature14550
   Huang WW, 2017, AGR FOREST METEOROL, V247, P240, DOI 10.1016/j.agrformet.2017.07.016
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Kirisits T., 2012, Journal of Agricultural Extension and Rural Development, V4, P184, DOI DOI 10.5897/JAERD12.046
   Kohler M, 2010, EUR J FOREST RES, V129, P1109, DOI 10.1007/s10342-010-0397-9
   Koppen W., 1900, Geographische Zeitschrift, V11, P593
   Kreyling J, 2012, ENVIRON EXP BOT, V78, P99, DOI 10.1016/j.envexpbot.2011.12.026
   Kunreuther H, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P151
   Leibing C, 2013, FORESTS, V4, P155, DOI 10.3390/f4010155
   Lévesque M, 2013, GLOBAL CHANGE BIOL, V19, P3184, DOI 10.1111/gcb.12268
   Luedeling E, 2014, CURR OPIN ENV SUST, V6, P1, DOI 10.1016/j.cosust.2013.07.013
   MacLeod A, 2002, CROP PROT, V21, P635, DOI 10.1016/S0261-2194(02)00016-9
   Martinez-Meier A, 2008, FOREST ECOL MANAG, V256, P837, DOI 10.1016/j.foreco.2008.05.041
   Martínez-Sancho E, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00598
   Martínez-Vilalta J, 2012, BIOL LETTERS, V8, P689, DOI 10.1098/rsbl.2011.1059
   Mauri A, 2017, SCI DATA, V4, DOI 10.1038/sdata.2016.123
   McSweeney Carol F., 2016, Climate Services, V1, P24, DOI 10.1016/j.cliser.2016.02.001
   Metzger MJ, 2013, GLOBAL ECOL BIOGEOGR, V22, P630, DOI 10.1111/geb.12022
   MONSERUD RA, 1992, ECOL MODEL, V62, P275, DOI 10.1016/0304-3800(92)90003-W
   Nabuurs G-J., 2018, Climate-Smart Forestry: mitigation impacts in three European regions (From Science to Policy 6)
   Olson DM, 2001, BIOSCIENCE, V51, P933, DOI 10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2
   PASTOR J, 1988, NATURE, V334, P55, DOI 10.1038/334055a0
   Perkins D, 2018, FORESTS, V9, DOI 10.3390/f9030108
   Pfleiderer P, 2018, CLIM DYNAM, V51, P627, DOI 10.1007/s00382-017-3945-x
   Pichler P, 2007, FOREST ECOL MANAG, V242, P688, DOI 10.1016/j.foreco.2007.02.007
   R Core Team, 2017, R LANG ENV STAT COMP
   Rebetez M, 2004, THEOR APPL CLIMATOL, V79, P1, DOI 10.1007/s00704-004-0058-3
   Rehschuh R, 2017, DENDROCHRONOLOGIA, V45, P81, DOI 10.1016/j.dendro.2017.07.003
   Rigling A, 2013, GLOBAL CHANGE BIOL, V19, P229, DOI 10.1111/gcb.12038
   Sarkar D, 2008, USE R, P1
   Scharnweber T, 2013, TREE PHYSIOL, V33, P425, DOI 10.1093/treephys/tpt020
   Scharnweber T, 2011, FOREST ECOL MANAG, V262, P947, DOI 10.1016/j.foreco.2011.05.026
   Scherrer D, 2017, DIVERS DISTRIB, V23, P517, DOI 10.1111/ddi.12548
   Schleussner CF, 2016, NAT CLIM CHANGE, V6, P827, DOI 10.1038/NCLIMATE3096
   SHANNON CE, 1948, BELL SYST TECH J, V27, P623, DOI 10.1002/j.1538-7305.1948.tb00917.x
   Sousa-Silva R, 2018, FOREST POLICY ECON, V90, P22, DOI 10.1016/j.forpol.2018.01.004
   Sykes MT, 1996, CLIMATIC CHANGE, V34, P161, DOI 10.1007/BF00224628
   Walentowski H, 2017, ANN FOR RES, V60, P101, DOI 10.15287/afr.2016.789
   Zang C, 2014, GLOBAL CHANGE BIOL, V20, P3767, DOI 10.1111/gcb.12637
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
   Zscheischler J, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1700263
NR 69
TC 168
Z9 173
U1 7
U2 94
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 1664-462X
J9 FRONT PLANT SCI
JI Front. Plant Sci.
PD JAN 11
PY 2019
VL 9
AR 1986
DI 10.3389/fpls.2018.01986
PG 13
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA HH2EA
UT WOS:000455530200001
PM 30687375
OA Green Published, gold
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Tirado, MC
   Crahay, P
   Mahy, L
   Zanev, C
   Neira, M
   Msangi, S
   Brown, R
   Scaramella, C
   Coitinho, DC
   Müller, A
AF Tirado, M. C.
   Crahay, P.
   Mahy, L.
   Zanev, C.
   Neira, M.
   Msangi, S.
   Brown, R.
   Scaramella, C.
   Coitinho, D. Costa
   Mueller, A.
TI Climate change and nutrition: Creating a climate for nutrition security
SO FOOD AND NUTRITION BULLETIN
LA English
DT Article
DE Adaptation; agriculture; climate change; diets; food security; health;
   nutrition; mitigation; undernutrition; sustainable; risk reduction
ID PROTEIN-CONCENTRATION; FOOD; HEALTH; UNDERNUTRITION; CO2
AB Background: Climate change further exacerbates the enormous existing burden of undernutrition. It affects food and nutrition security and undermines current efforts to reduce hunger and promote nutrition. Undernutrition in turn undermines climate resilience and the coping strategies of vulnerable populations.
   Objectives: The objectives of this paper are to identify and undertake a cross-sectoral analysis of the impacts of climate change on nutrition security and the existing mechanisms, strategies, and policies to address them.
   Methods: A cross-sectoral analysis of the impacts of climate change on nutrition security and the mechanisms and policies to address them was guided by an analytical framework focused on the three 'underlying causes' of undernutrition: 1) household food access, 2) maternal and child care and feeding practices, 3) environmental health and health access. The analytical framework includes the interactions of the three underlying causes of undernutrition with climate change,vulnerability, adaptation and mitigation.
   Results: Within broad efforts on climate change mitigation and adaptation and climate-resilient development, a combination of nutrition-sensitive adaptation and mitigation measures, climate-resilient and nutrition-sensitive agricultural development, social protection, improved maternal and child care and health, nutrition-sensitive risk reduction and management, community development measures, nutrition-smart investments, increased policy coherence, and institutional and cross-sectoral collaboration are proposed as a means to address the impacts of climate change to food and nutrition security. This paper proposes policy directions to address nutrition in the climate change agenda and recommendations for consideration by the UN Framework Convention on Climate Change (UNFCCC).
   Conclusions: Nutrition and health stakeholders need to be engaged in key climate change adaptation and mitigation initiatives, including science-based assessment by the Intergovernmental Panel on Climate Change (IPCC), and policies and actions formulated by the UN Framework Convention on Climate Change (UNFCCC). Improved multi-sectoral coordination and political will is required to integrate nutrition-sensitive actions into climate-resilient sustainable development efforts in the UNFCCC work and in the post 2015 development agenda. Placing human rights at the center of strategies to mitigate and adapt to the impacts of climate change and international solidarity is essential to advance sustainable development and to create a climate for nutrition security.
C1 [Tirado, M. C.] Univ Calif Los Angeles, Fielding Sch Publ Hlth, Los Angeles, CA 90064 USA.
   [Crahay, P.; Brown, R.] Act Contre la Faim Int, Paris, France.
   [Mahy, L.; Coitinho, D. Costa] UN, Syst Standing Comm Nutr, Geneva, Switzerland.
   [Zanev, C.; Scaramella, C.] World Food Programme, Rome, Italy.
   [Neira, M.] WHO, Dept Publ Hlth & Environm, Geneva, Switzerland.
   [Msangi, S.] Int Food Policy Res Inst, Washington, DC 20036 USA.
   [Mueller, A.] Inst Adv Sustainabil Studies, Potsdam, Germany.
C3 University of California System; University of California Los Angeles;
   World Health Organization; CGIAR; International Food Policy Research
   Institute (IFPRI)
RP Tirado, MC (corresponding author), Univ Calif Los Angeles, Sch Publ Hlth, 2539 Vet Ave, Los Angeles, CA 90064 USA.
EM cristinatirado@ucla.edu
OI Tirado, Maria Cristina/0000-0001-6203-1927
FU Action Against Hunger
FX The authors are grateful to Javier von der Pahlen, Pai-Yei Whung, Elaine
   Fletcher, Diarmid Campbell-Lendrum, Elaine Marshall, Florence Egal,
   Andrew Tomkins, and other reviewers for helpful comments and to Rebecca
   Foelber, Willetta May Waisath, and Julia Boedecker for assistance in
   editing the paper. Action Against Hunger funded this work. The authors
   declare that they have no conflicts of interest.
CR Adato M., 2007, Conditional cash transfer programs: A" magic bullet" For reducing poverty?. 2020 Focus Brief on the World's Poor and Hungry People
   Alderman H., 2005, Economic and Political Weekly, V40, P4837
   [Anonymous], FACT SHEET RED EM DE
   [Anonymous], SCAL NUTR FRAM ACT
   [Anonymous], 2008, PROT HLTH CLIM CHANG
   [Anonymous], 6 UN SYST STAND COMM
   [Anonymous], 2001, ASS NUTR STAT VULN S
   [Anonymous], 2002, GEND EQ CLIM CHANG W
   [Anonymous], 2012, OECD FAO AGR OUTL 20
   [Anonymous], 2008, Climate Change and AIDS: A Joint Working Paper
   [Anonymous], 2009, AGR CROSSROADS
   [Anonymous], HUNGR CHANG 8 STEP C
   [Anonymous], 2010, CLIM CHANG NUTR SEC
   [Anonymous], 2009, The State of Food and Agriculture 2009: Livestock in the balance
   [Anonymous], ASS ENV IMP CONS PRO
   [Anonymous], 2007, Hyogo Framework for Action 2005-2015: Building the Resilience of Nations and Communities to Disasters
   [Anonymous], 2007, HUMAN DEV REPORT 200
   [Anonymous], CLIMATE CHANGE 2007
   [Anonymous], DISPL DUE NAT HAZ IN
   [Anonymous], EM EV DAT EM DAT
   [Anonymous], 6 SESS AD HOC WORK G
   [Anonymous], HAG C AGR FOOD SEC C
   [Anonymous], ETH MOD DEV AGR TECH
   [Anonymous], 2011, PROTEIN PUZZLE CONSU
   [Anonymous], 2018, STATE FOOD INWORLD
   [Anonymous], 2010, CLIM SMART AGR POL P
   [Anonymous], 16 SESS AG IT UNPUB
   [Anonymous], CLIM CHANG IMPL FOOD
   [Anonymous], GROWING BETTER FUTUR
   [Anonymous], 2007, CLIMATE CHANGE 2007
   [Anonymous], 2006, Livestock's Long Shadow: Environmental Issues and Options, DOI DOI 10.1007/S10666-008-9149-3
   [Anonymous], 2010, P INT SCI S BIODIVER
   [Anonymous], 3200137 IDS COMM UN
   [Anonymous], CLIM CHANG FOOD INS
   [Anonymous], 2007, CLIM CHANG CHILDR
   [Anonymous], 2008, LANCET, DOI DOI 10.1016/S0140-6736(07)61693-6
   [Anonymous], IFPRI 2020 C
   [Anonymous], CLIM AGR FOOD SEC ST
   Beddington S.J., 2011, INT J AGR MANAG, V1, P2
   Benson T., 2008, IMPROVING NUTR DEV P
   Black RE, 2008, LANCET, V371, P243, DOI [10.1016/S0140-6736(07)61690-0, 10.1016/S0140-6736(13)60937-X]
   Bloem MW, 2010, J NUTR, V140, p132S, DOI 10.3945/jn.109.112094
   Caesens E., 2009, Climate change and the right to food
   Carlsson-Kanyama A, 2009, AM J CLIN NUTR, V89, pS1704, DOI 10.3945/ajcn.2009.26736AA
   Cohen MJ., 2008, IMPACT CLIMATE CHANG
   Costello A, 2009, LANCET, V373, P1693, DOI 10.1016/S0140-6736(09)60929-6
   Crahay P., 2010, SCN News, P4
   Davies M, 2008, IDS BULL-I DEV STUD, V39, P105
   Del Ninno C, 2003, WORLD DEV, V31, P1221, DOI 10.1016/S0305-750X(03)00071-8
   Easterling W, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P273
   Fernando N, 2012, FOOD CHEM, V133, P1307, DOI 10.1016/j.foodchem.2012.01.105
   Friel S, 2009, LANCET, V374, P2016, DOI 10.1016/S0140-6736(09)61753-0
   Gillespie Stuart., 2005, INT FOOD POLICY RES
   Hawkes C., 2006, UNDERSTANDING LINKS
   Hazell P., 2010, The potential for scale and sustainability in weather index insurance for agriculture and rural livelihoods
   Horton S., 2010, Scaling up nutrition: What will it cost?
   Liniger H.P., 2011, Sustainable land management in practice - guidelines and best practices for sub-saharan Africa
   Lloyd SJ, 2011, ENVIRON HEALTH PERSP, V119, P1817, DOI 10.1289/ehp.1003311
   Maxwell D., 2008, RETHINKING FOOD SECU
   McMichael A., 2004, COMP QUANTIFICATION
   McMichael AJ, 2007, LANCET, V370, P1253, DOI 10.1016/S0140-6736(07)61256-2
   Nabarro D., 2010, Introducing the Policy Brief -'Scaling up Nutrition': A Framework for Action
   Nelson J, 2009, CLIMATE CHANGE AND GLOBAL POVERTY: A BILLION LIVES IN THE BALANCE, P223
   Parry M, 2009, CLIMATE CHANGE: OBSERVED IMPACTS ON PLANET EARTH, pXIII, DOI 10.1016/B978-0-444-53301-2.00027-0
   Sheeran J, 2010, WASH QUART, V33, P3, DOI 10.1080/01636601003673790
   Shekar M., 2006, REPOSITIONING NUTR C
   Smith P., 2007, Climate change: Mititgation. Contribution of Working Group III to the Fourth Assessment Report of Intergovernmental Panel on climate change, P499
   Taub D., 2010, Nature Education Knowledge, V1, P21
   Taub DR, 2008, GLOBAL CHANGE BIOL, V14, P565, DOI 10.1111/j.1365-2486.2007.01511.x
   Tirado MC, 2010, FOOD RES INT, V43, P1745, DOI 10.1016/j.foodres.2010.07.003
   Tirado MC, 2010, FOOD RES INT, V43, P1729, DOI 10.1016/j.foodres.2010.03.010
   UNEP-United Nations Environment Program, 2009, ENV FOOD CRIS ENV RO
   United Nations Framework Convention on Climate Change, 2010, OUTC WORK AD HOC WOR
   Wilkinson P, 2009, LANCET, V374, P1917, DOI 10.1016/S0140-6736(09)61713-X
   Yohe GW, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P811
NR 75
TC 44
Z9 47
U1 2
U2 96
PU SAGE PUBLICATIONS INC
PI THOUSAND OAKS
PA 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
SN 0379-5721
EI 1564-8265
J9 FOOD NUTR BULL
JI Food Nutr. Bull.
PD DEC
PY 2013
VL 34
IS 4
BP 533
EP 547
DI 10.1177/156482651303400415
PG 15
WC Food Science & Technology; Nutrition & Dietetics
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology; Nutrition & Dietetics
GA 287QA
UT WOS:000329556100015
PM 24605700
DA 2025-01-10
ER

PT J
AU Ma, X
   Wu, SH
   Li, Y
   Zhang, XY
   Gao, QZ
   Wu, Y
AF Ma Xin
   Wu Shaohong
   Li Yu'e
   Zhang Xueyan
   Gao Qingzhu
   Wu Yang
TI Rice re-cultivation in southern China: An option for enhanced climate
   change resilience in rice production
SO JOURNAL OF GEOGRAPHICAL SCIENCES
LA English
DT Article
DE climate change; adaptation; rice; seasonal drought
ID IMPACT
AB Rice planted in southern China accounts for 94% of the total in sown acreage and 88% of the total in production, which matters a lot to Chinese food security. However, due to the prolonged conflict between water availability and rice growth in spatial/temporal distribution, rice production suffers from seasonal drought at acreage of 16%-22%, which compromises food production capacity and food security. Focusing on the spatial distribution of seasonal drought with rice and the practices to adapt to it, and based on an analysis of balanced water supply for and demand by rice at a growing season scale during 1981-2030, this paper assesses the changing seasonal drought in the process of rice production under the changing climate in the future, and identifies general rice re-cultivation options for climate change adaptation. Some conclusions can be drawn as follows. (1) Rice suggests a decline in seasonal drought, with early season rice (early rice hereafter) by 12,500 km(2), middle season rice (middle rice) by 80,000 km(2), and in particular late season rice (late rice) by 25,000 km(2), which accounts for almost 20% of its cultivated acreage. It is indicated that due to climate change, seasonal drought in major rice producing areas tends to alleviate in general, late season rice in particular. (2) Future climate change brings about a significant impact on the spatial/temporal distribution of water resources in rice producing areas in China. Based on 'pre-designed' adaptation actions for rice-re-cultivation, the rice cultivation pattern undergoes a significant alteration between 1981-2000 and 2001-2030. In eastern Guizhou and western Hunan, the pattern of single early plus single dry farming is changed into double cropping. In eastern Hunan, the pattern of dry cropping is changed into single early plus single dry farming. In northern Anhui, the pattern of dry farming cropping is changed into middle rice. All this is aimed at a potential adequate availability of water for rice production in the future. (3) Rice re-cultivation patterns developed in this paper help re-balance water demand and supply for rice growth using the spatial analysis tool to adapt rice growth to the changing water availability from spatial perspective, and come up with rice producer-friendly re-cultivation options in response to climate change.
C1 [Ma Xin; Li Yu'e; Gao Qingzhu; Wu Yang] CAAS, Inst Environm & Sustainable Dev Agr, Beijing 100083, Peoples R China.
   [Wu Shaohong; Zhang Xueyan] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
C3 Chinese Academy of Agricultural Sciences; Institute of Environment &
   Sustainable Development in Agriculture, CAAS; Chinese Academy of
   Sciences; Institute of Geographic Sciences & Natural Resources Research,
   CAS
RP Wu, SH (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
EM max@ami.ac.cn; Wush@igsnrr.ac.cn
FU National Key Technology Research & Development Program [2012BAC19B01]
FX Foundation: National Key Technology Research & Development Program,
   No.2012BAC19B01
CR 张斌, 1995, 生态学报, V15, P413
   [Anonymous], GBT2009
   [Anonymous], CLIMATE CHANGE B
   [Anonymous], J FUJIAN AGR U
   [Anonymous], CHIN NAT ASS REP CLI
   [Anonymous], HYDROPOWER SICHUAN
   [Anonymous], ADV CLIMATE CHANGE R
   [Anonymous], J HYDROLOGY
   [Anonymous], STUDY CONTOUR LINE W
   [Anonymous], J IRRIGATION DRAINAG
   [Anonymous], GLOBAL PLANETARY CHA
   [Anonymous], CHIN ADDR CLIM CHANG
   [Anonymous], 1994, SYNTACTIC STUDY ZUO
   [Anonymous], J APPL METEOROLOGY
   [Anonymous], J GEOPHYS RES
   [Anonymous], HYDROPOWER GUANGXI
   [Anonymous], WATER RESOURCES RES
   [Anonymous], J WATER RESOURCE ENG
   [Anonymous], MODERN AGR SCI TECHN
   [Anonymous], RECLAMATION RICE
   [Anonymous], J HYDRAULIC ENG
   [Anonymous], CHINESE RURAL EC
   [Anonymous], HYDROPOWER SICHUAN
   [Anonymous], ADV CLIMATE CHANGE R
   [Anonymous], CHIN RIC PLANT ZON
   [Anonymous], RURAL EC
   [Anonymous], ANHUI AGR SCI
   [Anonymous], RURAL ECOENVIRONMENT
   [Anonymous], GLOBAL ENV CHANGE
   [Anonymous], YELLOW RIVER
   Chen Hua Chen Hua, 2004, Jiangsu Journal of Agricultural Sciences, V20, P129
   Gao FH, 2012, PROCEDIA ENGINEER, V28, P319, DOI 10.1016/j.proeng.2012.01.726
   [郭海英 GUO Haiying], 2008, [水土保持通报, Bulletin of Soil and Water Conservation], V28, P77
   [黄道友 Huang Daoyou], 2004, [生态学报, Acta Ecologica Sinica], V24, P2516
   Huang WanHua Huang WanHua, 2010, Transactions of the Chinese Society of Agricultural Engineering, V26, P50
   Huang WanHua Huang WanHua, 2009, Transactions of the Chinese Society of Agricultural Engineering, V25, P28
   Li Yong Li Yong, 2011, Transactions of the Chinese Society of Agricultural Engineering, V27, P175
   Liang X, 2003, GLOBAL PLANET CHANGE, V38, P101, DOI 10.1016/S0921-8181(03)00012-2
   [刘绿柳 Liu Luliu], 2012, [气候变化研究进展, Advances in Climate Change Research], V8, P28
   [马欣 MA Xin], 2011, [自然资源学报, Journal of Natural Resources], V26, P1052
   Meehl GA, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P747
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Qiu GY, 2012, J INTEGR AGR, V11, P144, DOI 10.1016/S1671-2927(12)60792-5
   Xiong W, 2010, AGR ECOSYST ENVIRON, V135, P58, DOI 10.1016/j.agee.2009.08.015
   Xiong W, 2009, GLOBAL ENVIRON CHANG, V19, P34, DOI 10.1016/j.gloenvcha.2008.10.006
   Xu YinLong Xu YinLong, 2005, Journal of Nanjing Institute of Meteorology, V28, P323
   [姚凤梅 YAO FengMei], 2007, [气候与环境研究, Climatic and Environmental Research], V12, P659
NR 47
TC 13
Z9 14
U1 3
U2 75
PU SCIENCE PRESS
PI BEIJING
PA 16 DONGHUANGCHENGGEN NORTH ST, BEIJING 100717, PEOPLES R CHINA
SN 1009-637X
EI 1861-9568
J9 J GEOGR SCI
JI J. Geogr. Sci.
PD FEB
PY 2013
VL 23
IS 1
BP 67
EP 84
DI 10.1007/s11442-013-0994-x
PG 18
WC Geography, Physical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography
GA 069RG
UT WOS:000313453600006
DA 2025-01-10
ER

PT J
AU Van de Vliert, E
AF Van de Vliert, Evert
TI White, gray, and black domains of cultural adaptations to climato-
   economic conditions
SO BEHAVIORAL AND BRAIN SCIENCES
LA English
DT Article
ID NATIONAL CHARACTER; COLLECTIVISM; ROOTS; INTERVENTION; PATTERNS; POORER;
   LESS
AB Forty-nine commentators have reviewed the theory that needs-based stresses and freedoms are shaped differently in threatening, comforting, and challenging climato-economic habitats. Their commentaries cover the white domain, where the theory does apply (e.g., happiness, collectivism, and democracy), the gray domain, where it may or may not apply (e.g., personality traits and creativity), and the black domain, where it does not apply (e.g., human intelligence and gendered culture). This response article provides clarifications, recommendations, and expectations.
C1 [Van de Vliert, Evert] Univ Groningen, Dept Social & Org Psychol, NL-9712 TS Groningen, Netherlands.
   [Van de Vliert, Evert] Univ Bergen, Dept Psychosocial Sci, N-5015 Bergen, Norway.
C3 University of Groningen; University of Bergen
RP Van de Vliert, E (corresponding author), Univ Groningen, Dept Social & Org Psychol, NL-9712 TS Groningen, Netherlands.
EM E.Van.de.Vliert@rug.nl
OI Van de Vliert, Evert/0000-0003-3322-7829
CR ADAMOPOULOS J, 1999, SOCIAL PSYCHOL CULTU, P63
   Adamopoulos John, 2012, HDB SOCIAL RESOURCE, P255
   Allik J, 2004, J CROSS CULT PSYCHOL, V35, P13, DOI 10.1177/0022022103260382
   [Anonymous], 2009, CLIMATE AFFLUENCE CU
   [Anonymous], 1997, COMPLEX INTERPERSONA
   Bandura A., 1997, SELF EFFICACY EXERCI
   Bell D., 1973, COMING POST-IND SOC
   Burghardt GM, 2005, GENESIS OF ANIMAL PLAY: TESTING THE LIMITS, P1
   Cline WilliamR., 2007, Global Warming and Agriculture: Impact Estimates by Country
   Coleman J.S., 1994, Foundations of Social Theory
   Conway LG, 2006, J CROSS CULT PSYCHOL, V37, P20, DOI 10.1177/0022022105282293
   Emrich C.G., 2004, Culture, leadership, and organizations: The GLOBE study of 62 societies, P343, DOI DOI 10.1016/S0263-2373(00)00015-3
   Fincher CL, 2012, BEHAV BRAIN SCI, V35, P99, DOI 10.1017/S0140525X11001774
   Fischer R, 2011, PERS SOC PSYCHOL B, V37, P1031, DOI 10.1177/0146167211407075
   Fiske A.P., 1991, Structures of social life: The four elementary forms of human relations: Communal sharing, authority ranking, equality matching, market pricing
   Foa U.G., 1974, SOC STRUCTURES MIND
   Fukuyama Francis., 1995, Trust: The Social Virtues and the Creation of Prosperity
   Harrison Lawrence., 2000, CULTURE MATTERS VALU, DOI DOI 10.1017/S0021911810002901
   Hofstede G., 1998, Masculinity and Femininity: The taboo dimension of national cultures
   HOFSTEDE G., 1980, Cultures Consequences: International Differences in Work-Related Values
   Inglehart R., 2004, HUMAN BELIEFS VALUES
   Inglehart R., 2005, Modernization, Cultural Change, and Democracy: The Human Development Sequence
   John O.P., 2000, Encyclopedia of Psychology, V6, P140
   Kong DT, 2013, J CROSS CULT PSYCHOL, V44, P574, DOI 10.1177/0022022112466700
   Lynn Richard., 2006, IQ GLOBAL INEQUALITY
   Marx K., 1993, Grundrisse: Foundations of the Critique of Political Economy
   McCrae RR, 2007, EUR J PERSONALITY, V21, P953, DOI 10.1002/per.647
   MONTESQUIEU C, 1989, ESPRIT LOIS
   Pennebaker JW, 1996, J PERS SOC PSYCHOL, V70, P372, DOI 10.1037/0022-3514.70.2.372
   Richerson Peter J., 2005, Not By Genes Alone: How Culture Transformed Human Evolution
   Sen A., 1999, Development as freedom, V1st
   Smith PB, 2004, J CROSS CULT PSYCHOL, V35, P6, DOI 10.1177/0022022103260460
   Terracciano A, 2005, SCIENCE, V310, P96, DOI 10.1126/science.1117199
   Triandis H., 1995, Individualism and Collectivism
   TRIANDIS HC, 1985, J RES PERS, V19, P395, DOI 10.1016/0092-6566(85)90008-X
   Van de Vliert E, 2004, J ENVIRON PSYCHOL, V24, P17, DOI 10.1016/S0272-4944(03)00021-5
   Van de Vliert E, 2003, J INT BUS STUD, V34, P40, DOI 10.1057/palgrave.jibs.8400007
   van de Vliert E, 2002, J CROSS CULT PSYCHOL, V33, P380, DOI 10.1177/00222102033004002
   Van de Vliert E, 2000, J ECON PSYCHOL, V21, P143, DOI 10.1016/S0167-4870(99)00040-9
   Van de Vliert E, 1999, J CROSS CULT PSYCHOL, V30, P291, DOI 10.1177/0022022199030003002
   Van de Vliert E., 2013, ADV CULTURE PSYCHOL, V3, P227, DOI [10.1093/acprof:oso/9780199930449.003.0005, DOI 10.1093/ACPROF:OSO/9780199930449.003.0005]
   Van De Vliert E, 2007, J CROSS CULT PSYCHOL, V38, P156, DOI 10.1177/0022022106297298
   Van de Vliert E, 2013, J CROSS CULT PSYCHOL, V44, P589, DOI 10.1177/0022022112463605
   Van de Vliert E, 2013, WORK STRESS, V27, P106, DOI 10.1080/02678373.2013.760901
   Van de Vliert E, 2009, INT J CROSS CULT MAN, V9, P185, DOI 10.1177/1470595809335715
   Van de Vliert E, 2012, BEHAV BRAIN SCI, V35, P94, DOI 10.1017/S0140525X11001075
   Van de Vliert E, 2011, J CROSS CULT PSYCHOL, V42, P494, DOI 10.1177/0022022110381120
   Vandello JA, 1999, J PERS SOC PSYCHOL, V77, P279, DOI 10.1037/0022-3514.77.2.279
   vandeVliert E, 1996, ACAD MANAGE J, V39, P986
   VANDEVLIERT E, 1977, J APPL BEHAV SCI, V13, P557, DOI 10.1177/002188637701300408
   VANDEVLIERT E, 1985, J APPL BEHAV SCI, V21, P19, DOI 10.1177/002188638502100103
   VANDEVLIERT E, CAN TOO FEW IN PRESS
   VANDEVLIERT E, 2012, CLIMATO EC LIV UNPUB
   Weber M., 1905, The Protestant Ethic and the Spirit of Capitalism and Other Writings, DOI DOI 10.4324/9780203995808
NR 54
TC 23
Z9 24
U1 1
U2 24
PU CAMBRIDGE UNIV PRESS
PI NEW YORK
PA 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA
SN 0140-525X
EI 1469-1825
J9 BEHAV BRAIN SCI
JI Behav. Brain Sci.
PD OCT
PY 2013
VL 36
IS 5
BP 503
EP 521
DI 10.1017/S0140525X13000277
PG 19
WC Psychology, Biological; Behavioral Sciences; Neurosciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Psychology; Behavioral Sciences; Neurosciences & Neurology
GA 234YR
UT WOS:000325681000026
DA 2025-01-10
ER

PT J
AU Hossain, MZ
   Adhikary, SK
   Nath, H
   Kafy, AA
   Altuwaijri, HA
   Rahman, MT
AF Hossain, Md. Zahed
   Adhikary, Sajal Kumar
   Nath, Hrithik
   Kafy, Abdulla Al
   Altuwaijri, Hamad Ahmed
   Rahman, Muhammad Tauhidur
TI Integrated Geospatial and Analytical Hierarchy Process Approach for
   Assessing Sustainable Management of Groundwater Recharge Potential in
   Barind Tract
SO WATER
LA English
DT Article
DE groundwater recharge; sustainable development; analytical hierarchical
   process; GIS; Barind tract
ID SOIL-WATER CONTENT; RAINFALL INTENSITY; LAND-USE; INFORMATION-SYSTEM;
   GIS; ZONES; BASIN; SURFACE; IDENTIFICATION; VARIABILITY
AB Groundwater depletion in Bangladesh's Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 x 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 x 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200-1400 mm/year) and high slope (6-40%). Conversely, very good recharge potential is associated with high rainfall zones (1800-2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.
C1 [Hossain, Md. Zahed] Bangladesh Univ Business & Technol BUBT, Dept Text Engn, Dhaka 1216, Bangladesh.
   [Hossain, Md. Zahed; Adhikary, Sajal Kumar; Nath, Hrithik] Khulna Univ Engn & Technol KUET, Dept Civil Engn, Khulna 9203, Bangladesh.
   [Nath, Hrithik] Univ Creat Technol Chittagong UCTC, Dept Civil Engn, Chattogram 4212, Bangladesh.
   [Kafy, Abdulla Al] Univ Texas Austin, Dept Geog & Environm, 1 Univ Stn A3100, Austin, TX 78712 USA.
   [Altuwaijri, Hamad Ahmed] King Saud Univ, Coll Humanities & Social Sci, Dept Geog, Riyadh 11451, Saudi Arabia.
   [Rahman, Muhammad Tauhidur] Univ Texas Dallas, Sch Econ Polit & Policy Sci, Geospatial Informat Sci Program, 800 Campbell Rd, Richardson, TX 75080 USA.
C3 Bangladesh University of Business & Technology (BUBT); Khulna University
   of Engineering & Technology (KUET); University of Texas System;
   University of Texas Austin; King Saud University; University of Texas
   System; University of Texas Dallas
RP Rahman, MT (corresponding author), Univ Texas Dallas, Sch Econ Polit & Policy Sci, Geospatial Informat Sci Program, 800 Campbell Rd, Richardson, TX 75080 USA.
EM zahedhossain@bubt.edu.bd; sajal@ce.kuet.ac.bd; hrithik@uctc.edu.bd;
   abdullaalkafy@utexas.edu; haaltuwaijri@ksu.edu.sa; mtr@utdallas.edu
RI Altuwaijri, Hamad/GRE-8676-2022; Adhikary, Sajal Kumar/I-7604-2019;
   Kafy, Abdulla Al/AAF-2173-2020; Rahman, Muhammad Tauhidur/C-3117-2015
OI Kafy, Abdulla Al/0000-0002-7544-5165; Nath, Hrithik/0000-0002-8381-715X;
   Rahman, Muhammad Tauhidur/0000-0003-1348-0536; Adhikary, Sajal
   Kumar/0000-0001-9899-8531; /0000-0002-2604-5974
FU King Saud University, Riyadh, Saudi Arabia;  [RSPD2024R848]
FX This research work was supported by King Saud University, Riyadh, Saudi
   Arabia under grant number RSPD2024R848.
CR Adham MI, 2010, J GEOL SOC INDIA, V75, P432, DOI 10.1007/s12594-010-0039-3
   Adhikary SK, 2013, 20TH INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2013), P2917
   Ahmad I, 2020, J AFR EARTH SCI, V164, DOI 10.1016/j.jafrearsci.2019.103747
   Ahmed A, 2021, WATER-SUI, V13, DOI 10.3390/w13182571
   Allison G.B., 1988, ESTIMATION NATURAL G, P49, DOI DOI 10.1007/978-94-015-7780-9_
   Andualem TG, 2019, J HYDROL-REG STUD, V24, DOI 10.1016/j.ejrh.2019.100610
   [Anonymous], 2017, Bangladesh Statistics 2017
   [Anonymous], 2021, UN WORLD WATER DEV R
   Anuraga TS, 2006, AGR WATER MANAGE, V84, P65, DOI 10.1016/j.agwat.2006.01.017
   Arulbalaji P, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-38567-x
   Avtar R, 2010, GEOCARTO INT, V25, P379, DOI 10.1080/10106041003731318
   BADC, 2020, Minor Irrigation Servey Report 20182019
   BMDA, 2019, Annual Report: 20182019
   BMDA, 2006, Borandro Authority PastPresent
   Valverde JPB, 2016, WATER-SUI, V8, DOI 10.3390/w8090391
   BROERSMA K, 1995, COMMUN SOIL SCI PLAN, V26, P1795, DOI 10.1080/00103629509369409
   Cristiano E, 2017, HYDROL EARTH SYST SC, V21, P3859, DOI 10.5194/hess-21-3859-2017
   Cui XF, 2024, ENVIRON MODELL SOFTW, V175, DOI 10.1016/j.envsoft.2024.105969
   Das N, 2020, ENVIRON DEV SUSTAIN, V22, P931, DOI 10.1007/s10668-018-0227-7
   de Vries JJ, 2002, HYDROGEOL J, V10, P5, DOI 10.1007/s10040-001-0171-7
   Dey Nepal C., 2017, Groundwater for Sustainable Development, V4, P66, DOI 10.1016/j.gsd.2017.02.001
   Dhaka Water Supply and Sewerage Authority, 2018, Establishment of Groundwater Monitoring System in Dhaka City for Aquifer Systems and DWASA Production Wells
   Ferozur RM, 2019, GROUNDWATER SUST DEV, V8, P205, DOI 10.1016/j.gsd.2018.11.006
   Fu BJ, 2000, CATENA, V39, P69, DOI 10.1016/S0341-8162(99)00084-3
   Guth PL, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13183581
   Hammouri N., 2012, Journal of Water Resource and Protection, V4, P717
   Hawke RM, 2006, CATENA, V65, P237, DOI 10.1016/j.catena.2005.11.013
   He S, 2019, HUM ECOL RISK ASSESS, V25, P354, DOI 10.1080/10807039.2019.1570463
   HENDERSON-SELLERS A, 1983, REV GEOPHYS, V21, P1743, DOI 10.1029/RG021i008p01743
   Horton RE, 1932, EOS T AM GEOPHYS UN, V13, P350
   Huang J, 2013, CATENA, V104, P93, DOI 10.1016/j.catena.2012.10.013
   Irwin EG, 2001, AGR ECOSYST ENVIRON, V85, P7, DOI 10.1016/S0167-8809(01)00200-6
   Iserloh T, 2013, Z GEOMORPHOL, V57, P11, DOI 10.1127/0372-8854/2012/S-00085
   Jahan CS, 2019, SUST WAT RESOUR MAN, V5, P689, DOI 10.1007/s40899-018-0240-x
   Januchowski SR, 2010, INT J GEOGR INF SCI, V24, P1327, DOI 10.1080/13658811003591680
   Jha MK, 2007, WATER RESOUR MANAG, V21, P427, DOI 10.1007/s11269-006-9024-4
   Jha MK, 2010, HYDROGEOL J, V18, P1713, DOI 10.1007/s10040-010-0631-z
   Jha MK, 2020, WATER RES, V179, DOI 10.1016/j.watres.2020.115867
   Jhariya DC, 2016, J GEOL SOC INDIA, V88, P481, DOI 10.1007/s12594-016-0511-9
   Kaewdum N, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.717313
   Kaliraj S, 2014, ARAB J GEOSCI, V7, P1385, DOI 10.1007/s12517-013-0849-x
   KARCZ I, 1978, TECTONOPHYSICS, V44, pT29, DOI 10.1016/0040-1951(78)90059-8
   LERNER DN, 1990, ATMOS ENVIRON B-URB, V24, P29, DOI 10.1016/0957-1272(90)90006-G
   Li FP, 2014, J HYDROL, V514, P53, DOI 10.1016/j.jhydrol.2014.04.010
   Liu H, 2011, J HYDROL, V396, P24, DOI 10.1016/j.jhydrol.2010.10.028
   Loken E, 2007, RENEW SUST ENERG REV, V11, P1584, DOI 10.1016/j.rser.2005.11.005
   Machiwal D, 2014, HYDROL PROCESS, V28, P2824, DOI 10.1002/hyp.9816
   Makki ZF, 2021, ENVIRON MONIT ASSESS, V193, DOI 10.1007/s10661-021-08858-w
   Malczewski J, 1999, SPATIAL MULTICRITERIA DECISION MAKING AND ANALYSIS, P11
   Michael HA, 2009, HYDROGEOL J, V17, P1329, DOI 10.1007/s10040-009-0443-1
   Mukherjee A  ..., 2021, Global groundwater, P3, DOI [10.1016/B978-0-12-818172-0.00001-3, DOI 10.1016/B978-0-12-818172-0.00001-3]
   Mukherjee S, 2013, INT J APPL EARTH OBS, V21, P205, DOI 10.1016/j.jag.2012.09.004
   Naghibi SA, 2016, ENVIRON MONIT ASSESS, V188, DOI 10.1007/s10661-015-5049-6
   Nath H., 2022, Advances in Civil Engineering: Select Proceedings of ICACE 2020. Lecture Notes in Civil Engineering (184), P25, DOI 10.1007/978-981-16-5547-0_3
   Nath H, 2024, THEOR APPL CLIMATOL, V155, P3693, DOI 10.1007/s00704-024-04843-8
   Nithya CN, 2019, REMOTE SENS APPL, V15, DOI 10.1016/j.rsase.2019.100248
   Nowreen S, 2021, ENVIRON MONIT ASSESS, V193, DOI 10.1007/s10661-020-08790-5
   Ogunbode T. O., 2019, International Journal of Hydrology, V3, P210, DOI [10.15406/ijh.2019.03.00182, DOI 10.15406/IJH.2019.03.00182, https://doi.org/10.15406/ijh.2019.03.00182]
   Pirone M, 2015, LANDSLIDES, V12, P259, DOI 10.1007/s10346-014-0483-z
   Qureshi A.S., 2014, Groundwater Management in Bangladesh: An Analysis of Problems and Opportunities
   Rahmati O, 2015, ARAB J GEOSCI, V8, P7059, DOI 10.1007/s12517-014-1668-4
   Roy S, 2020, SUST WAT RESOUR MAN, V6, DOI 10.1007/s40899-020-00373-z
   Saaty T.L., 1980, J. Oper. Res. Soc, V41, P1073, DOI DOI 10.1057/JORS.1991.178
   SAATY TL, 1990, MANAGE SCI, V36, P259, DOI 10.1287/mnsc.36.3.259
   Saaty TL., 2002, Int J Serv Sci, V9, P215, DOI [10.1504/IJSSCI.2008.017590, DOI 10.1504/IJSSCI.2008.017590, 10.1108/JMTM-03-2014-0020, DOI 10.1108/JMTM-03-2014-0020, 10.1504/ijssci.2008.017590]
   Sander P, 2007, HYDROGEOL J, V15, P71, DOI 10.1007/s10040-006-0138-9
   Saranya T, 2020, MODEL EARTH SYST ENV, V6, P1105, DOI 10.1007/s40808-020-00744-7
   Shaban A, 2006, HYDROGEOL J, V14, P433, DOI 10.1007/s10040-005-0437-6
   Shamsudduha M, 2011, HYDROGEOL J, V19, P901, DOI 10.1007/s10040-011-0723-4
   Song QR, 2024, ECOL INDIC, V160, DOI 10.1016/j.ecolind.2024.111907
   Thapa R, 2017, APPL WATER SCI, V7, P4117, DOI 10.1007/s13201-017-0571-z
   The World Bank, 2021, Annual Report
   Tucker GE, 2001, GEOMORPHOLOGY, V36, P187, DOI 10.1016/S0169-555X(00)00056-8
   Upwanshi M, 2023, URBAN CLIM, V48, DOI 10.1016/j.uclim.2023.101415
   Velasquez Mark, 2013, International lournal of Operations Research, V10, P56, DOI DOI 10.1007/978-3-319-12586-2
   Wang HJ, 2006, GLOBAL PLANET CHANGE, V50, P212, DOI 10.1016/j.gloplacha.2006.01.005
   Xu JH, 2014, WATER RESOUR MANAG, V28, P2523, DOI 10.1007/s11269-014-0625-z
   Yasrebi Jafar, 2008, Journal of Applied Sciences, V8, P1642, DOI 10.3923/jas.2008.1642.1650
   Yeh HF, 2009, ENVIRON GEOL, V58, P185, DOI 10.1007/s00254-008-1504-9
   Zghibi A, 2020, WATER-SUI, V12, DOI 10.3390/w12092525
NR 80
TC 1
Z9 1
U1 0
U2 0
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD OCT
PY 2024
VL 16
IS 20
AR 2918
DI 10.3390/w16202918
PG 21
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA K1J1Q
UT WOS:001341506200001
OA gold
DA 2025-01-10
ER

PT J
AU Liang, MS
   Dong, ZF
   Julius, S
   Neal, J
   Yang, YJ
AF Liang, Marissa S.
   Dong, Zhifei
   Julius, Susan
   Neal, Jill
   Yang, Y. Jeffrey
TI Storm Surge Projection and Objective-Based Risk Management for Climate
   Change Adaptation along the US Atlantic Coast
SO JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
LA English
DT Article
DE Coastal adaptation; Storm surge; Inundation; Modeling uncertainty; Risk
   assessment; Oceanic climate process
ID SEA-LEVEL RISE; TROPICAL CYCLONES; WIND; INTENSITY; IMPACTS; THREAT;
   WAVES; HRD
AB Climate change brings intense hurricanes and storm surges to the US Atlantic coast. These disruptive meteorological events, combined with sea level rise (SLR), inundate coastal areas and adversely impact infrastructure and environmental assets. Thus, storm surge projection and associated risk quantification are needed in coastal adaptation planning and emergency management. However, the projections can have large uncertainties depending on the planning time horizon. Excessive uncertainties arise from inadequately quantified ocean-climatic processes that control hurricane formation, storm track, and SLR in time of climate change. For this challenge, we propose an objective-based analytical-statistical approach using the National Oceanic and Atmospheric Administration's (NOAA)'s Sea, Lake, and Overland Surge from Hurricanes (SLOSH) model in scenario analysis of the storm surge impacts. In this approach, synthetic hurricanes (wind profile and track direction) are simulated to yield the likely range of the maximum envelope of water (MEOW), the maximum of the maximum (MOM), local wind speed, and directions. The surge height and time progression at a location are analyzed using a validated SLOSH model for a given adaptation or planning objective with a set of uncertainty tolerance. We further illustrate the approach in three case studies at Mattapoisett (MA), Bridgeport (CT), and Lower Chesapeake Bay along the US Atlantic coast. Simulated MOMs as the worst-case surge scenarios defined the long-term climate risk to the shoreside wastewater plants in Bridgeport and environmental assets in the Lower Chesapeake Bay. The wind-surge probability envelopes in simulated MEOWs provide location-specific estimates of the storm surge probability for local adaptation analysis at four locations in Lower Chesapeake Bay and at Mattapoisett of the southeastern Massachusetts coast. Using the constraints of local bathymetry and topography, the wind-surge probability curves and time progression also provide quantitative probability estimates for emergency response planning, as illustrated in the Mattapoisett case study.
C1 [Liang, Marissa S.] Off Chem Safety & Pollut Prevent, USEPA, 1200 Penn Ave NW, Washington, DC 20460 USA.
   [Dong, Zhifei] APTIM Inc, Coastal Ports & Marine Div, 2481 NW Boca Raton Blvd, Boca Raton, FL 33431 USA.
   [Julius, Susan] Ctr PublicHealth & Environm Assessment CPHEA, Ctr Publ Hlth & Environm Assessment CPHEA, USEPA, Off Res & Dev ORD, 1200 Penn Ave NW, Washington, DC 20460 USA.
   [Neal, Jill] US EPA, Off Res & Dev, Ctr Environm Solut & Emergency Response CESER, 26W Martin Luther King Dr, Cincinnati, OH 45268 USA.
   [Yang, Y. Jeffrey] Ctr Environmen tal Solut & Emergency Response CESE, Ctr Environm Solut & Emergency Response CESER, USEPA, 26W Martin Luther King Dr, Cincinnati, OH 45268 USA.
C3 United States Environmental Protection Agency; United States
   Environmental Protection Agency; United States Environmental Protection
   Agency; United States Environmental Protection Agency
RP Yang, YJ (corresponding author), Ctr Environmen tal Solut & Emergency Response CESE, Ctr Environm Solut & Emergency Response CESER, USEPA, 26W Martin Luther King Dr, Cincinnati, OH 45268 USA.
EM yang.jeff@epa.gov
FU EPA Office of Research and Development (ORD)
FX The research underpinning this paper is funded and conducted under the
   Air-Climate-Energy (ACE) National Research Program managed by the EPA
   Office of Research and Development (ORD). Any opinions expressed in this
   manuscript are those of the authors and do not necessarily reflect the
   views of the USEPA; therefore, no official endorsement should be
   inferred. The authors also thank anonymous peer reviewers for their
   constructive comments, Jerri Weiss (EPA Region 1) and Regina Poeske (EPA
   Region 3) for coordination in the case studies, and William (Quin)
   Robertson, formerly at Aptim Inc. for assistance in SLOSH modeling.
CR Anarde KA, 2018, NAT HAZARDS REV, V19, DOI [10.1061/(ASCE)NH.1527-6996.0000265, 10.1061/(asce)nh.1527-6996.0000265]
   [Anonymous], 2009, National Weather Digest
   [Anonymous], 2018, Impacts, risks, and adaptation in the united states: Fourth national climate assessment, VII, P1515, DOI DOI 10.7930/NCA4.2018
   [Anonymous], 1992, SLOSH: Sea, Lake and Overland Surges from Hurricanes
   Bacmeister JT, 2018, CLIMATIC CHANGE, V146, P547, DOI 10.1007/s10584-016-1750-x
   Barnard PL, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14365
   Bhattachan A, 2018, ENVIRON SCI POLICY, V90, P122, DOI 10.1016/j.envsci.2018.10.006
   BLAIN CA, 1994, J GEOPHYS RES-OCEANS, V99, P18467, DOI 10.1029/94JC01348
   Bunya S, 2010, MON WEATHER REV, V138, P345, DOI 10.1175/2009MWR2906.1
   Cha EJ, 2020, TROP CYCLONE RES REV, V9, P75, DOI 10.1016/j.tcrr.2020.04.005
   Chang NB, 2017, ATMOS RES, V193, P107, DOI 10.1016/j.atmosres.2017.04.018
   Cheung KF, 2003, OCEAN ENG, V30, P1353, DOI 10.1016/S0029-8018(02)00133-6
   DiNapoli SM, 2012, J ATMOS OCEAN TECH, V29, P822, DOI 10.1175/JTECH-D-11-00165.1
   Flynn T.J., 1984, Greenhouse Effect and Sea Level Rise: A Challenge for This Generation, P271
   Forbes C, 2014, J MAR SCI ENG, V2, P437, DOI 10.3390/jmse2020437
   Holland G, 2008, MON WEATHER REV, V136, P3432, DOI 10.1175/2008MWR2395.1
   Houston SH, 1999, WEATHER FORECAST, V14, P671, DOI 10.1175/1520-0434(1999)014<0671:COHASS>2.0.CO;2
   HOUSTON SH, 1994, WEATHER FORECAST, V9, P427, DOI 10.1175/1520-0434(1994)009<0427:OAMWAW>2.0.CO;2
   Jelesnianski C. P., 1973, A preliminary view of storm surges before and after storm modifications
   Knutson T, 2019, B AM METEOROL SOC, V100, P1987, DOI 10.1175/BAMS-D-18-0189.1
   Kossin JP, 2014, NATURE, V509, P349, DOI 10.1038/nature13278
   Leonardi N, 2018, GEOMORPHOLOGY, V301, P92, DOI 10.1016/j.geomorph.2017.11.001
   Liang M. S., 2017, On coastal topography and storm surge for infrastructure risk assessment and adaptation
   Liang MS, 2020, J ENVIRON MANAGE, V264, DOI 10.1016/j.jenvman.2020.110494
   Lin N, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD013630
   Lin N, 2019, CLIMATIC CHANGE, V154, P143, DOI 10.1007/s10584-019-02431-8
   Lin N, 2012, NAT CLIM CHANGE, V2, P462, DOI 10.1038/NCLIMATE1389
   Lin N, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD017126
   Liu MF, 2018, J CLIMATE, V31, P7269, DOI [10.1175/jcli-d-17-0747.1, 10.1175/JCLI-D-17-0747.1]
   Mayo T, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10040193
   Morrow BH, 2015, B AM METEOROL SOC, V96, P35, DOI 10.1175/BAMS-D-13-00197.1
   Phadke AC, 2003, OCEAN ENG, V30, P553, DOI 10.1016/S0029-8018(02)00033-1
   Powell MD, 1998, J WIND ENG IND AEROD, V77-8, P53, DOI 10.1016/S0167-6105(98)00131-7
   Rego JL, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2008GL036953
   Sheng YP, 2010, J GEOPHYS RES-OCEANS, V115, DOI 10.1029/2009JC005402
   Small C, 2016, J MAR SCI ENG, V4, DOI 10.3390/jmse4040067
   Sweet W. V., 2017, NOSCOOPS083 NOAA
   van Hengstum PJ, 2016, SCI REP-UK, V6, DOI 10.1038/srep21728
   Walsh KJE, 2016, WIRES CLIM CHANGE, V7, P65, DOI 10.1002/wcc.371
   Webster PJ, 2005, SCIENCE, V309, P1844, DOI 10.1126/science.1116448
   Westerink J. J., 1992, Report 2: Users Manual for ADCIRC-2DDI . Dredging Research Program Tech. Rep. No.DRP-92-6
   Westerink JJ, 2008, MON WEATHER REV, V136, P833, DOI 10.1175/2007MWR1946.1
   Yang JA, 2020, CLIMATIC CHANGE, V162, P425, DOI 10.1007/s10584-020-02782-7
   Yasuda T, 2014, COAST ENG, V83, P65, DOI 10.1016/j.coastaleng.2013.10.003
   Yin K, 2017, OCEAN ENG, V136, P80, DOI 10.1016/j.oceaneng.2017.03.016
   Zilli MT, 2019, CLIM DYNAM, V52, P2545, DOI 10.1007/s00382-018-4277-1
NR 46
TC 0
Z9 0
U1 3
U2 7
PU ASCE-AMER SOC CIVIL ENGINEERS
PI RESTON
PA 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
SN 0733-9496
EI 1943-5452
J9 J WATER RES PLAN MAN
JI J. Water Resour. Plan. Manage.-ASCE
PD JUN 1
PY 2024
VL 150
IS 6
AR 04024014
DI 10.1061/JWRMD5.WRENG-5483
PG 12
WC Engineering, Civil; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Water Resources
GA NT1R6
UT WOS:001202619100006
DA 2025-01-10
ER

PT J
AU Hussain, SA
   Razi, F
   Hewage, K
   Sadiq, R
AF Hussain, Syed Asad
   Razi, Faran
   Hewage, Kasun
   Sadiq, Rehan
TI The perspective of energy poverty and 1st energy crisis of green
   transition
SO ENERGY
LA English
DT Article
DE Climate change; Energy crisis; Energy poverty; Green transition;
   Renewable energy; Geo-politics; COVID-19
ID RENEWABLE ENERGY; IMPACT; STRATEGIES; MANAGEMENT; SYSTEMS; DESIGN
AB The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage; solar, wind, hydro, green hydrogen, etc.; renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations.
C1 [Hussain, Syed Asad; Razi, Faran; Hewage, Kasun; Sadiq, Rehan] Univ British Columbia, Life Cycle Management Lab, Sch Engn, Vancouver, BC, Canada.
C3 University of British Columbia
RP Hussain, SA (corresponding author), Univ British Columbia, Life Cycle Management Lab, Sch Engn, Vancouver, BC, Canada.
EM asad.hussain@ubc.ca
RI Hussain, Syed/C-4283-2015
OI Hussain, Syed Asad/0000-0003-2634-0014
CR Abnett Kate, 2022, SUSTAINABLE BUSINESS
   Adom PK, 2021, RENEW ENERG, V178, P1337, DOI 10.1016/j.renene.2021.06.120
   Ahl A, 2020, RENEW SUST ENERG REV, V117, DOI 10.1016/j.rser.2019.109488
   Aktar A, 2021, SUSTAIN PROD CONSUMP, V26, P770, DOI 10.1016/j.spc.2020.12.029
   Hoang AT, 2021, ENERG POLICY, V154, DOI 10.1016/j.enpol.2021.112322
   [Anonymous], 2009, World Energy Outlook 2009
   [Anonymous], 2021, The Role of Critical Minerals in Clean Energy Transitions, DOI [DOI 10.1787/F262B91C-EN, 10.1787/f262b91c-en]
   [Anonymous], 2018, The Role of Energy Efficiency: Perspectives for the Energy Transition
   [Anonymous], 2014, World Investment Report 2014
   [Anonymous], 2016, International Energy Outlook: 2016 with Projections to 2040
   [Anonymous], ENERGY PERFORMANCE B
   Arima J, 2022, EXPLORING SHORTTERM
   Atkins E, 2022, ENERGY RES SOC SCI, V90, DOI 10.1016/j.erss.2022.102681
   Baer D, 2022, LETS PLACE SUSTAINAB
   Balgar A.-C, 2021, GLOBAL EC OBSERVER, V9, P55
   Bedná O, 2022, ENERGIES, V15, DOI 10.3390/en15093443
   Bednar DJ, 2020, NAT ENERGY, V5, P432, DOI 10.1038/s41560-020-0582-0
   Belaïd F, 2023, RENEW ENERG, V205, P534, DOI 10.1016/j.renene.2023.01.083
   Belaïd F, 2022, ENERGY RES SOC SCI, V92, DOI 10.1016/j.erss.2022.102790
   Benton TG, 2022, UKRAINE WAR THREATS, P2022
   Berahab R, 2022, Policy
   Bergman N, 2020, ENERGY RES SOC SCI, V63, DOI 10.1016/j.erss.2019.101386
   Brew G, 2022, HDB OIL INT RELATION, P114
   Brook PJ, 2000, Energy services for the world's poor: energy and development report 2000
   Caseloads R., 2022, World Economic Outlook
   Castner L., 2010, LOW INCOME HOUSEHOLD
   Celasun O, 2022, IMFBLOG INSIGHTS ANA
   Chen H, 2022, ENERG ECON, V105, DOI 10.1016/j.eneco.2021.105757
   Connolly D, 2016, RENEW SUST ENERG REV, V60, P1634, DOI 10.1016/j.rser.2016.02.025
   Cormio C, 2003, RENEW SUST ENERG REV, V7, P99, DOI 10.1016/S1364-0321(03)00004-2
   da Silva SRS, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21502-y
   de Pee S, 2022, NAT FOOD, V3, P306, DOI 10.1038/s43016-022-00515-w
   de Sadeleer I, 2020, RESOUR CONSERV RECY, V160, DOI 10.1016/j.resconrec.2020.104908
   del Granado PC, 2022, ENERGY, V239, P12
   Demary Markus, 2022, Inter Econ, V57, P34, DOI 10.1007/s10272-022-1025-x
   Dietrich S, 2022, AM J AGR ECON, V104, P569, DOI 10.1111/ajae.12278
   Doman L., 2017, EIA projects 28% increase in world energy use by 2040 - Today in Energy - U.S. Energy Information Administration (EIA)
   Dunlap Alexander., 2021, A critical approach to the social acceptance of renewable energy infrastructures, P83, DOI [DOI 10.1007/978-3-030-73699-6_5, 10.1007/978-3-030-73699-6_5.Cham.acceptanceofrenewableenergyinfrastructures]
   Dzirutwe MacDonald, 2022, ENERGY
   Famiyeh S, 2021, RESOUR POLICY, V70, DOI 10.1016/j.resourpol.2020.101910
   Finn MG, 2000, J MONEY CREDIT BANK, V32, P400, DOI 10.2307/2601172
   Finnegan JJ, 2022, COMP POLIT STUD, V55, P1198, DOI 10.1177/00104140211047416
   Flood Colleen M, VULNERABLE POLICY LA
   Fred BO, 2021, GEOPOLITICS OIL GAS
   Gandhi HH, 2022, ENERGY STRATEG REV, V43, DOI 10.1016/j.esr.2022.100921
   Garrett-Peltier H, 2017, ECON MODEL, V61, P439, DOI 10.1016/j.econmod.2016.11.012
   Gatto A, 2022, ENERGY RES SOC SCI, V89, DOI 10.1016/j.erss.2022.102639
   Gdansk newsroom, 2022, TURKEYS INFLATION HI
   Gennaioli C, 2016, PUBLIC CHOICE, V166, P261, DOI 10.1007/s11127-016-0322-y
   Georgieva K, 2022, IMF BLOGS
   Giaccaglia C, 2022, THIRD WORLD Q, V43, P2888, DOI 10.1080/01436597.2022.2115883
   Gwynn G, 2022, US INFLATION RATE AC
   Hanke SH, 2022, HANKE DISCUSSES INFL
   Henry CL, 2021, ENERG ECON, V104, DOI 10.1016/j.eneco.2021.105665
   Heslin A, 2021, J PEACE RES, V58, P199, DOI 10.1177/0022343319898227
   Hosseini S. E., 2022, Future Energy, V1, P2, DOI [10.55670/fpll.fuen.1.1.8, DOI 10.55670/FPLL.FUEN.1.1.8]
   Howell S, 2017, RENEW SUST ENERG REV, V77, P193, DOI 10.1016/j.rser.2017.03.107
   IEA, 2024, SDG7: Data and Projections
   IEA, 2022, NAT'L L. REv.
   IEA, 2021, WHAT IS SOAR EN PRIC
   IEA, 2022, World Energy Outlook
   IEA, 2021, Energy efficiency 2021
   IEA U, 2020, GLOBAL ENERGY REV 20
   IPCC, 2019, FOOD SEC SPEC REP CL
   Jacobson MZ, 2022, ENERG ENVIRON SCI, V15, P3343, DOI 10.1039/d2ee00722c
   Jarrett R, 2022, ENERGY
   Jo-Anne M., FOOD PRICE INDEX HIT
   Josefa Sacko, 2022, RUSSIA UKRAINE CONFL
   Jun Z, 2022, RENEW ENERGY, P186
   Klein D., 2017, The Paris Agreement on Climate Change
   Kok K, 2012, IEEE POW ENER SOC GE, DOI 10.1109/PESGM.2012.6345058
   Kumar L, 2022, Future foods, P49, DOI DOI 10.1016/B978-0-323-91001-9.00009-8
   Lai LL, 2022, IEEE POWER ENERGY M, V20, P26, DOI 10.1109/MPE.2022.3184059
   Lazard O, 2022, BLIND SPOTS GREEN EN
   Leimbach M, 2019, CLIMATIC CHANGE, V155, P273, DOI 10.1007/s10584-019-02469-8
   Li R, 2014, ENERG J, V35, P159, DOI 10.5547/01956574.35.4.7
   Lidgett A., 2022, DIGICAT
   Limb L, 2022, EURONEWS
   Liu L, 2022, TECHNOL ECON DEV ECO, P1
   Luckeneder S, 2021, GLOBAL ENVIRON CHANG, V69, DOI 10.1016/j.gloenvcha.2021.102303
   Lund H., 2016, Int J Sustain Energy Plan Manag, DOI [DOI 10.5278/IJSEPM.2016.11.2, 10.5278/ijsepm.2016.11.2, DOI 10.1016/J.ENERGY.2017.05.123]
   Lund H, 2022, RENEWABLE SUSTAINABL, V168
   Lund H, 2018, ENERGY, V151, P94, DOI 10.1016/j.energy.2018.03.010
   Lund H, 2017, ENERGY, V137, P556, DOI 10.1016/j.energy.2017.05.123
   Lund H, 2012, ENERGY, V43, P192, DOI 10.1016/j.energy.2012.02.075
   Macchiarelli C, 2021, NATL INST ECON REV, P258
   MacDonald AP, 2021, CANADIAN FOREIGN POL, V27, P194, DOI 10.1080/11926422.2021.1936098
   Mancheri NA, 2019, RESOUR CONSERV RECY, V142, P101, DOI 10.1016/j.resconrec.2018.11.017
   Marsh S, 2022, COAL
   Meade S, 2021, CLIMATE MIGRATION HU
   Mercure JF, 2016, GLOBAL ENVIRON CHANG, V37, P102, DOI 10.1016/j.gloenvcha.2016.02.003
   Meyer JE, 2022, POSTPANDEMIC WORLD S
   Michaels R, 2021, The Private Side of Transforming Our World: UN Sustainable Development Goals 2030 and the Role of Private International Law
   Mir-Artigues P, 2015, RENEW SUST ENERG REV, V46, P166, DOI 10.1016/j.rser.2015.02.005
   Misík M, 2022, ENERG POLICY, V165, DOI 10.1016/j.enpol.2022.112930
   Mukherjee A., SPECIAL THEME MACROE, P119
   Mutezo G, 2021, RENEW SUST ENERG REV, V137, DOI 10.1016/j.rser.2020.110609
   Mutikani L, 2022, MACROMATTERS
   Ngepah N, 2011, AFR DEV REV, V23, P335, DOI 10.1111/j.1467-8268.2011.00290.x
   O'Brien K, 2004, CLIMATIC CHANGE, V64, P193, DOI 10.1023/B:CLIM.0000024668.70143.80
   Oxford Analytica, RIS POW PRIC RAIS RI
   Pirani S, 2022, PETROL BUSINESS REV, P6
   Polak P, 2022, CHANGES EUS GEOPOLIT, P1
   Popescu C., 2022, Energy transition industrial ecology, P289, DOI DOI 10.1007/978-981-19-3540-4_11
   Popkostova Y., 2022, Europes Energy Crisis Conundrum
   Qadir SA, 2021, ENERGY REP, V7, P3590, DOI 10.1016/j.egyr.2021.06.041
   Radhakrishnan BM, 2016, ENERGY, V103, P192, DOI 10.1016/j.energy.2016.02.117
   Ram M, 2022, ENERGY, V238, DOI 10.1016/j.energy.2021.121690
   Renner S, 2019, ENVIRON DEV ECON, V24, P180, DOI 10.1017/S1355770X18000402
   Reuters, 2022, US PROM DEL 15 BCM M
   Reuters, 2021, BRAZIL MINISTER WARN
   Reuters, 2022, FACTB 3 STAG GERM EM
   Ritchie H., 2019, FOSSIL FUELS
   Rogelj J, 2016, NATURE, V534, P631, DOI 10.1038/nature18307
   Sharma V, 2019, ENERGY RES SOC SCI, V52, P10, DOI 10.1016/j.erss.2019.01.025
   Solangi KH, 2011, RENEW SUST ENERG REV, V15, P2149, DOI 10.1016/j.rser.2011.01.007
   Stern DI, 2012, ENERG J, V33, P125, DOI 10.5547/01956574.33.3.5
   Stern DI, 1997, ECOL ECON, V21, P197, DOI 10.1016/S0921-8009(96)00103-6
   Stoferle RP, 2022, GOLD WE TRUST REPORT
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tarhan Mumtaz Derya., 2015, Journal of Entrepreneurial and Organizational Diversity, V4, P104, DOI [DOI 10.5947/JEOD.2015, 10.5947/jeod.2015.006]
   Tetlow G, 2022, Tackling rising inflation and slowing growth Government's big decision on how to share the pain
   The Economist, 2021, 1 BIG EN SHOCK GREEN
   Tian JF, 2022, APPL ENERG, V307, DOI 10.1016/j.apenergy.2021.118205
   Toman MA, 2003, ENERG J, V24, P93
   Tonn B, 2007, ENERG POLICY, V35, P743, DOI 10.1016/j.enpol.2005.12.011
   Tracker C. A., 2022, GLOBAL REACTION ENER
   Trading Economics, 2022, EU natural gas
   UNCTAD, 2022, INT INV CLIM CHANG M
   Vangala Shreyas, 2022, Climate and Energy, P1, DOI 10.1002/gas.22299
   Vaughan A, 2022, 1 GLOBAL ENERGY CRIS
   Walker AM, 2021, J CLEAN PROD, P286
   Wong D., 2022, CLIMATE CRISIS
   World Bank, 2019, World Development Indicators
   World Bank Group, 2022, Minerals for climate action: the mineral intensity of the clean energy transition
   WorldEconomicForum(WEF, HER WHY EN SEC IS VI
   Yep E, 2022, S P GLOB COMMODITY I
   Yin C., 2022, SCI TOTAL ENVIRON
   Yu Z, 2022, OPER MANAGE RES, V15, P233, DOI 10.1007/s12063-021-00179-y
   Zakeri B, 2022, ENERGIES, V15, DOI 10.3390/en15176114
   Zhang YG, 2022, RESOUR POLICY, V79, DOI 10.1016/j.resourpol.2022.102977
   Zhao J, 2022, RENEW ENERG, V186, P299, DOI 10.1016/j.renene.2022.01.005
NR 142
TC 69
Z9 71
U1 50
U2 141
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-5442
EI 1873-6785
J9 ENERGY
JI Energy
PD JUL 15
PY 2023
VL 275
AR 127487
DI 10.1016/j.energy.2023.127487
EA APR 2023
PG 9
WC Thermodynamics; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Energy & Fuels
GA G5JC6
UT WOS:000989507500001
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Jo, HW
   Krasovskiy, A
   Hong, MA
   Corning, S
   Kim, W
   Kraxner, F
   Lee, WK
AF Jo, Hyun-Woo
   Krasovskiy, Andrey
   Hong, Mina
   Corning, Shelby
   Kim, Whijin
   Kraxner, Florian
   Lee, Woo-Kyun
TI Modeling Historical and Future Forest Fires in South Korea: The FLAM
   Optimization Approach
SO REMOTE SENSING
LA English
DT Article
DE forest fire; risk modeling; model optimization; South Korea
ID TEMPERATURE CONDITION INDEX; CLIMATE-CHANGE ADAPTATION; SOIL-WATER
   CONTENT; BOREAL FOREST; LAND; DYNAMICS; NDVI
AB Climate change-induced heat waves increase the global risk of forest fires, intensifying biomass burning and accelerating climate change in a vicious cycle. This presents a challenge to the response system in heavily forested South Korea, increasing the risk of more frequent and large-scale fire outbreaks. This study aims to optimize IIASA's wildFire cLimate impacts and Adaptation Model (FLAM)-a processed-based model integrating biophysical and human impacts-to South Korea for projecting the pattern and scale of future forest fires. The developments performed in this study include: (1) the optimization of probability algorithms in FLAM based on the national GIS data downscaled to 1 km(2) with additional factors introduced for national specific modeling; (2) the improvement of soil moisture computation by adjusting the Fine Fuel Moisture Code (FFMC) to represent vegetation feedbacks by fitting soil moisture to daily remote sensing data; and (3) projection of future forest fire frequency and burned area. Our results show that optimization has considerably improved the modeling of seasonal patterns of forest fire frequency. Pearson's correlation coefficient between monthly predictions and observations from national statistics over 2016-2022 was improved from 0.171 in the non-optimized to 0.893 in the optimized FLAM. These findings imply that FLAM's main algorithms for interpreting biophysical and human impacts on forest fire at a global scale are only applicable to South Korea after the optimization of all modules, and climate change is the main driver of the recent increases in forest fires. Projections for forest fire were produced for four periods until 2100 based on the forest management plan, which included three management scenarios (current, ideal, and overprotection). Ideal management led to a reduction of 60-70% of both fire frequency and burned area compared to the overprotection scenario. This study should be followed by research for developing adaptation strategies corresponding to the projected risks of future forest fires.
C1 [Jo, Hyun-Woo; Kim, Whijin; Lee, Woo-Kyun] Korea Univ, Dept Environm Sci & Ecol Engn, Seoul 02841, South Korea.
   [Jo, Hyun-Woo; Krasovskiy, Andrey; Corning, Shelby; Kraxner, Florian] Int Inst Appl Syst Anal IIASA, Biodivers & Nat Resources BNR Program, Agr Forestry & Ecosyst Serv AFE Grp, Schlosspl 1, A-2361 Laxenburg, Austria.
   [Hong, Mina] Korea Univ, OJEong Resilience Inst OJERI, Seoul 02841, South Korea.
C3 Korea University; International Institute for Applied Systems Analysis
   (IIASA); Korea University
RP Lee, WK (corresponding author), Korea Univ, Dept Environm Sci & Ecol Engn, Seoul 02841, South Korea.
EM leewk@korea.ac.kr
RI Lee, Woo-Kyun/AAP-9837-2020; Krasovskiy, Andrey/AFO-4757-2022; Jo,
   Hyun-Woo/GZK-7613-2022
OI Krasovskiy, Andrey/0000-0003-0940-9366; Jo,
   Hyun-Woo/0000-0001-6127-883X; Kim, Whijin/0000-0002-7093-7312; Lee,
   Woo-Kyun/0000-0002-2188-359X
FU International Institute for Applied Systems Analysis, Laxenburg
   (Austria); National Research Foundation of Korea; Korea Forest Service
   (Korea Forestry Promotion Institute) [2021345B10-2223-CD01]; Integrated
   Future Wildfire Hot Spot Mapping for Austria (Austria Fire Futures) -
   Climate and Energy Fund [C265157]
FX This study was carried out with the support of R&D Program for Forest
   Science Technology (project No.2021345B10-2223-CD01) provided by Korea
   Forest Service (Korea Forestry Promotion Institute). This research was
   funded by the project "Integrated Future Wildfire Hot Spot Mapping for
   Austria (Austria Fire Futures)" number C265157, funded by the Climate
   and Energy Fund and carried out within the framework of the Austrian
   Climate Research Program (ACRP).
CR Arora VK, 2005, J GEOPHYS RES-BIOGEO, V110, DOI 10.1029/2005JG000042
   Bergeron Y, 2004, AMBIO, V33, P356, DOI 10.1639/0044-7447(2004)033[0356:PCAFFF]2.0.CO;2
   Lee Sung-Keun, 2004, [The Journal of Korean Association of Computer Education, 컴퓨터교육학회 논문지], V7, P37
   Chen J, 2004, REMOTE SENS ENVIRON, V91, P332, DOI 10.1016/j.rse.2004.03.014
   Cimdins R, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14225826
   Clark JS, 1996, ECOLOGY, V77, P2148, DOI 10.2307/2265709
   Engle NL, 2014, MITIG ADAPT STRAT GL, V19, P1295, DOI 10.1007/s11027-013-9475-x
   Pérez-Corona ME, 2021, EUR J FOREST RES, V140, P1081, DOI 10.1007/s10342-021-01387-8
   Fernandez-Anez N, 2021, AIR SOIL WATER RES, V14, DOI 10.1177/11786221211028185
   Ganteaume A, 2013, ENVIRON MANAGE, V51, P651, DOI 10.1007/s00267-012-9961-z
   Gavin DG, 2007, FRONT ECOL ENVIRON, V5, P499, DOI 10.1890/060161
   Gillies RR, 1997, INT J REMOTE SENS, V18, P3145, DOI 10.1080/014311697217026
   Hong M, 2022, CARBON BAL MANAGE, V17, DOI 10.1186/s13021-022-00208-8
   Jadmiko SD, 2017, IOP C SER EARTH ENV, V58, DOI 10.1088/1755-1315/58/1/012030
   Khabarov N, 2016, REG ENVIRON CHANGE, V16, P21, DOI 10.1007/s10113-014-0621-0
   Kim Jin-Hyeon, 2020, [Fire Science and Engineering, 한국화재소방학회 논문지], V34, P121, DOI 10.7731/KIFSE.2020.34.1.121
   Kim SJ, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11010086
   Kloster S, 2010, BIOGEOSCIENCES, V7, P1877, DOI 10.5194/bg-7-1877-2010
   Korea Forest Service, FOR FIR RISK PRED SY
   Korea Forest Service, 2018, 6 BAS FOR PLAN 2018, P151
   Korea Forest Service, 2022, YB FOR FIR STAT
   Krasovskii A, 2018, FORESTS, V9, DOI 10.3390/f9070437
   Krasovskii A, 2016, INT J WILDLAND FIRE, V25, P811, DOI 10.1071/WF15012
   Lawson B.D., 2008, WEATHER GUIDE CANADI
   Lee JG, 2009, ATMOS-KOREA, V19, P331
   Lee SJ, 2018, FORESTS, V9, DOI 10.3390/f9100625
   Lim CH, 2019, GEOMAT NAT HAZ RISK, V10, P719, DOI 10.1080/19475705.2018.1543210
   Migliavacca M, 2013, J GEOPHYS RES-BIOGEO, V118, P265, DOI 10.1002/jgrg.20026
   Moritz MA, 2014, NATURE, V515, P58, DOI 10.1038/nature13946
   Munang R, 2013, CURR OPIN ENV SUST, V5, P47, DOI 10.1016/j.cosust.2013.02.002
   Park E., 2021, ASSESSMENT AFFORESTA
   Park E, 2022, GISCI REMOTE SENS, V59, P36, DOI 10.1080/15481603.2021.2012370
   Patel NR, 2022, GEOCARTO INT, V37, P179, DOI 10.1080/10106049.2019.1704074
   Rahgozar Mandana., 2012, ISRN Soil Science. 2012, DOI DOI 10.5402/2012/726806
   Randerson JT, 2006, SCIENCE, V314, P1130, DOI 10.1126/science.1132075
   RICHARDS FJ, 1959, J EXP BOT, V10, P290, DOI 10.1093/jxb/10.2.290
   Scandella F., 2012, Firefighters: feeling the heat, ETUI- EPSU
   Song C, 2019, FORESTS, V10, DOI 10.3390/f10060523
   Sun H, 2016, IEEE J-STARS, V9, P336, DOI 10.1109/JSTARS.2015.2500605
   Sung MK, 2010, ATMOS-KOREA, V20, P27
   Sutanto SJ, 2020, ENVIRON INT, V134, DOI 10.1016/j.envint.2019.105276
   Turner M.G., 2015, Landscape Ecology in Theory and Practice, DOI DOI 10.1007/978-1-4939-2794-41
   Van Wagner CE., 1985, Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System
   Varela V, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11164284
   Wang PX, 2001, INT GEOSCI REMOTE SE, P141, DOI 10.1109/IGARSS.2001.976083
   Wang SW, 2023, ENVIRON REV, V31, P111, DOI 10.1139/er-2022-0041
   Won Myoungsoo, 2016, [Korean Journal of Agricultural and Forest Meteorology, 한국농림기상학회지], V18, P199, DOI 10.5532/KJAFM.2016.18.4.199
   Yang WJ, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11154188
NR 48
TC 6
Z9 6
U1 2
U2 13
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2072-4292
J9 REMOTE SENS-BASEL
JI Remote Sens.
PD MAR
PY 2023
VL 15
IS 5
AR 1446
DI 10.3390/rs15051446
PG 22
WC Environmental Sciences; Geosciences, Multidisciplinary; Remote Sensing;
   Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging
   Science & Photographic Technology
GA 9U7LD
UT WOS:000947887100001
OA Green Accepted, gold
DA 2025-01-10
ER

PT J
AU Elhegazy, H
   Zhang, JS
   Amoudi, O
   Zaki, JN
   Yahia, M
   Eid, M
   Mahdi, I
AF Elhegazy, Hosam
   Zhang, Jiansong
   Amoudi, Omar
   Zaki, Joliviana Nashaat
   Yahia, Mohamed
   Eid, Mohamed
   Mahdi, Ibrahim
TI An Exploratory Study on the Impact of the Construction Industry on
   Climate Change
SO JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT-INNOVATION AND
   ENTREPRENEURSHIP
LA English
DT Article
DE Climate change; construction industry; sustainable construction; climate
   change adaptation; climate change impacts
ID CARBON EMISSIONS; CO2 EMISSIONS
AB In the last decade, the construction industry in Egypt has been booming, and many mega projects are under construction. The lack of awareness of the construction industry's impact on climate change could be very harmful in terms of CO2 emission, water and soil pollution, etc. This paper aims to explore the critical factors in the Egyptian construction industry that contributes to climate change. Moreover, given the shared features between the construction industry in Egypt and those in other countries, this research could also shed light on the general impacts of the construction industry on the various aspects of climate change. So, to achieve this aim, an intensive literature review was carried out to identify various factors contributing to climate change within the construction industry. This is followed by conducting 11 interviews with construction experts to explore any further factors throughout the lifecycle of a construction project. The identified factors from the literature review and the interviews were used to design a questionnaire survey to collect construction professionals' opinions on the impact of these factors on climate change in Egypt. 48 valid responses were received. The collected data were statistically analyzed to rank and determine the criticality level of these factors. The results revealed that the most significant factors influencing climate change are the impact of industrial construction on climate change, the use of primary renewable energy as raw materials during the construction and use phases, and the effect of heavy civil and highway construction on climate change. The results also show that managing these factors requires considerable awareness and proactive actions during the project life cycle and pre-construction stage. The findings could inform decision-makers and construction professionals to raise awareness and make informed decisions to handle these key factors and minimize their potential contribution to climate change. Therefore, it can be recommended that construction clients may involve a climate change management plan as a requirement of tender documents.
C1 [Elhegazy, Hosam; Yahia, Mohamed; Mahdi, Ibrahim] Future Univ Egypt, Dept Struct Engn & Construction Management, Cairo, Egypt.
   [Elhegazy, Hosam; Zhang, Jiansong] Purdue Univ, Sch Construct Management Technol, W Lafayette, IN 47907 USA.
   [Amoudi, Omar] Oxford Brookes Univ, Sch Built Environm, Oxford, England.
   [Zaki, Joliviana Nashaat] Future Univ Egypt, Dept Biomed Engn, Cairo, Egypt.
   [Eid, Mohamed] Heliopolis Univ Sustainable Dev, Fac Organ Agr, Cairo, Egypt.
C3 Egyptian Knowledge Bank (EKB); Future University in Egypt; Purdue
   University System; Purdue University; Oxford Brookes University;
   Egyptian Knowledge Bank (EKB); Future University in Egypt; Egyptian
   Knowledge Bank (EKB); Heliopolis University
RP Elhegazy, H (corresponding author), Future Univ Egypt, Dept Struct Engn & Construction Management, Cairo, Egypt.; Elhegazy, H (corresponding author), Purdue Univ, Sch Construct Management Technol, W Lafayette, IN 47907 USA.
EM hossam.mostaffa@fue.edu.eg
RI Mahdi, Ibrahim/O-6741-2019; Hegazy, Hosam Mostafa/AAP-9018-2020
OI Yahia, Mohamed/0000-0002-0063-9408; Hegazy, Hosam
   Mostafa/0000-0002-8454-0690; Eid, Mohammed/0000-0001-9091-4145
CR Acquaye AA, 2010, BUILD ENVIRON, V45, P784, DOI 10.1016/j.buildenv.2009.08.022
   Ahmed N, 2021, AIN SHAMS ENG J, V12, P1375, DOI 10.1016/j.asej.2020.11.002
   Ahove M.A., 2018, In The political ecology of oil and gas activities in the Nigerian aquatic ecosystem, P277
   Bherwani H, 2022, ENERGY NEXUS, V5, DOI 10.1016/j.nexus.2022.100047
   Bhirud A., 2015, INT J RECENT INNOVAT, V3, P757
   Brand WVD., 2022, 15 EUROPEAN ACAD OCC
   Chen JD, 2022, ENVIRON IMPACT ASSES, V92, DOI 10.1016/j.eiar.2021.106679
   Chen JD, 2017, J CLEAN PROD, V168, P645, DOI 10.1016/j.jclepro.2017.09.072
   Chen Y, 2020, J IND INTEGR MANAG, V5, P33, DOI 10.1142/S2424862219500167
   Chen Y, 2016, J IND INF INTEGR, V2, P30, DOI 10.1016/j.jii.2016.04.004
   Crippa M., 2021, GHG EMISSIONS ALL WO
   Ding YJ, 2021, ADV CLIM CHANG RES, V12, P210, DOI 10.1016/j.accre.2021.03.002
   Earth Negotiations Bulletin, 2021, UN FRAM CONV CLIM CH
   Elhegazy H, 2022, INNOV INFRASTRUCT SO, V7, DOI 10.1007/s41062-021-00611-z
   Enshassi A, 2014, REV ING CONSTR, V29, P234, DOI 10.4067/S0718-50732014000300002
   European Commission, 2022, EDGAR EM DAT GLOB AT
   Gorkhali A., 2016, Journal of Industrial Integration and Management, V1
   Gustavsson L., 2015, CLIMATE CHANGE EFFEC
   Ha S, 2017, NAT HAZARDS REV, V18, DOI 10.1061/(ASCE)NH.1527-6996.0000247
   Hannah Ritchie M.R., 2020, Tech. rep., Our World in Data
   Huang CF, 2021, J CLEAN PROD, V311, DOI 10.1016/j.jclepro.2021.127576
   Hurlimann AC, 2018, BUILD ENVIRON, V137, P235, DOI 10.1016/j.buildenv.2018.04.015
   Hurlimann AC, 2019, BUILD ENVIRON, V153, P128, DOI 10.1016/j.buildenv.2019.02.008
   Ijigah E. A., 2013, Civil and Environmental Research, V3, P93
   IMF, 2022, EG AD CLIM CHANG
   Izoukumor, 2022, NIGERIAS LEGAL RESPO
   Khairy, 2022, J IND INTEGR MANAG
   Kit  KT, 2022, INT J ARCHITECTURAL, V16
   Kron W, 2012, NAT HAZARD EARTH SYS, V12, P535, DOI 10.5194/nhess-12-535-2012
   Kuh K F., 2018, Encyclopedia of the Anthropocene
   Li HX, 2017, ENERG BUILDINGS, V138, P666, DOI 10.1016/j.enbuild.2016.12.030
   Li LY, 2021, CLEAN ENG TECHNOL, V5, DOI 10.1016/j.clet.2021.100286
   Li N, 2021, J IND INF INTEGR, V22, DOI 10.1016/j.jii.2021.100203
   Lin BQ, 2019, SCI TOTAL ENVIRON, V659, P1505, DOI 10.1016/j.scitotenv.2018.12.449
   Lin BQ, 2015, BUILD ENVIRON, V94, P239, DOI 10.1016/j.buildenv.2015.08.013
   Lu, 2016, J IND INTEGR MANAG, V1
   Lu YJ, 2016, BUILD ENVIRON, V95, P94, DOI 10.1016/j.buildenv.2015.09.011
   Moore T., 2019, ENERGY PERFORMANCE A, P45, DOI DOI 10.1007/978-981-10-7880-4_4
   Muller M., 2020, PUTTING CONSTRUCTION
   Muto Y., 2022, ENV ADV, V7
   Naoum S.G., 2007, DISSERTATION RES WRI
   NASA, 2022, GISS SURF TEMP AN GI
   Niu Y., 2021, RESOUR CONSERV RECY, V170, P1
   Rajagopalan P., 2019, ENERGY PERFORMANCE A, P61
   Rana M.M. P., 2021, Environmental Challenges, V5, P100242, DOI DOI 10.1016/J.ENVC.2021.100242
   Rizqa EY., 2014, CIVIL ENV RES, V6
   Sadri H, 2022, BUILD ENVIRON, V207, DOI 10.1016/j.buildenv.2021.108446
   Säynäjoki A, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034037
   Seo Y, 2013, RENEW SUST ENERG REV, V26, P625, DOI 10.1016/j.rser.2013.06.003
   Smith M., 2013, Assessing Climate Change Risk and Opportunities for Investors- Mining and Minerals Processing Sector
   Swanson D., 2021, Advancing the Climate Resilience of Canadian InfrastructureA Review of Literature to Inform the Way Forward
   The Nature Conservancy, 2021, CLIM CHANG STOR CLIM
   Tiseo I, 2022, GLOBAL CARBON DIOXID
   Tracy A, 2007, CHINA PERSPECT, V1, P18
   United Nations, 1994, 7 UN FRAM CONV CLIM
   United Nations, 2018, DO YOU KNOW ALL 17 S
   Xu L., 2016, J IND INTEGR MANAG, V1
   Xu L.D., 2015, Enterprise Integration and Information Architecture: A Systems Perspective on Industrial Information Integration
   Xu LD, 2020, J IND INF INTEGR, V17, DOI 10.1016/j.jii.2020.100128
   Xu LD, 2011, IEEE T IND INFORM, V7, P630, DOI 10.1109/TII.2011.2167156
   Xu YY, 2022, BUILD ENVIRON, V215, DOI 10.1016/j.buildenv.2022.108936
   Zhang XC, 2016, BUILD ENVIRON, V104, P188, DOI 10.1016/j.buildenv.2016.05.018
   Zhang ZY, 2016, ENERG BUILDINGS, V112, P244, DOI 10.1016/j.enbuild.2015.12.026
   Zhong SS, 2022, AIN SHAMS ENG J, V13, DOI 10.1016/j.asej.2021.09.024
NR 64
TC 8
Z9 8
U1 7
U2 34
PU WORLD SCIENTIFIC PUBL CO PTE LTD
PI SINGAPORE
PA 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE
SN 2424-8622
EI 2424-8630
J9 J IND INTEGR MANAG
JI J. Ind. Integr. Manag.
PD SEP
PY 2024
VL 09
IS 03
BP 397
EP 418
DI 10.1142/S2424862222500282
EA JAN 2023
PG 22
WC Management
WE Emerging Sources Citation Index (ESCI)
SC Business & Economics
GA K4Y9H
UT WOS:000922466600001
DA 2025-01-10
ER

PT J
AU Lopes, HS
   Remoaldo, P
   Ribeiro, V
   Martín-Vide, J
AF Silva Lopes, Helder
   Remoaldo, Paula
   Ribeiro, Vitor
   Martin-Vide, Javier
TI The Use of Collaborative Practices for Climate Change Adaptation in the
   Tourism Sector until 2040-A Case Study in the Porto Metropolitan Area
   (Portugal)
SO APPLIED SCIENCES-BASEL
LA English
DT Article
DE urban tourism; climate change; adaptation; planning; Porto Metropolitan
   Area
ID POLICY DELPHI; URBAN SPACES; IMPACT; CITIES; HOT; MAP
AB When climate change became a global concern in the 1980s, mitigation was considered the best strategy to address all challenges. For a long time, it was thought possible to stabilize atmospheric concentrations of greenhouse gases (GHGs), which, according to many experts, brought on an unfit adaptation. There are international agreements designed to significantly reduce CO2 emissions and achieve carbon neutrality by 2050, but the policy measures taken so far are insufficient to achieve this goal. In addition, the crisis caused by the COVID-19 pandemic highlighted the relevance of placing this issue at the core of international policies and the need for bottom-up measures and options. The purpose of this paper is to explore how collaborative planning can contribute to adapting the urban tourism sector to climate change in the Porto Metropolitan Area (PMA), located in the northern region of mainland Portugal. In this investigation, we used mixed methods based on the following: (1) the discussion of urban tourism's adaptation planning to climate change with undergraduate students; (2) the application of a modified Delphi questionnaire survey, to 47 international researchers and technicians in the first round and 35 international researchers and technicians in the second round, about the predictability of the adaptation measures; and (3) a theoretical-practical workshop aimed to discuss the main action intentions and ways of adaptation in the short and medium term. All empirical data were collected during the year of 2021. This research highlights the need for more detailed information, the weak interaction between stakeholders and the limitation of resources. Our research identifies the main impacts and local vulnerabilities and determines priorities for adaptation and implementation of actions, aimed at mitigating the effects of climate change and maintaining tourism attractiveness in urban areas. In addition, this investigation allowed the definition of a research agenda, which seeks to guide the area of tourism climatology regarding the new challenges imposed by the COVID-19 pandemic.
C1 [Silva Lopes, Helder; Remoaldo, Paula; Ribeiro, Vitor] Univ Minho, Dept Geog, Lab2PT Landscape Heritage & Terr Lab, ICS, P-4800058 Guimaraes, Portugal.
   [Silva Lopes, Helder; Martin-Vide, Javier] Univ Barcelona, Dept Geog, FGH, IdRA Climatol Grp, Barcelona 08001, Spain.
   [Ribeiro, Vitor] ESE Paula Frassinetti, Dept Teacher Training, CIPAF, P-4000225 Porto, Portugal.
C3 Universidade do Minho; University of Barcelona
RP Lopes, HS (corresponding author), Univ Minho, Dept Geog, Lab2PT Landscape Heritage & Terr Lab, ICS, P-4800058 Guimaraes, Portugal.
EM htsltiago@hotmail.com; premoaldo@geografia.uminho.pt;
   vitor.geografia@gmail.com; jmartinvide@ub.edu
RI Lopes, Hélder/ADP-8422-2022; Remoaldo, Paula/M-2800-2017; RIBEIRO,
   Vitor/M-7663-2013
OI Martin-Vide, Javier/0000-0002-1179-7380; Lopes,
   Helder/0000-0002-2931-5175; RIBEIRO, Vitor/0000-0002-5993-3492
FU FCT Portugal [SFRH/BD/129153/2017]; FCT; FEDER [COMPETE2020-POCI 01 0145
   FEDER 007528]; Lab2PT-Landscapes, Heritage and Territory Laboratory
   [AUR/04509]; Fundação para a Ciência e a Tecnologia
   [SFRH/BD/129153/2017] Funding Source: FCT
FX This research was funded by FCT Portugal, grant number
   SFRH/BD/129153/2017 and Lab2PT-Landscapes, Heritage and Territory
   Laboratory-AUR/04509 and FCT through national funds and when applicable
   of the FEDER co-financing, in the aim/under the scope of the
   new-partnership agreement PT2020 and COMPETE2020-POCI 01 0145 FEDER
   007528.
CR Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   [Anonymous], 2018, World disasters report: leaving no one behind
   [Anonymous], 2018, Tourism and Climate Change Mitigation - Embracing the Paris Agreement
   Baláz V, 2021, MITIG ADAPT STRAT GL, V26, DOI 10.1007/s11027-021-09955-4
   Barriopedro D, 2011, SCIENCE, V332, P220, DOI 10.1126/science.1201224
   Berke P, 2021, CITIES, V119, DOI 10.1016/j.cities.2021.103408
   Camara Municipal do Porto, 2016, CLIMADAPT LOC ESTR M
   Carmona M, 2019, J URBAN DES, V24, P1, DOI 10.1080/13574809.2018.1472523
   Cheng Y, 2021, URBAN CLIM, V39, DOI 10.1016/j.uclim.2021.100962
   Clemente F, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11030297
   Collins L, 2018, J GEOGR, V117, P137, DOI 10.1080/00221341.2017.1374990
   Costa JP, 2014, URBAN DES INT, V19, P77, DOI 10.1057/udi.2013.15
   Costa JP., 2013, Urbanismo e Adaptacao as Alteracoes Climaticas-As Frentes de Agua
   Lopes HD, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116399
   DALKEY N, 1969, FUTURES, V1, P408, DOI 10.1016/S0016-3287(69)80025-X
   de Loë RC, 2016, TECHNOL FORECAST SOC, V104, P78, DOI 10.1016/j.techfore.2015.12.009
   DELOE RC, 1995, APPL GEOGR, V15, P53, DOI 10.1016/0143-6228(95)91062-3
   Depledge J, 2022, CLIM POLICY, V22, P147, DOI 10.1080/14693062.2022.2038482
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Garrod B, 2009, J TRAVEL RES, V47, P346, DOI 10.1177/0047287508322785
   Garrod B, 2005, TOURISM RESEARCH METHODS: INTEGRATING THEORY WITH PRACTICE, P85, DOI 10.1079/9780851999968.0085
   Gehl, 1987, LIFE BUILDINGS, V23
   GEHL J., 2006, La humanizacion del espacio urbano: La vida social entre los edificios
   Geneletti D, 2016, LAND USE POLICY, V50, P38, DOI 10.1016/j.landusepol.2015.09.003
   Giorgi F, 2010, CLIMATIC CHANGE, V100, P787, DOI [10.1007/s10584-010-9864-z, 10.1007/s10584-010-9864-Z]
   Gonçalves C, 2022, SCI TOTAL ENVIRON, V805, DOI 10.1016/j.scitotenv.2021.150320
   Hoerling M, 2012, J CLIMATE, V25, P2146, DOI 10.1175/JCLI-D-11-00296.1
   INE, 2021, POP RES N LOC RES RE
   IPCC, 2013, Climate Change 2013: The Physical Science Basis
   Jacobs J., 1961, DEATH LIFE GREAT AM
   Jevrejeva S, 2012, GLOBAL PLANET CHANGE, V80-81, P14, DOI 10.1016/j.gloplacha.2011.09.006
   Jiricka-Pürrer A, 2020, J OUTDOOR REC TOUR, V31, DOI 10.1016/j.jort.2020.100329
   Jopp R, 2013, ASIA PAC J TOUR RES, V18, P144, DOI 10.1080/10941665.2012.688515
   Kakderi C, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063158
   Kattirtzi M, 2020, TECHNOL FORECAST SOC, V153, DOI 10.1016/j.techfore.2020.119924
   Lemonsu A, 2015, URBAN CLIM, V14, P586, DOI 10.1016/j.uclim.2015.10.007
   Lerner Jamie., 2014, URBAN ACUPUNCTURE
   Lopes H. S., 2021, IMPACT TOURIST ACTIV, DOI [https://doi.org/10.1007/978-3-030-65524-2_9, DOI 10.1007/978-3-030-65524-2_9]
   Lopes H.S., 2022, CUAD GEOGR-BOGOTA, V31, P1
   Lopes H, 2021, B ASOC GEOGR ESP, DOI 10.21138/bage.3116
   Lopes HS, 2022, J ENVIRON MANAGE, V315, DOI 10.1016/j.jenvman.2022.115161
   Madureira H, 2021, CLIMATE, V9, DOI 10.3390/cli9030049
   Martinez-Ibarra E., 2008, Estudios Geograficos, V69, P135
   Martinez-Molina A, 2022, ENERG BUILDINGS, V262, DOI 10.1016/j.enbuild.2022.111997
   Masson-Delmotte V., 2021, CLIMATE CHANGE 2014, DOI [10.1016/S0925-7721(01)00003-7, DOI 10.1016/S0925-7721(01)00003-7]
   Masson-Delmotte V., 2018, Global warming of 1.5C, P1
   Matteucci X, 2022, J SUSTAIN TOUR, V30, P169, DOI 10.1080/09669582.2021.1924180
   McCall M, 2020, Cities & Health, DOI [DOI 10.1080/23748834.2020, 10.1080/23748834.2020.1780074]
   Mdaureira H, 2021, GEOGR SUSTAIN, V2, P182, DOI 10.1016/j.geosus.2021.08.001
   Megahed NA, 2020, SUSTAIN CITIES SOC, V61, DOI 10.1016/j.scs.2020.102350
   Meisch SP, 2022, FUTURES, V135, DOI 10.1016/j.futures.2021.102868
   MEYER JW, 1977, AM J SOCIOL, V83, P340, DOI 10.1086/226550
   Moeller G. H., 1987, Travel, tourism, and hospitality research. A handbook for managers and researchers, P417
   Monteiro A., 2018, Clima e Ambiente Urbano (Relatorio de Caracterizacao e Diagnostico)
   Moreira C.O., 2014, TURISMO TERRITORIO D
   Moreira CO, 2020, CUAD TUR, P423, DOI 10.6018/turismo.451911
   Ng E, 2009, BUILD ENVIRON, V44, P1478, DOI 10.1016/j.buildenv.2008.06.013
   Nielsen CP, 2011, J GEOGR, V110, P60, DOI 10.1080/00221341.2011.534171
   Önder DE, 2010, CITIES, V27, P260, DOI 10.1016/j.cities.2009.12.006
   Onete M, 2010, ENVIRON ENG MANAG J, V9, P1637, DOI 10.30638/eemj.2010.225
   Owen G, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102071
   Pamukcu-Albers P, 2021, LANDSCAPE ECOL, V36, P665, DOI 10.1007/s10980-021-01212-y
   Pandy WR, 2019, URBANI IZZIV, V30, P225, DOI 10.5379/urbani-izziv-en-2019-30-supplement-015
   Park J., 2019, THESIS U WASHINGTON
   Patterson JJ, 2021, GLOBAL ENVIRON CHANG, V68, DOI 10.1016/j.gloenvcha.2021.102279
   Penning-Rowsell E, 2006, GLOBAL ENVIRON CHANG, V16, P323, DOI 10.1016/j.gloenvcha.2006.01.006
   Perry J, 2021, CLIMATE, V9, DOI 10.3390/cli9080128
   Project for Public Spaces, 2000, TURN PLAC HDB CREAT
   Rodrguez G.A., 2018, Mediterr. J. Soc. Sci, V9, P145, DOI [10.2478/mjss-2018-0170, DOI 10.2478/MJSS-2018-0170]
   Nouri AS, 2017, BUILD ENVIRON, V118, P67, DOI 10.1016/j.buildenv.2017.03.027
   Santos NouriA., 2017, Journal of Urbanism: International Research on Placemaking and Urban Sustainability, V10, P356, DOI DOI 10.1080/17549175.2017.1295096
   Santos-Lacueva R, 2018, J SUSTAIN TOUR, V26, P1708, DOI 10.1080/09669582.2018.1503672
   Scott D, 2008, CLIM RES, V38, P61, DOI 10.3354/cr00774
   Scott Daniel, 2009, V1, P171, DOI 10.1007/978-1-4020-8921-3_8
   Sharifi A, 2020, SCI TOTAL ENVIRON, V749, DOI 10.1016/j.scitotenv.2020.142391
   Lopes HS, 2021, BUILD ENVIRON, V205, DOI 10.1016/j.buildenv.2021.108246
   Stringer E.T., 2020, ACTION RES-LONDON
   Susskind L, 2022, CLIM POLICY, V22, P593, DOI 10.1080/14693062.2021.1874860
   Urwin K, 2008, GLOBAL ENVIRON CHANG, V18, P180, DOI 10.1016/j.gloenvcha.2007.08.002
   Valls JF, 2009, TOUR REV, V64, P41, DOI 10.1108/16605370910963518
   van den Hove S, 2000, ECOL ECON, V33, P457, DOI 10.1016/S0921-8009(99)00165-2
   Vidal DG, 2022, ENVIRON SCI POLICY, V132, P262, DOI 10.1016/j.envsci.2022.03.002
   Vidal DG, 2021, INT J SUST DEV WORLD, V28, P291, DOI 10.1080/13504509.2020.1808108
   von Bergner NM, 2014, J TRAVEL RES, V53, P420, DOI 10.1177/0047287513506292
   von der Gracht HA, 2012, TECHNOL FORECAST SOC, V79, P1525, DOI 10.1016/j.techfore.2012.04.013
   Whyte W., 2001, SOCIAL LIFE SMALL UR
   Willems JJ, 2021, J ENVIRON POL PLAN, V23, P84, DOI 10.1080/1523908X.2020.1798750
   Yasmeen R., 2019, TOP 100 CIT DEST 201
   Sossa JWZ, 2019, FORESIGHT, V21, P525, DOI 10.1108/FS-11-2018-0095
   Zeppel H, 2012, CURR ISSUES TOUR, V15, P603, DOI 10.1080/13683500.2011.615913
   Zhang WQ, 2021, ENVIRON SCI POLLUT R, V28, P6561, DOI 10.1007/s11356-020-10919-5
NR 91
TC 3
Z9 3
U1 5
U2 19
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2076-3417
J9 APPL SCI-BASEL
JI Appl. Sci.-Basel
PD JUN
PY 2022
VL 12
IS 12
AR 5835
DI 10.3390/app12125835
PG 47
WC Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials
   Science, Multidisciplinary; Physics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Engineering; Materials Science; Physics
GA 2M2OA
UT WOS:000817544300001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Nnadi, OI
   Lyimo, JG
   Liwenga, ET
   Madukwe, MC
AF Nnadi, O., I
   Lyimo, J. G.
   Liwenga, E. T.
   Madukwe, M. C.
TI Equity and implications of response strategies on gender relations:
   Identifying ways of mainstreaming gender into response strategies in
   Southeast Nigeria
SO ENVIRONMENTAL DEVELOPMENT
LA English
DT Article
DE Climate change; Equity; Implications; Response strategies; Gender;
   Mainstreaming
ID CLIMATE-CHANGE ADAPTATION; CHANGING CLIMATE; HOUSEHOLDS; COMMUNITIES;
   EQUALITY; AFRICA
AB The interactions between prevailing gender gaps and climate variability and change (CVC) response strategies can intensify inequalities among farmers. Hence, this study examined implications of CVC response strategies on gender relations among farmers in Southeast Nigeria and ways of mainstreaming gender into the strategies. Specifically, it scrutinized the implications of CVC response strategies on gender relations; compliance of response strategies with equity dimensions and ways of mainstreaming gender into response strategies among farmers in SE region. Data were collected in various stages using focus group discussion, key informant interview and household (questionnaire) surveys of 150 men and 150 women farmers. Data analysis was performed using mean, standard deviations, and Pearson's chi-square in SPSS software. Findings revealed thatuse of government supports increase gender inequality because it provides limited gender sensitive response strategies. In addition, use of migrations cause women to spend more time on care giving works (p = 0.004). The response of men and women were significantly different for some variables that complied with contextual equity like the setting up of crop and animal insurance; procedural equity such as crop diversification (p = 0.020), and distributive equity such as the support of farmers to increase crop production. Gender differences (p < 0.05) exist in some ways of mainstreaming gender into response strategies such as improving women's training on access to fund, ensuring higher access to finance by women, and gender mainstreaming into traditional norms. Hence, this study recommends the use of gender-specific and equitable interventions such as providing trainings in line with needs of men and women to improve their information, technologies, knowledge and capacity for efficient use of CVC response strategies. In addition, there is need for sensitization of local communities to allow improved access to finance and economic resource for women in order to reduce gender inequalities and promote effective use of CVC response strategies.
C1 [Nnadi, O., I; Lyimo, J. G.; Liwenga, E. T.] Univ Dar Es Salaam Tanzania, Inst Resource Assessment, Dept Nat Resources Assessment & Management, Tanzania, Nigeria.
   [Nnadi, O., I; Madukwe, M. C.] Univ Nigeria Nsukka, Fac Agr, Dept Agr Extens, Nsukka, Nigeria.
C3 University of Nigeria
RP Nnadi, OI (corresponding author), Univ Dar Es Salaam Tanzania, Inst Resource Assessment, Dept Nat Resources Assessment & Management, Tanzania, Nigeria.
EM Onyinyechi.ogbonna@unn.edu.ng
RI ; LIWENGA, EMMA/IWD-9972-2023
OI Nnadi, Onyinyechi Ifeanyi/0000-0001-8990-947X; LIWENGA,
   EMMA/0000-0003-1731-3428
FU University of Nigeria Nsukka; University of Dar es Salaam Tanzania
FX We thank Trans-disciplinary Training for Resource Efficiency and Climate
   Change Adaptation in Africa II Intra-ACP (TreccAfrica II) for providing
   mobility programme to the principal investigator. We acknowledge the
   University of Nigeria Nsukka and University of Dar es Salaam Tanzania
   for additional support for this research work.
CR Aguilar A, 2015, AGR ECON-BLACKWELL, V46, P311, DOI 10.1111/agec.12167
   Aguilar L, 2008, GENDER PERSPECTIVES
   Agwu J., 2009, Gender and climate change in Nigeria
   Ajaero CK, 2017, FOOD SECUR, V9, P685, DOI 10.1007/s12571-017-0695-x
   Ali D, 2016, WORLD DEV, V87, P152, DOI 10.1016/j.worlddev.2016.06.006
   Alston M, 2014, WOMEN STUD INT FORUM, V47, P287, DOI 10.1016/j.wsif.2013.01.016
   Ampaire EL, 2017, ENVIRON SCI POLICY, V75, P81, DOI 10.1016/j.envsci.2017.05.013
   Amusa T.A., 2015, AM-EURASIAN J AGRIC, V15, P1779, DOI [DOI 10.5829/idosi.aejaes.2015.15.9.1880, 10.5829/idosi.aejaes.2015.15.9.1880]
   [Anonymous], 2018, CRIT POLICY STUD, DOI DOI 10.1080/19460171.2016.1191363
   [Anonymous], 2015, INT RES J NAT SCI
   [Anonymous], 2011, Gender and climate change adaptation: Tools for community-level action in Nigeria
   Aura R., 2017, GENDER REV CLIMATE C
   Awotide B.A., 2016, AGR FOOD EC, V4, P3, DOI [DOI 10.1186/S40100-016-0047-8, 10.1186/s40100-016-0047-8]
   Backiny-Yitna P., 2015, WORLD BANK POLICY RE
   Bernier Q., 2015, CCAFS Working Paper No. 79
   Bernier Q., 2013, Addressing gender in climate-smart smallholder agriculture. ICRAF Policy Brief 14
   Bryan E, 2018, CLIM DEV, V10, P417, DOI 10.1080/17565529.2017.1301870
   Bryant CR, 2017, J SETTL SPAT PLAN, V8, P79, DOI 10.24193/JSSP.2017.2.01
   Carr ER, 2014, GEOGR COMPASS, V8, P182, DOI 10.1111/gec3.12121
   Connolly-Boutin L, 2016, REG ENVIRON CHANGE, V16, P385, DOI 10.1007/s10113-015-0761-x
   Djoudi H, 2016, AMBIO, V45, pS248, DOI 10.1007/s13280-016-0825-2
   Eastin J, 2018, WORLD DEV, V107, P289, DOI 10.1016/j.worlddev.2018.02.021
   Enete AA, 2016, INT J CLIM CHANG STR, V8, P96, DOI 10.1108/IJCCSM-07-2014-0084
   Fabiyi E. F., 2015, Journal of Agricultural Science (Toronto), V7, P236
   Farnworth CR, 2016, INT J AGR SUSTAIN, V14, P142, DOI 10.1080/14735903.2015.1065602
   Federal Ministry of Women Affairs and Social Development, 2006, NAT GEND POL FED REP
   Haynes K., 2010, 2 IDS
   Ifeanyi-Obi CC, 2017, J AGRIC EXT, V21, P91, DOI 10.4314/jae.v21i2.8
   Issa FO, 2015, J AGRIC EXT, V19, P35, DOI 10.4314/jae.v19i1.3
   Kehinde A. D., 2016, International Journal of Agricultural Policy and Research, V4, P276
   Koyenikan MJ, 2017, J AGRIC EXT, V21, P162, DOI 10.4314/jae.v21i3.16
   Kristjanson P, 2017, INT J AGR SUSTAIN, V15, P482, DOI 10.1080/14735903.2017.1336411
   Lawal A., 2017, J AGR SCI-CAMBRIDGE, V12
   Leedy P.D., 2010, PRACTICAL RES PLANNI
   Mayowa P.C, 2008, MAINSTREAMING TRUE G
   McDermott M, 2013, ENVIRON SCI POLICY, V33, P416, DOI 10.1016/j.envsci.2012.10.006
   Mtupile E.E, 2017, INT J ENV AGR BIOTEC, V2
   National Bureau of Statistics, 2018, 2017 STAT REP WOM ME
   Ngigi MW, 2017, ECOL ECON, V138, P99, DOI 10.1016/j.ecolecon.2017.03.019
   Ngodoo A.C., 2014, INT J HUMANIT SOC SC, V4, P11
   Nnadi OI, 2019, HELIYON, V5, DOI 10.1016/j.heliyon.2019.e02085
   Nwapi C, 2016, AFR J LEG STUD, V9, P124, DOI 10.1163/17087384-12340005
   Nwosu E., 2015, 201501 PARTN EC POL
   Ogunsumi L. O., 2017, Journal of Agricultural Science (Toronto), V9, P201, DOI 10.5539/jas.v9n9p201
   Okam C., 2016, ASIAN J AGR EXTENSIO, V10, P1, DOI [https://doi.org/10.9734/ajaees/2016/18391, DOI 10.9734/AJAEES/2016/18391]
   Okeke C. C., 2016, International Journal of Agriculture and Biosciences, V5, P124
   Okonkwo A., 2018, COOU AFRICAN J ENV R, V1, P151
   Ologeh IO., 2018, Limits to Climate Change Adaptation, P159
   Onasanya A. S., 2018, J SOCIAL HUMANITIES, V3, P53
   Ongeko K.O., 2017, INT J SCI RES PUBL, V7, P680
   Onyeneke R. U., 2010, Science World Journal, V5, P32
   Perez C, 2015, GLOBAL ENVIRON CHANG, V34, P95, DOI 10.1016/j.gloenvcha.2015.06.003
   Peterman Amber., 2014, GENDER AGR FOOD SECU, P145, DOI [DOI 10.1007/978-94-017-8616-47, DOI 10.1007/978-94-017-8616-4_7]
   Reckien D, 2017, ENVIRON URBAN, V29, P159, DOI 10.1177/0956247816677778
   The Center for People and Forests (RECOFTC), 2014, EQ CLIM CHANG REDD H
   Warmbrod JR., 2014, JAE, V55, P30
   Wilmoth T.C., 2015, 85 AM PUBL U SYST DI
   Women U.N, 2015, COST GEND GAP AGR PR
   Wong S, 2016, J INT DEV, V28, P428, DOI 10.1002/jid.3212
   Wrigley-Asante C, 2019, AFR GEOGR REV, V38, P126, DOI 10.1080/19376812.2017.1340168
   Zusman E., 2016, Mainstreaming Gender into Climate Mitigation Activities: Guidelines for Policy Makers and Proposal Developers
NR 61
TC 2
Z9 2
U1 4
U2 13
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2211-4645
EI 2211-4653
J9 ENVIRON DEV
JI Environ. Dev.
PD SEP
PY 2021
VL 39
AR 100618
DI 10.1016/j.envdev.2021.100618
EA AUG 2021
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA UD6EB
UT WOS:000687296900003
DA 2025-01-10
ER

PT J
AU Caillouet, L
   Vidal, JP
   Sauquet, E
   Devers, A
   Lauvernet, C
   Graff, B
   Vannier, O
AF Caillouet, Laurie
   Vidal, Jean-Philippe
   Sauquet, Eric
   Devers, Alexandre
   Lauvernet, Claire
   Graff, Benjamin
   Vannier, Olivier
TI Inter-comparison of extreme low-flow events in France since 1871
SO LHB-HYDROSCIENCE JOURNAL
LA French
DT Article
DE Historical reanalysis; extreme low-flow events; spatio-temporal events
ID 20TH-CENTURY REANALYSIS; SENSITIVITY-ANALYSIS; RECONSTRUCTION; CLIMATE
AB The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work makes use of a daily 140-year ensemble streamflow reanalysis for a reference network of 661 near-natural catchments in France. This reanalysis, called FYRE Hydro, is based on (1) the high-resolution surface reanalysis FYRE Climate combining the outputs of a probabilistic downscaling of the Twentieth Century Reanalysis and historical observations from the Meteo-France database, (2) a continuous hydrological modelling using this reanalysis as forcings over the whole period and (3) a data assimilation scheme using all available historical streamflow observations.
   This work makes use of tools defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the Sequent Peak Algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the ensemble dataset to characterise in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over more than 140 years on the whole set of 661 catchments.
   Many different results can be derived from this work, allowing to better understand and characterise extreme low-flow events. Local severity, duration, dynamics or spatial extent are obtained for each station. The spatial characterisation provides a national outlook of such extreme events, with the region of incidence, the percentage of the territory affected, or the temporal evolution. Applied to the last 140 years, results highlight well-known events like 1949 or 1989-1990, but also older and relatively forgotten events like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes.
C1 [Caillouet, Laurie; Graff, Benjamin; Vannier, Olivier] Compagnie Natl Rhone, Lyon, France.
   [Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Lauvernet, Claire] INRAE, UR RiverLy, Villeurbanne, France.
C3 INRAE
RP Caillouet, L (corresponding author), Compagnie Natl Rhone, Lyon, France.
EM l.caillouet@cnr.tm.fr
RI Vidal, Jean-Philippe/E-6187-2010; Caillouet, Laurie/J-4465-2016; Devers,
   Alexandre/GOH-1395-2022; Devers, Alexandre/S-9216-2017
OI Sauquet, Eric/0000-0001-9539-7730; Devers, Alexandre/0000-0001-6708-0066
CR [Anonymous], TEMANORD
   Caillouet L, 2019, EARTH SYST SCI DATA, V11, P241, DOI 10.5194/essd-11-241-2019
   Caillouet L, 2017, HYDROL EARTH SYST SC, V21, P2923, DOI 10.5194/hess-21-2923-2017
   Caillouet L, 2016, CLIM PAST, V12, P635, DOI 10.5194/cp-12-635-2016
   Catalogne C, 2014, HOUILLE BLANCHE, P78, DOI 10.1051/lhb/2014042
   Chauveau M, 2013, HOUILLE BLANCHE, P5, DOI 10.1051/lhb/2013027
   Compo GP, 2011, Q J ROY METEOR SOC, V137, P1, DOI 10.1002/qj.776
   Devers A., 2019, THESIS U GRENOBE ALP
   Devers a, 2021, CLIMATE HIGH RESOLUT
   Devers A, 2020, Q J ROY METEOR SOC, V146, P153, DOI 10.1002/qj.3663
   Evensen G., 2003, Ocean Dynamics, V53, P343, DOI [10.1007/s10236-003-0036-9, DOI 10.1007/S10236-003-0036-9]
   Giuntoli I, 2013, J HYDROL, V482, P105, DOI [1, 10.1016/j.jhydrol.2012.12.038]
   Le Moigne P, 2020, GEOSCI MODEL DEV, V13, P3925, DOI 10.5194/gmd-13-3925-2020
   Pushpalatha R, 2011, J HYDROL, V411, P66, DOI 10.1016/j.jhydrol.2011.09.034
   Soubeyroux JM, 2010, HOUILLE BLANCHE, P30, DOI 10.1051/lhb/2010051
   Tallaksen L. M, 2004, DEV WATER SCI
   Valéry A, 2014, J HYDROL, V517, P1176, DOI 10.1016/j.jhydrol.2014.04.058
   Vidal JP, 2010, INT J CLIMATOL, V30, P1627, DOI 10.1002/joc.2003
NR 18
TC 2
Z9 2
U1 0
U2 4
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
EI 2767-8490
J9 LHB
JI LHB
PY 2021
VL 107
IS 1
AR 1914463
DI 10.1080/00186368.2021.1914463
PG 9
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA YU7BX
UT WOS:000752194900009
OA gold
DA 2025-01-10
ER

PT J
AU Won, J
   Choi, J
   Lee, O
   Kim, S
AF Won, Jeongeun
   Choi, Jeonghyeon
   Lee, Okjeong
   Kim, Sangdan
TI Copula-based Joint Drought Index using SPI and EDDI and its application
   to climate change
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Copula-based joint drought index; Partial duration
   series; Drought severity-duration-frequency curve
ID FREQUENCY-ANALYSIS; MULTIMODEL ASSESSMENT; FUTURE DROUGHT; SEVERITY;
   DURATION; EVAPOTRANSPIRATION; EVOLUTION; IMPACTS; CHINA; CO2
AB The drought index, which mainly focuses on the moisture supply side of the atmosphere, which has been mainly used in the field of drought monitoring, has limitations that cannot reflect drought caused by changes in various climate variables such as an increase in surface air temperature due to global warming. To overcome these limitations, various evaporation demand-based drought indices have been proposed, focusing on the aspect of atmospheric moisture demand. However, drought indices that consider only precipitation or the demand for atmospheric evaporation are difficult to comprehensively interpret drought caused by various climatic factors. The novelty of this study is to propose a new drought index to simultaneously monitor droughts occurring in terms of atmospheric moisture supply and demand. The proposed Copula-based Joint Drought Index (CJDI) combines the Standardized Precipitation Index and the Evaporative Demand Drought Index using copula. Since CJDI reflects the correlation between the two drought indices, it is shown that CIDI can better monitor Korea's past droughts than other drought indices. It is found that quantification of past drought using CJDI can be used to objectively recognize the level of drought currently in progress by combining with drought severity-duration-frequency curves derived from partial duration series. As a result of analyzing the future drought pattern in Korea, it was revealed that the drought would be alleviated by about 11% in the case of SPI and SPEI, but the drought would intensify by about 89% in the case of EDDI. In the case of CJDI, it is projected that the drought is likely to intensify to about 17%. From the perspective of better reproducing past droughts and projecting a more convincing future drought than other drought indices, CJDI is expected to be fully utilized as a drought index to monitor droughts and establish climate change adaptation policies. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Won, Jeongeun; Choi, Jeonghyeon] Pukyong Natl Univ, Div Earth Environm Syst Sci, Major Environm Engn, Busan 48513, South Korea.
   [Lee, Okjeong; Kim, Sangdan] Pukyong Natl Univ, Dept Environm Engn, Busan 48513, South Korea.
C3 Pukyong National University; Pukyong National University
RP Kim, S (corresponding author), Pukyong Natl Univ, Dept Environm Engn, Busan 48513, South Korea.
EM skim@pknu.ac.kr
OI Won, Jeongeun/0000-0001-8944-8642
FU National Research Foundation of Korea (NRF) - Korea government (MSIT)
   [NRF2019R1A2C1003114]
FX This work was supported by the National Research Foundation of Korea
   (NRF) grant funded by the Korea government (MSIT) (No.
   NRF2019R1A2C1003114).
CR Ahmadalipour A, 2019, SCI TOTAL ENVIRON, V662, P672, DOI 10.1016/j.scitotenv.2019.01.278
   Ahmadalipour A, 2017, THEOR APPL CLIMATOL, V128, P71, DOI 10.1007/s00704-015-1695-4
   Ainsworth EA, 2007, PLANT CELL ENVIRON, V30, P258, DOI 10.1111/j.1365-3040.2007.01641.x
   Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Ault TR, 2016, SCI ADV, V2, DOI 10.1126/sciadv.1600873
   Azam M, 2018, WATER-SUI, V10, DOI 10.3390/w10060765
   Beguería S, 2014, INT J CLIMATOL, V34, P3001, DOI 10.1002/joc.3887
   Cancelliere A, 2007, WATER RESOUR MANAG, V21, P801, DOI 10.1007/s11269-006-9062-y
   Cetin M., 2018, DERIVING ACCUMULATED, P39
   Chen L, 2013, J HYDROL ENG, V18, P797, DOI 10.1061/(ASCE)HE.1943-5584.0000697
   Choi J, 2019, INT J CLIMATOL, V39, P887, DOI 10.1002/joc.5850
   Christian JI, 2019, J HYDROMETEOROL, V20, P833, DOI 10.1175/JHM-D-18-0198.1
   Chun SiYoung Chun SiYoung, 2015, Journal of Korea Water Resources Association, V48, P969, DOI 10.3741/JKWRA.2015.48.12.969
   Ciais P, 2005, NATURE, V437, P529, DOI 10.1038/nature03972
   Cook Benjamin I., 2014, Climate Dynamics, V43, P2607, DOI 10.1007/s00382-014-2075-y
   Dalezios NR, 2000, HYDROLOG SCI J, V45, P751, DOI 10.1080/02626660009492375
   Dehghani M, 2019, HYDROL RES, V50, P1230, DOI 10.2166/nh.2019.051
   Dijkstra FA, 2010, FUNCT ECOL, V24, P1152, DOI 10.1111/j.1365-2435.2010.01717.x
   Ghosh S, 2007, WATER RESOUR RES, V43, DOI 10.1029/2006WR005351
   Hao ZC, 2015, J HYDROL, V527, P668, DOI 10.1016/j.jhydrol.2015.05.031
   Hao ZC, 2013, ADV WATER RESOUR, V57, P12, DOI 10.1016/j.advwatres.2013.03.009
   Heim RR, 2000, ROUTLEDGE HAZARDS DI, P159
   Hessl AE, 2018, SCI ADV, V4, DOI 10.1126/sciadv.1701832
   Hobbins MT, 2016, J HYDROMETEOROL, V17, P1745, DOI 10.1175/JHM-D-15-0121.1
   Jentsch A, 2007, FRONT ECOL ENVIRON, V5, P365, DOI 10.1890/1540-9295(2007)5[365:ANGOCE]2.0.CO;2
   Jeong Min su, 2020, Journal of Korea Water Resources Association, V53, P107
   Kang ShinUk Kang ShinUk, 2014, Journal of Korea Water Resources Association, V47, P813, DOI 10.3741/JKWRA.2014.47.9.813
   Kao SC, 2010, J HYDROL, V380, P121, DOI 10.1016/j.jhydrol.2009.10.029
   Karnauskas KB, 2016, NAT CLIM CHANGE, V6, P720, DOI [10.1038/NCLIMATE2987, 10.1038/nclimate2987]
   Katerji N, 2011, WATER RESOUR MANAG, V25, P1581, DOI 10.1007/s11269-010-9762-1
   Kempes CP, 2008, J ARID ENVIRON, V72, P350, DOI 10.1016/j.jaridenv.2007.07.009
   Kim CJ, 2014, INT J CLIMATOL, V34, P61, DOI 10.1002/joc.3666
   Kim G, 2021, ASIA-PAC J ATMOS SCI, V57, P119, DOI 10.1007/s13143-020-00180-8
   Kim JinYoung Kim JinYoung, 2016, Journal of Korea Water Resources Association, V49, P823
   Kim JS, 2020, INT J CLIMATOL, V40, P4528, DOI 10.1002/joc.6473
   Kim Jungho, 2016, [Journal of The Korean Society of Hazard Mitigation, 한국방재학회논문집], V16, P351
   Kim K, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11010022
   Kim SH, 2012, J POWER ELECTRON, V12, P223, DOI 10.6113/JPE.2012.12.1.223
   박명우, 2015, [Journal of The Korean Society of Hazard Mitigation, 한국방재학회논문집], V15, P347
   Kisi O, 2019, J HYDROL, V578, DOI 10.1016/j.jhydrol.2019.124053
   Kumar MN, 2009, METEOROL APPL, V16, P381, DOI 10.1002/met.136
   Kwon MinSung Kwon MinSung, 2018, Journal of Korea Water Resources Association, V51, P875, DOI 10.3741/JKWRA.2018.51.10.875
   Lee JH, 2013, HYDROL PROCESS, V27, P2800, DOI 10.1002/hyp.9390
   Lee JooHeon Lee JooHeon, 2011, Journal of Korea Water Resources Association, V44, P889, DOI 10.3741/JKWRA.2011.44.11.889
   Lee O, 2020, J HYDROL, V585, DOI 10.1016/j.jhydrol.2019.124318
   Lee TaeSam Lee TaeSam, 2016, Journal of Korea Water Resources Association, V49, P177
   Lehner B, 2006, CLIMATIC CHANGE, V75, P273, DOI 10.1007/s10584-006-6338-4
   Li X, 2019, CLIM DYNAM, V52, P2247, DOI 10.1007/s00382-018-4249-5
   Livada I, 2007, THEOR APPL CLIMATOL, V89, P143, DOI 10.1007/s00704-005-0227-z
   Mavromatis T, 2007, INT J CLIMATOL, V27, P911, DOI 10.1002/joc.1444
   McDowell NG, 2015, NAT CLIM CHANGE, V5, P669, DOI [10.1038/nclimate2641, 10.1038/NCLIMATE2641]
   McEvoy DJ, 2012, EARTH INTERACT, V16, DOI 10.1175/2012EI000447.1
   MCKEE TB, 1993, P 8 C APPL CLIM AN C
   McMahon TA, 2013, HYDROL EARTH SYST SC, V17, P1331, DOI 10.5194/hess-17-1331-2013
   Mehr AD, 2020, HYDROLOG SCI J, V65, P254, DOI 10.1080/02626667.2019.1691218
   Milly PCD, 2016, NAT CLIM CHANGE, V6, P946, DOI [10.1038/NCLIMATE3046, 10.1038/nclimate3046]
   Mirabbasi R, 2012, THEOR APPL CLIMATOL, V108, P191, DOI 10.1007/s00704-011-0524-7
   Mishra AK, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2008JD010986
   Mo KC, 2008, J HYDROMETEOROL, V9, P1212, DOI 10.1175/2008JHM1002.1
   Montaseri M, 2018, J HYDROL, V559, P166, DOI 10.1016/j.jhydrol.2018.02.018
   Moon Jang Won, 2012, [Journal of The Korean Society of Hazard Mitigation, 한국방재학회논문집], V12, P91
   Mortuza MR, 2019, THEOR APPL CLIMATOL, V135, P855, DOI 10.1007/s00704-018-2407-7
   Nabaei S, 2019, AGR FOREST METEOROL, V276, DOI 10.1016/j.agrformet.2019.06.010
   Nam WH, 2015, AGR WATER MANAGE, V160, P106, DOI 10.1016/j.agwat.2015.06.029
   Nelson RR, 2006, INTELLECTUAL PROPERTY RIGHTS: INNOVATION, GOVERNANCE AND THE INSTITUTIONAL ENVIRONMENT, P17
   Otkin JA, 2016, AGR FOREST METEOROL, V218, P230, DOI 10.1016/j.agrformet.2015.12.065
   Otkin JA, 2015, B AM METEOROL SOC, V96, P1073, DOI 10.1175/BAMS-D-14-00219.1
   Parente J, 2019, SCI TOTAL ENVIRON, V685, P150, DOI 10.1016/j.scitotenv.2019.05.298
   Park C, 2020, INT J CLIMATOL, V40, P2270, DOI 10.1002/joc.6331
   Querner EP, 2001, J HYDROL, V252, P51, DOI 10.1016/S0022-1694(01)00452-8
   Rahmat SN, 2015, AUSTRALAS J WAT RESO, V19, P31, DOI 10.7158/W14-019.2015.19.1
   Ramírez JA, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023549
   Reddy MJ, 2012, HYDROL PROCESS, V26, P1672, DOI 10.1002/hyp.8287
   Rossi G., 2002, Proc 2nd international conference "New trends in water and environmental engineering for safety and life: eco-compatible solutions for aquatic environments", P1
   Ryu JungSu Ryu JungSu, 2012, Journal of Korea Water Resources Association, V45, P1043, DOI 10.3741/JKWRA.2012.45.10.1043
   Saghafian B, 2003, HYDROLOGY OF MEDITERRANEAN AND SEMIARID REGIONS, V278, P305
   Salvadori G, 2015, J HYDROL, V526, P101, DOI 10.1016/j.jhydrol.2014.11.056
   Santos JF, 2011, WATER RESOUR MANAG, V25, P3537, DOI 10.1007/s11269-011-9869-z
   Sharafati A, 2020, J SOIL SEDIMENT, V20, P2977, DOI 10.1007/s11368-020-02632-0
   Sharafati A, 2020, THEOR APPL CLIMATOL, V139, P389, DOI 10.1007/s00704-019-02979-6
   Sharafati A, 2020, INT J CLIMATOL, V40, P1864, DOI 10.1002/joc.6307
   Shiau JT, 2006, WATER RESOUR MANAG, V20, P795, DOI 10.1007/s11269-005-9008-9
   Shiau JT, 2009, METEOROL APPL, V16, P481, DOI 10.1002/met.145
   Shiau JT, 2007, HYDROL PROCESS, V21, P2157, DOI 10.1002/hyp.6400
   Sim I, 2019, WATER-SUI, V11, DOI 10.3390/w11040771
   Sivakumar B, 2011, STOCH ENV RES RISK A, V25, P583, DOI 10.1007/s00477-010-0423-y
   Sklar A, 1959, Fonctions De repartition a n dimensions et leurs marges, V8, P229, DOI DOI 10.1007/978-3-642-33590-7
   Smakhtin VU, 2007, ENVIRON MODELL SOFTW, V22, P880, DOI 10.1016/j.envsoft.2006.05.013
   Sohn KyungHwan Sohn KyungHwan, 2014, Journal of Korea Water Resources Association, V47, P71, DOI 10.3741/JKWRA.2014.47.1.71
   Solomon S., 2007, Climate Change 2007The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC, V4
   Song JY, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab875f
   Song SB, 2010, STOCH ENV RES RISK A, V24, P425, DOI 10.1007/s00477-009-0331-1
   Sönmez FK, 2005, NAT HAZARDS, V35, P243, DOI 10.1007/s11069-004-5704-7
   Stall J., 1964, BULLETIN
   Sterl A, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034071
   Svoboda M, 2002, B AM METEOROL SOC, V83, P1181, DOI 10.1175/1520-0477(2002)083<1181:TDM>2.3.CO;2
   Swann ALS, 2016, P NATL ACAD SCI USA, V113, P10019, DOI 10.1073/pnas.1604581113
   Tang XS, 2015, STRUCT SAF, V52, P90, DOI 10.1016/j.strusafe.2014.09.007
   Taylor CM, 2012, NATURE, V489, P423, DOI 10.1038/nature11377
   Teuling AJ, 2013, GEOPHYS RES LETT, V40, P2071, DOI 10.1002/grl.50495
   Tirivarombo S, 2018, PHYS CHEM EARTH, V106, P1, DOI 10.1016/j.pce.2018.07.001
   van der Schrier G, 2013, J GEOPHYS RES-ATMOS, V118, P4025, DOI 10.1002/jgrd.50355
   Vazifehkhah S, 2019, J HYDROL ENG, V24, DOI 10.1061/(ASCE)HE.1943-5584.0001775
   VEIJALAINEN N, 2019, SUSTAINABILITY-BASEL, V11, DOI [DOI 10.3390/su11082450, DOI 10.3390/SU11082450]
   Vicente-Serrano SM, 2010, J HYDROMETEOROL, V11, P1033, DOI 10.1175/2010JHM1224.1
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Vidal JP, 2009, INT J CLIMATOL, V29, P2056, DOI 10.1002/joc.1843
   Wang F, 2020, J HYDROL, V585, DOI 10.1016/j.jhydrol.2020.124793
   Wang HJ, 2019, INT J CLIMATOL, V39, P4392, DOI 10.1002/joc.6081
   Wilhite DA, 2000, ROUTLEDGE HAZARDS DI, P149
   Wilks DS, 2015, Q J ROY METEOR SOC, V141, P945, DOI 10.1002/qj.2414
   Won J, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11050476
   Won Jeongeun, 2018, [Journal of The Korean Society of Hazard Mitigation, 한국방재학회논문집], V18, P431, DOI 10.9798/KOSHAM.2018.18.6.431
   Xia YL, 2014, J HYDROMETEOROL, V15, P1636, DOI 10.1175/JHM-D-13-058.1
   Xia YL, 2014, J GEOPHYS RES-ATMOS, V119, P2947, DOI 10.1002/2013JD020994
   Xiang KY, 2020, AGR WATER MANAGE, V232, DOI 10.1016/j.agwat.2020.106043
   Xu K, 2015, J HYDROL, V527, P630, DOI 10.1016/j.jhydrol.2015.05.030
   Yang HB, 2012, J HYDROL, V414, P184, DOI 10.1016/j.jhydrol.2011.10.043
   Yao N, 2018, SCI TOTAL ENVIRON, V616, P73, DOI 10.1016/j.scitotenv.2017.10.327
   Yoon Y., 1997, J KOREA WATER RESOUR, V30, P55
   Yu J.S., 2017, J KOREAN SOC CIV ENG, V37, P231, DOI [10.12652/Ksce.2017.37.1.0231, DOI 10.12652/KSCE.2017.37.1.0231]
   Yu JiSoo Yu JiSoo, 2016, Journal of Korea Water Resources Association, V49, P217
   Zhang BQ, 2016, AGR FOREST METEOROL, V230, P58, DOI 10.1016/j.agrformet.2015.11.015
NR 124
TC 94
Z9 97
U1 5
U2 114
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 20
PY 2020
VL 744
AR 140701
DI 10.1016/j.scitotenv.2020.140701
PG 16
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA NU3OA
UT WOS:000573550400003
PM 32755772
DA 2025-01-10
ER

PT J
AU Gebrechorkos, SH
   Bernhofer, C
   Hülsmann, S
AF Gebrechorkos, Solomon H.
   Bernhofer, Christian
   Huelsmann, Stephan
TI Climate change impact assessment on the hydrology of a large river basin
   in Ethiopia using a local-scale climate modelling approach
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate projection; SDSM; Climate change; Hydro-climate modelling;
   Impact assessment; Awash Basin
ID EASTERN AFRICA; GREATER HORN; PRECIPITATION; RAINFALL; WATER;
   TEMPERATURE; TRENDS; CALIBRATION; VALIDATION; PRODUCTS
AB Local-scale climate change adaptation is receiving more attention to reduce the adverse effects of climate change. The process of developing adaptation measures at local-scale (e.g., river basins) requires high-quality climate information with higher resolution. Climate projections are available at a coarser spatial resolution from Global Climate Models (GCMs) and require spatial downscaling and bias correction to drive hydrological models. We used the hybrid multiple linear regression and stochastic weather generator model (Statistical Down-Scaling Model, SDSM) to develop a location-based climate projection, equivalent to future station data, from GCMs. Meteorological data from 24 ground stations and the most accurate satellite and reanalysis products identified for the region, such as Climate Hazards Group InfraRed Precipitation with Station Data were used. The Soil Water Assessment Tool (SWAT) was used to assess the impacts of the projected climate on hydrology. Both SDSM and SWAT were calibrated and validated using the observed climate and streamflow data, respectively. Climate projection based on SDSM, in one of the large and agricultural intensive basins in Ethiopia (i.e., Awash), show high variability in precipitation but an increase in maximum (Tmax) and minimum (Tmin) temperature, which agrees with global warming. On average, the projection shows an increase in annual precipitation (>10%), Tmax (>0.4 degrees C), Trnin (>0.2 degrees C) and streamflow (>34%) in the 2020s (2011-2040), 2050s (2041-2070), and 2080s (2071-2100) under RCP2.6-RCP8.5. Although no significant trend in precipitation is found, streamflow during March-May and June-September is projected to increase throughout the 21 century by an average of more than 1.1% and 24%, respectively. However, streamflow is projected to decrease during January-February and October-November by more than 6%. Overall, considering the projected warming and changes in seasonal flow, local-scale adaptation measures to limit the impact on agriculture, water and energy sectors are required. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Gebrechorkos, Solomon H.] Univ Southampton, Sch Geog & Environm Sci, Southampton, Hants, England.
   [Gebrechorkos, Solomon H.; Huelsmann, Stephan] United Nat Univ, Inst Integrated Management Mat Fluxes & Resources, Dresden, Germany.
   [Bernhofer, Christian] Tech Univ Dresden, Fac Environm Sci, Inst Hydrol & Meteorol, Dresden, Germany.
   [Huelsmann, Stephan] Global Change Res Inst CAS, Brno 60300, Czech Republic.
C3 University of Southampton; Technische Universitat Dresden; Czech Academy
   of Sciences; Global Change Research Centre of the Czech Academy of
   Sciences
RP Gebrechorkos, SH (corresponding author), Univ Southampton, Sch Geog & Environm Sci, Southampton, Hants, England.
EM gebrechorkos@unu.edu
RI Hülsmann, Stephan/N-3889-2018; Gebrechorkos, Solomon/AAE-4977-2020;
   Hulsmann, Stephan/K-9146-2015
OI Gebrechorkos, Solomon Hailu/0000-0001-7498-0695; Hulsmann,
   Stephan/0000-0002-9569-7626; Bernhofer, Christian/0000-0003-1061-3073
CR Abbaspour K., 2015, SWAT-CUP: SWAT Calibration and Uncertainty Programs, P100, DOI DOI 10.1007/S00402-009-1032-4
   Adhikari U, 2015, FOOD ENERGY SECUR, V4, P110, DOI 10.1002/fes3.61
   Alazzy AA, 2017, ADV METEOROL, V2017, DOI 10.1155/2017/3695285
   Almeida RA, 2018, ENG AGR-JABOTICABAL, V38, P55, DOI [10.1590/1809-4430-Eng.Agric.v38n1p55-63/2018, 10.1590/1809-4430-eng.agric.v38n1p55-63/2018]
   [Anonymous], 2005, Encyclopedia of Hydrological Sciences, DOI 10.1002/0470848944.hsa140
   [Anonymous], 2014, The State of Food Insecurity in the World 2014.Strengthening the enabling environment for food security and nutrition
   Ayenew T, 2008, HYDROL PROCESS, V22, P1548, DOI 10.1002/hyp.6716
   Ayugi B, 2019, ATMOS RES, V225, P96, DOI 10.1016/j.atmosres.2019.03.032
   Bárdossy A, 2007, HYDROL EARTH SYST SC, V11, P703, DOI 10.5194/hess-11-703-2007
   Basheer M, 2019, ATMOS RES, V215, P128, DOI 10.1016/j.atmosres.2018.08.028
   Behera S., 2016, APPL STAT DOWNSCALIN
   Berhe FT, 2013, CATENA, V109, P118, DOI 10.1016/j.catena.2013.04.007
   Borgomeo E, 2018, ECOL ECON, V146, P621, DOI 10.1016/j.ecolecon.2017.11.038
   Bosch NS, 2011, J GREAT LAKES RES, V37, P263, DOI 10.1016/j.jglr.2011.03.004
   Brown ME, 2008, SCIENCE, V319, P580, DOI 10.1126/science.1154102
   Camberlin P, 2017, CLIM DYNAM, V48, P477, DOI 10.1007/s00382-016-3088-5
   Cattani E, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10060931
   Chan W.C.H., 2020, HYDROLOG SCI J, DOI [10.1080/02626667.2020.1767782null, DOI 10.1080/02626667.2020.1767782NULL]
   Chaney NW, 2014, J CLIMATE, V27, P5815, DOI 10.1175/JCLI-D-13-00423.1
   Coulibaly P, 2005, J HYDROMETEOROL, V6, P483, DOI 10.1175/JHM409.1
   Dile YT, 2014, J AM WATER RESOUR AS, V50, P1226, DOI 10.1111/jawr.12182
   Engelbrecht F, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/085004
   Fenta AA, 2017, HYDROL PROCESS, V31, P4555, DOI 10.1002/hyp.11378
   Fernandez G.P., 2005, DEV TESTING WATERSHE
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fischer G., 2008, Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008), P10
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1543, DOI 10.1002/joc.1616
   Fuka DR, 2014, HYDROL PROCESS, V28, P5613, DOI 10.1002/hyp.10073
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Gebrechorkos SH, 2019, SCI TOTAL ENVIRON, V682, P160, DOI 10.1016/j.scitotenv.2019.05.053
   Gebrechorkos SH, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab055a
   Gebrechorkos SH, 2019, SCI DATA, V6, DOI 10.1038/s41597-019-0038-1
   Gebrechorkos SH, 2019, INT J CLIMATOL, V39, P18, DOI 10.1002/joc.5777
   Gebrechorkos SH, 2018, HYDROL EARTH SYST SC, V22, P4547, DOI 10.5194/hess-22-4547-2018
   Gessesse AA, 2019, WATER CONSERV SCI EN, V4, P201, DOI 10.1007/s41101-019-00076-3
   Girvetz E., 2019, The Climate-Smart Agriculture Papers, P15, DOI [DOI 10.1007/978-3-319-92798-5_2, 10.1007/978-3-319-92798-5_2]
   Goodess CM., 2012, An intercomparison of statistical downscaling methods for Europe and European regions - assessing their performance with respect to extreme temperature and precipitation events
   Guo YX, 2020, SCI TOTAL ENVIRON, V710, DOI 10.1016/j.scitotenv.2019.136275
   Gutmann ED, 2012, J CLIMATE, V25, P262, DOI 10.1175/2011JCLI4109.1
   Haile GG, 2020, SCI TOTAL ENVIRON, V704, DOI 10.1016/j.scitotenv.2019.135299
   Hashmi MZ, 2011, STOCH ENV RES RISK A, V25, P475, DOI 10.1007/s00477-010-0416-x
   Hassan Z, 2014, THEOR APPL CLIMATOL, V116, P243, DOI 10.1007/s00704-013-0951-8
   Hirpa FA, 2019, CLIMATIC CHANGE, V156, P341, DOI 10.1007/s10584-019-02547-x
   Hirpa FA, 2010, J APPL METEOROL CLIM, V49, P1044, DOI 10.1175/2009JAMC2298.1
   Jiang DJ, 2019, WATER-SUI, V11, DOI 10.3390/w11081615
   Joetzjer E, 2013, CLIM DYNAM, V41, P2921, DOI 10.1007/s00382-012-1644-1
   Khan MS, 2010, J HYDROMETEOROL, V11, P482, DOI 10.1175/2009JHM1160.1
   Liu JM, 2016, ADV METEOROL, V2016, DOI 10.1155/2016/7463963
   Liu ZF, 2011, INT J CLIMATOL, V31, P2006, DOI 10.1002/joc.2211
   Luo YZ, 2013, SCI TOTAL ENVIRON, V450, P72, DOI 10.1016/j.scitotenv.2013.02.004
   Lutz AF, 2016, INT J CLIMATOL, V36, P3988, DOI 10.1002/joc.4608
   Ma J, 2018, IEEE ACCESS, V6, P9006, DOI 10.1109/ACCESS.2018.2810252
   Mejia J.F., 2012, J CONT WATER RES ED, P17
   Mersha AN, 2018, WATER-SUI, V10, DOI 10.3390/w10070892
   Motovilov YG, 1999, AGR FOREST METEOROL, V98-9, P257, DOI 10.1016/S0168-1923(99)00102-1
   Mulugeta S, 2019, WATER-SUI, V11, DOI 10.3390/w11071498
   Murendo C, 2011, RISK MANAG-UK, V13, P247, DOI 10.1057/rm.2011.17
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Neitsch S.L., 2011, Technical Report
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Osima S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaba1b
   Schnorbus MA, 2014, WATER RESOUR RES, V50, P8907, DOI 10.1002/2014WR015279
   Sheffield J, 2006, J CLIMATE, V19, P3088, DOI 10.1175/JCLI3790.1
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P1
   Stocker, 2013, Climate Change 2013. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
   Tadese MT, 2020, INT J CLIMATOL, V40, P3649, DOI 10.1002/joc.6418
   Tan ML, 2014, IOP C SER EARTH ENV, V18, DOI 10.1088/1755-1315/18/1/012060
   Tavakol-Davani H, 2013, INT J CLIMATOL, V33, P2561, DOI 10.1002/joc.3611
   Taye MT, 2018, WATER-SUI, V10, DOI 10.3390/w10111560
   Tryhorn L, 2011, INT J CLIMATOL, V31, P1975, DOI 10.1002/joc.2208
   Wang YQ, 2019, ADV METEOROL, V2019, DOI 10.1155/2019/1545746
   Wilby RL, 2013, HYDROL EARTH SYST SC, V17, P3937, DOI 10.5194/hess-17-3937-2013
   Wilby RL, 2013, INT J CLIMATOL, V33, P1707, DOI 10.1002/joc.3544
   Wilby R. L., 2002, Environmental Modelling & Software, V17, P147, DOI 10.1016/S1364-8152(01)00060-3
   Wu PL, 2013, NAT CLIM CHANGE, V3, P807, DOI [10.1038/NCLIMATE1932, 10.1038/nclimate1932]
   Yanto, 2017, J HYDROL-REG STUD, V9, P127, DOI 10.1016/j.ejrh.2016.09.007
NR 76
TC 58
Z9 59
U1 2
U2 239
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD NOV 10
PY 2020
VL 742
AR 140504
DI 10.1016/j.scitotenv.2020.140504
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA NO3WN
UT WOS:000569416600015
PM 32623168
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Rocha, J
   Carvalho-Santos, C
   Diogo, P
   Beça, P
   Keizer, JJ
   Nunes, JP
AF Rocha, Joao
   Carvalho-Santos, Claudia
   Diogo, Paulo
   Beca, Pedro
   Keizer, Jan Jacob
   Nunes, Joao Pedro
TI Impacts of climate change on reservoir water availability, quality and
   irrigation needs in a water scarce Mediterranean region (southern
   Portugal)
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Water availability; Climate change; SWAT modelling; WEI - Water
   exploitation index; Alentejo multipurpose reservoirs
ID LAND-USE CHANGES; FUTURE CLIMATE; CHANGE PROJECTIONS; PHOSPHORUS LOSS;
   RESOURCES; MODEL; RIVER; SOIL; MANAGEMENT; UNCERTAINTY
AB Future climate for the Mediterranean climatic region is expected to bring an increase in temperatures, decrease in the precipitation quantity and shifts in the seasonal precipitation pattern. Although the impacts of climate change on water resources have been relatively well explored for the Mediterranean climatic region, the specific consequences for reservoirs and, in particular, water availability and irrigation issues have been less studied. The objective of this work is two-fold: (i) to assess the impacts of future climate changes on water resources availability, quality (focusing on phosphorus loads as this is the limiting nutrient for eutrophication) and irrigation needs for two multipurpose reservoirs in southern Portugal; (ii) to suggest climate change adaptation strategies, especially for the agricultural sector. To this end, the SWAT model was first calibrated against existing data on reservoir inflows as well as phosphorus loads. Then, SWAT was run with climate derived EURO-CORDEX models (RCA4/RACMO22E) for four periods (1970-2000, 2010-2040, 2040-2070 and 2070-2100). Water availability was analysed using the Water Exploitation Index (WEI) that was calculated for both reservoirs combining changes of inflows and irrigation requirements. The results indicated that climate change will negatively impact water availability in both reservoirs, especially under RCP8.5. In the case of the Monte Novo reservoir, future domestic water supply could be constrained by water quality problems related with phosphorus loads. For Vigia reservoir, the high water exploitation will lead to water scarcity problems, mainly as this reservoir on presentday conditions is restrictive on irrigation requirements. Adaptation strategies such as the implementation of high end technology (e.g. soil moisture and plant water stress probes, satellite imagery and drones to evaluate water stress - NDVI) as well as the renewal of the irrigation network and adequate crop selection can help attenuating the effects of climate change on the water resources in this region. (c) 2020 Elsevier B.V. All rights reserved.
C1 [Rocha, Joao; Carvalho-Santos, Claudia; Keizer, Jan Jacob; Nunes, Joao Pedro] Univ Aveiro, Dept Environm & Planning DAO, Ctr Environm & Marine Studies CESAM, P-3810193 Aveiro, Portugal.
   [Carvalho-Santos, Claudia] Univ Minho, CBMA Ctr Mol & Environm Biol, Braga, Portugal.
   [Diogo, Paulo; Beca, Pedro] Univ Nova Lisboa, Fac Sci & Technol, Dept Environm Sci, MARE NOVA Marine & Environm Sci Ctr, P-2829516 Caparica, Portugal.
   [Nunes, Joao Pedro] Univ Lisbon, Fac Sci, Ctr Ecol Evolut & Environm Changes CE3C, P-1749016 Lisbon, Portugal.
C3 Universidade de Aveiro; Universidade do Minho; Universidade Nova de
   Lisboa; Universidade de Lisboa
RP Rocha, J (corresponding author), Univ Aveiro, Dept Environm & Planning DAO, Ctr Environm & Marine Studies CESAM, P-3810193 Aveiro, Portugal.
EM joaocrocha@ua.pt; c.carvalho.santos@bio.uminho.pt; pad@fct.unl.pt;
   pmfb@fct.unl.pt; jjkeizer@ua.pt; jpcnunes@fc.ul.pt
RI Nunes, João/AAB-2128-2020; Diogo, Paulo/O-5353-2015; Beça,
   Pedro/ABD-2549-2020; Carvalho-Santos, Claudia/G-6530-2011; Keizer, Jan
   Jacob/E-8938-2015; Nunes, Joao Pedro/A-5497-2011
OI rocha, joao/0000-0001-9168-5559; Beca, Pedro/0000-0003-3821-0807;
   Carvalho-Santos, Claudia/0000-0003-1841-209X; Keizer, Jan
   Jacob/0000-0003-4833-0415; Nunes, Joao Pedro/0000-0002-0164-249X;
   Marques Diogo, Paulo Alexandre/0000-0003-4592-0110
FU Foundation for Science and Technology (FCT, Portugal) [IF/00586/2015,
   IF/01465/2015]
FX This study has been developed within the context of the project
   GestAqua.AdaPT under the Financial Mechanism of the European Economic
   Area (EEA FM/EEA-Grants), operated by the Portuguese Environment Agency
   as manager of the Portuguese Carbon Fund. JP Nunes and JJ Keizer were
   also funded by the Foundation for Science and Technology (FCT, Portugal)
   under grants IF/00586/2015 and IF/01465/2015, respectively,
CR Abbaspour K., 2015, SWAT CUP SWAT CALIBR, DOI DOI 10.1007/S00402-009-1032-4
   Abbaspour KC, 2015, J HYDROL, V524, P733, DOI 10.1016/j.jhydrol.2015.03.027
   Abbaspour KC, 2007, MODSIM 2007: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION, P1603
   [Anonymous], 2005, EUR ENV STAT OUTL
   [Anonymous], 2013, SWAT-CUP 2012. SWAT Calibration and Uncertainty Program-A User Manual
   Arias R, 2014, WATER-SUI, V6, P3049, DOI 10.3390/w6103049
   Arnold JG, 2012, T ASABE, V55, P1491
   Bucak T, 2017, SCI TOTAL ENVIRON, V581, P413, DOI [10.1016/jscitotenv2016.12.149, 10.1016/j.scitotenv.2016.12.149]
   Butcher JB, 2014, J HYDROL, V513, P322, DOI 10.1016/j.jhydrol.2014.03.073
   Caetano M., 2009, Accuracy assessment of the CORINE Land Cover 2006 map of Continental Portugal
   Carvalho-Santos C, 2017, WATER RESOUR MANAG, V31, P3355, DOI 10.1007/s11269-017-1672-z
   Carvalho-Santos C, 2016, HYDROL PROCESS, V30, P720, DOI 10.1002/hyp.10621
   cerkasova N, 2018, ECOL ENG, V124, P99, DOI 10.1016/j.ecoleng.2018.09.025
   Chaubey I., 2006, Modeling Phosphorus in the Environment, P163, DOI DOI 10.1201/9781420005417.SEC2
   Chavez-Jimenez A, 2015, WATER RESOUR MANAG, V29, P1413, DOI 10.1007/s11269-014-0882-x
   Collick AS, 2016, J ENVIRON QUAL, V45, P1215, DOI 10.2134/jeq2015.03.0135
   Di Luzio M., 2001, SOIL ANDWATER ASSESS
   Dietrich J, 2009, PHYS CHEM EARTH, V34, P580, DOI 10.1016/j.pce.2008.11.001
   Diogo PA, 2008, DESALINATION, V226, P200, DOI 10.1016/j.desal.2007.01.242
   Diogo P.A., 2012, THESIS
   Diogo PAM, 2008, THESIS
   El-Khoury A, 2015, J ENVIRON MANAGE, V151, P76, DOI 10.1016/j.jenvman.2014.12.012
   Francés GE, 2017, ENVIRON SCI POLICY, V69, P1, DOI 10.1016/j.envsci.2016.12.006
   Estrela T, 2012, HYDROLOG SCI J, V57, P1154, DOI 10.1080/02626667.2012.702213
   Fader M, 2016, HYDROL EARTH SYST SC, V20, P953, DOI 10.5194/hess-20-953-2016
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Gabriel M, 2016, HYDROL PROCESS, V30, P1403, DOI 10.1002/hyp.10707
   García-Ruiz JM, 2011, EARTH-SCI REV, V105, P121, DOI 10.1016/j.earscirev.2011.01.006
   Garrote L, 2015, WATER RESOUR MANAG, V29, P325, DOI 10.1007/s11269-014-0736-6
   Giorgi F, 2008, GLOBAL PLANET CHANGE, V63, P90, DOI 10.1016/j.gloplacha.2007.09.005
   Gray SB, 2016, DEV BIOL, V419, P64, DOI 10.1016/j.ydbio.2016.07.023
   Gupta HV, 1999, J HYDROL ENG, V4, P135, DOI 10.1061/(ASCE)1084-0699(1999)4:2(135)
   Iglesias A, 2015, AGR WATER MANAGE, V155, P113, DOI 10.1016/j.agwat.2015.03.014
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Koppen W., 1931, GRUNDRISSE KLIMAKUND
   Krause P., 2005, ADV GEOSCIENCES, V5, P89, DOI DOI 10.5194/ADGEO-5-89-2005
   La Jeunesse I, 2016, SCI TOTAL ENVIRON, V543, P981, DOI 10.1016/j.scitotenv.2015.04.062
   Levidow L, 2014, AGR WATER MANAGE, V146, P84, DOI 10.1016/j.agwat.2014.07.012
   Lobanova A, 2017, J HYDROL, V548, P436, DOI 10.1016/j.jhydrol.2017.03.015
   López-Moreno JI, 2014, SCI TOTAL ENVIRON, V493, P1222, DOI 10.1016/j.scitotenv.2013.09.031
   Ludwig R, 2010, FRESEN ENVIRON BULL, V19, P2379
   Lutz SR, 2016, SCI TOTAL ENVIRON, V571, P1392, DOI 10.1016/j.scitotenv.2016.07.102
   Majone B, 2016, SCI TOTAL ENVIRON, V543, P965, DOI 10.1016/j.scitotenv.2015.05.009
   Mehdi B, 2015, J HYDROL-REG STUD, V4, P60, DOI 10.1016/j.ejrh.2015.04.009
   Milano M, 2013, HYDROLOG SCI J, V58, P498, DOI 10.1080/02626667.2013.774458
   Molina-Navarro E, 2014, J HYDROL, V509, P354, DOI 10.1016/j.jhydrol.2013.11.053
   Morais J, 1959, MEMORIAS NOTICIAS PU, P27
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Neitsch S.L, 2011, SOIL ANDWATER ASSESS
   Nunes JP, 2013, CATENA, V102, P27, DOI 10.1016/j.catena.2011.04.001
   Nunes JP, 2008, HYDROL PROCESS, V22, P3115, DOI 10.1002/hyp.6897
   Nunes JP, 2017, SCI TOTAL ENVIRON, V584, P219, DOI 10.1016/j.scitotenv.2017.01.131
   Pedro-Monzonís M, 2015, J HYDROL, V527, P482, DOI 10.1016/j.jhydrol.2015.05.003
   Prosdocimi M, 2016, SCI TOTAL ENVIRON, V547, P323, DOI 10.1016/j.scitotenv.2015.12.076
   Reis R.M. M., 1987, Caracterizacao Climatica da regiao agricola do Alentejo
   Rocha J, 2015, SCI TOTAL ENVIRON, V536, P48, DOI 10.1016/j.scitotenv.2015.07.038
   Rolim J, 2017, IRRIG DRAIN, V66, P3, DOI 10.1002/ird.1996
   Sánchez E, 2004, GLOBAL PLANET CHANGE, V44, P163, DOI 10.1016/j.gloplacha.2004.06.010
   Sellami H., 2015, HYDROLOG SCI J, V8
   Sellami H, 2016, SCI TOTAL ENVIRON, V543, P924, DOI 10.1016/j.scitotenv.2015.07.006
   Senatore A, 2011, J HYDROL, V399, P70, DOI 10.1016/j.jhydrol.2010.12.035
   Serpa D, 2015, SCI TOTAL ENVIRON, V538, P64, DOI 10.1016/j.scitotenv.2015.08.033
   Soares PMM, 2015, CLIM DYNAM, V45, P1771, DOI 10.1007/s00382-014-2432-x
   Stefanidis K, 2018, SCI TOTAL ENVIRON, V627, P756, DOI 10.1016/j.scitotenv.2018.01.282
   Teshager AD, 2016, HYDROL EARTH SYST SC, V20, P3325, DOI 10.5194/hess-20-3325-2016
   Thomson AM, 2011, CLIMATIC CHANGE, V109, P77, DOI 10.1007/s10584-011-0151-4
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   Vadas PA, 2010, T ASABE, V53, P1469
   Vadas PA, 2012, J ENVIRON QUAL, V41, P1750, DOI 10.2134/jeq2012.0003
   Valverde P, 2015, AGR WATER MANAGE, V152, P17, DOI 10.1016/j.agwat.2014.12.012
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P95, DOI 10.1007/s10584-011-0152-3
   White MJ, 2014, J ENVIRON QUAL, V43, P215, DOI 10.2134/jeq2011.0348
   White MJ, 2010, ENVIRON MODELL SOFTW, V25, P1121, DOI 10.1016/j.envsoft.2010.03.017
   Whitehead PG, 2009, HYDROLOG SCI J, V54, P101, DOI 10.1623/hysj.54.1.101
   Wilby RL, 2006, ENVIRON INT, V32, P1043, DOI 10.1016/j.envint.2006.06.017
NR 75
TC 95
Z9 96
U1 9
U2 83
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD SEP 20
PY 2020
VL 736
AR 139477
DI 10.1016/j.scitotenv.2020.139477
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA MA7IY
UT WOS:000542087400018
PM 32485369
OA Green Published
DA 2025-01-10
ER

PT J
AU Bourgault, M
   Webber, HA
   Chenu, K
   O'Leary, GJ
   Gaiser, T
   Siebert, S
   Dreccer, F
   Huth, N
   Fitzgerald, GJ
   Tausz, M
   Ewert, F
AF Bourgault, Maryse
   Webber, Heidi A.
   Chenu, Karine
   O'Leary, Garry J.
   Gaiser, Thomas
   Siebert, Stefan
   Dreccer, Fernanda
   Huth, Neil
   Fitzgerald, Glenn J.
   Tausz, Michael
   Ewert, Frank
TI Early vigour in wheat: Could it lead to more severe terminal drought
   stress under elevated atmospheric [CO<sub>2</sub>] and semi-arid
   conditions?
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE climate change adaptation; drought adaptive traits; model
   intercomparison; physiological pre-breeding; Triticum aestivum
ID TRANSPIRATION EFFICIENCY; GENETIC-IMPROVEMENT; RICE GENOTYPES;
   CLIMATE-CHANGE; HEAT-STRESS; HAYING-OFF; YIELD; GROWTH; NITROGEN; CARBON
AB Early vigour in wheat is a trait that has received attention for its benefits reducing evaporation from the soil surface early in the season. However, with the growth enhancement common to crops grown under elevated atmospheric CO2 concentrations (e[CO2]), there is a risk that too much early growth might deplete soil water and lead to more severe terminal drought stress in environments where production relies on stored soil water content. If this is the case, the incorporation of such a trait in wheat breeding programmes might have unintended negative consequences in the future, especially in dry years. We used selected data from cultivars with proven expression of high and low early vigour from the Australian Grains Free Air CO2 Enrichment (AGFACE) facility, and complemented this analysis with simulation results from two crop growth models which differ in the modelling of leaf area development and crop water use. Grain yield responses to e[CO2] were lower in the high early vigour group compared to the low early vigour group, and although these differences were not significant, they were corroborated by simulation model results. However, the simulated lower response with high early vigour lines was not caused by an earlier or greater depletion of soil water under e[CO2] and the mechanisms responsible appear to be related to an earlier saturation of the radiation intercepted. Whether this is the case in the field needs to be further investigated. In addition, there was some evidence that the timing of the drought stress during crop growth influenced the effect of e[CO2] regardless of the early vigour trait. There is a need for FACE investigations of the value of traits for drought adaptation to be conducted under more severe drought conditions and variable timing of drought stress, a risky but necessary endeavour.
C1 [Bourgault, Maryse] Montana State Univ, Northern Agr Res Ctr, Havre, MT USA.
   [Bourgault, Maryse; Fitzgerald, Glenn J.] Univ Melbourne, Fac Vet & Agr Sci, Creswick, Vic, Australia.
   [Webber, Heidi A.; Gaiser, Thomas; Siebert, Stefan; Ewert, Frank] Univ Bonn, Inst Crop Sci & Resource Conservat INRES, Bonn, Germany.
   [Webber, Heidi A.; Ewert, Frank] Leibniz Ctr Agr Landscape Res ZALF, Brandenburg, Germany.
   [Chenu, Karine] Univ Queensland, Queensland Alliance Agr & Food Innovat QAAFI, Toowoomba, Qld, Australia.
   [O'Leary, Garry J.; Fitzgerald, Glenn J.] Grains Innovat Pk, Agr Victoria, Horsham, Vic, Australia.
   [Siebert, Stefan] Univ Gottingen, Dept Crop Sci, Gottingen, Germany.
   [Dreccer, Fernanda] Univ Queensland, Agr & Food Cooper Lab, CSIRO, Gatton, Qld, Australia.
   [Huth, Neil] CSIRO Agr & Food, Toowoomba, Qld, Australia.
   [Tausz, Michael] CQ Univ, Dept Agr Sci & Environm, Norman Gardens, Qld, Australia.
   [Bourgault, Maryse] Univ Saskatchewan, Coll Agr & Bioresources, 51 Campus Dr, Saskatoon, SK S7N 5A0, Canada.
C3 Montana State University System; Montana State University Bozeman;
   Montana State University Northern; University of Melbourne; University
   of Bonn; Leibniz Association; Leibniz Zentrum fur
   Agrarlandschaftsforschung (ZALF); University of Queensland; Agriculture
   Victoria; University of Gottingen; University of Queensland;
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Central Queensland University; University of Saskatchewan
RP Bourgault, M (corresponding author), Univ Saskatchewan, Coll Agr & Bioresources, 51 Campus Dr, Saskatoon, SK S7N 5A0, Canada.
EM maryse.bourgault@usask.ca
RI Huth, Neil/F-7882-2010; Bourgault, Maryse/D-4416-2009; Tausz,
   Michael/AHC-9128-2022; Dreccer, Maria Fernanda/F-2150-2010; Gaiser,
   Thomas/AAD-6326-2021; Ewert, Frank/AER-0007-2022; Siebert,
   Stefan/B-8621-2009; Chenu, Karine/A-8967-2009; Tausz,
   Michael/C-1990-2013
OI Dreccer, Maria Fernanda/0000-0003-3528-9580; Siebert,
   Stefan/0000-0002-9998-0672; Ewert, Frank/0000-0002-4392-8154; Webber,
   Heidi/0000-0001-8301-5424; Chenu, Karine/0000-0001-7273-2057; Bourgault,
   Maryse/0000-0001-7756-7353; Fitzgerald, Glenn/0000-0001-6972-4443;
   Tausz, Michael/0000-0001-8205-8561; Gaiser, Thomas/0000-0002-5820-2364
FU Australian Commonwealth Department of Agriculture and Water Resources;
   Grains Research and Development Corporation
FX Australian Commonwealth Department of Agriculture and Water Resources;
   Grains Research and Development Corporation
CR ADDISCOTT TM, 1991, SOIL USE MANAGE, V7, P94, DOI 10.1111/j.1475-2743.1991.tb00856.x
   Ainsworth EA, 2008, PLANT CELL ENVIRON, V31, P1317, DOI 10.1111/j.1365-3040.2008.01841.x
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Boote KJ, 2006, CROP SCI, V46, P2270, DOI 10.2135/cropsci2006.01.0039gas
   Bourgault M, 2017, EUR J AGRON, V87, P50, DOI 10.1016/j.eja.2017.05.003
   Bourgault M, 2013, FUNCT PLANT BIOL, V40, P172, DOI 10.1071/FP12193
   *BUR MET, 2016, DAT CLIM
   BUTLER DG, 2009, MIXED MODELS S LANGU, P149
   Chenu K, 2013, NEW PHYTOL, V198, P801, DOI 10.1111/nph.12192
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fischer RA, 2011, CROP PASTURE SCI, V62, P95, DOI 10.1071/CP10344
   Fitzgerald GJ, 2016, GLOBAL CHANGE BIOL, V22, P2269, DOI 10.1111/gcb.13263
   Gabaldón-Leal C, 2016, FIELD CROP RES, V198, P226, DOI 10.1016/j.fcr.2016.08.013
   Gaiser T, 2013, ECOL MODEL, V256, P6, DOI 10.1016/j.ecolmodel.2013.02.016
   GIFFORD RM, 1979, AUST J PLANT PHYSIOL, V6, P367, DOI 10.1071/PP9790367
   Gray SB, 2016, NAT PLANTS, V2, DOI [10.1038/nplants.2016.132, 10.1038/NPLANTS.2016.132]
   Holzworth DP, 2014, ENVIRON MODELL SOFTW, V62, P327, DOI 10.1016/j.envsoft.2014.07.009
   Houshmandfar A, 2015, J PLANT PHYSIOL, V174, P157, DOI 10.1016/j.jplph.2014.10.008
   Kimball BA, 2016, CURR OPIN PLANT BIOL, V31, P36, DOI 10.1016/j.pbi.2016.03.006
   KOENKER R, 2017, PACKAGE QUANTREG QUA
   Leakey ADB, 2009, J EXP BOT, V60, P2859, DOI 10.1093/jxb/erp096
   Mitchell JH, 2012, CROP PASTURE SCI, V63, P128, DOI 10.1071/CP11260
   Mollah M, 2009, CROP PASTURE SCI, V60, P697, DOI 10.1071/CP08354
   MONTEITH JL, 1986, EXP AGR, V22, P329, DOI 10.1017/S0014479700014575
   Nie M, 2013, GLOBAL ECOL BIOGEOGR, V22, P1095, DOI 10.1111/geb.12062
   Nuttall JG, 2012, CROP PASTURE SCI, V63, P593, DOI 10.1071/CP12062
   O'Leary GJ, 2015, GLOBAL CHANGE BIOL, V21, P2670, DOI 10.1111/gcb.12830
   Palta JA, 2011, FUNCT PLANT BIOL, V38, P347, DOI 10.1071/FP11031
   Pandey R, 2018, PLANT CELL REP, V37, P1231, DOI 10.1007/s00299-018-2307-4
   Pang JY, 2014, FUNCT PLANT BIOL, V41, P215, DOI 10.1071/FP13143
   R Core Team, 2017, R LANG ENV STAT COMP
   Rebetzke GJ, 2004, FIELD CROP RES, V88, P179, DOI 10.1016/j.fcr.2004.01.007
   Rebetzke GJ, 1999, AUST J AGR RES, V50, P291, DOI 10.1071/A98125
   Rebetzke GJ, 2014, FUNCT PLANT BIOL, V41, P107, DOI 10.1071/FP13177
   Reyenga PJ, 1999, ENVIRON MODELL SOFTW, V14, P297, DOI 10.1016/S1364-8152(98)00081-4
   Schorr Martin, 2012, Libellula, P5
   Setiyono TD, 2008, FIELD CROP RES, V108, P82, DOI 10.1016/j.fcr.2008.03.005
   Shimono H, 2019, FUNCT PLANT BIOL, V46, P1, DOI [10.1071/FP18087, 10.1071/fp18087]
   Shimono H, 2014, PHYSIOL PLANTARUM, V152, P520, DOI 10.1111/ppl.12202
   Shimono H, 2011, AGR ECOSYST ENVIRON, V141, P240, DOI 10.1016/j.agee.2011.02.028
   Smith AB, 2005, J AGR SCI-CAMBRIDGE, V143, P449, DOI 10.1017/S0021859605005587
   Tanner C. B., 1983, Limitations to efficient water use in crop production, P1
   Tardieu F, 1999, NEW PHYTOL, V143, P33, DOI 10.1046/j.1469-8137.1999.00433.x
   Tausz M, 2013, ENVIRON EXP BOT, V88, P71, DOI 10.1016/j.envexpbot.2011.12.005
   Tausz-Posch S, 2020, PLANT BIOLOGY, V22, P38, DOI 10.1111/plb.12994
   Tausz-Posch S., 2013, Physiologia Plantarum, V148, P232, DOI 10.1111/j.1399-3054.2012.01701.x
   Tausz-Posch S, 2015, EUR J AGRON, V64, P21, DOI 10.1016/j.eja.2014.12.009
   Tausz-Posch S, 2012, FIELD CROP RES, V133, P160, DOI 10.1016/j.fcr.2012.04.007
   van der Kooi CJ, 2016, ENVIRON EXP BOT, V122, P150, DOI 10.1016/j.envexpbot.2015.10.004
   van Herwaarden AF, 1998, AUST J AGR RES, V49, P1067, DOI 10.1071/A97039
   Webber H, 2016, ENVIRON MODELL SOFTW, V77, P143, DOI 10.1016/j.envsoft.2015.12.003
   Wilson PB, 2015, FUNCT PLANT BIOL, V42, P1107, DOI 10.1071/FP15228
   ZADOKS JC, 1974, WEED RES, V14, P415, DOI 10.1111/j.1365-3180.1974.tb01084.x
   Zhao G, 2015, GLOBAL CHANGE BIOL, V21, P4031, DOI 10.1111/gcb.13008
   Zheng B., 2015, APSIM WHEAT MODULE 7
   Ziska LH, 2012, P ROY SOC B-BIOL SCI, V279, P4097, DOI 10.1098/rspb.2012.1005
NR 56
TC 13
Z9 16
U1 3
U2 47
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD JUL
PY 2020
VL 26
IS 7
BP 4079
EP 4093
DI 10.1111/gcb.15128
EA MAY 2020
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA LX7HQ
UT WOS:000531594100001
PM 32320514
OA Green Accepted, Green Published
DA 2025-01-10
ER

PT J
AU Fischer, AM
   Keller, DE
   Liniger, MA
   Rajczak, J
   Schär, C
   Appenzeller, C
AF Fischer, A. M.
   Keller, D. E.
   Liniger, M. A.
   Rajczak, J.
   Schaer, C.
   Appenzeller, C.
TI Projected changes in precipitation intensity and frequency in
   Switzerland: a multi-model perspective
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE regional climate models; climate change; precipitation change;
   convective fraction; large-scale precipitation; convective
   precipitation; Alps; dry spells; wet spells
ID CLIMATE-CHANGE SCENARIOS; CONVECTIVE PRECIPITATION; MODEL; SIMULATIONS;
   SCHEME; TEMPERATURE; PARAMETERIZATION; UNCERTAINTY; STATISTICS; EUROPE
AB Fundamental changes in the hydrological cycle are to be expected in a future warmer climate. For Switzerland, recent climate change assessments based on the ENSEMBLES regional climate models project for the A1B emission scenario summer mean precipitation to significantly decrease by the end of this century, whereas winter mean precipitation tend to rise in Southern Switzerland. From an end-user perspective, projected changes in seasonal means are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we investigate the projected changes in seasonal precipitation by considering changes in frequency and intensity, precipitation type (convective vs stratiform) and temporal structure (wet and dry spells) over Switzerland. As proxies for rain-type changes, we rely on the parameterized convective and large-scale precipitation components simulated by the models. The study reveals that the projected summer drying over Switzerland at the end of the century is mainly driven by a widespread reduction in the number of precipitation days. Thereby, the drying evolves altitude-specific: over low-land regions it is associated with a decrease in both convective and large-scale precipitation. Over elevated regions it is primarily associated with a decline in large-scale precipitation only, whereas convective precipitation remains at current levels. As a consequence, almost all the models project an increase in convective fraction at elevated altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in the number of multi-day wet (dry) spells. This future shift in multi-day episodes also lowers down the likelihood of short dry spell occurrence in all of the models. The models further project a higher mean precipitation intensity in spring and autumn north of the Alps, whereas a similar tendency is expected for the winter season over most of Switzerland.
C1 [Fischer, A. M.; Keller, D. E.; Liniger, M. A.; Appenzeller, C.] MeteoSwiss, Fed Off Meteorol & Climatol, CH-8058 Zurich, Switzerland.
   [Keller, D. E.; Liniger, M. A.; Schaer, C.; Appenzeller, C.] ETH, Ctr Climate Syst Modeling C2SM, Zurich, Switzerland.
   [Rajczak, J.; Schaer, C.] ETH, Inst Atmospher & Climate Sci, Zurich, Switzerland.
C3 Federal Office of Meteorology & Climatology (MeteoSwiss); Swiss Federal
   Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of
   Technology Domain; ETH Zurich
RP Fischer, AM (corresponding author), MeteoSwiss, Fed Off Meteorol & Climatol, Operat Ctr 1,Postfach 257, CH-8058 Zurich, Switzerland.
EM andreas.fischer@meteoswiss.ch
RI Schar, Christoph/A-1033-2008; Appenzeller, Christof/AAA-8989-2022;
   Liniger, Mark/K-7757-2013
OI Appenzeller, Christof/0000-0002-9939-9845; Liniger,
   Mark/0000-0003-4294-6868
FU CHIRP-II project (ETH research grant) [CH2-01 11-1]
FX Denise Keller is funded through the CHIRP-II project (ETH research grant
   CH2-01 11-1). Helpful comments on the manuscript by Andreas Weigel are
   acknowledged here. We are grateful to C2SM, especially Harald von
   Waldow, for downloading the daily precipitation data of ENSEMBLES.
CR Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   [Anonymous], SWISS CLIM CHANG SCE
   [Anonymous], HIRLAM NEWSLETTER
   [Anonymous], 2013, CLIMATE CHANGE KIRIB
   [Anonymous], THESIS ETH ZURICH ZU
   [Anonymous], AMS MONOGRAPH
   [Anonymous], 302 KNMI
   [Anonymous], ENSEMBLES CLIMATE CH
   [Anonymous], REGCM VERSION 3 1 IC
   [Anonymous], J GEOPHYS RES ATMOS
   Ban N, 2014, J GEOPHYS RES-ATMOS, V119, DOI 10.1002/2014JD021478
   Berg P, 2013, NAT GEOSCI, V6, P181, DOI 10.1038/ngeo1731
   Boberg F, 2012, NAT CLIM CHANGE, V2, P433, DOI 10.1038/NCLIMATE1454
   Boberg F, 2009, CLIM DYNAM, V32, P1097, DOI 10.1007/s00382-008-0446-y
   Boé J, 2009, CLIM DYNAM, V33, P265, DOI 10.1007/s00382-008-0474-7
   BOUGEAULT P, 1985, MON WEATHER REV, V113, P2108, DOI 10.1175/1520-0493(1985)113<2108:ASPOTL>2.0.CO;2
   Brockhaus P, 2008, METEOROL Z, V17, P433, DOI 10.1127/0941-2948/2008/0316
   Buishand TA, 2001, WATER RESOUR RES, V37, P2761, DOI 10.1029/2001WR000291
   Buser CM, 2009, CLIM DYNAM, V33, P849, DOI 10.1007/s00382-009-0588-6
   Calanca P, 2007, GLOBAL PLANET CHANGE, V57, P151, DOI 10.1016/j.gloplacha.2006.11.001
   Christensen JH, 2007, CLIMATIC CHANGE, V81, P1, DOI 10.1007/s10584-006-9211-6
   Christensen JH, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035694
   Christensen OB, 2004, GLOBAL PLANET CHANGE, V44, P107, DOI 10.1016/j.gloplacha.2004.06.013
   Collins M, 2006, CLIM DYNAM, V27, P127, DOI 10.1007/s00382-006-0121-0
   Dai A, 2006, J CLIMATE, V19, P4605, DOI 10.1175/JCLI3884.1
   EMANUEL KA, 1991, J ATMOS SCI, V48, P2313, DOI 10.1175/1520-0469(1991)048<2313:ASFRCC>2.0.CO;2
   Emanuel KA, 1999, J ATMOS SCI, V56, P1766, DOI 10.1175/1520-0469(1999)056<1766:DAEOAC>2.0.CO;2
   Fischer AM, 2012, INT J CLIMATOL, V32, P2348, DOI 10.1002/joc.3396
   Frei C, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD002287
   Giorgi F, 2011, J CLIMATE, V24, P5309, DOI 10.1175/2011JCLI3979.1
   Giorgi F, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL031223
   Gregory D, 1997, Q J ROY METEOR SOC, V123, P1153, DOI 10.1002/qj.49712354103
   GREGORY D, 1990, MON WEATHER REV, V118, P1483, DOI 10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Held IM, 2006, J CLIMATE, V19, P5686, DOI 10.1175/JCLI3990.1
   Hirschi M, 2012, EARTH SYST DYNAM, V3, P33, DOI 10.5194/esd-3-33-2012
   Hohenegger C, 2009, J CLIMATE, V22, P5003, DOI 10.1175/2009JCLI2604.1
   Im ES, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2009GL041801
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Jaeger EB, 2011, CLIM DYNAM, V36, P1919, DOI 10.1007/s00382-010-0780-8
   Jakob C, 2003, MON WEATHER REV, V131, P2765, DOI 10.1175/1520-0493(2003)131<2765:ANSMFM>2.0.CO;2
   Jones PD, 2011, NONLINEAR PROC GEOPH, V18, P503, DOI 10.5194/npg-18-503-2011
   Karl TR, 1999, CLIMATIC CHANGE, V42, P3, DOI 10.1023/A:1005491526870
   Kendon EJ, 2012, J CLIMATE, V25, P5791, DOI 10.1175/JCLI-D-11-00562.1
   Kendon EJ, 2010, CLIM DYNAM, V35, P489, DOI 10.1007/s00382-009-0639-z
   Khodayar S, 2013, METEOROL Z, V22, P507, DOI 10.1127/0941-2948/2013/0431
   Kjellström E, 2011, TELLUS A, V63, P24, DOI 10.1111/j.1600-0870.2010.00475.x
   Knutti R, 2010, J CLIMATE, V23, P2739, DOI 10.1175/2009JCLI3361.1
   Langhans W, 2012, J ATMOS SCI, V69, P2207, DOI 10.1175/JAS-D-11-0252.1
   Maraun D, 2010, REV GEOPHYS, V48, DOI 10.1029/2009RG000314
   May W, 2008, CLIM DYNAM, V30, P581, DOI 10.1007/s00382-007-0309-y
   Nakicenovic N., 2000, IPCC Special Report on Emissions Scenarios (SRES)
   Nordeng T E., 1994, Extended versions of the convective parameterization scheme at ECMWF and their impact on the mean and transient activity of the model in the Tropics, P1
   Rajczak J, 2013, J GEOPHYS RES-ATMOS, V118, P3610, DOI 10.1002/jgrd.50297
   Rowell DP, 2006, CLIM DYNAM, V27, P281, DOI 10.1007/s00382-006-0125-9
   Rulfová Z, 2013, ATMOS RES, V134, P100, DOI 10.1016/j.atmosres.2013.07.015
   Stephenson TS, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009127
   TIEDTKE M, 1989, MON WEATHER REV, V117, P1779, DOI 10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2
   Trenberth KE, 2003, B AM METEOROL SOC, V84, P1205, DOI 10.1175/BAMS-84-9-1205
   Tselioudis G, 2012, INT J CLIMATOL, V32, P1572, DOI 10.1002/joc.2360
   van Ulden AP, 2006, ATMOS CHEM PHYS, V6, P863, DOI 10.5194/acp-6-863-2006
   Wilks D.S, 2011, International Geophysics, DOI DOI 10.1016/B978-0-12-385022-5.00008-7
   Zubler EM, 2014, CLIMATIC CHANGE, V125, P237, DOI 10.1007/s10584-014-1144-x
NR 63
TC 46
Z9 46
U1 2
U2 44
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD SEP
PY 2015
VL 35
IS 11
BP 3204
EP 3219
DI 10.1002/joc.4162
PG 16
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA CQ9FF
UT WOS:000360917500002
DA 2025-01-10
ER

PT J
AU Flannery, W
   Lynch, K
   Cinnéide, MO
AF Flannery, Wesley
   Lynch, Kevin
   Cinneide, Micheal O.
TI Consideration of coastal risk in the Irish spatial planning process
SO LAND USE POLICY
LA English
DT Article
DE Coastal risk management; Climate change adaptation; Coastal management;
   Local planning and coastal risks; Coastal policy
ID SEA-LEVEL RISE; CLIMATE-CHANGE; MANAGEMENT; VULNERABILITY; PERCEPTION;
   FRAMEWORK; INSIGHTS; ZONE; BAY
AB The vulnerability of coastal areas to associated hazards is increasing due to population growth, development pressure and climate change. It is incumbent on coastal governance regimes to address the vulnerability of coastal inhabitants to these hazards. This is especially so at the local level where development planning and control has a direct impact on the vulnerability of coastal communities. To reduce the vulnerability of coastal populations, risk mitigation and adaptation strategies need to be built into local spatial planning processes. Local government, however, operates within a complex hierarchal governance framework which may promote or limit particular actions. It is important, therefore, to understand how local coastal planning practices are shaped by national and supranational entities. Local governments also have to respond to the demands of local populations. Consequently, it is important to understand local populations' perceptions of coastal risk and its management. Adopting an in-depth study of coastal planning in County Mayo, Ireland, this paper evaluates: (a) how European and national policies and legislation shape coastal risk management at local level; (b) the incorporation of risk management strategies into local plans; and (c) local perception of coastal risks and risk management. Despite a strong steer from supranational and national legislation and policy, statutory local plans are found to be lacking in appropriate risk mitigation or adaptation strategies. Local residents appear to be lulled into a sense of complacency towards these risks because of the low level of attention afforded to them by the local planning authorities. To avoid potentially disastrous consequences for local residents and businesses, it is imperative that this situation is redressed urgently. Based on our analysis, we recommend: the development and implementation of a national ICZM strategy, supported by detailed local ICZM plans; and obliging local government to address known risks in their plans rather than defer them to project level decision making. (C) 2014 Elsevier Ltd. All rights reserved.
C1 [Flannery, Wesley] Queens Univ Belfast, Sch Planning Architecture & Civil Engn, Belfast BT9 5AG, Antrim, North Ireland.
   [Lynch, Kevin; Cinneide, Micheal O.] Natl Univ Ireland, Sch Geog & Archaeol, Galway, Ireland.
C3 Queens University Belfast; Ollscoil na Gaillimhe-University of Galway
RP Flannery, W (corresponding author), Queens Univ Belfast, Sch Planning Architecture & Civil Engn, Belfast BT9 5AG, Antrim, North Ireland.
EM w.flannery@qub.ac.uk; kevin.lynch@nuigalway.ie;
   micheal.ocinneide@nuigalway.ie
RI Flannery, Wesley/AAX-3693-2020
OI Lynch, Kevin/0000-0002-2358-1958; Flannery, Wesley/0000-0003-0998-3851
CR Adger W. N., 1999, Mitig Adapt Strateg Glob Change, V4, P253, DOI [10.1023/A:1009601904210, DOI 10.1023/A:1009601904210]
   Agrawal A, 2010, NEW FRONT SOC POLICY, P173
   [Anonymous], 2010, Int. J. Sustain. Dev. Plann., DOI DOI 10.2495/SDP-V5-N1-57-67
   [Anonymous], 2010, BBC
   Bertin X, 2012, OCEAN MODEL, V42, P16, DOI 10.1016/j.ocemod.2011.11.001
   Biesbroek GR, 2010, GLOBAL ENVIRON CHANG, V20, P440, DOI 10.1016/j.gloenvcha.2010.03.005
   Comfort L., 1999, Glob Environ Chang Part B Environ Hazard, V1, P39, DOI [DOI 10.3763/EHAZ.1999.0105, 10.1016/S1464-2867(99)00005-4]
   Connolly N., 2001, ASSESSMENT HUMAN ACT
   Cooper JAG, 2009, J COASTAL RES, V25, P533, DOI 10.2112/09A-0001.1
   Crabbé P, 2006, CLIMATIC CHANGE, V78, P103, DOI 10.1007/s10584-006-9087-5
   CRABTREE BF, 1992, RES METH PR, V3, P93
   Cutter SL, 2000, ANN ASSOC AM GEOGR, V90, P713, DOI 10.1111/0004-5608.00219
   d'Auria L., 2009, Impact Assessment and Project Appraisal, V27, P309, DOI 10.3152/146155109X480600
   DEHLG, 2007, NAT DEV PLAN 2007 20
   DEHLG, 2009, PLANN SYST FLOOD RIS
   DEHLG, 2002, NAT SPAT STRAT 2002
   Devoy RJN, 2008, J COASTAL RES, V24, P325, DOI 10.2112/07A-0007.1
   DOECLG, 2012, NAT CLIM CHANG AD FR
   Domurat G. W., 1991, CALIFORNIA COASTAL Z
   Duxbury J, 2007, ECOL ECON, V63, P319, DOI 10.1016/j.ecolecon.2007.01.016
   Ellis G., 2002, TOWN PLAN REV, V73, P437, DOI [https://doi.org/10.3828/tpr.73.4.4, DOI 10.3828/TPR.73.4.4]
   Eurosion, 2004, EUR EUR IN SUST COAS
   Falaleeva M, 2011, MAR POLICY, V35, P784, DOI 10.1016/j.marpol.2011.01.005
   Fealy R., 2009, CLIMATE CHANGE HERIT
   Few R, 2007, COAST MANAGE, V35, P255, DOI 10.1080/08920750601042328
   Fitzpatrick J., 2001, FLOOD RISK MANAGEMEN
   Flannery W, 2008, MAR POLICY, V32, P980, DOI 10.1016/j.marpol.2008.02.001
   Government of Ireland, 2004, SEA GUID REG AUTH PL
   Gray SRJ, 2014, OCEAN COAST MANAGE, V94, P74, DOI 10.1016/j.ocecoaman.2013.11.008
   Grist B., 2013, INTRO IRISH PLANNING
   Harley CDG, 2006, ECOL LETT, V9, P228, DOI 10.1111/j.1461-0248.2005.00871.x
   Inter-governmental Panel on Climate Change IPCC, 2007, SUMM POL WORK GROUP
   Jeffers J. M., 2011, Irish Geography, V44, P61, DOI 10.1080/00750778.2011.615283
   LAVE TR, 1991, RISK ANAL, V11, P255, DOI 10.1111/j.1539-6924.1991.tb00602.x
   Lloyd MG, 2013, LAND USE POLICY, V30, P925, DOI 10.1016/j.landusepol.2012.06.012
   Long R., 2007, IRELAND
   Martin Brady Shipman, 1997, COASTAL ZONE MANAGEM
   Martínez ML, 2007, ECOL ECON, V63, P254, DOI 10.1016/j.ecolecon.2006.10.022
   Mayo County Council, 2009, COUNT MAYO DEV PLAN
   Mayo County Council, 2014, PROP AM DRAFT MAYO C
   McElduff L, 2013, TOWN PLAN REV, V84, P419, DOI 10.3828/tpr.2013.22
   McKenna J, 2003, COAST MANAGE, V31, P229, DOI 10.1080/08920750390198478
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Morrissey K, 2011, MAR POLICY, V35, P721, DOI 10.1016/j.marpol.2011.02.013
   National CoastalErosion Committee, 1992, COAST MAN CAS ACT
   Nicholls RJ, 1999, GLOBAL ENVIRON CHANG, V9, pS69, DOI 10.1016/S0959-3780(99)00019-9
   Nicholls RJ, 2004, GLOBAL ENVIRON CHANG, V14, P229, DOI 10.1016/j.gloenvcha.2004.04.005
   Næss LO, 2005, GLOBAL ENVIRON CHANG, V15, P125, DOI 10.1016/j.gloenvcha.2004.10.003
   O'Connor MC, 2009, MAR POLICY, V33, P923, DOI 10.1016/j.marpol.2009.03.007
   O'Hagan AM, 2002, J COASTAL RES, P544
   O'Hagan AM, 2011, MAR POLICY, V35, P772, DOI 10.1016/j.marpol.2011.01.004
   O'Hagan AM, 2010, OCEAN COAST MANAGE, V53, P750, DOI 10.1016/j.ocecoaman.2010.10.014
   O'Mahony C, 2012, COAST MANAGE, V40, P461, DOI 10.1080/08920753.2012.709462
   O'Mahony C, 2009, MAR POLICY, V33, P930, DOI 10.1016/j.marpol.2009.04.010
   Pini B, 2007, AUST GEOGR, V38, P161, DOI 10.1080/00049180701399985
   Riegel R., 2014, IRELAND 250 ACRES SM
   SANDELOWSKI M, 1995, RES NURS HEALTH, V18, P371, DOI 10.1002/nur.4770180411
   Terry G., 2011, UNDERSTANDING PUBLIC
   Tompkins EL, 2005, GLOBAL ENVIRON CHANG, V15, P139, DOI 10.1016/j.gloenvcha.2004.11.002
   West Regional Authority, 2010, REG PLANN GUID W REG
   Westport Town Council, 2010, WESTP TOWN ENV DEV P
NR 61
TC 23
Z9 25
U1 2
U2 59
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0264-8377
EI 1873-5754
J9 LAND USE POLICY
JI Land Use Pol.
PD FEB
PY 2015
VL 43
BP 161
EP 169
DI 10.1016/j.landusepol.2014.11.001
PG 9
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA CA4PB
UT WOS:000348885800016
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Thomas, SM
   Griffiths, SW
   Ormerod, SJ
AF Thomas, Stephen M.
   Griffiths, Sian W.
   Ormerod, Steve J.
TI Adapting streams for climate change using riparian broadleaf trees and
   its consequences for stream salmonids
SO FRESHWATER BIOLOGY
LA English
DT Article
DE riparian subsidy; river; salmonidae; stable isotopes; temperature
ID BROWN TROUT; TERRESTRIAL INVERTEBRATES; RIVER RESTORATION;
   STABLE-ISOTOPE; UPLAND STREAMS; MACROINVERTEBRATE COMMUNITIES; HEADWATER
   STREAMS; TROPHIC POSITION; WATER YIELD; LAND-USE
AB The societal value, ecological importance and thermal sensitivity of stream-dwelling salmonids have prompted interest in adaptive management strategies to limit the effects of climate change on their habitats. Additionally, in northern temperate regions, the management and restoration of riparian broadleaf forest is advocated increasingly to dampen variations in stream water temperature and discharge, but might have collateral effects on salmonids by changing allochthonous subsidies. Here, in a cross-sectional analysis of 18 temperate headwaters with different riparian and catchment land use, we use classical fisheries data alongside stable isotope ratios in salmonids and their macroinvertebrate prey to examine whether increasing catchment cover of broadleaf trees could (i) increase the density, biomass and size of salmonids, (ii) increase brown trout (Salmo trutta) dietary reliance on production of terrestrial origin and (iii) mediate allochthonous energy flux between aquatic macroinvertebrates and brown trout. Contrary to expectation, catchment broadleaf cover had no systematic effect on salmonid density or individual size, although salmonid biomass was lowest in streams draining non-native conifers. Moreover, there was no major effect of land use on the dependence of S.trutta on terrestrial production: averaged across all sites, trout used more production from in-stream (623%: mean +/- 1 SE) than terrestrial (38 +/- 3%) sources. Dependence on terrestrial production varied more substantially among individual streams than with riparian land use, mirroring site-specific patterns observed in macroinvertebrates. Although increased broadleaf cover could benefit salmonids by offsetting the impacts of warming related to climate change, these results imply that broadleaf restoration along temperate, upland headwaters is neutral with respect to salmonid biomass, density and terrestrial subsidies. In contrast, the use of non-native conifers for stream shading could have negative effects on salmonid production. Knowledge of the ecological implications of climate change adaptation remains rudimentary, and we advocate further evaluations like ours not only for fresh waters, but for ecosystems more generally.
C1 [Thomas, Stephen M.; Griffiths, Sian W.; Ormerod, Steve J.] Cardiff Univ, Cardiff Sch Biosci, Catchment Res Grp, Cardiff CF10 3AX, S Glam, Wales.
   [Thomas, Stephen M.] Univ Helsinki, Dept Environm Sci, Helsinki, Finland.
C3 Cardiff University; University of Helsinki
RP Thomas, SM (corresponding author), Univ Helsinki, Dept Environm Sci, POB 65, FI-00014 Helsinki, Finland.
EM stephen.thomas@helsinki.fi
RI Griffiths, Sian/A-5240-2010; Ormerod, Stephen J/A-4326-2010
OI Ormerod, Stephen J/0000-0002-8174-302X; Griffiths,
   Sian/0000-0001-6348-7352
FU Knowledge Economy Skills Scholarship scheme; NERC [NE/J014818/1] Funding
   Source: UKRI
FX We thank the Knowledge Economy Skills Scholarship scheme for funding
   this work, South East Wales Rivers Trust and Natural Resources Wales for
   help in kind, and Caitlin Pearson, Matthew Dray, Don A'Bear, Susannah
   Williams, Eleanor Kean, Eleanor Sherrard-Smith, Rhian Wilson and Stuart
   Rudd for assistance in the field. Two reviewers provided insightful and
   helpful comments on the manuscript.
CR Allan JD, 2003, CAN J FISH AQUAT SCI, V60, P309, DOI 10.1139/F03-019
   [Anonymous], 2011, ELECT FISHING COMPLE
   [Anonymous], CHANGES
   [Anonymous], PHASE1 HAB SURV
   [Anonymous], 2012, R: A Language and Environment for Statistical Computing
   [Anonymous], ARCGIS VERS 9 2 SOFT
   [Anonymous], GOOGL EARTH VERS 5 2
   [Anonymous], HDB BIOL STAT
   [Anonymous], FRESHWATERS OPENWATE
   Barto K., 2013, MuMIn: Multi-model inference. R package version 1.9.0
   Battin J, 2007, P NATL ACAD SCI USA, V104, P6720, DOI 10.1073/pnas.0701685104
   Baxter CV, 2005, FRESHWATER BIOL, V50, P201, DOI 10.1111/j.1365-2427.2004.01328.x
   Bernhardt ES, 2005, SCIENCE, V308, P636, DOI 10.1126/science.1109769
   Bond N, 2011, MAR FRESHWATER RES, V62, P1043, DOI 10.1071/MF10286
   BOSCH JM, 1982, J HYDROL, V55, P3, DOI 10.1016/0022-1694(82)90117-2
   Bradford MJ, 2000, CAN J FISH AQUAT SCI, V57, P13, DOI 10.1139/cjfas-57-1-13
   Broadmeadow SB, 2011, RIVER RES APPL, V27, DOI 10.1002/rra.1354
   Capon SJ, 2013, ECOSYSTEMS, V16, P359, DOI 10.1007/s10021-013-9656-1
   CHAPMAN DW, 1980, T AM FISH SOC, V109, P357, DOI 10.1577/1548-8659(1980)109<357:CALIOS>2.0.CO;2
   CHAPMAN DW, 1966, AM NAT, V100, P345, DOI 10.1086/282427
   Clews E, 2010, GLOBAL CHANGE BIOL, V16, P3271, DOI 10.1111/j.1365-2486.2010.02211.x
   del Rio CM, 2009, BIOL REV, V84, P91, DOI 10.1111/j.1469-185X.2008.00064.x
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Doucett RR, 1996, CAN J FISH AQUAT SCI, V53, P1913, DOI 10.1139/cjfas-53-8-1913
   Durance I, 2007, GLOBAL CHANGE BIOL, V13, P942, DOI 10.1111/j.1365-2486.2007.01340.x
   Elliott JM, 2010, J FISH BIOL, V77, P1793, DOI 10.1111/j.1095-8649.2010.02762.x
   ELLIOTT JM, 1973, OECOLOGIA, V12, P329, DOI 10.1007/BF00345047
   ELLIOTT JM, 1984, J ANIM ECOL, V53, P979, DOI 10.2307/4672
   Farley KA, 2005, GLOBAL CHANGE BIOL, V11, P1565, DOI 10.1111/j.1365-2486.2005.01011.x
   Ficke AD, 2007, REV FISH BIOL FISHER, V17, P581, DOI 10.1007/s11160-007-9059-5
   GEORGE T.N., 1970, BRIT REGIONAL GEOLOG, VThird
   GLOVA GJ, 1994, NEW ZEAL J MAR FRESH, V28, P255, DOI 10.1080/00288330.1994.9516613
   Goodwin CN, 1997, RESTOR ECOL, V5, P4, DOI 10.1111/j.1526-100X.1997.00004.x
   GRANT JWA, 1990, CAN J FISH AQUAT SCI, V47, P1724, DOI 10.1139/f90-197
   HAX CL, 1993, FRESHWATER BIOL, V29, P79, DOI 10.1111/j.1365-2427.1993.tb00746.x
   Heino J, 2009, BIOL REV, V84, P39, DOI 10.1111/j.1469-185X.2008.00060.x
   HESSLEIN RH, 1993, CAN J FISH AQUAT SCI, V50, P2071, DOI 10.1139/f93-230
   Hill WR, 2001, ECOLOGY, V82, P2306, DOI 10.1890/0012-9658(2001)082[2306:SERTFL]2.0.CO;2
   Hulme PE, 2005, J APPL ECOL, V42, P784, DOI 10.1111/j.1365-2664.2005.01082.x
   Ishikawa NF, 2012, OECOLOGIA, V170, P541, DOI 10.1007/s00442-012-2308-x
   Jonsson B, 2009, J FISH BIOL, V75, P2381, DOI 10.1111/j.1095-8649.2009.02380.x
   Kawaguchi Y, 2001, FRESHWATER BIOL, V46, P303, DOI 10.1046/j.1365-2427.2001.00667.x
   Kowalik RA, 2007, GLOBAL CHANGE BIOL, V13, P2439, DOI 10.1111/j.1365-2486.2007.01437.x
   Kruse Carter G., 1998, North American Journal of Fisheries Management, V18, P940, DOI 10.1577/1548-8675(1998)018<0940:SPEPTA>2.0.CO;2
   Lassalle G, 2009, GLOBAL CHANGE BIOL, V15, P1072, DOI 10.1111/j.1365-2486.2008.01794.x
   Layman CA, 2012, BIOL REV, V87, P545, DOI 10.1111/j.1469-185X.2011.00208.x
   Maitland P.S., 1972, Scientific Publs Freshwater Biol Ass, VNo. 27, P1
   Manel S, 2000, J APPL ECOL, V37, P756, DOI 10.1046/j.1365-2664.2000.00537.x
   Mantua NJ, 1997, B AM METEOROL SOC, V78, P1069, DOI 10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2
   Marcarelli AM, 2011, ECOLOGY, V92, P1215, DOI 10.1890/10-2240.1
   Millar CI, 2007, ECOL APPL, V17, P2145, DOI 10.1890/06-1715.1
   Moog O., 1995, FAUNA AQUATICA AUSTR
   Muotka T, 2002, J APPL ECOL, V39, P145, DOI 10.1046/j.1365-2664.2002.00698.x
   Naiman RJ, 2012, P NATL ACAD SCI USA, V109, P21201, DOI 10.1073/pnas.1213408109
   Nakano S, 2001, P NATL ACAD SCI USA, V98, P166, DOI 10.1073/pnas.98.1.166
   Ormerod SJ, 2009, AQUAT CONSERV, V19, P609, DOI 10.1002/aqc.1062
   Ormerod SJ, 2004, HYDROL EARTH SYST SC, V8, P578, DOI 10.5194/hess-8-578-2004
   ORMEROD SJ, 1993, J APPL ECOL, V30, P13, DOI 10.2307/2404266
   Palmer MA, 2010, FRESHWATER BIOL, V55, P205, DOI 10.1111/j.1365-2427.2009.02372.x
   Palmer MA, 2009, ENVIRON MANAGE, V44, P1053, DOI 10.1007/s00267-009-9329-1
   Parnell AC, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0009672
   Parrish DL, 1998, CAN J FISH AQUAT SCI, V55, P281, DOI 10.1139/cjfas-55-S1-281
   Pinheiro J., 2022, R package version 3.1-159, V3, P1
   Pinnegar JK, 1999, FUNCT ECOL, V13, P225, DOI 10.1046/j.1365-2435.1999.00301.x
   Post DM, 2002, ECOLOGY, V83, P703, DOI 10.2307/3071875
   Rader RB, 1997, CAN J FISH AQUAT SCI, V54, P1211, DOI 10.1139/cjfas-54-6-1211
   Richardson JS, 2010, CAN J FISH AQUAT SCI, V67, P1197, DOI 10.1139/F10-063
   Riley WD, 2009, FISHERIES MANAG ECOL, V16, P100, DOI 10.1111/j.1365-2400.2008.00649.x
   Robinson M, 2003, FOREST ECOL MANAG, V186, P85, DOI 10.1016/S0378-1127(03)00238-X
   Rybczynski SM, 2008, ECOL FRESHW FISH, V17, P199, DOI 10.1111/j.1600-0633.2007.00289.x
   SCHLOSSER IJ, 1991, BIOSCIENCE, V41, P704, DOI 10.2307/1311765
   Seavy N. E., 2009, Ecological Restoration, V27, P330, DOI 10.3368/er.27.3.330
   SOMA K, 1983, PLANT SOIL, V75, P139, DOI 10.1007/BF02178621
   Valachovic YS, 2004, CAN J FOREST RES, V34, P2131, DOI [10.1139/x04-089, 10.1139/X04-089]
   VANNOTE RL, 1980, CAN J FISH AQUAT SCI, V37, P130, DOI 10.1139/f80-017
   WALLACE JB, 1991, LIMNOL OCEANOGR, V36, P670, DOI 10.4319/lo.1991.36.4.0670
   Wallace JB, 1997, SCIENCE, V277, P102, DOI 10.1126/science.277.5322.102
   Warton DI, 2011, ECOLOGY, V92, P3, DOI 10.1890/10-0340.1
   WEATHERLEY NS, 1990, FRESHWATER BIOL, V24, P109, DOI 10.1111/j.1365-2427.1990.tb00312.x
   WEATHERLEY NS, 1991, FRESHWATER BIOL, V26, P121, DOI 10.1111/j.1365-2427.1991.tb00514.x
   Wipfli MS, 2010, FISHERIES, V35, P373, DOI 10.1577/1548-8446-35.8.373
   Wipfli MS, 1997, CAN J FISH AQUAT SCI, V54, P1259, DOI 10.1139/cjfas-54-6-1259
   Wipfli MS, 2004, HYDROBIOLOGIA, V520, P153, DOI 10.1023/B:HYDR.0000027734.95586.24
   Zoellick BW, 2004, WEST N AM NATURALIST, V64, P18
NR 84
TC 10
Z9 11
U1 3
U2 101
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0046-5070
EI 1365-2427
J9 FRESHWATER BIOL
JI Freshw. Biol.
PD JAN
PY 2015
VL 60
IS 1
BP 64
EP 77
DI 10.1111/fwb.12467
PG 14
WC Ecology; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology
GA AW1SI
UT WOS:000346069800005
DA 2025-01-10
ER

PT J
AU Henrico, I
   Dobos, B
AF Henrico, Ivan
   Dobos, Bohumil
TI Shifting sands: the geopolitical impact of climate change on Africa's
   resource conflicts
SO SOUTH AFRICAN GEOGRAPHICAL JOURNAL
LA English
DT Article; Early Access
DE Climate change; conflict; resource scarcity; Africa; climate adaptation;
   environmental security
ID ENVIRONMENTAL-CHANGE; CIVIL-WAR; MIGRATION; RAINFALL; DROUGHT; WATER
AB This study examines the complex relationships among climate change, resource scarcity, and conflict in Africa, focusing on the regions of Darfur, Lake Chad, and South Sudan. This highlights how climate change is a threat multiplier, intensifying socio-political challenges and worsening competition over vital resources such as water and arable land. Through a comparative analysis of these regions, this paper explores how environmental degradation, combined with weak governance and ethnic tensions, has led to conflict. In Darfur, prolonged droughts and desertification have exacerbated competition between herders and farmers. At the same time, in the Lake Chad Basin, the drastic shrinking of the lake has created fertile ground for extremist groups, including Boko Haram. In South Sudan, the impacts of erratic rainfall and water scarcity have contributed to ongoing civil conflict. This paper emphasizes the importance of addressing these climate-driven conflicts through better governance, climate adaptation, and resource management. Ultimately, this study contributes to the broader understanding of how climate change exacerbates conflict in vulnerable regions and underscores the need for coordinated international efforts to mitigate these impacts.
C1 [Henrico, Ivan] Stellenbosch Univ, Fac Mil Sci, Frans Erasmus Dr, Saldanha Bay, ZA-7395 Stellenbosch, South Africa.
   [Dobos, Bohumil] Charles Univ Prague, Fac Social Sci, Prague, Czech Republic.
C3 Charles University Prague
RP Henrico, I (corresponding author), Stellenbosch Univ, Fac Mil Sci, Frans Erasmus Dr, Saldanha Bay, ZA-7395 Stellenbosch, South Africa.
EM ivanh@sun.ac.za
RI Henrico, Ivan/ABG-4617-2021
CR Abel GJ, 2019, GLOBAL ENVIRON CHANG, V54, P239, DOI 10.1016/j.gloenvcha.2018.12.003
   ACLED, 2024, Data and analysis on political violence and protest events
   AfDB, 2022, African Development Bank
   African Centre for Strategic Studies, 2019, Timeline of South Sudan peace agreements and violence
   Altoom MB, 2023, LAND-BASEL, V12, DOI 10.3390/land12020307
   [Anonymous], 2019, Global Environmental Outlook 6
   [Anonymous], 2007, SUDAN POSTCONFLICT E
   [Anonymous], 2021, WMO-No. 1290
   [Anonymous], 2023, Global Report on Internal Displacement 2023
   Asafu-Adjaye J, 2014, J AFR ECON, V23, P17, DOI 10.1093/jae/eju011
   Barrios S, 2010, REV ECON STAT, V92, P350, DOI 10.1162/rest.2010.11212
   Berridge W., 2022, Sudans unfinished democracy: The promise and betrayal of a peoples revolution
   Burke MB, 2009, P NATL ACAD SCI USA, V106, P20670, DOI 10.1073/pnas.0907998106
   Busby JW, 2021, J PEACE RES, V58, P186, DOI 10.1177/0022343320971019
   Cilliers J., 2015, Institute for Security Studies Papers, V2015, P32, DOI [https://doi.org/10.2139/ssrn.2690116, DOI 10.2139/SSRN.2690116]
   Cilliers J., 2015, Institute for Security Studies Papers, V2015, P24, DOI [https://doi.org/10.2139/ssrn.2690080, DOI 10.2139/SSRN.2690080]
   De Juan A, 2015, POLIT GEOGR, V45, P22, DOI 10.1016/j.polgeo.2014.09.001
   Dunne D., 2023, Carbon Brief
   Ehiane S, 2022, J ASIAN AFR STUD, V57, P1677, DOI 10.1177/00219096211063817
   El-Fadel M., 2003, Journal of Natural Resources and Life Sciences Education, V32, P107
   FAO, 2024, The State of Food Security and Nutrition in the World, DOI [10.4060/cb4474-n, DOI 10.4060/CC2622EN]
   Ferguson P, 2019, GLOBAL ENVIRON POLIT, V19, P104, DOI 10.1162/glep_a_00500
   Freeman L, 2017, J ENVIRON DEV, V26, P351, DOI 10.1177/1070496517727325
   Frontires M. S., 2020, Lake Chad Crisis: In depth
   Gleick PH, 2014, WEATHER CLIM SOC, V6, P331, DOI 10.1175/WCAS-D-13-00059.1
   Hendrix CS, 2012, J PEACE RES, V49, P35, DOI 10.1177/0022343311426165
   Herbst Jeffrey., 2000, States and Power in Africa: Comparative Lessons in Authority and Control, V149
   Homer-Dixon TF, 2009, NATO SCI PEACE SECUR, P18, DOI 10.1007/978-94-007-1214-0_3
   Homer-Dixon ThomasF., 1999, ENV SCARCITY VIOLENC
   Ide T, 2016, HEXAG SER HUM ENVIRO, V10, P285, DOI 10.1007/978-3-319-43884-9_12
   IPCC, 2022, Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
   IPCC, 2024, Climate change, 2021: The physical science basis
   IPCC, 2024, Special report on climate change and land
   JACKSON RH, 1982, WORLD POLIT, V35, P1, DOI 10.2307/2010277
   Jedwab R., 2023, IZA discussion paper No. 16396
   Kaplan RobertD., 1994, The Atlantic Monthly, V273, P44
   Kazeem O. S., 2024, Journal of Contemporary International Relations and Diplomacy, V5, P74, DOI [https://doi.org/10.53982/jcird.2024.0501.05-j, DOI 10.53982/JCIRD.2024.0501.05-J]
   Larémont RR, 2021, AFR STUD REV, V64, P748, DOI 10.1017/asr.2021.114
   Maystadt JF, 2014, AM J AGR ECON, V96, P1157, DOI 10.1093/ajae/aau010
   Merem E., 2020, World Environment, V10, P27, DOI [https://doi.org/10.5923/j.env.20201002.01, DOI 10.5923/J.ENV.20201002.01]
   Meteoblue, 2024, Climate change in Juba, South Sudan
   Meteoblue, 2024, Climate change in Central Darfur, Sudan
   Meteoblue, 2024, Climate change in Lake Chad Basin (13.058N
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Nigam S., 2020, Encyclopedia of the Worlds biomes, V2020, P201
   Nkomo S., 2020, Afrobarometer policy paper
   NOAA, 2024, Global land and Africa temperature anomalies, 19102024
   Okpara UT, 2015, PROG DEV STUD, V15, P308, DOI 10.1177/1464993415592738
   Olanrewaju FO, 2020, INDIA Q, V76, P552, DOI 10.1177/0974928420961742
   Onapa SA, 2019, AFR SECUR REV, V28, P75, DOI 10.1080/10246029.2019.1680402
   Pham-Duc B, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-62417-w
   Piguet E, 2011, REFUG SURV Q, V30, P1, DOI 10.1093/rsq/hdr006
   Pinaud Clemence., 2021, War and Genocide in South Sudan
   Raleigh C, 2007, POLIT GEOGR, V26, P674, DOI 10.1016/j.polgeo.2007.06.005
   Ramdeen M., 2017, Conflict Trends, V2017, P49
   Roettinger J., 2019, A critical assessment of the link between climate change and violent conflict in the context of sub-saharan Africa: The case of Darfur
   Sakr S., 2023, Climate change and Darfur: A holistic security approach (capstone project)
   Sambo U., 2024, The Palgrave Handbook of Global Social Change, P1
   Schillinger J, 2020, WIRES WATER, V7, DOI 10.1002/wat2.1480
   Searchinger T., 2019, Creating a sustainable food future: A menu of solutions to feed nearly 10 billion people by 2050, p978156973963
   Skah M., 2020, Policy center for the new south
   Songwe V., 2024, Africa growth initiative
   Tesfaye B., 2022, Climate Change and Conflict in the Sahel. Discussion Paper Series on Managing Global Disorder No. 11 November 2022
   Tiitmamer N., 2022, Climate change and conflicts in South Sudan
   UN News, 2023, Explainer: How Darfur became a humanitarian calamity and catastrophic human rights crisis
   UNDP, 2024, Climate resilience can Be a catalyst for Peace and prosperity in the Sahel. United nations development programme (UNDP) climate promise
   UNHCR, 2023, Refugee data and global trends report
   UNISS, 2023, Geography of the Sahel. United nations integrated strategy for the Sahel
   United Nations, 2021, Climate change aggravating factor for terrorism: UN chief
   United Nations, 2021, People, countries impacted by climate change also vulnerable to terrorist recruitment, violence, speakers tell security council in open debate
   United Nations Climate Change, 2020, Climate change is an increasing threat to Africa
   Usigbe L., 2019, Silencing the guns: Drying Lake Chad Basin gives rise to crisis-food insecurity, conflicts, terrorism, displacement and climate change effects compound challenges
   Vivekananda J., 2019, Berlin: adelphi
   Von Uexkull N., 2021, Security implications of climate change: A decade of scientific progress, V58
   von Uexkull N, 2016, P NATL ACAD SCI USA, V113, P12391, DOI 10.1073/pnas.1607542113
   Wall M., 2019, Shoring up stability: Addressing climate and fragility risks in the Lake Chad Region
   WMO, 2023, 2023 shatters climate records, with Major impacts
   World Bank, 2021, Climate adaptation and economic transformation in Sub-Saharan Africa
NR 78
TC 0
Z9 0
U1 0
U2 0
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0373-6245
EI 2151-2418
J9 S AFR GEOGR J
JI S. Afr. Geogr. J.
PD 2024 DEC 20
PY 2024
DI 10.1080/03736245.2024.2441116
EA DEC 2024
PG 27
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA P7M2R
UT WOS:001379697200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Borba, J
   Bonatti, M
   Medina, L
   Loehr, K
   Tremblay, C
   Gutberlet, J
   Sieber, S
AF Borba, Juliano
   Bonatti, Michelle
   Medina, Leonardo
   Loehr, Katharina
   Tremblay, Crystal
   Gutberlet, Jutta
   Sieber, Stefan
TI Climate change education through drama and social learning: Playful
   inquiry for building extreme weather events adaptation scenarios
SO JOURNAL OF ADULT AND CONTINUING EDUCATION
LA English
DT Article
DE Climate change education; drama in education; extreme weather events;
   resilience; mitigation; arts-based research; social learning
AB Considering the projected impacts of climate change in upcoming decades, innovative educational approaches should encourage inventive problem-solving techniques and societal change, fostering transformative climate adaptation. The value of drama in climate adaptation education remains a novel area in the environmental education research literature and requires further exploration of its potential benefits to Climate Change Education (CCE). This article presents a proposal for CCE to include various elements in a drama workshop by evaluating a methodological framework. Participants in the workshop studied the vulnerabilities that arose from flooding and droughts while dramatizing different social conflicts to develop building adaptation scenarios. Through the exploration of problems via playful activities, participants collaboratively construct narratives and texts rich with meaning, based on a critical and creative perception of themes, needs, desires, and overlapping ideologies. This short-term experience manifests efficacy in elucidating the underpinnings of social systems structures, human values, and motivations. This article analyzes workshop results, providing a pedagogical structure and theoretical foundation, contributing to a better comprehension of drama in education and the creation of capacities towards CCE.
C1 [Borba, Juliano; Bonatti, Michelle; Medina, Leonardo; Loehr, Katharina; Sieber, Stefan] Leibniz Ctr Agr Landscape Res ZALF eV, Sustainable Land Use Developing Countries, Muncheberg, Germany.
   [Borba, Juliano] Florianopolis City Hall PMF, Educ Dept, Florianopolis, Brazil.
   [Bonatti, Michelle; Sieber, Stefan] Humboldt Univ, Dept Agr Econ, Berlin, Germany.
   [Bonatti, Michelle] Univ Vila Velha, Vila Velha, Brazil.
   [Loehr, Katharina] Humboldt Univ, Thaer Inst Agr & Hort Sci, Urban Plant Ecophysiol, Berlin, Germany.
   [Tremblay, Crystal; Gutberlet, Jutta] Univ Victoria UV, Dept Geog, Victoria, BC, Canada.
   [Borba, Juliano] Leibniz Ctr Agr LandscapeRes ZALF eV, Sustainable Land Use Developing Countries, Eberswalder Str 84, D-15374 Muncheberg, Germany.
C3 Leibniz Association; Leibniz Zentrum fur Agrarlandschaftsforschung
   (ZALF); Humboldt University of Berlin; Centro Universitario Vila Velha;
   Humboldt University of Berlin
RP Borba, J (corresponding author), Leibniz Ctr Agr LandscapeRes ZALF eV, Sustainable Land Use Developing Countries, Eberswalder Str 84, D-15374 Muncheberg, Germany.
EM juliano.borba@prof.pmf.sc.gov.br
RI Löhr, Katharina/KCL-0431-2024; Chevelev-Bonatti, Michelle/JFJ-8529-2023
OI Tremblay, Crystal/0000-0002-7727-0936; Borba,
   Juliano/0000-0002-3619-2740
FU Sinergia project
FX We would like to thank Tim Prentki for the reading an earlier version of
   the manuscript and providing us some insights and Sinergia project for
   support this research.
CR Bentz J, 2020, CLIMATIC CHANGE, V162, P1595, DOI 10.1007/s10584-020-02804-4
   Bentz J, 2019, ELEMENTA-SCI ANTHROP, V7, DOI 10.1525/elementa.390
   Boal A., 2002, GAMES ACTORS NONACTO, V2nd
   Boal Augusto., 2019, Theatre of the Oppressed
   Bonatti M, 2022, ENVIRON DEV SUSTAIN, DOI 10.1007/s10668-022-02167-z
   Bonatti M, 2016, LAND USE POLICY, V58, P114, DOI 10.1016/j.landusepol.2016.06.033
   Brymer ALB, 2018, ECOL SOC, V23, DOI 10.5751/ES-09959-230142
   Caillois R., 2001, Man, Play, and Games
   Collins Kevin, 2009, European Environment, V19, P358, DOI 10.1002/eet.523
   Courtney R., 1989, Play, drama thought: The intellectual background to dramatic education
   Cundill G, 2012, J ENVIRON MANAGE, V113, P7, DOI 10.1016/j.jenvman.2012.08.021
   Dennis L., 1970, Young Children, V25, P230
   Drewes A, 2018, INT J SCI EDUC, V40, P67, DOI 10.1080/09500693.2017.1397798
   Freire P., 1970, PEDAGOGY OPPRESSED
   Gifford R, 2011, AM PSYCHOL, V66, P290, DOI 10.1037/a0023566
   Hardy B., 1977, COOL WEB PATTERN CHI
   Heathcote D., 1984, Collected writings on education and drama
   Huizinga Johan., 1970, Homo Ludens: A Study of the Play-Element in Culture
   IPCC, 2019, CHOICES MADE NOW ARE
   Jacobson SK, 2016, ECOL SOC, V21, DOI 10.5751/ES-08626-210330
   Jonsdottir A. B., 2017, ARTISTIC ACTIONS SUS
   Kahan D.M., 2010, Journal of Risk Research, V9, P1, DOI DOI 10.1080/13669877.2010.511246
   Kolb A. Y., 2009, SAGE HDB MANAGEMENT, P42, DOI [DOI 10.4135/9780857021038.N3, 10.4135/9780857021038.n3]
   Leclercq C., 2023, SOCIAL SCI HUMANITIE, V8, P100510, DOI [10.1016/j.ssaho.2023.100510, DOI 10.1016/J.SSAHO.2023.100510]
   Leichenko R, 2020, ANTHROPOCENE, V30, DOI 10.1016/j.ancene.2020.100241
   McLean J., 1996, Aesthetic framework in drama: Issues and implications: Issues and implications: Nadie research monograph no 2
   NOVITZ D, 1989, PHILOS LITERATURE, V13, P57, DOI 10.1353/phl.1989.0056
   O'Neill C., 1995, DRAMA WORLDS
   O'Sullivan E., 1999, TRANSFORMATIVE LEARN
   Pruneau D., 2010, US-China Education Review, V7, P15, DOI 10.17265/2161-623X/2010.09A.002
   Ripple WJ, 2022, BIOSCIENCE, V72, P1149, DOI 10.1093/biosci/biac083
   Ronald C., 2015, TANGRAMS 330 PUZZLES
   Rosen H., 1986, LANGUAGE ART, V63, P226
   Rousell D, 2020, CHILD GEOGR, V18, P191, DOI 10.1080/14733285.2019.1614532
   Siegner A, 2020, ENVIRON EDUC RES, V26, P511, DOI 10.1080/13504622.2019.1607258
   Somers J.W., 2008, Music Arts in Action, V1, P61
   Spolin Viola., 1963, IMPROVISATION THEATE
   Taylor P., 2006, STRUCTURE SPONTANEIT
   Taylor P., 1995, PRETEXT STORY DRAMA
   Weber EU, 2016, WIRES CLIM CHANGE, V7, P125, DOI 10.1002/wcc.377
NR 40
TC 2
Z9 2
U1 7
U2 13
PU SAGE PUBLICATIONS LTD
PI LONDON
PA 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
SN 1477-9714
EI 1479-7194
J9 J ADULT CONTIN EDUC
JI J. Adult Contin. Educ.
PD NOV
PY 2024
VL 30
IS 2
BP 532
EP 550
DI 10.1177/14779714241227833
EA JAN 2024
PG 19
WC Education & Educational Research
WE Emerging Sources Citation Index (ESCI)
SC Education & Educational Research
GA J2U1O
UT WOS:001147575300001
DA 2025-01-10
ER

PT J
AU Gopalakrishnan, S
   McNamara, D
   Smith, MD
   Murray, AB
AF Gopalakrishnan, Sathya
   McNamara, Dylan
   Smith, Martin D.
   Murray, A. Brad
TI Decentralized Management Hinders Coastal Climate Adaptation: The
   Spatial-dynamics of Beach Nourishment
SO ENVIRONMENTAL & RESOURCE ECONOMICS
LA English
DT Article
DE Beach nourishment; Climate adaptation; Sea level rise; Spatial-dynamic
   feedbacks
ID POLLUTION-CONTROL; COASTLINE MODEL; PROPERTY; SPILLOVERS; RESOURCES;
   QUALITY; IMPACT; SCALE
AB Climate change threatens to alter coastline erosion patterns in space and time and coastal communities adapt to these threats with decentralized shoreline stabilization measures. We model interactions between two neighboring towns, and explore welfare implications of spatial-dynamic feedbacks in the coastal zone. When communities are adjacent, the community with a wider beach loses sand to the community with a narrower beach through alongshore sediment transport. Spatial-dynamic feedbacks create incentives for both communities to nourish less, resulting in lower long-run beach width and lower property values in both communities, a result that parallels the classic prisoner's dilemma. Intensifying erosion-consistent with accelerating sea level rise-increases the losses from failure to coordinate. Higher erosion also increases inequality in the distribution of benefits across communities under spatially coordinated management. This disincentive to coordinate suggests the need for higher-level government intervention to address a traditionally local problem. We show that a spatially targeted subsidy can achieve the first best outcome, and explore conditions under which a second-best uniform subsidy leads to small or large losses.
C1 [Gopalakrishnan, Sathya] Ohio State Univ, Dept Agr Environm & Dev Econ, 2120 Fyffe Rd, Columbus, OH 43210 USA.
   [McNamara, Dylan] UNC Wilmington, Dept Phys & Phys Oceanog, Ctr Marine Sci, Wilmington, NC USA.
   [Smith, Martin D.; Murray, A. Brad] Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA.
C3 University System of Ohio; Ohio State University; University of North
   Carolina; University of North Carolina Wilmington; Duke University
RP Gopalakrishnan, S (corresponding author), Ohio State Univ, Dept Agr Environm & Dev Econ, 2120 Fyffe Rd, Columbus, OH 43210 USA.
EM gopalakrishnan.27@osu.edu
RI Gopalakrishnan, Sathya/K-4079-2012
OI Murray, A. Brad/0000-0002-2484-9151; Gopalakrishnan,
   Sathya/0000-0002-3593-0297
FU NSF Biocomplexity Program [DEB0507987]; NSF Environment, Society and the
   Economy (ESE) Grant [EAR 0592120]
FX This research was funded by the NSF Biocomplexity Program (Grant
   #DEB0507987) and the NSF Environment, Society and the Economy (ESE)
   Grant (EAR 0592120).
CR [Anonymous], 1991, Game Theory
   Ashton A, 2001, NATURE, V414, P296, DOI 10.1038/35104541
   Ashton AD, 2006, J GEOPHYS RES-EARTH, V111, DOI 10.1029/2005JF000422
   Ashton AD, 2006, J GEOPHYS RES-EARTH, V111, DOI 10.1029/2005JF000423
   Bender MA, 2010, SCIENCE, V327, P454, DOI 10.1126/science.1180568
   Bhat MG, 2007, J ENVIRON ECON MANAG, V53, P54, DOI 10.1016/j.jeem.2006.04.002
   Bowles S., 2009, Microeconomics: behavior, institutions, and evolution
   Brock W, 2010, J ENVIRON ECON MANAG, V59, P149, DOI 10.1016/j.jeem.2009.07.003
   Bruun P., 1962, J WATERWAYS HARBORS, V88, P117, DOI DOI 10.1061/JWHEAU.0000252
   Christy FT, 1973, OCCASIONAL PAPER
   Clark CW., 2005, Mathematical Bioeconomics, The Optimal Management of Renewable Resources, V2nd
   Coburn T, 2009, 111 US SEN
   Costello C, 2008, J ENVIRON ECON MANAG, V56, P1, DOI 10.1016/j.jeem.2008.03.001
   Dean R.G., 2002, Beach Nourishment: Theory and Practice
   Ells K, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052627
   Epanchin-Niell RS, 2012, J ENVIRON ECON MANAG, V63, P260, DOI 10.1016/j.jeem.2011.10.003
   Fenichel EP, 2014, ENVIRON RESOUR ECON, V59, P231, DOI 10.1007/s10640-013-9726-z
   Gopalakrishnan S, 2011, J ENVIRON ECON MANAG, V61, P297, DOI 10.1016/j.jeem.2010.09.003
   Grafton RQ, 1996, REV FISH BIOL FISHER, V6, P5, DOI 10.1007/BF00058517
   Inman DL, 1963, INTERSCIENCE, V3
   IPCC (Intergovernmental Panel on Climate Change), 2015, AR6 Synthesis Report Climate Change 2023
   Kemp S, 2010, CAR TERET COUNTY NEW
   Landry Craig., 2003, Marine Resource Economics, V18, P105, DOI [10.1086/mre.18.2.42629388, DOI 10.1086/mre.18.2.42629388]
   Landry CE, 2011, LAND ECON, V87, P92, DOI 10.3368/le.87.1.92
   Lazarus ED, 2011, NONLINEAR PROC GEOPH, V18, P989, DOI 10.5194/npg-18-989-2011
   Lewis DJ, 2011, LAND ECON, V87, P250, DOI 10.3368/le.87.2.250
   List JA, 1999, ANN REGIONAL SCI, V33, P439, DOI 10.1007/s001680050114
   McCarthy N, 2001, J ENVIRON ECON MANAG, V42, P297, DOI 10.1006/jeem.2000.1164
   McNamara DE, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL047207
   Mendelsohn R, 2006, ENVIRON DEV ECON, V11, P159, DOI 10.1017/S1355770X05002755
   MONTGOMERY WD, 1972, J ECON THEORY, V5, P395, DOI 10.1016/0022-0531(72)90049-X
   Murray AB, 2013, COMPUT GEOSCI-UK, V53, P30, DOI 10.1016/j.cageo.2011.10.010
   NOAA, 2006, BEACH NOUR GUID LOC
   Ostrom E., 1994, RULES GAMES COMMON P
   Parker DC, 2007, ECOL ECON, V60, P821, DOI 10.1016/j.ecolecon.2006.02.002
   Parsons G.R., 2000, Marine Resource Economics, V14, P299, DOI [10.1086/mre.14.4.42629275, DOI 10.1086/MRE.14.4.42629275]
   Pelnard-Considere R, 1956, 4 JOURN HYD EN MER
   Pompe Jeffrey., 1995, Review of Regional Studies, V25, P271
   POMPE JJ, 1995, J LEISURE RES, V27, P143, DOI 10.1080/00222216.1995.11949739
   PSDS, 2006, BEACH NOUR DAT
   Sanchirico JN, 2005, J ENVIRON ECON MANAG, V50, P23, DOI 10.1016/j.jeem.2004.11.001
   Slott JM, 2008, COAST MANAGE, V36, P374, DOI 10.1080/08920750802266429
   Slott JM, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL027445
   Slott JM, 2010, J GEOPHYS RES-EARTH, V115, DOI 10.1029/2009JF001486
   Smith MD, 2009, J ENVIRON ECON MANAG, V58, P58, DOI 10.1016/j.jeem.2008.07.011
   Smith MD, 2009, J ENVIRON ECON MANAG, V57, P104, DOI 10.1016/j.jeem.2008.08.001
   Whitehead JC, 2008, MAR RESOUR ECON, V23, P119, DOI 10.1086/mre.23.2.42629607
   Williams ZC, 2013, J GEOPHYS RES-EARTH, V118, P887, DOI 10.1002/jgrf.20066
   Wolinsky MA, 2009, J GEOPHYS RES-EARTH, V114, DOI 10.1029/2007JF000856
   Zhang KQ, 2004, CLIMATIC CHANGE, V64, P41, DOI 10.1023/B:CLIM.0000024690.32682.48
NR 50
TC 22
Z9 23
U1 2
U2 20
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 0924-6460
EI 1573-1502
J9 ENVIRON RESOUR ECON
JI Environ. Resour. Econ.
PD AUG
PY 2017
VL 67
IS 4
BP 761
EP 787
DI 10.1007/s10640-016-0004-8
PG 27
WC Economics; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Business & Economics; Environmental Sciences & Ecology
GA FE7AB
UT WOS:000408358900006
DA 2025-01-10
ER

PT B
AU Li, BF
   Zhu, J
AF Li, Baofeng
   Zhu, Jia
BE Shen, Z
   Huang, L
   Peng, K
   Pai, J
TI Energy-Saving Design, Based on a Climate Adaptation Strategy, of the
   Dinosaur Egg Ruins Protecting Museum in Hubei
SO GREEN CITY PLANNING AND PRACTICES IN ASIAN CITIES: SUSTAINABLE
   DEVELOPMENT AND SMART GROWTH IN URBAN ENVIRONMENTS
SE Strategies for Sustainability
LA English
DT Article; Book Chapter
DE Energy-saving; Passive strategy; Site protection; Climate adaptation;
   Ventilation-friendly and light-resistant; Double-layered roof
AB With rapid urbanization, there are more and more construction projects of public facilities in China. The concept of green building has been introduced into the design process for museum buildings, which is one type of public facility pursuing energy savings. At present, artificial ventilation and heat preservation devices are utilized in museum buildings to maintain a stable temperature and humidity range for indoor exhibits. After equipment installation, energy consumption becomes a big cost of operating museum buildings. With the concept of green building, this work explores passive energy-saving strategies from a practical view of museum design. Lighting and heat preservation are pertinently considered under some special condition requirements, including processing of sloping field topography, adjustment of lighting and room temperature, combination with local materials and local culture, etc. As an example, the authors present a case study of implementation of the green building concept for energy saving in China.
C1 [Li, Baofeng; Zhu, Jia] Huazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Hubei, Peoples R China.
C3 Huazhong University of Science & Technology
RP Zhu, J (corresponding author), Huazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Hubei, Peoples R China.
EM zj_alice@163.com
CR [Anonymous], 2000, INTRO PHENOMENOLOGY
   Baofeng Li, 2001, ARCHITECT J
   Brager GS, 2000, ASHRAE J, V42, P21
   Chai W, 2009, STUDY HEAT INSULATIO
   Cheng HT, 2006, APPL LOW ENERGY CONS
   Cuce E, 2017, INT J LOW-CARBON TEC, V12, P126, DOI 10.1093/ijlct/ctw009
   Deszberg TM, 1983, EP, Patent No. EP0088567
   Fordham M, 2000, RENEW ENERG, V19, P17, DOI 10.1016/S0960-1481(99)00012-9
   Ghiaus C., 2005, NATURAL VENTILATION
   Guangcai BG, 2003, BUILDING ENERGY ENV
   Hou WS, 2012, BUILD SERV ENG RES T, V33, P407, DOI 10.1177/0143624411418153
   Huang C, 2007, LIGHT ARCHITECTURE
   Kim CS, 2014, KOREAN I INT DES J, V23, P3
   Kleiven T, 2003, NATURAL VENTILATION, V38, P491
   Lan L, 2009, CHIN OVERSEAS ARCHIT, V7, P81
   Ming-Hai LI, 2008, CONSTRUCTION CONSERV
   장현주, 2016, [KOREAN INSTITUTE OF INTERIOR DESIGN JOURNAL, 한국실내디자인학회 논문집], V25, P151
   Prockl GI, 1995, Patent No. [EP, EP 0685612 A1, 0685612]
   Qian K, 2009, CONSTRUCTION ENERGY
   Wen Y., 2013, MODERN DECORATION TH, V8, P253
   [杨柳 Yang Liu], 2015, [科学通报, Chinese Science Bulletin], V60, P1698
   Zhong A, 2015, ICCREM 2014 SMART CO, P140
NR 22
TC 1
Z9 1
U1 0
U2 5
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
BN 978-3-319-70025-0; 978-3-319-70024-3
J9 STRAT SUSTAIN
PY 2018
BP 259
EP 274
DI 10.1007/978-3-319-70025-0_13
D2 10.1007/978-3-319-70025-0
PG 16
WC Green & Sustainable Science & Technology; Environmental Studies;
   Regional & Urban Planning
WE Book Citation Index – Social Sciences & Humanities (BKCI-SSH)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Public Administration
GA BM5XJ
UT WOS:000465584100015
DA 2025-01-10
ER

PT J
AU Ghislain, NW
   Lucien, D
   Ali, D
   Inoussa, Z
   François, Z
AF Ghislain, Noba Wendkuni
   Lucien, Damiba
   Ali, Doumounia
   Inoussa, Zongo
   Francois, Zougmore
TI Climate projection and future rainfall trends analysis in the Nouhao
   sub-basin in Burkina Faso
SO GLOBAL NEST JOURNAL
LA English
DT Article
DE Regional climate model; climate scenario; rainfall distribution;
   standardized precipitation index; Nouhao sub-basin
AB Climate change is an indicator of changes happening in the biosphere. Monitoring it, will anticipating actions against the resulting disasters. This study, undertaken in Burkina Faso Nouaho sub basin, gives an overview of rainfall in the near, medium and long terms. It is built on regional climates models which are climates projections from global climate models downscaling. These models are generated basis on scenarios like greenhouse gas emissions and radiative forcing called Regional Concentration Pathways (RCP). The two scenarios RCP 4.5 and RCP 8.5 chosen in this study, have enabled to identify a rainfall regional climate model whose output corrected basis on Nouhao sub -basin observation data, highlight changes in sub -basin future precipitation. Over the three defined normal, i.e. normal 1 (2021-2050), normal 2 (2051-2080) and normal 3 (20712100), cumulative annual rainfall mean shows a downward trend under the RCP 4.5 scenario, and an upward trend under the RCP 8.5 scenario. The Standardized Precipitation Index (SPI) for the RCP 4.5 scenario shows very wet years at the start of normal 1, before giving way to alternating years close to normal rainfall, in normal 2 and 3. In the RCP 8.5 scenario, the SPI shows a dominance of dry years in normal 1. In normal 2 and 3, wet and very wet years return to dominate. The spatial dynamics of future rainfall, meanwhile, show a latitudinal shift in annual rainfall totals towards the south -east of the sub -basin under the RCP 4.5 scenario, and towards the north-west under the RCP 8.5 scenario. The climate projection thus highlights possible future changes in precipitation in the sub -basin. Its consideration could form the basis for the implementation of climate change adaptation strategies in the area.
C1 [Ghislain, Noba Wendkuni; Lucien, Damiba; Ali, Doumounia; Inoussa, Zongo; Francois, Zougmore] Joseph Ki Zerbo Univ, Dept Phys, Lab Mat & Environm LAME, Ouagadougou, Burkina Faso.
   [Lucien, Damiba] Res & Knowledge Management West Africa, Int Program Dept, WaterAid, Ouagadougou, Burkina Faso.
   [Inoussa, Zongo] Natl Ctr Sci & Technol Res, Ouagadougou, Burkina Faso.
   [Ali, Doumounia] Inst Sci, Dept Phys & Chem, Ouagadougou, Burkina Faso.
C3 Universite Joseph Ki-Zerbo
RP Ghislain, NW (corresponding author), Joseph Ki Zerbo Univ, Dept Phys, Lab Mat & Environm LAME, Ouagadougou, Burkina Faso.
EM ghislainnoba@yahoo.fr
CR Amrouni Y., 2022, These de doctorat
   [Anonymous], 2006, VertigO, DOI [DOI 10.4000/VERTIGO.2038, 10.4000/vertigo.2038]
   [Anonymous], CORDEX-AFR 44
   Bedoum A., 2014, Rev. Ivoirienne Sci. Technol, V23, P13
   Bernard D.K., 2014, Document De Strategie Du Programme National Changement Climatique (2015-2020)
   Bodian A, 2020, WATER-SUI, V12, DOI 10.3390/w12020436
   BRASSEL KE, 1979, GEOGR ANAL, V11, P289
   Cornet A., 1992, LARIDITE CONTRAINTE, P245
   David S. P., 2014, Journal Africain de Communication Scientifique et Technologique, V27, P3571
   Déqué M, 2007, GLOBAL PLANET CHANGE, V57, P16, DOI 10.1016/j.gloplacha.2006.11.030
   Djohy GL., 2015, AFRIQUE SCI, V11, P183
   Ebode V.B., 2021, Afrique SCI, V18, P36
   Eden JM, 2012, J CLIMATE, V25, P3970, DOI 10.1175/JCLI-D-11-00254.1
   Edlaen, 2015, Schema directeur d'amenagement et de gestion des eaux de l'espace de competance de l'agence de l'eau du nakanbe, Vi
   El Hawari J., 2023, Revue Internationale de La Recherche Scientifique (RevueIRS), V1, P61
   Fenta AA, 2018, ATMOS RES, V212, P43, DOI 10.1016/j.atmosres.2018.05.009
   Flaounas E, 2011, CLIM DYNAM, V36, P1083, DOI 10.1007/s00382-010-0785-3
   Ghenim AN, 2013, PHYSIO-GEO, V7, DOI 10.4000/physio-geo.3173
   Hakiekou Fiedi, 2011, Etude de l'impact des activites agro-sylvopastorales sur le sous-bassin versant de Nouaho nord au Burkina Faso: proposition de modele de gestion durable des ressources hydriques, pedologiques et vegetales au profit des communautes locales dans le contex
   IGB-BNDT-BDOT, 2002, Base nationale de donnees topographiques et d'occupation de terrain
   IRIE G.R., 2015, International Journal of Innovation and Applied Studies, V13, P386
   Kabore P.N., 2017, CLIMATOLOGIE, V14, P82, DOI [10.4267/climatologie.1268, DOI 10.4267/CLIMATOLOGIE.1268]
   Kone B., 2019, European Scientific Journal ESJ, V15, DOI [10.19044/esj.2019.v15n27p383, DOI 10.19044/ESJ.2019.V15N27P383]
   Kwawuvi D., 2023, Intra-Seasonal Rainfall Variability and Its Implications on Streamflow In The Oti Basin
   Labarere J., 2012, UE4 Biostatistique
   Larwanou M., 2011, Chapitre 7 Changements Climatiques Dans Le Sahel Et Les Savanes Ouest-Africaines: Impacts Sur Les Formations Boisees Et Les Ressources En Arbres. Forets, Faune Sauvage Et Changement Climatique En Afrique
   Lauret P., 2015, Cahiers Philosophiques, P121, DOI [10.3917/caph.142.0121, DOI 10.3917/CAPH.142.0121]
   Lavorel S., 2017, Les mecanismes d'adaptation de la biodiversite aux changements climatiques et leurs limites
   MERRA-2, POWER Data Access Viewer
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Ndiaye PM, 2021, J HYDROL-REG STUD, V35, DOI 10.1016/j.ejrh.2021.100820
   NICHOLSON SE, 1985, J CLIM APPL METEOROL, V24, P1388, DOI 10.1175/1520-0450(1985)024<1388:SSR>2.0.CO;2
   Noba Wendkuni Ghislain, 2023, Journal of Water Resource and Protection, V15, P149, DOI 10.4236/jwarp.2023.154009
   Nouaceur Z., 2020, PHYSIO G O, V15, P89, DOI DOI 10.4000/PHYSIO-GEO.10966
   Ogega OM, 2020, CLIMATE, V8, DOI 10.3390/cli8120143
   Okafor G.C., 2021, Environ. Chall, V5, DOI [10.1016/j.envc.2021.100285, DOI 10.1016/J.ENVC.2021.100285]
   OMS & OMM, 2012, Rapport, P7
   Ouzeau G., 2014, Le Climat de La France Au XXIe Siecle, V4
   Qadem Z., 2022, Geomaghreb, V16
   REW R, 1990, IEEE COMPUT GRAPH, V10, P76, DOI 10.1109/38.56302
   Robert E., 2010, Cahiers d'Outre-Mer, V63, P47, DOI [10.4000/com.5861, DOI 10.4000/COM.5861]
   Rodrigue A., 2023, African Scientific Journal, V03, P050
   Souberou K.T., 2018, European Scientific Journal, ESJ, V14, P136, DOI [10.19044/esj.2018.v14n21p136, DOI 10.19044/ESJ.2018.V14N21P136]
   Taibi S., 2021, Proc. IAHS, V384, P213, DOI [10.5194/piahs-384-213-2021, DOI 10.5194/PIAHS-384-213-2021]
   Taylor KE, 2001, J GEOPHYS RES-ATMOS, V106, P7183, DOI 10.1029/2000JD900719
   Thiessen A., 1911, Mon. Weather Rev., V39, P1082
   UNESCO, 2006, Prevision Et Gestion des Effets Du Changement Climatique Sur Le Patrimoine Mondial Rapport commun du Centre du patrimoine mondial, des Organisations consultatives et d'un large groupe d'experts a la 30e session du Comite du patrimoine mondial
   Yameogo Wennepinguere Virginie Marie, 2023, International Journal of Biological and Chemical Sciences, V17, P233, DOI 10.4314/ijbcs.v17i1.17
   Yonaba R.O, 2020, THESIS I INT INGENIE
NR 49
TC 0
Z9 0
U1 0
U2 0
PU GLOBAL NETWORK ENVIRONMENTAL SCIENCE & TECHNOLOGY
PI ATHENS
PA 30 VOULGAROKTONOU STR, ATHENS, GR 114 72, GREECE
SN 1790-7632
J9 GLOBAL NEST J
JI Glob. Nest. J.
PY 2024
VL 26
IS 3
AR 05724
DI 10.30955/gnj.005724
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA UC8I3
UT WOS:001245949500019
DA 2025-01-10
ER

PT J
AU Nam, L
   Song, NV
   Quilloy, AJA
   Ranola, RF
   Camacho, JV
   Camacho, LD
   Eluriagac, LMT
AF Nam, Le Phuong
   Song, Nguyen Van
   Quilloy, Antonio Jesus A.
   Ranola, Roberto F.
   Camacho, Jose V.
   Camacho, Leni D.
   Eluriagac, Louie Marie T.
TI Assessment of impacts of adaptation measures on rice farm economic
   performance in response to climate change: Case study in Vietnam
SO ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
LA English
DT Article
DE Climate change adaptation; Economic assessment; Propensity score
   matching; Rice production
ID AGRICULTURE; LEVEL; SMALLHOLDER; STRATEGIES; PRONE
AB Climate change impacts, including rising temperatures, erratic changes in the frequency and quantity of rainfall, and the prevalence of extreme weather phenomena, pose threats to rice cultivation. The primary objective of this study is to conduct an economic assessment of the effect of adaptation strategies on the agricultural performance of rice farmers. A total of 260 rice farmers from Nong Cong district were selected as the sample for the study. Collected data were analyzed using propensity scores matching (PSM) and the analysis of variance (ANOVA) technique, using Tukey's method. PSM was utilized to compare farmers who adapted and those who did not, while the ANOVA test was applied to examine disparities in the impacts, resulting from the use of various adaptive measures. The study's findings demonstrated that changing rice varieties led to the most substantial increment in profitability (a 73% surge in profits) while adjusting the seasonal timetable was the least costly measure. Among the plausible combinations of adaptive measures, farmers achieved the highest additional yield by utilizing increased fertilizers and pesticides (yielding a 26% increase). However, the highest increase in profitability was observed by adjusting the seasonal calendar and modifying rice varieties (yielding a 124.2% surge in profits). Significant factors influencing farmers' choice of adaptive measures include the extent of formal education, farming experience, agricultural income, participation in training programs, membership in agricultural associations, and access to 7-10-day weather forecasts. The study recommends that farmers cultivate high-yielding rice varieties resistant to extreme weather patterns. Furthermore, extension organizations are advised to intensify their efforts in conducting awareness campaigns focused on climate change, disseminating weather forecast information at the district level, and providing agricultural extension services coupled with training in advanced agricultural techniques.
C1 [Nam, Le Phuong; Song, Nguyen Van] Vietnam Natl Univ Agr VNUA, Hanoi, Vietnam.
   [Quilloy, Antonio Jesus A.; Ranola, Roberto F.; Camacho, Jose V.] Univ Philippines Los Banos UPLB, Coll Econ & Management, Laguna, Philippines.
   [Camacho, Leni D.] Univ Philippines Los Banos UPLB, Coll Forestry & Nat Resources, Laguna, Philippines.
   [Eluriagac, Louie Marie T.] Univ Philippines Visayas UPV, Coll Arts & Sci, Miagao 5023, Iloilo, Philippines.
C3 Vietnam National University of Agriculture (VNUA); University of the
   Philippines System; University of the Philippines Los Banos; University
   of the Philippines System; University of the Philippines Los Banos
RP Song, NV (corresponding author), Vietnam Natl Univ Agr VNUA, Hanoi, Vietnam.
EM lephuongnam87@gmail.com; nguyensongvnua@gmail.com; aaquilloy@up.edu.ph;
   bert1866@gmail.com; jdcamacho1@up.edu.ph; ldcamacho@up.edu.ph;
   lteluriaga@up.edu.ph
OI Le, Nam/0000-0003-0352-7345; Eluriaga, Louie Marie/0000-0002-2335-398X
FU Southeast Asian Regional Center for Graduate Study and Research in
   Agriculture (SEARCA); German Academic Exchange Service (DAAD);
   University of the Philippines Los Banos (UPLB)
FX First author want to thank the Southeast Asian Regional Center for
   Graduate Study and Research in Agriculture (SEARCA) and The German
   Academic Exchange Service (DAAD), two organizations already granted for
   the first author the scholarship to study PhD program at the University
   of the Philippines Los Banos (UPLB).
CR Abbasi S., 2023, Decision Analytics Journal, V6, P100189, DOI [10.1016/j.dajour.2023.100189, DOI 10.1016/J.DAJOUR.2023.100189]
   Abbasi S., 2021, Journal of Industrial Engineering International, V17, P83, DOI [DOI 10.30495/JIEI.2022.1942784.1169, 10.30495/JIEI.2022.1942784.1169]
   Abbasi S., 2023, Journal of Engineering Research, DOI [10.1016/J.JER.2023.100098, DOI 10.1016/J.JER.2023.100098]
   Abbasi S., 2023, RES SQUARE RES SQUAR, DOI [10.21203/rs.3.rs-3125845/v1, DOI 10.21203/RS.3.RS-3125845/V1]
   Abbasi S, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15043677
   Abbasi S, 2022, FOUND COMPUT DECIS S, V47, P327, DOI 10.2478/fcds-2022-0018
   Abbasi S, 2023, ENVIRON MODEL ASSESS, V28, P69, DOI 10.1007/s10666-022-09863-0
   Abbasi S, 2022, DISCRETE DYN NAT SOC, V2022, DOI 10.1155/2022/6967088
   Abdoussalami A., 2023, ROLE SOCIAL NETWORK, DOI [10.1007/s10668-023-03626-x, DOI 10.1007/S10668-023-03626-X]
   Abid M, 2016, J RURAL STUD, V47, P254, DOI 10.1016/j.jrurstud.2016.08.005
   Abunyewah M, 2023, ENVIRON SCI POLICY, V150, DOI 10.1016/j.envsci.2023.103594
   Ado AM, 2020, GEOJOURNAL, V85, P1075, DOI 10.1007/s10708-019-10011-7
   Akter S, 2021, ENVIRON DEV SUSTAIN, V23, P4358, DOI 10.1007/s10668-020-00778-y
   Alam GMM, 2016, ECOL ECON, V130, P243, DOI 10.1016/j.ecolecon.2016.07.012
   Alauddin M, 2014, ECOL ECON, V106, P204, DOI 10.1016/j.ecolecon.2014.07.025
   Alem Kidanu Alem Kidanu, 2016, Journal of Agricultural Extension and Rural Development, V8, P269, DOI 10.5897/JAERD2016.0800
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Amare A., 2017, Agric. Food Secur, V6, P64, DOI DOI 10.1186/S40066-017-0144-2
   Asfaw S., 2012, EC PLANT GENETIC RES
   Ashraf M. Q., 2019, DETERMINANTS ADAPTAT
   Asrat P, 2018, ECOL PROCESS, V7, DOI 10.1186/s13717-018-0118-8
   Atube Francis, 2021, Agriculture and Food Security, V10, DOI 10.1186/s40066-020-00279-1
   Aye GC, 2017, COGENT ECON FINANC, V5, DOI 10.1080/23322039.2017.1379239
   Azumah S., 2020, GHANA J GEOGRAPHY, V12, P29, DOI [10.4314/gjg.v12i1.2, DOI 10.4314/GJG.V12I1.2]
   Baloch ZA, 2022, ENVIRON SCI POLLUT R, V29, P57306, DOI 10.1007/s11356-022-19895-4
   Bedeke S, 2019, NJAS-WAGEN J LIFE SC, V88, P96, DOI 10.1016/j.njas.2018.09.001
   Belay Abrham., 2017, Agriculture Food Security, V6, P24, DOI [10.1186/s40066-017-0100-1, DOI 10.1186/S40066-017-0100-1]
   Below TB, 2012, GLOBAL ENVIRON CHANG, V22, P223, DOI 10.1016/j.gloenvcha.2011.11.012
   Burke M, 2016, AM ECON J-ECON POLIC, V8, P106, DOI 10.1257/pol.20130025
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Chen SA, 2016, J ENVIRON ECON MANAG, V76, P105, DOI 10.1016/j.jeem.2015.01.005
   Dasmani I, 2020, COGENT SOC SCI, V6, DOI 10.1080/23311886.2020.1751531
   Davis KF, 2021, NAT FOOD, V2, DOI 10.1038/s43016-020-00196-3
   Deressa T., 2008, Measuring Ethiopian farmers' vulnerability to climate change across regional states
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Gebru G. W., DETERMINANTS SMALLHO, P2405
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Iqbal M., 2015, IMPACT FARM HOUSEHOL
   Islam AMT, 2021, ENVIRON DEV SUSTAIN, V23, P2439, DOI 10.1007/s10668-020-00681-6
   Kabir M., 2015, J GEOGR NAT DISASTER, DOI [10.4172/2167-0587.1000152, DOI 10.4172/2167-0587.1000152]
   Kabubo-Mariara J, 2007, GLOBAL PLANET CHANGE, V57, P319, DOI 10.1016/j.gloplacha.2007.01.002
   Kamruzzaman M, 2023, INT J ENVIRON SCI TE, V20, P5609, DOI 10.1007/s13762-022-04254-0
   Katungi E., 2008, Journal of International Development, V20, P35, DOI 10.1002/jid.1426
   Lamichhane J., 2016, TURKISH J AGR FOOD S, V4, P476, DOI [10.24925/turjaf.v4i6.476-480.657, DOI 10.24925/TURJAF.V4I6.476-480.657]
   Magesa BA, 2023, CLIM SERV, V30, DOI 10.1016/j.cliser.2023.100362
   Maja MM, 2023, EARTH SYST ENVIRON, V7, P189, DOI 10.1007/s41748-022-00324-y
   Marie M, 2020, HELIYON, V6, DOI 10.1016/j.heliyon.2020.e03867
   Mendelsohn R, 2009, NEW HORIZ ENVIRON EC, P1
   Mengistu T. S., 2020, FARMER S PERCEPTION
   Menike LMCS, 2016, PROC FOOD SCI, V6, P288, DOI 10.1016/j.profoo.2016.02.057
   Mihiretu A, 2019, COGENT ENVIRON SCI, V5, DOI 10.1080/23311843.2019.1636548
   Mortimore MJ, 2001, GLOBAL ENVIRON CHANG, V11, P49, DOI 10.1016/S0959-3780(00)00044-3
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Motha R., 2011, IMPACT EXTREME WEATH
   Mulatu Debalke N., 2011, DETERMINANTS FARMERS
   Nam Le Phuong, 2022, AgBioForum, V24, P13
   Nhemachena C., 2007, INT FOOD POLICY RES
   Ojo TO, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2019.04.007
   Ortiz R., 2012, CLIMATE CHANGE AGR P
   Osasogie D. I., 2018, SOCIOECONOMIC DETERM
   Ouya FO, 2023, AGR FOOD SECUR, V12, DOI 10.1186/s40066-023-00418-4
   Pata UK, 2023, ENVIRON SCI POLLUT R, V30, P14821, DOI 10.1007/s11356-022-23160-z
   Peng CYJ, 2002, J EDUC RES, V96, P3, DOI 10.1080/00220670209598786
   ROSENBAUM PR, 1983, BIOMETRIKA, V70, P41, DOI 10.1093/biomet/70.1.41
   ROSENBAUM PR, 1983, J ROY STAT SOC B MET, V45, P212
   Roy R, 2016, ENVIRON DEV SUSTAIN, V18, P257, DOI 10.1007/s10668-015-9638-x
   Savari M, 2021, ENVIRON DEV SUSTAIN, V23, P4949, DOI 10.1007/s10668-020-00798-8
   Shongwe P., 2014, Sustainable Agriculture Research, V3, P37
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Solomon E., 2018, DETERMINANTS CLIMATE
   Stern N., 2007, The Economics of Climate Change: The Stern Review, DOI DOI 10.1017/CBO9780511817434
   Taro Yamane., 1967, Statistics an introductory analysis, V2nd
   Tesfaye T, 2023, ENVIRON DEV SUSTAIN, V25, P3183, DOI 10.1007/s10668-022-02185-x
   Thinda KT, 2021, J ASIAN AFR STUD, V56, P610, DOI 10.1177/0021909620934836
   Thoai TQ, 2018, LAND USE POLICY, V70, P224, DOI 10.1016/j.landusepol.2017.10.023
   Uddin MN, 2014, CLIMATE, V2, P223, DOI 10.3390/cli2040223
   Usman M, 2023, ENVIRON SCI POLLUT R, V30, P49930, DOI 10.1007/s11356-023-25883-z
   Williams EE., 2013, J INF ENG APPL, V3, P18
   Xenarios S, 2015, ENVIRON DEV SUSTAIN, V17, P963, DOI 10.1007/s10668-014-9583-0
   Zhang P, 2017, J ENVIRON ECON MANAG, V83, P8, DOI 10.1016/j.jeem.2016.12.001
NR 81
TC 0
Z9 0
U1 4
U2 5
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1387-585X
EI 1573-2975
J9 ENVIRON DEV SUSTAIN
JI Environ. Dev. Sustain.
PD DEC
PY 2024
VL 26
IS 12
BP 32479
EP 32507
DI 10.1007/s10668-023-04301-x
EA DEC 2023
PG 29
WC Green & Sustainable Science & Technology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA P3P5W
UT WOS:001131644000004
DA 2025-01-10
ER

PT J
AU Debele, SE
   Leo, LS
   Kumar, P
   Sahani, J
   Ommer, J
   Bucchignani, E
   Vranic, S
   Kalas, M
   Amirzada, Z
   Pavlova, I
   Shah, MAR
   Gonzalez-Ollauri, A
   Di Sabatino, S
AF Debele, Sisay E.
   Leo, Laura S.
   Kumar, Prashant
   Sahani, Jeetendra
   Ommer, Joy
   Bucchignani, Edoardo
   Vranic, Sasa
   Kalas, Milan
   Amirzada, Zahra
   Pavlova, Irina
   Shah, Mohammad Aminur Rahman
   Gonzalez-Ollauri, Alejandro
   Di Sabatino, Silvana
TI Nature-based solutions can help reduce the impact of natural hazards: A
   global analysis of NBS case studies
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate impact mitigation; NBS upscaling; NBS policies; NBS co-benefits;
   Disaster risk reduction; Sustainable Development Goal (SDG)
ID RESTORATION; PRINCIPLES; POLICY; RISK
AB The knowledge derived from successful case studies can act as a driver for the implementation and upscaling of nature-based solutions (NBS). This work reviewed 547 case studies to gain an overview of NBS practices and their role in reducing the adverse impact of natural hazards and climate change. The majority (60 %) of case studies are situated in Europe compared with the rest of the world where they are poorly represented. Of 547 case studies, 33 % were green solutions followed by hybrid (31 %), mixed (27 %), and blue (10 %) approaches. Approximately half (48 %) of these NBS interventions were implemented in urban (24 %), and river and lake (24 %) ecosystems. Regarding the scale of intervention, 92 % of the case studies were operationalised at local (50 %) and watershed (46 %) scales while very few (4 %) were implemented at the landscape scale. The results also showed that 63 % of NBS have been used to deal with natural hazards, climate change, and loss of biodiversity, while the remaining 37 % address socio-economic challenges (e.g., economic development, social justice, inequality, and cohesion). Around 88 % of NBS implementations were supported by policies at the national level and the rest 12 % at local and regional levels. Most of the analysed cases contributed to Sustainable Development Goals 15, 13, and 6, and biodiversity strategic goals B and D. Case studies also highlighted the co-benefits of NBS: 64 % of them were environmental co-benefits (e.g., improving biodiversity, air and water qualities, and carbon storage) while 36 % were social (27 %) and economic (9 %) co-benefits. This synthesis of case studies helps to bridge the knowledge gap between scientists, policymakers, and practitioners, which can allow adopting and upscaling of NBS for disaster risk reduction and climate change adaptation and enhance their preference in decision-making processes.
C1 [Debele, Sisay E.; Kumar, Prashant; Sahani, Jeetendra] Univ Surrey, Fac Engn & Phys Sci, Global Ctr Clean Air Res GCARE, Sch Sustainabil Civil & Environm Engn, Guildford GU2 7XH, Surrey, England.
   [Leo, Laura S.; Di Sabatino, Silvana] Univ Bologna, Dept Phys & Astron, Viale Berti Pichat 6-2, I-40127 Bologna, Italy.
   [Kumar, Prashant] Univ Surrey, Inst Sustainabil, Guildford GU2 7XH, Surrey, England.
   [Ommer, Joy] Univ Reading, Dept Geog & Environm Sci, Reading, England.
   [Ommer, Joy; Vranic, Sasa; Kalas, Milan] KAJO sro, Sladkovicova 228-8, Bytca 01401, Slovakia.
   [Bucchignani, Edoardo] Italian Aerosp Res Ctr CIRA, I-81043 Capua, Italy.
   [Amirzada, Zahra; Pavlova, Irina] United Nations Educ Sci & Cultural Org, Sect Earth Sci & Geohazards Risk Reduct, Nat Sci Sect, F-75007 Paris, France.
   [Shah, Mohammad Aminur Rahman] Univ Prince Edward Isl, Canadian Ctr Climate Change & Adaptat, Charlottetown, PE C1A 4P3, Canada.
   [Gonzalez-Ollauri, Alejandro] Glasgow Caledonian Univ, BEAM Res Ctr, Cowcaddens Rd, Glasgow G4 0BA, Scotland.
C3 University of Surrey; University of Bologna; University of Surrey;
   University of Reading; CIRA - Italian Aerospace Research Centre;
   University of Prince Edward Island; Glasgow Caledonian University
RP Kumar, P (corresponding author), Univ Surrey, Fac Engn & Phys Sci, Global Ctr Clean Air Res GCARE, Sch Sustainabil Civil & Environm Engn, Guildford GU2 7XH, Surrey, England.
EM p.kumar@surrey.ac.uk
RI Shah, Mohammad Aminur Rahman/HGU-4999-2022; Ommer, Joy/HJY-4980-2023;
   Bucchignani, Edoardo/AAL-4170-2020; pavlova, irina/GVR-7148-2022; Kumar,
   Prashant/C-6357-2011
OI Amirzada, Zahra/0009-0004-0990-1718; Kumar, Prashant/0000-0002-2462-4411
FU European Union [776848]; UKRI [EP/W034034/1, NE/X002799/1]
FX This work has been carried out under the framework of OPER-ANDUM
   (OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo
   risks) project, which is funded by the European Union's Horizon 2020 -
   Research and Innovation Framework Programme under the Grant Agreement
   No: 776848. PK acknowledges the support received through the UKRI-funded
   RECLAIM Network Plus (Grant No. EP/W034034/1) and Greencities project
   (NE/X002799/1). We also thank the Hereon teams for insightful discussion
   and suggestions on various topic areas covered in the article, and
   Surrey's GCARE team members (Dr Ana Paula Mendes Emygdio and Dr Gopinath
   Kalaiarasan) for proofreading the manuscript.
CR Almenar JB, 2021, LAND USE POLICY, V100, DOI 10.1016/j.landusepol.2020.104898
   [Anonymous], 2022, OPERANDUM D7.16
   Baills A, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031094
   Brand U, 2016, GAIA, V25, P23, DOI 10.14512/gaia.25.1.7
   Calliari E, 2022, CLIM RISK MANAG, V37, DOI 10.1016/j.crm.2022.100450
   Calliari E, 2019, SCI TOTAL ENVIRON, V656, P691, DOI 10.1016/j.scitotenv.2018.11.341
   Chausson A, 2020, GLOBAL CHANGE BIOL, V26, P6134, DOI 10.1111/gcb.15310
   Cohen-Shacham E., 2016, NATURE BASED SOLUTIO, V97, P2016
   Cohen-Shacham E, 2019, ENVIRON SCI POLICY, V98, P20, DOI 10.1016/j.envsci.2019.04.014
   Curt C, 2022, HELIYON, V8, DOI 10.1016/j.heliyon.2022.e12465
   Daniels E., Glob. Sustain., V3, P1
   Debele SE, 2019, ENVIRON RES, V179, DOI 10.1016/j.envres.2019.108799
   Dumitru A., 2021, Evaluating the impact of nature-based solutions: A summary for policy makers, DOI [10.2777/2498, 10.2777/244577]
   Dumitru A, 2020, ENVIRON SCI POLICY, V112, P107, DOI 10.1016/j.envsci.2020.05.024
   Dushkova D, 2020, METHODSX, V7, DOI 10.1016/j.mex.2020.101096
   EC, 2015, European Commission: Towards an EU Research and Innovation Policy Agenda for Nature-based Solutions & Re-naturing Cities Final Report of the Horizon 2020 Expert Group on "Nature-Based Solutions and Re-Naturing Cities, DOI [10.2777/765301, DOI 10.2777/765301]
   Eggermont H, 2015, GAIA, V24, P243, DOI 10.14512/gaia.24.4.9
   EIR, 2022, Environmental Implementation Review 2022. Turning the tide through environmental compliance
   Faivre N, 2018, INT J DISAST RISK RE, V32, P4, DOI 10.1016/j.ijdrr.2017.12.015
   Faivre N, 2017, ENVIRON RES, V159, P509, DOI 10.1016/j.envres.2017.08.032
   Findlater K, 2022, PEOPLE NAT, V4, P231, DOI 10.1002/pan3.10278
   Fletcher TD, 2015, URBAN WATER J, V12, P525, DOI 10.1080/1573062X.2014.916314
   Frantzeskaki N, 2020, LAND USE POLICY, V96, DOI 10.1016/j.landusepol.2020.104688
   Fritz M, 2017, THEOR PRACT URB SUST, P159, DOI 10.1007/978-3-319-56091-5_10
   GeoIKP, 2022, Geo Information Knowledge Platform
   Gill JC, 2014, REV GEOPHYS, V52, P680, DOI 10.1002/2013RG000445
   Girardin CAJ, 2021, NATURE, V593, P191, DOI 10.1038/d41586-021-01241-2
   Gonzalez-Ollauri A, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.676059
   Griscom BW, 2017, P NATL ACAD SCI USA, V114, P11645, DOI 10.1073/pnas.1710465114
   Haghighatafshar S, 2018, J ENVIRON MANAGE, V207, P60, DOI 10.1016/j.jenvman.2017.11.018
   Hobbie SE, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0124
   INSPIRE, 2012, D2.8.III.12 INSPIRE Data Specification on Natural Risk Zones-Draft Guidelines
   IRDR, 2014, IRDR DATA Publication No. 1
   Kabisch N, 2022, AMBIO, V51, P1388, DOI 10.1007/s13280-021-01685-w
   Kabisch N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08373-210239
   Kumar P, 2021, SCI TOTAL ENVIRON, V784, DOI 10.1016/j.scitotenv.2021.147058
   Kumar P, 2021, EARTH-SCI REV, V217, DOI 10.1016/j.earscirev.2021.103603
   Kumar P, 2020, SCI TOTAL ENVIRON, V731, DOI 10.1016/j.scitotenv.2020.138855
   Leo L.S., 2022, EGU General Assembly, DOI [10.5194/egusphere-egu22-8229, DOI 10.5194/EGUSPHERE-EGU22-8229]
   Maes J., 2013, ANALYTICAL FRAMEWORK, V5, P1
   Martin DM, 2017, RESTOR ECOL, V25, P668, DOI 10.1111/rec.12554
   Martín EG, 2021, SCI TOTAL ENVIRON, V794, DOI 10.1016/j.scitotenv.2021.148515
   Martín EG, 2020, ECOL ECON, V167, DOI 10.1016/j.ecolecon.2019.106460
   Nesshöver C, 2017, SCI TOTAL ENVIRON, V579, P1215, DOI 10.1016/j.scitotenv.2016.11.106
   Neumann VA, 2022, ENVIRON IMPACT ASSES, V93, DOI 10.1016/j.eiar.2022.106737
   Ommer J, 2022, INT J DISAST RISK RE, V75, DOI 10.1016/j.ijdrr.2022.102966
   OPERANDUM, 2023, OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks
   Ou XY, 2022, ECOL INDIC, V136, DOI 10.1016/j.ecolind.2022.108639
   Raymond C., 2017, Report prepared by the EKLIPSE expert working group on nature-based solutions to promote climate resilience in urban areas
   Riviere S., 2022, Nat. Based Solut., V2
   Rödl A, 2022, AMBIO, V51, P2278, DOI 10.1007/s13280-022-01740-0
   Ruangpan L, 2020, NAT HAZARD EARTH SYS, V20, P243, DOI 10.5194/nhess-20-243-2020
   Sahani J, 2019, SCI TOTAL ENVIRON, V696, DOI 10.1016/j.scitotenv.2019.133936
   Sarabi SE, 2019, RESOURCES-BASEL, V8, DOI 10.3390/resources8030121
   Schröter B, 2021, SCI TOTAL ENVIRON, V762, DOI 10.1016/j.scitotenv.2020.143074
   Seddon N, 2022, SCIENCE, V376, P1410, DOI 10.1126/science.abn9668
   Seddon N, 2021, GLOBAL CHANGE BIOL, V27, P1518, DOI 10.1111/gcb.15513
   Seddon N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0120
   Shah MAR, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101728
   Snyder H, 2019, J BUS RES, V104, P333, DOI 10.1016/j.jbusres.2019.07.039
   Souliotis I., 2022, Nat. Based Solut, V2, DOI [10.1016/j.nbsj.2022.100015, DOI 10.1016/J.NBSJ.2022.100015]
   Sowinska-Swierkosz B, 2021, SCI TOTAL ENVIRON, V787, DOI 10.1016/j.scitotenv.2021.147615
   Swann S., 2021, PUBLIC INT FUNDING N
   Tye S., 2022, POTENTIAL NATURE BAS
   UNDDR, 2020, Hazard Definition and Classification Review
   UNFCCC, 2015, PAR AGR
   United Nations General Assembly [UNGA], 2016, REP OP END INT EXP W
   van der Jagt A, 2023, ENVIRON SCI POLICY, V139, P51, DOI 10.1016/j.envsci.2022.10.011
   Wada CA, 2017, PAC SCI, V71, P401, DOI 10.2984/71.4.2
   Wamsler C, 2020, CLIMATIC CHANGE, V158, P235, DOI 10.1007/s10584-019-02557-9
   World Bank, 2020, Report, DOI [10.1596/978-1-4648-1457-0, 10.1596/978-1-4648-1457-0.A, DOI 10.1596/978-1-4648-1457-0.A]
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 72
TC 31
Z9 32
U1 19
U2 71
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD DEC 1
PY 2023
VL 902
AR 165824
DI 10.1016/j.scitotenv.2023.165824
EA AUG 2023
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA R2VA0
UT WOS:001062966100001
PM 37527720
OA hybrid, Green Accepted, Green Published
DA 2025-01-10
ER

PT J
AU Rahmani, N
   Sharifi, A
AF Rahmani, Neshat
   Sharifi, Ayyoob
TI Comparative Analysis of the Surface Urban Heat Island (SUHI) Effect
   Based on the Local Climate Zone (LCZ) Classification Scheme for Two
   Japanese Cities, Hiroshima, and Sapporo
SO CLIMATE
LA English
DT Article
DE surface urban heat island (SUHI); local climate zones (LCZs); land
   surface temperature (LST); climate change adaptation; Sapporo; Hiroshima
AB The Local Climate Zone (LCZ) classification system is used in this study to analyze the impacts of urban morphology on a surface urban heat island (SUHI). Our study involved a comparative analysis of SUHI effects in two Japanese cities, Sapporo and Hiroshima, between 2000 to 2022. We used geographical-information-system (GIS) mapping techniques to measure temporal LST changes using Landsat 7 and 8 images during the summer's hottest month (August) and classified the study area into LCZ classes using The World Urban Database and Access Portal Tools (WUDAPT) method with Google Earth Pro. The urban thermal field variance index (UTFVI) is used to examine each LCZ's thermal comfort level, and the SUHI heat spots (HS) in each LCZ classes are identified. The research findings indicate that the mean LST in Sapporo only experienced a 0.5 & DEG;C increase over the time, while the mean LST increased by 1.8 & DEG;C in Hiroshima City between 2000 and 2022. In 2000, open low-rise (LCZ 6) areas in Sapporo were the hottest, but by 2022, heavy industry (LCZ 10) became the hottest. In Hiroshima, compact mid-rise (LCZ 2) areas were the hottest in 2000, but by 2022, heavy-industry areas took the lead. The study found that LCZ 10, LCZ 8, LCZ E, and LCZ 3 areas in both Dfa and Cfa climate classifications had unfavorable UTFVI conditions. This was attributed to factors such as a high concentration of heat-absorbing materials, impervious surfaces, and limited green spaces. The majority of the SUHI HS and areas with the highest surface temperatures were situated near industrial zones and large low-rise urban forms in both cities. The study offers valuable insights into the potential long-term effects of various urban forms on the SUHI phenomenon.
C1 [Rahmani, Neshat] Hiroshima Univ, Grad Sch Adv Sci & Engn, Hiroshima 7398511, Japan.
   [Sharifi, Ayyoob] Hiroshima Univ, IDEC Inst, Hiroshima 7398529, Japan.
   [Sharifi, Ayyoob] Hiroshima Univ, Network Educ & Res Peace & Sustainabil NERPS, Hiroshima 7398529, Japan.
C3 Hiroshima University; Hiroshima University; Hiroshima University
RP Sharifi, A (corresponding author), Hiroshima Univ, IDEC Inst, Hiroshima 7398529, Japan.; Sharifi, A (corresponding author), Hiroshima Univ, Network Educ & Res Peace & Sustainabil NERPS, Hiroshima 7398529, Japan.
EM m221102@hiroshima-u.ac.jp; sharifi@hiroshima-u.ac.jp
RI ; Sharifi, Ayyoob/M-7584-2013
OI Rahmani, Neshat/0009-0007-9834-1995; Sharifi, Ayyoob/0000-0002-8983-8613
CR Althor G, 2016, SCI REP-UK, V6, DOI 10.1038/srep20281
   Avdan U, 2016, J SENSORS, V2016, DOI 10.1155/2016/1480307
   Bassani F, 2022, URBAN CLIM, V42, DOI 10.1016/j.uclim.2022.101099
   Bechtel B, 2019, URBAN CLIM, V28, DOI 10.1016/j.uclim.2019.01.005
   Bechtel B, 2015, ISPRS INT J GEO-INF, V4, P199, DOI 10.3390/ijgi4010199
   Berger C, 2017, REMOTE SENS ENVIRON, V193, P225, DOI 10.1016/j.rse.2017.02.020
   Brozovsky J, 2021, RENEW SUST ENERG REV, V138, DOI 10.1016/j.rser.2020.110551
   Cai M, 2018, URBAN CLIM, V24, P485, DOI 10.1016/j.uclim.2017.05.010
   Cardoso RD, 2018, INVESTIG GEOGR-SPAIN, P107, DOI 10.14198/INGEO2018.69.07
   Ching J, 2018, B AM METEOROL SOC, V99, P1907, DOI 10.1175/BAMS-D-16-0236.1
   Cilek MU, 2021, SUSTAIN CITIES SOC, V69, DOI 10.1016/j.scs.2021.102877
   COH, CITY HIR COF
   Das M, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100591
   Eldesoky AHM, 2021, URBAN CLIM, V37, DOI 10.1016/j.uclim.2021.100823
   Erdem U, 2021, ENVIRON DEV SUSTAIN, V23, P7835, DOI 10.1007/s10668-020-00950-4
   Gao Z, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab2740
   Geletic J, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8100788
   Grover A, 2015, ENVIRONMENTS, V2, P125, DOI 10.3390/environments2020125
   Hashimoto S, 2019, J NUCL SCI TECHNOL, V56, P345, DOI 10.1080/00223131.2019.1585989
   He BJ, 2023, ENERG BUILDINGS, V287, DOI 10.1016/j.enbuild.2023.112976
   Heisler G.M., 2010, URBAN ECOSYSTEM ECOL, P29, DOI [DOI 10.2134/AGRONMONOGR55.C2, 10.2134/agronmonogr55.c2]
   Hidalgo-García D, 2022, SUSTAIN CITIES SOC, V87, DOI 10.1016/j.scs.2022.104166
   Huang KN, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4b71
   Ignatius M, 2022, ISPRS ANN PHOTO REM, V10-4, P121, DOI 10.5194/isprs-annals-X-4-W2-2022-121-2022
   Kang S, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14063603
   Kim HJ, 2008, J METEOROL SOC JPN, V86, P981, DOI 10.2151/jmsj.86.981
   Liao YSY, 2022, SCI TOTAL ENVIRON, V811, DOI 10.1016/j.scitotenv.2021.151405
   macrotrends.net, MACR MACR
   Mutani G., 2019, Sustainability, V11, DOI [10.18280/i2m.180401, DOI 10.18280/I2M.180401]
   Najafzadeh F, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13214469
   Nassar AK, 2016, INT J APPL EARTH OBS, V51, P76, DOI 10.1016/j.jag.2016.05.004
   Nautiyal G, 2021, J INDIAN SOC REMOTE, V49, P1307, DOI 10.1007/s12524-021-01323-8
   Ochola EM, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100540
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Rodler A, 2019, URBAN CLIM, V28, DOI 10.1016/j.uclim.2019.100457
   Rostam MG, 2019, GEOGR PANNONICA, V23, P289, DOI 10.5937/gp23-24238
   Sakakibara Y., 2010, GEOGR REV JAPAN B, V82B, P196
   Seto KC, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P923
   Sharifi A, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103190
   Shi YR, 2019, SENSORS-BASEL, V19, DOI 10.3390/s19163459
   Solanky V, 2018, WATER SCI TECHNOL LI, V81, P343, DOI 10.1007/978-981-10-5801-1_24
   Stemn E, 2020, MODEL EARTH SYST ENV, V6, P1727, DOI 10.1007/s40808-020-00786-x
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Szabó AI, 2021, INT J CLIMATOL, V41, pE2482, DOI 10.1002/joc.6859
   Venter ZS, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abb9569
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wang R, 2018, URBAN CLIM, V24, P567, DOI 10.1016/j.uclim.2017.10.001
   Xia HP, 2022, REMOTE SENS ENVIRON, V273, DOI 10.1016/j.rse.2022.112972
   Yim SHL, 2019, J GEOPHYS RES-ATMOS, V124, P11568, DOI 10.1029/2019JD030562
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Zhang Y, 2019, INT J APPL EARTH OBS, V75, P171, DOI 10.1016/j.jag.2018.10.005
   [张勇 Zhang Yong], 2006, [遥感学报, Journal of Remote Sensing], V10, P789
   Zhao CH, 2020, GISCI REMOTE SENS, V57, P1083, DOI 10.1080/15481603.2020.1843869
   Zhao ZQ, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13214338
   Zheng YS, 2023, BUILD ENVIRON, V234, DOI 10.1016/j.buildenv.2023.110197
   Zhou XL, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100660
NR 56
TC 6
Z9 6
U1 7
U2 28
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2225-1154
J9 CLIMATE
JI Climate
PD JUL
PY 2023
VL 11
IS 7
AR 142
DI 10.3390/cli11070142
PG 23
WC Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Meteorology & Atmospheric Sciences
GA N1ZE1
UT WOS:001035068100001
OA gold
DA 2025-01-10
ER

PT J
AU Cloos, P
   Belloiseau, M
   Mc Pherson, N
   Harris-Glenville, F
   Joseph, DD
   Zinszer, K
AF Cloos, Patrick
   Belloiseau, Maeva
   Mc Pherson, Nickez
   Harris-Glenville, Fiona
   Joseph, Debra D.
   Zinszer, Kate
TI Discussing linkages between climate change, human mobility and health in
   the Caribbean: The case of Dominica. A qualitative study
SO JOURNAL OF CLIMATE CHANGE AND HEALTH
LA English
DT Article
DE Climate change; Health; Mental health; Migration; Human mobility;
   Caribbean; West indies
ID INEQUITIES
AB Introduction: The Caribbean region is repeatedly exposed to extreme climate-related events, such as hurricanes and tropical storms, which are expected to increase in severity with climate change. This study aims to better understand how extreme climate events affect human mobility, social circumstances, and healthrelated issues in the Eastern Caribbean, focusing more specifically on Dominica, a Small Island Developing State (SIDS). Methods: Semi-structured qualitative interviews were conducted with people who were internally displaced following an extreme climate event in Dominica, and with people who migrated from Dominica to Guadeloupe. Results: Mental health was a central issue discussed by participants. Some respondents raised issues regarding loss of livelihoods and poverty that affected their living conditions. For those who decided to migrate to Guadeloupe, the dif ficulties of getting migrant authorized status were very stressful. Other themes related to displacement trajectory, income, occupation, housing, access to food and water, health and psychosocial services, and the role of local and international assistance and social support and ties - that are well known social determinants of mental health, were raised by participants. Discussion and conclusion: Mental health and related determinants should be seen as a public health priority in Caribbean SIDS. Psycho-social interventions that focus on potential sources of vulnerabilities to mental health issues should be integrated in climate preparedness and response efforts. Otherwise, pre-existing social vulnerabilities may be aggravated, limiting the adaptation capacities of Caribbean SIDS to climate change. Public health and the health care system have a role to play in climate change adaptation. (c) 2023 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY-NCND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
C1 [Cloos, Patrick; Zinszer, Kate] Univ Montreal, Sch Publ Hlth ESPUM, Dept Social & Prevent Med, 7101 Ave Parc, Montreal, PQ H3N 1X9, Canada.
   [Belloiseau, Maeva; Harris-Glenville, Fiona] Univ West Indies, Fac Med Sci, Mona, Jamaica.
   [Mc Pherson, Nickez; Joseph, Debra D.] Univ West Indies Cave Hill, Dept Govt Sociol & Social Work, POB 64, BB-11000 Bridgetown, Barbados.
   [Cloos, Patrick] Univ Montreal, Sch Social Work, Montreal, PQ, Canada.
C3 Universite de Montreal; University West Indies Mona Jamaica; University
   West Indies Mona Jamaica; University West Indies Cave Hill Campus;
   Universite de Montreal
RP Cloos, P (corresponding author), Univ Montreal, Sch Publ Hlth ESPUM, Dept Social & Prevent Med, 7101 Ave Parc, Montreal, PQ H3N 1X9, Canada.; Cloos, P (corresponding author), Univ Montreal, Sch Social Work, Montreal, PQ, Canada.
EM Patrick.cloos@umontreal.ca
RI , Patrick Cloos/KHD-9628-2024
OI Cloos, Patrick/0000-0003-1508-1168
CR [Anonymous], 2013, Small Island Developing States
   [Anonymous], 2018, CLIMATE CHANGE HLTH
   [Anonymous], 2017, Dominica - Hurricane Maria response round 1
   [Anonymous], 2014, IPCC
   Baillat Alice, 2020, Rev Infirm, V69, P29, DOI 10.1016/S1293-8505(20)30183-4
   Bloemendaal N, 2022, SCI ADV, V8, DOI 10.1126/sciadv.abm8438
   Charles J, 2021, J CLIM CHANGE HEALTH, V4, DOI 10.1016/j.joclim.2021.100052
   Choi YJ, 2020, DISASTER MED PUBLIC, V14, P433, DOI 10.1017/dmp.2019.87
   Cloos P., 2022, Rev Liaison Energ-Francoph Internet, V110, P51
   Cloos P, 2017, Hurricane Maria assessment Dominica, P24
   Cloos P, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0231327
   Cloos P, 2018, LANCET PLANET HEALTH, V2, pE4, DOI 10.1016/S2542-5196(17)30176-6
   Duhaime AC, 2021, J CLIM CHANGE HEALTH, V4, DOI 10.1016/j.joclim.2021.100078
   Ebi KL, 2016, REV PANAM SALUD PUBL, V40, P181
   Fussell E, 2014, SOC SCI MED, V113, P137, DOI 10.1016/j.socscimed.2014.05.025
   Gautier L, 2020, J MIGRATION HEALTH, V1-2, DOI 10.1016/j.jmh.2020.100017
   Government of the Commonwealth of Dominica, Rapid Damage and Impact Assessment Tropical Storm Erika - August 27, 2015
   Inter-American Development Bank, Climate Change's Impact on the Caribbean's Ability to Sustain Tourism, Natural Assests and Livelihoods
   International Organization for Migration (IOM), 2017, IOM appeal: hurricane maria - Dominica
   Kelman I, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abe57d
   Knutson T, 2019, B AM METEOROL SOC, V100, P1987, DOI 10.1175/BAMS-D-18-0189.1
   Miles M. B., 1994, QUALITATIVE DATA ANA
   Pan American Health Organization, 2020, The burden of mental disorder in the americas: mental health country profile - Dominica
   Pan American Health Organization, 2019, Caribbean action plan on health and climate change
   Pan American Health Organization, HEALTH in the americas - Country Profile: dominica
   Pires A.P., 1997, RECHERCHE QUALITATIV, P113, DOI DOI 10.1522/030022877
   Ramphal Lilly, 2018, Proc (Bayl Univ Med Cent), V31, P294, DOI 10.1080/08998280.2018.1459399
   Riad JK, 1996, ENVIRON BEHAV, V28, P163, DOI 10.1177/0013916596282001
   Rock LF, 2018, ROUT INT HANDB, P144
   Schwerdtle P, 2018, BMC MED, V16, DOI 10.1186/s12916-017-0981-7
   Schwerdtle PN, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab9ece
   Serraglio D, 2021, Migration, environment, disaster and climate change data in the eastern caribbean. berlin
   Shields M, 2001, Health Rep, V13, P35
   The Government of the Commonwealth of Dominica, 2017, Post-Disaster needs assessment hurricane maria september 18
   Torres JM, 2017, BMC PUBLIC HEALTH, V17, DOI 10.1186/s12889-017-4508-0
   United Nations Children's Fund (UNICEF), 2019, Children uprooted in the caribbean. how stronger hurricanes linked to a changing climate are driving child displacement
   Wilhelmi OV, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014021
   World Health Organization, 2020, Health and climate change country profile 2020: dominica
NR 38
TC 3
Z9 3
U1 3
U2 3
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
EI 2667-2782
J9 J CLIM CHANGE HEALTH
JI J. Clim. Chang. Health
PD MAY-JUN
PY 2023
VL 11
AR 100237
DI 10.1016/j.joclim.2023.100237
PG 7
WC Environmental Sciences; Public, Environmental & Occupational Health
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health
GA YE8K1
UT WOS:001266898200002
OA gold
DA 2025-01-10
ER

PT J
AU Thevs, N
   Nowotny, R
AF Thevs, Niels
   Nowotny, Rainer
TI Water consumption of industrial hemp (Cannabis sativa L.) during dry
   growing seasons (2018-2022) in NE Germany
SO JOURNAL FUR KULTURPFLANZEN
LA English
DT Article
DE biomass; renewable raw material; water consumption; evapotranspiration;
   climate change adaptation; agriculture
ID LAND-SURFACE TEMPERATURE; DAILY EVAPOTRANSPIRATION; SIMPLE ALGORITHM;
   WINTER-WHEAT; AGRICULTURE; MANAGEMENT
AB Europe experienced unprecedented droughts during the years 2018, 2019, and 2020. In the course of climate change, it is expected that such drought events will occur more frequently so that agriculture needs to adapt to droughts. Hemp (Cannabis sativa L.) has been promoted as an adaptation to water limited conditions. Hemp delivers biomass as a raw material to a variety of different value chains, such as fibers and textiles, house construction, chemicals, or food applications.Hemp develops a deep root system, which enables it to cover its water demand even during longer dry periods. This may lead to an over exploitation of soil moisture of deeper soil layers or of the groundwater in the long-term. Against this background, this study assessed the water consumption of hemp in Northeastern Germany (region Uckermark) during the growing seasons 2018-2022. The Penman Monteith approach was used to calculate the water consumption, whereby the remote sensing based S-SEBI approach was employed, with Landsat satellite images as input data, to feed crop coefficients into those calculations.The water consumption of hemp ranged from 310 to 407 mm over the growing seasons 2018-2022, while stem yields were 9 t ha-1 (except 2018 with 7.8 t ha-1). This water consumption did exceed the precipitation during the growing seasons, but did not exceed the total precipitation of the given hydrological years so that growing hemp does not constitute an over -exploitation of water. Instead, hemp taps the soil moisture that has infiltrated into the soil during autumn and winter. This makes hemp a crop well suited for an adaptation to a drier, hotter, and more variable climate.
C1 [Thevs, Niels; Nowotny, Rainer] Hanffaser Uckermark, Prenzlau, Germany.
RP Thevs, N (corresponding author), Hanffaser Uckermark, Prenzlau, Germany.
EM niels.thevs@gmail.com
OI Thevs, Niels/0000-0003-1923-4280
CR Allen R. G., 2005, Irrigation and Drainage Systems, V19, P251, DOI 10.1007/s10795-005-5187-z
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Amaducci S., 2010, IND APPL NATURAL FIB, P109, DOI [10.1002/9780470660324.ch5, DOI 10.1002/9780470660324.CH5]
   Amt fur Statistik Berlin -Brandenburg, 2019, BES ERNT QUAL LAND B
   [Anonymous], 2019, Landsat 8 (L8) Data Users Handbook, LSDS-1574
   [Anonymous], 2002, Sebal Surface energy balance algorithms for land Idaho implementation Advanced Training and Users Manual
   Bastiaanssen WGM, 2000, AGR WATER MANAGE, V46, P137, DOI 10.1016/S0378-3774(00)00080-9
   Bastiaanssen WGM, 2005, J IRRIG DRAIN ENG, V131, P85, DOI 10.1061/(ASCE)0733-9437(2005)131:1(85)
   Bastiaanssen WGM, 1998, J HYDROL, V212, P198, DOI 10.1016/S0022-1694(98)00254-6
   Bastiaanssen WGM, 2002, WATER RESOUR RES, V38, DOI 10.1029/2001WR000386
   Bastiaanssen WGM, 1995, SC DLO
   Cammalleri C, 2012, J HYDROL, V452, P119, DOI 10.1016/j.jhydrol.2012.05.042
   Cosentino SL, 2013, IND CROP PROD, V50, P312, DOI 10.1016/j.indcrop.2013.07.059
   DWD, 2022, ABOUT US
   García-Tejero IF, 2014, J AGR SCI TECH-IRAN, V16, P887
   Ghavamsaeidi Noghabi S., 2021, J WATER RES AGR, V34, P563, DOI [10.22092/jwra.2021.122794, DOI 10.22092/JWRA.2021.122794]
   Gowda PH, 2007, T ASABE, V50, P1639, DOI 10.13031/2013.23964
   Gowda PH, 2008, IRRIGATION SCI, V26, P223, DOI 10.1007/s00271-007-0088-6
   Hari V, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-68872-9
   Hazaymeh K, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0117755
   Hochmuth H, 2015, ENVIRON EARTH SCI, V73, P5269, DOI 10.1007/s12665-014-3773-9
   Ingrao C, 2018, J CLEAN PROD, V204, P471, DOI 10.1016/j.jclepro.2018.09.068
   Knoblauch S., 2009, WASSERHAUSHALTSGROSS
   Kustas WP, 1996, HYDROLOG SCI J, V41, P495, DOI 10.1080/02626669609491522
   Li HJ, 2008, AGR WATER MANAGE, V95, P1271, DOI 10.1016/j.agwat.2008.05.003
   Liang SL, 2001, REMOTE SENS ENVIRON, V76, P213, DOI 10.1016/S0034-4257(00)00205-4
   Lisson S., 1998, Journal of the International Hemp Association, V5, P9
   Moscariello C, 2021, RESOUR CONSERV RECY, V175, DOI 10.1016/j.resconrec.2021.105864
   Muller J., 2009, Journal of Water and Land Development, P133, DOI 10.2478/v10025-010-0024-7
   Naumann G, 2021, NAT CLIM CHANGE, V11, P485, DOI 10.1038/s41558-021-01044-3
   Qu C, 2021, ISPRS J PHOTOGRAMM, V175, P431, DOI 10.1016/j.isprsjprs.2021.03.015
   Rakovec O, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002394
   Roerink GJ, 2000, PHYS CHEM EARTH PT B, V25, P147, DOI 10.1016/S1464-1909(99)00128-8
   Salehi H, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.795287
   Senay GB, 2007, SENSORS-BASEL, V7, P979, DOI 10.3390/s7060979
   Sobrino JA, 2007, REMOTE SENS ENVIRON, V110, P139, DOI 10.1016/j.rse.2007.02.017
   Sobrino JA, 2005, J HYDROL, V315, P117, DOI 10.1016/j.jhydrol.2005.03.027
   Struik PC, 2000, IND CROP PROD, V11, P107, DOI 10.1016/S0926-6690(99)00048-5
   Su Z, 2002, HYDROL EARTH SYST SC, V6, P85, DOI 10.5194/hess-6-85-2002
   Thevs N., 2022, CENTRAL ASIAN J WATE, V8, P19, DOI [10.29258/CAJWR/2022-R1.v8-2/19-30.eng, DOI 10.29258/CAJWR/2022-R1.V8-2/19-30.ENG]
   Thevs N, 2017, WATER-SUI, V9, DOI 10.3390/w9030207
   Thevs N, 2015, ENVIRON EARTH SCI, V73, P731, DOI 10.1007/s12665-014-3084-1
   Weng QH, 2014, REMOTE SENS ENVIRON, V145, P55, DOI 10.1016/j.rse.2014.02.003
   Zhao GH, 2020, SENSORS-BASEL, V20, DOI 10.3390/s20154337
NR 44
TC 1
Z9 1
U1 1
U2 8
PU Julius Kuhn Inst - JKI
PI Quedlinburg
PA Erwin-Baur-Str. 27, Quedlinburg, GERMANY
SN 1867-0911
EI 1867-0938
J9 J KULT
JI J. Kult.
PY 2023
VL 75
IS 7-8
BP 173
EP 184
DI 10.5073/JfK.2023.07-08.01
PG 12
WC Agronomy; Plant Sciences
WE Emerging Sources Citation Index (ESCI)
SC Agriculture; Plant Sciences
GA R1QG2
UT WOS:001062151000001
DA 2025-01-10
ER

PT J
AU Figueroa-Rangel, BL
   Olvera-Vargas, M
AF Lorena Figueroa-Rangel, Blanca
   Olvera-Vargas, Miguel
TI Environmental and spatial processes shaping <i>Quercus</i>-dominated
   forest communities in the Neotropics
SO ECOSPHERE
LA English
DT Article
DE community composition; elevation; maturity; Moran's eigenvector maps;
   Neotropics; Quercus forests; spatial analyses
ID OAK FORESTS; PHOSPHORUS; DIVERSITY; PATTERNS; BIODIVERSITY; TEMPERATE;
   FAGACEAE; TERNSTROEMIACEAE; TRANSFORMATIONS; CONSERVATION
AB Quercus-dominated forests in the Neotropics compose one of the broadest distributed ecosystems of mountainous zones whose species distribution has been explained by climate change adaptation over an abrupt physiography. This study aims to comprehend the contribution of environmental and spatial processes influential in species composition of Quercus-dominated forests. A database of 86 plots, randomly located in a highly diverse spot of the Mexican Neotropics, was examined; it involved vegetation, environment, and spatial data. Local spatial variables were derived from distance-based Moran's eigenvector maps, while regional spatial variables were obtained from geographical coordinates (latitude/longitude). Redundancy analysis and variance partitioning were run to reveal the relative importance of environmental and spatial processes explaining plant species composition of Quercus-dominated forests and ascertain the environmental variables controlling the species composition at the different spatial scales (local and regional). Results showed that both local and regional spatial variables significantly control species composition in Quercus-dominated forests, with the regional scale accounting for a higher explained variance than the local scale. At the regional scale, elevation, aspect, litter, maturity, and Mg were significant in explaining species community composition; elevation variance was twofold higher than variance for aspect and litter. At the local scale, elevation accounted for the highest variation followed by maturity, P, N, and Mg. The analysis also tested the variation of species community composition over environmental gradients mainly determined by elevation. This study indicated the importance of elevation at both local and regional spatial scales as an important driver in Quercus-dominated forests distribution, probably related to Quercus species adaptation to temperature and precipitation. Finally, evidence from this research emphasizes the significance and necessity of a multiscale analysis to discern the spatial structured environment responsible for the high species diversity and broad distribution of forests dominated by Quercus genus in the Neotropics.
C1 [Lorena Figueroa-Rangel, Blanca; Olvera-Vargas, Miguel] Univ Guadalajara, Dept Ecol & Recursos Nat, Ctr Univ Costa Sur, Autlan De Navarro, Mexico.
C3 Universidad de Guadalajara
RP Figueroa-Rangel, BL (corresponding author), Univ Guadalajara, Dept Ecol & Recursos Nat, Ctr Univ Costa Sur, Autlan De Navarro, Mexico.
EM bfrangel@cucsur.udg.mx
RI Olvera-Vargas, Miguel/I-3917-2019; Figueroa-Rangel, Blanca
   Lorena/B-6858-2008
OI Olvera-Vargas, Miguel/0000-0002-7290-1639; Figueroa-Rangel, Blanca
   Lorena/0000-0002-5869-5277
FU Universidad de Guadalajara
FX Universidad de Guadalajara
CR Aguilar-Romero R, 2016, BOT SCI, V94, P471, DOI 10.17129/botsci.620
   Alcántara-Ayala O, 2020, PEERJ, V8, DOI 10.7717/peerj.8307
   Alfaro-Reyna T, 2020, EUR J FOREST RES, V139, P179, DOI 10.1007/s10342-020-01258-8
   Anderson MJ, 2006, ECOL LETT, V9, P683, DOI 10.1111/j.1461-0248.2006.00926.x
   Anderson MJ, 2006, BIOMETRICS, V62, P245, DOI 10.1111/j.1541-0420.2005.00440.x
   [Anonymous], 1996, SITIOS PERMANENTES I
   [Anonymous], 1993, AGROCIENCIA-MEXICO
   [Anonymous], 2016, BASE CATIONS FOREST
   Encina-Domínguez JA, 2018, TURK J AGRIC FOR, V42, P262, DOI 10.3906/tar-1711-31
   Arenas-Navarro M, 2020, BOT SCI, V98, P219, DOI 10.17129/botsci.2398
   Benz Bruce F., 1996, SIDA Contributions to Botany, V17, P1
   Bobbink R, 1998, J ECOL, V86, P717, DOI 10.1046/j.1365-2745.1998.8650717.x
   Bölöni J, 2021, FOREST ECOL MANAG, V500, DOI 10.1016/j.foreco.2021.119629
   Borcard D, 2011, USE R, P1, DOI 10.1007/978-1-4419-7976-6
   Brödlin D, 2019, FRONT FOR GLOB CHANG, V2, DOI 10.3389/ffgc.2019.00066
   Bünemann EK, 2016, SOIL BIOL BIOCHEM, V101, P85, DOI 10.1016/j.soilbio.2016.07.005
   Cerano-Paredes J, 2015, BOSQUE, V36, P41, DOI 10.4067/S0717-92002015000100005
   Crous KY, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00664
   de la Riva EG, 2019, ECOSISTEMAS, V28, P199, DOI 10.7818/ECOS.1803
   Denk T, 2017, TREE PHYSIOL-NETH, V7, P13, DOI 10.1007/978-3-319-69099-5_2
   Dray S, 2012, ECOL MONOGR, V82, P257, DOI 10.1890/11-1183.1
   Dray S, 2006, ECOL MODEL, V196, P483, DOI 10.1016/j.ecolmodel.2006.02.015
   Edler D, 2017, SYST BIOL, V66, P197, DOI 10.1093/sysbio/syw087
   Etherington J., 1987, J ECOL, V75, P283
   Ferrier S, 2007, DIVERS DISTRIB, V13, P252, DOI 10.1111/j.1472-4642.2007.00341.x
   Figueroa-Rangel BL., 2020, NEOTROPICAL DIVERSIF, P449, DOI [10.1007/978-3-030-31167-4_17, DOI 10.1007/978-3-030-31167-4_17]
   Gil-Pelegrín E, 2017, TREE PHYSIOL-NETH, V7, P1, DOI 10.1007/978-3-319-69099-5_1
   Giorgetta MA, 2013, J ADV MODEL EARTH SY, V5, P572, DOI 10.1002/jame.20038
   Gonzaalez-Espinosa M., 2011, The red list of Mexican cloud forest trees
   Gravel D, 2006, ECOL LETT, V9, P399, DOI 10.1111/j.1461-0248.2006.00884.x
   Gual-Diaz M., 2014, BOSQUES MES FILOS MO
   Hernandez Vargas G., 2000, Madera y Bosques, V6, P13
   Hipp AL, 2018, NEW PHYTOL, V217, P439, DOI 10.1111/nph.14773
   Hong D. Y., 2013, PLANTS CHINA COMPANI
   Hubbell Stephen P., 2001, V32, pi
   Johnson P. S., 2009, The ecology and silviculture of oaks, DOI 10.1079/9781845934743.0000
   Kabrick J. M., 2004, General Technical Report - Southern Research Station, USDA Forest Service, P94
   Kabrick JM, 2011, SOIL SCI SOC AM J, V75, P164, DOI 10.2136/sssaj2009.0382
   Krasilnikov P., 2013, The soils of Mexico
   Lang F, 2017, BIOGEOCHEMISTRY, V136, P5, DOI 10.1007/s10533-017-0375-0
   Legendre P, 2001, OECOLOGIA, V129, P271, DOI 10.1007/s004420100716
   LEGENDRE P, 1993, ECOLOGY, V74, P1659, DOI 10.2307/1939924
   Lopez-Binnquist C., 2021, SISTEMAS AGROFORESTA
   Sabás-Rosales JL, 2015, BOT SCI, V93, P881, DOI 10.17129/botsci.205
   Santiago-Pérez AL, 2009, B SOC BOT MEX, V85, P31
   Luna-Vega I, 2012, BOTANY, V90, P637, DOI [10.1139/b2012-019, 10.1139/B2012-019]
   Manos PS, 2021, FORESTS, V12, DOI 10.3390/f12060786
   Manos PS, 2001, INT J PLANT SCI, V162, pS77, DOI 10.1086/323280
   Martin MP, 2021, ECOSPHERE, V12, DOI 10.1002/ecs2.3475
   Mitchell PL., 1993, USE HEMISPHERICAL PH
   Mölder A, 2019, FOREST ECOL MANAG, V437, P324, DOI 10.1016/j.foreco.2019.01.006
   Morales Pacheco JF, 2018, BOLET N ASOCIACI N G, V79, P1, DOI DOI 10.1006/fgbi.2000.1228
   Nixon K.C., 1997, Flora of North America Editorial Committee, V3
   NIXON KC, 2006, ECOLOGY CONSERVATION, P3, DOI DOI 10.1007/3-540-28909-7_1
   Olvera-Vargas M., 2012, Ecosistemas, V21, P74
   Olvera-Vargas M.., 2006, SPATIO TEMPORAL DYNA
   Olvera-Vargas M, 2018, MADERA BOSQUES, V24, DOI 10.21829/myb.2018.2431412
   Olvera-Vargas M, 2015, INTERCIENCIA, V40, P233
   Olvera-Vargas M, 2014, ECOL RES, V29, P711, DOI 10.1007/s11284-014-1163-0
   Olvera-Vargas M, 2010, PLANT ECOL, V211, P321, DOI 10.1007/s11258-010-9792-z
   Oyama K, 2018, TROP CONSERV SCI, V11, DOI 10.1177/1940082918766195
   Peres-Neto PR, 2006, ECOLOGY, V87, P2614, DOI 10.1890/0012-9658(2006)87[2614:VPOSDM]2.0.CO;2
   *R COR TEAM, 2021, A LANGUAGE ENV STAT
   RAO IM, 1995, PLANT PHYSIOL, V107, P1313, DOI 10.1104/pp.107.4.1313
   Reich PB, 2008, ECOL LETT, V11, P793, DOI 10.1111/j.1461-0248.2008.01185.x
   Rzedowski J., 2006, Vegetacion de Mexico, VFirst
   Sanchez-Rodriguez EV., 2003, Boletin de la Sociedad Botanica de Mexico, V73, P17, DOI DOI 10.17129/B0TSCI.1676
   Sandoval-García R, 2020, ACTA BOT MEX, V127, DOI 10.21829/abm127.2020.1627
   Shiau YJ, 2018, FORESTS, V9, DOI 10.3390/f9060294
   Turner BL, 2007, ECOSYSTEMS, V10, P1166, DOI 10.1007/s10021-007-9086-z
   Uribe-Salas D., 2018, ASPECTOS BIOGEOGR FI
   Valencia-A S, 2014, BOT SCI, V92, P193, DOI 10.17129/botsci.45
   Vega IL, 2004, BIODIVERS CONSERV, V13, P2723, DOI 10.1007/s10531-004-2145-2
   WALKER TW, 1976, GEODERMA, V15, P1, DOI 10.1016/0016-7061(76)90066-5
   Zheng XF, 2017, FORESTS, V8, DOI 10.3390/f8110460
NR 75
TC 1
Z9 1
U1 1
U2 9
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2150-8925
J9 ECOSPHERE
JI Ecosphere
PD JUN
PY 2022
VL 13
IS 6
AR e4103
DI 10.1002/ecs2.4103
PG 15
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 1W1ED
UT WOS:000806522000001
OA gold
DA 2025-01-10
ER

PT J
AU Tubi, A
AF Tubi, Amit
TI Recurring droughts or social shifts? Exploring drivers of large-scale
   transformations in a transformed country
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Transformation; Adaptation; Climate change; Drought; Water resources;
   Agriculture
ID GLOBAL ENVIRONMENTAL-CHANGE; CLIMATE-CHANGE ADAPTATION; WATER SCARCITY;
   POLICY; DESALINATION; GOVERNANCE; CHALLENGES; RESPONSES; PATHWAYS;
   LESSONS
AB As climate change intensifies, the need for large-scale transformations that reform vulnerable systems' prevailing values and development pathways is increasingly recognized. However, there is limited understanding of the factors that underlie such changes. This study sheds light on these factors by examining the case of Israel - a largely arid to semi-arid country with highly scarce natural water resources and a historical rural-agricultural ideology. Adopting an historically-informed systems perspective, I analyze two transformations that diminished Israel's vulnerability to recurring droughts: the 1960s' economic transformation from agriculture to industry, and the shift to seawater desalination in the mid-2000s. These changes are examined using causal-loop diagrams based on multiple data sources, including archival records, statistical reports and a systematic review of grey and academic literature.
   The findings show that both transformations, instigated by state institutions during exceptionally severe droughts, were driven by shifts away from development paradigms embedded in the nation-building ideology, as well as by social stresses that exceeded the natural limits of the agricultural system and water supply system. Repeated drought shocks activated and later reactivated the shift to desalination, intended to a certain degree to reduce drought vulnerability. However, drought did not significantly affect the economic transformation, initiated mainly due to saturation in agricultural development. Thus, I argue that alongside concerted adaptation efforts state institutions should dedicate greater attention to the management of broader social challenges and crises in a manner that fosters greater resilience against future climate changes. Ideological shifts and consequent restructuring of development paths, as well as the interaction between population growth and limited natural resources, may constitute important entry points. These entry points are particularly pertinent to emerging economies in other dry areas, many of which face similar social and economic trends to those experienced in Israel over the last decades.
C1 [Tubi, Amit] Hebrew Univ Jerusalem, Dept Geog, IL-9190501 Jerusalem, Israel.
C3 Hebrew University of Jerusalem
RP Tubi, A (corresponding author), Hebrew Univ Jerusalem, Dept Geog, IL-9190501 Jerusalem, Israel.
EM amit.tubi@mail.huji.ac.il
OI Tubi, Amit/0000-0002-4523-9141
CR Adamson GCD, 2018, GLOBAL ENVIRON CHANG, V48, P195, DOI 10.1016/j.gloenvcha.2017.12.003
   [Anonymous], 2012, SPECIAL REPORT WORKI
   [Anonymous], 2018, MET DAT
   [Anonymous], 2013, WATER POLICY ISRAEL
   Arlozorov S., 1999, Towards Sustainable Development'Ll, P51
   Bai XM, 2016, GLOBAL ENVIRON CHANG, V39, P351, DOI 10.1016/j.gloenvcha.2015.09.017
   Bank of Israel, 1962, ANN REPORT AGR
   Barlow M, 2016, J CLIMATE, V29, P8547, DOI 10.1175/JCLI-D-13-00692.1
   Barnett J, 2014, NAT CLIM CHANGE, V4, P1103, DOI 10.1038/NCLIMATE2383
   Berbel J, 2019, GLOBAL ENVIRON CHANG, V58, DOI 10.1016/j.gloenvcha.2019.101969
   BERNSTEIN D, 1982, BRIT J SOCIOL, V33, P64, DOI 10.2307/589337
   Chapin FS, 2010, TRENDS ECOL EVOL, V25, P241, DOI 10.1016/j.tree.2009.10.008
   Clarke V, 2017, J POSIT PSYCHOL, V12, P297, DOI 10.1080/17439760.2016.1262613
   Colloff MJ, 2017, ENVIRON SCI POLICY, V68, P87, DOI 10.1016/j.envsci.2016.11.007
   Denton F, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1101
   Dilling L, 2019, CLIM RISK MANAG, V23, P32, DOI 10.1016/j.crm.2018.11.001
   DON Y, 1977, SOCIOL RURALIS, V17, P59, DOI 10.1111/j.1467-9523.1977.tb00852.x
   Dowd AM, 2014, NAT CLIM CHANGE, V4, P558, DOI [10.1038/NCLIMATE2275, 10.1038/nclimate2275]
   Eklund L, 2017, ECOL SOC, V22, DOI [10.5751/ES-09179-220409, 10.5751/es-09179-220409]
   Farla J, 2012, TECHNOL FORECAST SOC, V79, P991, DOI 10.1016/j.techfore.2012.02.001
   Fazey I, 2016, CLIM DEV, V8, P26, DOI 10.1080/17565529.2014.989192
   Fazey I, 2011, GLOBAL ENVIRON CHANG, V21, P1275, DOI 10.1016/j.gloenvcha.2011.07.006
   Fedele G, 2019, ENVIRON SCI POLICY, V101, P116, DOI 10.1016/j.envsci.2019.07.001
   Feitelson E, 2017, GLOBAL ENVIRON CHANG, V44, P39, DOI 10.1016/j.gloenvcha.2017.03.001
   Feitelson E, 2012, GEOFORUM, V43, P272, DOI 10.1016/j.geoforum.2011.08.011
   Feola G, 2015, AMBIO, V44, P376, DOI 10.1007/s13280-014-0582-z
   Few R, 2017, PALGR COMMUN, V3, DOI 10.1057/palcomms.2017.92
   Folke C, 2010, ECOL SOC, V15, DOI 10.5751/es-03610-150420
   Fook TCT, 2017, CLIM DEV, V9, P5, DOI 10.1080/17565529.2015.1086294
   GALNOOR I, 1978, POLICY ANAL, V4, P339
   Garcia M, 2019, GLOBAL ENVIRON CHANG, V58, DOI 10.1016/j.gloenvcha.2019.101967
   Gelcich S, 2010, P NATL ACAD SCI USA, V107, P16794, DOI 10.1073/pnas.1012021107
   Gillard R, 2016, WIRES CLIM CHANGE, V7, P251, DOI 10.1002/wcc.384
   Gilmont M, 2018, LAND-BASEL, V7, DOI 10.3390/land7020063
   Gilmont M, 2014, WATER POLICY, V16, P79, DOI 10.2166/wp.2013.171
   Gosnell H, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101965
   Greve P, 2018, NAT SUSTAIN, V1, P486, DOI 10.1038/s41893-018-0134-9
   Halperin H., 1957, CHANGING PATTERNS IS
   Hananel R, 2010, LAND USE POLICY, V27, P1160, DOI 10.1016/j.landusepol.2010.03.006
   Hermans K, 2019, REG ENVIRON CHANGE, V19, P1101, DOI 10.1007/s10113-019-01473-z
   Huang JP, 2017, NAT CLIM CHANGE, V7, P417, DOI [10.1038/nclimate3275, 10.1038/NCLIMATE3275]
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Israel Central Bureau of Statistics, 2007, ISR STAT 1974 2008
   Israel Central Bureau of Statistics, 2013, AGR ISR SECT REP
   Israel Central Bureau of Statistics, 1964, ANN STAT YB
   Israel Water Authority, 2010, REP WAT AUTH ACT 200
   Israel Water Authority, 2012, NAT MAST ISR WAT E A
   Israel Water Authority, 2009, The Issue of Water between Israel and the Palestinians
   Israel Water Authority, 2018, WAT CONS 2018 SUMM R
   Jackson RC, 2018, GLOBAL ENVIRON CHANG, V52, P58, DOI 10.1016/j.gloenvcha.2018.05.006
   Jakku E, 2016, CLIMATIC CHANGE, V137, P557, DOI 10.1007/s10584-016-1698-x
   Kahil MT, 2015, J HYDROL, V522, P95, DOI 10.1016/j.jhydrol.2014.12.042
   Karthe D, 2015, ENVIRON EARTH SCI, V73, P487, DOI 10.1007/s12665-014-3789-1
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Katz D, 2016, WATER-SUI, V8, DOI 10.3390/w8040159
   Kelley CP, 2015, P NATL ACAD SCI USA, V112, P3241, DOI 10.1073/pnas.1421533112
   Kingdon JW, 1995, Agendas, alternatives and public policies, V2nd
   Knesset, 2018, ISR WAT EC MAIN ISS
   Knesset, 2009, SEAW DES ISR GOV DEC
   Leichenko R., 2015, J EXTR EVEN, P1550002, DOI DOI 10.1142/S2345737615500025
   Leichenko R., 2019, CLIMATE SOC TRANSFOR
   Linnér BO, 2020, ENVIRON SCI POLICY, V106, P221, DOI 10.1016/j.envsci.2020.01.007
   Lipchin C, 2007, NATO SCI PEACE SECUR, P251, DOI 10.1007/978-1-4020-5986-5_11
   Loorbach D, 2017, ANNU REV ENV RESOUR, V42, P599, DOI 10.1146/annurev-environ-102014-021340
   Maman D, 2012, STUD COMP INT DEV, V47, P342, DOI 10.1007/s12116-012-9098-3
   Manuel-Navarrete D, 2015, GLOBAL ENVIRON CHANG, V35, P558, DOI 10.1016/j.gloenvcha.2015.08.012
   Maron Asa., 2017, NEOLIBERALISM STATE
   Moore ML, 2014, ECOL SOC, V19, DOI 10.5751/ES-06966-190454
   Morag N, 2001, MIDDLE EASTERN STUD, V37, P179, DOI 10.1080/714004411
   Nalau J, 2015, ENVIRON SCI POLICY, V54, P349, DOI 10.1016/j.envsci.2015.07.022
   National Inquiry Commission, 2010, REP MAN ISR WAT RES
   Neori A, 2019, J COASTAL RES, P11, DOI 10.2112/SI86-003.1
   Newell B, 2011, ECOL SOC, V16
   Nursey-Bray M, 2017, LOCAL ENVIRON, V22, P156, DOI 10.1080/13549839.2016.1181618
   O'Brien K, 2013, ANNU REV ENV RESOUR, V38, P373, DOI 10.1146/annurev-environ-032112-100655
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   Otero I, 2017, GEOFORUM, V85, P234, DOI 10.1016/j.geoforum.2017.07.020
   Panda A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.520
   Park SE, 2012, GLOBAL ENVIRON CHANG, V22, P115, DOI 10.1016/j.gloenvcha.2011.10.003
   Parsons M, 2019, GLOBAL ENVIRON CHANG, V56, P95, DOI 10.1016/j.gloenvcha.2019.03.008
   Parsons M, 2016, GLOBAL ENVIRON CHANG, V38, P82, DOI 10.1016/j.gloenvcha.2016.01.010
   Patterson J, 2017, ENVIRON INNOV SOC TR, V24, P1, DOI 10.1016/j.eist.2016.09.001
   Pelling M, 2011, ECOL SOC, V16
   Proust K., 2020, CONSTRUCTING INFLUEN
   RAZIN E, 1987, URBAN STUD, V24, P296, DOI 10.1080/00420988720080471
   REICHMAN S, 1990, LAND BECAME ISRAEL S, P320
   Rippke U, 2016, NAT CLIM CHANGE, V6, P605, DOI [10.1038/nclimate2947, 10.1038/NCLIMATE2947]
   Rosenzweig C, 2014, GLOBAL ENVIRON CHANG, V28, P395, DOI 10.1016/j.gloenvcha.2014.05.003
   Sahin O, 2015, WATER RESOUR MANAG, V29, P253, DOI 10.1007/s11269-014-0794-9
   Schmidt TS, 2017, NAT ENERGY, V2, DOI 10.1038/nenergy.2017.84
   Selzer A., 2010, MEKOROT STORY ISRAEL
   Shafir G., 2009, 2009 DECLARED DROUGH
   Shohami D, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2011JD016004
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Solecki W, 2018, NAT CLIM CHANGE, V8, P177, DOI 10.1038/s41558-018-0101-5
   Sowers J, 2011, CLIMATIC CHANGE, V104, P599, DOI 10.1007/s10584-010-9835-4
   State Comptroller, 1990, REPORT MANAGEMENT WA
   Tal A, 2007, AGR HIST, V81, P228, DOI 10.3098/ah.2007.81.2.228
   Tenne A., 2010, Sea Water Desalination in Israel: Planning, coping with difficulties, and economic aspects of long-term risks
   Teschner N, 2013, ENVIRON POLICY GOV, V23, P91, DOI 10.1002/eet.1607
   Thomas DSG, 2005, GLOBAL ENVIRON CHANG, V15, P115, DOI 10.1016/j.gloenvcha.2004.10.001
   Thurstan RH, 2020, GLOBAL ENVIRON CHANG, V61, DOI 10.1016/j.gloenvcha.2020.102058
   Toledano M, 2009, PUBLIC RELAT REV, V35, P361, DOI 10.1016/j.pubrev.2009.08.007
   Tubi A, 2016, POLIT GEOGR, V51, P30, DOI 10.1016/j.polgeo.2015.11.009
   Ulibarri N, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.102005
   Waha K, 2017, REG ENVIRON CHANGE, V17, P1623, DOI 10.1007/s10113-017-1144-2
   Walker B, 2004, ECOL SOC, V9
   Wiering M, 2017, GLOBAL ENVIRON CHANG, V44, P15, DOI 10.1016/j.gloenvcha.2017.02.006
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
   World Bank, 2006, WAT RES MAN AR ENV C
   Yang H, 2002, WORLD DEV, V30, P1413, DOI 10.1016/S0305-750X(02)00047-5
   Ziv B, 2014, REG ENVIRON CHANGE, V14, P1751, DOI 10.1007/s10113-013-0414-x
NR 112
TC 5
Z9 5
U1 0
U2 20
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD NOV
PY 2020
VL 65
AR 102157
DI 10.1016/j.gloenvcha.2020.102157
PG 12
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA PL0JP
UT WOS:000602819700009
DA 2025-01-10
ER

PT C
AU Elagiry, M
   Kraus, F
   Scharf, B
   Costa, A
   De Lotto, R
AF Elagiry, Mohamed
   Kraus, Florian
   Scharf, Bernhard
   Costa, Andrea
   De Lotto, Roberto
BE Corrado, V
   Fabrizio, E
   Gasparella, A
   Patuzzi, F
TI Nature4Cities: Nature-Based Solutions and Climate Resilient Urban
   Planning and Modelling with GREENPASS® - A Case Study in
   Segrate/Milano/IT
SO PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA
SE Building Simulation Conference Proceedings
LA English
DT Proceedings Paper
CT 16th Conference of the
   International-Building-Performance-Simulation-Association (IBPSA)
CY SEP 02-04, 2019
CL Rome, ITALY
SP Int Bldg Performance Simulat Assoc
AB Beyond doubt, climate-sensitive urban planning and architecture have to be considered in urban development and retrofitting process, to counteract to current urban challenges, like climate change adaptation, water management, air pollution and many more.
   In line with that, the municipality of Segrate and cities all over the world need an easy-to-use, fact-based and in planning processes integrable decision support regarding urban challenges, to apply climate-resilient urban planning and architecture and to finally achieve a higher quality of life for current and future conditions.
   Microclimate simulations exist since more than 20 years but are very complex and scientific systems to use in daily practical world of urban planning and architecture.
   The innovative GREENPASS (R) technology combines first time (ENVI-met) microclimatic simulation and evaluation analysis with complex numerical resources and cost calculations in a standardized and transparent way - applicable by common architects and urban planners. It provides the relevant information for decision making in planning processes regarding the urban challenges: climate, water, air, biodiversity, energy and cost. The easy-to-use software tool allows to compare different designs for one urban development areas, moreover, comparison of different projects based on the unique set of Key Performance Indicators (KPIs) for planning, evaluation, optimization and certification of projects (Kraus et al. 2019, Scharf 2018).
   For the Case Study areas, a selected set of KPIs got applied, including following meaningful indicators: TCS (Thermal Comfort Score), PET (Physiological Equivalent Temperature - Thermal performance), AT (Air temperature), RH (Relative humidity) and WF (Wind flow).
   The results show potential thermal outdoor hot spots within the areas, will give information about the human temperature behaviour and the wind flow of the areas. The final output are easily understandable thermal image maps and meaningful scores, shown by extracted results for the thermal performance of the areas.
C1 [Elagiry, Mohamed; Costa, Andrea] R2M Solut, Pavia, Italy.
   [Kraus, Florian; Scharf, Bernhard] GREENPASS GmbH, Vienna, Austria.
   [De Lotto, Roberto] Univ Pavia, Pavia, Italy.
C3 University of Pavia
RP Elagiry, M (corresponding author), R2M Solut, Pavia, Italy.
RI ELAGIRY, Mohamed/C-8625-2019
CR [Anonymous], 2016, URBAN EUROPE STAT CI, DOI [10.2785/91120, DOI 10.2785/91120]
   [Anonymous], 2016, Establishing the Urban Agenda for the EU
   Tuan DV, 2017, PHYS REV X, V7, DOI 10.1103/PhysRevX.7.041040
   ERA-SME R&D project, 2011, PROGR AD STADT URB H
   ERA-SME R&D project, 2012, GREEN4CITIES DEV EV
   GP.me, 2015, VIENN BUS AG GREENPA
   Kraus F., 2017, GREENPASS METH PAN E
   Kraus F., 2019, GEOPH RES ABSTR, V21
   Scharf B., 2018, COOLE STADTE PLANEN
NR 9
TC 0
Z9 0
U1 2
U2 7
PU INT BUILDING PERFORMANCE SIMULATION ASSOC-IBPSA
PI TORONTO
PA C/O MILLER-THOMPSON, 40 KING ST W, STE 5800, TORONTO, M5H 3S1, CANADA
SN 2522-2708
BN 978-1-7750520-1-2
J9 BUILD SIMUL CONF PR
PY 2020
BP 2699
EP 2706
DI 10.26868/25222708.2019.211002
PG 8
WC Construction & Building Technology; Operations Research & Management
   Science
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Construction & Building Technology; Operations Research & Management
   Science
GA BS3CE
UT WOS:000709431302099
OA Bronze
DA 2025-01-10
ER

PT J
AU Smith, P
   Calvin, K
   Nkem, J
   Campbell, D
   Cherubini, F
   Grassi, G
   Korotkov, V
   Hoang, AL
   Lwasa, S
   McElwee, P
   Nkonya, E
   Saigusa, N
   Soussana, JF
   Taboada, MA
   Manning, FC
   Nampanzira, D
   Arias-Navarro, C
   Vizzarri, M
   House, J
   Roe, S
   Cowie, A
   Rounsevell, M
   Arneth, A
AF Smith, Pete
   Calvin, Katherine
   Nkem, Johnson
   Campbell, Donovan
   Cherubini, Francesco
   Grassi, Giacomo
   Korotkov, Vladimir
   Anh Le Hoang
   Lwasa, Shuaib
   McElwee, Pamela
   Nkonya, Ephraim
   Saigusa, Nobuko
   Soussana, Jean-Francois
   Angel Taboada, Miguel
   Manning, Frances C.
   Nampanzira, Dorothy
   Arias-Navarro, Cristina
   Vizzarri, Matteo
   House, Jo
   Roe, Stephanie
   Cowie, Annette
   Rounsevell, Mark
   Arneth, Almut
TI Which practices co-deliver food security, climate change mitigation and
   adaptation, and combat land degradation and desertification?
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE adaptation; adverse side effects; co-benefits; demand management;
   desertification; food security; land degradation; land management;
   mitigation; practice; risk management
ID GREENHOUSE-GAS MITIGATION; FEDERAL CROP INSURANCE; SOIL CARBON
   SEQUESTRATION; LIFE-CYCLE ASSESSMENT; ORGANIC-CARBON; NEGATIVE
   EMISSIONS; LIVESTOCK SYSTEMS; URBAN SPRAWL; AIR-QUALITY; AGRICULTURAL
   SUSTAINABILITY
AB There is a clear need for transformative change in the land management and food production sectors to address the global land challenges of climate change mitigation, climate change adaptation, combatting land degradation and desertification, and delivering food security (referred to hereafter as "land challenges"). We assess the potential for 40 practices to address these land challenges and find that: Nine options deliver medium to large benefits for all four land challenges. A further two options have no global estimates for adaptation, but have medium to large benefits for all other land challenges. Five options have large mitigation potential (>3 Gt CO(2)eq/year) without adverse impacts on the other land challenges. Five options have moderate mitigation potential, with no adverse impacts on the other land challenges. Sixteen practices have large adaptation potential (>25 million people benefit), without adverse side effects on other land challenges. Most practices can be applied without competing for available land. However, seven options could result in competition for land. A large number of practices do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at a large scale, though the impact is scale and context specific, highlighting the need for safeguards to ensure that expansion of land for mitigation does not impact natural systems and food security. A number of practices, such as increased food productivity, dietary change and reduced food loss and waste, can reduce demand for land conversion, thereby potentially freeing-up land and creating opportunities for enhanced implementation of other practices, making them important components of portfolios of practices to address the combined land challenges.
C1 [Smith, Pete; Manning, Frances C.] Univ Aberdeen, Inst Biol & Environm Sci, Aberdeen, Scotland.
   [Calvin, Katherine] Pacific Northwest Natl Lab, Joint Global Change Res Inst, College Pk, MD USA.
   [Nkem, Johnson] United Nations Econ Commiss Africa, Addis Ababa, Ethiopia.
   [Campbell, Donovan] Univ West Indies, Mona, Jamaica.
   [Cherubini, Francesco] Norwegian Univ Sci & Technol NTNU, Dept Energy & Proc Engn, Ind Ecol Programme, Trondheim, Norway.
   [Grassi, Giacomo; Vizzarri, Matteo] European Commiss, Joint Res Ctr, Ispra, Italy.
   [Korotkov, Vladimir] Yu A Izrael Inst Global Climate & Ecol, Moscow, Russia.
   [Anh Le Hoang] Minist Agr & Rural Dev MARD, Hanoi, Vietnam.
   [Lwasa, Shuaib] Makerere Univ, Dept Geog, Kampala, Uganda.
   [McElwee, Pamela] Rutgers State Univ, Dept Human Ecol, New Brunswick, NJ USA.
   [Nkonya, Ephraim] IFPRI, Washington, DC USA.
   [Saigusa, Nobuko] Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki, Japan.
   [Soussana, Jean-Francois; Arias-Navarro, Cristina] French Natl Inst Agr Environm & Food Res INRA, Paris, France.
   [Angel Taboada, Miguel] Natl Agr Technol Inst INTA, Nat Resources Res Ctr CIRN, Inst Soils, Buenos Aires, DF, Argentina.
   [Nampanzira, Dorothy] Makerere Univ, Dept Livestock & Ind Resources, Kampala, Uganda.
   [House, Jo] Univ Bristol, Sch Geog Sci, Bristol, Avon, England.
   [Roe, Stephanie] Univ Virginia, Dept Environm Sci, Charlottesville, VA USA.
   [Roe, Stephanie] Climate Focus, Berlin, Germany.
   [Cowie, Annette] Univ New England, Livestock Ind Ctr, DPI Agr, NSW Dept Primary Ind, Armidale, NSW, Australia.
   [Rounsevell, Mark; Arneth, Almut] Karlsruhe Inst Technol, Atmospher Environm Res, IMK IFU, Garmisch Partenkirchen, Germany.
   [Rounsevell, Mark] Univ Edinburgh, Inst Geog, Edinburgh, Midlothian, Scotland.
C3 University of Aberdeen; United States Department of Energy (DOE);
   Pacific Northwest National Laboratory; University West Indies Mona
   Jamaica; Norwegian University of Science & Technology (NTNU); European
   Commission Joint Research Centre; EC JRC ISPRA Site; Makerere
   University; Rutgers University System; Rutgers University New Brunswick;
   CGIAR; International Food Policy Research Institute (IFPRI); National
   Institute for Environmental Studies - Japan; INRAE; Instituto Nacional
   de Tecnologia Agropecuaria (INTA); Makerere University; University of
   Bristol; University of Virginia; Department of Primary Industries &
   Regional Development NSW; University of New England; Helmholtz
   Association; Karlsruhe Institute of Technology; University of Edinburgh
RP Smith, P (corresponding author), Univ Aberdeen, Inst Biol & Environm Sci, Aberdeen, Scotland.
EM pete.smith@abdn.ac.uk
RI Roe, Stephanie/KGL-4255-2024; Rounsevell, Mark/AAC-4498-2021; Vizzarri,
   Matteo/H-9544-2019; Cherubini, Francesco/AFS-6064-2022; Nampanzira,
   Dorothy/GSM-9631-2022; Lwasa, Shuaib/G-3723-2014; McElwee,
   Pamela/AAP-1695-2020; Calvin, Katherine/ADF-2443-2022; Arias-Navarro,
   Cristina/AAC-3341-2019; Soussana, Jean-Francois/KAM-4127-2024; Arneth,
   Almut/B-2702-2013; Smith, Pete/G-1041-2010; Korotkov,
   Vladimir/E-4849-2014; Arias-Navarro, Cristina/N-5216-2017; McElwee,
   Pamela/A-9442-2009; Soussana, Jean-Francois/P-2094-2016; Lwasa,
   Shuaib/E-8840-2013; Cowie, Annette/E-1485-2016; House,
   Joanna/B-6477-2016
OI Smith, Pete/0000-0002-3784-1124; Arneth, Almut/0000-0001-6616-0822; Roe,
   Stephanie/0000-0002-3821-6435; Cherubini, Francesco/0000-0002-7147-4292;
   Rounsevell, Mark/0000-0001-7476-9398; Korotkov,
   Vladimir/0000-0002-1367-2303; Arias-Navarro,
   Cristina/0000-0002-5125-4962; McElwee, Pamela/0000-0003-3525-9285;
   Vizzarri, Matteo/0000-0002-9505-783X; Manning,
   Frances/0000-0002-4535-5900; Soussana,
   Jean-Francois/0000-0002-1932-6583; Lwasa, Shuaib/0000-0003-4312-2836;
   Cowie, Annette/0000-0002-3858-959X; House, Joanna/0000-0003-4576-3960
FU UKRI [NE/M021327/1, EP/M013200/1, NE/M016900/1]; UKERC [NE/P019455/1,
   BB/N013484/1]; European Union [774378, 773901, 774124, 776810]; Wellcome
   Trust; Norwegian Research Council [286773, 257622, 281113, 294534]; IPCC
   Trust Fund; H2020 Societal Challenges Programme [774378, 773901] Funding
   Source: H2020 Societal Challenges Programme; EPSRC [EP/M013200/1]
   Funding Source: UKRI; NERC [NE/M016900/1, NE/P019455/1, NE/P019765/1,
   NE/M021327/1] Funding Source: UKRI
FX The input of P.S. contributes to the following UKRI-funded projects:
   DEVIL (NE/M021327/1), MAGLUE (EP/M013200/1), U-GRASS (NE/M016900/1),
   Assess-BECCS (funded by UKERC), Soils-R-GRREAT (NE/P019455/1), N-Circle
   (BB/N013484/1), the European Union's Horizon 2020 Research and
   Innovation Programme through projects: CIRCASA (grant agreement no.
   774378), UNISECO (grant agreement no. 773901), SUPERG (grant agreement
   no. 774124), and VERIFY (grant agreement no. 776810) and the Wellcome
   Trust-funded project Sustainable and Healthy Food Systems (SHEFS). P. S.
   received support for his role as a Convening Lead Author of the IPCC
   Special Report on Climate Change and Land, from the UK Department for
   Business, Energy & Industrial Strategy (BEIS). F.C. acknowledges the
   support of the Norwegian Research Council through the projects
   MITISTRESS (project no. 286773), Bio4Fuels (project no. 257622),
   Carbo-Fertil (project no. 281113), and BIOPATH (project no. 294534). All
   other authors acknowledge support from their respective governments, or
   from the IPCC Trust Fund, to support their attendance at author meetings
   of the IPCC Special Report on Climate Change and Land, for which this
   analysis was undertaken. The views expressed are purely those of the
   authors and may not in any circumstances be regarded as stating an
   official position of the European Commission or any other Government
   Agency.
CR Adger WN, 2011, WIRES CLIM CHANGE, V2, P757, DOI 10.1002/wcc.133
   Alderman H, 2010, J NUTR, V140, p148S, DOI 10.3945/jn.109.110825
   Aleksandrowicz L, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0165797
   Alexander P, 2019, GLOBAL ENVIRON CHANG, V57, DOI 10.1016/j.gloenvcha.2019.101932
   Alexander P, 2016, GLOBAL ENVIRON CHANG, V41, P88, DOI 10.1016/j.gloenvcha.2016.09.005
   Ali G, 2018, LAND USE POLICY, V70, P471, DOI 10.1016/j.landusepol.2017.11.003
   Alkama R, 2016, SCIENCE, V351, P600, DOI 10.1126/science.aac8083
   Allington GRH, 2010, J ARID ENVIRON, V74, P973, DOI 10.1016/j.jaridenv.2009.12.005
   Alreshoodi M, 2015, I SYMP CONSUM ELECTR, P253, DOI 10.1109/ICCE.2015.7066401
   Altieri MA, 2015, AGRON SUSTAIN DEV, V35, P869, DOI 10.1007/s13593-015-0285-2
   Altieri MA, 2012, AGRON SUSTAIN DEV, V32, P1, DOI 10.1007/s13593-011-0065-6
   Anderson HR, 2017, LANCET RESP MED, V5, P916, DOI 10.1016/S2213-2600(17)30396-X
   Anderson K, 2016, SCIENCE, V354, P182, DOI 10.1126/science.aah4567
   Anenberg SC, 2012, ENVIRON HEALTH PERSP, V120, P831, DOI 10.1289/ehp.1104301
   Annan F, 2015, AM ECON REV, V105, P262, DOI 10.1257/aer.p20151031
   [Anonymous], 2017, Voluntary Guidelines for Sustainable Soil Management
   [Anonymous], 2016, PHILOS T R SOC B, DOI DOI 10.1098/RSTB.2015.0345
   [Anonymous], 2014, KEY WORLD EN STAT
   [Anonymous], 2011, Integrated Assessment of Black Carbon and Tropospheric Ozone
   [Anonymous], 2012, CLIMATE VULNERABILIT, V2nd
   [Anonymous], 2015, The State of Food Insecurity in the World Meeting the 2015 interation hunger targets: taking stock of uneven progress
   Antwi-Agyei P, 2014, REG ENVIRON CHANGE, V14, P1615, DOI 10.1007/s10113-014-0597-9
   Arnáez J, 2015, CATENA, V128, P122, DOI 10.1016/j.catena.2015.01.021
   Arndt C., 2012, Effects of food price shocks on child malnutrition: The Mozambican experience 2008/09, DOI DOI 10.1146/annurev.environ.33.013007.103754
   Arora VK, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03838-0
   Arslan A, 2018, J DEV STUD, V54, P457, DOI 10.1080/00220388.2017.1293813
   Asfaw S, 2018, WORLD DEV, V101, P219, DOI 10.1016/j.worlddev.2017.09.004
   Auld G, 2008, ANNU REV ENV RESOUR, V33, P187, DOI 10.1146/annurev.environ.33.013007.103754
   Baccini A, 2017, SCIENCE, V358, P230, DOI 10.1126/science.aam5962
   Bajzelj B, 2014, NAT CLIM CHANGE, V4, P924, DOI [10.1038/nclimate2353, 10.1038/NCLIMATE2353]
   Baker JS, 2019, ENERG POLICY, V126, P391, DOI 10.1016/j.enpol.2018.10.009
   Bala G, 2013, BIOGEOSCIENCES, V10, P7147, DOI 10.5194/bg-10-7147-2013
   Baldos ULC, 2014, AUST J AGR RESOUR EC, V58, P554, DOI 10.1111/1467-8489.12048
   Barbero-Sierra C, 2013, J ARID ENVIRON, V90, P95, DOI 10.1016/j.jaridenv.2012.10.014
   Barrett CB, 2001, FOOD POLICY, V26, P315, DOI 10.1016/S0306-9192(01)00014-8
   Bassoum S., 2010, INT S URB PER URB HO, P367, DOI DOI 10.1038/s41477-018-0108-y
   Bastin JF, 2019, SCIENCE, V365, P76, DOI 10.1126/science.aax0848
   Bastin JF, 2017, SCIENCE, V356, P635, DOI 10.1126/science.aam6527
   Batterbury S, 2001, ECUMENE, V8, P437, DOI 10.1177/096746080100800404
   Baumhardt RL, 2015, SUSTAINABILITY-BASEL, V7, P2936, DOI 10.3390/su7032936
   Baur AH, 2015, LANDSCAPE ECOL, V30, P1195, DOI 10.1007/s10980-015-0169-5
   Beerling DJ, 2018, NAT PLANTS, V4, P138, DOI 10.1038/s41477-018-0108-y
   Benis K, 2017, J CLEAN PROD, V140, P784, DOI 10.1016/j.jclepro.2016.05.176
   Bennetzen EH, 2016, GLOBAL ENVIRON CHANG, V37, P43, DOI 10.1016/j.gloenvcha.2015.12.004
   Bennetzen EH, 2016, GLOBAL CHANGE BIOL, V22, P763, DOI 10.1111/gcb.13120
   Bestelmeyer BT, 2015, FRONT ECOL ENVIRON, V13, P28, DOI 10.1890/140162
   Bhattacharjee K, 2017, LAND USE POLICY, V67, P436, DOI 10.1016/j.landusepol.2017.06.013
   Birkmann J, 2015, CLIMATIC CHANGE, V133, P53, DOI 10.1007/s10584-013-0913-2
   Birthal PS, 2015, WORLD DEV, V72, P70, DOI 10.1016/j.worlddev.2015.02.015
   Bisht IS, 2018, AGROECOL SUST FOOD, V42, P77, DOI 10.1080/21683565.2017.1363118
   Boysen LR, 2017, GLOBAL CHANGE BIOL, V23, P4303, DOI 10.1111/gcb.13745
   Briber BM, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0136237
   Brinkman HJ, 2010, J NUTR, V140, p153S, DOI 10.3945/jn.109.110767
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Burney JA, 2010, P NATL ACAD SCI USA, V107, P12052, DOI 10.1073/pnas.0914216107
   Byerlee D, 2006, FOOD POLICY, V31, P275, DOI 10.1016/j.foodpol.2006.02.002
   Calvin K, 2014, CLIMATIC CHANGE, V123, P691, DOI 10.1007/s10584-013-0897-y
   Campbell BM, 2016, GLOB FOOD SECUR-AGR, V11, P34, DOI 10.1016/j.gfs.2016.06.002
   Campbell BM, 2014, CURR OPIN ENV SUST, V8, P39, DOI 10.1016/j.cosust.2014.07.002
   Campbell JE, 2008, ENVIRON SCI TECHNOL, V42, P5791, DOI 10.1021/es800052w
   Campbell JR, 2015, REG ENVIRON CHANGE, V15, P1313, DOI 10.1007/s10113-014-0697-6
   Caon L., 2017, GLOBAL LAND OUTLOOK, P28, DOI DOI 10.1002/eap.1473
   Carlson KM, 2013, CARBON MANAG, V4, P347, DOI 10.4155/CMT.13.39
   CBD (Secretariat of the Convention on Biological Diversity), 2008, MONTR TECHN SER
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   CHAMEN WCT, 1992, SOIL TILL RES, V24, P359, DOI 10.1016/j.still.2014.09.011
   Chaturvedi V, 2015, MITIG ADAPT STRAT GL, V20, P389, DOI 10.1007/s11027-013-9497-4
   Chen J, 2007, CATENA, V69, P1, DOI 10.1016/j.catena.2006.04.019
   Chen WY, 2017, LANDSCAPE URBAN PLAN, V157, P170, DOI 10.1016/j.landurbplan.2016.06.010
   Chhatre A, 2009, P NATL ACAD SCI USA, V106, P17667, DOI 10.1073/pnas.0905308106
   Chow J, 2018, J SUSTAIN FOREST, V37, P139, DOI 10.1080/10549811.2017.1339615
   Claassen R., 2011, Journal of Agricultural and Applied Economics, V43, P195
   Clark M, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6cd5
   Clarke L, 2014, ROUTL RES INT LAW, P142
   Cohn AS, 2017, ANNU REV ENV RESOUR, V42, P347, DOI 10.1146/annurev-environ-102016-060946
   Conant RT, 2017, ECOL APPL, V27, P662, DOI 10.1002/eap.1473
   Conant RT, 2005, NUTR CYCL AGROECOSYS, V71, P239, DOI 10.1007/s10705-004-5085-z
   Conant RT, 2002, GLOBAL BIOGEOCHEM CY, V16, DOI 10.1029/2001GB001661
   Coomes OT, 2015, FOOD POLICY, V56, P41, DOI 10.1016/j.foodpol.2015.07.008
   Couwenberg J, 2010, GLOBAL CHANGE BIOL, V16, P1715, DOI 10.1111/j.1365-2486.2009.02016.x
   CRED, 2018, The human cost of natural disasters: a global perspective
   Cromsigt JPGM, 2018, PHILOS T R SOC B, V373, DOI 10.1098/rstb.2017.0440
   d'Amour CB, 2017, P NATL ACAD SCI USA, V114, P8939, DOI 10.1073/pnas.1606036114
   Dagar J.C., 2016, Innovative Saline Agriculture, DOI DOI 10.1016/j.gloenvcha.2017.11.014
   Darnton-Hill I, 2010, J NUTR, V140, p162S, DOI 10.3945/jn.109.111682
   Dasgupta P, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P613
   Datta KK, 2000, AGR WATER MANAGE, V46, P55, DOI 10.1016/S0378-3774(00)00077-9
   de Brauw A, 2011, FOOD POLICY, V36, P28, DOI 10.1016/j.foodpol.2010.11.002
   De Vries W, 2006, GLOBAL CHANGE BIOL, V12, P1151, DOI 10.1111/j.1365-2486.2006.01151.x
   De Zeeuw H., 2015, CITIES AGR DEV RESIL, DOI DOI 10.1029/2007WR006200
   Deal B, 2004, ECOL ECON, V51, P79, DOI 10.1016/j.ecolecon.2004.04.008
   del Ninno C, 2007, FOOD POLICY, V32, P413, DOI 10.1016/j.foodpol.2006.11.007
   Delang C. O., 2015, CHINAS GRAIN GREEN P, P135
   Deng L, 2014, GLOBAL CHANGE BIOL, V20, P3544, DOI 10.1111/gcb.12508
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Dickie IA, 2014, BIOL INVASIONS, V16, P705, DOI 10.1007/s10530-013-0609-6
   Dillon P., 2016, Integrated groundwater management, P435, DOI [DOI 10.1007/978-3-319-23576-9_17, 10.1007/978-3-319-23576-9_17]
   Djeddaoui F, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9101031
   Doelman JC, 2018, GLOBAL ENVIRON CHANG, V48, P119, DOI 10.1016/j.gloenvcha.2017.11.014
   Donato DC, 2011, NAT GEOSCI, V4, P293, DOI [10.1038/NGEO1123, 10.1038/ngeo1123]
   Dooley K, 2018, INT ENVIRON AGREEM-P, V18, P79, DOI 10.1007/s10784-017-9382-9
   Drewry JJ, 2006, AGR ECOSYST ENVIRON, V114, P159, DOI 10.1016/j.agee.2005.11.028
   Dudley N., 2010, Natural Solutions: Protected Areas Helping People Cope with Climate Change
   Dugan AJ, 2018, CARBON BAL MANAGE, V13, DOI 10.1186/s13021-018-0100-x
   Durigan G, 2013, PHILOS T R SOC B, V368, DOI 10.1098/rstb.2012.0165
   Eisenbies MH, 2007, FOREST ECOL MANAG, V242, P77, DOI 10.1016/j.foreco.2007.01.051
   Ellison D, 2017, GLOBAL ENVIRON CHANG, V43, P51, DOI 10.1016/j.gloenvcha.2017.01.002
   EPA, 2018, RISK MAN PLA RPM ES
   Epron D, 2016, FOREST ECOL MANAG, V382, P1, DOI 10.1016/j.foreco.2016.09.037
   Erb KH, 2018, NATURE, V553, P73, DOI 10.1038/nature25138
   Erb KH, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11382
   Erisman JW, 2008, NAT GEOSCI, V1, P636, DOI 10.1038/ngeo325
   Evans RG, 2008, WATER RESOUR RES, V44, DOI 10.1029/2007WR006200
   Fakhruddin SHM, 2015, INT J DISAST RISK RE, V14, P323, DOI 10.1016/j.ijdrr.2015.08.004
   FAO, 2017, pathways to 2050, DOI 10.4161/chan.4.6.12871
   FAO, 2015, IMPACT DISASTERS AGR
   FAO, 2011, The State of the World's Land and Water Resources for Food and Agriculture (SOLAW)-Managing systems at risk
   Favero A., 2017, Journal of Environmental Protection, V8, P61, DOI 10.4236/jep.2017.81006
   Vasconcelos ACF, 2013, LAND USE POLICY, V34, P250, DOI 10.1016/j.landusepol.2013.03.017
   Feng Y, 2017, HYDROL RES, V48, P1156, DOI 10.2166/nh.2016.099
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Findell KL, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01038-w
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Foley JA, 2011, NATURE, V478, P337, DOI 10.1038/nature10452
   Forest and Climate Change Government of India Ministry of Environment and World Bank, 2018, STRENGTH FOR FIR MAN, DOI [10.1596/30013, DOI 10.1596/30013]
   Francis CA, 2012, INT J AGR SUSTAIN, V10, P8, DOI 10.1080/14735903.2012.649588
   Frank S, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa8c83
   Frumkin H, 2002, PUBLIC HEALTH REP, V117, P201, DOI 10.1093/phr/117.3.201
   Fujimori S, 2019, NAT SUSTAIN, V2, P386, DOI 10.1038/s41893-019-0286-2
   Fuss S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabf9f
   Garbrecht JD, 2015, WEATHER CLIM EXTREME, V10, P32, DOI 10.1016/j.wace.2015.06.002
   Gariano SL, 2016, EARTH-SCI REV, V162, P227, DOI 10.1016/j.earscirev.2016.08.011
   Genesio L, 2011, ATMOS SCI LETT, V12, P142, DOI 10.1002/asl.332
   Gibbs HK, 2015, APPL GEOGR, V57, P12, DOI 10.1016/j.apgeog.2014.11.024
   Godfray H Charles J, 2014, Philos Trans R Soc Lond B Biol Sci, V369, P20120273, DOI 10.1098/rstb.2012.0273
   Goodwin BK, 2004, AM J AGR ECON, V86, P1058, DOI 10.1111/j.0002-9092.2004.00653.x
   Goodwin BK, 2003, J AGR RESOUR ECON, V28, P201
   Grassi G, 2018, CARBON BAL MANAGE, V13, DOI 10.1186/s13021-018-0096-2
   Greenwood KL, 2001, AUST J EXP AGR, V41, P1231, DOI 10.1071/EA00102
   Grey D, 2007, WATER POLICY, V9, P545, DOI 10.2166/wp.2007.021
   Griscom BW, 2017, P NATL ACAD SCI USA, V114, P11645, DOI 10.1073/pnas.1710465114
   Gustavsson L., 2006, Mitigation and Adaptation Strategies for Global Change, V11, P1097, DOI 10.1007/s11027-006-9035-8
   Haddad L., 2016, Food systems and diets: Facing the challenges of the 21st century
   Hamza MA, 2005, SOIL TILL RES, V82, P121, DOI 10.1016/j.still.2004.08.009
   Hawken P., 2017, Drawdown: The Most Comprehensive Plan Ever Proposed to Reverse Global Warming
   He B, 2015, CATENA, V127, P129, DOI 10.1016/j.catena.2014.12.028
   Headey D, 2008, AGR ECON-BLACKWELL, V39, P375, DOI 10.1111/j.1574-0862.2008.00345.x
   Hedenus F, 2014, CLIMATIC CHANGE, V124, P79, DOI 10.1007/s10584-014-1104-5
   Hejazi MI, 2015, P NATL ACAD SCI USA, V112, P10635, DOI 10.1073/pnas.1421675112
   Henderson BB, 2015, AGR ECOSYST ENVIRON, V207, P91, DOI 10.1016/j.agee.2015.03.029
   Herrero M, 2016, NAT CLIM CHANGE, V6, P452, DOI [10.1038/NCLIMATE2925, 10.1038/nclimate2925]
   Herrmann SM, 2005, J ARID ENVIRON, V63, P538, DOI 10.1016/j.jaridenv.2005.03.003
   Hiç C, 2016, ENVIRON SCI TECHNOL, V50, P4269, DOI 10.1021/acs.est.5b05088
   Hijbeek R, 2017, PLANT SOIL, V411, P293, DOI 10.1007/s11104-016-3031-x
   Hillbruner C, 2012, GLOB FOOD SECUR-AGR, V1, P20, DOI 10.1016/j.gfs.2012.08.001
   Hinkel J, 2014, P NATL ACAD SCI USA, V111, P3292, DOI 10.1073/pnas.1222469111
   Hoffmann T, 2013, EARTH SURF DYNAM, V1, P45, DOI 10.5194/esurf-1-45-2013
   Hooijer A, 2010, BIOGEOSCIENCES, V7, P1505, DOI 10.5194/bg-7-1505-2010
   Houghton RA, 2015, NAT CLIM CHANGE, V5, P1022, DOI 10.1038/nclimate2869
   Houghton RA, 2018, GLOBAL CHANGE BIOL, V24, P350, DOI 10.1111/gcb.13876
   Howard J, 2017, FRONT ECOL ENVIRON, V15, P42, DOI 10.1002/fee.1451
   Howard PH, 2015, CROP SCI, V55, P2489, DOI 10.2135/cropsci2014.09.0669
   Howell TA, 2015, AGR WATER MANAGE, V162, P33, DOI 10.1016/j.agwat.2015.08.008
   IPCC Intergovernmental Panel on Climate Change, 2018, GLOBAL WARMING 1 5 C
   ITPS, 2015, Status of the world's soil resources main report
   Ivanic M, 2008, AGR ECON-BLACKWELL, V39, P405, DOI 10.1111/j.1574-0862.2008.00347.x
   Jacinthe PA, 2001, LAND DEGRAD DEV, V12, P329, DOI 10.1002/ldr.454
   Jactel H, 2017, CURR FOR REP, V3, P223, DOI 10.1007/s40725-017-0064-1
   James SJ, 2010, FOOD RES INT, V43, P1944, DOI 10.1016/j.foodres.2010.02.001
   Jat HS, 2015, SOIL USE MANAGE, V31, P534, DOI 10.1111/sum.12208
   Jauhiainen J, 2008, ECOLOGY, V89, P3503, DOI 10.1890/07-2038.1
   Jaworski A, 2016, NEW YORK U LAW REV, V91, P1684
   Jeffery S, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa67bd
   Johnston FH, 2012, ENVIRON HEALTH PERSP, V120, P695, DOI 10.1289/ehp.1104422
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Joosten Hans., 2008, Assessment on Peatlands, Biodiversity and Climate Change: Main Report
   Kapos V., 2008, Carbon and biodiversity: a demonstration atlas
   Karjalainen Eeva, 2010, Environmental Health and Preventive Medicine, V15, P1, DOI 10.1007/s12199-008-0069-2
   Kauppi P., 2001, CLIMATE CHANGE 2001, V3, P301, DOI DOI 10.1016/j.gfs.2014.05.002
   Keddy PA, 2009, BIOSCIENCE, V59, P39, DOI 10.1525/bio.2009.59.1.8
   Keenan RJ, 2015, FOREST ECOL MANAG, V352, P9, DOI 10.1016/j.foreco.2015.06.014
   Kobayashi Y, 2017, ENVIRON MANAGE, V59, P807, DOI 10.1007/s00267-017-0820-9
   Koplitz SN, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094023
   Krause A, 2017, BIOGEOSCIENCES, V14, P4829, DOI 10.5194/bg-14-4829-2017
   Kreidenweis U, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/8/085001
   Kummu M, 2012, SCI TOTAL ENVIRON, V438, P477, DOI 10.1016/j.scitotenv.2012.08.092
   Kummu M, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/3/034006
   Kurz W. A., 2016, Unasylva (English ed.), V67, P61
   Lal R, 2006, LAND DEGRAD DEV, V17, P197, DOI 10.1002/ldr.696
   Lal R, 2004, SCIENCE, V304, P1623, DOI 10.1126/science.1097396
   Lal R, 2001, LAND DEGRAD DEV, V12, P519, DOI 10.1002/ldr.472
   Lal R, 1998, CRIT REV PLANT SCI, V17, P319, DOI 10.1016/S0735-2689(98)00363-3
   Lal R, 2015, SUSTAINABILITY-BASEL, V7, P5875, DOI 10.3390/su7055875
   Lal R, 2014, PROGR SOIL SCI, P339, DOI 10.1007/978-3-319-04084-4_35
   Lambin EF, 2011, P NATL ACAD SCI USA, V108, P3465, DOI 10.1073/pnas.1100480108
   Lasco RD, 2014, CURR OPIN ENV SUST, V6, P83, DOI 10.1016/j.cosust.2013.11.013
   Lawrence D, 2015, NAT CLIM CHANGE, V5, P27, DOI [10.1038/NCLIMATE2430, 10.1038/nclimate2430]
   Lenton TM, 2014, ISS ENVIRON SCI TECH, V38, P52
   Lenton TM, 2010, CARBON MANAG, V1, P145, DOI 10.4155/CMT.10.12
   Leskinen P., 2018, From Science to Policy 7
   Lestrelin G, 2007, LAND DEGRAD DEV, V18, P55, DOI 10.1002/ldr.756
   Lewis SL, 2019, NATURE, V568, P25, DOI 10.1038/d41586-019-01026-8
   Li JY, 2006, APPL GEOCHEM, V21, P1750, DOI 10.1016/j.apgeochem.2006.06.013
   Lin BB, 2011, BIOSCIENCE, V61, P183, DOI 10.1525/bio.2011.61.3.4
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Liu JG, 2017, EARTHS FUTURE, V5, P545, DOI 10.1002/2016EF000518
   Liu YS, 2015, APPL ENERG, V155, P904, DOI 10.1016/j.apenergy.2015.06.051
   Liu Z, 2015, WORLD DEV, V70, P147, DOI 10.1016/j.worlddev.2015.01.004
   Lobell DB, 2014, GLOB FOOD SECUR-AGR, V3, P72, DOI 10.1016/j.gfs.2014.05.002
   Locatelli B., 2011, SYNERGIES ADAPTATION, V8, DOI DOI 10.1016/j.foodpol.2004.07.009
   Locatelli B, 2015, WIRES CLIM CHANGE, V6, P585, DOI 10.1002/wcc.357
   Locatelli B, 2015, RESTOR ECOL, V23, P337, DOI 10.1111/rec.12209
   Locatelli B, 2011, FORESTS, V2, P431, DOI 10.3390/f2010431
   Long A, 2013, TROP CONSERV SCI, V6, P384, DOI 10.1177/194008291300600306
   Lopoukhine N., 2012, S.A.P.I.E.N.S, V5
   Louwaars N. P., 2002, Journal of New Seeds, V4, P1, DOI 10.1300/J153v04n01_01
   Lowder SK, 2016, WORLD DEV, V87, P16, DOI 10.1016/j.worlddev.2015.10.041
   Mahmud T, 2012, GLOBAL ENVIRON CHANG, V22, P933, DOI 10.1016/j.gloenvcha.2012.07.003
   Massawe F, 2016, TRENDS PLANT SCI, V21, P365, DOI 10.1016/j.tplants.2016.02.006
   McElwee P, 2020, GLOBAL CHANGE BIOL, V26, P4691, DOI 10.1111/gcb.15219
   McElwee P, 2017, FORESTS, V8, DOI 10.3390/f8010011
   McGuire S, 2016, FOOD SECUR, V8, P179, DOI 10.1007/s12571-015-0528-8
   McIntyre PB, 2016, P NATL ACAD SCI USA, V113, P12880, DOI 10.1073/pnas.1521540113
   McLaren D, 2012, PROCESS SAF ENVIRON, V90, P489, DOI 10.1016/j.psep.2012.10.005
   McLeman R, 2006, CLIMATIC CHANGE, V76, P31, DOI 10.1007/s10584-005-9000-7
   McMichael P, 2012, J PEASANT STUD, V39, P681, DOI 10.1080/03066150.2012.661369
   McMichael P, 2011, THIRD WORLD Q, V32, P119, DOI 10.1080/01436597.2011.543818
   Medugu NI, 2010, INT J CLIM CHANG STR, V2, P35, DOI 10.1108/17568691011020247
   Mekuria W, 2013, LAND DEGRAD DEV, V24, P528, DOI 10.1002/ldr.1146
   Mello FFC, 2014, NAT CLIM CHANGE, V4, P605, DOI [10.1038/nclimate2239, 10.1038/NCLIMATE2239]
   Melo FPL, 2013, ENVIRON SCI POLICY, V33, P395, DOI 10.1016/j.envsci.2013.07.013
   Meze-Hausken E, 2009, GLOBAL ENVIRON CHANG, V19, P66, DOI 10.1016/j.gloenvcha.2008.09.001
   Miao LJ, 2015, LAND DEGRAD DEV, V26, P450, DOI 10.1002/ldr.2399
   Miner R., 2010, Impact of the global forest industry on atmospheric greenhouse gases
   Molotoks A, 2018, GLOBAL CHANGE BIOL, V24, P5895, DOI 10.1111/gcb.14459
   Molotoks A, 2017, LAND-BASEL, V6, DOI 10.3390/land6040067
   [Montanarella L. IPBES IPBES], 2018, Secretariate of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, P1, DOI [10.5281/zenodo.3237392, DOI 10.5281/ZENODO.3237392]
   Morita K, 2018, FOREST POLICY ECON, V87, P59, DOI 10.1016/j.forpol.2017.10.013
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Mousseau F., 2015, Development (London), V58, P341
   Mueller ND, 2012, NATURE, V490, P254, DOI 10.1038/nature11420
   Muller A, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01410-w
   Munang R, 2014, ENVIRONMENT, V56, P18, DOI 10.1080/00139157.2014.861676
   Nabuurs GJ, 2007, EUR J FOREST RES, V126, P391, DOI 10.1007/s10342-006-0158-y
   Nabuurs GJ, 2017, FORESTS, V8, DOI 10.3390/f8120484
   Nair P.K. Ramachandran., 2012, Advances in Agroforestry, V9, DOI [DOI 10.1007/978-94-007-4676-36, 10.1007/978-94-007-4676-3, DOI 10.1007/978-94-007-4676-3, 10.1007/978-94-007-4676-36]
   Nandy S, 2016, SOC SCI MED, V149, P153, DOI 10.1016/j.socscimed.2015.11.036
   Nasi R, 2011, INT FOREST REV, V13, P355, DOI 10.1505/146554811798293872
   Naylor RL, 2000, NATURE, V405, P1017, DOI 10.1038/35016500
   Niehof A, 2004, FOOD POLICY, V29, P321, DOI 10.1016/j.foodpol.2004.07.009
   Nizeyimana EL, 2001, SOIL SCI SOC AM J, V65, P391, DOI 10.2136/sssaj2001.652391x
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   Nowak DJ, 2014, ENVIRON POLLUT, V193, P119, DOI 10.1016/j.envpol.2014.05.028
   Nunes A, 2016, SCI TOTAL ENVIRON, V566, P722, DOI 10.1016/j.scitotenv.2016.05.136
   Núñez M, 2010, INT J LIFE CYCLE ASS, V15, P67, DOI 10.1007/s11367-009-0126-0
   O'Mara FP, 2012, ANN BOT-LONDON, V110, P1263, DOI 10.1093/aob/mcs209
   Oldeman L.R., 1991, World map of the status of human-induced soil degradation: An explanatory note (GLASOD project)
   Oliver CD, 2014, J SUSTAIN FOREST, V33, P248, DOI 10.1080/10549811.2013.839386
   Osbahr H, 2008, GEOFORUM, V39, P1951, DOI 10.1016/j.geoforum.2008.07.010
   Pacala S, 2004, SCIENCE, V305, P968, DOI 10.1126/science.1100103
   Padgham J, 2015, URBAN CLIM, V12, P183, DOI 10.1016/j.uclim.2015.04.003
   Pan GX, 2009, AGR ECOSYST ENVIRON, V129, P344, DOI 10.1016/j.agee.2008.10.008
   Patnaik A, 2017, INT REV SOCIOL, V27, P179, DOI 10.1080/03906701.2016.1235213
   Patt A, 2010, GLOBAL ENVIRON CHANG, V20, P153, DOI 10.1016/j.gloenvcha.2009.10.007
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   PEFC & FSC, 2018, DOUBL CERT FSC PEFC
   Cerri CEP, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10040989
   Pendleton L, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0043542
   Pimentel David, 2006, Environment Development and Sustainability, V8, P119, DOI 10.1007/s10668-005-1262-8
   Platteau JP, 2017, WORLD DEV, V94, P139, DOI 10.1016/j.worlddev.2017.01.010
   Poeplau C, 2015, AGR ECOSYST ENVIRON, V200, P33, DOI 10.1016/j.agee.2014.10.024
   Poeplau C, 2011, GLOBAL CHANGE BIOL, V17, P2415, DOI 10.1111/j.1365-2486.2011.02408.x
   Popp A, 2017, GLOBAL ENVIRON CHANG, V42, P331, DOI 10.1016/j.gloenvcha.2016.10.002
   Popp A, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/3/034017
   Popp A, 2010, GLOBAL ENVIRON CHANG, V20, P451, DOI 10.1016/j.gloenvcha.2010.02.001
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Poulter B, 2014, NATURE, V509, P600, DOI 10.1038/nature13376
   Powell TWR, 2012, ENERG ENVIRON SCI, V5, P8116, DOI 10.1039/c2ee21592f
   Powlson DS, 2014, NAT CLIM CHANGE, V4, P678, DOI 10.1038/NCLIMATE2292
   Pozzi W, 2013, B AM METEOROL SOC, V94, P776, DOI 10.1175/BAMS-D-11-00176.1
   Pradhan P, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0062228
   Pratt K, 2010, BIOMASS BIOENERG, V34, P1149, DOI 10.1016/j.biombioe.2010.03.004
   Pretty J, 2018, NAT SUSTAIN, V1, P441, DOI 10.1038/s41893-018-0114-0
   Qadir M, 2013, LAND DEGRAD DEV, V24, P12, DOI 10.1002/ldr.1091
   Rahman M. R., 2015, Environment and Ecology Research, V3, P1, DOI [10.13189/eer.2015.030101, DOI 10.13189/EER.2015.030101, DOI 10.1002/2016GL068824]
   Raleigh C, 2015, GLOBAL ENVIRON CHANG, V32, P187, DOI 10.1016/j.gloenvcha.2015.03.005
   Ramage MH, 2017, RENEW SUST ENERG REV, V68, P333, DOI 10.1016/j.rser.2016.09.107
   Rametsteiner E, 2003, J ENVIRON MANAGE, V67, P87, DOI 10.1016/S0301-4797(02)00191-3
   Randerson J. T., 2012, J. Geophys. Res, V117, DOI [DOI 10.1029/2012JG002128, 10.1029/2012jg002128, https://doi.org/10.1029/2012JG002128, 10.1029/2012JG002128]
   Rao CS, 2017, CURR SCI INDIA, V112, P471, DOI 10.18520/cs/v112/i03/471-477
   Reed MS., 2016, Land Degradation, Desertification and Climate Change: Anticipating, Assessing and Adapting to Future Change.
   Regmi A, 2013, GLOB FOOD SECUR-AGR, V2, P166, DOI 10.1016/j.gfs.2013.08.001
   Reisman E, 2017, WORLD DEV, V98, P160, DOI 10.1016/j.worlddev.2017.04.024
   Reyer C, 2009, NEW FOREST, V38, P15, DOI 10.1007/s11056-008-9129-0
   Reynolds LP, 2015, J NUTR, V145, P1377, DOI 10.3945/jn.115.212217
   Palacios MR, 2013, LAND USE POLICY, V30, P814, DOI 10.1016/j.landusepol.2012.06.007
   Rigg J, 2006, WORLD DEV, V34, P180, DOI 10.1016/j.worlddev.2005.07.015
   Rivera-Ferre MG, 2016, WIRES CLIM CHANGE, V7, P869, DOI 10.1002/wcc.421
   Roberts KG, 2010, ENVIRON SCI TECHNOL, V44, P827, DOI 10.1021/es902266r
   Robertson GP, 2017, SCIENCE, V356, DOI 10.1126/science.aal2324
   Robledo C, 2004, MT RES DEV, V24, P14, DOI 10.1659/0276-4741(2004)024[0014:ITROHC]2.0.CO;2
   Roe S, 2019, NAT CLIM CHANGE, V9, P817, DOI 10.1038/s41558-019-0591-9
   Rojas-Downing MM, 2017, CLIM RISK MANAG, V16, P145, DOI 10.1016/j.crm.2017.02.001
   Rowe RL, 2011, BIOMASS BIOENERG, V35, P325, DOI 10.1016/j.biombioe.2010.08.046
   Rowland D, 2017, ENVIRON CONSERV, V44, P102, DOI 10.1017/S0376892916000151
   Safriel U, 2017, SILVA FENN, V51, DOI 10.14214/sf.1650
   Salvati L, 2014, INT FOREST REV, V16, P485, DOI 10.1505/146554814813484149
   Sanderman J, 2017, P NATL ACAD SCI USA, V114, P9575, DOI 10.1073/pnas.1706103114
   Sanderson MA, 2013, RENEW AGR FOOD SYST, V28, P129, DOI 10.1017/S1742170512000312
   Sanderson MA, 2013, RENEW AGR FOOD SYST, V28, P194, DOI 10.1017/S1742170513000124
   Santilli Juliana., 2012, Agrobiodiversity and the Law: Regulating Genetic Resources, Food Security and Cultural Diversity
   Sasaki N, 2016, FRONT ENV SCI-SWITZ, V4, DOI 10.3389/fenvs.2016.00050
   Sathre R, 2010, ENVIRON SCI POLICY, V13, P104, DOI 10.1016/j.envsci.2009.12.005
   Schmitz OJ, 2018, SCIENCE, V362, DOI 10.1126/science.aar3213
   Schmitz OJ, 2014, ECOSYSTEMS, V17, P344, DOI 10.1007/s10021-013-9715-7
   Schwilch G, 2014, ENVIRON MANAGE, V54, P983, DOI 10.1007/s00267-013-0071-3
   Scott CA, 2011, ENERG POLICY, V39, P6622, DOI 10.1016/j.enpol.2011.08.013
   Seidl R, 2017, NAT CLIM CHANGE, V7, P395, DOI [10.1038/NCLIMATE3303, 10.1038/nclimate3303]
   Shindell D, 2012, SCIENCE, V335, P183, DOI 10.1126/science.1210026
   Skees J.R., 2012, Greening the Financial Sector, P111, DOI [DOI 10.1007/978-3-642-05087-9_4, DOI 10.1016/j.eneco.2015.05.009]
   Smith P, 2015, SOIL-GERMANY, V1, P665, DOI 10.5194/soil-1-665-2015
   Smith P, 2008, PHILOS T R SOC B, V363, P789, DOI 10.1098/rstb.2007.2184
   Smith P, 2016, NAT CLIM CHANGE, V6, P42, DOI [10.1038/NCLIMATE2870, 10.1038/nclimate2870]
   Smith P, 2016, ENVIRON SCI-PROC IMP, V18, P1400, DOI [10.1039/c6em00386a, 10.1039/C6EM00386A]
   Smith P, 2016, GLOBAL CHANGE BIOL, V22, P1315, DOI 10.1111/gcb.13178
   Smith P, 2016, GLOBAL CHANGE BIOL, V22, P1008, DOI 10.1111/gcb.13068
   Smith P, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P811
   Smith P, 2013, GLOBAL CHANGE BIOL, V19, P2285, DOI 10.1111/gcb.12160
   Smith SV, 2005, ECOL APPL, V15, P1929, DOI 10.1890/05-0073
   Smith SV, 2001, GLOBAL BIOGEOCHEM CY, V15, P697, DOI 10.1029/2000GB001341
   Smyth CE, 2014, BIOGEOSCIENCES, V11, P3515, DOI 10.5194/bg-11-3515-2014
   Smyth C, 2017, GCB BIOENERGY, V9, P1071, DOI 10.1111/gcbb.12389
   Sohi SP, 2012, SCIENCE, V338, P1034, DOI 10.1126/science.1225987
   Sommer R, 2014, J ENVIRON MANAGE, V144, P83, DOI 10.1016/j.jenvman.2014.05.017
   Sonntag S, 2016, GEOPHYS RES LETT, V43, P6546, DOI 10.1002/2016GL068824
   Soussana JF, 2019, SOIL TILL RES, V188, P3, DOI 10.1016/j.still.2017.12.002
   Specht K, 2014, AGR HUM VALUES, V31, P33, DOI 10.1007/s10460-013-9448-4
   Springmann M, 2018, NATURE, V562, P519, DOI 10.1038/s41586-018-0594-0
   Springmann M, 2016, LANCET, V387, P1937, DOI 10.1016/S0140-6736(15)01156-3
   Squires V., 2005, J RANGELAND SCI, V5, P336
   Stallard RF, 1998, GLOBAL BIOGEOCHEM CY, V12, P231, DOI 10.1029/98GB00741
   Stehfest E, 2009, CLIMATIC CHANGE, V95, P83, DOI 10.1007/s10584-008-9534-6
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Stone B, 2010, ENVIRON HEALTH PERSP, V118, P1425, DOI 10.1289/ehp.0901879
   Sunderland T., 2013, Food Security and Nutrition: The Role of Forest
   Taboada MA, 2011, ACSESS PUBL, P301, DOI 10.2136/2011.soilmanagement.c20
   Tacconi L, 2016, NAT CLIM CHANGE, V6, P640, DOI 10.1038/nclimate3008
   Tang YZ, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11030358
   Tansey K, 2004, J GEOPHYS RES-ATMOS, V109, DOI 10.1029/2003JD003598
   Tayleur C, 2017, CONSERV LETT, V10, P610, DOI 10.1111/conl.12314
   Taylor LL, 2016, NAT CLIM CHANGE, V6, P402, DOI [10.1038/nclimate2882, 10.1038/NCLIMATE2882]
   The High Level Panel of Experts on Food Security and Nutrition, 2017, Nutrition and Food Systems: A Report by the High Level of Experts on Food Security and Nutrition of the Committee on World Food Security
   Thornbush M, 2013, SUSTAIN CITIES SOC, V9, P1, DOI 10.1016/j.scs.2013.01.003
   Thornton PK, 2009, AGR SYST, V101, P113, DOI 10.1016/j.agsy.2009.05.002
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Tilman D, 2014, NATURE, V515, P518, DOI 10.1038/nature13959
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Timmer CP, 2010, J NUTR, V140, p224S, DOI 10.3945/jn.109.110379
   Torlesse H, 2003, J NUTR, V133, P1320
   Tullberg J, 2018, SOIL TILL RES, V176, P18, DOI 10.1016/j.still.2017.09.014
   UNCCD (Secretariat), 2013, ZER NET LAND DEGR SU
   UNCTAD, 2011, WAT FOOD INN WAT MAN
   van Niekerk J, 2017, AGROECOL SUST FOOD, V41, P1099, DOI 10.1080/21683565.2017.1359738
   Van Oost K, 2007, SCIENCE, V318, P626, DOI 10.1126/science.1145724
   Vellakkal S, 2015, J NUTR, V145, P1942, DOI 10.3945/jn.115.211250
   Vermeulen SJ, 2012, ANNU REV ENV RESOUR, V37, P195, DOI 10.1146/annurev-environ-020411-130608
   Vira B, 2015, FORESTS AND FOOD: ADDRESSING HUNGER AND NUTRITION ACROSS SUSTAINABLE LANDSCAPES, P1, DOI 10.11647/OBP.0085
   VONBRAUN J, 2014, IMPACTS CURES WORLD, V1, P34
   Vries W. de, 2009, Forest Ecology and Management, V258, P1814, DOI 10.1016/j.foreco.2009.02.034
   Waha K, 2018, GLOBAL CHANGE BIOL, V24, P3390, DOI 10.1111/gcb.14158
   Wang M, 2017, J CLIMATE, V30, P2535, DOI [10.1175/jcli-d-16-0610.1, 10.1175/JCLI-D-16-0610.1]
   Warren A, 2002, LAND DEGRAD DEV, V13, P449, DOI 10.1002/ldr.532
   Watson JEM, 2014, NATURE, V515, P67, DOI 10.1038/nature13947
   Webb NP, 2017, FRONT ECOL ENVIRON, V15, P450, DOI 10.1002/fee.1530
   West JJ, 2013, NAT CLIM CHANGE, V3, P885, DOI [10.1038/NCLIMATE2009, 10.1038/nclimate2009]
   Westhoek H, 2014, GLOBAL ENVIRON CHANG, V26, P196, DOI 10.1016/j.gloenvcha.2014.02.004
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Wijitkosum S, 2016, SUSTAIN ENVIRON RES, V26, P84, DOI 10.1016/j.serj.2015.11.004
   Wise M, 2015, ENERG ECON, V50, P337, DOI 10.1016/j.eneco.2015.05.009
   Wise M, 2009, SCIENCE, V324, P1183, DOI 10.1126/science.1168475
   Wolff S, 2018, GLOBAL ENVIRON CHANG, V52, P259, DOI 10.1016/j.gloenvcha.2018.08.002
   Wong VNL, 2010, SOIL USE MANAGE, V26, P2, DOI 10.1111/j.1475-2743.2009.00251.x
   Woolf D, 2010, NAT COMMUN, V1, DOI 10.1038/ncomms1053
   World Bank, 2009, GLOBAL ECONOMIC PROSPECTS: COMMODITIES AT THE CROSSROADS, P1, DOI 10.1596/978-0-8213-7799-4
   World Bank, 2018, COMM MARK OUTL OIL E
   World Bank, 2017, FUT FOOD SHAP FOOD S
   Wright CK, 2013, P NATL ACAD SCI USA, V110, P4134, DOI 10.1073/pnas.1215404110
   Wunder S, 2014, WORLD DEV, V64, pS1, DOI 10.1016/j.worlddev.2014.03.007
   Xu DY, 2019, FRONT EARTH SCI-PRC, V13, P43, DOI 10.1007/s11707-018-0706-z
   Yao SB, 2010, ENVIRON MANAGE, V45, P541, DOI 10.1007/s00267-009-9416-3
   Zaehle S, 2011, CURR OPIN ENV SUST, V3, P311, DOI 10.1016/j.cosust.2011.08.008
   Zezza A, 2009, WORLD DEV, V37, P1297, DOI 10.1016/j.worlddev.2008.11.004
   Zhang KR, 2013, BIOL CONSERV, V158, P205, DOI 10.1016/j.biocon.2012.08.021
   Zhang PC, 2000, SCIENCE, V288, P2135, DOI 10.1126/science.288.5474.2135
   Zhang TW, 2001, LAND USE POLICY, V18, P221, DOI 10.1016/S0264-8377(01)00018-7
   Zhou GY, 2017, GLOBAL CHANGE BIOL, V23, P1167, DOI 10.1111/gcb.13431
   Ziervogel G, 2010, WIRES CLIM CHANGE, V1, P525, DOI 10.1002/wcc.56
   Zomer RJ, 2016, SCI REP-UK, V6, DOI 10.1038/srep29987
   ,, 2020, The state of food security and nutrition in the world 2020: transforming food systems for affordable healthy diets, DOI 10.4060/ca9692en
NR 399
TC 157
Z9 163
U1 10
U2 51
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD MAR
PY 2020
VL 26
IS 3
BP 1532
EP 1575
DI 10.1111/gcb.14878
EA DEC 2019
PG 44
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA KS0ZZ
UT WOS:000502467300001
PM 31637793
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Zhang, SH
   Zhang, JJ
   Yue, TJ
   Jing, XE
AF Zhang, Shouhong
   Zhang, Jianjun
   Yue, Tongjia
   Jing, Xueer
TI Impacts of climate change on urban rainwater harvesting systems
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Rainwater harvesting; Downscaling; Water saving;
   Stormwater capture efficiency
ID ANALYTICAL PROBABILISTIC MODEL; WATER-SAVING EFFICIENCY; PRECIPITATION
   CHANGE; CAPTURE EFFICIENCY; LOESS PLATEAU; SOIL-EROSION; STORMWATER;
   PERFORMANCE; CLIGEN; RUNOFF
AB Rainwater harvesting (RWH) is promoted in many cities (e.g., Beijing and Shenzhen) as a climate change adaptation measure to relieve urban water supply and drainage pressures. In this study, the impacts of future climate change on water saving and stormwater capture performances of RWH systems at cities across four climatic zones of China are investigated. A downscaling technique based on the Climate Generator is evaluated and employed to generate future (2020-2050) daily rainfall data. Performance indices of RWH systems (i.e., water saving efficiency, reliability, and stormwater capture efficiency) calculated using both the future and historical (1985-2015) daily rainfall data are compared. Twowater demand scenarios (i.e., lawn irrigation and toilet flushing) are included in the investigation. The water saving performance is positively affected by the increases in future rainfall at the four cities, while the stormwater capture performance is negatively affected as a larger tank size is required to achieve a desired stormwater capture efficiency in the future period. The responses of water saving and stormwater capture performances of RWH systems to climate change are varying with not only the system dimensions (i.e., storage capacity and catchment area), but also the water demand scenarios and locations. RWH systems with larger storage capacity for larger water demand scenarios at humid and semi-humid cities is expected to be more resilient to climate change. The various changing patterns of the performance indices highlight the importance of incorporating climate change in the design of RWH systems. Location-specific adaptive adjustments (e.g., adjusting tank sizes, catchment areas or water demand rates) need to be adopted so that RWH systems can sustainably meet water saving and stormwater control requirements under future climate conditions. (c) 2019 Elsevier B.V. All rights reserved.
C1 [Zhang, Shouhong; Zhang, Jianjun; Yue, Tongjia; Jing, Xueer] Beijing Forestry Univ, Sch Soil & Water Conservat, 35 Qinghua East Rd, Beijing 100083, Peoples R China.
C3 Beijing Forestry University
RP Zhang, SH; Zhang, JJ (corresponding author), Beijing Forestry Univ, Sch Soil & Water Conservat, 35 Qinghua East Rd, Beijing 100083, Peoples R China.
EM zhangs@bjfu.edu.cn; zhangjianjun@bjfu.edu.cn
RI yue, tong/KFR-9919-2024
OI Zhang, Shouhong/0000-0002-8914-2421; zhang, jianjun/0000-0002-7135-9542
FU Fundamental Research Funds for the Central Universities [2018BLCB04,
   2015ZCQ-SB-01, 2016ZCQ06]; National Natural Science Foundation of China
   [51609004]
FX This work is supported by the Fundamental Research Funds for the Central
   Universities (2018BLCB04, 2015ZCQ-SB-01, and 2016ZCQ06) and the National
   Natural Science Foundation of China (NO. 51609004). We acknowledge the
   Program for Climate Model Diagnosis and Intercomparison (PCMDI),
   theWorld Climate Research Programme (WCRP) on CMIP, and the National
   Climate Center of China for providing the GCM outputs. We also thank Dr.
   Y. Zhang and Dr. Y. Guan from BFU and Dr. S. Hu from IGSNRR for their
   helpful suggestions in downscaling GCM projected climate data.
CR Abdulla FA, 2009, DESALINATION, V243, P195, DOI 10.1016/j.desal.2008.05.013
   Al-Zahrani MA, 2015, WATER RESOUR MANAG, V29, P3651, DOI 10.1007/s11269-015-1021-z
   Allen R.G., 1998, FAO Irrig. Drain. Pap., V56, P300, DOI DOI 10.1016/S0141-1187(05)80058-6
   Almazroui M, 2017, ATMOS RES, V189, P11, DOI 10.1016/j.atmosres.2017.01.004
   Amos CC, 2016, WATER-SUI, V8, DOI 10.3390/w8040149
   Andrade LR, 2017, J HYDROL, V545, P163, DOI 10.1016/j.jhydrol.2016.12.027
   [Anonymous], 2010, MANAGEMENT WORLD
   Basinger M, 2010, J HYDROL, V392, P105, DOI 10.1016/j.jhydrol.2010.07.039
   BMCoPNR, 2013, COD DES STORMW MAN H
   Burns MJ, 2015, HYDROL PROCESS, V29, P152, DOI 10.1002/hyp.10142
   Campisano A, 2017, WATER RES, V115, P195, DOI 10.1016/j.watres.2017.02.056
   Chen ZW, 2017, HYDROL EARTH SYST SC, V21, P2233, DOI 10.5194/hess-21-2233-2017
   Chou C, 2013, NAT GEOSCI, V6, P263, DOI [10.1038/NGEO1744, 10.1038/ngeo1744]
   Chou C, 2009, J CLIMATE, V22, P1982, DOI 10.1175/2008JCLI2471.1
   Cowden JR, 2008, J HYDROL, V361, P64, DOI 10.1016/j.jhydrol.2008.07.025
   DeBusk KM, 2013, J AM WATER RESOUR AS, V49, P1398, DOI 10.1111/jawr.12096
   Fernandes LFS, 2015, SCI TOTAL ENVIRON, V529, P91, DOI 10.1016/j.scitotenv.2015.05.061
   Fewkes A., 2000, BUILD SERV ENG RES T, V21, P99, DOI [DOI 10.1177/014362440002100204, 10.1177/014362440002100204]
   GhaffarianHoseini A, 2016, DESALIN WATER TREAT, V57, P95, DOI 10.1080/19443994.2015.1021097
   Ghisi E, 2007, BUILD ENVIRON, V42, P1654, DOI 10.1016/j.buildenv.2006.02.007
   Guo YP, 2007, J HYDROL ENG, V12, P197, DOI 10.1061/(ASCE)1084-0699(2007)12:2(197)
   Haque MM, 2016, J CLEAN PROD, V137, P60, DOI 10.1016/j.jclepro.2016.07.038
   Herrera M, 2010, J HYDROL, V387, P141, DOI 10.1016/j.jhydrol.2010.04.005
   Imteaz MA, 2011, RESOUR CONSERV RECY, V56, P80, DOI 10.1016/j.resconrec.2011.09.008
   Jing XE, 2018, WATER RESOUR MANAG, V32, P2649, DOI 10.1007/s11269-018-1950-4
   Jing XE, 2017, RESOUR CONSERV RECY, V126, P74, DOI 10.1016/j.resconrec.2017.07.027
   Khastagir A, 2010, J HYDROL, V381, P181, DOI 10.1016/j.jhydrol.2009.11.040
   Kim H, 2012, SCI TOTAL ENVIRON, V424, P213, DOI 10.1016/j.scitotenv.2012.02.021
   Kim K, 2009, J HYDROL ENG, V14, P545, DOI 10.1061/(ASCE)HE.1943-5584.0000030
   Li Z, 2011, CLIMATIC CHANGE, V105, P223, DOI 10.1007/s10584-010-9875-9
   Liaw CH, 2004, J AM WATER RESOUR AS, V40, P901, DOI 10.1111/j.1752-1688.2004.tb01054.x
   Lim KY, 2015, SCI TOTAL ENVIRON, V523, P95, DOI 10.1016/j.scitotenv.2015.03.077
   Litofsky A. L. E., 2014, J ENV ENG, V140, P223
   Lo KFA, 2015, ENVIRONMENTS, V2, P105, DOI 10.3390/environments2010105
   Lobo GP, 2015, CATENA, V127, P206, DOI 10.1016/j.catena.2015.01.002
   Melville-Shreeve P, 2016, WATER-SUI, V8, DOI 10.3390/w8040129
   Morales-Pinzón T, 2014, SCI TOTAL ENVIRON, V470, P1257, DOI 10.1016/j.scitotenv.2013.10.101
   Nicks A., 1995, USDA-Water Erosion Prediction Project Hillslope Profile and Watershed Model Documentation, pCh2
   Palla A, 2017, J ENVIRON MANAGE, V191, P297, DOI 10.1016/j.jenvman.2017.01.025
   Pavolová H, 2019, J CLEAN PROD, V209, P1119, DOI 10.1016/j.jclepro.2018.10.308
   Petrucci G, 2012, URBAN WATER J, V9, P45, DOI 10.1080/1573062X.2011.633610
   Piao SL, 2010, NATURE, V467, P43, DOI 10.1038/nature09364
   Silva CM, 2015, RESOUR CONSERV RECY, V94, P21, DOI 10.1016/j.resconrec.2014.11.004
   Soden BJ, 2006, J CLIMATE, V19, P3354, DOI [10.1175/JCLI3799.1, 10.1175/JCLI3990.1]
   Vaghefi P, 2017, J HYDROMETEOROL, V18, P2011, DOI [10.1175/JHM-D-16-0237.1, 10.1175/jhm-d-16-0237.1]
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P95, DOI 10.1007/s10584-011-0152-3
   Wallace CD, 2015, J HYDROL, V529, P1798, DOI 10.1016/j.jhydrol.2015.08.006
   Ward S, 2012, WATER RES, V46, P5127, DOI 10.1016/j.watres.2012.06.043
   Wilks DS, 1999, CLIM RES, V11, P125, DOI 10.3354/cr011125
   Xu CH, 2012, ATMOS OCEAN SCI LETT, V5, P527, DOI 10.1080/16742834.2012.11447042
   Youn SG, 2012, RESOUR CONSERV RECY, V65, P136, DOI 10.1016/j.resconrec.2012.05.005
   Yu BF, 2005, CATENA, V61, P196, DOI 10.1016/j.catena.2005.03.004
   Zhang SH, 2018, J CLEAN PROD, V196, P1341, DOI 10.1016/j.jclepro.2018.06.133
   Zhang SH, 2015, J IRRIG DRAIN ENG, V141, DOI 10.1061/(ASCE)IR.1943-4774.0000810
   Zhang SH, 2013, J HYDROL ENG, V18, P1739, DOI 10.1061/(ASCE)HE.1943-5584.0000734
   Zhang SH, 2014, WATER RESOUR MANAG, V28, P149, DOI 10.1007/s11269-013-0477-y
   Zhang SH, 2013, J HYDROL ENG, V18, P19, DOI 10.1061/(ASCE)HE.1943-5584.0000593
   Zhang XC, 2007, CLIMATIC CHANGE, V84, P337, DOI 10.1007/s10584-007-9256-1
   Zhang Y, 2008, CATENA, V73, P1, DOI 10.1016/j.catena.2007.08.001
   Zhao CL, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15112540
NR 60
TC 85
Z9 92
U1 9
U2 129
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD MAY 15
PY 2019
VL 665
BP 262
EP 274
DI 10.1016/j.scitotenv.2019.02.135
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA HO0XH
UT WOS:000460628600029
PM 30772557
DA 2025-01-10
ER

PT J
AU Moon, TH
   Kim, DH
   Park, CS
   Lee, DS
AF Moon, Tae Hoon
   Kim, Dong-Hwan
   Park, Chang Sug
   Lee, Dong-Sung
TI Policy Analysis to Reduce Climate Change-Induced Risks in Urban and
   Rural Areas in Korea
SO SUSTAINABILITY
LA English
DT Article
DE climate change policy; risk management; system dynamics simulation;
   urban and rural areas
AB The purpose of this paper was to project changes in climate change-induced risks over time and to investigate policy alternatives to mitigate the risks from increases in sea level, heavy rains, and heat waves in urban and rural areas. System dynamics simulation was used to build a model and conduct policy analysis for a simulation period over the years 2000-2050. The model was built with a focus on the interaction among three factors: damage restoration costs from heavy rains, heat waves, and sea level rise; the total cost of food imports due to decreases in arable land and agricultural productivity; and changes in the government budget to respond to climate change problems. A policy experiment was conducted with the model under four scenarios mainly based on the government budget for climate change. The results indicated, firstly, that the climate budget needs to be increased to at least 13 trillion KoreanWon (US $11.6 billion) per year. Secondly, an earlier budget increase would more effectively reduce the total disaster restoration cost than a delayed budget increase. Third, if an earlier budget increase is difficult, the next best alternative would be to allocate a greater fraction of the climate budget to urban rather than to rural areas. Lastly, an early response to climate change would more effectively reduce food import costs, maintain agricultural productivity, and improve infrastructure for climate change adaptation than a delayed response. In conclusion, an earlier increase in the climate change budget would be more effective than a delayed budget increase of the same amount, and allocating a larger fraction of the climate budget to urban areas could be more cost-effective than increasing the budget, if urban and rural parties could agree on the method of allocation.
C1 [Moon, Tae Hoon; Lee, Dong-Sung] Chung Ang Univ, Dept Urban Planning & Real Estate, Seoul 06974, South Korea.
   [Kim, Dong-Hwan] Chung Ang Univ, Dept Publ Serv, Seoul 06974, South Korea.
   [Park, Chang Sug] Korea Environm Inst, Div Climate Change & Interdisciplinary Res, Sejong 30147, South Korea.
C3 Chung Ang University; Chung Ang University; Korea Environment Institute
   (KEI)
RP Moon, TH (corresponding author), Chung Ang Univ, Dept Urban Planning & Real Estate, Seoul 06974, South Korea.; Kim, DH (corresponding author), Chung Ang Univ, Dept Publ Serv, Seoul 06974, South Korea.
EM sapphire@cau.ac.kr; sddhkim@cau.ac.kr; plade@kei.re.kr;
   baby8803@cau.ac.kr
OI Moon, Tae Hoon/0000-0002-5964-165X
FU Korea Environment Institute (KEI), Republic of Korea [GP2015-03-01]
FX This research was supported by research project #GP2015-03-01 through
   the Korea Environment Institute (KEI), Republic of Korea.
CR [Anonymous], 2000, Business Dynamics: Systems Thinking and Modeling for a Complex World
   [Anonymous], 2004, The Limits to Growth the 30-Year Update
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Bell J.A., 1980, ELEMENTS SYSTEM DYNA
   Cho G.W., 2014, STUD QUANT RISK EFF
   Cho K.W., 2011, NATL ASSESSMENT SEA, VI
   Cho K.W., 2012, NATL ASSESSMENT SEA, VII
   Cooke Philip., 2015, Journal of Open Innovation: Technology, Market, and Complexity, V1, P1, DOI [10.1186/s40852-015-0002-z, DOI 10.1186/S40852-015-0002-Z]
   Fiddaman T, 1995, P 1995 SYST DYN C TO
   Fiddaman T., 1997, FEEDBACK COMPLEXITY
   Fiddaman TS, 2002, SYST DYNAM REV, V18, P243, DOI 10.1002/sdr.241
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Forrester J.W., 1982, PRINCIPLE OF SYSTEMS
   Forrester Jay, 1971, World dynamics
   George P.R., 1981, INTRO SYSTEM DYNAMIC
   Ha J.S., 2014, STUDY ESTABLISHMENT
   Huera J.M., 2011, P 29 INT C SYST DYN
   KMA, 2014, Korean Climate Change Assessment Report 2014
   Korea Adaptation Center for Climate Change (KACC), CLIM CHANG AD BUDG
   Korea Adaptation Center for Climate Change (KACC), NUMB HEAT WAV DAYS
   Korea Rural Corporation, AR LAND INCR RAT
   Meadows D.H., 1992, LIMIT GLOBAL COLLAPS
   Meadows D. L., 1974, Dynamics of growth in a finite world.
   Meadows DH, 1972, THE LIMIT TO GROWTH
   Meadows DonellaH., 1980, ELEMENTS SYSTEM DYNA
   Millennium Institute, THRESH 21 MOD
   Ministry of Agriculture Food and Rural Affairs, MAJ STAST AGR AN HUS
   Ministry of Environment (MOE); National Institute of Environmental Research (NIER), 2015, KOR CLIM CHANG ASS R
   Ministry of Public Safety and Security, ANN FLOOD DAM DAT
   Ministry of Public Safety and Security, FLOOD DAM ASS VAL UR
   Ministry of Public Safety and Security (MPSS), 2016, 2015 STAT YB NAT DIS
   Mitchell B., 2002, RESOURCE ENV MANAGEM, V2nd
   Moon T.H., 2007, SUST CIT VIEW SYST T
   Morecroft J., 2007, Strategic modelling and business dynamics: A feedback systems approach
   National Institute of Meteorological Research (NIMR), 2011, CLIM CHANG SCEN REP
   Park C.S., 2014, CLIM ENV RISKS OUTL
   Park Y.S., 2013, UN FUTURE REPORT 203
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Randers Jorgen., 2012, 2052 GLOBAL FORECAST, DOI DOI 10.1080/0969160X.2012.720407
   Shin Y.S., 2012, INTRO ENV BURD DIS N
   Song B.N., 1990, The Rise of the Korean Economy
   Statistics Korea, AR LAND INCR DECR RA
   Statistics Korea, FOOD CONS PER CAP
   Statistics Korea, FOOD PROD AR LAND
   Statistics Korea, POP TREND PROJ 1960
   Statistics Korea, FOOD PROD CONS
   Sterman J, 2012, SYST DYNAM REV, V28, P295, DOI 10.1002/sdr.1474
NR 47
TC 6
Z9 6
U1 0
U2 19
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD APR
PY 2017
VL 9
IS 4
AR 524
DI 10.3390/su9040524
PG 17
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA EV9FE
UT WOS:000402090300047
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Talchabhadel, R
   Bhattarai, S
   Bista, S
AF Talchabhadel, Rocky
   Bhattarai, Saurav
   Bista, Sunil
TI Projected Changes in Precipitation Extremes Across the Mississippi River
   Basin Using the NASA Global Daily Downscaled Datasets NEX-GDDP-CMIP6
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article; Early Access
DE climate model; CMIP6; extreme precipitation; Mississippi River basin
ID UNITED-STATES; CLIMATE; TRENDS; TEMPERATURE
AB This study comprehensively analyzes historical and projected changes in various precipitation parameters within the Mississippi River basin. These parameters include annual total values, simple daily intensity index, consecutive dry and wet spells, as well as heavy precipitation event related indices, such as maximum one-day, three-day, five-day, and seven-day consecutive precipitation. We examine the quantity exceeding specific percentile-based thresholds (95th and 99th) as well as the frequency of days surpassing absolute thresholds (1, 10, 20, 50 mm). Additionally, we assess the percentage contribution of various extreme precipitation events to the annual total. The study employs a total of 32 Climate Models with a spatial resolution of 0.25 degrees (approximately 25 km) for the historical period spanning from 1985 to 2014, and the projected period from 2015 to 2094. A comparison is made between climate models and ground-based observations during the historical period. Using climate models, projected deviations in future periods are then computed, specifically the near future (2025 to 2054) and far future (2065 to 2094), with respect to the historical period. These climate models are part of the Coupled Model Inter-comparison Project phase 6 (CMIP6), and have undergone downscaling and bias-correction by the NASA Earth Exchange Global Daily Downscaled Projections project, referred to as NEX-GDDP-CMIP6. The findings across the Mississippi River basin reveal an increasing trend in precipitation extremes, particularly in frequency and intensity rather than annual totals. In terms of annual totals, which averaged around 1045 +/- 260 mm during the historical period, the precipitation total is projected to reach 1095 +/- 285 mm under SSP245 or 1110 +/- 293 mm under SSP585 in the far future. Occurrences surpassing the 95th and 99th percentiles, as well as the maximum consecutive precipitation, are projected to substantially increase under both shared socioeconomic pathways (SSP245 and SSP585) in the future, with a more pronounced increase in the severe scenario (SSP585). This study highlights the potential impact of human-induced activities on precipitation extremes. It is crucial that these findings inform the development of climate change adaptation and mitigation strategies for the future.
C1 [Talchabhadel, Rocky; Bhattarai, Saurav; Bista, Sunil] Jackson State Univ, Dept Civil & Environm Engn, Jackson, MS 39217 USA.
RP Talchabhadel, R (corresponding author), Jackson State Univ, Dept Civil & Environm Engn, Jackson, MS 39217 USA.
EM rocky.talchabhadel@jsums.edu
FU U.S. Army Engineer Research and Development Center (ERDC)
FX This research is supported by the Hydrological Impacts Computing,
   Outreach, and Resiliency Partnership (HICORPS) Project, in collaboration
   with the U.S. Army Engineer Research and Development Center (ERDC) and
   Taylor-WOOLPERT.
CR Alexander LV, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006290
   Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   Anderson BT, 2015, J GEOPHYS RES-ATMOS, V120, P4842, DOI 10.1002/2014JD022960
   Benedict I, 2020, J HYDROMETEOROL, V21, P299, DOI 10.1175/JHM-D-19-0094.1
   Bird LJ, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-023-01142-4
   Cook BI, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1400082
   Di Virgilio G, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002625
   Donat MG, 2016, NAT CLIM CHANGE, V6, P508, DOI [10.1038/nclimate2941, 10.1038/NCLIMATE2941]
   Easterling D. R., 2017, CLIMATE SCI SPECIAL, P207, DOI DOI 10.7930/J0H993CC
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Eyring V, 2019, NAT CLIM CHANGE, V9, P102, DOI 10.1038/s41558-018-0355-y
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Gautam S, 2023, SCI REP-UK, V13, DOI 10.1038/s41598-023-48650-z
   Groisman PY, 2005, J CLIMATE, V18, P1326, DOI 10.1175/JCLI3339.1
   Groisman PY, 2004, J HYDROMETEOROL, V5, P64, DOI 10.1175/1525-7541(2004)005<0064:CCOTHC>2.0.CO;2
   Harp RD, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2022GL099955
   Higgins RW, 2013, J HYDROMETEOROL, V14, P105, DOI 10.1175/JHM-D-12-062.1
   Ingram W, 2016, NAT CLIM CHANGE, V6, P443, DOI 10.1038/nclimate2966
   Kahraman A, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2020GL092361
   Kharin VV, 2007, J CLIMATE, V20, P1419, DOI 10.1175/JCLI4066.1
   Kim H, 2024, NAT COMMUN, V15, DOI 10.1038/s41467-023-44415-4
   Kunkel KE, 2013, B AM METEOROL SOC, V94, P499, DOI 10.1175/BAMS-D-11-00262.1
   Lehner B., 2008, EoS Transactions, V89, P93, DOI [DOI 10.1029/2008EO100001, 10.1029/2008EO100001]
   Lehner B, 2013, HYDROL PROCESS, V27, P2171, DOI 10.1002/hyp.9740
   Lewis JW, 2023, THEOR APPL CLIMATOL, V151, P1013, DOI 10.1007/s00704-022-04243-w
   Mallakpour I, 2022, WEATHER CLIM EXTREME, V36, DOI 10.1016/j.wace.2022.100433
   Mallakpour I, 2017, THEOR APPL CLIMATOL, V130, P345, DOI 10.1007/s00704-016-1881-z
   Meehl GA, 2000, B AM METEOROL SOC, V81, P427, DOI 10.1175/1520-0477(2000)081<0427:TIEWAC>2.3.CO;2
   Meehl GA, 2000, B AM METEOROL SOC, V81, P413, DOI 10.1175/1520-0477(2000)081<0413:AITTIE>2.3.CO;2
   Moustakis Y, 2020, COMMUN EARTH ENVIRON, V1, DOI 10.1038/s43247-020-0003-0
   Munoz SE, 2018, NATURE, V556, P95, DOI 10.1038/nature26145
   Myhre G, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-52277-4
   O'Gorman PA, 2009, P NATL ACAD SCI USA, V106, P14773, DOI 10.1073/pnas.0907610106
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Oh SG, 2023, ASIA-PAC J ATMOS SCI, V59, P367, DOI 10.1007/s13143-023-00320-w
   Pendergrass AG, 2015, GEOPHYS RES LETT, V42, P8767, DOI 10.1002/2015GL065854
   Pendergrass AG, 2014, J CLIMATE, V27, P757, DOI 10.1175/JCLI-D-13-00163.1
   Rahimi L, 2024, EARTHS FUTURE, V12, DOI 10.1029/2024EF004531
   Rajib A, 2021, SCI DATA, V8, DOI 10.1038/s41597-021-01048-w
   Robinson A, 2021, NPJ CLIM ATMOS SCI, V4, DOI 10.1038/s41612-021-00202-w
   Sun Y, 2007, J CLIMATE, V20, P4801, DOI 10.1175/JCLI4263.1
   Tabari H, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab55fd
   Talchabhadel R, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14235954
   Talchabhadel R, 2018, INT J CLIMATOL, V38, P4296, DOI 10.1002/joc.5669
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Thornton MM, 2022, ORNL DAAC
   Thrasher B, 2012, HYDROL EARTH SYST SC, V16, P3309, DOI 10.5194/hess-16-3309-2012
   Thrasher B, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01393-4
   Toreti A, 2013, GEOPHYS RES LETT, V40, P4887, DOI 10.1002/grl.50940
   Trenberth KE, 2003, B AM METEOROL SOC, V84, P1205, DOI 10.1175/BAMS-84-9-1205
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Wood RR, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac10dd
   Xu ZF, 2015, J GEOPHYS RES-ATMOS, V120, P3063, DOI 10.1002/2014JD022958
   Yu G, 2023, J HYDROMETEOROL, V24, P87, DOI 10.1175/JHM-D-22-0117.1
NR 54
TC 0
Z9 0
U1 0
U2 0
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD 2024 DEC 30
PY 2024
DI 10.1002/joc.8748
EA DEC 2024
PG 18
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA R0H3N
UT WOS:001388368900001
DA 2025-01-10
ER

PT J
AU Vasconcelos, L
   Langemeyer, J
   Cole, HVS
   Baró, F
AF Vasconcelos, Luma
   Langemeyer, Johannes
   Cole, Helen V. S.
   Baro, Francesc
TI Nature-based climate shelters? Exploring urban green spaces as cooling
   solutions for older adults in a warming city
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE Thermal comfort; Climate shelters; Climate change adaptation;
   Nature-based solutions; Urban Heat Island; Ecosystem services;
   Vulnerability
ID ECOSYSTEM SERVICES; THERMAL COMFORT; HEAT; MICROCLIMATE; PREFERENCES;
   HEALTH; HOT
AB As cities grapple with the escalating challenges of urban heat and its impacts on vulnerable populations, particularly older adults, green spaces are increasingly promoted as effective urban cooling solutions. However, despite the extensive literature on people's access to and preferences for urban green spaces, little is known about the perception and use of these spaces as nature-based climate shelters on hot days, especially by older adults. This study focuses on Barcelona, a Mediterranean city facing rising temperatures, to explore older adults' patterns of use and preferences for urban green spaces on hot days. The research aims to: 1) analyze heat coping behaviors, emphasizing visits to urban green spaces; 2) identify crucial characteristics of green spaces for older adults; and 3) assess variations in behaviors and preferences based on socio-demographic factors. The study leverages survey data from 291 older adult residents, combining face-to-face and online formats. Results indicate that 54 % of older adults use urban green spaces for cooling on hot days, with preferences for morning or evening visits. Factors influencing non-visitation include perceived lack of thermal comfort, noisiness or crowdedness, and proximity issues. Alternative heat coping strategies include staying at home, traveling to cooler areas outside the city, visiting blue spaces, or air-conditioned indoor facilities. Preferred green space characteristics include abundant shade, leafy vegetation, accessibility factors (e.g., walkability), urban furniture (e.g., benches), and water features. Socio-demographic differences reveal higher green space use among younger age groups and residents in certain districts. Mobility limitations and lower education levels influence preferences, with mobility-challenged individuals prioritizing accessibility aspects. Lower-educated respondents are more likely to report barriers to accessing green spaces. These findings highlight the need for tailored urban planning strategies, considering sociodemographic variations, to mitigate heat-related health risks for older adults. By prioritizing green space accessibility, enhancing its quality, promoting its cooling benefits, addressing cooling inequalities and integrating climate considerations in urban green planning, cities facing increasingly pressing heat challenges can create climate-resilient and inclusive green environments that prioritize the well-being of their aging populations.
C1 [Vasconcelos, Luma] Univ Politecn Madrid UPM, Higher Tech Sch Architecture Madrid, Dept Urbanist & Ordenac Terr, Juan Herrera Ave, 4, Madrid 28040, Spain.
   [Langemeyer, Johannes; Cole, Helen V. S.] Univ Autonoma Barcelona UAB, Inst Environm Sci & Technol ICTA, Edif Z ICTA ICP, Carrer Columnes S-N,Campus UAB, Cerdanyola Del Valles 08193, Spain.
   [Langemeyer, Johannes] Humboldt Univ, Dept Geog, Berlin, Germany.
   [Baro, Francesc] Vrije Univ Brussel VUB, Dept Geog, Pleinlaan 2, B-1050 Brussels, Belgium.
   [Baro, Francesc] Vrije Univ Brussel VUB, Dept Sociol, Pleinlaan 2, B-1050 Brussels, Belgium.
   [Langemeyer, Johannes] Barcelona Supercomp Ctr BSC, Placa Eusebi Guell 1-3, Barcelona 08034, Spain.
C3 Universidad Politecnica de Madrid; Autonomous University of Barcelona;
   Humboldt University of Berlin; Vrije Universiteit Brussel; Vrije
   Universiteit Brussel; Universitat Politecnica de Catalunya; Barcelona
   Supercomputer Center (BSC-CNS)
RP Baró, F (corresponding author), Vrije Univ Brussel VUB, Dept Geog, Pleinlaan 2, B-1050 Brussels, Belgium.
RI Langemeyer, Johannes/AAH-7736-2020; Baro, Francesc/C-1564-2019
OI Cole, Helen/0000-0003-0936-6810; Langemeyer,
   Johannes/0000-0002-0558-8486; Baro, Francesc/0000-0002-0145-6320
FU RADARS project; Maria de Maeztu" Program for Units of Excellence of the
   Spanish Ministry of Science and Innovation [CEX2019-000940-M]
FX We thank the Urban Resilience Department of the Barcelona City Council,
   ICTA-UAB communication department, the RADARS project, the Caritas
   Diocesana de Barcelona, and the professors of the course Urban and
   Industrial Ecology (Master SAES, UAB) for their valuable help in the
   development of this research. We also acknowledge the invaluable
   contribution of the older adults who responded to the questionnaire and
   the volunteers who assisted some of them. This research contributes to
   the "Maria de Maeztu" Program for Units of Excellence of the Spanish
   Ministry of Science and Innovation (CEX2019-000940-M) . Finally, we also
   appreciate the work of two anonymous reviewers for their valuable
   comments and suggestions to the original version of the manuscript.
CR Akinci ZS, 2021, J AGING PHYS ACTIV, V29, P781, DOI 10.1123/japa.2020-0254
   Ali SB, 2018, URBAN CLIM, V24, P954, DOI 10.1016/j.uclim.2017.11.006
   Alied M, 2022, LANCET HEALTH LONGEV, V3, pE647, DOI 10.1016/S2666-7568(22)00198-2
   Amorim-Maia A.T., 2023, The Conversation
   Amorim-Maia AT, 2023, LANDSCAPE URBAN PLAN, V238, DOI 10.1016/j.landurbplan.2023.104836
   [Anonymous], 2008, Reducing Urban Heat Islands: Compendium of Strategies
   Arnberger A, 2017, URBAN FOR URBAN GREE, V21, P102, DOI 10.1016/j.ufug.2016.11.012
   Arnberger A, 2015, URBAN FOR URBAN GREE, V14, P872, DOI 10.1016/j.ufug.2015.07.005
   Baquero Larriva Maria Teresa, 2019, Rev Esp Geriatr Gerontol, V54, P280, DOI 10.1016/j.regg.2019.01.006
   Barcelona City Council, 2021, SUPERILLA BARCELONA
   Barcelona City Council, 2018, Climate Plan 2018-2030
   Barcelona City Council, 2022, Estadistica y Difusion de Datos
   Barcelona City Council, 2021, Barcelona Nature Plan 2030
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Baro F, 2019, ENVIRON SCI POLICY, V102, P54, DOI 10.1016/j.envsci.2019.08.016
   Barreira AP, 2023, CITIES, V141, DOI 10.1016/j.cities.2023.104478
   Basu S, 2021, URBAN FOR URBAN GREE, V57, DOI 10.1016/j.ufug.2020.126959
   Berisha V, 2017, WEATHER CLIM SOC, V9, P71, DOI 10.1175/WCAS-D-16-0033.1
   Camacho-Caballero D, 2024, SUSTAIN CITIES SOC, V103, DOI 10.1016/j.scs.2024.105257
   Enssle F, 2020, ENVIRON SCI POLICY, V109, P36, DOI 10.1016/j.envsci.2020.04.008
   Eurostat, 2023, Statistics Explained
   Farahani Leila Mahmoudi, 2018, Landscape Online, P1, DOI 10.3097/LO.201861
   Frantzeskaki N, 2019, BIOSCIENCE, V69, P455, DOI 10.1093/biosci/biz042
   Garcia-Sierra M., 2022, Heat in the future: Climate change vulnerability index (IVAC)
   Gómez-Baggethun E, 2013, ECOL ECON, V86, P235, DOI 10.1016/j.ecolecon.2012.08.019
   Hanson HI, 2021, URBAN FOR URBAN GREE, V63, DOI 10.1016/j.ufug.2021.127198
   INE, 2023, ENCUESTA EQUIPAMIENT
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2021The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel On Climate Change, DOI [10.1017/9781009325844.001, DOI 10.1017/9781009157940, 10.1017/9781009157896]
   Kabisch N, 2020, ENVIRON SCI POLICY, V107, P56, DOI 10.1016/j.envsci.2020.02.008
   Laatikainen T, 2015, LANDSCAPE URBAN PLAN, V144, P22, DOI 10.1016/j.landurbplan.2015.08.004
   Lau KKL, 2021, URBAN FOR URBAN GREE, V64, DOI 10.1016/j.ufug.2021.127251
   Louafi-Bellara S, 2016, J NEW TECHNOL MATER, V6, P87
   Lu RY, 2023, ATMOS OCEAN SCI LETT, V16, DOI 10.1016/j.aosl.2022.100290
   Ma XY, 2021, SCI TOTAL ENVIRON, V768, DOI 10.1016/j.scitotenv.2021.144985
   Marando F, 2022, SUSTAIN CITIES SOC, V77, DOI 10.1016/j.scs.2021.103564
   Mees HLP, 2015, REG ENVIRON CHANGE, V15, P1065, DOI 10.1007/s10113-014-0681-1
   Moss JL, 2019, URBAN FOR URBAN GREE, V37, P65, DOI 10.1016/j.ufug.2018.07.023
   Mueller N, 2020, ENVIRON INT, V134, DOI 10.1016/j.envint.2019.105132
   Panno A, 2017, ENVIRON RES, V159, P249, DOI 10.1016/j.envres.2017.08.016
   Phillips A, 2022, URBAN FOR URBAN GREE, V74, DOI 10.1016/j.ufug.2022.127674
   Phillips A, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063461
   Prodhomme C, 2022, CLIM DYNAM, V58, P2149, DOI 10.1007/s00382-021-05828-3
   Ribeiro AI, 2021, ENVIRON INT, V154, DOI 10.1016/j.envint.2021.106664
   Ring Z, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127131
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Rousi E, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-31432-y
   Seddon N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0120
   Singh S, 2021, ASIAN J PSYCHIATR, V65, DOI 10.1016/j.ajp.2021.102850
   Singleton R., 1999, Royce Singleton, and Bruce C. Straits. Approaches to Social Research
   Sodoudi S, 2018, URBAN FOR URBAN GREE, V34, P85, DOI 10.1016/j.ufug.2018.06.002
   Thomson H, 2019, ENERG BUILDINGS, V196, P21, DOI 10.1016/j.enbuild.2019.05.014
   Tirado-Herrero S., 2022, Energy Poverty Alleviation: New Approaches and Contexts, P267, DOI [10.1007/978-3-030-91084-613, DOI 10.1007/978-3-030-91084-6_13, DOI 10.1007/978-3-030-91084-613]
   UN, 2023, World Social Report 2023
   Veerkamp CJ, 2021, ECOSYST SERV, V52, DOI 10.1016/j.ecoser.2021.101367
   Wen C, 2020, URBAN FOR URBAN GREE, V55, DOI 10.1016/j.ufug.2020.126820
   Widerynski S., 2017, The Use of Cooling Centers to Prevent Heat-Related Illness: Summary of Evidence and Strategies for Implementation Climate and Health Technical Report Series Climate and Health Program, DOI [10.13140/RG.2.2, DOI 10.13140/RG.2.2]
   Wolff M, 2022, ECOL SOC, V27, DOI 10.5751/ES-13180-270217
   Wu HW, 2022, J BUILD ENG, V54, DOI 10.1016/j.jobe.2022.104682
   Xu C, 2022, SCI TOTAL ENVIRON, V841, DOI 10.1016/j.scitotenv.2022.156687
   Zhang KL, 2022, SCI TOTAL ENVIRON, V821, DOI 10.1016/j.scitotenv.2022.153388
   Zhou WQ, 2021, ONE EARTH, V4, P1764, DOI 10.1016/j.oneear.2021.11.010
   Ziter CD, 2019, P NATL ACAD SCI USA, V116, P7575, DOI 10.1073/pnas.1817561116
NR 62
TC 0
Z9 0
U1 20
U2 20
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 1618-8667
EI 1610-8167
J9 URBAN FOR URBAN GREE
JI Urban For. Urban Green.
PD AUG
PY 2024
VL 98
AR 128408
DI 10.1016/j.ufug.2024.128408
EA JUN 2024
PG 10
WC Plant Sciences; Environmental Studies; Forestry; Urban Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Plant Sciences; Environmental Sciences & Ecology; Forestry; Urban
   Studies
GA H7R7G
UT WOS:001325384100001
DA 2025-01-10
ER

PT J
AU Sperlich, D
   Hanewinkel, M
   Yousefpour, R
AF Sperlich, Dominik
   Hanewinkel, Marc
   Yousefpour, Rasoul
TI Aiming at a moving target: economic evaluation of adaptation strategies
   under the uncertainty of climate change and CO<sub>2</sub> fertilization
   of European beech (<i>Fagus sylvatica</i> L.) and Silver fir (<i>Abies
   alba</i> Mill.)
SO ANNALS OF FOREST SCIENCE
LA English
DT Article
DE Climate change adaptation; eCO(2); Drought; Mixed forests; Land
   expectation value; Uncertainty
ID NORWAY SPRUCE; FOREST MANAGEMENT; MIXED STANDS; SILVICULTURAL
   MANAGEMENT; ABOVEGROUND BIOMASS; CYCLE MODELS; WATER FLUXES; DROUGHT;
   GROWTH; CARBON
AB Key message Drought severely worsened till 2100 and eventually outplayed growth-enhancing CO2 fertilization turning productivity gains into losses for beech and fir. Most scenarios generated notable losses in profitability but economic tipping points were later than for productivity due to lag effects related to discounting. Time mixture of fir and shortening rotation can counteract economic risks under climate change, but requires early admixture and moderate establishment costs.Context Adaptation strategies to climate change (CC) such as establishing mixed forests are often based on ecological understanding while economic rationale is often disregarded.Aims This paper studies CC uncertainty on productivity and profitability of European beech (Fagus sylvatica L.) and Silver fir (Abies alba Mill.). Besides, the economic consequences to actively adapt beech forests by admixing Silver fir are investigated.Methods We used the process-based forest growth model GOTILWA + to simulate RCP2.6, RCP4.5 and RCP8.5 climatic projection by the MPI-ESM-LR global circulation model (MPI-ESM-LR) with the CO2 fertilization effect (eCO2) switched on and off. We analysed the sensitivity of the land expectation value (LEV) on CC and economic parameters.Results CC initially increased productivity, but declined after a tipping point (2040-2070) and later also profitability (2045-2100). RCP8.5 had positive, RCP2.6 negative and RCP4.5 neutral effects on LEV. Switching off eCO2 turned RCP8.5 from the most profitable to the least profitable scenario and the opposite for RCP2.6. CC generally reduced optimal rotation (Ropt) being scenario dependant, but comparatively more for fir than beech. Admixing fir created an economic benefit when implemented before stand age 50 of beech. This benefit was nullified with protection costs for browsing control (fencing or tree shelters).Conclusions Economic parameters (not CC) were the major source of uncertainty stemming from discounting factors and establishment costs. Admixture of fir and shortening rotation can provide a solution to tackle economic and climate uncertainties, but requires early admixture and browsing control.
C1 [Sperlich, Dominik; Hanewinkel, Marc; Yousefpour, Rasoul] Univ Freiburg, Fac Environm & Nat Resources, Forestry Econ & Forest Planning, D-79106 Freiburg, Germany.
   [Yousefpour, Rasoul] Univ Toronto, Inst Forestry & Conservat, John Daniels Fac Architecture Landscape & Design, 33 Willcocks St, Toronto, ON M5S 3B3, Canada.
C3 University of Freiburg; University of Toronto
RP Sperlich, D (corresponding author), Univ Freiburg, Fac Environm & Nat Resources, Forestry Econ & Forest Planning, D-79106 Freiburg, Germany.
EM dominik.sperlich@ife.uni-freiburg.de
RI hanewinkel, marc/E-5639-2011; Yousefpour, Rasoul/F-1601-2017
OI Hanewinkel, Marc/0000-0003-4081-6621
FU BMEL
FX Not applicable.
CR Aicher S, 2016, CONSTR BUILD MATER, V124, P1007, DOI 10.1016/j.conbuildmat.2016.08.051
   Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Almeida I, 2018, FORESTS, V9, DOI 10.3390/f9100627
   ALRahahleh L, 2018, FORESTS, V9, DOI 10.3390/f9040208
   Anderegg WRL, 2013, NAT CLIM CHANGE, V3, P30, DOI 10.1038/nclimate1635
   [Anonymous], 2020, Encycl. Life
   Augustynczik ALD, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-33389-9
   Augustynczik ALD, 2017, FOREST ECOL MANAG, V401, P192, DOI 10.1016/j.foreco.2017.06.061
   Augustynczik ALD, 2019, SCI TOTAL ENVIRON, V650, P2717, DOI 10.1016/j.scitotenv.2018.09.366
   Barna M, 2015, FOREST ECOL MANAG, V342, P93, DOI 10.1016/j.foreco.2015.01.017
   Baumbach L, 2019, REG ENVIRON CHANGE, V19, P1159, DOI 10.1007/s10113-019-01472-0
   BayStat, 2016, Tannenoffensive Bayern
   Bernard M, 2017, FOREST ECOL MANAG, V400, P269, DOI 10.1016/j.foreco.2017.05.040
   BMEL, 2016, Der Wald in Deutschland - Ausgewahlte Ergebnisse der dritten Bundeswaldinventur
   BMEL, 2022, Ergebnisse Waldzustandsbericht 2021
   BMEL, 2022, Bundesministerium fur Ernahrung und Landwirtschaft
   Bolte A, 2009, SCAND J FOREST RES, V24, P473, DOI 10.1080/02827580903418224
   Bonn B, 2020, CLIMATE, V8, DOI 10.3390/cli8100105
   Bosela M, 2018, SCI TOTAL ENVIRON, V615, P1460, DOI 10.1016/j.scitotenv.2017.09.092
   Bravo-Oviedo A, 2014, FOREST SYST, V23, P518, DOI 10.5424/fs/2014233-06256
   Brodribb TJ, 2020, SCIENCE, V368, P261, DOI 10.1126/science.aat7631
   Brunette M, 2020, CLIMATIC CHANGE, V162, P2157, DOI 10.1007/s10584-020-02751-0
   BRZEZIECKI B, 1994, FOREST ECOL MANAG, V69, P167, DOI 10.1016/0378-1127(94)90227-5
   Büntgen U, 2014, FRONT ECOL ENVIRON, V12, P100, DOI 10.1890/130089
   Bugmann H, 2019, ECOSPHERE, V10, DOI 10.1002/ecs2.2616
   BuTaKli, 2019, Buchen-Tannen-Mischwalder zur Anpassung von Wirtschaftswaldern an Extremereignisse des Klimawandels
   BWI, 2012, Dritte Bundeswaldinventur
   Ciais P, 2005, NATURE, V437, P529, DOI 10.1038/nature03972
   de Wergifosse L, 2020, ANN FOREST SCI, V77, DOI 10.1007/s13595-020-00966-w
   Destatis, 2022, Erzeugerpreisindizes der Produkte des Holzeinschlags aus den Staatsforsten
   Dieter M, 2001, FOREST POLICY ECON, V2, P157, DOI 10.1016/S1389-9341(01)00045-4
   Dyderski MK, 2018, GLOBAL CHANGE BIOL, V24, P1150, DOI 10.1111/gcb.13925
   EEA-European Environment Agency, 2016, European Forest Ecosystems. State and Trends
   Ellenberg H., 1996, Vegetation Mitteleuropas mit den Alpen
   Espinoza O, 2018, CURR FOR REP, V4, P1, DOI 10.1007/s40725-018-0071-x
   Faustmann M., 1849, Journal of Forest Economics, V1, P7, DOI [10.4324/9781315182681-2, DOI 10.4324/9781315182681-2]
   FNR, 2023, Klimaangepasstes Waldmanagement
   Forest Europe, 2020, MINISTERIAL C PROTEC
   Forrester DI, 2013, FOREST ECOL MANAG, V304, P233, DOI 10.1016/j.foreco.2013.04.038
   Friedrich S, 2019, FOREST POLICY ECON, V104, P65, DOI 10.1016/j.forpol.2019.04.003
   FVA-BW, 2019, Waldzustandsbericht 2019
   FVA-BW, 2020, Waldzustandsbericht 2020
   Gebauer T, 2008, TREE PHYSIOL, V28, P1821, DOI 10.1093/treephys/28.12.1821
   Gessler A, 2007, TREES-STRUCT FUNCT, V21, P1, DOI 10.1007/s00468-006-0107-x
   Gracia CA, 1999, ECOL STU AN, V137, P163
   Groom B, 2005, ENVIRON RESOUR ECON, V32, P445, DOI 10.1007/s10640-005-4681-y
   Hagen R, 2017, EUR J WILDLIFE RES, V63, DOI 10.1007/s10344-017-1155-9
   Hanewinkel M., 2009, CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, V4, P1, DOI 10.1079/PAVSNNR20094031
   Hanewinkel M, 2001, FOREST ECOL MANAG, V151, P181, DOI 10.1016/S0378-1127(00)00707-6
   Hanewinkel M, 2014, J ENVIRON MANAGE, V134, P153, DOI 10.1016/j.jenvman.2014.01.010
   Hanewinkel M, 2013, NAT CLIM CHANGE, V3, P203, DOI [10.1038/NCLIMATE1687, 10.1038/nclimate1687]
   Hanewinkel M, 2010, FOREST ECOL MANAG, V259, P710, DOI 10.1016/j.foreco.2009.08.021
   Headache classification Committee of the International Headache Society (IHS), 2018, Cephalalgia, V38, P1, DOI [10.1177/0333102417738202, DOI 10.1177/0333102417738202, DOI 10.2833/9937]
   Hepburn CJ, 2007, J FOREST ECON, V13, P169, DOI 10.1016/j.jfe.2007.02.008
   Hickler T, 2015, CURR FOR REP, V1, P69, DOI 10.1007/s40725-015-0014-8
   IPCC, 2018, Global Warming of 1.5C. An IPCC Special Report on the Impacts of Global Warming of 1.5C above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty
   Jump AS, 2006, GLOBAL CHANGE BIOL, V12, P2163, DOI 10.1111/j.1365-2486.2006.01250.x
   Jump AS, 2005, ECOL LETT, V8, P1010, DOI 10.1111/j.1461-0248.2005.00796.x
   Kahle HP, 2008, EUR FOR I RES REP, V21, P127
   Kant S., 2013, Post-Faustmann Forest Resource Economics, P1, DOI [10.1007/978-94-007-5778-3, DOI 10.1007/978-94-007-5778-3, DOI 10.1007/978-94-007-5778-3_1]
   Keenan T, 2009, BIOGEOSCIENCES, V6, P1423, DOI 10.5194/bg-6-1423-2009
   Keenan TF, 2023, NAT CLIM CHANGE, V13, P1376, DOI 10.1038/s41558-023-01867-2
   Keenan T, 2011, GLOBAL CHANGE BIOL, V17, P565, DOI 10.1111/j.1365-2486.2010.02254.x
   Kellomäki S, 2018, FORESTS, V9, DOI 10.3390/f9030118
   Kladtke J, 2010, Die Durchforstungshilfe 2010 - eine Entscheidungshilfe fur die Praxis
   Klemperer W.D., 1996, Forest resource economics and finance
   Klopcic M, 2017, EUR J FOREST RES, V136, P1071, DOI 10.1007/s10342-017-1052-5
   Knoke T, 2003, ECOL MODEL, V169, P295, DOI 10.1016/S0304-3800(03)00276-X
   Knoke T, 2005, FOREST ECOL MANAG, V213, P102, DOI 10.1016/j.foreco.2005.03.043
   Knoke T, 2005, ECOL ECON, V52, P97, DOI 10.1016/j.ecolecon.2004.06.012
   Knoke T, 2008, ECOL MODEL, V210, P487, DOI 10.1016/j.ecolmodel.2007.08.011
   Knoke T, 2020, FOREST POLICY ECON, V118, DOI 10.1016/j.forpol.2020.102239
   Knoke T, 2017, FOREST POLICY ECON, V83, P58, DOI 10.1016/j.forpol.2017.06.005
   Knoke T, 2017, CURR FOR REP, V3, P93, DOI 10.1007/s40725-017-0054-3
   Knutti R, 2015, CLIMATIC CHANGE, V133, P361, DOI 10.1007/s10584-015-1340-3
   Kolo H, 2020, ECOSYST SERV, V44, DOI 10.1016/j.ecoser.2020.101147
   Kramer K, 2002, GLOBAL CHANGE BIOL, V8, P213, DOI 10.1046/j.1365-2486.2002.00471.x
   Kublin E, 2007, Das Sortenund Volumenprogramm BDAT
   Landesforest.RLP, 2019, Weisstanneninitiative
   LFBW, 2014, Richtlinie Landesweiter Waldentwicklungstypen
   Li XY, 2020, FOREST POLICY ECON, V113, DOI 10.1016/j.forpol.2020.102133
   Liang PH, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-018-37823-w
   Liu YW, 2019, NAT GEOSCI, V12, P809, DOI 10.1038/s41561-019-0436-1
   Meure CM, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL026152
   Magh RK, 2020, J HYDROL, V587, DOI 10.1016/j.jhydrol.2020.124944
   Magh RK, 2019, FORESTS, V10, DOI 10.3390/f10100897
   Metz J, 2016, GLOBAL CHANGE BIOL, V22, P903, DOI 10.1111/gcb.13113
   Mohring B., 2021, Holz-Zentralblatt, V147, P155
   Morales P, 2005, GLOBAL CHANGE BIOL, V11, P2211, DOI 10.1111/j.1365-2486.2005.01036.x
   Moure M, 2023, CURR CLIM CHANGE REP, DOI 10.1007/s40641-023-00189-x
   Müller F, 2018, FOREST POLICY ECON, V95, P46, DOI 10.1016/j.forpol.2018.07.009
   Nadal-Sala D, 2017, MANAG FOR ECOSYST, V34, P81, DOI 10.1007/978-3-319-28250-3_5
   Nadal-Sala D, 2021, GLOBAL CHANGE BIOL, V27, P2970, DOI 10.1111/gcb.15590
   Nadal-Sala D, 2019, FOREST ECOL MANAG, V449, DOI 10.1016/j.foreco.2019.117448
   Nadal-Sala D, 2019, J APPL METEOROL CLIM, V58, P55, DOI 10.1175/JAMC-D-18-0170.1
   Neuner S, 2015, GLOBAL CHANGE BIOL, V21, P935, DOI 10.1111/gcb.12751
   NOAA-GML, 2023, Trends in Atmospheric Carbon Dioxide - Global Monitoring Laboratory (GML)
   Nölte A, 2018, FOREST ECOL MANAG, V422, P345, DOI 10.1016/j.foreco.2018.04.036
   Norby RJ, 2011, ANNU REV ECOL EVOL S, V42, P181, DOI 10.1146/annurev-ecolsys-102209-144647
   Norby RJ, 2010, P NATL ACAD SCI USA, V107, P19368, DOI 10.1073/pnas.1006463107
   Norby RJ, 2005, P NATL ACAD SCI USA, V102, P18052, DOI 10.1073/pnas.0509478102
   Nord-Larsen T, 2015, SCAND J FOREST RES, V30, P135, DOI 10.1080/02827581.2014.986519
   Oberdorfer E, 1977, SUDDEUTSCHE PFLANZ 1
   ONF, 2019, Secheresse: les sapins du Grand Est rougissent
   ONF, 2019, Les degats de la secheresse en cartes
   Otto H.J., 1994, Waldokologie
   Ozkan M, 2022, ISCIENCE, V25, DOI 10.1016/j.isci.2022.103990
   Paul C, 2019, ANN FOREST SCI, V76, DOI 10.1007/s13595-018-0793-8
   Piao SL, 2013, GLOBAL CHANGE BIOL, V19, P2117, DOI 10.1111/gcb.12187
   Popkin G, 2021, SCIENCE, V374, P1184, DOI 10.1126/science.acx9733
   Pretzsch H, 2020, EUR J FOREST RES, V139, P349, DOI 10.1007/s10342-019-01233-y
   Pretzsch H, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms5967
   Radke N, 2020, CLIMATIC CHANGE, V163, P891, DOI 10.1007/s10584-020-02905-0
   Radke N, 2017, ANN FOREST SCI, V74, DOI 10.1007/s13595-017-0641-2
   Reyer C, 2015, CURR FOR REP, V1, P53, DOI 10.1007/s40725-015-0009-5
   Reyer CPO, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5ef1
   Roberge JM, 2016, AMBIO, V45, pS109, DOI 10.1007/s13280-015-0747-4
   Schier F, 2018, EUR J FOREST RES, V137, P279, DOI 10.1007/s10342-018-1111-6
   Schuldt B, 2020, BASIC APPL ECOL, V45, P86, DOI 10.1016/j.baae.2020.04.003
   Schwarz JA, 2019, FRONT FOR GLOB CHANG, V2, DOI 10.3389/ffgc.2019.00079
   Sciomenta M, 2021, CONSTR BUILD MATER, V271, DOI 10.1016/j.conbuildmat.2020.121589
   Sedmáková D, 2019, DENDROCHRONOLOGIA, V54, P37, DOI 10.1016/j.dendro.2019.02.001
   Senn J, 2003, FOREST ECOL MANAG, V181, P151, DOI 10.1016/S0378-1127(03)00129-4
   Sperlich D, 2020, CLIMATE, V8, DOI 10.3390/cli8120141
   Spiecker H, 1999, WATER AIR SOIL POLL, V116, P33, DOI 10.1023/A:1005205515952
   Spiecker H, 2003, J ENVIRON MANAGE, V67, P55, DOI 10.1016/S0301-4797(02)00188-3
   Staupendahl K, 2011, FOREST POLICY ECON, V13, P496, DOI 10.1016/j.forpol.2011.05.007
   Tegel W, 2014, EUR J FOREST RES, V133, P61, DOI 10.1007/s10342-013-0737-7
   Töchterle P, 2020, FORESTS, V11, DOI 10.3390/f11020162
   Valladares F., 2008, V17, P15, DOI 10.1007/978-1-4020-8343-3_2
   Vejpustkova M., 2015, Journal of Forest Science (Prague), V61, P45, DOI 10.17221/100/2014-JFS
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Vitale M, 2007, ATMOS ENVIRON, V41, P5385, DOI 10.1016/j.atmosenv.2007.02.014
   Vitali V, 2017, GLOBAL CHANGE BIOL, V23, P5108, DOI 10.1111/gcb.13774
   Vitasse Y, 2019, EUR J FOREST RES, V138, P547, DOI 10.1007/s10342-019-01192-4
   Vítková L, 2021, FORESTRY, V94, P479, DOI 10.1093/forestry/cpab005
   Wang SH, 2020, SCIENCE, V370, P1295, DOI 10.1126/science.abb7772
   WBW, 2020, Eckpunkte der Wald-strategie 2050
   Willner W, 2017, APPL VEG SCI, V20, P494, DOI 10.1111/avsc.12299
   Yang J, 2015, FOREST CHRON, V91, P23, DOI 10.5558/tfc2015-007
   Yin RS, 1997, FOREST SCI, V43, P113
   Zaehle S, 2014, NEW PHYTOL, V202, P803, DOI 10.1111/nph.12697
   Zamora-Pereira JC, 2021, ANN FOREST SCI, V78, DOI 10.1007/s13595-021-01085-w
   Zanchi G, 2014, ECOL MODEL, V284, P48, DOI 10.1016/j.ecolmodel.2014.04.006
   Zang C, 2014, GLOBAL CHANGE BIOL, V20, P3767, DOI 10.1111/gcb.12637
   Zell J, 2014, EUR J FOREST RES, V133, P649, DOI 10.1007/s10342-014-0793-7
   Zhang Y, 2012, J ECOL, V100, P742, DOI 10.1111/j.1365-2745.2011.01944.x
NR 148
TC 1
Z9 1
U1 0
U2 4
PU SPRINGER FRANCE
PI PARIS
PA 22 RUE DE PALESTRO, PARIS, 75002, FRANCE
SN 1286-4560
EI 1297-966X
J9 ANN FOREST SCI
JI Ann. For. Sci.
PD JAN 15
PY 2024
VL 81
IS 1
AR 4
DI 10.1186/s13595-023-01215-6
PG 42
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA FD6O6
UT WOS:001143864100001
OA gold
DA 2025-01-10
ER

PT J
AU Lesnikowski, A
   Jodoin, S
   Lemay, JP
   Thomson, V
   Johnson, K
AF Lesnikowski, Alexandra
   Jodoin, Sebastien
   Lemay, Jean-Philippe
   Thomson, Verity
   Johnson, Kasia
TI Human rights in climate change adaptation policies: a systematic
   assessment
SO CLIMATE POLICY
LA English
DT Article
DE Human rights; climate change; adaptation; public policy; resilience
ID ADAPTIVE CAPACITY; VULNERABILITY; PERSPECTIVE; GOVERNANCE; PRINCIPLES;
   POLITICS; HEALTH
AB Human rights have potential to enhance adaptation because they reflect internationally agreed upon standards of human dignity, aim to advance formal and substantive forms of equality, and can be used to hold public and private actors accountable for rights violations. We assess whether, how, and under what conditions national adaptation policies recognize human rights principles and standards. We analyze 217 adaptation policies from 147 countries to examine whether there is substantive recognition of the vulnerability and needs of equity-deserving groups that experience systemic marginalization and exclusion, and procedural inclusion of these groups in adaptation planning and decision-making. Results indicate that while under the Paris Agreement governments commit to respect human rights in their adaptation policies and actions, few countries are abiding by this commitment. Only one-third of countries refer to respect, promotion, or consideration of human rights within their adaptation policies. While most countries included here recognize specific conditions of different vulnerable groups in their policies, there is minimal evidence of their inclusion in the adaptation planning and decision-making process, and half of countries fail to identify specific measures that will be developed to reduce their vulnerability. None of the strategies that we reviewed pointed to the creation of accountability mechanisms for redressing harms that may arise due to adaptation actions. We also develop a series of regression models to examine whether hypothesized national predictors of adaptation action are associated with attention to human rights principles and standards. The models indicate that countries with greater wealth and equality are more likely to include attention to human rights norms in their adaptation strategies, but countries with less wealth, more inequality, and less political freedom appear to achieve a more substantive level of engagement with these norms in their strategies.
   Most countries fail to link human rights obligations and adaptation in national policies.Most countries situate national adaptation policies within various structural drivers of vulnerability.Equity-deserving groups are not being included in national adaptation planning in meaningful ways.Participation of equity-deserving groups predicts inclusion of measures to build adaptive capacity among those groups.National governments do not identify accountability mechanisms that address human rights harms from adaptation actions.
C1 [Lesnikowski, Alexandra] Concordia Univ, Dept Geog Planning & Environm, Montreal, PQ, Canada.
   [Jodoin, Sebastien; Lemay, Jean-Philippe; Thomson, Verity; Johnson, Kasia] McGill Univ, Fac Law, Montreal, PQ, Canada.
   [Lesnikowski, Alexandra] Concordia Univ, Dept Geog Planning & Environm, Montreal, PQ H3G 1M8, Canada.
C3 Concordia University - Canada; McGill University; Concordia University -
   Canada
RP Lesnikowski, A (corresponding author), Concordia Univ, Dept Geog Planning & Environm, Montreal, PQ H3G 1M8, Canada.
EM alexandra.lesnikowski@concordia.ca
FU Social Sciences and Humanities Research Council of Canada
FX This work was supported by Social Sciences and Humanities Research
   Council of Canada.
CR Adelman S, 2018, TRANSNATL ENVIRON LA, V7, P9, DOI 10.1017/S2047102518000067
   Atapattu S, 2016, ROUT RES INT ENV LAW, P1
   Bassett TJ, 2013, GEOFORUM, V48, P42, DOI 10.1016/j.geoforum.2013.04.010
   Beauregard C, 2021, CLIM POLICY, V21, P652, DOI 10.1080/14693062.2020.1867047
   Berrang-Ford L, 2015, REG ENVIRON CHANGE, V15, P755, DOI 10.1007/s10113-014-0708-7
   Berrang-Ford L, 2014, CLIMATIC CHANGE, V124, P441, DOI 10.1007/s10584-014-1078-3
   Biesbroek R, 2015, NAT CLIM CHANGE, V5, P493, DOI 10.1038/nclimate2615
   Cameron Edward., 2010, GEORGIA J INT COMP L, V38, P673
   Cameron ES, 2012, GLOBAL ENVIRON CHANG, V22, P103, DOI 10.1016/j.gloenvcha.2011.11.004
   Carmalt J, 2014, HEALTH HUM RIGHTS, V16, P41
   Carmona R., 2023, Climate Action, V2, P1, DOI DOI 10.1038/S44168-023-00048-3
   Christoplos I, 2016, FORUM DEV STUD, V43, P437, DOI 10.1080/08039410.2016.1199443
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   Dekens J., 2019, COORDINATING CLIMATE
   Duyck S., 2018, ROUTLEDGE HDB HUMAN, DOI [https://doi.org/10.4324/9781315312576, DOI 10.4324/9781315312576]
   Duyck S, 2015, REV EUR COMP INT ENV, V24, P123, DOI 10.1111/reel.12125
   Ensor JE, 2015, GLOBAL ENVIRON CHANG, V31, P38, DOI 10.1016/j.gloenvcha.2014.12.005
   Ensor J, 2018, DISASTERS, V42, pS287, DOI 10.1111/disa.12304
   Eriksen S, 2011, CLIM DEV, V3, P7, DOI 10.3763/cdev.2010.0060
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Ford JD, 2018, CLIMATIC CHANGE, V151, P189, DOI 10.1007/s10584-018-2304-1
   Ford JD, 2016, MITIG ADAPT STRAT GL, V21, P839, DOI 10.1007/s11027-014-9627-7
   Ford JD, 2011, CLIMATIC CHANGE, V106, P327, DOI 10.1007/s10584-011-0045-5
   Ford JD, 2004, ARCTIC, V57, P389, DOI 10.14430/arctic516
   Hafner-Burton EM, 2005, AM J SOCIOL, V110, P1373, DOI 10.1086/428442
   Hughes S, 2017, URBAN AFF REV, V53, P362, DOI 10.1177/1078087416649756
   Hyde SD, 2011, AM J POLIT SCI, V55, P356, DOI 10.1111/j.1540-5907.2011.00508.x
   Javeline D, 2014, PERSPECT POLIT, V12, P420, DOI 10.1017/S1537592714000784
   Jodoin S., 2017, Forest Preservation in a Changing Climate: REDD+ and Indigenous and Community Rights in Indonesia and Tanzania Cambridge, United Kingdom
   Jodoin S, 2021, CURR OPIN ENV SUST, V52, P45, DOI 10.1016/j.cosust.2021.06.004
   Jodoin S, 2020, ECOL LAW QUART, V47, P73, DOI 10.15779/Z38W37KW48
   Jodoin S, 2015, REV EUR COMP INT ENV, V24, P117, DOI 10.1111/reel.12126
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Lebovic JH, 2009, J PEACE RES, V46, P79, DOI 10.1177/0022343308098405
   Lesnikowski AC, 2013, GLOBAL ENVIRON CHANG, V23, P1153, DOI 10.1016/j.gloenvcha.2013.04.008
   Lesnikowski AC, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/4/044009
   Lesnikowski A, 2019, CLIMATIC CHANGE, V156, P447, DOI 10.1007/s10584-019-02533-3
   Lesnikowski A, 2016, NAT CLIM CHANGE, V6, P261, DOI [10.1038/NCLIMATE2863, 10.1038/nclimate2863]
   Lesnikowski AC, 2015, MITIG ADAPT STRAT GL, V20, P277, DOI 10.1007/s11027-013-9491-x
   Lewis B., 2018, ENV HUMAN RIGHTS CLI, DOI [https://doi.org/10.1007/978-981-13-1960-0, DOI 10.1007/978-981-13-1960-0]
   Lewis Bridget., 2018, ENV HUMAN RIGHTS CLI
   Massey E, 2014, GLOBAL ENVIRON CHANG, V29, P434, DOI 10.1016/j.gloenvcha.2014.09.002
   McDonnell S, 2020, ANTHROPOL FORUM, V30, P55, DOI 10.1080/00664677.2019.1647828
   McNamara KE, 2017, LOCAL ENVIRON, V22, P443, DOI 10.1080/13549839.2016.1216954
   Merry S.E., 2006, Human Rights and Gender Violence: Translating International Law into Local Justice
   Nyong A., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P787, DOI 10.1007/s11027-007-9099-0
   O'Brien K., 2013, P TRANSFORMATION CHA, P16
   O'Brien K, 2007, CLIM POLICY, V7, P73, DOI 10.1080/14693062.2007.9685639
   Peel Jaqueline, 2020, Climate Change Litigation in the Asia Pacific, P294
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Pelling M, 2015, CLIMATIC CHANGE, V133, P113, DOI 10.1007/s10584-014-1303-0
   Quirico O, 2018, NETH INT LAW REV, V65, P185, DOI 10.1007/s40802-018-0110-0
   Remling E, 2015, CLIM DEV, V7, P16, DOI 10.1080/17565529.2014.886992
   Risse T., 2013, The persistent power of human rights: From commitment to compliance
   Roht-Arriaza Naomi, 2010, Georgia Journal of International Comparative Law, V38, P593
   Romero-Lankao P, 2018, NAT CLIM CHANGE, V8, P754, DOI 10.1038/s41558-018-0264-0
   Savaresi A, 2022, J HUM RIGHTS ENVIRON, V13, P7
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   SHELLEY M, 1984, J AM STAT ASSOC, V79, P240, DOI 10.2307/2288384
   Shi LD, 2016, NAT CLIM CHANGE, V6, P131, DOI 10.1038/NCLIMATE2841
   Simmons BethA., 2009, MOBILIZING HUMAN RIG
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Sovacool BK., 2016, The Political Economy of Climate Change Adaptation
   Termeer CJAM, 2017, J ENVIRON PLANN MAN, V60, P558, DOI 10.1080/09640568.2016.1168288
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   UNFCCC, 2015, THE PARIS AGREEMENT, VFCCC/CP/20
   Venn A., 2017, CLIM LAW, V7, P322, DOI [https://doi.org/10.1163/18786561-00704005, DOI 10.1163/18786561-00704005]
   Weichselgartner J, 2015, PROG HUM GEOG, V39, P249, DOI 10.1177/0309132513518834
   Wellstead AM, 2013, ECOL SOC, V18, DOI 10.5751/ES-05685-180323
   Whitehead M, 2013, URBAN STUD, V50, P1348, DOI 10.1177/0042098013480965
   Zeileis A, 2008, J STAT SOFTW, V27, P1, DOI 10.18637/jss.v027.i08
NR 71
TC 0
Z9 0
U1 1
U2 13
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PD SEP 13
PY 2024
VL 24
IS 8
BP 1050
EP 1064
DI 10.1080/14693062.2023.2261881
EA OCT 2023
PG 15
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA D1P2Q
UT WOS:001080194300001
DA 2025-01-10
ER

PT J
AU Booth, RK
   Schuurman, GW
   Lynch, EA
   Huff, MG
   Bebout, JA
   Montano, NM
AF Booth, Robert K.
   Schuurman, Gregor W.
   Lynch, Elizabeth A.
   Huff, Matthew G.
   Bebout, Julia A.
   Montano, Nisogaabokwe Melonee
TI Paleoecology provides context for conserving culturally and ecologically
   important pine forest and barrens communities
SO ECOLOGICAL APPLICATIONS
LA English
DT Article
DE climate change adaptation; cultural landscape; fire history; Indigenous
   stewardship; natural resource management; Ojibwe people; palynology;
   testate amoebae; vegetation history
ID CLIMATE-CHANGE; HOLOCENE CLIMATE; CHARCOAL RECORDS; FIRE REGIMES;
   NORTHERN ROCKIES; SEDIMENTS; LAKES; BIODIVERSITY; VEGETATION; DROUGHT
AB In fire-prone ecosystems, knowledge of vegetation-fire-climate relationships and the history of fire suppression and Indigenous cultural burning can inform discussions of how to use fire as a management tool, particularly as climate continues to change rapidly. On Wiisaakodewan-minis/Stockton Island in the Apostle Islands National Lakeshore of Wisconsin, USA, structural changes in a pine-dominated natural area containing a globally rare barrens community occurred after the cessation of cultural burning by the Indigenous Ojibwe people and the imposition of fire-suppression policies, leading to questions about the historical role of fire in this culturally and ecologically important area. To help understand better the ecological context needed to steward these pine forest and barrens communities, we developed palaeoecological records of vegetation, fire, and hydrological change using pollen, charcoal, and testate amoebae preserved in peat and sediment cores collected from bog and lagoon sediments within the pine-dominated landscape. Results indicated that fire has been an integral part of Stockton Island ecology for at least 6000 years. Logging in the early 1900s led to persistent changes in island vegetation, and post-logging fires of the 1920s and 1930s were anomalous in the context of the past millennium, likely reflecting more severe and/or extensive burning than in the past. Before that, the composition and structure of pine forest and barrens had changed little, perhaps due to regular low-severity surface fires, which may have occurred with a frequency consistent with Indigenous oral histories (similar to 4-8 years). Higher severity fire episodes, indicated by large charcoal peaks above background levels in the records, occurred predominantly during droughts, suggesting that more frequent or more intense droughts in the future may increase fire frequency and severity. The persistence of pine forest and barrens vegetation through past periods of climatic change indicates considerable ecological resistance and resilience. Future persistence in the face of climate changes outside this historical range of variability may depend in part on returning fire to these systems.
C1 [Booth, Robert K.; Bebout, Julia A.] Lehigh Univ, Earth & Environm Sci Dept, Bethlehem, PA 18015 USA.
   [Schuurman, Gregor W.] United States Natl Pk Serv Climate Change Response, Ft Collins, CO USA.
   [Lynch, Elizabeth A.] Luther Coll, Biol Dept, Decorah, IA USA.
   [Montano, Nisogaabokwe Melonee] Red Cliff Band Lake Super Chippewa, Bayfield, WI USA.
   [Montano, Nisogaabokwe Melonee] Great Lakes Indian Fish & Wildlife Commiss, Climate Change Program, Odanah, WI USA.
C3 Lehigh University
RP Booth, RK (corresponding author), Lehigh Univ, Earth & Environm Sci Dept, Bethlehem, PA 18015 USA.
EM rkb205@lehigh.edu
RI Booth, Robert/G-5563-2010
OI Lynch, Elizabeth Ann/0000-0002-4455-764X; Schuurman,
   Gregor/0000-0002-9304-7742; Bebout, Julia/0009-0006-1893-0670
FU ~National Park Service [140P6418P0035]
FX National Park Service, Grant/Award Number: 140P6418P0035
CR Amesbury MJ, 2018, QUATERNARY SCI REV, V201, P483, DOI 10.1016/j.quascirev.2018.10.034
   Anderegg WRL, 2022, ECOL LETT, V25, P1510, DOI 10.1111/ele.14018
   Anderson RC., 1999, Savannas, barrens, and rock outcrop plant communities of North America, DOI [10.1017/CBO9780511574627, DOI 10.1017/CBO9780511574627]
   Anderton J.B., 1999, GREAT LAKES GEOGRAPH, V6, P29
   Ashland Daily Press, 1934, ASHLAND DAILY P 0815
   BEALS EW, 1960, ECOLOGY, V41, P743, DOI 10.2307/1931808
   Berkes F, 2006, INT SOC SCI J, V58, P35, DOI 10.1111/j.1468-2451.2006.00605.x
   Blaauw M, 2010, QUAT GEOCHRONOL, V5, P512, DOI 10.1016/j.quageo.2010.01.002
   Booth R. K., 2021, NPSAAPISNRR20212221, DOI [10.36967/nrr-2284385, DOI 10.36967/NRR-2284385]
   Booth RK, 2004, QUATERNARY RES, V61, P1, DOI 10.1016/j.yqres.2003.07.013
   Booth RK, 2006, EARTH PLANET SC LETT, V242, P415, DOI 10.1016/j.epsl.2005.12.028
   Booth RK., 2010, Mires and Peat, V7, P1, DOI DOI 10.4067/50716-078X2007000300008
   Booth RK, 2008, J QUATERNARY SCI, V23, P43, DOI 10.1002/jqs.1114
   Booth RK, 2012, ECOLOGY, V93, P219, DOI 10.1890/11-1068.1
   Buma B, 2019, LANDSCAPE ECOL, V34, P17, DOI 10.1007/s10980-018-0754-5
   Burkman P., 2008, RETHINKING PROTECTED
   Busch JaneC., 2008, People and Places: A Human History of the Apostle Islands - Historic Resource Study of Apostle Islands National Lakeshore
   Calcote R, 2021, HOLOCENE, V31, P409, DOI 10.1177/0959683620972760
   Calder WJ, 2015, P NATL ACAD SCI USA, V112, P13261, DOI 10.1073/pnas.1500796112
   Charman DJ, 2006, QUATERNARY SCI REV, V25, P336, DOI 10.1016/j.quascirev.2005.05.005
   Clifford MJ, 2015, HOLOCENE, V25, P1102, DOI 10.1177/0959683615580182
   Clifford MJ, 2013, CLIMATIC CHANGE, V119, P693, DOI 10.1007/s10584-013-0771-y
   Coffin B. A., 1977, THESIS U MINNESOTA
   Collins M, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1029
   Conedera M, 2009, QUATERNARY SCI REV, V28, P555, DOI 10.1016/j.quascirev.2008.11.005
   Davis M, 2000, CONSERV BIOL, V14, P968, DOI 10.1046/j.1523-1739.2000.99219.x
   Davis MB, 2000, ANNU REV EARTH PL SC, V28, P1, DOI 10.1146/annurev.earth.28.1.1
   DEAN WE, 1974, J SEDIMENT PETROL, V44, P242
   Dunnette PV, 2014, NEW PHYTOL, V203, P900, DOI 10.1111/nph.12828
   Epstein E.E., 2017, ECOLOGICAL LANDSCAPE
   Faegri K., 1975, Textbook of pollen analysis.
   Feldman JW, 2011, WEYER ENVIRON BOOKS, P1
   Florescu G, 2018, QUATERN INT, V488, P41, DOI 10.1016/j.quaint.2018.03.042
   Froyd CA, 2008, QUATERNARY SCI REV, V27, P1723, DOI 10.1016/j.quascirev.2008.06.006
   Galka M, 2015, HOLOCENE, V25, P421, DOI 10.1177/0959683614561887
   GLISA (Great Lakes Integrated Sciences and Assessment), 2020, 2019 ANN CLIM TRENDS
   Grimm E.C., 1991, TILIA and TILIAGRAPH
   GRIMM EC, 1987, COMPUT GEOSCI, V13, P13, DOI 10.1016/0098-3004(87)90022-7
   Guyette RP, 2016, FORESTS, V7, DOI 10.3390/f7090189
   Handler S., 2020, NPSAPISNRR20202121
   Hannah L, 2002, CONSERV BIOL, V16, P264, DOI 10.1046/j.1523-1739.2002.00465.x
   Heyerdahl EK, 2008, ECOLOGY, V89, P705, DOI 10.1890/06-2047.1
   Higuera PE, 2005, HOLOCENE, V15, P238, DOI 10.1191/0959683605hl789rp
   Higuera PE, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2103135118
   Higuera PE, 2010, INT J WILDLAND FIRE, V19, P996, DOI 10.1071/WF09134
   Higuera PE, 2009, ECOL MONOGR, V79, P201, DOI 10.1890/07-2019.1
   Hop K., 2010, NPSGLKNNRR2010199
   Hotchkiss SC, 2007, LANDSCAPE ECOL, V22, P25, DOI 10.1007/s10980-007-9133-3
   Jensen K, 2007, HOLOCENE, V17, P907, DOI 10.1177/0959683607082405
   Johnson LB, 2016, ECOL APPL, V26, P1030, DOI 10.1890/15-1151
   Johnston JW, 2012, CAN J EARTH SCI, V49, P1263, DOI 10.1139/e2012-057
   Jones MW, 2022, REV GEOPHYS, V60, DOI 10.1029/2020RG000726
   Kelly R, 2013, P NATL ACAD SCI USA, V110, P13055, DOI 10.1073/pnas.1305069110
   Kelly RF, 2011, QUATERNARY RES, V75, P11, DOI 10.1016/j.yqres.2010.07.011
   Kipfmueller K. F., 2019, FIRE HIST STAND DEV
   Kipfmueller KF, 2021, ECOSPHERE, V12, DOI 10.1002/ecs2.3673
   Knight CA, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2116264119
   Larson ER, 2021, ANN AM ASSOC GEOGR, V111, P1, DOI 10.1080/24694452.2020.1768042
   LINEBACK JA, 1979, GEOL SOC AM BULL, V90, P781, DOI 10.1130/0016-7606(1979)90<781:GAPSIL>2.0.CO;2
   Loope WL, 1998, AM MIDL NAT, V140, P206, DOI 10.1674/0003-0031(1998)140[0206:HVLIOP]2.0.CO;2
   Lynch AJ, 2021, FRONT ECOL ENVIRON, V19, P461, DOI 10.1002/fee.2377
   Lynch EA, 2002, WETLANDS, V22, P637, DOI 10.1672/0277-5212(2002)022[0637:PAGAPE]2.0.CO;2
   Lynch EA, 2014, CAN J FOREST RES, V44, P1331, DOI 10.1139/cjfr-2014-0107
   Lynch EA, 2011, QUATERNARY RES, V75, P125, DOI 10.1016/j.yqres.2010.08.007
   Lynch JA, 2004, CAN J FOREST RES, V34, P1642, DOI [10.1139/x04-071, 10.1139/X04-071]
   Millar CI, 2007, ECOL APPL, V17, P2145, DOI 10.1890/06-1715.1
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Minckley TA, 2012, ECOL MONOGR, V82, P49, DOI 10.1890/11-0283.1
   Morgan P, 2008, ECOLOGY, V89, P717, DOI 10.1890/06-2049.1
   Norrgard Chantal., 2009, American Indian Quarterly, V33, P33, DOI [DOI 10.1353/AIQ.0.0035, 10.2307/25487918, DOI 10.2307/25487918]
   Notaro M, 2015, J CLIMATE, V28, P1661, DOI 10.1175/JCLI-D-14-00467.1
   Notaro M, 2014, J CLIMATE, V27, P6526, DOI 10.1175/JCLI-D-13-00520.1
   Payne RJ, 2009, J PALEOLIMNOL, V42, P483, DOI 10.1007/s10933-008-9299-y
   Reimer PJ, 2013, RADIOCARBON, V55, P1869, DOI 10.2458/azu_js_rc.55.16947
   Rhodes AN, 1998, HOLOCENE, V8, P113, DOI 10.1191/095968398671104653
   Roos CI, 2022, SCI ADV, V8, DOI 10.1126/sciadv.abq3221
   Roos CI, 2020, NAT SUSTAIN, V3, P898, DOI 10.1038/s41893-020-0579-5
   Schuurman G. W., 2020, 20202213 NAT PARK SE, DOI [10.36967/nrr-2283597, DOI 10.36967/NRR-2283597]
   Schuurman GW, 2022, BIOSCIENCE, V72, P16, DOI 10.1093/biosci/biab067
   Shultz A, 2022, FISHERIES MANAG ECOL, V29, P392, DOI 10.1111/fme.12568
   Shuman B, 2009, ECOLOGY, V90, P2792, DOI 10.1890/08-0985.1
   Shuman BN, 2018, CLIM PAST, V14, P665, DOI 10.5194/cp-14-665-2018
   Shuman BN, 2016, QUATERNARY SCI REV, V141, P38, DOI 10.1016/j.quascirev.2016.03.009
   Sim TG, 2023, QUATERNARY SCI REV, V305, DOI 10.1016/j.quascirev.2023.108020
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Stuiver M., 2017, CALIB 71
   SUGITA S, 1994, J ECOL, V82, P881, DOI 10.2307/2261452
   Swain A., 1983, Park Science, V3, P3
   Thompson LM, 2021, FISHERIES, V46, P8, DOI 10.1002/fsh.10506
   Tweiten MA, 2015, ECOL APPL, V25, P1984, DOI 10.1890/14-2015.1
   Tweiten MA, 2009, HOLOCENE, V19, P1049, DOI 10.1177/0959683609340993
   Vachula RS, 2018, PALAEOGEOGR PALAEOCL, V508, P166, DOI 10.1016/j.palaeo.2018.07.032
   Vogl R. J., 1970, Proceedings Annual Tall Timbers Fire Ecology Conference, P175
   Warren W. W., 1984, HIST OJIBWAY PEOPLE, P411
   Willis KJ, 2006, SCIENCE, V314, P1261, DOI 10.1126/science.1122667
NR 95
TC 0
Z9 0
U1 4
U2 15
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1051-0761
EI 1939-5582
J9 ECOL APPL
JI Ecol. Appl.
PD SEP
PY 2023
VL 33
IS 6
DI 10.1002/eap.2901
EA JUL 2023
PG 24
WC Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA R3LP7
UT WOS:001021965300001
PM 37334723
OA hybrid
DA 2025-01-10
ER

PT J
AU Thomas, T
   Ghosh, NC
   Sudheer, KP
AF Thomas, T.
   Ghosh, N. C.
   Sudheer, K. P.
TI Optimal reservoir operation - A climate change adaptation strategy for
   Narmada basin in central India
SO JOURNAL OF HYDROLOGY
LA English
DT Article
DE Climate change; Reservoir operation; Simulation; Optimization; Narmada
ID CHANGE IMPACT ASSESSMENT; WATER-RESOURCES; RIVER-BASIN; HYDROLOGIC
   IMPACTS; TRENDS; SCALE; STABILIZATION; VARIABILITY; PERFORMANCE;
   STREAMFLOW
AB The potential impacts of climate change on the water resources of the Narmada basin in central India has been investigated using the Soil and Water Assessment Tool (SWAT). The existing dams in the river basin have been incorporated in the model setups, calibration and validation. The COordinated Regional climate Downscaling EXperiment datasets for South-Asia (CORDEX-SA) at 0.5 degrees x 0.5 degrees resolution for four-time horizons, viz., 1970-05 (historical), 2006-40 (near-term), 2041-70 (mid-term) and 2071-99 (end-term) under Representative Concentration Pathways (RCP) scenarios, RCP4.5 and RCP8.5 has been used to investigate the changes in the future climate and simulation of future streamflow. The proposed dams have also been incorporated for modeling the future developmental scenarios. The scenario analysis based on the projected climate variables has led to the inference that the change in the precipitation pattern coupled with the warming trends, maybe contributing towards higher variability in water availability. A future scenario of lower water availability and higher water demands thus calls for optimal utilization of available water resources in the future, so that the higher water demands can be satisfied with lower anticipated future flows. Various alternatives were explored for devising adaptation strategies using the engineering/technical solutions in which the optimal water resources management approaches were explored using the simulation-only and the genetic algorithm based simulation-optimization approaches. The simulation-optimization framework based integrated reservoir operation of four reservoirs has led to better reservoir performance and the number of irrigation failures has decreased substantially from 92 to 12 during 2006-40, 86 to 22 during 2041-70 and 89 to 10 during 2071-99. The hydropower failures have also decreased considerably from 202 to 96 during 2006-40, 192 to 28 during 2041-70 and 179 to 67 during 2071-99 under the RCP8.5 scenario. There were no failures in meeting the domestic water supply and environment flow demands. This may be an important adaptation measure to address the issues of climate change impacts on the water resources in the future in the Narmada basin.
C1 [Thomas, T.] Cent India Hydrol Reg Ctr, Natl Inst Hydrol, WALMI Campus, Bhopal, India.
   [Ghosh, N. C.] Natl Inst Hydrol, Roorkee, Uttar Pradesh, India.
   [Sudheer, K. P.] Indian Inst Technol Madras, Civil Engn Dept, Chennai, Tamil Nadu, India.
C3 Indian Institute of Technology System (IIT System); Indian Institute of
   Technology (IIT) - Madras
RP Thomas, T (corresponding author), Cent India Hydrol Reg Ctr, Natl Inst Hydrol, WALMI Campus, Bhopal, India.
EM thomas_nih@yahoo.com
RI thomas, thomas/KCX-9616-2024; KP, Sudheer/C-7123-2013
CR Abera FF, 2018, WATER-SUI, V10, DOI 10.3390/w10030273
   Acreman MC, 2009, ECOHYDROLOGY, V2, P1, DOI 10.1002/eco.37
   Alvarez UFH, 2014, WATER RESOUR MANAG, V28, P3667, DOI 10.1007/s11269-014-0694-z
   [Anonymous], 2011, CLIMATIC CHANGE, DOI DOI 10.1007/s10584-011-0157-y
   Argüeso D, 2013, HYDROL EARTH SYST SC, V17, P4379, DOI 10.5194/hess-17-4379-2013
   Arnell NW, 2003, HYDROL EARTH SYST SC, V7, P619, DOI 10.5194/hess-7-619-2003
   Arnold JG, 1999, WATER SCI TECHNOL, V39, P121, DOI 10.1016/S0273-1223(99)00044-X
   Asokan SM, 2008, HYDROL PROCESS, V22, P3589, DOI 10.1002/hyp.6962
   Bae DH, 2008, CLIM RES, V35, P213, DOI 10.3354/cr00704
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Christensen NS, 2004, CLIMATIC CHANGE, V62, P337, DOI 10.1023/B:CLIM.0000013684.13621.1f
   Chung ES, 2011, HYDROL PROCESS, V25, P544, DOI 10.1002/hyp.7781
   Cloke HL, 2010, HYDROL PROCESS, V24, P3476, DOI 10.1002/hyp.7769
   Dankers R, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009719
   Dash SK, 2011, THEOR APPL CLIMATOL, V105, P563, DOI 10.1007/s00704-011-0416-x
   Deb K., 2002, KANGAL REPORT NO 200
   Ehsani N, 2017, J HYDROL, V555, P435, DOI 10.1016/j.jhydrol.2017.09.008
   Eum HI, 2012, HYDROL PROCESS, V26, P485, DOI 10.1002/hyp.8145
   Fujihara Y., 2007, FINAL REP ICCAP 89 9
   Ghosh S, 2010, CURR SCI INDIA, V98, P1084
   Gohari A, 2014, J WATER CLIM CHANGE, V5, P391, DOI 10.2166/wcc.2014.189
   Gosain AK, 2011, CURR SCI INDIA, V101, P356
   Gosain AK, 2006, CURR SCI INDIA, V90, P346
   Goswami BN, 2006, SCIENCE, V314, P1442, DOI 10.1126/science.1132027
   Guhathakurta P, 2008, INT J CLIMATOL, V28, P1453, DOI 10.1002/joc.1640
   Haddeland I, 2012, HYDROL EARTH SYST SC, V16, P305, DOI 10.5194/hess-16-305-2012
   HARGREAVES GH, 1982, J IRR DRAIN DIV-ASCE, V108, P225
   HASHIMOTO T, 1982, WATER RESOUR RES, V18, P14, DOI 10.1029/WR018i001p00014
   Hoanh C. T., 2010, MRC TECH PAP
   Jain SK, 1998, J WATER RES PL-ASCE, V124, P31, DOI 10.1061/(ASCE)0733-9496(1998)124:1(31)
   Jha M, 2004, J GEOPHYS RES-ATMOS, V109, DOI 10.1029/2003JD003686
   Jiang T, 2007, J HYDROL, V336, P316, DOI 10.1016/j.jhydrol.2007.01.010
   Johnson F, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010464
   Kumar V, 2010, HYDROLOG SCI J, V55, P484, DOI 10.1080/02626667.2010.481373
   Lauri H, 2012, HYDROL EARTH SYST SC, V16, P4603, DOI 10.5194/hess-16-4603-2012
   Li LH, 2010, WATER RESOUR MANAG, V24, P83, DOI 10.1007/s11269-009-9438-x
   Li Z, 2010, QUATERN INT, V226, P92, DOI 10.1016/j.quaint.2010.03.003
   Liu XC, 2016, HYDROL EARTH SYST SC, V20, P3343, DOI 10.5194/hess-20-3343-2016
   Ludwig R., 2009, Adv. Geosci, V21, P63, DOI DOI 10.5194/ADGEO
   Masui T, 2011, CLIMATIC CHANGE, V109, P59, DOI 10.1007/s10584-011-0150-5
   Meenu R, 2013, HYDROL PROCESS, V27, P1572, DOI 10.1002/hyp.9220
   Milly PCD, 2005, NATURE, V438, P347, DOI 10.1038/nature04312
   Minville M, 2010, J WATER RES PLAN MAN, V136, P376, DOI 10.1061/(ASCE)WR.1943-5452.0000041
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Ngo L, 2018, CLIMATIC CHANGE, V149, P107, DOI 10.1007/s10584-016-1875-y
   O'Neil Kyle, 2013, World Environmental and Water Resources Congress 2013. Showcasing the Future. Proceedings of the 2013 Congress, P1175
   Panda DK, 2014, INT J CLIMATOL, V34, P3585, DOI 10.1002/joc.3931
   Panda DK, 2013, INT J CLIMATOL, V33, P1633, DOI 10.1002/joc.3538
   Payne JT, 2004, CLIMATIC CHANGE, V62, P233, DOI 10.1023/B:CLIM.0000013694.18154.d6
   PENMAN HL, 1948, PROC R SOC LON SER-A, V193, P120, DOI 10.1098/rspa.1948.0037
   Piani C, 2010, J HYDROL, V395, P199, DOI 10.1016/j.jhydrol.2010.10.024
   Praskievicz S, 2009, PROG PHYS GEOG, V33, P650, DOI 10.1177/0309133309348098
   PRIESTLEY CHB, 1972, MON WEATHER REV, V100, P81, DOI 10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2
   Raje D, 2010, ADV WATER RESOUR, V33, P312, DOI 10.1016/j.advwatres.2009.12.008
   Rajeevan M, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035143
   Randall DA, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P589
   Rehana S, 2013, HYDROL PROCESS, V27, P2918, DOI 10.1002/hyp.9379
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Rungee J, 2017, WATER-SUI, V9, DOI 10.3390/w9090649
   Soundharajan BS, 2016, J HYDROL, V538, P625, DOI 10.1016/j.jhydrol.2016.04.051
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Teutschbein C, 2010, GEOGR COMPASS, V4, DOI 10.1111/j.1749-8198.2010.00357.x
   Thomson AM, 2011, CLIMATIC CHANGE, V109, P77, DOI 10.1007/s10584-011-0151-4
   Vicuña S, 2011, CLIMATIC CHANGE, V109, P151, DOI 10.1007/s10584-011-0301-8
   Vonk E, 2014, WATER RESOUR MANAG, V28, P625, DOI 10.1007/s11269-013-0499-5
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Yu PS, 2014, HYDROLOG SCI J, V59, P1196, DOI 10.1080/02626667.2014.912035
   Zamani R, 2017, J HYDROL ENG, V22, DOI 10.1061/(ASCE)HE.1943-5584.0001559
NR 69
TC 26
Z9 28
U1 6
U2 31
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0022-1694
EI 1879-2707
J9 J HYDROL
JI J. Hydrol.
PD JUL
PY 2021
VL 598
AR 126238
DI 10.1016/j.jhydrol.2021.126238
EA MAR 2021
PG 20
WC Engineering, Civil; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA SS5RK
UT WOS:000661813200073
DA 2025-01-10
ER

PT J
AU Rivett, MO
   Budimir, L
   Mannix, N
   Miller, AVM
   Addison, MJ
   Moyo, P
   Wanangwa, GJ
   Phiri, OL
   Songola, CE
   Nhlema, M
   Thomas, MAS
   Polmanteer, RT
   Borge, A
   Kalin, RM
AF Rivett, Michael O.
   Budimir, Laura
   Mannix, Nicholas
   Miller, Alexandra V. M.
   Addison, Marc J.
   Moyo, Phideria
   Wanangwa, Gift J.
   Phiri, Owen L.
   Songola, Chrispine E.
   Nhlema, Muthi
   Thomas, Mavuto A. S.
   Polmanteer, Reid T.
   Borge, Amando
   Kalin, Robert M.
TI Responding to salinity in a rural African alluvial valley aquifer
   system: To boldly go beyond the world of hand-pumped groundwater supply?
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Salinity; Groundwater; Sustainable Development Goal (SDG) 6; Drinking
   water; Malawi; Alluvial aquifer
ID CLIMATE-CHANGE ADAPTATION; WATER-SUPPLIES; SALINIZATION; IRRIGATION;
   MALAWI; MANAGEMENT; IMPACTS
AB Effective response to groundwater salinity in the developing world may critically safeguard drinking-water supplies. Groundwater resources throughout rural Africa are exploited by a vast and increasing number of hand-pumped boreholes for community supply. Our research in TA Ngabu (Shire Valley), Southern Malawi aims to: define groundwater-salinity problem occurrence within the semi-arid alluvial-valley aquifer, rural developing-world setting; critique current capacity to respond; and, to discuss future response options - in particular considering the need to explore alternative options that boldly go beyond the world of hand-pumped groundwater supply. Salinity problem definition was achieved through survey of 419 hand-pumped boreholes that revealed widespread brackish groundwater leading to non-potable (unpalatable) drinking-water supplies. Persistent non-functionality or abandonment of boreholes was typically ascribed to salinity. Whilst salinity is conceptualised to arise from shallow-groundwater evaporation, formation-evaporite dissolution and faulted-area upwelling, sparse data locally renders attribution of salinity sources to individual boreholes difficult. There is a significant need to better resolve the vertical distribution of salinity and local controlling processes. Problem response capacity was hampered by multiple factors, including, sector inertia, low drilling costs compromising water-point integrity, and lack of technical vision for alternatives. Various recommendations are made to improve response capacity continuing to work at the hand-pump supply scale. However, in areas where salinity is significant, exploring the feasibility of other options is advocated in conjunction with technical capacity development. Groundwater options may utilise high borehole yields possible from alluvial aquifers, grossly under-exploited by hand pumps. Groundwater at depth, albeit of unknown quality typically, or pipeline transfers of probable good-quality groundwater from valley-margin units, should be considered. Surface-water pipeline supplies may be viable for (growing) population centres. Canal-fed irrigation schemes (pending for the area), should be multiple-use, protective of groundwater and embrace pipeline drinking-water supply and managed-aquifer-recharge opportunities. Advancing desalination technologies, although presently unaffordable, should be kept under review. (c) 2018 Elsevier B.V. All rights reserved.
C1 [Rivett, Michael O.; Budimir, Laura; Mannix, Nicholas; Miller, Alexandra V. M.; Addison, Marc J.; Polmanteer, Reid T.; Borge, Amando; Kalin, Robert M.] Univ Strathclyde, Dept Civil & Environm Engn, Glasgow G1 1XJ, Lanark, Scotland.
   [Moyo, Phideria; Wanangwa, Gift J.; Phiri, Owen L.] Minist Agr Irrigat & Water Dev, Reg Irrigat & Water Dev Off, South Private Bag 13, Blantyre, Malawi.
   [Songola, Chrispine E.] Chikwawa Dist Council, Dist Water Dev Off, Private Bag 1, Chikwawa, Malawi.
   [Nhlema, Muthi] BASEflow, Galaxy House, Blantyre, Malawi.
   [Thomas, Mavuto A. S.] Dowa Dist Hlth Off, POB 25, Dowa, Malawi.
   [Thomas, Mavuto A. S.] Chikwawa Dist Hlth Off, Chikwawa, Malawi.
   [Polmanteer, Reid T.] HRS Water Consultants, Lakewood, CO 80215 USA.
C3 University of Strathclyde
RP Rivett, MO (corresponding author), Univ Strathclyde, Dept Civil & Environm Engn, Glasgow G1 1XJ, Lanark, Scotland.
EM Michael.Rivett@strath.ac.uk
RI Rivett, Michael/W-9249-2019; Kalin, Robert M/E-8620-2011
OI Kalin, Robert M/0000-0003-3768-3848; Addison, Marc/0000-0002-6113-493X;
   Borge, Amando/0000-0002-0895-3012; Rivett, Michael/0000-0003-4626-7985
FU Scottish Government under the Scottish Government Climate Justice Fund
   Water Futures Programme [HN-CJF-03]
FX We gratefully acknowledge the funding of this research by the Scottish
   Government under the Scottish Government Climate Justice Fund Water
   Futures Programme research grant HN-CJF-03 awarded to the University of
   Strathclyde (R.M. Kalin).
CR Abu-alnaeem MF, 2018, SCI TOTAL ENVIRON, V615, P972, DOI 10.1016/j.scitotenv.2017.09.320
   Addison M., 2017, THESIS
   Adekile D., 2014, SUPERVISING WATER WE
   Ali R., 2002, 2102CSIRO
   [Anonymous], 2015, OR15019 BRIT GEOL SU
   [Anonymous], LOW SHIR VALL LANDF
   [Anonymous], 2017, MIN 17 STAT SOFTW
   [Anonymous], 2017, NAT WAT RES MAST PLA
   APHA, 2005, STANDARD METHODS EXA
   Argamasilla M, 2017, SCI TOTAL ENVIRON, V580, P50, DOI 10.1016/j.scitotenv.2016.11.173
   Back JO, 2018, SCI TOTAL ENVIRON, V613, P592, DOI 10.1016/j.scitotenv.2017.09.071
   Bath AH, 1980, Report WD/OS/80/20
   Bennet J. D., 1972, T580 GEOL SURV MAL
   Bonsor H, 2018, HYDROGEOL J, V26, P367, DOI 10.1007/s10040-017-1711-0
   Boukhari K, 2015, ENVIRON EARTH SCI, V73, P6195, DOI 10.1007/s12665-014-3844-y
   Bradford R. B., 1973, RB5GEOL SURV
   Bruvold W. H., 1969, J AM WATER WORKS ASS, V1969, P61
   Budimir L., 2017, THESIS
   Burney JA, 2013, P NATL ACAD SCI USA, V110, P12513, DOI 10.1073/pnas.1203597110
   Carter R. C., 2016, Waterlines, V35, P94, DOI 10.3362/1756-3488.2016.008
   Carter R. C., 2015, 42 C INT ASS HYDR RO
   CASTAING C, 1991, TECTONOPHYSICS, V191, P55, DOI 10.1016/0040-1951(91)90232-H
   Chen H, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-6006-6
   Chien NP, 2018, SCI TOTAL ENVIRON, V618, P379, DOI 10.1016/j.scitotenv.2017.11.019
   Chowdhury AH, 2018, HYDROGEOL J, V26, P197, DOI 10.1007/s10040-017-1619-8
   CJF (Climate Justice Fund: Water Futures Programme), 2018, PRELIMINARY SURVEY O
   COULIBALY J.Y., 2015, American Journal of Climate Change, V4, P282, DOI [10.4236/ajcc.2015.43023, DOI 10.4236/AJCC.2015.43023]
   Danert K., 2009, P 34 WEDC INT C ADD
   DAVIS R W, 1969, Ground Water, V7, P34, DOI 10.1111/j.1745-6584.1969.tb01275.x
   Eastoe CJ, 2016, APPL GEOCHEM, V74, P1, DOI 10.1016/j.apgeochem.2016.08.015
   EED Advisory, 2018, EV SUST SOL POW WAT
   Foster SSD, 2003, PHILOS T R SOC B, V358, P1957, DOI 10.1098/rstb.2003.1380
   Foster S, 2018, HYDROGEOL J, V26, P2781, DOI 10.1007/s10040-018-1830-2
   Freeze R.A., 1979, GROUNDWATER
   Garduno H., 2010, GW MATE BRIEFING NOT, V6
   GORCHEV HG, 1984, WHO CHRON, V38, P104
   Government of Malawi, 2016, MIN AGR IRR WAT DEV
   Greene R., 2016, Integrated Groundwater Management: Concepts, Approaches and Challenges, P377
   Habgood F., 1963, GEOLOGY COUNTRY W SH
   Howard G, 2016, ANNU REV ENV RESOUR, V41, P253, DOI 10.1146/annurev-environ-110615-085856
   Huang J, 2016, SCI TOTAL ENVIRON, V551, P460, DOI 10.1016/j.scitotenv.2016.01.200
   HUTCHINGS P, 2017, EARTHSCAN STUD WATER, P1
   Hutchings P, 2015, WATER POLICY, V17, P963, DOI 10.2166/wp.2015.128
   JICA (Japan International Cooperation Agency), 2018, PREP SURV PROJ IMPR
   Joshua MK, 2016, JAMBA-J DISASTER RIS, V8, DOI 10.4102/jamba.v8i3.255
   Liu YL, 2018, HYDROL PROCESS, V32, P3108, DOI 10.1002/hyp.13243
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   MacDonald AM, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/2/024009
   MacDonald AM, 2009, DESALINATION, V248, P546, DOI 10.1016/j.desal.2008.05.100
   Malawi Standards (MS), 2013, MS2142013
   Malawi Standards (MS), 2005, MS7332005
   Mannix N., 2018, P 41 WEDC INT C EG U, P2018
   Maoulidi M., 2012, MCI MILLENNIUM CITIE, DOI [10.7916/D8D7997F, DOI 10.7916/D8D7997F]
   Mapoma H. W. T., 2014, African Journal of Environmental Science and Technology, V8, P190
   Miller A., 2018, P 41 WEDC INT C EG U, P2018
   MoAIWD, 2016, STAT BAS REP SHIR RI
   MoAIWD (Ministry of Agriculture Irrigation and Water Development), 2016, IRR CASH CROPS BETT
   MoAIWD (Ministry of Agriculture Irrigation andWater Development), 2017, SHIR VAL IRR PROJ EN
   Monjerezi M., 2012, THESIS
   Monjerezi M, 2012, J AFR EARTH SCI, V68, P67, DOI 10.1016/j.jafrearsci.2012.03.012
   Monjerezi M, 2012, WATER QUAL EXPOS HEA, V4, P39, DOI 10.1007/s12403-012-0064-0
   Monjerezi M, 2011, APPL GEOCHEM, V26, P2201, DOI 10.1016/j.apgeochem.2011.08.003
   Monjerezi M, 2011, APPL GEOCHEM, V26, P1399, DOI 10.1016/j.apgeochem.2011.05.013
   Muir A., 1957, GEOL MIN RES, V6, P391
   National Statistical Office of Malawi, 2008, 2008 POP HOUS CENS M
   Ngongondo C, 2011, THEOR APPL CLIMATOL, V106, P79, DOI 10.1007/s00704-011-0413-0
   Pauwels H, 2013, PROCED EARTH PLAN SC, V7, P660, DOI 10.1016/j.proeps.2013.03.189
   Pavelic P., 2012, Groundwater availability and use in sub-saharan Africa: A review of 15 countries, DOI DOI 10.5337/2012.213
   Peiris M. J. N. R., 2009, DOES STEREOTYPE FIT
   Phiri IMG, 2008, FUTURE OF DRYLANDS, P545
   Pisinaras V, 2010, ENVIRON MONIT ASSESS, V166, P79, DOI 10.1007/s10661-009-0986-6
   Pitkin SE, 1999, GROUND WATER MONIT R, V19, P122, DOI 10.1111/j.1745-6592.1999.tb00213.x
   Polmanteer R. T., 2014, ASSESSMENT NEEDS IMP
   Rivett Michael O., 2018, Groundwater for Sustainable Development, V6, P213, DOI 10.1016/j.gsd.2018.01.005
   Rivett MO, 2018, J ENVIRON MANAGE, V209, P354, DOI 10.1016/j.jenvman.2017.12.029
   Rivett MO, 2016, SCI TOTAL ENVIRON, V565, P324, DOI 10.1016/j.scitotenv.2016.04.095
   Robins N, 2013, HYDROGEOL J, V21, P905, DOI 10.1007/s10040-013-0956-5
   Robinson H., 2018, THESIS
   Salameh E, 2014, CHEM ERDE-GEOCHEM, V74, P735, DOI 10.1016/j.chemer.2014.04.007
   Seo DH, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-02871-3
   Smedley P., 2004, BRIT GEOL SURV, V6
   Smith-Carington AK., 1983, Groundwater resources of Malawi
   Smout I., 1999, WAT NGOS P ODA WORKS
   Sutcliffe C, 2016, REG ENVIRON CHANGE, V16, P1215, DOI 10.1007/s10113-015-0842-x
   Talukder MRR, 2016, ENVIRON POLLUT, V214, P248, DOI 10.1016/j.envpol.2016.03.074
   Tan Z, 2018, SCIENCE, V360, P518, DOI 10.1126/science.aar6308
   Upton K., 2018, BRIT GEOL SURV
   van den Broek M, 2015, GEOFORUM, V67, P51, DOI 10.1016/j.geoforum.2015.10.009
   Van Weert F., 2009, GP20091 INT GROUNDW
   Vineis P, 2011, J EPIDEMIOL GLOB HEA, V1, P5, DOI 10.1016/j.jegh.2011.09.001
   Wanda EMM, 2013, PHYS CHEM EARTH, V66, P51, DOI 10.1016/j.pce.2013.09.001
   Water Aid, 2013, HAND PUMPS
   WHO/UNICEF Joint Water Supply & Sanitation Monitoring Programme, 2014, Progress on Drinking Water and Sanitation: 2014 Update
   WRA (Water Resources Act), 2013, ACT PROV MAN CONS US
   Xue JY, 2018, SCI TOTAL ENVIRON, V619, P1170, DOI 10.1016/j.scitotenv.2017.11.145
NR 95
TC 30
Z9 31
U1 1
U2 24
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD FEB 25
PY 2019
VL 653
BP 1005
EP 1024
DI 10.1016/j.scitotenv.2018.10.337
PG 20
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA HL3PA
UT WOS:000458626800099
PM 30759542
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Abbas, N
   Wasimi, SA
   Al-Ansari, N
   Baby, SN
AF Abbas, Nahlah
   Wasimi, Saleh A.
   Al-Ansari, Nadhir
   Baby, Sultana Nasrin
TI Recent Trends and Long-Range Forecasts of Water Resources of Northeast
   Iraq and Climate Change Adaptation Measures
SO WATER
LA English
DT Article
DE climate change; SWAT model; general circulation model; Iraq
ID MODEL; SWAT; UNCERTAINTY; CALIBRATION; IMPACTS; SENSITIVITY; PARAMETERS;
   SCARCITY; QUALITY; AFRICA
AB Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water resources of a region has been sparsely addressed in published literature. To fill that gap this research work first investigates if there has been a significant change in climate in the region, which has been found to be true. In the next stage, the research projects future climatic scenarios of the region based on six oft-used General Circulation Model (GCM) ensembles, namely CCSM4, CSIRO-Mk3.6.0, GFDL-ESM2M, MEROC5, HadGEM2-ES, and IPSL-CM5A-LR. The relationship between climate change and its impact on water resources is explored through the application of the popular, widely used SWAT model. The model depicts the availability of water resources, classified separately as blue and green waters, for near and distant futures for the region. Some of the findings are foreboding and warrants urgent attention of planners and decision makers. According to model outputs, the region may experience precipitation reduction of about 12.6% and 21% in near (2049-2069) and distant (2080-2099) futures, respectively under RCP8.5. Those figures under RCP4.5 are 15% and 23.4%, respectively and under RCP2.6 are 12.2% and 18.4%, respectively. As a consequence, the blue water may experience decreases of about 22.6% and 40% under RCP8.5, 25.8% and 46% under RCP4.5, and 34.4% and 31% under RCP2.6 during the periods 2049-2069 and 2080-2099, respectively. Green water, by contrast, may reduce by about 10.6% and 19.6% under RCP8.5, by about 14.8% and 19.4% under RCP4.5, and by about 15.8% and 14.2% under RCP2.6 during the periods 2049-2069 and 2080-2099, respectively. The research further investigates how the population are adapting to already changed climates and how they are expected to cope in the future when the shift in climate is expected to be much greater.
C1 [Abbas, Nahlah; Wasimi, Saleh A.] Cent Queensland Univ, Sch Engn & Technol, Melbourne, Vic 3000, Australia.
   [Al-Ansari, Nadhir] Lulea Univ Technol, Dept Civil Environm & Nat Resources Engn, S-97187 Lulea, Sweden.
   [Baby, Sultana Nasrin] RMIT Univ, Dept Geospatial Sci, Melbourne, Vic 3000, Australia.
C3 Central Queensland University; Lulea University of Technology; Royal
   Melbourne Institute of Technology (RMIT)
RP Al-Ansari, N (corresponding author), Lulea Univ Technol, Dept Civil Environm & Nat Resources Engn, S-97187 Lulea, Sweden.
EM n.abbas@cqu.edu.au; s.wasimi@cqu.edu.au; nadhir.alansari@ltu.se;
   Nasrin.Sultana@whittlesea.vic.gov.au
OI Al-Ansari, Nadhir/0000-0002-6790-2653; Wasimi, Saleh/0000-0002-3647-2080
FU government of Iraq
FX This research forms part of the doctoral study of the first author,
   which was funded by the government of Iraq.
CR Abbas N., 2016, J ENV HYDROL, V24, P1, DOI [10.4236/eng.2016.810064, DOI 10.4236/ENG.2016.810064]
   Abbas N.A., 2018, THESIS
   Abbaspour KC, 2007, J HYDROL, V333, P413, DOI 10.1016/j.jhydrol.2006.09.014
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Al-Ansari N, 2014, OPEN ENG, V4, P250, DOI 10.2478/s13531-013-0151-4
   Al-Mukhtar M, 2014, WATER RESOUR MANAG, V28, P2731, DOI 10.1007/s11269-014-0675-2
   Angulo R, 2016, SOC INDIC RES, V127, P1, DOI 10.1007/s11205-015-0964-z
   [Anonymous], GRIDD POP WORLD GPW
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   Borgomeo E, 2015, WATER RESOUR RES, V51, P8927, DOI 10.1002/2015WR017324
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Cibin R, 2010, HYDROL PROCESS, V24, P1133, DOI 10.1002/hyp.7568
   Coffey R, 2014, HUM ECOL RISK ASSESS, V20, P724, DOI 10.1080/10807039.2013.802583
   Delpla I, 2009, ENVIRON INT, V35, P1225, DOI 10.1016/j.envint.2009.07.001
   Deressa T. T., 2009, Global Environmental Change, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   FALKENMARK M, 1989, AMBIO, V18, P112
   FAO, 1995, DIG SOIL MAP WORLD D
   Fellmann T., 2012, Building resilience for adaptation to climate change in the agriculture sector. Proceedings of a Joint FAO/OECD Workshop, Rome, Italy, 23-24 April 2012, P37
   Gosal SS, 2010, J CROP IMPROV, V24, P153, DOI 10.1080/15427520903584555
   Jansson Å, 1999, ECOSYSTEMS, V2, P351, DOI 10.1007/s100219900085
   Knisel W. G., 1980, USDA Conservation Research Report
   Legates DR, 1999, WATER RESOUR RES, V35, P233, DOI 10.1029/1998WR900018
   Maurer EP, 2014, B AM METEOROL SOC, V95, P1011, DOI 10.1175/BAMS-D-13-00126.1
   Mimikou MA, 2000, J HYDROL, V234, P95, DOI 10.1016/S0022-1694(00)00244-4
   Morgan RPC, 1998, EARTH SURF PROC LAND, V23, P527, DOI 10.1002/(SICI)1096-9837(199806)23:6<527::AID-ESP868>3.0.CO;2-5
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   NEARING MA, 1989, T ASAE, V32, P1587
   Neitsch S.L., 2005, Soil water assessment tool theoretical document, version 2005
   Orindi V., 2005, J SOIL WATER CONSERV, V44, P168
   Owor M, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/035009
   Pechlivanidis IG, 2011, GLOBAL NEST J, V13, P193
   Rijsberman FR, 2006, AGR WATER MANAGE, V80, P5, DOI 10.1016/j.agwat.2005.07.001
   Schuol J, 2007, ECOL MODEL, V201, P301, DOI 10.1016/j.ecolmodel.2006.09.028
   Sinnathamby S, 2017, AGR WATER MANAGE, V180, P61, DOI 10.1016/j.agwat.2016.10.024
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Sullivan C, 2002, WORLD DEV, V30, P1195, DOI 10.1016/S0305-750X(02)00035-9
   Tolson BA, 2007, J HYDROL, V337, P68, DOI 10.1016/j.jhydrol.2007.01.017
   Tong STY, 2012, APPL GEOGR, V32, P477, DOI 10.1016/j.apgeog.2011.06.014
   UN ESCWA, BGR INV SHAR WAT RES
   Veith TL, 2010, T ASABE, V53, P1477
   Wu KS, 2007, J HYDROL, V337, P187, DOI 10.1016/j.jhydrol.2007.01.030
   Xuan ZM, 2014, ECOL MODEL, V288, P79, DOI 10.1016/j.ecolmodel.2014.05.014
   Yang J, 2008, J HYDROL, V358, P1, DOI 10.1016/j.jhydrol.2008.05.012
   YOUNG RA, 1989, J SOIL WATER CONSERV, V44, P168
   Zang CF, 2012, HYDROL EARTH SYST SC, V16, P2859, DOI 10.5194/hess-16-2859-2012
NR 46
TC 16
Z9 18
U1 1
U2 16
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD NOV
PY 2018
VL 10
IS 11
AR 1562
DI 10.3390/w10111562
PG 19
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Water Resources
GA HC3XM
UT WOS:000451736300069
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Mango, LM
   Melesse, AM
   McClain, ME
   Gann, D
   Setegn, SG
AF Mango, L. M.
   Melesse, A. M.
   McClain, M. E.
   Gann, D.
   Setegn, S. G.
TI Land use and climate change impacts on the hydrology of the upper Mara
   River Basin, Kenya: results of a modeling study to support better
   resource management
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID SWAT MODEL; WATER-RESOURCES; RAINFALL; VULNERABILITY; UNCERTAINTY;
   CATCHMENT; QUALITY
AB Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5-10%) accompanied by increases in temperature (2.5-3.5 degrees C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (-3%) and high (+25%) extremes of projected precipitation changes, but under median projections (+7%) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned largely to increased evapotranspiration. Overall, model results support the existing efforts of Mara water resource managers to protect headwater forests and indicate that additional emphasis should be placed on improving land management practices that enhance infiltration and aquifer recharge as part of a wider program of climate change adaptation.
C1 [Mango, L. M.; Melesse, A. M.; McClain, M. E.; Setegn, S. G.] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA.
   [McClain, M. E.] UNESCO IHE Inst Water Educ, Dept Water Sci & Engn, Delft, Netherlands.
   [Gann, D.] Florida Int Univ, Geog Informat Syst Remote Sensing Ctr, Miami, FL 33199 USA.
C3 State University System of Florida; Florida International University;
   IHE Delft Institute for Water Education; State University System of
   Florida; Florida International University
RP Mango, LM (corresponding author), Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA.
EM lm_mango@yahoo.com
RI McClain, Michael/A-2475-2009; Melesse, Assefa/F-9931-2013
OI Gann, David/0000-0002-8245-3948; Gann, Daniel/0000-0001-6131-3391;
   Melesse, Assefa/0000-0003-4724-9367; Setegn, Shimelis
   Gebriye/0000-0002-7603-9505
FU Global Water for Sustainability (GLOWS) program; United States Agency
   for International Development (USAID); Worldwide Fund for Nature
   Offices, Kenya
FX The authors acknowledge the Global Water for Sustainability (GLOWS)
   program and the United States Agency for International Development
   (USAID) that funded the study. Authors thank the Worldwide Fund for
   Nature Offices, Kenya and Tanzania Ministries of Water and Irrigation,
   and Lake Victoria South Catchment Area of Kenya's Water Resources
   Management Authority. The authors thank Stefan Uhlenbrook and two
   anonymous reviewers for their valuable suggestions.
CR Abbaspour KC, 2007, J HYDROL, V333, P413, DOI 10.1016/j.jhydrol.2006.09.014
   Abbaspour KC, 2004, VADOSE ZONE J, V3, P1340
   Anderson J.R., 1976, A land use and land cover classification system for use with remote sensor data, P1, DOI [10.3133/pp964, DOI 10.3133/PP964]
   [Anonymous], 2005, 8 INT RIVER S
   [Anonymous], SCI CLIM CHANG
   Anyah RO, 2012, INT J CLIMATOL, V32, P347, DOI 10.1002/joc.2270
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   Christensen J.H., 2007, Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
   Di Luzio M, 2002, J AM WATER RESOUR AS, V38, P1127, DOI 10.1111/j.1752-1688.2002.tb05551.x
   DUAN QY, 1992, WATER RESOUR RES, V28, P1015, DOI 10.1029/91WR02985
   FAO, 2010, Global Forest Resource Assessment Report: Country Report Uganda
   Gereta Emmanuel, 2002, Ecohydrology & Hydrobiology, V2, P135
   *GOK, REP PRIM MIN TASK FO
   Hothorn T, 2006, J COMPUT GRAPH STAT, V15, P651, DOI 10.1198/106186006X133933
   Hulme M, 2001, CLIM RES, V17, P145, DOI 10.3354/cr017145
   Jacobs J.H., 2007, Journal of Spatial hydrology, V7, P23, DOI DOI 10.1017/CBO9780511806049
   Jayakrishnan R, 2005, HYDROL PROCESS, V19, P749, DOI 10.1002/hyp.5624
   *KWRMA, 2008, CATCHM MAN STRAT LAK
   Legesse D, 2003, J HYDROL, V275, P67, DOI 10.1016/S0022-1694(03)00019-2
   Li L, 2009, NAT HAZARDS, V50, P109, DOI 10.1007/s11069-008-9324-5
   Mati Bancy M., 2008, Lakes & Reservoirs Research and Management, V13, P169, DOI 10.1111/j.1440-1770.2008.00367.x
   Melesse A., 2008, P WORLD ENV WATER RE, DOI DOI 10.1061/40976(316)589
   Mulungu DMM, 2007, PHYS CHEM EARTH, V32, P1032, DOI 10.1016/j.pce.2007.07.053
   Mutie S., 2006, 2 WORKSH EARSEL SIG
   Neitsch S.L., 2005, Soil water assessment tool theoretical document, version 2005
   Olang LO, 2011, HYDROL PROCESS, V25, P80, DOI 10.1002/hyp.7821
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Ruosteenoja K., 2003, FINNISH ENV, V644
   Schuol J, 2007, ECOL MODEL, V201, P301, DOI 10.1016/j.ecolmodel.2006.09.028
   Setegn SG, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009248
   Setegn SG, 2009, HYDROL PROCESS, V23, P3738, DOI 10.1002/hyp.7476
   Shongwe ME, 2011, J CLIMATE, V24, P3718, DOI 10.1175/2010JCLI2883.1
   Shrestha MS, 2008, J FLOOD RISK MANAG, V1, P89, DOI 10.1111/j.1753-318X.2008.00011.x
   van Griensven A, 2006, WATER SCI TECHNOL, V53, P51, DOI 10.2166/wst.2006.007
   Vörösmarty CJ, 2000, SCIENCE, V289, P284, DOI 10.1126/science.289.5477.284
   Wilk J, 2006, J HYDROL, V331, P18, DOI 10.1016/j.jhydrol.2006.04.049
   *WRI DEP RES SURV, 2007, NAT BEN KEN ATL EC H
   Xie PP, 1997, B AM METEOROL SOC, V78, P2539, DOI 10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2
NR 38
TC 307
Z9 341
U1 7
U2 199
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1027-5606
EI 1607-7938
J9 HYDROL EARTH SYST SC
JI Hydrol. Earth Syst. Sci.
PY 2011
VL 15
IS 7
BP 2245
EP 2258
DI 10.5194/hess-15-2245-2011
PG 14
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA 799EW
UT WOS:000293268200013
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Skarzauskiene, A
   Maciuliene, M
   Kovaite, K
AF Skarzauskiene, Aelita
   Maciuliene, Monika
   Kovaite, Kristina
TI Citizen engagement in climate adaptation surveyed: Identifying
   challenges in education and capacity building
SO EUROPEAN JOURNAL OF EDUCATION
LA English
DT Article
DE climate adaptation strategies; climate-related hazards; motivation for
   climate adaptation; resilient communities; socio-cultural context
AB The accelerating impacts of climate change present significant challenges to sustainable urban development, testing the resilience of current governance frameworks and stakeholder responsibilities. In alignment with the EU's Green Deal, robust adaptation strategies and proactive climate risk anticipation are essential. Traditional discussions emphasize overcoming technological, financial and institutional barriers; however, social and individual factors also significantly hinder adaptation. This study explores the pivotal role of citizen engagement in climate risk management and adaptation, focusing on the Lithuanian context and comparing the results with a survey in Sweden. The research evaluates both external influences, such as experiences with climate-related hazards and adaptation actions, and internal factors, including beliefs, values and individual adaptive capacity. Key findings reveal that adaptation behaviour in Lithuania and in Sweden is deeply influenced by past experiences with extreme weather events and economic considerations, with a significant portion of the population having faced such events recently. Factors such as economic considerations (low costs, financial benefits) are identified as critical motivators for future adaptation actions in Lithuania. On the other hand, in Sweden, respondents first preferred ecological factors (such as contributing to climate change mitigation) when considering future adaptation actions. The study underscores the need for targeted educational interventions to enhance community resilience, highlighting the importance of socio-cultural contexts in shaping adaptation strategies. It emphasizes the necessity for comprehensive, inclusive educational programmes that address local climate impacts and promote proactive community involvement. The findings advocate for further comparative studies across diverse socio-cultural settings to deepen insights into effective adaptation measures and to support the development of resilient communities worldwide.
C1 [Skarzauskiene, Aelita; Maciuliene, Monika; Kovaite, Kristina] Vilnius Gediminas Tech Univ, Fac Creat Ind, Sauletekio Al 11, Vilnius 30308, Lithuania.
C3 Vilnius Gediminas Technical University
RP Skarzauskiene, A (corresponding author), Vilnius Gediminas Tech Univ, Fac Creat Ind, Sauletekio Al 11, Vilnius 30308, Lithuania.
EM aelita@mruni.eu
RI Maciuliene, Monika/LVS-4641-2024; Kovaite, Kristina/ACB-7209-2022;
   Skarzauskiene, Aelita/L-7900-2016
OI Kovaite, Kristina/0000-0003-4362-8001; Skarzauskiene,
   Aelita/0000-0003-1606-0676
FU HORIZON EUROPE Framework Programme [101094021]; Horizon Europe - Pillar
   II [101094021] Funding Source: Horizon Europe - Pillar II
FX HORIZON EUROPE Framework Programme, Grant/Award Number: 101094021
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Agliardi E., 2021, J ENVIRON PSYCHOL, V76, P1, DOI [10.1016/j.jenvp.2021.101627, DOI 10.1016/J.JENVP.2021.101627]
   Baron G.N., 2021, Cuadernos Del Centro de Estudios de Diseo y Comunicacin, V321, P131, DOI [10.18682/cdc.vi132.4983, DOI 10.18682/CDC.VI132.4983]
   Bhme J., 2022, ENVIRON POLICY GOV, V32, P199, DOI [10.1002/eet.1990, DOI 10.1002/EET.1990]
   Boluda-Verdú I, 2022, J ENVIRON PSYCHOL, V84, DOI 10.1016/j.jenvp.2022.101904
   Botzen W. J. W., 2009, CLIMATE CHANGE HUMAN, P331
   Brgger A., 2011, GLOBAL ENVIRON CHANG, V21, P1312, DOI [10.1016/j.gloenvcha.2011.06.019, DOI 10.1016/J.GLOENVCHA.2011.06.019]
   Brink E., 2018, ENVIRON POLICY GOV, V28, P337, DOI [10.1002/eet.1843, DOI 10.1002/EET.1843]
   Campiglio E., 2023, ENVIRON SCI POLICY, V55, P162, DOI [10.1016/j.envsci.2015.07.013, DOI 10.1016/J.ENVSCI.2015.07.013]
   Chen X., 2019, J CLEAN PROD, V239
   Diniz R., 2018, Psyecology, V9, P237, DOI DOI 10.1080/21711976.2018.1433080
   Doyle J, 2018, SOC SCI RES, V75, P32, DOI 10.1016/j.ssresearch.2018.07.006
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Göpfert C, 2019, CITY ENVIRON INTERAC, V1, DOI 10.1016/j.cacint.2019.100004
   goston C., 2022, J ENVIRON PSYCHOL, V79, P112, DOI [10.1016/j.jenvp.2014.11.012, DOI 10.1016/J.JENVP.2014.11.012]
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Harris D., 2022, INT J DISAST RISK RE, V72
   Hegger D, 2022, ENVIRON POLICY GOV, V32, P161, DOI 10.1002/eet.1990
   Intergov Panel Clim Chg, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P1, DOI 10.1017/CBO9781139177245
   Ivashkiv I., 2020, MANAG SCI LETT, V10, P2973, DOI [10.5267/j.msl.2020.5.028, DOI 10.5267/J.MSL.2020.5.028]
   Jain Nishtha, 2022, IOP Conference Series: Earth and Environmental Science, DOI 10.1088/1755-1315/1084/1/012007
   Jastrzbska M., 2023, URBAN CLIM, V53
   Kiss B, 2022, ENVIRON POLICY GOV, V32, P247, DOI 10.1002/eet.1987
   Kollmuss A., 2002, Environ Educ Res, V8, P239, DOI [10.1080/13504620220145401, DOI 10.1080/13504620220145401]
   Lacroix K., 2018, J ENVIRON PSYCHOL, V55, P81, DOI [10.1016/j.jenvp.2017.12.007, DOI 10.1016/J.JENVP.2017.12.007]
   Lutz PK, 2023, CURR RES ECOL PS, V4, DOI 10.1016/j.cresp.2023.100110
   Lutz PK, 2023, COLLABRA-PSYCHOL, V9, DOI 10.1525/collabra.67838
   Navarro O, 2020, PSYECOLOGY, V11, P37, DOI 10.1080/21711976.2019.1643662
   O'Brien, 2019, CLIMATE CULTURE MULT, DOI [10.1017/97811085052, DOI 10.1017/97811085052]
   O'Brien KL, 2010, WIRES CLIM CHANGE, V1, P232, DOI 10.1002/wcc.30
   Prokosch Marjorie L, 2023, Politics Life Sci, V41, P200, DOI 10.1017/pls.2022.20
   Sawatzky B., 2021, ARCT SCI, V7, P83, DOI [10.1139/AS-2020-0021, DOI 10.1139/AS-2020-0021]
   Schmid-Petri H, 2022, PUBLIC UNDERST SCI, V31, P152, DOI 10.1177/09636625211024550
   Schwaab L, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19159142
   Shah SMM, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13116257
   Wamsler C., 2007, DISASTER PREV MANAG, V16, P791, DOI [10.1108/09653560710834865, DOI 10.1108/09653560710834865]
   Wamsler C., 2014, ENVIRON POLICY GOV, V24, P395, DOI [10.1002/eet.1652, DOI 10.1002/EET.1652]
   Wamsler C., 2014, MANAG ENVIRON QUAL, V25, P457, DOI [10.1108/MEQ-09-2013-0081, DOI 10.1108/MEQ-09-2013-0081]
   Wamsler C, 2022, CLIMATIC CHANGE, V173, DOI 10.1007/s10584-022-03398-9
   Webb J., 2003, ENVIRON HAZARDS-UK, V3, P49, DOI [10.1016/j.hazards.2003.06.001, DOI 10.1016/J.HAZARDS.2003.06.001]
   Whitley T., 2018, GLOBAL ENVIRON CHANG, V53, P33, DOI [10.1016/j.gloenvcha.2018.08.001, DOI 10.1016/J.GLOENVCHA.2018.08.001]
   Woroniecki J., 2019, J ENVIRON PSYCHOL, V65
   Yohe G, 2002, GLOBAL ENVIRON CHANG, V12, P25, DOI 10.1016/S0959-3780(01)00026-7
NR 44
TC 0
Z9 0
U1 4
U2 4
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0141-8211
EI 1465-3435
J9 EUR J EDUC
JI Eur. J. Educ.
PD DEC
PY 2024
VL 59
IS 4
DI 10.1111/ejed.12732
EA AUG 2024
PG 16
WC Education & Educational Research
WE Social Science Citation Index (SSCI)
SC Education & Educational Research
GA N1C2D
UT WOS:001283263300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Heidenreich, S
   Næss, R
AF Heidenreich, Sara
   Naess, Robert
TI Controlling the water: citizens' place-related adaptation to landslides
   in mid-Norway
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Climate adaptation; Landslides; Place; Citizens; Socio-material
   assemblage; Norway
ID ATTACHMENT; CARE; RISK; TECHNOLOGY; PERCEPTION; ASSEMBLAGE
AB In light of an increasing frequency of climate change-related hazards such as landslides, climate adaptation is increasingly on the agenda of Norwegian municipalities. Nevertheless, municipalities face constraints in addressing these challenges, with smaller, remote municipalities being particularly susceptible. They often cover expansive geographical areas with high landslide risk, yet have limited financial resources, expertise, and personnel for climate adaptation. Consequently, the active involvement of citizens in adaptation plays an important role in these remote places. This paper investigates how citizens of three small remote communities deal with landslides, emphasizing the role of people-place relations in shaping adaptive practices. Grounded in assemblage theory, our analysis reveals that most citizens maintained a pragmatic relation to landslides, while only a few expressed concern. Regardless of the degree of concern, all citizens constructed landslides as integral element within their socio-material place assemblages, as part of their lives in the respective places. Furthermore, citizens developed various adaptive practices, including nature observation, reporting to authorities, and implementing practical preventive measures to control water that could trigger landslides. These practices are manifestations of socio-material assemblages that have evolved through citizens' relations to their specific places. Importantly, irrespective of the level of concern regarding landslides, these practices were carried out as part of everyday life. Through these practices, enabled by experience-based, embodied, and often tacit local knowledge, citizens acted as community guardians. Thus, comprehensive people-place relations emerge as a pivotal factor for a community's adaptative capacity in the face of climate change-induced hazards.
C1 [Heidenreich, Sara; Naess, Robert] Norwegian Univ Sci & Technol, Dept Interdisciplinary Studies Culture, N-7491 Trondheim, Norway.
C3 Norwegian University of Science & Technology (NTNU)
RP Heidenreich, S (corresponding author), Norwegian Univ Sci & Technol, Dept Interdisciplinary Studies Culture, N-7491 Trondheim, Norway.
EM sara.heidenreich@ntnu.no; robert.ness@ntnu.no
RI Heidenreich, Sara/AAW-9506-2020
OI Heidenreich, Sara/0000-0003-2524-8080
FU NordForsk
FX We would like to thank our study participants in the three
   municipalities for their valuable input and the reviewers and editors
   for their very helpful feedback.
CR Amundsen H, 2015, LOCAL ENVIRON, V20, P257, DOI 10.1080/13549839.2013.838751
   Anderson B, 2011, AREA, V43, P124, DOI 10.1111/j.1475-4762.2011.01004.x
   Anderson Ben., 2012, DIALOGUES HUM GEOGR, V2, P171, DOI DOI 10.1177/2043820612449261
   Arora S, 2020, SUSTAINABILITY-SCI P, V16, P247, DOI 10.1080/15487733.2020.1816687
   Berroeta H, 2021, CHANGING SENSES OF PLACE, P43
   Bingham AJ, 2023, INT J QUAL METH, V22, DOI 10.1177/16094069231183620
   Bonaiuto M, 2016, J ENVIRON PSYCHOL, V48, P33, DOI 10.1016/j.jenvp.2016.07.007
   Brink E, 2019, J CLEAN PROD, V209, P1342, DOI 10.1016/j.jclepro.2018.10.164
   Cieslik K, 2019, FRONT EARTH SC-SWITZ, V7, DOI 10.3389/feart.2019.00278
   Dapilah F, 2020, CLIM DEV, V12, P42, DOI 10.1080/17565529.2019.1596063
   De Dominicis S, 2015, J ENVIRON PSYCHOL, V43, P66, DOI 10.1016/j.jenvp.2015.05.010
   de la Bellacasa MP, 2011, SOC STUD SCI, V41, P85, DOI 10.1177/0306312710380301
   de Moura EO, 2020, CAN J ADM SCI, V37, P350, DOI 10.1002/cjas.1548
   Deleuze G., 1987, A Thousand Plateaus: Capitalism and Schizophrenia
   Devine-Wright P., 2020, Place Attachment, DOI DOI 10.4324/9780429274442-14
   Dey I., 2004, Qualitative research practice, P80
   Diener AC, 2022, GEOGR REV, V112, P171, DOI 10.1080/00167428.2020.1839899
   Domingues RB, 2021, INT J DISAST RISK RE, V60, DOI 10.1016/j.ijdrr.2021.102288
   Dovey Kim., 2020, The Routledge Handbook of Place, P21
   DSB, Prevention of natural hazards in Norway. Direktoratet for samfunnsikkerhet og beredskap
   Feng XL, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su142316073
   Fletcher AJ, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01645-2
   Guillou E, 2016, Pap Soc Representations, V25
   Hegger D, 2022, ENVIRON POLICY GOV, V32, P161, DOI 10.1002/eet.1990
   Heidenreich S, 2023, Storytelling. Engagement methods for climate, energy and mobility transitions, V11
   Hisdal H, 2021, NCCS report no 2/2021
   Hovelsrud GK, 2010, COMMUNITY ADAPTATION AND VULNERABILITY IN ARCTIC REGIONS, P23, DOI 10.1007/978-90-481-9174-1_2
   Jones O, 2008, MATERIAL AGENCY:TOWARDS A NON-ANTHROPOCENTRIC APPROACH, P79, DOI 10.1007/978-0-387-74711-8_5
   Kervyn M., 2015, Belgian Journal of Geography, V1, P1, DOI [10.4000/belgeo.15944, DOI 10.4000/BELGEO.15944]
   Latour B., 2018, Down to earth: Politics in the new climatic regime
   Lewicka M, 2011, J ENVIRON PSYCHOL, V31, P207, DOI 10.1016/j.jenvp.2010.10.001
   Lie LB, 2023, REG ENVIRON CHANGE, V23, DOI 10.1007/s10113-023-02106-2
   Lindn L., 2021, Nordic Journal of Science and Technology Studies, V9, P3, DOI [10.5324/njsts.v9i1.4000, DOI 10.5324/NJSTS.V9I1.4000]
   Liu QY, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127188
   Luís S, 2016, J RISK RES, V19, P810, DOI 10.1080/13669877.2015.1042507
   Lujala P, 2015, LOCAL ENVIRON, V20, P489, DOI 10.1080/13549839.2014.887666
   Masterson VA, 2019, SUSTAIN SCI, V14, P555, DOI 10.1007/s11625-019-00695-8
   McGowran P, 2021, PROG HUM GEOG, V45, P1601, DOI 10.1177/03091325211003328
   Mertens K., 2021, Belgeo, V4, P76, DOI [10.4000/belgeo.53076, DOI 10.4000/BELGEO.53076]
   Miljodirektoratet, 2023, Klimaendringer i Norge
   Moezzi M, 2017, ENERGY RES SOC SCI, V31, P1, DOI 10.1016/j.erss.2017.06.034
   Mol Annemarie., 2010, CARE PRACTICE TINKER
   Mortreux C, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab7834
   Mourik RM, 2021, ENERGY RES SOC SCI, V73, DOI 10.1016/j.erss.2021.101940
   Müller M, 2016, T I BRIT GEOGR, V41, P217, DOI 10.1111/tran.12117
   Murphy M, 2015, SOC STUD SCI, V45, P717, DOI 10.1177/0306312715589136
   Naess LO, 2013, WIRES CLIM CHANGE, V4, P99, DOI 10.1002/wcc.204
   Nass R., 2013, Klimakunnskap og kunnskapsklima: Hvordan drives klimatilpasning?
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   NOU, 2023, Generalistkommunesystemet. Likt ansvar - ulike forutsetninger, P9
   NOU, 2010, Tilpassing til eit klima i endringSamfunnet si sarbarheit og behov for tilpassing til konsekvensar av klimaendringane, P10
   Orlikowski WJ, 2007, ORGAN STUD, V28, P1435, DOI 10.1177/0170840607081138
   Ratnam C, 2018, GEOGR RES-AUST, V56, P42, DOI 10.1111/1745-5871.12250
   Raymond CM, 2017, FRONT PSYCHOL, V8, DOI 10.3389/fpsyg.2017.01674
   Rollero C, 2010, J ENVIRON PSYCHOL, V30, P198, DOI 10.1016/j.jenvp.2009.12.003
   Scannell L, 2010, J ENVIRON PSYCHOL, V30, P1, DOI 10.1016/j.jenvp.2009.09.006
   Scherzer S, 2019, INT J DISAST RISK RE, V36, DOI 10.1016/j.ijdrr.2019.101107
   Setten G, 2019, INT J DISAST RISK RE, V38, DOI 10.1016/j.ijdrr.2019.101184
   Solli J., 2014, NORD J SCI TECHNOL S, V2, P18
   Stewart K, 2008, J FOLKLORE RES, V45, P71, DOI 10.2979/JFR.2008.45.1.71
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Torres HR, 2018, WEATHER CLIM SOC, V10, P361, DOI 10.1175/WCAS-D-17-0094.1
   Tosse SE, 2012, Uncertainties and insufficiencies: making sense of climate adaptation
   Troan B, 2017, Poretrykksutloste jordog flomskred: En studie av skredhendelser i Melen i Forradalen, Stjordal kommune
   Uittenbroek CJ, 2022, ENVIRON POLICY GOV, V32, P192, DOI 10.1002/eet.1983
   van Valkengoed AM, 2022, CLIMATIC CHANGE, V171, DOI 10.1007/s10584-022-03338-7
   Williams D.R., 2020, Place Attachment: Advances in Theory, Methods and Application, P12, DOI [10.4324/9780429274442-1, DOI 10.4324/9780429274442-1]
   Zwiers S, 2018, COMMUNITY DEV J, V53, P281, DOI 10.1093/cdj/bsw020
NR 68
TC 1
Z9 1
U1 1
U2 4
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD JUN
PY 2024
VL 24
IS 2
AR 39
DI 10.1007/s10113-024-02207-6
PG 13
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA JX0Q5
UT WOS:001176345800001
OA hybrid
DA 2025-01-10
ER

PT J
AU O'Keeffe, JM
   Cummins, V
   Devoy, RJN
   Lyons, D
   Gault, J
AF O'Keeffe, Jane M.
   Cummins, Valerie
   Devoy, Robert J. N.
   Lyons, Donald
   Gault, Jeremy
TI Stakeholder awareness of climate adaptation in the commercial seaport
   sector: A case study from Ireland
SO MARINE POLICY
LA English
DT Article
DE Adaptive capacity; Climate adaptation; Maritime industry; Port sector;
   Stakeholder; Environmental management
ID STRATEGIES; ROTTERDAM
AB Seaports as critical shore-based infrastructure are particularly vulnerable to impacts such as sea level rise and increasing incidents of severe weather events. In excess of ninety percent of global trade by volume is transported by sea. In Ireland, seaports are of strategic importance to the national economy. As an island nation, ninety eight percent of trade by volume comes through its seaports. Climate issues facing Irish ports include increasing storminess, such as the Atlantic storms experienced in the winter of 2014. Ireland provides a particularly valuable case study as the scale of Irish port sizes, analysed in this research, range from 500,000 to 30 million throughput tonnage. This tonnage range, is more typical of port sizes globally, and adds relevance to the study. The specific objectives of this paper are to establish the readiness of the seaport sector in Ireland to build adaptive capacity to respond to climate change and to assess lessons from and for Ireland in the context of international best practice. The research identified a lack of awareness and understanding of climate change amongst the sample population of seventy senior managers (comprising of national regulators and local authorities; commercial port harbour companies; and indigenous and multinational industries located in the port hinterland), as representatives of the maritime sector in Ireland. Evidence of a knowledge gap was identified from in-depth semi-structured interviews conducted over a twelve month period. Many industry stakeholders were actually implementing adaptation measures within their organisational strategies, unaware of the explicit links with climate adaptation. (C) 2016 Elsevier Ltd. All rights reserved.
C1 [O'Keeffe, Jane M.] NMCI, Ringaskiddy, Cork, Ireland.
   [Cummins, Valerie; Devoy, Robert J. N.; Gault, Jeremy] UCC, Marine & Renewable Energy Ireland MaREI Ctr, Haulbowline Rd, Ringaskiddy, Cork, Ireland.
   [O'Keeffe, Jane M.; Devoy, Robert J. N.; Lyons, Donald] UCC, Dept Geog, Cork, Ireland.
   [Cummins, Valerie] UCC, MaREI, Future Earth Coasts, Land Ocean Interact Coastal Zone LOICZ, Ringaskiddy, Cork, Ireland.
C3 University College Cork
RP O'Keeffe, JM (corresponding author), NMCI, Ringaskiddy, Cork, Ireland.
EM Jane.okeeffe@nmci.ie; v.cummins@imerc.ie; r.devoy@ucc.ie;
   d.lyons@ucc.ie; J.Gault@ucc.ie
FU Cork Institute of Technology (CIT); Marine and Renewable Energy Ireland
   (MaREI) Centre, University College Cork (UCC)
FX The authors acknowledge the funding support of those organisations that
   funded the study: Cork Institute of Technology (CIT); and Marine and
   Renewable Energy Ireland (MaREI) Centre, University College Cork (UCC).
   We also thank the reviewers of this paper, interview partners, workshop
   participants and collaborators in the on-going research. The paper is
   part of a broader study on Maritime Industry in the context of its
   resource capabilities, adaptive capacity and responsiveness to climate
   change.
CR [Anonymous], 2009, SMART ENERGY WE CAN
   [Anonymous], NAT CLIM CHANG AD FR
   [Anonymous], 2014, SUSTAINABLE PORT SUS
   [Anonymous], 2007, Climate Change 2007: A Synthesis Report, P22
   [Anonymous], 2012, Sustainability Reporting Statement for Wastewater Systems
   [Anonymous], 2008, CORK HARBOUR INTEGRA
   [Anonymous], 2013, Sustainability Report 2012
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Ballinger R, 2008, POINT COREPOINT IMPR, P81
   Becker A, 2012, CLIMATIC CHANGE, V110, P5, DOI 10.1007/s10584-011-0043-7
   Cooper JAG, 2012, OCEAN COAST MANAGE, V64, P1, DOI 10.1016/j.ocecoaman.2012.04.001
   Cooper JAG, 2009, MAR POLICY, V33, P869, DOI 10.1016/j.marpol.2009.04.007
   Davoudi S., 2011, ELECT WORKING PAPER, V44
   Dawson R, 2007, PHILOS T R SOC A, V365, P3085, DOI 10.1098/rsta.2007.0008
   Department of Agriculture & Cooperation Ministry of Agriculture Government of India, 2007, NAT FOOD SEC MISS OP, P7
   Department of Agriculture Food and the Marine, 2012, HARNESSING OUR OCEAN
   Department of Transport Tourism and Sport, 2013, NAT PORTS POL 2013
   Desmond M., 2012, SHINE EPA CLIMATE CH
   Desmond M., 2009, EPA CLIMATE CHANGE R
   Devoy R.J., 2014, MARINE HAZARDS RISKS, V2015, P197
   Dillen J., 2012, RISICOBEOORDELING
   Dooms M, 2013, RES TRANSP BUS MANAG, V8, P148, DOI 10.1016/j.rtbm.2013.06.004
   DUTT S, 2012, TENCON 2012 2012 IEE, P1
   Fagan Brian., 2013, The Attacking Ocean: The Past, Present, and Future of Rising Sea Levels
   Field C.B., 2012, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, P555
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Greene CH, 2013, OCEANOGRAPHY, V26, P8, DOI 10.5670/oceanog.2013.11
   Hawkes P, 2010, P ICE CIV ENG 163 MA, P55
   Inoue S., 2013, JRC WORKSH RISK ASS
   International Association of Ports and Harbours IAPH, 2008, C40 WORLDS PORTS CLI
   International Association of Ports and Harbours-IAHP, 2010, SEAP CLIM CHANG AN A
   IPCC, 2013, WORK GROUP 2 CONTR I
   Lu PW, 2013, CITIES, V35, P200, DOI 10.1016/j.cities.2013.06.001
   McEvoy D, 2013, WORK PACKAGE 1 ENHAN, P77
   McEvoy D, 2011, WORK PACKAGE 4 ENHAN, P1
   McEvoy D., 2013, WORK PACKAGE 4 ENHAN, P1
   McEvoy D, 2012, WORK PACKAGE 1 ENHAN
   McLaughlin B., 2011, ANTICIPATING CLIMATE
   Morecroft M.D., 2013, LOCAL EC, V25
   Muir D, 2014, OCEAN COAST MANAGE, V94, P1, DOI 10.1016/j.ocecoaman.2014.03.017
   Ng AKY, 2013, RES TRANSP BUS MANAG, V8, P186, DOI 10.1016/j.rtbm.2013.05.005
   Nicholls R.J., 2008, OECD ENV WORKING PAP, DOI [DOI 10.1787/011766488208, 10.1787/011766488208]
   O'Hagan AM, 2010, OCEAN COAST MANAGE, V53, P750, DOI 10.1016/j.ocecoaman.2010.10.014
   O'Hagan AM, 2009, MAR POLICY, V33, P912, DOI 10.1016/j.marpol.2009.04.009
   Office of Public Works (OPW), 2014, S W RBD CFRAM STUD S
   Park S, 2012, ENVIRON SCI POLICY, V15, P23, DOI 10.1016/j.envsci.2011.09.004
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Ranger N, 2012, CLIM DEV, V4, P288, DOI 10.1080/17565529.2012.732919
   Scott H., 2013, ENHANCING RESILIENCE, P1
   Shine T., 2011, IRELAND ADAPTS CLIMA, V9
   Smythe T, 2013, 238 U COL NAT HAZ CT
   Sturt F, 2013, J ARCHAEOL SCI, V40, P3963, DOI 10.1016/j.jas.2013.05.023
   UNCTAD, 2008, UN C TRAD DEV UNCTAD
   USEPA (US Environmental Protection Agency), 2008, PLANN CLIM CHANG IMP
   Van der Meer Rinske., 2011, Port Climate action at Rotterdam
   Vellinga T., 2012, MARITIME TRANSPORT C
   World Ports Climate Initiative (WPCI), 2014, IAPH TOOLB PORT CLAN
   World Ports Climate Initiative (WPCI), 2008, HIST WPCI BEG CHIEF
NR 58
TC 12
Z9 13
U1 1
U2 18
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0308-597X
EI 1872-9460
J9 MAR POLICY
JI Mar. Pol.
PD JAN
PY 2020
VL 111
AR 102404
DI 10.1016/j.marpol.2016.04.044
PG 10
WC Environmental Studies; International Relations
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; International Relations
GA JW8TI
UT WOS:000503319000019
DA 2025-01-10
ER

PT J
AU van der Knaap, YAM
   Bakker, MM
   Alam, SJ
   Witte, JPM
   Aerts, R
   van Ek, R
   van Bodegom, PM
AF van der Knaap, Yasmijn A. M.
   Bakker, Martha M.
   Alam, Shah Jamal
   Witte, Jan-Philip M.
   Aerts, Rien
   van Ek, Remco
   van Bodegom, Peter M.
TI Projected vegetation changes are amplified by the combination of climate
   change, socio-economic changes and hydrological climate adaptation
   measures
SO LAND USE POLICY
LA English
DT Article
DE Interdisciplinary approach; Coupled modelling; Set-aside; Hydrology;
   Ecology; Plant traits
ID LAND-USE; CHANGE IMPACTS; ECOSYSTEMS; WATER; NETHERLANDS; SIMULATION;
   CATCHMENT; SCIENCE; GAP; WET
AB Climate change is projected to strongly affect the hydrological cycle, altering water availability and causing successive shifts in vegetation composition and distribution. To reduce potential negative effects on vegetation, policymakers may implement hydrological climate adaptation measures, which may -in turn- require land use changes to be successful. Policy driven land use changes should therefore be taken into account when evaluating climate change and adaptation effects on the water-vegetation system, but this is rarely done. To support such policy interventions, we applied a coupled land use - hydrology - vegetation model to simulate effects of (i) climate change, (ii) socio-economic change, (iii) hydrological measures and (iv) policy driven land use change, alone and in interaction, on vegetation communities in the Netherlands. We simulated two climate scenarios for 2050 that differed in predicted temperature (+ 0.9 degrees C and + 2.8 degrees C) and precipitation changes (groundwater recharge + 4% or - 14%). The associated socio-economic scenarios differed in the increase of gross margins per agricultural class. The land use changes concerned agricultural changes and development of new nature areas from agricultural land. Individually, land use changes had the biggest effect on vegetation distribution and composition, followed by the hydrological measures and climate change itself. Our results also indicate that the combination of all four factors triggered the biggest response in the extent of newly created nature areas ( + 6.5%) and the highest diversity in vegetation types, compared to other combinations (max. + 5.4%) and separate factors. This study shows that an interdisciplinary, coupled modelling approach is essential when evaluating climate adaptation measures.
C1 [van der Knaap, Yasmijn A. M.; Witte, Jan-Philip M.; Aerts, Rien; van Bodegom, Peter M.] Vrije Univ Amsterdam, Fac Earth & Life Sci, Dept Ecol Sci, Syst Ecol, De Boelelaan 1085, NL-1081 HV Amsterdam, Netherlands.
   [Bakker, Martha M.] Wageningen Univ & Res, Land Use Planning Grp, Droevendaalsesteeg 3, NL-6708 BA Wageningen, Netherlands.
   [Alam, Shah Jamal] Univ Edinburgh, Sch GeoSci, Drummond St, Edinburgh EH8 9XP, Midlothian, Scotland.
   [Alam, Shah Jamal] Habib Univ, Sch Sci & Engn, Block 18,Gulistan E Jauhar Univ Ave, Karachi, Pakistan.
   [Witte, Jan-Philip M.] KWR Watercycle Res Inst, POB 1072, NL-3430 BB Nieuwegein, Netherlands.
   [van Ek, Remco] Deltares, Sect Groundwater Management, Unit Subsurface & Groundwater Syst, POB 85467, NL-3508 AL Utrecht, Netherlands.
   [van Bodegom, Peter M.] Leiden Univ, Inst Environm Sci, Dept Conservat Biol, Einsteinweg 2, NL-2333 CC Leiden, Netherlands.
C3 Vrije Universiteit Amsterdam; Wageningen University & Research;
   University of Edinburgh; KWR Watercycle Research Institute; Deltares;
   Leiden University; Leiden University - Excl LUMC
RP van der Knaap, YAM (corresponding author), Natl Inst Publ Hlth & Environm, Ctr Environm Safety & Secur, POB 1, NL-3720 BA Bilthoven, Netherlands.
EM yasmijn.van.der.knaap@rivm.nl
RI ; van Bodegom, Peter/N-8150-2015
OI Aerts, Rien/0000-0001-6694-0669; van Bodegom, Peter/0000-0003-0771-4500
FU Knowledge for Climate programme
FX We thank Jacco Hoogewoud for his help in interpreting the hydrological
   results and Myrjam de Graaf for providing the data for the hydrological
   measures and for her advice regarding the climate adaptation modelling.
   Furthermore, we thank the KNMI for the use of their climate data and
   Gerrit Hendriksen for his help in acquiring the data. Ruud Bartholomeus
   was very helpful in running the transfer functions for PROBE. Finally,
   we thank Lieneke Verheijen for her assistance in setting up R scripts
   for data analysis and an anonymous reviewer for providing valuable
   comments on an earlier version of the manuscript. This research was
   funded by the Knowledge for Climate programme, theme 3
   (www.knowledgeforclimate.org).
CR Alexander LV, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006290
   [Anonymous], H2O
   [Anonymous], 2013, ECOHYDROLOGICAL STRE
   Arnell NW, 2013, J HYDROL, V486, P351, DOI 10.1016/j.jhydrol.2013.02.010
   Bakker M, 2015, LANDSCAPE ECOL, V30, P791, DOI 10.1007/s10980-014-0145-5
   Bakker MM, 2015, LANDSCAPE ECOL, V30, P763, DOI 10.1007/s10980-015-0181-9
   Bakker MM, 2015, LANDSCAPE ECOL, V30, P273, DOI 10.1007/s10980-014-0116-x
   Bartholomeus RP, 2011, J GEOPHYS RES-BIOGEO, V116, DOI 10.1029/2011JG001693
   Briffa KR, 2009, INT J CLIMATOL, V29, P1894, DOI 10.1002/joc.1836
   Capon SJ, 2013, ECOSYSTEMS, V16, P359, DOI 10.1007/s10021-013-9656-1
   Daloglu I, 2014, AGR SYST, V129, P93, DOI 10.1016/j.agsy.2014.05.007
   Douma JC, 2012, ECOGRAPHY, V35, P364, DOI 10.1111/j.1600-0587.2011.07068.x
   Douma JC, 2012, FUNCT ECOL, V26, P1355, DOI 10.1111/j.1365-2435.2012.02054.x
   Fohrer N, 2002, PHYS CHEM EARTH, V27, P655, DOI 10.1016/S1474-7065(02)00050-5
   Fohrer N, 2001, PHYS CHEM EARTH PT B, V26, P577, DOI 10.1016/S1464-1909(01)00052-1
   Hughes SJ, 2012, AREA, V44, P432, DOI 10.1111/j.1475-4762.2012.01114.x
   Kanellopoulos A, 2014, EUR J AGRON, V52, P69, DOI 10.1016/j.eja.2013.10.003
   KNMI, 2011, KLIM LANGJ GEM 1981
   Kros J, 2015, LANDSCAPE ECOL, V30, P871, DOI 10.1007/s10980-014-0131-y
   Laniak GF, 2013, ENVIRON MODELL SOFTW, V39, P3, DOI 10.1016/j.envsoft.2012.09.006
   McDonald M.G., 1988, MODULAR 3 DIMENSIONA
   Memarian H, 2014, HYDROLOG SCI J, V59, P1808, DOI 10.1080/02626667.2014.892598
   Ministry of Economic Affairs, 2009, NAT 2000 GEB PROF HA
   Ministry of Infrastructure and the Environment, 2011, ADM AGR WAT AFF
   Ordoñez JC, 2010, AM NAT, V175, P225, DOI 10.1086/649582
   Paas W., 2013, IMPACTS CLIMATE CHAN
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Qiu GY, 2011, J ENVIRON QUAL, V40, P1745, DOI 10.2134/jeq2010.0263
   Rajczak J, 2013, J GEOPHYS RES-ATMOS, V118, P3610, DOI 10.1002/jgrd.50297
   Riedijk A., 2007, Integrated scenarios of socioeconomic and climate change; a framework for the "Climate changes Spatial Planning" programme. Spinlab Reseach Memorandum SL-06
   Runhaar J., 2004, GORTERIA, V30, P12
   Smith JWN, 2008, HYDROL PROCESS, V22, P151, DOI 10.1002/hyp.6902
   Stocker, 2014, CLIMATE CHANGE 2013
   Straatman J. H. M., 2002, STROOMGEBIEDSVISIE T
   Susnik J, 2015, SCI TOTAL ENVIRON, V503, P279, DOI 10.1016/j.scitotenv.2014.06.111
   TNO-NITG, 1998, REGIS REG GEOH INF S
   van den Hurk B., 2006, 200601 KNMI WR
   van der Knaap YAM, 2015, LANDSCAPE ECOL, V30, P855, DOI 10.1007/s10980-014-0142-8
   van der Sande C, 2010, SENSORS-BASEL, V10, P8198, DOI 10.3390/s100908198
   van Haren R, 2013, CLIM DYNAM, V40, P1, DOI 10.1007/s00382-012-1401-5
   van Roosmalen L, 2009, WATER RESOUR RES, V45, DOI 10.1029/2007WR006760
   van Walsum PEV, 2008, VADOSE ZONE J, V7, P769, DOI 10.2136/vzj2007.0146
   Vautard R, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034006
   Veldhuizen A., 2007, 2007UR0193B TNO
   Weltzin JF, 2003, BIOSCIENCE, V53, P941, DOI 10.1641/0006-3568(2003)053[0941:ATROTE]2.0.CO;2
   Witte JPM, 2012, HYDROL EARTH SYST SC, V16, P3945, DOI 10.5194/hess-16-3945-2012
   Witte JPM, 2007, J VEG SCI, V18, P605, DOI 10.1111/j.1654-1103.2007.tb02574.x
   Witte JPM, 2015, LANDSCAPE ECOL, V30, P835, DOI 10.1007/s10980-014-0086-z
   Witte JPM, 2000, ECOL ENG, V16, P143, DOI 10.1016/S0925-8574(00)00098-7
   Wolf J., 2013, AGR ADAPTATION CLIMA
   Wolf J., 2011, Integrated assessment of adaptation to climate change in Flevoland at farm and regional levels
   Wösten JHM, 2001, J HYDROL, V251, P123, DOI 10.1016/S0022-1694(01)00464-4
   Zolina O, 2013, J CLIMATE, V26, P2022, DOI 10.1175/JCLI-D-11-00498.1
NR 53
TC 6
Z9 6
U1 1
U2 23
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0264-8377
EI 1873-5754
J9 LAND USE POLICY
JI Land Use Pol.
PD MAR
PY 2018
VL 72
BP 547
EP 562
DI 10.1016/j.landusepol.2017.12.071
PG 16
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA FW8FN
UT WOS:000425564900055
OA Green Published
DA 2025-01-10
ER

PT J
AU Takong, RR
   Abiodun, BJ
AF Takong, Ridick Roland
   Abiodun, Babatunde J.
TI Projected changes in precipitation characteristics over the Drakensberg
   Mountain Range
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE climate change; CORDEX; Drakensberg; NEX; precipitation; precipitation
   index
ID CLIMATE-CHANGE; REGIONAL CLIMATE; SOUTH-AFRICA; EXTREME PRECIPITATION;
   SUMMER RAINFALL; FUTURE CHANGES; INDEXES; CHINA; CMIP5; SIMULATIONS
AB This study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0 & DEG;C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi-model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi-model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX-GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self-organizing-map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.
C1 [Takong, Ridick Roland; Abiodun, Babatunde J.] Univ Cape Town, Dept Environm & Geog Sci, Climate Syst Anal Grp, Cape Town, South Africa.
C3 University of Cape Town
RP Takong, RR (corresponding author), Univ Cape Town, Dept Environm & Geog Sci, Climate Syst Anal Grp, Cape Town, South Africa.
EM takong@aims.ac.za
RI ; Abiodun, Babatunde/ABG-6340-2021
OI TAKONG, Ridick Roland/0000-0002-9735-5726; Abiodun,
   Babatunde/0000-0002-3878-0116
FU University of Cape Town (UCT); Water Research Commission (WRC)
FX University of Cape Town (UCT); Water Research Commission (WRC)
CR Abatan AA, 2023, FRONT CLIM, V4, DOI 10.3389/fclim.2022.1031226
   Abiodun BJ, 2020, INT J CLIMATOL, V40, P3118, DOI 10.1002/joc.6386
   Abiodun BJ, 2019, THEOR APPL CLIMATOL, V137, P1785, DOI 10.1007/s00704-018-2693-0
   Abiodun BJ, 2017, CLIMATIC CHANGE, V143, P399, DOI 10.1007/s10584-017-2001-5
   Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   [Anonymous], 1976, CLIMATE DRAKENSBERG
   Ayar PV, 2016, CLIM DYNAM, V46, P1301, DOI 10.1007/s00382-015-2647-5
   Baldocchi DD, 2003, GLOBAL CHANGE BIOL, V9, P479, DOI 10.1046/j.1365-2486.2003.00629.x
   Bao Y, 2017, J METEOROL RES-PRC, V31, P236, DOI 10.1007/s13351-017-6106-6
   Barimalala R, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abeb34
   Becker A., 1997, PREDICTING GLOBAL CH
   Beniston M, 2003, CLIMATIC CHANGE, V59, P5, DOI 10.1023/A:1024458411589
   Beniston M, 2006, HYDROBIOLOGIA, V562, P3, DOI 10.1007/s10750-005-1802-0
   Blamey RC, 2013, J CLIMATE, V26, P1654, DOI 10.1175/JCLI-D-12-00239.1
   Huo-Po C, 2017, ATMOS OCEAN SCI LETT, V10, P403, DOI 10.1080/16742834.2017.1367625
   Crétat J, 2012, CLIM DYNAM, V38, P613, DOI 10.1007/s00382-011-1055-8
   Deque Michel, 2017, Climate Services, V7, P87, DOI 10.1016/j.cliser.2016.06.002
   Dieppois B, 2016, J GEOPHYS RES-ATMOS, V121, P6215, DOI 10.1002/2015JD024576
   Dosio A, 2018, GEOPHYS RES LETT, V45, P935, DOI 10.1002/2017GL076222
   Drobinski P, 2018, CLIM DYNAM, V51, P1237, DOI 10.1007/s00382-016-3083-x
   ECHO, 2022, ECHO DAIL FLASH TUES
   Engelbrecht FA, 2009, INT J CLIMATOL, V29, P1013, DOI 10.1002/joc.1742
   Fatti CE, 2013, APPL GEOGR, V36, P13, DOI 10.1016/j.apgeog.2012.06.011
   Favre A, 2016, CLIM DYNAM, V46, P1799, DOI 10.1007/s00382-015-2677-z
   Fosser G, 2015, CLIM DYNAM, V44, P45, DOI 10.1007/s00382-014-2242-1
   Funk CC, 2014, U.S. Geological Survey Data Series, V4, DOI [DOI 10.3133/DS832, 10.3133/ds832]
   Giorgi F, 1999, J GEOPHYS RES-ATMOS, V104, P6335, DOI 10.1029/98JD02072
   GIORGI F, 1991, REV GEOPHYS, V29, P191, DOI 10.1029/90RG02636
   Hart NCG, 2013, CLIM DYNAM, V41, P1199, DOI 10.1007/s00382-012-1589-4
   Hertig E, 2012, METEOROL Z, V21, P61, DOI 10.1127/0941-2948/2012/0271
   Hewitson BC, 2006, INT J CLIMATOL, V26, P1315, DOI 10.1002/joc.1314
   Hohenegger C, 2008, METEOROL Z, V17, P383, DOI 10.1127/0941-2948/2008/0303
   Hulme M, 2001, CLIM RES, V17, P145, DOI 10.3354/cr017145
   Hunter E. C., 2016, P 17 NORDIC GEOTECHN
   Hydén L, 2000, WATER SA, V26, P83
   Karl TR, 2003, SCIENCE, V302, P1719, DOI 10.1126/science.1090228
   Kendon EJ, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09776-9
   Klein Tank A., 2009, WMO TD 1500, V72
   Klutse NAB, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab37b
   Kohonen T., 1998, Neurocomputing, V21, P1, DOI 10.1016/S0925-2312(98)00030-7
   Kruger AC, 2006, INT J CLIMATOL, V26, P2275, DOI 10.1002/joc.1368
   Kruger AC, 2004, INT J CLIMATOL, V24, P1929, DOI 10.1002/joc.1096
   Kumi N, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab89e
   Kusangaya S, 2014, PHYS CHEM EARTH, V67-69, P47, DOI 10.1016/j.pce.2013.09.014
   Landman WA, 2018, THEOR APPL CLIMATOL, V132, P1153, DOI 10.1007/s00704-017-2168-8
   Maidment RI, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.63
   Malherbe J, 2016, NAT HAZARDS, V80, P657, DOI 10.1007/s11069-015-1989-y
   Malherbe J, 2014, CLIM DYNAM, V42, P3121, DOI 10.1007/s00382-013-2027-y
   Mason SJ, 1999, CLIMATIC CHANGE, V41, P249, DOI 10.1023/A:1005450924499
   Maúre G, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab190
   Mba WP, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab048
   Mbokodo I, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11070712
   Mizuta R, 2014, SOLA, V10, P167, DOI 10.2151/sola.2014-035
   Monerie PA, 2017, CLIM DYNAM, V48, P2751, DOI 10.1007/s00382-016-3236-y
   Ndarana T, 2021, INT J CLIMATOL, V41, pE1000, DOI 10.1002/joc.6745
   NEL W., 2006, South African Geographical Journal, V88, P130
   Nel W, 2008, GEOGR ANN A, V90A, P97, DOI 10.1111/j.1468-0459.2008.00337.x
   New M, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006289
   Nikulin G, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab1b1
   Novella NS, 2013, J APPL METEOROL CLIM, V52, P588, DOI 10.1175/JAMC-D-11-0238.1
   Pathak R, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-45907-4
   Pinto I, 2016, CLIMATIC CHANGE, V135, P655, DOI 10.1007/s10584-015-1573-1
   Pohl B, 2017, SCI REP-UK, V7, DOI 10.1038/srep46466
   Qian JH, 1999, J GEOPHYS RES-ATMOS, V104, P6501, DOI 10.1029/98JD02649
   Anh QT, 2018, PROG EARTH PLANET SC, V5, DOI 10.1186/s40645-018-0185-6
   Ratna SB, 2014, CLIM DYNAM, V42, P2931, DOI 10.1007/s00382-013-1918-2
   Ruane AC, 2015, AGR FOREST METEOROL, V200, P233, DOI 10.1016/j.agrformet.2014.09.016
   Sakalli Abdulla, 2017, Climate Services, V7, P64, DOI 10.1016/j.cliser.2017.03.006
   Schär C, 2016, CLIMATIC CHANGE, V137, P201, DOI 10.1007/s10584-016-1669-2
   Schroeer K, 2018, CLIM DYNAM, V50, P3981, DOI 10.1007/s00382-017-3857-9
   Sorooshian S, 2000, B AM METEOROL SOC, V81, P2035, DOI 10.1175/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2
   Sylla MB, 2013, INT J CLIMATOL, V33, P1805, DOI 10.1002/joc.3551
   Tadross M, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL024460
   Tang JP, 2016, J GEOPHYS RES-ATMOS, V121, P2110, DOI 10.1002/2015JD023977
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   TENNANT WJ, 1994, S AFR J SCI, V90, P45
   Thoithi W, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2020GL091041
   Thompson LG, 2000, QUATERNARY SCI REV, V19, P19, DOI 10.1016/S0277-3791(99)00052-9
   Thrasher B, 2012, HYDROL EARTH SYST SC, V16, P3309, DOI 10.5194/hess-16-3309-2012
   Thrasher B, 2015, NASA earth exchange global daily downscaled projections (nex-gddp)
   UNESCO, 2000, UN ED SCI CULT ORG C
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Vautard R, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034006
   Warburton M., 2005, Climate Change and Water Resources in Southern Africa: Studies on Scenarios, Impacts, Vulnerabilities and Adaptation, P275
   Weedon GP, 2014, WATER RESOUR RES, V50, P7505, DOI 10.1002/2014WR015638
   Whiteman C.D., 2000, Mountain meteorology: fundamentals and applications
   Wilby RL, 1997, PROG PHYS GEOG, V21, P530, DOI 10.1177/030913339702100403
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Wood AW, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD000659
   Yhang YB, 2017, ADV METEOROL, V2017, DOI 10.1155/2017/2956373
   Yu R, 2018, INT J CLIMATOL, V38, P2374, DOI 10.1002/joc.5340
NR 91
TC 1
Z9 1
U1 3
U2 12
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD MAY
PY 2023
VL 43
IS 6
BP 2541
EP 2567
DI 10.1002/joc.7989
EA JAN 2023
PG 27
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA AR7I4
UT WOS:000921258300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Uawisetwathana, U
   Situmorang, ML
   Arayamethakorn, S
   Haniswita
   Suantika, G
   Panya, A
   Karoonuthaisiri, N
   Rungrassamee, W
AF Uawisetwathana, Umaporn
   Situmorang, Magdalena Lenny
   Arayamethakorn, Sopacha
   Haniswita
   Suantika, Gede
   Panya, Atikorn
   Karoonuthaisiri, Nitsara
   Rungrassamee, Wanilada
TI Supplementation of Ex-Situ Biofloc to Improve Growth Performance and
   Enhance Nutritional Values of the Pacific White Shrimp Rearing at Low
   Salinity Conditions
SO APPLIED SCIENCES-BASEL
LA English
DT Article
DE ex-situ biofloc; Pacific white shrimp; Litopenaeus vannamei; trace
   mineral; amino acid profile; fatty acid profile; nutritional value; feed
   supplement; growth performance
ID LITOPENAEUS-VANNAMEI CULTURE; POLYUNSATURATED FATTY-ACIDS; DIGESTIVE
   ENZYME-ACTIVITY; IMMUNE GENE-EXPRESSION; BLACK TIGER SHRIMP; DISEASE
   RESISTANCE; AQUACULTURE SYSTEM; WATER-QUALITY; BACILLUS; SURVIVAL
AB Featured Application
   This ex situ biofloc technology has high potential to be a strategy for climate change adaptation and mitigation, which is useful for improving shrimp farming practice in the Asia Pacific region and for enhancing food security with high quality of shrimp to serve consumers worldwide.
   Shrimp is an important food source consumed worldwide. An intensive aquaculture system with overuse of feed in combination with detrimental effects from climate change are serious problems leading to mass mortality of cultured shrimp. Biofloc technology is an approach to managing water quality and controlling the disease to counter the negative side of intensive culture system; however, most of the biofloc applications are naturally formed, which could be inconsistent. In this study, we employed an established optimal ratio of microbial consortium called "ex-situ biofloc (BF)" to be used as a feed supplement in shrimp cultured in a zero-water discharged system at low salinity conditions. Three feeding groups (100%commercial pellet (C), 95%C+BF, 90%C+BF) of shrimp were cultured for six weeks. The effect of an ex-situ biofloc supplement with commercial pellet reduction showed that levels of ammonium, nitrite, nitrate and phosphate were significantly decreased in water culture. Shrimp fed with ex-situ biofloc supplement with commercial pellet reduction exhibited significantly increased shrimp weight and survival, and significantly expressed growth-related genes involving lipolysis and energy metabolism higher than those fed with 100% commercial pellet. Nutritional analysis indicated a significant increase of docosahexaenoic acid (DHA) and eicosenoic acid (C20:1) concentrations in the ex-situ biofloc supplemented shrimp. This finding revealed the potential of ex-situ biofloc to manage water quality, improve shrimp growth performance and enhance shrimp nutritional value under intensive culture at low salinity conditions. The beneficial effects of the ex-situ biofloc in shrimp culture system make it a promising alternative strategy to mitigate climate change effects leading to the sustainable production of high-quality shrimp in the future.
C1 [Uawisetwathana, Umaporn; Arayamethakorn, Sopacha; Karoonuthaisiri, Nitsara; Rungrassamee, Wanilada] Natl Ctr Genet Engn & Biotechnol, Microarray Res Team, Pathum Thani 12120, Thailand.
   [Situmorang, Magdalena Lenny; Haniswita; Suantika, Gede] Inst Teknol Bandung, Sch Life Sci & Technol, Microbial Biotechnol Res Grp, Java 40132, Indonesia.
   [Panya, Atikorn] Natl Ctr Genet Engn & Biotechnol, Food Biotechnol Res Team, Pathum Thani 12120, Thailand.
C3 National Science & Technology Development Agency - Thailand; National
   Center Genetic Engineering & Biotechnology (BIOTEC); Institute
   Technology of Bandung; National Science & Technology Development Agency
   - Thailand; National Center Genetic Engineering & Biotechnology (BIOTEC)
RP Uawisetwathana, U (corresponding author), Natl Ctr Genet Engn & Biotechnol, Microarray Res Team, Pathum Thani 12120, Thailand.; Situmorang, ML (corresponding author), Inst Teknol Bandung, Sch Life Sci & Technol, Microbial Biotechnol Res Grp, Java 40132, Indonesia.
EM umaporn.uaw@biotec.or.th; situmorangml@sith.itb.ac.id;
   sopacha.ara@biotec.or.th; haniswit.haniswita@ugent.be;
   gsuantika@sith.itb.ac.id; atikorn.pan@biotec.or.th;
   nitsara.kar@biotec.or.th; wanilada.run@biotec.or.th
RI Situmorang, Magdalena/AAD-9742-2021; Rungrassamee, Wanilada/E-1718-2011;
   Uawisetwathana, Umaporn/E-8974-2011
OI Situmorang, Magdalena Lenny/0000-0003-2209-5349; Rungrassamee,
   Wanilada/0000-0002-5802-4342; panya, atikorn/0000-0003-2229-3257; ,
   Haniswita/0000-0002-6493-9418
FU International Foundation for Science, Sweden [J-3-B-6003-1]; BIOTEC
   fellow's research grant, National Center for Genetic Engineering and
   Biotechnology, BIOTEC, Thailand [P16-52214]
FX This research was funded by the International Foundation for Science,
   Sweden, grant number J-3-B-6003-1 under the IFS collaborative grant and
   the publication cost was supported by BIOTEC fellow's research grant,
   National Center for Genetic Engineering and Biotechnology, BIOTEC,
   Thailand, grant number P16-52214.
CR Vidal JMA, 2018, REV CAATINGA, V31, P495, DOI 10.1590/1983-21252018v31n226rc
   Adhikari S, 2007, J WORLD AQUACULT SOC, V38, P161, DOI 10.1111/j.1749-7345.2006.00085.x
   Ahmmed MK, 2020, COMPR REV FOOD SCI F, V19, P64, DOI 10.1111/1541-4337.12510
   Amin SA, 2012, MICROBIOL MOL BIOL R, V76, P667, DOI 10.1128/MMBR.00007-12
   Anand PSS, 2014, AQUACULTURE, V418, P108, DOI 10.1016/j.aquaculture.2013.09.051
   Anand PSS, 2017, AQUAC RES, V48, P4512, DOI 10.1111/are.13276
   [Anonymous], 1998, STANDARD METHOD EXAM, V20th
   Arantes R, 2017, AQUAC RES, V48, P1478, DOI 10.1111/are.12984
   Lage LPA, 2017, AQUACULTURE, V479, P142, DOI 10.1016/j.aquaculture.2017.05.030
   Avnimelech Y, 2006, AQUACULT ENG, V34, P172, DOI 10.1016/j.aquaeng.2005.04.001
   Avnimelech Y, 2003, AQUACULTURE, V220, P549, DOI 10.1016/S0044-8486(02)00641-5
   Avnimelech Y., 2009, Biofloc Technology. A Practical Guide Book
   Becker W., 2004, MICROALGAE HUMAN ANI
   Bell JG, 2002, J NUTR, V132, P222, DOI 10.1093/jn/132.2.222
   Boyd C.E., 2016, GLOB AQUAC
   Brito LO, 2014, AQUACULT INT, V22, P1649, DOI 10.1007/s10499-014-9771-9
   Burford MA, 2004, AQUACULTURE, V232, P525, DOI 10.1016/S0044-8486(03)00541-6
   Caldow MK, 2019, FRONT NUTR, V6, DOI 10.3389/fnut.2019.00172
   Cheng KM, 2006, AQUACULTURE, V251, P472, DOI 10.1016/j.aquaculture.2005.06.022
   Crab R, 2012, AQUACULTURE, V356, P351, DOI 10.1016/j.aquaculture.2012.04.046
   Davis DA, 2005, J WORLD AQUACULT SOC, V36, P416
   De Schryver P, 2008, AQUACULTURE, V277, P125, DOI 10.1016/j.aquaculture.2008.02.019
   Defoirdt T, 2007, TRENDS BIOTECHNOL, V25, P472, DOI 10.1016/j.tibtech.2007.08.001
   Delgadillo-Mirquez Liliana, 2016, Biotechnol Rep (Amst), V11, P18, DOI 10.1016/j.btre.2016.04.003
   Durmus M, 2019, FOOD SCI TECH-BRAZIL, V39, P454
   Emerenciano M. G. C., 2017, Water quality, P91
   FAO, CONTR FOOD SEC NUTR
   Fox JM, 2018, MICROALGAE IN HEALTH AND DISEASE PREVENTION, P177, DOI 10.1016/B978-0-12-811405-6.00008-6
   Foysal MJ, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-62655-y
   Frassinetti S, 2006, J ENVIRON PATHOL TOX, V25, P597, DOI 10.1615/JEnvironPatholToxicolOncol.v25.i3.40
   Galbraith ED, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00509
   Galkanda-Arachchige HSC, 2021, AQUAC RES, V52, P589, DOI 10.1111/are.14916
   Bernal MG, 2017, AQUACULT INT, V25, P927, DOI 10.1007/s10499-016-0085-y
   Glencross BD, 2009, REV AQUACULT, V1, P71, DOI 10.1111/j.1753-5131.2009.01006.x
   Hai T.N., 2020, OCEANOGR FISH OPEN A, V11, DOI [10.19080/OFOAJ.2020.11.555821, DOI 10.19080/OFOAJ.2020.11.555821]
   Han S, 2017, ISJ-INVERT SURVIV J, V14, P221
   HUNER JV, 1976, COMP BIOCHEM PHYS A, V55, P183, DOI 10.1016/0300-9629(76)90090-6
   Innis SM, 2016, CRIT REV FOOD SCI, V56, P1952, DOI 10.1080/10408398.2015.1018045
   Jäger R, 2020, PROBIOTICS ANTIMICRO, V12, P1330, DOI 10.1007/s12602-020-09656-5
   Jiménez-Ordaz FJ, 2021, LAT AM J AQUAT RES, V49, P155, DOI 10.3856/vol49-issue1-fulltext-2442
   Jónasdóttir SH, 2019, MAR DRUGS, V17, DOI 10.3390/md17030151
   KIRCHMAN DL, 1994, MICROBIAL ECOL, V28, P255, DOI 10.1007/BF00166816
   Kumar V, 2020, FRONT MICROBIOL, V11, DOI 10.3389/fmicb.2020.01270
   Lee Chorong, 2017, Fisheries and Aquatic Sciences, V20, P15, DOI 10.1186/s41240-017-0059-7
   Ley RE, 2008, SCIENCE, V320, P1647, DOI 10.1126/science.1155725
   Li P, 2018, AMINO ACIDS, V50, P29, DOI 10.1007/s00726-017-2490-6
   Li XL, 2011, AMINO ACIDS, V40, P1159, DOI 10.1007/s00726-010-0740-y
   Lin SM, 2013, AQUACULTURE, V406, P79, DOI 10.1016/j.aquaculture.2013.04.026
   Livak KJ, 2001, METHODS, V25, P402, DOI 10.1006/meth.2001.1262
   Maret W, 2013, ADV NUTR, V4, P82, DOI 10.3945/an.112.003038
   Martínez-Córdova LR, 2015, REV AQUACULT, V7, P131, DOI 10.1111/raq.12058
   Miandare HK, 2017, FISH SHELLFISH IMMUN, V70, P621, DOI 10.1016/j.fsi.2017.09.048
   Moriarty D.J., 1999, P 8 INT S MICROBIAL, P237
   Naorbe M. C., 2015, ABAH Bioflux, V7, P28
   Natrah FMI, 2014, REV AQUACULT, V6, P48, DOI 10.1111/raq.12024
   Ning P, 2018, DEV COMP IMMUNOL, V81, P74, DOI 10.1016/j.dci.2017.11.010
   Pereira H, 2012, MAR DRUGS, V10, P1920, DOI 10.3390/md10091920
   Pirahanchi Y., 2020, Lipase
   Roy LA, 2007, AQUACULTURE, V262, P461, DOI 10.1016/j.aquaculture.2006.10.011
   Saini RK, 2020, FOODS, V9, DOI 10.3390/foods9091179
   Senarath S, 2018, EUR J LIPID SCI TECH, V120, DOI 10.1002/ejlt.201700512
   Seraspe E. B., 2012, Asian Fisheries Science, V25, P343
   Shi B, 2021, AQUACULT REP, V19, DOI 10.1016/j.aqrep.2021.100638
   Shurson GC, 2015, J ANIM SCI BIOTECHNO, V6, DOI 10.1186/s40104-015-0005-4
   Sorgeloos P., 1986, MANUAL CULTURE USE B
   Suantika G, 2020, METABOLOMICS, V16, DOI 10.1007/s11306-020-01675-1
   Suantika G, 2018, AQUACULT ENG, V82, P12, DOI 10.1016/j.aquaeng.2018.04.002
   Tacon A. G. J., 2013, FAO Fisheries and Aquaculture Technical Paper, P481
   Thitamadee S, 2016, AQUACULTURE, V452, P69, DOI 10.1016/j.aquaculture.2015.10.028
   Tocher DR, 2019, NUTRIENTS, V11, DOI 10.3390/nu11010089
   Turkmen S, 2019, INT J MOL SCI, V20, DOI 10.3390/ijms20246250
   Uengwetwanit T, 2020, PEERJ, V8, DOI 10.7717/peerj.9646
   Wanders RJA, 2004, MOL GENET METAB, V83, P16, DOI 10.1016/j.ymgme.2004.08.016
   Wei JK, 2014, COMP BIOCHEM PHYS D, V11, P37, DOI 10.1016/j.cbd.2014.07.001
   Xie SW, 2014, AQUACULTURE, V418, P159, DOI 10.1016/j.aquaculture.2013.10.023
   Xie SW, 2020, FRONT PHYSIOL, V11, DOI 10.3389/fphys.2020.01024
   Xu WJ, 2020, WATER-SUI, V12, DOI 10.3390/w12113000
   Yang ZH, 2016, LIPIDS HEALTH DIS, V15, DOI 10.1186/s12944-016-0366-5
   Ziaei-Nejad S, 2006, AQUACULTURE, V252, P516, DOI 10.1016/j.aquaculture.2005.07.021
   Zokaeifar H, 2012, FISH SHELLFISH IMMUN, V33, P683, DOI 10.1016/j.fsi.2012.05.027
NR 80
TC 8
Z9 9
U1 3
U2 17
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2076-3417
J9 APPL SCI-BASEL
JI Appl. Sci.-Basel
PD MAY
PY 2021
VL 11
IS 10
AR 4598
DI 10.3390/app11104598
PG 20
WC Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials
   Science, Multidisciplinary; Physics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Engineering; Materials Science; Physics
GA ST7PV
UT WOS:000662632600001
OA gold
DA 2025-01-10
ER

PT J
AU Cian, F
   Giupponi, C
   Marconcini, M
AF Cian, Fabio
   Giupponi, Carlo
   Marconcini, Mattia
TI Integration of earth observation and census data for mapping a
   multi-temporal flood vulnerability index: a case study on Northeast
   Italy
SO NATURAL HAZARDS
LA English
DT Article
DE Flood; Vulnerability index; Earth observation; Census data; Memory
   effect; Multi-criteria analysis
ID SOCIAL VULNERABILITY; CLIMATE-CHANGE; RISK-ASSESSMENT; BIG DATA
AB Climate sciences foresee a future where extreme weather events could happen with increased frequency and strength, which would in turn increase risks of floods (i.e. the main source of losses in the world). The Mediterranean basin is considered a hot spot in terms of climate vulnerability and risk. The expected impacts of those events are exacerbated by land-use change and, in particular, by urban growth which increases soil sealing and, hence, water runoff. The ultimate consequence would be an increase of fatalities and injuries, but also of economic losses in urban areas, commercial and productive sites, infrastructures and agriculture. Flood damages have different magnitudes depending on the economic value of the exposed assets and on level of physical contact with the hazard. This work aims at proposing a methodology, easily customizable by experts' elicitation, able to quantify and map the social component of vulnerability through the integration of earth observation (EO) and census data with the aim of allowing for a multi-temporal spatial assessment. Firstly, data on employment, properties and education are used for assessing the adaptive capacity of the society to increase resilience to adverse events, whereas, secondly, coping capacity, i.e. the capacities to deal with events during their manifestation, is mapped by aggregating demographic and socio-economic data, urban growth analysis and memory on past events. Thirdly, the physical dimension of exposed assets (susceptibility) is assessed by combining building properties acquired by census data and land-surface characteristics derived from EO data. Finally, the three components (i.e. adaptive and coping capacity and susceptibility) are aggregated for calculating the dynamic flood vulnerability index (FVI). The approach has been applied to Northeast Italy, a region frequently hit by floods, which has experienced a significant urban and economic development in the past decades, thus making the dynamic study of FVI particularly relevant. The analysis has been carried out from 1991 to 2016 at a 5-year steps, showing how the integration of different data sources allows to produce a dynamic assessment of vulnerability, which can be very relevant for planning in support of climate change adaptation and disaster risk reduction.
C1 [Cian, Fabio; Giupponi, Carlo] Ca Foscari Univ Venice, Dept Econ, Fondamenta San Giobbe 873, I-30121 Venice, Italy.
   [Marconcini, Mattia] German Aerosp Ctr DLR, Muenchener Str 20, D-82234 Wessling, Germany.
C3 Universita Ca Foscari Venezia; Helmholtz Association; German Aerospace
   Centre (DLR)
RP Cian, F (corresponding author), Ca Foscari Univ Venice, Dept Econ, Fondamenta San Giobbe 873, I-30121 Venice, Italy.
EM fabio.cian@unive.it; cgiupponi@unive.it; mattia.marconcini@dlr.de
FU Universita Ca' Foscari Venezia
FX Open Access funding provided by Universita Ca' Foscari Venezia.
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P330, DOI [10.1038/nclimate1751, 10.1038/NCLIMATE1751]
   Animesh, 2013, SERRA METHODOLOGY
   [Anonymous], 2004, P 13 WORLD C EARTHQ
   Apel H, 2009, NAT HAZARDS, V49, P79, DOI 10.1007/s11069-008-9277-8
   Balbi, 2013, INTEGRATED ASSESSMEN, DOI 10.2139/ssrn.2233312
   BALDASSARRE D, 2015, WATER RESOUR RES
   Birkmann J., 2006, Measuring Vulnerability to Natural Hazards-Towards Disaster Resilient Societies, V01, P9
   BLOSCHL G, 2019, NATURE
   Bojovic D, 2020, J ENVIRON PLANN MAN, V63, P818, DOI 10.1080/09640568.2019.1614435
   Boko M, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P433
   Borden KA, 2007, J HOMEL SECUR EMERG, V4, DOI 10.2202/1547-7355.1279
   Boruff BJ., 2010, GEOGR REV, DOI 10.1111/j.1931-0846.2007.tb00278.x
   Burton C., 2008, Natural Hazards Review, V9, P136, DOI 10.1061/(ASCE)1527-6988(2008)9:3(136)
   Cardona OD., 2005, SCIENCE, DOI 10.1126/science.284.5416.939
   Carney D., 1998, SUSTAINABLE LIVELIHO
   CECCATO L, 2011, ENVIRON SCI POLICY
   Chakraborty J., 2005, Natural Hazards Review
   CIAN F, 2018, REMOTE SENS ENVIRON
   CIAN F, 2018, NAT HAZARD EARTH SYS
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Cutter SL, 2000, ANN ASSOC AM GEOGR, V90, P713, DOI 10.1111/0004-5608.00219
   De Sherbinin AM., 2014, SPAT ANAL VULNERABIL, DOI 10.3990/1.9789036538091
   Di Baldassarre G, 2013, HYDROL EARTH SYST SC, V17, P3235, DOI 10.5194/hess-17-3235-2013
   Ebert A, 2009, NAT HAZARDS, V48, P275, DOI 10.1007/s11069-008-9264-0
   Esch T, 2014, APPL GEOGR, V55, P212, DOI 10.1016/j.apgeog.2014.09.009
   Esch T., 2019, WORLD BANK LAND POV
   Fekete A, 2009, NAT HAZARD EARTH SYS, V9, P393, DOI 10.5194/nhess-9-393-2009
   FINCH C, 2010, POPUL ENVIRON
   Fussel H-M., 2010, WORLD DEV REP, DOI 10.1016/j.gloenvcha.2010.07.009
   Gain AK, 2015, NAT HAZARDS, V79, P1499, DOI 10.1007/s11069-015-1911-7
   GEISS C, 2016, IEEE J SELECT TOPICS
   Ghaffarian S, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10111760
   Giupponi C., 2013, The KULTURisk Methodological Framework
   Giupponi C, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/12/123002
   Guo HD, 2015, ADV CLIM CHANG RES, V6, P108, DOI 10.1016/j.accre.2015.09.007
   Guo HD, 2014, CHINESE SCI BULL, V59, P5066, DOI 10.1007/s11434-014-0645-3
   Guzzetti F, 2004, NAT HAZARD EARTH SYS, V4, P213, DOI 10.5194/nhess-4-213-2004
   Hu SS, 2017, NAT HAZARDS, V87, P1525, DOI 10.1007/s11069-017-2828-0
   Johnson CL, 2005, INT J WATER RESOUR D, V21, P561, DOI 10.1080/07900620500258133
   Johnson R. A., 2007, Applied Multivariate Statistical Analysis, VSixth edition
   Kates RW, 2006, P NATL ACAD SCI USA, V103, P14653, DOI 10.1073/pnas.0605726103
   KUMAGAI K, 2012, INT ARCH PHOTOGRAMM
   Kundzewicz Z.W., 2014, HYDROLOG SCI J
   Ludy J, 2012, NAT HAZARDS, V61, P829, DOI 10.1007/s11069-011-0072-6
   Marconcini M, 2015, 2015 JOINT URBAN REMOTE SENSING EVENT (JURSE)
   Marconcini M, 2013, INT GEOSCI REMOTE SE, P4273, DOI 10.1109/IGARSS.2013.6723778
   MASOZERA M, 2007, ECOL ECON
   Mechler R, 2015, CLIMATIC CHANGE, V133, P23, DOI 10.1007/s10584-014-1141-0
   Metz B., 2001, CLIMATE CHANGE 2001
   Montz B. E., 2008, Natural Hazards Review, V9, P150, DOI 10.1061/(ASCE)1527-6988(2008)9:3(150)
   MULLER A, 2013, NAT HAZARDS
   O'Brien K, 2007, CLIM POLICY, V7, P73, DOI 10.1080/14693062.2007.9685639
   Penning-Rowsell E, 2006, GLOBAL ENVIRON CHANG, V16, P323, DOI 10.1016/j.gloenvcha.2006.01.006
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Richards J.A., 2012, Remote Sensing Digital Image Analysis: An Introduction
   Roder G, 2017, WEATHER CLIM SOC, V9, P717, DOI 10.1175/WCAS-D-16-0090.1
   Schwarz B, 2018, EARTH OBSERVATION OP
   SLATER L, 2015, GEOPHYS RES LETT
   SOFIA G, 2017, SCI REP-UK
   TAUBENBOCK H, 2009, REMOTE SENS ENV MONI
   The UN Office for Disaster Risk & Centre for Research on the Epidemiology of Disasters, 2015, HUM COST WEATH REL D
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   USAID, 2014, SPAT CLIM CHANG VULN
   VIERO D, 2019, SCI TOTAL ENVIRON
   Viero DP, 2013, ADV WATER RESOUR, V59, P82, DOI 10.1016/j.advwatres.2013.05.011
   Wind HG, 1999, WATER RESOUR RES, V35, P3459, DOI 10.1029/1999WR900192
   WINSEMIUS H, 2016, NAT CLIM CHANGE
   Winsemius HC, 2013, HYDROL EARTH SYST SC, V17, P1871, DOI 10.5194/hess-17-1871-2013
   WOLTERS M, 2015, J COAST CONSERV
   WOOD N, 2010, NAT HAZARDS
   YAGER R, 1988, IEEE T SYST MAN CYB
   Yarnal, 2006, MITIG ADAPT STRAT GL, DOI 10.1007/s11027-006-0265-6
NR 72
TC 13
Z9 13
U1 2
U2 21
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0921-030X
EI 1573-0840
J9 NAT HAZARDS
JI Nat. Hazards
PD APR
PY 2021
VL 106
IS 3
BP 2163
EP 2184
DI 10.1007/s11069-021-04535-w
EA FEB 2021
PG 22
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA RM3RF
UT WOS:000614656400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Haskett, JD
   Simane, B
   Smith, C
AF Haskett, Jonathan D.
   Simane, Belay
   Smith, Caitlin
TI Energy and Climate Change Mitigation Benefits of <i>Faidherbia
   albida</i> Agroforestry in Ethiopia
SO FRONTIERS IN ENVIRONMENTAL SCIENCE
LA English
DT Article
DE food energy water nexus; climate change adaptation and mitigation;
   Faidherbia albida; agroforestry; Ethiopia; evergreen agriculture;
   nitrogen fertilization; avoided emissions
ID FOOD SECURITY; ACACIA-ALBIDA; YIELD; SYSTEMS; TREES
AB Agriculture must raise productivity while addressing climate change in order to ensure the food security of a growing population. Adding fossil fuel energy to the agricultural system can increase productivity through the use of manufactured fertilizer but creates greenhouse gas emissions. This study quantifies an alternative in which energy is added to the agricultural system through a substitution of solar energy for fossil fuel energy by the tree species Faidherbia albida. This substitution can be quantified as an avoided emission of greenhouse gas, a climate benefit. F. albida trees have unusual phenology, leafing out during the dry season and shedding leaves in the rainy season. In agroforestry systems, F. albida adds nutrients and organic matter to the soil through leaf drop, and these are beneficial to the crop growing under the tree canopy. Dormant during the cropping season, they do not compete for light, water or nutrients, and contribute nitrogen to the soil under their canopy. This nitrogen benefit is analyzed in relation to an equivalent quantity of urea fertilizer. This is a substitution of solar energy that the trees use to obtain nitrogen from the atmosphere, for the fossil fuels used in the manufacture and transport of urea fertilizer. This energy contribution by the tree, within the food energy and water system, enhances the food production, and resilience of the system, as soil organic matter increases available water for the plants. This energy contribution to the Ethiopian farming system is estimated as 3.48 GJ ha(-1) year(-1), based on the nitrogen contribution. Greenhouse gas emissions are avoided by the substitution of solar energy for fossil fuel energy, a climate change mitigation benefit estimated as 0.116 tons CO2 ha(-1) year(-1). This mitigation is fundamentally different from sequestration of carbon in biomass or soil organic matter. It is a permanently avoided emission of carbon dioxide into the atmosphere, associated with a particular cropping year, and is not reversible, unlike carbon stored in biomass or soil organic matter that could return to the atmosphere. The potential extent of F. albida agroforestry is substantial and its potential climate change mitigation benefits are great.
C1 [Haskett, Jonathan D.; Smith, Caitlin] Johns Hopkins Univ, Sch Adv Int Studies, Energy Resources & Environm Program, Washington, DC USA.
   [Simane, Belay] Addis Ababa Univ, Coll Dev Studies, Ctr Environm & Dev, Addis Ababa, Ethiopia.
C3 Johns Hopkins University; Addis Ababa University
RP Haskett, JD (corresponding author), Johns Hopkins Univ, Sch Adv Int Studies, Energy Resources & Environm Program, Washington, DC USA.
EM Jhaskett314@gmail.com
RI Simane, Belay/KII-9723-2024
OI Haskett, Jonathan/0000-0003-1444-7789
FU National Science Foundation [BCS-1639214]
FX This research was support by National Science Foundation award
   BCS-1639214.
CR Abdulkadi B., 2017, CIAT PUBLICATION, V443, P2
   [Anonymous], 2015, INTENDED NATL DETERM
   [Anonymous], 2003, FAIDHERBIA ALBIDA MO
   [Anonymous], WORLDS WATER
   [Anonymous], 2005, GLOBAL CHANGE EARTH, DOI [DOI 10.1007/B137870, 10.1007/b137870]
   [Anonymous], 1999, AGROFORESTRY PARKLAN
   [Anonymous], 2009, TRANSP EN CO2 MOV SU, DOI DOI 10.1787/9789264073173-EN
   [Anonymous], 2010, IFPRI DISCUSSION PAP
   [Anonymous], 2005, FOOD AGR ORG
   Bakker C, 2018, AGR SYST, V164, P165, DOI 10.1016/j.agsy.2018.04.005
   Beedy TL, 2016, AGROFOREST SYST, V90, P1061, DOI 10.1007/s10457-015-9883-x
   CTFT (Centre Technique Forestier Tropical), 1989, FAIDH ALB DEL A CHEV
   Dancette C., 1969, Sols Africains, V14, P143
   de Sousa K, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-45491-7
   Deutsche Bahn, 2017, TABL SPEC PRIM EN CO
   Edwards R., 2004, Well-to-wheels Analysis of Future Automotive Fuels and Powertrains in the European Context, Institute for Environment and 44 Sustainability of the European Commission's Joint Research Centre JRC/IES
   Fertillizers Europe, 2000, BEST AV TECHN POLL P
   Foley JA, 2011, NATURE, V478, P337, DOI 10.1038/nature10452
   Garrity DP, 2010, FOOD SECUR, V2, P197, DOI 10.1007/s12571-010-0070-7
   Hadgu K.M., 2011, INT J AGR SCI, V1, P6
   Hadgu KM, 2009, FOOD SECUR, V1, P337, DOI 10.1007/s12571-009-0030-2
   Haileslassie A, 2005, AGR ECOSYST ENVIRON, V108, P1, DOI 10.1016/j.agee.2004.12.010
   Hailu BT, 2015, APPL GEOGR, V62, P357, DOI 10.1016/j.apgeog.2015.05.013
   Harrison A., 2015, SOURCE CITED PREPARA
   IFDC (International Fertilizer Development Centre), 2012, ETH FERT ASS
   KAMARA CS, 1992, AGROFOREST SYST, V18, P17, DOI 10.1007/BF00114814
   Kandji SerigneTacko., 2006, Climate Change and Variability in the Sahel Region: Impacts and Adaptation Strategies in the Agricultural Sector
   Kermeli K., 2017, ENERGY EFFICIENCY CO
   Kho RM, 2001, AGROFOREST SYST, V52, P219, DOI 10.1023/A:1011820412140
   Kindt R, 2018, ENVIRON MODELL SOFTW, V100, P136, DOI 10.1016/j.envsoft.2017.11.009
   Leck H, 2015, GEOGR COMPASS, V9, P445, DOI 10.1111/gec3.12222
   Marenya PP, 2009, AM J AGR ECON, V91, P991, DOI 10.1111/j.1467-8276.2009.01313.x
   McKinnon A C., 2010, Measuring and managing CO2 emissions in European chemical transport
   National Research Council, 2007, COAL RES DEV SUPP NA
   Patzek TW, 2004, CRIT REV PLANT SCI, V23, P519, DOI 10.1080/07352680490886905
   Pieri C. J. M. G., 1992, FERTILITY SOILS FUTU, P216
   Pimentel D, 2009, ENERGIES, V2, P1, DOI 10.3390/en20100001
   Reij C, 2009, REGREENING SAHEL FAR
   RHOADES C, 1995, AGROFOREST SYST, V29, P133, DOI 10.1007/BF00704882
   SAKA AR, 1994, FOREST ECOL MANAG, V64, P217, DOI 10.1016/0378-1127(94)90296-8
   Shitumbanuma V., 2012, ANAL CROP TRIALS FAI
   Sida TS, 2018, AGR FOREST METEOROL, V248, P339, DOI 10.1016/j.agrformet.2017.10.013
   Sileshi GW, 2016, J ARID ENVIRON, V132, P1, DOI 10.1016/j.jaridenv.2016.03.002
   Simonsen M, 2011, ENERGIES, V4, P324, DOI 10.3390/en4020324
   Taddese G, 2001, ENVIRON MANAGE, V27, P815, DOI 10.1007/s002670010190
   Tennekes M, 2018, J STAT SOFTW, V84, P1, DOI 10.18637/jss.v084.i06
   Umar B. B., 2013, African Journal of Agricultural Research, V8, P173
   Victor DG, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P111
   Wahl CT, 2013, INT J AGR SUSTAIN, V11, P382, DOI 10.1080/14735903.2013.812607
   Warren G. F., 1998, Weed Technology, V12, P752
   Yengwe J, 2018, EUR J AGRON, V99, P148, DOI 10.1016/j.eja.2018.07.004
   Yengwe J, 2018, AGROFOREST SYST, V92, P349, DOI 10.1007/s10457-016-0063-4
NR 52
TC 7
Z9 7
U1 1
U2 18
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-665X
J9 FRONT ENV SCI-SWITZ
JI Front. Environ. Sci.
PD NOV 1
PY 2019
VL 7
AR 146
DI 10.3389/fenvs.2019.00146
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA LR6WD
UT WOS:000535831900001
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Andrew, ME
   Warrener, H
AF Andrew, Margaret E.
   Warrener, Haylea
TI Detecting microrefugia in semi-arid landscapes from remotely sensed
   vegetation dynamics
SO REMOTE SENSING OF ENVIRONMENT
LA English
DT Article
DE Biodiversity; Climate change adaptation; Granite outcrops; Hydrologic
   refugia; Landsat time series; Southwestern Australia
ID LANDSAT TIME-SERIES; INCORPORATING CLIMATE-CHANGE; SPECIES DISTRIBUTION
   MODELS; FOREST DISTURBANCE; SURFACE-TEMPERATURE; AIR TEMPERATURES;
   FINE-GRAIN; REFUGIA; CONSERVATION; PLANT
AB Microrefugia are sites with stable, high quality habitat within landscapes characterized by dynamic environmental conditions driven by climate variability or ecological disturbances. There is considerable interest in the potential of microrefugia to provide climate change resilience to landscapes and to biodiversity conservation. Although attractive conceptually, there is yet little guidance on how to identify climate change microrefugia in order to study and protect them, and the data required to do so are often lacking. This study demonstrates how time series remote sensing, using all available Landsat images of a study area, can be used to directly detect microrefugia maintained by water subsidies in a semi-arid landscape in southwest Western Australia.
   Microrefugia were identified as pixels with abundant vegetation and consistent vegetation dynamics between wet and dry years. At every pixel, a harmonic model was fit to the intra-annual time series of vegetation index values compiled from the wettest years in the Landsat-5 Thematic Mapper (TM) archive. This model was then used to predict the phenological cycle of the driest years at that pixel. Candidate microrefugia were defined to be those pixels with (1) high vegetation activity in dry years and (2) highly predictable phenologies that are consistent regardless of the weather conditions experienced in a given year. Spatial relationships between candidate microrefugia and landscape features associated with elevated moisture availability (thought to drive climate microrefugia in these semi-arid landscapes) were assessed. The candidate microrefugia show great promise. Evaluations against high-resolution imagery reveal that candidate microrefugia most likely buffer against drought, although refugia from other disturbances, especially fire, were also detected. In contrast, spatial proxies of the physical features expected to maintain microrefugia failed to adequately represent the distribution of microrefugia across the landscape, likely due to data quality and the heterogeneity of microrefugia. Direct detection of microrefugia with Earth observation data is a promising solution in data limited regions. Landsat time series analyses are well suited to this application as they can characterize both the habitat quality and stability aspects of microrefugia.
C1 [Andrew, Margaret E.; Warrener, Haylea] Murdoch Univ, Sch Vet & Life Sci, Environm & Conservat Sci, Murdoch, WA, Australia.
C3 Murdoch University
RP Andrew, ME (corresponding author), Murdoch Univ, Sch Vet & Life Sci, 90 South St, Murdoch, WA 6150, Australia.
EM m.andrew@murdoch.edu.au
OI Andrew, Margaret/0000-0003-3285-3684
FU Gunduwa Regional Conservation Association
FX This research was funded by a Gunduwa Regional Conservation Association
   grant to Conservation Council of Western Australia Citizen Science
   Program and MEA, 'Do climate refugia exist on the conservation
   stations?' Special thanks are owed to collaborator Nic Dunlop (CCWA) for
   contributions throughout the project and to Bush Heritage for
   encouraging this research and field surveys at Charles Darwin Reserve.
CR ABBOTT I, 1984, Journal of the Royal Society of Western Australia, V66, P107
   Ackerly DD, 2010, DIVERS DISTRIB, V16, P476, DOI 10.1111/j.1472-4642.2010.00654.x
   Ahmed OS, 2017, REMOTE SENS LETT, V8, P29, DOI 10.1080/2150704X.2016.1233371
   Alibegovic G, 2015, J SPAT SCI, V60, P37, DOI 10.1080/14498596.2014.952253
   [Anonymous], 1997, Journal of the Royal Society of Western Australia
   Ashcroft MB, 2013, AGR FOREST METEOROL, V176, P77, DOI 10.1016/j.agrformet.2013.03.008
   Ashcroft MB, 2012, GLOBAL CHANGE BIOL, V18, P1866, DOI 10.1111/j.1365-2486.2012.02661.x
   Ashcroft MB, 2010, J BIOGEOGR, V37, P1407, DOI 10.1111/j.1365-2699.2010.02300.x
   Banskota A, 2014, CAN J REMOTE SENS, V40, P362, DOI 10.1080/07038992.2014.987376
   Barron OV, 2014, HYDROL PROCESS, V28, P372, DOI 10.1002/hyp.9609
   Bengtsson J, 2003, AMBIO, V32, P389, DOI 10.1639/0044-7447(2003)032[0389:RRADL]2.0.CO;2
   Bindon P., 1997, J R SOC WEST AUST, V80, P173
   Birks HJB, 2008, PLANT ECOL DIVERS, V1, P147, DOI 10.1080/17550870802349146
   Byrne M, 2008, MOL ECOL, V17, P4398, DOI 10.1111/j.1365-294X.2008.03899.x
   Byrne M, 2008, QUATERNARY SCI REV, V27, P2576, DOI 10.1016/j.quascirev.2008.08.032
   Carroll C, 2017, GLOBAL CHANGE BIOL, V23, P4508, DOI 10.1111/gcb.13679
   Carroll C, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0140486
   Céré J, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00012.1
   Cohen WB, 2016, FOREST ECOL MANAG, V360, P242, DOI 10.1016/j.foreco.2015.10.042
   Cohen WB, 2004, BIOSCIENCE, V54, P535, DOI 10.1641/0006-3568(2004)054[0535:LRIEAO]2.0.CO;2
   Contreras S, 2011, J HYDROL, V397, P10, DOI 10.1016/j.jhydrol.2010.11.014
   Corlett RT, 2013, TRENDS ECOL EVOL, V28, P482, DOI 10.1016/j.tree.2013.04.003
   Davis FW, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1573
   Davis J, 2013, GLOBAL CHANGE BIOL, V19, P1970, DOI 10.1111/gcb.12203
   Deel LN, 2012, REMOTE SENS ENVIRON, V118, P40, DOI 10.1016/j.rse.2011.10.026
   Dickman CR, 2011, J MAMMAL, V92, P1193, DOI 10.1644/10-MAMM-S-329.1
   Dingman J R., 2013, ECOL PROCESS, V2, P30, DOI DOI 10.1186/2192-1709-2-30
   Dobrowski SZ, 2011, GLOBAL CHANGE BIOL, V17, P1022, DOI 10.1111/j.1365-2486.2010.02263.x
   Fox E., 2016, Birds of the Great Western Woodland: Report for the Nature Conservancy
   Franklin J, 2013, GLOBAL CHANGE BIOL, V19, P473, DOI 10.1111/gcb.12051
   Frey SJK, 2016, SCI ADV, V2, DOI 10.1126/sciadv.1501392
   Gavin DG, 2014, NEW PHYTOL, V204, P37, DOI 10.1111/nph.12929
   Geoscience Australia, 2006, GEODATA TOPO 250K SE
   Gould SF, 2015, LANDSCAPE ECOL, V30, P141, DOI 10.1007/s10980-014-0112-1
   Griffin G. F., 1995, REFUGIA BIOL DIVERSI
   Groves CR, 2012, BIODIVERS CONSERV, V21, P1651, DOI 10.1007/s10531-012-0269-3
   Hamann A, 2015, GLOBAL CHANGE BIOL, V21, P997, DOI 10.1111/gcb.12736
   Hampe A, 2011, ANNU REV ECOL EVOL S, V42, P313, DOI 10.1146/annurev-ecolsys-102710-145015
   Hannah L, 2014, TRENDS ECOL EVOL, V29, P390, DOI 10.1016/j.tree.2014.04.006
   HARDISKY MA, 1983, PHOTOGRAMM ENG REM S, V49, P77
   Ji L, 2011, INT J REMOTE SENS, V32, P6901, DOI 10.1080/01431161.2010.510811
   Jones KR, 2016, BIOL CONSERV, V194, P121, DOI 10.1016/j.biocon.2015.12.008
   Kennedy RE, 2007, REMOTE SENS ENVIRON, V110, P370, DOI 10.1016/j.rse.2007.03.010
   Kennedy RE, 2014, FRONT ECOL ENVIRON, V12, P339, DOI 10.1890/130066
   Kennedy RE, 2010, REMOTE SENS ENVIRON, V114, P2897, DOI 10.1016/j.rse.2010.07.008
   Keppel G, 2015, FRONT ECOL ENVIRON, V13, P106, DOI 10.1890/140055
   Keppel G, 2012, GLOBAL ECOL BIOGEOGR, V21, P393, DOI 10.1111/j.1466-8238.2011.00686.x
   Lawrence RL, 1999, REMOTE SENS ENVIRON, V67, P309, DOI 10.1016/S0034-4257(98)00092-3
   Lehmann EA, 2013, INT J APPL EARTH OBS, V21, P453, DOI 10.1016/j.jag.2012.06.005
   Lenoir J, 2017, ECOGRAPHY, V40, DOI 10.1111/ecog.02788
   Mackey B, 2012, ECOL APPL, V22, P1852, DOI 10.1890/11-1479.1
   Masek JG, 2006, IEEE GEOSCI REMOTE S, V3, P68, DOI 10.1109/LGRS.2005.857030
   McCullough IM, 2016, LANDSCAPE ECOL, V31, P1063, DOI 10.1007/s10980-015-0318-x
   Mclaughlin BC, 2017, GLOBAL CHANGE BIOL, V23, P2941, DOI 10.1111/gcb.13629
   Meineri E, 2017, ECOGRAPHY, V40, P1003, DOI 10.1111/ecog.02494
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   Morton SR, 2011, J ARID ENVIRON, V75, P313, DOI 10.1016/j.jaridenv.2010.11.001
   Morton S.R., 1995, REFUGIA BIOL DIVERSI
   O'Grady AP, 2011, HYDROL EARTH SYST SC, V15, P3731, DOI 10.5194/hess-15-3731-2011
   Ouarmim S, 2014, J QUATERNARY SCI, V29, P123, DOI 10.1002/jqs.2685
   Patsiou TS, 2014, GLOBAL CHANGE BIOL, V20, P2286, DOI 10.1111/gcb.12515
   Pavey CR, 2014, J MAMMAL, V95, P615, DOI 10.1644/13-MAMM-A-183
   Pepin NC, 2016, J GEOPHYS RES-ATMOS, V121, P9998, DOI 10.1002/2016JD025497
   Pettorelli N, 2014, J APPL ECOL, V51, P839, DOI 10.1111/1365-2664.12261
   Potter KA, 2013, GLOBAL CHANGE BIOL, V19, P2932, DOI [10.1111/gcb.12257, 10.1111/]
   Rabus B, 2003, ISPRS J PHOTOGRAMM, V57, P241, DOI 10.1016/S0924-2716(02)00124-7
   Randin CF, 2009, GLOBAL CHANGE BIOL, V15, P1557, DOI 10.1111/j.1365-2486.2008.01766.x
   Reside AE, 2014, AUSTRAL ECOL, V39, P887, DOI 10.1111/aec.12146
   Roy DP, 2010, REMOTE SENS ENVIRON, V114, P35, DOI 10.1016/j.rse.2009.08.011
   Rull V, 2009, J BIOGEOGR, V36, P481, DOI 10.1111/j.1365-2699.2008.02023.x
   Schut AGT, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0082778
   Shepherd D. P., 2003, MILESTONE 6 REPORT
   Slavich E, 2014, DIVERS DISTRIB, V20, P952, DOI 10.1111/ddi.12216
   Stewart JR, 2010, P ROY SOC B-BIOL SCI, V277, P661, DOI 10.1098/rspb.2009.1272
   Storey EA, 2016, REMOTE SENS ENVIRON, V183, P53, DOI 10.1016/j.rse.2016.05.018
   TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127, DOI 10.1016/0034-4257(79)90013-0
   Turner W, 2015, BIOL CONSERV, V182, P173, DOI 10.1016/j.biocon.2014.11.048
   Vogelmann JE, 2012, REMOTE SENS ENVIRON, V122, P92, DOI 10.1016/j.rse.2011.06.027
   Wilkin KM, 2016, FORESTS, V7, DOI 10.3390/f7040077
   Wilson EH, 2002, REMOTE SENS ENVIRON, V80, P385, DOI 10.1016/S0034-4257(01)00318-2
   Withers P. C., 2000, Journal of the Royal Society of Western Australia, V83, P103
   Wulder MA, 2012, REMOTE SENS ENVIRON, V122, P2, DOI 10.1016/j.rse.2012.01.010
   Zhu Z, 2012, REMOTE SENS ENVIRON, V122, P75, DOI 10.1016/j.rse.2011.10.030
   Zhu Z, 2012, REMOTE SENS ENVIRON, V118, P83, DOI 10.1016/j.rse.2011.10.028
NR 84
TC 13
Z9 14
U1 1
U2 43
PU ELSEVIER SCIENCE INC
PI NEW YORK
PA STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA
SN 0034-4257
EI 1879-0704
J9 REMOTE SENS ENVIRON
JI Remote Sens. Environ.
PD OCT
PY 2017
VL 200
BP 114
EP 124
DI 10.1016/j.rse.2017.08.005
PG 11
WC Environmental Sciences; Remote Sensing; Imaging Science & Photographic
   Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Remote Sensing; Imaging Science &
   Photographic Technology
GA FJ3CI
UT WOS:000412607600009
DA 2025-01-10
ER

PT J
AU Sapkota, TB
   Jat, ML
   Shankar, V
   Singh, LK
   Rai, M
   Grewal, MS
   Stirling, CM
AF Sapkota, Tek B.
   Jat, M. L.
   Shankar, Vivek
   Singh, Love K.
   Rai, Munmun
   Grewal, M. S.
   Stirling, Clare M.
TI Tillage, residue and nitrogen management effects on methane and nitrous
   oxide emission from rice-wheat system of Indian Northwest Indo-Gangetic
   Plains
SO JOURNAL OF INTEGRATIVE ENVIRONMENTAL SCIENCES
LA English
DT Article
DE Greenhouse gas; tillage and residue management; Indo-Gangetic Plains
ID GREENHOUSE-GAS EMISSIONS; CONSERVATION AGRICULTURE; SOIL; ROTATION;
   CARBON
AB Zero-tillage, residue management and precision nutrient management techniques are being promoted in the rice-wheat (RW) production system of Indo-Gangetic Plains (IGPs) to enhance climate change adaptation and increase food production. These management practices may also influence greenhouse gas emissions through their effects on various soil processes such as oxidation-reduction and nitrification-denitrification. We measured soil fluxes of CH4 and N2O in RW system under three tillage and residue management systems layered with four nitrogen (N) management treatments. The tillage and residue management systems comprised: conventional tillage (CT), zero-tillage without residue retention (ZT-R) and ZT with full residue retention (ZT+R) for both the crops. The four N management treatments for rice were: (a) basmati cultivar with recommended dose of nitrogen (RDN) applied in three splits, (b) basmati cultivar with 80% RDN as basal dose followed by Green Seeker (GS) guided N application, (c) hybrid cultivar with RDN applied in three splits and (d) hybrid with 80% RDN as basal dose followed by GS guided N application. The four N management treatments for wheat comprised combinations of RDN with and without relay green gram (GG), and 80% of RDN as basal dose followed by GS guided N application with and without relay GG. We employed the static chamber method to collect gas samples from the experimental plots which were subsequently analysed using gas chromatograph. Significant CH4 emissions were detected only in the CT rice system during the initial phase of continuous flooding, irrespective of N management strategies. N fertilization management affected the pattern of N2O emission with higher emission rates during crop establishment phase under 80% RDN as basal followed by GS guided N application than conventional RDN. In case of wheat, 80% RDN as basal followed by GS guided N application also induced higher cumulative N2O emissions than applying RDN at three regular splits. In rice, ZT-based RW system emitted more N2O than CT-based system. Overall ZT-based RW system reduced CH4 emission but this benefit is counterbalanced by higher N2O production compared to CT-based RW system.
C1 [Sapkota, Tek B.; Jat, M. L.; Singh, Love K.; Rai, Munmun] Int Maize & Wheat Improvement Ctr CIMMYT, New Delhi, India.
   [Shankar, Vivek; Grewal, M. S.] Chaudhary Charan Singh Haryana Agr Univ, Dept Agron, Hisar, Haryana, India.
   [Stirling, Clare M.] Int Maize & Wheat Improvement Ctr CIMMYT, Ynys Mon, Wales.
C3 CGIAR; International Maize & Wheat Improvement Center (CIMMYT); CCS
   Haryana Agricultural University
RP Jat, ML (corresponding author), Int Maize & Wheat Improvement Ctr CIMMYT, New Delhi, India.
EM m.jat@cgiar.org
RI Jat, ML/O-2824-2019; Sapkota, Tek/AAC-3155-2020
OI Sapkota, Tek/0000-0001-5311-0586; Pandey, Alok Kumar/0000-0001-5604-3243
FU Bayer CropScience; CGIAR research programme on climate change
   agriculture and food security (CCAFS)
FX This work was supported by Bayer CropScience and CGIAR research
   programme on climate change agriculture and food security (CCAFS).
CR [Anonymous], CLIM CHANG MIT CONTR
   [Anonymous], 2010, India: Greenhouse gas emissions 2007
   Aryal JP, 2015, EXP AGR, V51, P1, DOI 10.1017/S001447971400012X
   Bhatia A, 2011, AGR ECOSYST ENVIRON, V144, P21, DOI 10.1016/j.agee.2011.07.003
   Bijay-Singh, 2011, AGRON SUSTAIN DEV, V31, P589, DOI 10.1007/s13593-011-0005-5
   Bolinder MA, 2007, AGR ECOSYST ENVIRON, V118, P29, DOI 10.1016/j.agee.2006.05.013
   Dendooven L, 2012, SCI TOTAL ENVIRON, V431, P237, DOI 10.1016/j.scitotenv.2012.05.029
   Gathala MK, 2013, AGR ECOSYST ENVIRON, V177, P85, DOI 10.1016/j.agee.2013.06.002
   Gathala MK, 2011, SOIL SCI SOC AM J, V75, P1851, DOI 10.2136/sssaj2010.0362
   Gathala MK, 2011, AGRON J, V103, P961, DOI 10.2134/agronj2010.0394
   Jantalia CP, 2008, NUTR CYCL AGROECOSYS, V82, P161, DOI 10.1007/s10705-008-9178-y
   Jat ML, 2009, SOIL TILL RES, V105, P112, DOI 10.1016/j.still.2009.06.003
   Jat ML, 2015, NATL DIALOGUE EFFICI
   Jat RK, 2014, FIELD CROP RES, V164, P199, DOI 10.1016/j.fcr.2014.04.015
   Johnson JMF, 2006, AGRON J, V98, P622, DOI 10.2134/agronj2005.0179
   Kapil, 2012, OPERATIONAL MANUAL M
   Kumar V, 2011, ADV AGRON, V111, P297, DOI 10.1016/B978-0-12-387689-8.00001-1
   Kumar V, 2013, FIELD CROP RES, V142, P1, DOI 10.1016/j.fcr.2012.11.013
   Ladha J.K., 2009, Integrated Crop and Resource Management in the Rice-Wheat System of South Asia, P69
   Li CS, 2011, ACS SYM SER, V1072, P299
   Malla G, 2005, CHEMOSPHERE, V58, P141, DOI 10.1016/j.chemosphere.2004.09.003
   MASSCHELEYN PH, 1993, CHEMOSPHERE, V26, P251, DOI 10.1016/0045-6535(93)90426-6
   Neue HU, 1997, NUTR CYCL AGROECOSYS, V49, P111, DOI 10.1023/A:1009714526204
   Pathak H, 2003, AGR ECOSYST ENVIRON, V97, P309, DOI 10.1016/S0167-8809(03)00033-1
   Saharawat Y.S., 2011, J SOIL SCI ENV MANAG, V2, P9, DOI DOI 10.1002/GHG.27
   Salam MU, 1997, AGRON J, V89, P653, DOI 10.2134/agronj1997.00021962008900040018x
   Sapkota TB, 2014, FIELD CROP RES, V155, P233, DOI 10.1016/j.fcr.2013.09.001
   Sidhu HS, 2015, FIELD CROP RES, V184, P201, DOI 10.1016/j.fcr.2015.07.025
   Steinbach HS, 2006, J ENVIRON QUAL, V35, P3, DOI 10.2134/jeq2005.0050
   Ussiri DAN, 2009, SOIL TILL RES, V104, P247, DOI 10.1016/j.still.2009.03.001
NR 30
TC 36
Z9 39
U1 10
U2 58
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1943-815X
EI 1943-8168
J9 J INTEGR ENVIRON SCI
JI J. Integr. Environ. Sci.
PD DEC 18
PY 2015
VL 12
SU 1
SI SI
BP 31
EP 46
DI 10.1080/1943815X.2015.1110181
PG 16
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA DF9OL
UT WOS:000371690600004
OA Bronze
DA 2025-01-10
ER

PT J
AU Jim, CY
AF Jim, C. Y.
TI Thermal performance of climber greenwalls: Effects of solar irradiance
   and orientation
SO APPLIED ENERGY
LA English
DT Article
DE Greenwall passive cooling; Threshold solar irradiance; Airgap thermal
   insulation; Solar-barrier function; Air-barrier function; Bidirectional
   cooling benefit
ID ENERGY PERFORMANCE; LIVING WALLS; TEMPERATURE; MANCHESTER; BUILDINGS;
   FACADES; SYSTEMS; AREAS; ROOFS
AB Thermal performance of greenwalls, a critical and common concern, is regulated by solar irradiance vis-a-vis orientation and shading. A field experiment was conducted in humid-tropical Hong Kong to address the research question under typical summer-weather scenarios: sunny, cloudy and rainy. On a large circular concrete tank, climber-greenwall experimental plots were established with duplication in four cardinal compass directions. Air and infrared-radiometer surface temperature sensors monitored at different greenwall positions: ambient-air (control), bare-concrete-surface (control), vegetation-surface, behind-mesh-airgap, and behind-mesh-concrete surface. Pyranometers were installed vertically at four orientations and horizontally at tank-top (control) to monitor solar-energy input. Habitat verticality induces notable variations in solar-energy capture at four orientations by daily total, peak level, intensity, duration and timing. On sunny day, solar fraction reaching east side was only 37.1% of tank-top. Early morning sunshine striking east side nearly perpendicularly brings maximum intensity. South side facing the sun but at tangential incident angle has only 23.3% reception. Strong irradiance drives high control-surface temperature, but also induces notable vegetation-surface and adjacent ambient-air cooling by transpiration. A threshold solar intensity of about 300 Wm(-2) is necessary to impart notable cooling-effect. Summer-sunny day and rainy-day sunshine-burst episodes could satisfy this condition; cloudy day and rainfall periods with attenuated-diffused sunlight could not. Cloudy day and rainfall periods suppress cooling differences by orientation. Behind-mesh concrete surface is consistently cooler than control concrete surface in the three summer-weather scenarios. Behind-mesh-air remains warmer than ambient-air but cooler than two adjoining surfaces (vegetation and behind-mesh-concrete), indicating air-barrier effect and restricted air exchange between ambience and airgap. It implies that greenwall can bring bidirectional cooling, but transpiration cooling of anterior (ambient) air is more effective than shading and thermal-insulation cooling of posterior (airgap) air and concrete-surface. The findings could inform greenwall design to enhance ecosystem services for climate-change adaption and urban heat island amelioration. (C) 2015 Elsevier Ltd. All rights reserved.
C1 Univ Hong Kong, Dept Geog, Hong Kong, Hong Kong, Peoples R China.
C3 University of Hong Kong
RP Jim, CY (corresponding author), Univ Hong Kong, Dept Geog, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China.
EM hragjcy@hku.hk
RI Jim, CY/O-1025-2019
OI Jim, C.Y./0000-0003-4052-8363
FU government's Drainage Services Department
FX This study was supported by a research Grant kindly provided by the
   government's Drainage Services Department, to whom gratitude is owed.
   The laborious field work and technical support kindly offered by
   Jeannette Liu and Wing Yiu Wong are warmly appreciated.
CR Alexandria E, 2008, BUILD ENVIRON, V43, P480, DOI 10.1016/j.buildenv.2006.10.055
   [Anonymous], 2014, LANDSC URBAN PLAN
   Berardi U, 2014, APPL ENERG, V115, P411, DOI 10.1016/j.apenergy.2013.10.047
   Bolton C, 2014, BUILD ENVIRON, V80, P32, DOI 10.1016/j.buildenv.2014.05.020
   Burras J.K., 1994, MANUAL CLIMBERS WALL
   Cameron RWF, 2014, BUILD ENVIRON, V73, P198, DOI 10.1016/j.buildenv.2013.12.005
   Catita C, 2014, COMPUT GEOSCI-UK, V66, P1, DOI 10.1016/j.cageo.2014.01.002
   Eumorfopoulo EA, 2009, BUILD ENVIRON, V44, P1024, DOI 10.1016/j.buildenv.2008.07.004
   Francis RA, 2011, J ENVIRON MANAGE, V92, P1429, DOI 10.1016/j.jenvman.2011.01.012
   Franz-Vasdeki J, 2011, NAT CLIM CHANGE
   Gregory K, 2008, ENERG BUILDINGS, V40, P459, DOI 10.1016/j.enbuild.2007.04.001
   Haggag M, 2014, ENERG BUILDINGS, V82, P668, DOI 10.1016/j.enbuild.2014.07.087
   Hall JM, 2012, LANDSCAPE URBAN PLAN, V104, P410, DOI 10.1016/j.landurbplan.2011.11.015
   Hergaty EE, 1991, BIOL VINES, P357, DOI DOI 10.1017/CBO9780511897658.015
   Hong Kong Observatory, CLIM OF HONG KONG
   Hong Kong Observatory, OBS CLIM CHANG HONG
   Jim CY, 2015, ECOL ENG, V77, P348, DOI 10.1016/j.ecoleng.2015.01.021
   Jim CY, 2015, LANDSCAPE URBAN PLAN, V137, P107, DOI 10.1016/j.landurbplan.2015.01.001
   Jim CY, 2014, ECOL ENG, V69, P265, DOI 10.1016/j.ecoleng.2014.04.016
   Jim CY, 2014, APPL ENERG, V128, P49, DOI 10.1016/j.apenergy.2014.04.055
   Jim CY, 2014, ECOL ENG, V62, P1, DOI 10.1016/j.ecoleng.2013.10.022
   Jim CY, 2013, URBAN ECOSYST, V16, P741, DOI 10.1007/s11252-012-0268-x
   Jim CY, 2011, ECOL ENG, V37, P1112, DOI 10.1016/j.ecoleng.2011.02.005
   Jim CY, 1996, COMMUN SOIL SCI PLAN, V27, P2049, DOI 10.1080/00103629609369687
   Johnston J., 2004, BUILDING GREEN GUIDE
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Koehler Manfred, 2008, Urban Ecosystems, V11, P423, DOI 10.1007/s11252-008-0063-x
   Koyama T, 2014, ECOL ENG, V70, P217, DOI 10.1016/j.ecoleng.2014.05.026
   Mathey J, 2011, LOCAL SUSTAIN, V1, P479, DOI 10.1007/978-94-007-0785-6_47
   Mazzali U, 2013, BUILD ENVIRON, V64, P57, DOI 10.1016/j.buildenv.2013.03.005
   Olivieri F, 2014, BUILD ENVIRON, V77, P61, DOI 10.1016/j.buildenv.2014.03.019
   Peng JQ, 2013, APPL ENERG, V112, P646, DOI 10.1016/j.apenergy.2012.12.026
   Pérez G, 2011, APPL ENERG, V88, P4854, DOI 10.1016/j.apenergy.2011.06.032
   Perini K, 2011, BUILD ENVIRON, V46, P2287, DOI 10.1016/j.buildenv.2011.05.009
   Putz FE, 1991, BIOL VINES
   Santos T, 2014, APPL GEOGR, V51, P48, DOI 10.1016/j.apgeog.2014.03.008
   Scarpa M, 2014, ENERG BUILDINGS, V79, P155, DOI 10.1016/j.enbuild.2014.04.014
   Smith C, 2008, ENERG POLICY, V36, P4558, DOI 10.1016/j.enpol.2008.09.011
   Stasinopoulos T.N., 2002, ENV MANAG HLTH, V13, P339, DOI [10.1108/09566160210439242, DOI 10.1108/09566160210439242]
   Susorova I, 2014, BUILD ENVIRON, V76, P113, DOI 10.1016/j.buildenv.2014.03.011
   Svendsen E., 2012, Cities Environ, V5, P1, DOI [DOI 10.15365/CATE.5132012, 10.15365/cate.5132012]
   Taha H, 2008, ATMOS ENVIRON, V42, P8795, DOI 10.1016/j.atmosenv.2008.06.036
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   Verba Volant Ltd, 2007, VERT GARD
   Wong NH, 2010, BUILD ENVIRON, V45, P663, DOI 10.1016/j.buildenv.2009.08.005
NR 45
TC 82
Z9 89
U1 9
U2 66
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0306-2619
EI 1872-9118
J9 APPL ENERG
JI Appl. Energy
PD SEP 15
PY 2015
VL 154
BP 631
EP 643
DI 10.1016/j.apenergy.2015.05.077
PG 13
WC Energy & Fuels; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels; Engineering
GA CP4TI
UT WOS:000359875100059
DA 2025-01-10
ER

PT J
AU Hayles, C
   Huddleston, M
   Chinowsky, P
   Helman, J
AF Hayles, Carolyn
   Huddleston, Matt
   Chinowsky, Paul
   Helman, Jacob
TI Climate Adaptation Planning: Developing a Methodology for Evaluating
   Future Climate Change Impacts on Museum Environments and Their
   Collections
SO HERITAGE
LA English
DT Article
DE adaptation; comfort; climate change; buildings; indoor environmental
   quality; modelling; museum
ID TEMPERATURE; HUMIDITY
AB As organisations, museums are responsible for conserving, protecting, and displaying artwork and artefacts. Museum buildings must deliver an environment that will continue to provide this facility for both current and future generations. This research focused on presenting a museum with quantifiable and measurable data to help with climate adaptation planning. A methodology was developed using monitored data. Subhourly data for both indoor and outdoor temperature and humidity spanning the years 2012-2021 was used to produce a daily maximum, daily minimum, and daily average dataset. A sensitivity analysis determined which years to use to derive the indoor-outdoor relationships used in climate modelling. Future impacts were calculated using UK Climate Projections 2018 (UKCP18) data (12 models on a 2.2 km scale), as published by the Met Office Hadley Centre. The data contained within the 12 models was overlayed with the relationships derived to calculate the projected indoor temperature and humidity conditions within the museum. The results presented indicate that temperature and humidity conditions are projected to exceed design conditions more frequently in the coming decades. Consequently, adaptation plans must consider the potential impacts that include indoor environmental deterioration, leading to discomfort and health implications, increased energy costs, and system upgrade costs, as well as the potential for accelerated degradation of artwork and artefacts.
C1 [Hayles, Carolyn] Cardiff Metropolitan Univ, Cardiff Sch Art & Design, Dept Designed & Built Environm, Llandaff Campus, Cardiff CF5 2YB, Wales.
   [Huddleston, Matt; Chinowsky, Paul; Helman, Jacob] Resilient Analyt Inc, Lafayette, CO 80026 USA.
C3 Cardiff Metropolitan University
RP Hayles, C (corresponding author), Cardiff Metropolitan Univ, Cardiff Sch Art & Design, Dept Designed & Built Environm, Llandaff Campus, Cardiff CF5 2YB, Wales.
EM cshayles@cardiffmet.ac.uk; mhuddleston@resilient-analytics.com;
   pchinowsky@resilient-analytics.com; jhelman@resilient-analytics.com
OI Hayles, Carolyn/0000-0002-0811-0816
FU Cardiff Metropolitan University
FX The authors would like to thank staff at National Museum Cardiff,
   Amgueddfa Cymru-Museum Wales for providing access to the monitored
   temperature and relative humidity data.
CR Bertolin C, 2019, GEOSCIENCES, V9, DOI 10.3390/geosciences9060250
   Bonazza A, 2021, INT J DISAST RISK RE, V63, DOI 10.1016/j.ijdrr.2021.102455
   Cameron F, 2013, WIRES CLIM CHANGE, V4, P9, DOI 10.1002/wcc.200
   Centre for Environmental Data Analysis Met Office Hadley Centre, 2019, UKCP Local Projections at 2.2 km Resolution for 1980-2080 2021
   Gardiner Stephen., 2013, A Perfect Moral Storm: The Ethical Tragedy of Climate Change
   Georgiadou MC, 2012, ENERG POLICY, V47, P145, DOI 10.1016/j.enpol.2012.04.039
   Hallegatte S., 2011, Policy Research Working Paper Series 5617
   Hamilton P, 2020, J MUS EDUC, V45, P16, DOI 10.1080/10598650.2020.1720375
   Huerto-Cardenas HE, 2021, CLIMATE, V9, DOI 10.3390/cli9080132
   Huijbregts Z, 2012, BUILD ENVIRON, V55, P43, DOI 10.1016/j.buildenv.2012.01.008
   ICOM International Council of Museums, 2022, Museum Definion
   Larsen MAD, 2020, ENERG BUILDINGS, V226, DOI 10.1016/j.enbuild.2020.110397
   Lucchi E, 2018, J CULT HERIT, V29, P180, DOI 10.1016/j.culher.2017.09.003
   Mansouri A, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192315616
   Marshall George, 2014, Don't Even Think About It: Why Our Brains Are Wired to Ignore Climate Change
   McGhie H, 2020, MUS MANAGE CURATOR, V35, P653, DOI 10.1080/09647775.2020.1844589
   González CMM, 2020, APPL ENERG, V276, DOI 10.1016/j.apenergy.2020.115483
   Nguyen JL, 2016, INT J BIOMETEOROL, V60, P221, DOI 10.1007/s00484-015-1019-5
   Rees M, 2017, NAT CLIM CHANGE, V7, P166, DOI 10.1038/nclimate3237
   Salazar Juan F., 2011, Museum and Society, V9, P123
   Saunders D., 2008, Studies in Conservation, V53, P287, DOI [10.1179/sic.2008.53.4.287, DOI 10.1179/SIC.2008.53.4.287]
   Schito E, 2016, BUILDINGS, V6, DOI 10.3390/buildings6040041
   Shen PY, 2019, APPL ENERG, V233, P254, DOI 10.1016/j.apenergy.2018.10.041
   Stoknes PE., 2015, What we think about when we try not to think about global warming: Toward a New Psychology of Climate Action
   Sutton S, 2020, MUS MANAGE CURATOR, V35, P618, DOI 10.1080/09647775.2020.1837000
   Tamerius JD, 2013, WEATHER CLIM SOC, V5, P168, DOI 10.1175/WCAS-D-12-00030.1
NR 26
TC 1
Z9 1
U1 1
U2 2
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 2571-9408
J9 HERITAGE-BASEL
JI Heritage
PD DEC
PY 2023
VL 6
IS 12
BP 7446
EP 7465
DI 10.3390/heritage6120390
PG 20
WC Humanities, Multidisciplinary; Multidisciplinary Sciences
WE Emerging Sources Citation Index (ESCI)
SC Arts & Humanities - Other Topics; Science & Technology - Other Topics
GA DH1H0
UT WOS:001131041200001
OA gold
DA 2025-01-10
ER

PT J
AU Skidmore, TA
   Cohon, JL
AF Skidmore, Tyler A.
   Cohon, Jared L.
TI A multicriteria decision analysis framework for developing and
   evaluating coastal retreat policy
SO INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT
LA English
DT Article
DE Climate adaptation; Coastal retreat; Managed retreat; MCDA;
   Multiple-criteria decision analysis
ID MANAGED RETREAT
AB Managed retreat may be a necessity for coastal communities as sea levels rise due to climate change. Selecting the right policy decisions and timing is difficult given the vested interests of communities and stakeholder groups and requires careful balancing of the benefits and risks associated with each management alternative. State and federal agencies often employ single-objective optimization frameworks such as cost-benefit analysis to analyze coastal relocation alternatives, but such methods are limited in their ability to balance competing value considerations and stakeholder demands. The use of a multicriteria decision analysis (MCDA) methodology allows for such considerations to be quantified and evaluated, thereby improving planning and decision-making for coastal retreat policies. This paper provides a strategic MCDA framework to evaluate coastal retreat policy that could be leveraged by at-risk coastal communities. The MCDA is applied to a hypothetical coastal retreat scenario to visualize policy preferences and differing value considerations among stakeholders. This model can be used by government agencies to foster more sound, acceptable, and implementable coastal retreat policies and streamline the incorporation of this climate adaptation mechanism, which may be necessary for the near future. Integr Environ Assess Manag 2022;00:1-16. (c) 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
C1 [Skidmore, Tyler A.; Cohon, Jared L.] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA.
C3 Carnegie Mellon University
RP Skidmore, TA (corresponding author), Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA.
EM tskidmor@alumni.cmu.edu
OI Skidmore, Tyler/0000-0001-7229-9900
CR Agyeman J, 2009, ENVIRON PLANN A, V41, P509, DOI 10.1068/a41301
   Anderson RB, 2022, ECON ANTHROPOL, V9, P284, DOI 10.1002/sea2.12247
   [Anonymous], 2022, COASTAL SYSTEMS PORT
   Brans JP, 2005, INT SER OPER RES MAN, V78, P163, DOI 10.1007/b100605
   Carey J, 2020, P NATL ACAD SCI USA, V117, P13182, DOI 10.1073/pnas.2008198117
   de Ruig LT, 2019, SCI TOTAL ENVIRON, V678, P647, DOI 10.1016/j.scitotenv.2019.04.308
   Decerns MCDA, 2022, US
   Forman EH, 2001, OPER RES, V49, P469, DOI 10.1287/opre.49.4.469.11231
   Gittman RK, 2016, BIOSCIENCE, V66, P763, DOI 10.1093/biosci/biw091
   Haasnoot M, 2021, CLIM RISK MANAG, V34, DOI 10.1016/j.crm.2021.100355
   Hamilton LC, 2016, POPUL ENVIRON, V38, P115, DOI 10.1007/s11111-016-0259-6
   Hammond JohnS., 2002, SMART CHOICES PRACTI
   Hayes T., 2006, KIVALINA ALASKA RELO
   Jacobson M., 2012, NEW ORLEANS WETLANDS
   KOSKO B, 1986, INT J MAN MACH STUD, V24, P65, DOI 10.1016/S0020-7373(86)80040-2
   Lawrence J, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11020406
   Linkov I., 2020, Multi-Criteria Decision Analysis-Case Studies in Engineering and the Environment, V2nd
   Mach KJ, 2021, SCIENCE, V372, P1294, DOI 10.1126/science.abh1894
   Martha's Vineyard Commission, 2022, CLIMATE CHANGE
   Morgan M. G., 2017, Theory and Practice in Policy Analysis Including Applications in Science and Technology
   Pilkey O.H., 1998, CORPS SHORE
   Pilkey O H., 2019, Sea level rise: A slow tsunami on America's shores
   Pilkey OrrinH., 2016, Retreat from the Rising Sea: Hard Decisions in an Age of Climate Change
   Raiffa H., 1993, DECISIONS MULTIPLE O
   Roca E, 2008, RISK ANAL, V28, P399, DOI 10.1111/j.1539-6924.2008.01026.x
   Roy B, 2005, INT SER OPER RES MAN, V78, P3, DOI 10.1007/0-387-23081-5_1
   Shearer C, 2012, J POLIT ECOL, V19, P174, DOI 10.2458/v19i1.21725
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   Teirstein Z., 2021, RETREAT COASTLINES P
   The Data Center, 2021, WHO LIV NEW ORL METR
   Trump BD, 2018, ARCT ANTARCT ALP RES, V50, DOI 10.1080/15230430.2018.1438345
   US Census Bureau, 2022, TOT POP KIV ANVSA AK
   USACE Alaska District, 2022, AVETA REP SUMM
   USCensus Bureau, 2010, QUICKFACTS
   USCensus Bureau, 2021, QUICKFACTS
   Velasquez M., 2013, INT J OPERATIONS RES, V10, P56
   Willis D., 2004, SEA ENGULFING ALASKA
   Wilson ECF, 2015, PHARMACOECONOMICS, V33, P105, DOI 10.1007/s40273-014-0219-x
   YCC Team, 2020, WHY MIAM IS ON MOST
NR 39
TC 2
Z9 2
U1 1
U2 12
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1551-3777
EI 1551-3793
J9 INTEGR ENVIRON ASSES
JI Integr. Environ. Assess. Manag.
PD JAN
PY 2023
VL 19
IS 1
BP 83
EP 98
DI 10.1002/ieam.4662
EA SEP 2022
PG 16
WC Environmental Sciences; Toxicology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Toxicology
GA 7U6RO
UT WOS:000852829700001
PM 35903915
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Axelsson, C
   Giove, S
   Soriani, S
AF Axelsson, Charles
   Giove, Silvio
   Soriani, Stefano
TI Urban Pluvial Flood Management Part 1: Implementing an AHP-TOPSIS
   Multi-Criteria Decision Analysis Method for Stakeholder Integration in
   Urban Climate and Stormwater Adaptation
SO WATER
LA English
DT Article
DE policy making; stormwater; climate adaptation; analytic hierarchy
   process; technique for order of preference by similarity to ideal
   solution; green infrastructure
ID ANALYTIC HIERARCHY PROCESS; GREEN INFRASTRUCTURE; JUDGMENT SCALES; RANK
   REVERSAL; CRITERIA; CATCHMENT; MCDA
AB Cities are facing increasing pressures to enact adaptation measures due to climate change. While blue-green infrastructure has emerged as a focal adaptation technique for stormwater management, in order to craft adaptation policies cities must consider a multitude of emerging, complex, and competing stakeholder interests around multiple adaptation alternatives. However, accounting for these different interests, analyzing their diverse priorities, and maintaining a transparent decision-making process is not easily achieved within the existing policy frameworks. Here we define and present a combined multi-criteria decision analysis (MCDA) of the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) methods that easily integrates and quantifies stakeholder priorities while remaining accessible for non-experts engaged in the policy-making process. We demonstrate the method's effectiveness through analyzing opinions about stormwater adaptation in New York City across several stakeholder groups. The method succeeds in integrating quantitative and qualitative judgements, indicating stakeholder preferential differences and allowing for more inclusive policy to be crafted. It can be extended beyond stormwater to many urban climate adaptation decisions facing multi-criteria considerations.
C1 [Axelsson, Charles; Giove, Silvio; Soriani, Stefano] Ca Foscari Univ Venice, Dept Econ, I-30121 Venice, Italy.
C3 Universita Ca Foscari Venezia
RP Axelsson, C (corresponding author), Ca Foscari Univ Venice, Dept Econ, I-30121 Venice, Italy.
EM charles.axelsson@unive.it; sgiove@unive.it; soriani@unive.it
OI Axelsson, Charles/0000-0002-8529-7020
CR García RA, 2022, URBAN RES PRACT, V15, P350, DOI 10.1080/17535069.2020.1811886
   Aguarón J, 2003, EUR J OPER RES, V147, P137, DOI 10.1016/S0377-2217(02)00255-2
   Al-Aomar R, 2010, INT J IND ENG-THEORY, V17, P12
   Alhumaid M, 2018, WATER-SUI, V10, DOI 10.3390/w10050581
   André K, 2012, J ENVIRON POL PLAN, V14, P243, DOI 10.1080/1523908X.2012.702562
   [Anonymous], 2014, CLIM POL, DOI DOI 10.1080/14693062.2014.937388
   [Anonymous], 2021, ZOHO SURVEY SURVEY S
   [Anonymous], 2013, P INT S AN HIER PROC
   Antrobus D, 2011, URBAN RES PRACT, V4, P207, DOI 10.1080/17535069.2011.579777
   Aragon T.J., 2017, Deriving criteria weights for health decision making: A brief tutorial
   Axelsson C, 2021, J ENVIRON PLANN MAN, V64, P1408, DOI 10.1080/09640568.2020.1823346
   Aylett A, 2015, URBAN CLIM, V14, P4, DOI 10.1016/j.uclim.2015.06.005
   Barzilai J, 1997, J OPER RES SOC, V48, P1226, DOI 10.1057/palgrave.jors.2600474
   Barzilai J., 1998, J. Multi-Criteria Decis. Anal, V7, P123, DOI [10.1002/(SICI)1099-1360(199805)7:3andlt;123::AID-MCDA181andgt;3.0.CO;2-8, DOI 10.1002/(SICI)1099-1360(199805)7:3ANDLT;123::AID-MCDA181ANDGT;3.0.CO;2-8]
   Barzilai J., 1992, Systems and management science by extremal methods: Research honoring Abraham Charnes at age 70, P361
   Barzilai J., 2001, P NSF DES MAN RES C, P1
   BELTON V, 1983, OMEGA-INT J MANAGE S, V11, P228, DOI 10.1016/0305-0483(83)90047-6
   Brugha R, 2000, HEALTH POLICY PLANN, V15, P239, DOI 10.1093/heapol/15.3.239
   Brunelli M., 2015, INTRO ANAL HIERARCHY, DOI DOI 10.1007/978-3-319-12502-2
   Cappucci M., 2021, WASH POST
   Chuansheng Xie., 2012, SYSTEMS ENG PROCEDIA, V4, P203
   CRAWFORD G, 1985, J MATH PSYCHOL, V29, P387, DOI 10.1016/0022-2496(85)90002-1
   Czakó V, 2013, URBAN RES PRACT, V6, P95, DOI 10.1080/17535069.2012.762221
   De Montis A., 2005, Alternatives for environmental valuation, P99
   De Montis A., 2000, Transitions Towards a Sustainable Europe, P1
   Ebrahimian A, 2015, AUTOMAT CONSTR, V58, P118, DOI 10.1016/j.autcon.2015.07.014
   Ekmekcioglu Ö, 2021, INT J DISAST RISK RE, V60, DOI 10.1016/j.ijdrr.2021.102327
   Erdogan M, 2019, SUSTAIN CITIES SOC, V45, P117, DOI 10.1016/j.scs.2018.10.027
   Farnia L., 2015, ADV NEURAL NETWORKS, V37
   Fedrizzi M., 2018, SOFT COMPUTING APPL
   Fedrizzi M, 2007, EUR J OPER RES, V183, P303, DOI 10.1016/j.ejor.2006.09.065
   Fedrizzi M, 2013, INT J GEN SYST, V42, P366, DOI 10.1080/03081079.2012.755523
   Forman E, 1998, EUR J OPER RES, V108, P165, DOI 10.1016/S0377-2217(97)00244-0
   Franek J, 2014, PROC ECON FINANC, V12, P164, DOI 10.1016/S2212-5671(14)00332-3
   Gallo EM, 2020, WATER-SUI, V12, DOI 10.3390/w12072005
   Goepel KD, 2019, INT J INF TECH DECIS, V18, P445, DOI 10.1142/S0219622019500044
   Gogate NG, 2017, J CLEAN PROD, V142, P2046, DOI 10.1016/j.jclepro.2016.11.079
   González JE, 2019, ANN NY ACAD SCI, V1439, P30, DOI 10.1111/nyas.14007
   Guarini MR, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10020507
   Guitouni A, 1998, EUR J OPER RES, V109, P501, DOI 10.1016/S0377-2217(98)00073-3
   Hager J., 2019, AN INTEGRATED PLANNING FRAMEWORK FOR URBAN STORMWATER MANAGEMENT: A ONE WATER APPROACH
   Henstra D, 2020, J ENVIRON PLANN MAN, V63, P1077, DOI 10.1080/09640568.2019.1634015
   Huang YS, 2012, GROUP DECIS NEGOT, V21, P461, DOI 10.1007/s10726-010-9218-2
   Hwang C.-L., 1981, MULTIPLE ATTRIBUTE D, DOI DOI 10.1007/978-3-642-48318-93
   ISAHP, 2018, JUDG SCAL AN HIER PR
   Ishizaka A., 2004, Development of an intelligent tutoring system for AHP (Analytic Hierarchy Process)
   Ivanco M, 2017, EXPERT SYST APPL, V90, P111, DOI 10.1016/j.eswa.2017.08.003
   Jayasooriya VM, 2018, WATER RESOUR MANAG, V32, P4297, DOI 10.1007/s11269-018-2052-z
   Jiri M., 2019, WORLD C MED PHYS BIO
   Keshavarz-Ghorabaee M, 2018, ECON COMPUT ECON CYB, V52, P121, DOI 10.24818/18423264/52.3.18.08
   Koc K, 2021, J ENVIRON MANAGE, V294, DOI 10.1016/j.jenvman.2021.113023
   Kordana S, 2020, RESOURCES-BASEL, V9, DOI 10.3390/resources9020020
   Li PY, 2013, ENVIRON MONIT ASSESS, V185, P2453, DOI 10.1007/s10661-012-2723-9
   Liu Y, 2020, ENVIRON SCI POLLUT R, V27, P4008, DOI 10.1007/s11356-019-07005-w
   Locatelli L, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093792
   Luan B, 2019, J CLEAN PROD, V223, P680, DOI 10.1016/j.jclepro.2019.03.028
   Martinez-Juarez P, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11030647
   Matthews T, 2015, LANDSCAPE URBAN PLAN, V138, P155, DOI 10.1016/j.landurbplan.2015.02.010
   Mayne R, 2018, PALGR COMMUN, V4, DOI 10.1057/s41599-018-0176-7
   Moghadas M, 2019, INT J DISAST RISK RE, V35, DOI 10.1016/j.ijdrr.2019.101069
   Moore TL, 2016, CLIMATIC CHANGE, V138, P491, DOI 10.1007/s10584-016-1766-2
   NYC Department of Environmental Protection, 2017, CLOUDB RES PLANN STU
   NYC Department of Environmental Protection, 2019, NYC STORMW MAN PROGR
   Ossadnik W, 2016, GROUP DECIS NEGOT, V25, P421, DOI 10.1007/s10726-015-9448-4
   Pakfetrat A, 2020, URBAN RES PRACT, V13, P45, DOI 10.1080/17535069.2018.1495757
   Pauer F, 2016, BMC MED INFORM DECIS, V16, DOI 10.1186/s12911-016-0346-8
   Qi YF, 2020, WATER-SUI, V12, DOI 10.3390/w12102788
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Reed MS, 2009, J ENVIRON MANAGE, V90, P1933, DOI 10.1016/j.jenvman.2009.01.001
   Russo RDSM, 2015, PROCEDIA COMPUT SCI, V55, P1123, DOI 10.1016/j.procs.2015.07.081
   Saardchom N, 2012, J BUS ECON STAT, V3, P164, DOI [10.15341/jbe(2155-7950)/03.03.2012/002, DOI 10.15341/JBE(2155-7950)/03.03.2012/002]
   Saaty T.L., 2009, International Journal of the Analytic Hierarchy Process, V1, P121, DOI DOI 10.13033/IJAHP.V1I2.53
   Saaty TL, 2003, MATH COMPUT MODEL, V38, P233, DOI [10.1016/S0895-7177(03)90083-5, 10.1016/S0895-7177(03)00216-4]
   SAATY TL, 1984, MATH MODELLING, V5, P309, DOI 10.1016/0270-0255(84)90008-3
   SAATY TL, 1990, EUR J OPER RES, V48, P156, DOI 10.1016/0377-2217(90)90073-K
   Saaty TL., 1980, Agric Econ Rev, V70, P10, DOI DOI 10.3414/ME10-01-0028
   Sahin O., 2013, WATER CONSERVATION P
   Shih HS, 2007, MATH COMPUT MODEL, V45, P801, DOI 10.1016/j.mcm.2006.03.023
   Siems R., 2014, IWTJ, V4, P135
   García-Cascales MS, 2012, MATH COMPUT MODEL, V56, P123, DOI 10.1016/j.mcm.2011.12.022
   Song JY, 2016, WATER RESOUR MANAG, V30, P4751, DOI 10.1007/s11269-016-1451-2
   Steele K, 2009, RISK ANAL, V29, P26, DOI 10.1111/j.1539-6924.2008.01130.x
   Tabak RG, 2015, PUBLIC HEALTH, V129, P698, DOI 10.1016/j.puhe.2015.02.016
   Torabi E, 2022, URBAN RES PRACT, V15, P561, DOI 10.1080/17535069.2020.1846771
   Vega A, 2014, PROCEDIA COMPUT SCI, V31, P308, DOI 10.1016/j.procs.2014.05.273
   Velasquez Mark, 2013, International lournal of Operations Research, V10, P56, DOI DOI 10.1007/978-3-319-12586-2
   Vogler D., 2017, Lessons in Conservation, V7, P5
   Wang YM, 2009, MATH COMPUT MODEL, V49, P1221, DOI 10.1016/j.mcm.2008.06.019
   WEDLEY WC, 1993, MATH COMPUT MODEL, V17, P151, DOI 10.1016/0895-7177(93)90183-Y
   Young KD, 2010, J CONTEMP WAT RES ED, V146, P50, DOI 10.1111/j.1936-704X.2010.00391.x
   Yu ZJ, 2021, ENVIRON SCI POLLUT R, V28, P28571, DOI 10.1007/s11356-021-12525-5
   Zeng JJ, 2021, URBAN FOR URBAN GREE, V64, DOI 10.1016/j.ufug.2021.127287
   Zhang Z., 2009, COMMUNICATIONS COMPU, V35
   Zhang ZX, 2021, ENVIRON SCI POLLUT R, V28, P10872, DOI 10.1007/s11356-020-11353-3
NR 94
TC 17
Z9 17
U1 3
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD SEP
PY 2021
VL 13
IS 17
AR 2422
DI 10.3390/w13172422
PG 24
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Water Resources
GA UO1JR
UT WOS:000694458900001
OA gold
DA 2025-01-10
ER

PT C
AU Karasu, A
   Hantouch, Y
   Steffan, C
AF Karasu, Arda
   Hantouch, Yaser
   Steffan, Claus
BE Kurnitski, J
   Kalamees, T
TI Climate adaptation of listed buildings: an interaction between design,
   regulations and energy efficiency
SO 12TH NORDIC SYMPOSIUM ON BUILDING PHYSICS (NSB 2020)
SE E3S Web of Conferences
LA English
DT Proceedings Paper
CT 12th Nordic Symposium on Building Physics (NSB)
CY SEP 06-09, 2020
CL Tallinn, ESTONIA
AB Energy retrofitting of listed buildings requires a rethink as it is economically and technically complicated to retrofit. The Technische Universitat Berlin has 47 buildings with a total net floor area above 500.000 m(2) in its central campus, and 60% of them are listed. In Germany, optimizing the energy efficiency of such buildings has not to fulfill the requirements of the energy efficiency regulations. On the one hand, this situation is not corresponding to the national objectives regarding climate adaptation. On the other hand, they have to be retrofitted because of issues like poor energy efficiency and user comfort, and not privileged with special regulations. However, instead of changing the regulations, it is possible to solve the problem by changing the way of thinking In this regard, rather than retrofitting such buildings directly, a new approach has been developed where the surrounding climatic conditions are optimized. Hereby, a simulation-based concept has been developed with an external transparent envelope. This "climate envelope" creates an intermediate space between outdoor and indoor, where through controlled air movement and passive solar gains, the balance in seasonal energy efficiency can be kept economically without any implementation on the buildings according to the building thermal and CFD simulations. This overall approach activates the yet not exploited capacity of energy savings by listed buildings using intelligent design and saves up to 30% more of primary energy.
C1 [Karasu, Arda; Hantouch, Yaser; Steffan, Claus] Tech Univ Berlin, Fak 6, Fachgebiet Gebaudetech & Entwerfen, Str 17 Juli 152, D-10623 Berlin, Germany.
C3 Technical University of Berlin
RP Karasu, A (corresponding author), Tech Univ Berlin, Fak 6, Fachgebiet Gebaudetech & Entwerfen, Str 17 Juli 152, D-10623 Berlin, Germany.
EM karasu@tu-berlin.de
FU German Federal Ministry for Economic Affairs and Energy [03ET1632A]
FX This research is a part of the project EnEff: HCBC 1. Umsetzungsphase
   funded by the German Federal Ministry for Economic Affairs and Energy,
   Ref. #03ET1632A
CR Altaha N., 2003, MAUERWERK EUROPEAN J, V7, P210
   [Anonymous], 2019, BERL EN KLIM 2030 BE
   BMWI, 2017, EN BAUEN 2017 FORSCH
   Bundesministerium fur Umwelt Naturschutz und nukleare Sicherheit, 2019, KLIM ZAHL FAKT TREDN
   Bundesministerium fur Umwelt Naturschutz und nukleare Sicherheit, 2019, KLIM 2050 KLIM GRUND
   Conrad C, 2007, BAUPHYSIK, V29, P221, DOI 10.1002/bapi.200710031
   Doster S., 2016, ENERGIEEFFIZIENTE UN
   Jochum P., 2012, TECHNISCHE RESTRIKTI
   Karasu A., BUILDING CLIMATE ENV
   Karasu A., 2019, BS CAIRO SIMULATION
   Kolbe G., 2012, MAUERWERK EUROPEAN J, P102
   Kriegel M., 2019, ENEFF HCBC HOCHSCHUL
   Krus M., 2005, FACHTAGUNG INNENDAMM
   Sadineni SB, 2011, RENEW SUST ENERG REV, V15, P3617, DOI 10.1016/j.rser.2011.07.014
   Santamouris M., SOLAR ENERGY, V70, P201
   Senatsverwaltung fur Umwelt V. u, 2019, BER UMS BERL EN KLIM
   Singhal P., 2019, WARMEMONITOR 2018 ST
   Westermann R., 2019, DENA GEBAUDEREPORT K
NR 18
TC 1
Z9 1
U1 0
U2 4
PU E D P SCIENCES
PI CEDEX A
PA 17 AVE DU HOGGAR PARC D ACTIVITES COUTABOEUF BP 112, F-91944 CEDEX A,
   FRANCE
SN 2267-1242
J9 E3S WEB CONF
PY 2020
VL 172
AR 15003
DI 10.1051/e3sconf/202017215003
PG 6
WC Architecture; Construction & Building Technology; Green & Sustainable
   Science & Technology; Engineering, Civil; Physics, Applied
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Architecture; Construction & Building Technology; Science & Technology -
   Other Topics; Engineering; Physics
GA BQ4RB
UT WOS:000594033400142
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Uittenbroek, CJ
   Mees, HLP
   Hegger, DLT
   Driessen, PPJ
AF Uittenbroek, Caroline J.
   Mees, Heleen L. P.
   Hegger, Dries L. T.
   Driessen, Peter P. J.
TI The design of public participation: who participates, when and how?
   Insights in climate adaptation planning from the Netherlands
SO JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT
LA English
DT Article
DE public participation; responsibilities; local government; societal
   actors; legitimacy
ID PRIVATE RESPONSIBILITIES; FRAMEWORK; GOVERNANCE; PERSPECTIVE; CONTEXT;
   SCOPE
AB The planning and implementation of climate adaptation measures requires the participation of citizens. The design of public participation is often determined by local government. Yet, it remains largely unclear to what extent there is deliberate design of participation efforts and which objectives are served with the designs put into practice. This article reviews three cases of adaptation planning in the Netherlands, using a theory-derived framework that links the design of public participation with nine different objectives that participation could have. These case studies illustrate that participants did not depart from an explicitly formulated and agreed-upon objective, leading to a design of the participatory process that was highly contingent. The findings suggest that a more systematic and deliberate approach, in which both the objectives and the design of public participation are communicated explicitly, and are discussed by participants, increases the chance that the objectives are met.
C1 [Uittenbroek, Caroline J.; Mees, Heleen L. P.; Hegger, Dries L. T.; Driessen, Peter P. J.] Univ Utrecht, Copernicus Inst Sustainable Dev, Environm Governance, Utrecht, Netherlands.
C3 Utrecht University
RP Uittenbroek, CJ (corresponding author), Univ Utrecht, Copernicus Inst Sustainable Dev, Environm Governance, Utrecht, Netherlands.
EM c.j.uittenbroek@uu.nl
RI Hegger, Dries/S-8727-2016; Uittenbroek, Caroline/C-3186-2017; Driessen,
   Peter/M-6751-2013; Mees, Heleen/L-5394-2013; Hegger, Dries/L-9301-2013
OI Driessen, Peter/0000-0002-0724-6666; Mees, Heleen/0000-0002-4401-6106;
   Hegger, Dries/0000-0003-2721-3527
CR ANDRE P., 2006, International Association for Impact Assessment Special Publication Series. n.˚4, P1
   ARNSTEIN SR, 1969, J AM I PLANNERS, V35, P216, DOI 10.1080/01944366908977225
   Boonstra B, 2011, URBAN RES PRACT, V4, P99, DOI 10.1080/17535069.2011.579767
   Bulkeley H, 2013, T I BRIT GEOGR, V38, P361, DOI 10.1111/j.1475-5661.2012.00535.x
   Chavez B., 2008, IMPACT ASSESS PROJEC, V26, P163, DOI DOI 10.3152/146155108X363052
   Dietz S, 2008, REV ENV ECON POLICY, V2, P94, DOI 10.1093/reep/ren001
   Driessen P., 1995, MANAGING ENV DISPUTE, P155
   Ertiö TP, 2017, INT J INFORM MANAGE, V37, P111, DOI 10.1016/j.ijinfomgt.2017.01.001
   Evans-Cowley J, 2010, PLAN PRACT RES, V25, P397, DOI 10.1080/02697459.2010.503432
   Few R, 2007, CLIM POLICY, V7, P46, DOI 10.1080/14693062.2007.9685637
   Glucker AN, 2013, ENVIRON IMPACT ASSES, V43, P104, DOI 10.1016/j.eiar.2013.06.003
   Hajer M., 2011, The energetic society: in search of a governance philosophy for a clean economy
   Hegger DLT, 2017, ENVIRON POLICY GOV, V27, P336, DOI 10.1002/eet.1766
   Howlett M, 2009, POLICY SCI, V42, P73, DOI 10.1007/s11077-009-9079-1
   Innes JE, 1999, J AM PLANN ASSOC, V65, P412, DOI 10.1080/01944369908976071
   Lemos MC, 2006, ANNU REV ENV RESOUR, V31, P297, DOI 10.1146/annurev.energy.31.042605.135621
   Massey E, 2013, REG ENVIRON CHANGE, V13, P341, DOI 10.1007/s10113-012-0341-2
   Mees H. L. P., 2016, WORK PACKAGE 2 NETHE
   Mees H, 2019, J ENVIRON PLANN MAN, V62, P671, DOI 10.1080/09640568.2018.1428184
   Mees H, 2017, J ENVIRON POL PLAN, V19, P374, DOI 10.1080/1523908X.2016.1223540
   Mees HLP, 2014, REG ENVIRON CHANGE, V14, P671, DOI 10.1007/s10113-013-0527-2
   Mees HLP, 2013, J ENVIRON PLANN MAN, V56, P802, DOI 10.1080/09640568.2012.706600
   Mees HLP, 2012, J ENVIRON POL PLAN, V14, P305, DOI 10.1080/1523908X.2012.707407
   Newig J, 2018, POLICY STUD J, V46, P269, DOI 10.1111/psj.12209
   O'Faircheallaigh C, 2010, ENVIRON IMPACT ASSES, V30, P19, DOI 10.1016/j.eiar.2009.05.001
   Petts Judith, 2003, Journal of Environmental Assessment Policy and Management, V5, P269, DOI 10.1142/S1464333203001358
   Pierson Paul., 1993, WORLD POLIT, V45, P595, DOI DOI 10.2307/2950710
   Renn O, 2006, LAND USE POLICY, V23, P34, DOI 10.1016/j.landusepol.2004.08.005
   Runhaar H, 2009, ENVIRON IMPACT ASSES, V29, P200, DOI 10.1016/j.eiar.2008.09.003
   Schaatsbergen R., 2015, WATERPLEIN TIEL ALLE
   Scharpf F.W., 1978, Interogranisational policy making, P345
   Stewart Jennifer M. P., 2007, Journal of Environmental Assessment Policy and Management, V9, P161, DOI 10.1142/S1464333207002743
   Sztompka P., 1999, Trust: A sociological theory
   Tennekes J, 2014, J ENVIRON POL PLAN, V16, P241, DOI 10.1080/1523908X.2013.836961
   Termeer CJAM, 2017, Oxford Research Encyclopedia of Climate Science
   Tompkins EL, 2012, GLOBAL ENVIRON CHANG, V22, P3, DOI 10.1016/j.gloenvcha.2011.09.010
   van der Heijden J, 2012, ENVIRON POLICY GOV, V22, P177, DOI 10.1002/eet.1583
   van Herk S, 2011, ENVIRON SCI POLICY, V14, P543, DOI 10.1016/j.envsci.2011.04.006
NR 38
TC 70
Z9 77
U1 1
U2 22
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0964-0568
EI 1360-0559
J9 J ENVIRON PLANN MAN
JI J. Environ. Plan. Manag.
PD DEC 6
PY 2019
VL 62
IS 14
BP 2529
EP 2547
DI 10.1080/09640568.2019.1569503
PG 19
WC Development Studies; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Development Studies; Public Administration
GA JI1CI
UT WOS:000493203100007
OA Green Published, hybrid
DA 2025-01-10
ER

PT B
AU Zimmermann, K
   Boghrat, J
   Weber, M
AF Zimmermann, Karsten
   Boghrat, Jasmin
   Weber, Meike
BE Heinelt, H
   Lamping, W
TI The epistemologies of local climate change policies in Germany
SO POLICY CHOICE IN LOCAL RESPONSES TO CLIMATE CHANGE: A COMPARISON OF
   URBAN STRATEGIES
LA English
DT Article; Book Chapter
ID GOVERNANCE; POLITICS; CITIES
AB Measures for climate adaptation and mitigation at the local level result in profound changes for the daily routines of municipal administrative staff. New agencies are created, new organisational relationships are established and the development of new competencies is needed. In particular, urban planning and environmental planning departments claim leading roles in cities' socio-technical transitions. This article seeks to describe how knowledge is generated and used in this transition process in three German cities. The results show the combination of climate adaptation and mitigation is the dominant 'narrative' in large parts of the municipal administrations (as is the case in most other German and European cities). All three cities developed sophisticated strategies for ambitious goals to reduce CO2 emissions. Furthermore, the governance of local knowledge shares distinct characteristics and organisational aspects in the cities. However, internally competing epistemologies in the sense of the infrastructure for the interpretation of reality and determination of what is known and how can be identified and discussed.
C1 [Zimmermann, Karsten; Weber, Meike] Tech Univ Dortmund, Fac Spatial Planning, European Planning Cultures, Dortmund, Germany.
   [Boghrat, Jasmin] Tech Univ Darmstadt, Fac Architecture, Darmstadt, Germany.
C3 Dortmund University of Technology; Technical University of Darmstadt
RP Zimmermann, K (corresponding author), Tech Univ Dortmund, Fac Spatial Planning, European Planning Cultures, Dortmund, Germany.
RI Zimmermann, Karsten/AAP-8341-2020
CR [Anonymous], 2011, Social knowledge in the making, DOI DOI 10.7208/CHICAGO/9780226092102.001.0001
   [Anonymous], 2008, THEORETISCHE EMPIRIE
   [Anonymous], 2009, ORG FORSCHUNG FALL A
   [Anonymous], 2005, DESIGNS NATURE SCI D
   [Anonymous], 2008, GOVERNANCE DURCH WIS
   Betsill MM, 2006, GLOBAL GOV, V12, P141, DOI 10.1163/19426720-01202004
   Boschen S, 2010, HYBRIDE WISSENSREGIM
   Bulkeley H, 2006, URBAN STUD, V43, P2237, DOI 10.1080/00420980600936491
   Bulkeley H, 2012, LOCAL ENVIRON, V17, P545, DOI 10.1080/13549839.2012.681464
   Camic Charles., 2011, SOCIAL KNOWLEDGE MAK, P1, DOI [DOI 10.7208/CHICAGO/9780226092102.001.0001, 10.7208/chicago/9780226092102.001.0001]
   Cetina Karin Knorr, 1999, EPISTEMIC CULTURES S
   Daston L., 2007, Objectivity
   DAVOUDI S., 2006, DISP PLANNING REV, V42, P14, DOI [https://doi.org/10.1080/02513625.2006.10556951, DOI 10.1080/02513625.2006.10556951]
   Demeritt D, 2001, ANN ASSOC AM GEOGR, V91, P307, DOI 10.1111/0004-5608.00245
   Edmondson Ricca, 1997, POLITICAL CONTEXT CO, P210
   Frohlich J., 2009, Z UMWELTRECHT, V3, P325
   Gherardi S, 2000, HUM RELAT, V53, P1057
   Grundmann R, 2007, ENVIRON POLIT, V16, P414, DOI 10.1080/09644010701251656
   Hodson M, 2011, ROUTL STUD HUM GEOGR, V35, P54
   Holden M, 2008, PROG PLANN, V69, P1, DOI 10.1016/j.progress.2007.12.001
   Hoppe Robert., 2011, The Governance of Problems: Puzzling, Powering and Participation
   Iedema R., 2003, DISCOURSES POSTBUREA
   Kapp R., 2011, NATUR STADT IM WANDE, P53
   Landeshauptstadt Munchen, 2008, AKT LEITH OK PERSP M
   Landeshauptstadt Stuttgart, 2010, STADT EN EFF SEE STU
   Landeshauptstadt Stuttgart, 2010, KLIM HER STADTK, V3
   Landeshauptstadt Stuttgart, 1997, KLIM STUTT KLIKS
   Landeshauptstadt Stuttgart, 2013, VERW ALLG STELLV OB
   Landeshauptstadt Stuttgart, 2007, GRDRS 723 2007 FORTS
   Landeshauptstadt Stuttgart, 2008, UMW RAUM PLAN STUTT, V1
   Landeshauptstadt Stuttgart, 2012, KLIM STUTTG KLIMAKS
   Matthiesen U., 2005, Working Paper Erkner
   Miller CA, 2007, GOVERNANCE, V20, P325, DOI 10.1111/j.1468-0491.2007.00359.x
   Nilsson M, 2005, ENVIRON PLANN C, V23, P207, DOI 10.1068/c0405j
   Reckwitz A., 2004, Paradigmen der akteurszentrierten Soziologie S, P303
   Rein M., 1993, ARGUMENTATIVE TURN P, P145
   Ren C, 2011, INT J CLIMATOL, V31, P2213, DOI 10.1002/joc.2237
   Rub Friedbert W, 2012, AUFSTIEG LEGITIMITAT, P377
   Stone D., 2002, Policy Paradox
   StraBheim H., 2011, POLITIK REGULIERUNG, P48
   Strassheim H, 2014, EVID POLICY, V10, P259, DOI 10.1332/174426514X13990433991320
   Termeer CJAM, 2013, PUBLIC MANAG REV, V15, P43, DOI 10.1080/14719037.2012.664014
   Wagenaar H, 2004, PUBLIC ADMIN REV, V64, P643, DOI 10.1111/j.1540-6210.2004.00412.x
   Wagner J., 2005, 42005101 WZB
   Weingart Peter., 2003, Wissenschaftssoziologie
   WIESENTHAL H, 1995, Z SOZIOL, V24, P137
   Zimmermann K, 2009, DISP, V45, P56, DOI 10.1080/02513625.2009.10557041
NR 47
TC 2
Z9 2
U1 0
U2 3
PU ROUTLEDGE
PI ABINGDON
PA 2 PARK SQ, MILTON PARK, ABINGDON OX14 4RN, OXFORD, ENGLAND
BN 978-1-317-20653-8; 978-1-138-67148-5
PY 2016
BP 29
EP 44
PG 16
WC Environmental Studies; Regional & Urban Planning
WE Book Citation Index – Social Sciences & Humanities (BKCI-SSH)
SC Environmental Sciences & Ecology; Public Administration
GA BN1ZS
UT WOS:000475729900003
DA 2025-01-10
ER

PT J
AU Melero, Y
   Evans, LC
   Kuussaari, M
   Schmucki, R
   Stefanescu, C
   Roy, DB
   Oliver, TH
AF Melero, Yolanda
   Evans, Luke C.
   Kuussaari, Mikko
   Schmucki, Reto
   Stefanescu, Constanti
   Roy, David B.
   Oliver, Tom H.
TI Local adaptation to climate anomalies relates to species phylogeny
SO COMMUNICATIONS BIOLOGY
LA English
DT Article
ID HABITAT FRAGMENTATION; DENSITY-DEPENDENCE; RANGE SHIFTS; BUTTERFLIES;
   ABUNDANCE; BIODIVERSITY; VULNERABILITY; POPULATIONS; SENSITIVITY;
   GENERATION
AB Climatic anomalies are increasing in intensity and frequency due to rapid rates of global change, leading to increased extinction risk for many species. The impacts of anomalies are likely to vary between species due to different degrees of sensitivity and extents of local adaptation. Here, we used long-term butterfly monitoring data of 143 species across six European bioclimatic regions to show how species' population dynamics have responded to local or globally-calculated climatic anomalies, and how species attributes mediate these responses. Contrary to expectations, degree of apparent local adaptation, estimated from the relative population sensitivity to local versus global anomalies, showed no associations with species mobility or reproductive rate but did contain a strong phylogenetic signal. The existence of phylogenetically-patterned local adaptation to climate has important implications for forecasting species responses to current and future climatic conditions and for developing appropriate conservation practices.
   Melero et al. investigate butterfly responses to climatic anomalies from long-term monitoring observations in the field. They found the degree of adaptation to local fluctuations in climate had a strong phylogenetic signal but was not associated with mobility or reproductive rate of a species.
C1 [Melero, Yolanda; Evans, Luke C.; Oliver, Tom H.] Univ Reading, Sch Biol Sci, POB 217, Reading RG6 6AH, Berks, England.
   [Melero, Yolanda] CREAF, E-08193 Cerdanyola Del Valles, Catalonia, Spain.
   [Kuussaari, Mikko] Biodivers Ctr, Finnish Environm Inst SYKE, Latokartanonkaari 11, FI-00790 Helsinki, Finland.
   [Schmucki, Reto; Roy, David B.] UK Ctr Ecol & Hydrol, Wallingford OX10 8BB, Oxon, England.
   [Stefanescu, Constanti] Museu Ciencies Nat Granollers, Francesc Macia 51, Granollers 08402, Catalonia, Spain.
C3 University of Reading; Centro de Investigacion Ecologica y Aplicaciones
   Forestales (CREAF-CERCA); Finnish Environment Institute; UK Centre for
   Ecology & Hydrology (UKCEH)
RP Melero, Y (corresponding author), Univ Reading, Sch Biol Sci, POB 217, Reading RG6 6AH, Berks, England.; Melero, Y (corresponding author), CREAF, E-08193 Cerdanyola Del Valles, Catalonia, Spain.
EM yolanda.melero@reading.ac.uk
RI Kuussaari, Mikko/Y-4070-2019; Evans, Luke Christopher/AAM-7967-2020;
   Schmucki, Reto/A-6312-2012; Melero, Yolanda/H-4687-2015
OI Evans, Luke Christopher/0000-0001-8649-0589; Schmucki,
   Reto/0000-0003-3064-7553; Melero, Yolanda/0000-0002-4337-1448
FU European Commission [H2020-MSCA-IF-2017 795890]; Foundation for
   Biodiversity Research; CESAB (Centre for the Synthesis and Analysis of
   Biodiversity, France) project LOLA
FX This work and Y.M. were supported by Marie Sklodowska Curie
   H2020-MSCA-IF-2017 795890 project EXTINCT of the European Commission; as
   well as, initially by Foundation for Biodiversity Research and CESAB
   (Centre for the Synthesis and Analysis of Biodiversity, France) project
   LOLA. We thank the eBMS (https://butterflymonitoring.net/) for the data
   and their volunteers for providing the data needed for the study; and
   Roger Vila and the three reviewers for their revision on the manuscript.
CR Altwegg R, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0141
   Angilletta MJ, 2003, TRENDS ECOL EVOL, V18, P234, DOI 10.1016/S0169-5347(03)00087-9
   Atkins KE, 2010, J THEOR BIOL, V266, P449, DOI 10.1016/j.jtbi.2010.07.014
   Barton K., 2020, MuMIn: Multi-model inference
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Briere JF, 1999, ENVIRON ENTOMOL, V28, P22, DOI 10.1093/ee/28.1.22
   Bush A, 2016, ECOL LETT, V19, P1468, DOI 10.1111/ele.12696
   Carnicer J, 2013, GLOBAL ECOL BIOGEOGR, V22, P6, DOI 10.1111/j.1466-8238.2012.00762.x
   Dapporto L, 2019, MOL ECOL RESOUR, V19, P1623, DOI 10.1111/1755-0998.13059
   Dapporto L, 2013, BIOL CONSERV, V157, P229, DOI 10.1016/j.biocon.2012.09.016
   DeLong JP, 2016, ECOL EVOL, V6, P935, DOI 10.1002/ece3.1959
   Dennis EB, 2013, METHODS ECOL EVOL, V4, P637, DOI 10.1111/2041-210X.12053
   Devictor V, 2012, NAT CLIM CHANGE, V2, P121, DOI 10.1038/NCLIMATE1347
   Dinca V, 2021, COMMUN BIOL, V4, DOI 10.1038/s42003-021-01834-7
   Dooley CA, 2013, ECOL ENTOMOL, V38, P608, DOI 10.1111/een.12055
   Eskildsen A, 2015, DIVERS DISTRIB, V21, P792, DOI 10.1111/ddi.12340
   Essens T, 2017, J INSECT CONSERV, V21, P439, DOI 10.1007/s10841-017-9972-4
   Fei SL, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1603055
   González-Suárez M, 2013, ECOSPHERE, V4, DOI 10.1890/ES12-00380.1
   Gonzalez-Voyer A., 2014, MODERN PHYLOGENETIC, P201, DOI [DOI 10.1007/978-3-662-43550-2_8, 10.1007/978-3-662-43550-2_8]
   Haeler E, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0111955
   Haldane JBS, 1930, J GENET, V22, P359, DOI 10.1007/BF02984197
   Hampe A, 2005, ECOL LETT, V8, P461, DOI 10.1111/j.1461-0248.2005.00739.x
   HAYLOCK MR, 2008, J GEOPHYS RES, V113, DOI DOI 10.1029/2008JD010201
   Herrando S., 2019, Scientific reports, V9, P1
   Hewitt GM., 2008, BIOL J LINN SOC, V68, P112
   Hu G, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2102762118
   Jentsch A, 2007, FRONT ECOL ENVIRON, V5, P365, DOI 10.1890/1540-9295(2007)5[365:ANGOCE]2.0.CO;2
   Kerr JT, 2015, SCIENCE, V349, P177, DOI 10.1126/science.aaa7031
   KINGSOLVER JG, 1983, AM NAT, V121, P32, DOI 10.1086/284038
   KINGSOLVER JG, 1991, AM NAT, V137, P816, DOI 10.1086/285195
   Klok EJ, 2009, INT J CLIMATOL, V29, P1182, DOI 10.1002/joc.1779
   Kraft NJB, 2015, FUNCT ECOL, V29, P592, DOI 10.1111/1365-2435.12345
   Krauss J, 2010, ECOL LETT, V13, P597, DOI 10.1111/j.1461-0248.2010.01457.x
   Long OM, 2017, J ANIM ECOL, V86, P108, DOI 10.1111/1365-2656.12594
   Macgregor CJ, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12479-w
   MacLean HJ, 2016, CONSERV PHYSIOL, V4, DOI 10.1093/conphys/cow035
   MacLean SA, 2017, GLOBAL CHANGE BIOL, V23, P4094, DOI 10.1111/gcb.13736
   Marsh T.J., 2004, WEATHER, V59, P224, DOI [DOI 10.1256/WEA.79.04, 10.1256/wea.79.04]
   Merlin C, 2019, J EXP BIOL, V222, DOI 10.1242/jeb.191890
   Metzger MJ, 2013, GLOBAL ECOL BIOGEOGR, V22, P630, DOI 10.1111/geb.12022
   Mills SC, 2017, GLOBAL ECOL BIOGEOGR, V26, P1374, DOI 10.1111/geb.12659
   Morlon H, 2011, ECOL LETT, V14, P141, DOI 10.1111/j.1461-0248.2010.01563.x
   Münkemüller T, 2012, METHODS ECOL EVOL, V3, P743, DOI 10.1111/j.2041-210X.2012.00196.x
   Oliver TH, 2015, NAT CLIM CHANGE, V5, P941, DOI [10.1038/nclimate2746, 10.1038/NCLIMATE2746]
   Pacifici M, 2017, NAT CLIM CHANGE, V7, P205, DOI 10.1038/NCLIMATE3223
   Pagel M, 1999, NATURE, V401, P877, DOI 10.1038/44766
   Palmer G, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0144
   Pandori LLM, 2019, OIKOS, V128, P621, DOI 10.1111/oik.05886
   Pfeifer SP, 2018, MOL BIOL EVOL, V35, P792, DOI 10.1093/molbev/msy004
   Pöyry J, 2009, GLOBAL CHANGE BIOL, V15, P732, DOI 10.1111/j.1365-2486.2008.01789.x
   POLLARD E, 1977, BIOL CONSERV, V12, P115, DOI 10.1016/0006-3207(77)90065-9
   POLLARD E, 1987, ECOLOGY, V68, P2046, DOI 10.2307/1939895
   Pöyry J, 2017, GLOBAL ECOL BIOGEOGR, V26, P18, DOI 10.1111/geb.12521
   Radchuk V, 2013, J ANIM ECOL, V82, P275, DOI 10.1111/j.1365-2656.2012.02029.x
   Razgour O, 2019, P NATL ACAD SCI USA, V116, P10418, DOI 10.1073/pnas.1820663116
   Reusch TBH, 2007, MOL ECOL, V16, P3973, DOI 10.1111/j.1365-294X.2007.03454.x
   Revell LJ, 2012, METHODS ECOL EVOL, V3, P217, DOI 10.1111/j.2041-210X.2011.00169.x
   Rothery P, 1997, OECOLOGIA, V112, P518, DOI 10.1007/s004420050340
   Roy DB, 2015, GLOBAL CHANGE BIOL, V21, P3313, DOI 10.1111/gcb.12920
   Roy DB., 2008, J ANIM ECOL, V70, P217
   Schmucki R, 2016, J APPL ECOL, V53, P501, DOI 10.1111/1365-2664.12561
   Shi PJ, 2010, J THERM BIOL, V35, P225, DOI 10.1016/j.jtherbio.2010.05.005
   Stefanescu C, 2011, ECOGRAPHY, V34, P353, DOI 10.1111/j.1600-0587.2010.06264.x
   Stephens PA, 2016, SCIENCE, V352, P84, DOI 10.1126/science.aac4858
   Suggitt AJ, 2012, BIOL LETTERS, V8, P590, DOI 10.1098/rsbl.2012.0112
   Thomas JA, 2005, PHILOS T R SOC B, V360, P339, DOI 10.1098/rstb.2004.1585
   Tigano A, 2016, MOL ECOL, V25, P2144, DOI 10.1111/mec.13606
   Titeux N, 2017, DIVERS DISTRIB, V23, P1393, DOI 10.1111/ddi.12634
   Tolman T, 2008, BUTTERFLIES EUROPE
   Trisos CH, 2020, NATURE, V580, P496, DOI 10.1038/s41586-020-2189-9
   Valladares F, 2014, ECOL LETT, V17, P1351, DOI 10.1111/ele.12348
   Van Dyck H, 2015, OIKOS, V124, P54, DOI 10.1111/oik.02066
   Vanden Broeck A, 2017, BIOL CONSERV, V209, P89, DOI 10.1016/j.biocon.2017.02.001
   Verdura J, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-41929-0
   Wiemers M, 2018, ZOOKEYS, P9, DOI 10.3897/zookeys.811.28712
   Zeuss D, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4874
NR 77
TC 11
Z9 13
U1 0
U2 17
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
EI 2399-3642
J9 COMMUN BIOL
JI Commun. Biol.
PD FEB 17
PY 2022
VL 5
IS 1
AR 143
DI 10.1038/s42003-022-03088-3
PG 9
WC Biology; Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Science & Technology - Other
   Topics
GA ZC4QJ
UT WOS:000757506400002
PM 35177761
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Shilengwe, C
   Banda, K
   Nyambe, I
AF Shilengwe, Christopher
   Banda, Kawawa
   Nyambe, Imasiku
TI Machine learning downscaling of GRACE/GRACE-FO data to capture
   spatial-temporal drought effects on groundwater storage at a local scale
   under data-scarcity
SO ENVIRONMENTAL SYSTEMS RESEARCH
LA English
DT Article
DE Barotse catchment; Drought; Downscaling; GRACE TWSA; Groundwater storage
   anomaly; Machine learning
ID SALINITY; BASIN; TIME
AB The continued threat from climate change and human impacts on water resources demands high-resolution and continuous hydrological data accessibility for predicting trends and availability. This study proposes a novel threefold downscaling method based on machine learning (ML) which integrates: data normalization; interaction of hydrometeorological variables; and the application of a time series split for cross-validation that produces a high spatial resolution groundwater storage anomaly (GWSA) dataset from the Gravity Recovery and Climate Experiment (GRACE) and its successor mission, GRACE Follow-On (GRACE-FO). In the study, the relationship between the terrestrial water storage anomaly (TWSA) from GRACE and other land surface and hydrometeorological variables (e.g., vegetation coverage, land surface temperature, precipitation, and in situ groundwater level data) is leveraged to downscale the GWSA. The predicted downscaled GWSA datasets were tested using monthly in situ groundwater level observations, and the results showed that the model satisfactorily reproduced the spatial and temporal variations in the GWSA in the study area, with Nash-Sutcliffe efficiency (NSE) correlation coefficient values of 0.8674 (random forest) and 0.7909 (XGBoost), respectively. Evapotranspiration was the most influential predictor variable in the random forest model, whereas it was rainfall in the XGBoost model. In particular, the random forest model excelled in aligning closely with the observed groundwater storage patterns, as evidenced by its high positive correlations and lower error metrics (Mean Absolute Error (MAE) of 54.78 mm; R-squared (R-2) of 0.8674). The downscaled 5 km GWSA data (based on random forest) showed a decreasing trend in storage associated with variability in the rainfall pattern. An increase in drought severity during El Ni & ntilde;o lengthened the full recovery time of groundwater based on historical storage trends. Furthermore, the time lag between the occurrence of precipitation and recharge was likely controlled by the drought intensity and the spatial recharge characteristics of the aquifer. Projected increases in drought severity could further increase groundwater recovery times in response to droughts in a changing climate, resetting storage to a new tipping condition. Therefore, climate change adaptation strategies must recognise that less groundwater will be available to supplement the surface water supply during droughts.
C1 [Shilengwe, Christopher] Natl Remote Sensing Ctr, Airport Rd, Lusaka, Zambia.
   [Shilengwe, Christopher; Banda, Kawawa; Nyambe, Imasiku] Univ Zambia, Integrated Water Resource Management Ctr, Sch Mines, Dept Geol, Lusaka, Zambia.
C3 University of Zambia
RP Shilengwe, C (corresponding author), Natl Remote Sensing Ctr, Airport Rd, Lusaka, Zambia.; Shilengwe, C (corresponding author), Univ Zambia, Integrated Water Resource Management Ctr, Sch Mines, Dept Geol, Lusaka, Zambia.
EM shilengwe93@gmail.com
RI Banda, Kawawa/JXN-6128-2024
OI Banda, Kawawa/0000-0001-7083-3014
FU Germany Federal Ministry of Education and Research
FX This work was supported by the Germany Federal Ministry of Education and
   Research-supported SASSCAL 2.0 project, Tipping Points Explained by
   Climate Change(TIPPECC).
CR Agarwal V, 2023, SCI TOTAL ENVIRON, V865, DOI 10.1016/j.scitotenv.2022.161138
   Ali S, 2021, Improving the Resolution of GRACE Data for Spatio-Temporal Groundwater Storage Assessment Remote Sens, V13, P3513, DOI [10.3390/rs13173513, DOI 10.3390/RS13173513]
   Ali S, 2024, GROUNDWATER SUST DEV, V25, DOI 10.1016/j.gsd.2024.101100
   Banda AM, 2021, Land Use change and its drivers in the wetlands of Barotse Floodplain of Zambezi River Sub-basin, DOI [10.21203/rs.3.rs-501786/v1, DOI 10.21203/RS.3.RS-501786/V1]
   Banda K, 2023, Geol Ecol Landsc., P1
   Banda KE, 2019, J AFR EARTH SCI, V153, P72, DOI 10.1016/j.jafrearsci.2019.02.022
   Beilfuss R., 2012, INT RIVERS, P1, DOI [10.13140/RG.2.2.30193.48486, DOI 10.13140/RG.2.2.30193.48486]
   Bhanja S, 2018, arXiv, DOI DOI 10.48550/ARXIV.1812.05519
   Bierkens MFP, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab1a5f
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Cai XL, 2017, PHYS CHEM EARTH, V100, P278, DOI 10.1016/j.pce.2016.10.011
   Chen C, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-60698-9
   Chen L, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11242979
   Chen TQ, 2016, KDD'16: PROCEEDINGS OF THE 22ND ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P785, DOI 10.1145/2939672.2939785
   Chomba IC., 2022, J Hum Earthand Future, V3, P2785, DOI DOI 10.28991/HEF-2022-03-02-09
   Chongo M, 2011, PHYS CHEM EARTH, V36, P798, DOI 10.1016/j.pce.2011.07.044
   Deng RL, 2022, WATER-SUI, V14, DOI 10.3390/w14233914
   Didan K., 2015, MOD13A2 MODIS/Terra Vegetation Indices 16-DayL3 Global 1km SIN Grid V006 Data set WWW Document, DOI [DOI 10.5067/MODIS/MOD13A2.006, 10.5067/MODIS/MOD13A2.061, DOI 10.5067/MODIS/MOD13A2.061]
   Rodríguez JD, 2010, IEEE T PATTERN ANAL, V32, P569, DOI 10.1109/TPAMI.2009.187
   Engelbrecht F, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/085004
   Fajar MHM., 2021, Indonesia Chem Eng Trans., V89, P385, DOI [10.3303/CET2189065, DOI 10.3303/CET2189065]
   Fan Y, 2013, SCIENCE, V339, P940, DOI 10.1126/science.1229881
   FAO, 2020, WaPOR V2 Database Methodology. Remote Sensing for Water Productivity Technical Report: Methodology Series
   Fatolazadeh F, 2022, J HYDROL, V615, DOI 10.1016/j.jhydrol.2022.128635
   Ferreira V, 2023, SCI DATA, V10, DOI 10.1038/s41597-023-02122-1
   Foroumandi E, 2023, J HYDROL, V616, DOI 10.1016/j.jhydrol.2022.128838
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Gemitzi A, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13245149
   Gleeson T, 2011, GEOPHYS RES LETT, V38, DOI [10.1029/2010GL045565, 10.1029/2010GL046427]
   Gong YC, 2015, WATER-SUI, V7, P6598, DOI 10.3390/w7116598
   Gstaiger V, 2012, INT J REMOTE SENS, V33, P7291, DOI 10.1080/01431161.2012.700421
   Hellwig J, 2018, HYDROL EARTH SYST SC, V22, P6209, DOI 10.5194/hess-22-6209-2018
   Huang J, 2015, NAT HAZARD EARTH SYS, V15, P2715, DOI 10.5194/nhess-15-2715-2015
   Humphrey V, 2023, SURV GEOPHYS, V44, P1489, DOI 10.1007/s10712-022-09754-9
   Izonin I, 2022, MATHEMATICS-BASEL, V10, DOI 10.3390/math10111942
   Jyolsna PJ, 2021, HYDROLOG SCI J, V66, P874, DOI 10.1080/02626667.2021.1896719
   Kalu I, 2024, SCI REP-UK, V14, DOI 10.1038/s41598-024-60366-2
   Khorrami B, 2023, EARTH SCI INFORM, DOI 10.1007/s12145-023-00964-2
   King RD, 2021, NAT MACH INTELL, V3, P276, DOI 10.1038/s42256-021-00332-z
   Kolusu SR, 2019, HYDROL EARTH SYST SC, V23, P1751, DOI 10.5194/hess-23-1751-2019
   Landerer FW, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011453
   Leasor ZT, 2020, Utilizing Objective Drought Severity thresholds to Improve Drought Monitoring, DOI [10.1175/JAMC-D-19-0217.1, DOI 10.1175/JAMC-D-19-0217.1]
   Li BL, 2015, J HYDROL, V526, P78, DOI 10.1016/j.jhydrol.2014.09.027
   Li J, 2011, ENVIRON MODELL SOFTW, V26, P1647, DOI 10.1016/j.envsoft.2011.07.004
   Liu YY, 2015, NAT CLIM CHANGE, V5, P470, DOI [10.1038/nclimate2581, 10.1038/NCLIMATE2581]
   Makungu E, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.127039
   Mapedza E, 2022, Current directions in Water Scarcity Research, Indigenous Water and Drought Management in a changing World, P209, DOI [10.1016/B978-0-12-824538-5.00011-X, DOI 10.1016/B978-0-12-824538-5.00011-X]
   Mathivha FI, 2024, ATMOSPHERE-BASEL, V15, DOI 10.3390/atmos15030249
   McNally A, 2022, EARTH SYST SCI DATA, V14, P3115, DOI 10.5194/essd-14-3115-2022
   Milewski A M., 2019, REMOTE SENS-BASEL, V11, P2756, DOI DOI 10.3390/rs11232756
   MILUPI ID, 2022, Impact and adaptation to flooding: a focus on water supply, sanitation, and health in rural communities on the Barotse floodplain in Zambia, DOI [10.21203/rs.3.rs-1283256/v1, DOI 10.21203/RS.3.RS-1283256/V1]
   Miro ME, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10010143
   Money NJ, 1972, , AN OUTLINE OF THE GEOLOGY OF, WESTERN ZAMBIA.
   Mupangwa W, 2023, CLIMATE, V11, DOI 10.3390/cli11040084
   Ndehedehe CE, 2023, SCI TOTAL ENVIRON, V904, DOI 10.1016/j.scitotenv.2023.166571
   Nenweli R, 2024, J HYDROL-REG STUD, V52, DOI 10.1016/j.ejrh.2024.101699
   Ning S, 2014, Statistical Downscaling of Grace-Derived Terrestrial Water Storage Using Satellite and Gldas Products, V70, pI133, DOI [10.2208/jscejhe.70.I133, DOI 10.2208/JSCEJHE.70.I133]
   Oiro S, 2020, HYDROGEOL J, V28, P2635, DOI 10.1007/s10040-020-02236-5
   Ouyang Z., 2021, Eng Proc, V5, P42, DOI DOI 10.3390/ENGPROC2021005042
   Pasqualino M., 2015, SEASONAL FOOD AVAILA
   Peixeiro M., 2022, Time series forecasting in python
   Puth MT, 2015, ANIM BEHAV, V102, P77, DOI 10.1016/j.anbehav.2015.01.010
   Rahaman MM, 2019, ENVIRONMENTS, V6, DOI 10.3390/environments6060063
   Rodell M, 2004, B AM METEOROL SOC, V85, P381, DOI 10.1175/BAMS-85-3-381
   Rodell M, 2009, NATURE, V460, P999, DOI 10.1038/nature08238
   Rodriguez-Galiano VF, 2012, ISPRS J PHOTOGRAMM, V67, P93, DOI 10.1016/j.isprsjprs.2011.11.002
   Sahour H, 2020, Statistical downscaling techniques to enhance the spatial resolution of the Grace Satellite Data and to fill temporal gaps
   Satizabal-Alarc DA, 2023, haracterization of groundwater storage changes in the Amazon River Basin based on downscaling of GRACE/GRACE-FO data with machine learning models
   Save H, 2016, J GEOPHYS RES-SOL EA, V121, P7547, DOI 10.1002/2016JB013007
   Scanlon BR, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011312
   Serdeczny O, 2017, REG ENVIRON CHANGE, V17, P1585, DOI 10.1007/s10113-015-0910-2
   Seyoum WM, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11070824
   Shilengwe C., 2023, Zambia ICT J, V7, P7, DOI [10.33260/zictjournal.v7i1.122, DOI 10.33260/ZICTJOURNAL.V7I1.122]
   Tao H, 2023, ATMOS RES, V291, DOI 10.1016/j.atmosres.2023.106815
   Tapley BD, 2019, NAT CLIM CHANGE, V9, P358, DOI 10.1038/s41558-019-0456-2
   Teng TP, 2024, CASE STUD THERM ENG, V53, DOI 10.1016/j.csite.2023.103924
   van der Schalie R, 2017, REMOTE SENS ENVIRON, V189, P180, DOI 10.1016/j.rse.2016.11.026
   Verdonck T, 2024, MACH LEARN, V113, P3917, DOI 10.1007/s10994-021-06042-2
   Wan Z., 2021, MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid V061 [Data set], DOI DOI 10.5067/MODIS/MOD11A1.061
   Wang JZ, 2015, WATER RESOUR RES, V51, P8658, DOI 10.1002/2015WR017104
   Xulu NG, 2020, CLIMATE, V8, DOI 10.3390/cli8070086
   Yazdian H, 2023, J HYDROL, V626, DOI 10.1016/j.jhydrol.2023.130214
   Yin WJ, 2022, J HYDROL, V613, DOI 10.1016/j.jhydrol.2022.128447
   Yin WJ, 2018, J GEOPHYS RES-ATMOS, V123, P5973, DOI 10.1029/2017JD027468
   Zaitchik BF, 2008, Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: results for the Mississippi River Basin, DOI [10.1175/2007JHM951.1, DOI 10.1175/2007JHM951.1]
   Zhang YP, 2022, J HYDROL, V609, DOI 10.1016/j.jhydrol.2022.127714
   Zhong DT, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13050900
   Zimba HM, 2024, HYDROL EARTH SYST SC, V28, P3633, DOI 10.5194/hess-28-3633-2024
   Zuo JP, 2021, PHYS CHEM EARTH, V123, DOI 10.1016/j.pce.2021.103042
NR 89
TC 1
Z9 1
U1 2
U2 2
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
EI 2193-2697
J9 ENVIRON SYST RES
JI Environ. Syst. Res.
PD SEP 3
PY 2024
VL 13
IS 1
AR 38
DI 10.1186/s40068-024-00368-1
PG 19
WC Environmental Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA M5K7F
UT WOS:001357929800001
OA gold
DA 2025-01-10
ER

PT J
AU Tormey, D
   Wei, DY
   Feng, AX
AF Tormey, Daniel
   Wei Dongying
   Feng Aixia
TI Geoheritage Education as a Gateway to Developing a Conservation Ethic in
   High School Students from China and the USA
SO GEOHERITAGE
LA English
DT Article
DE Conservation; Education; Geoheritage; Geoethics; International
   collaboration
ID CURRICULUM REFORM
AB A recent summary of geoheritage and protected area management as reported by Gordon (International Journal of Geoheritage and Parks 7:199-210, 2019) notes that a broader discipline has been emerging in geoheritage that recognizes the links to landscape and biodiversity conservation, economic development, climate change adaptation, sustainable management of land and water, historical and cultural heritage, and geotourism. Our focus in this study is to emphasize that geoheritage can serve as a gateway to developing a broader conservation ethic by developing educational programs that have a broader aim of interpretation, education, and enjoyment. Ultimately, these enjoyable educational experiences in areas of geoheritage value lead to a deeply felt conservation ethic. The US National Park Service recognizes the progression as "through interpretation, understanding; through understanding, appreciation; through appreciation, protection" as discussed by Tilden (1957). We have been working towards this goal through the expansion of a high school environmental education program in the USA, the National Conservation Foundation Envirothon, to China. The Envirothon is an environmental education program that culminates in the annual NCF-Envirothon Competition in which winning teams from participating states and Canadian provinces compete for recognition and scholarships by demonstrating their knowledge of environmental science and natural resource management. Much of the field education and field competitions are held in areas protected for their geoheritage and biodiversity values, and this use of geoheritage as a gateway to the broader educational goals is central to the program. We have been seeking to broaden the influence of the Envirothon program and underlying conservation goals in China. With educational curriculum reform since 2000 in China, students are encouraged to have more project-based learning opportunities and field-based experiences. The group at Beijing Normal University supports hundreds of high school partner programs. The Envirothon is a natural extension of this work and provides enhanced opportunities for international collaboration between the USA and China. Geoheritage value is a primary determinant of which areas are used for Envirothon field education and competitions; through this gateway, students from both countries will have educational, fun, and memorable experiences that will lead from understanding to appreciation to protection.
C1 [Tormey, Daniel] Catalyst Environm Solut Corp, Santa Monica, CA 90403 USA.
   [Wei Dongying; Feng Aixia] Beijing Normal Univ, Fac Geog, Beijing 100875, Peoples R China.
C3 Beijing Normal University
RP Tormey, D (corresponding author), Catalyst Environm Solut Corp, Santa Monica, CA 90403 USA.
EM dtormey@ce.solutions; weidy@bnu.edu.cn
CR Crofts R., 2020, BEST PRACT PROT AREA, V31, P144
   Gordon J.E., 2019, International Journal of Geoheritage and Parks, V7, P199, DOI [DOI 10.1016/J.IJGEOP.2019.12.005, 10.1016/j.ijgeop.2019.12.005]
   Law WW, 2014, J CURRICULUM STUD, V46, P332, DOI 10.1080/00220272.2014.883431
   NCF Envirothon, 2019, KNOWL SKILLS CHANG W
   Qian HY, 2013, ASIA-PAC J TEACH EDU, V41, P304, DOI 10.1080/1359866X.2013.809050
   Sharples C., 2002, CONCEPTS PRINCIPLES
   Tilden Freeman., 1957, INTERPRETING OUR HER
   Yin HB, 2014, EDUC MANAG ADM LEAD, V42, P293, DOI 10.1177/1741143213499261
NR 8
TC 5
Z9 5
U1 3
U2 20
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1867-2477
EI 1867-2485
J9 GEOHERITAGE
JI Geoheritage
PD SEP
PY 2022
VL 14
IS 3
AR 79
DI 10.1007/s12371-022-00713-9
PG 6
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA 2H9WQ
UT WOS:000814637600001
DA 2025-01-10
ER

PT J
AU Nakayama, M
   Fujikura, R
   Okuda, R
   Fujii, M
   Takashima, R
   Murakawa, T
   Sakai, E
   Iwama, H
AF Nakayama, Mikiyasu
   Fujikura, Ryo
   Okuda, Rie
   Fujii, Mai
   Takashima, Ryuta
   Murakawa, Tomoya
   Sakai, Erika
   Iwama, Hiroaki
TI Alternatives for the Marshall Islands to Cope with the Anticipated Sea
   Level Rise by Climate Change
SO JOURNAL OF DISASTER RESEARCH
LA English
DT Article
DE atoll country; climate change adaptation; Marshall Islands; migration;
   sea level rise
ID ADAPTATION; MIGRATION
AB There are four atoll states in the world: The Republic of Kiribati, the Maldives, the Republic of the Marshall Islands (RMI), and Tuvalu. These countries are comprised entirely of low-lying land approximately 2 m above sea level. The Intergovernmental Panel on Climate Change (IPCC) has recognized that atoll countries are highly vulnerable to rising sea levels due to climate change. This study aimed to clarify the relative advantages and disadvantages of possible alternatives compared to the present livelihoods of the Marshallese in their home country. We also attempted to identify the best plausible option, using few sets of possible value judgements over the evaluation criteria. The following four alternatives were examined in this study: (i) migration to the developed world, (ii) migration to other island states, (iii) land reclamation and raising, and (iv) development of floating platforms. To evaluate the performance of the four alternatives, we selected 16 criteria representing the societal conditions that would result from each alternative. The performance of each alternative per criterion was rated from 1 to 5 by a literature survey, interviews with researchers who worked on the livelihood of Marshallese immigrants in the U.S. states of Arkansas, Hawaii, and Oregon, and interviews with people knowledgeable about the behavior of the Marshallese both in their home country and in the United States as immigrants. The "migration to the developed world" alternative proved the best choice, followed by "developing floating platforms," "land reclamation and raising," and "migration to other island states." We also found that "migration to the developed world" offered the most change to immigrants, while the alternative of "land reclamation and raising" resulted in the smallest change. The magnitude of anticipated change should be considered. We employed the Analytic Hierarchy Process (AHP) to experimentally evaluate four alternatives in an integrated manner and about three cases were "all the criteria are equally important," "social environment is more important," and "personal environment is more important." With AHP, the "migration to the developed world" alternative yielded the highest point for all three cases examined. Notably, climate migrants do not suddenly emerge, because climate change is a slow-onset process. The Marshallese should make wise use of the available lead time to prepare for migration in the future.
C1 [Nakayama, Mikiyasu; Murakawa, Tomoya; Sakai, Erika; Iwama, Hiroaki] Global Infrastruct Fund Res Fdn Japan, Minato Ku, Roppongi T Cube 14F,3-1-1 Roppongi, Tokyo 1060032, Japan.
   [Fujikura, Ryo] Hosei Univ, Fac Sustainabil Studies, Tokyo, Japan.
   [Okuda, Rie] Kobe Univ, Grad Sch Int Cooperat Studies, Kobe, Hyogo, Japan.
   [Fujii, Mai] Sasakawa Peace Fdn, Ocean Policy Res Inst, Tokyo, Japan.
   [Takashima, Ryuta] Tokyo Univ Sci, Dept Ind Adm, Chiba, Japan.
C3 Hosei University; Kobe University; Tokyo University of Science
RP Nakayama, M (corresponding author), Global Infrastruct Fund Res Fdn Japan, Minato Ku, Roppongi T Cube 14F,3-1-1 Roppongi, Tokyo 1060032, Japan.
EM m.nakayama@gif.or.jp
RI Fujikura, Ryo/M-9718-2013
OI Fujikura, Ryo/0000-0002-0742-0767
FU Global Infrastructure Fund Research Foundation Japan (GIF Japan); Ocean
   Policy Research Institute of The Sasakawa Peace Foundation (OPRI-SPF);
   JSPS KAKENHI [19KK0025, 21H03711]; Grants-in-Aid for Scientific Research
   [21H03711, 19KK0025] Funding Source: KAKEN
FX The authors would like to express their sincere appreciation to the
   Global Infrastructure Fund Research Foundation Japan (GIF Japan) and the
   Ocean Policy Research Institute of The Sasakawa Peace Foundation
   (OPRI-SPF) for their support of this study. We would like to thank all
   the informants who provided us with valuable input and observations.
   This study was also supported by JSPS KAKENHI (Grant Numbers 19KK0025
   and 21H03711). Lastly, we very much appreciate the assistance provided
   by Ms. Ayane Komeichi and Ms. Rion Miyauchi, Research Associates of GIF
   Japan.
CR Adger WN, 2005, NATURE, V436, P328, DOI 10.1038/436328c
   [Anonymous], AM J MED SCI, DOI [DOI 10.1007/s11270-007-9372-6, DOI 10.1016/J.AMJMS.2021.03.001,00089-6]
   [Anonymous], GDP PER CAP
   Asian Development Bank (ADB),, 2018, 51077002 ADB
   Barnett J, 2003, CLIMATIC CHANGE, V61, P321, DOI 10.1023/B:CLIM.0000004559.08755.88
   Bauer T. K., 2002, IZA DISCUSSION PAPER, V551
   Biermann F, 2018, ROUTL STUD ENV MIGR, P265
   Biermann F, 2008, ENVIRONMENT, V50, P8
   Brown S, 2020, J FLOOD RISK MANAG, V13, DOI 10.1111/jfr3.12567
   Campbell John., 2010, Climate Change and Displacement: Multidisciplinary Perspectives
   Department of Business Economic Development & Tourism State of Hawaii, 2020, COFA MIGR HAW
   Department of State United States of America, 2003, COMP FREE ASS
   Department of Statistics Int. Labour Organization (ILO), 2021, STAT SOC PROT
   East-West Center, 2021, CLIM HLTH MIGR MARSH
   Esteban M, 2019, OCEAN COAST MANAGE, V168, P35, DOI 10.1016/j.ocecoaman.2018.10.031
   Farbotko C., 2019, DEALING CLIMATE CHAN, P251, DOI DOI 10.17875/GUP2019-1219
   Food and Agriculture Organization of the United Nations (FAO), 2021, REP MARSH ISL FOOD S
   Greussing E, 2017, J ETHN MIGR STUD, V43, P1749, DOI 10.1080/1369183X.2017.1282813
   International Organization for Migration (IOM),, 2020, MIGR REP FIJ COUNTR
   Ives M., 2016, REMOTE PACIFIC NATIO
   Johnson G, 2019, MARSHALL ISLANDS J, V50
   Kurosaki T, 2012, THESIS WASEDA U
   Kuroyanagi A., 2018, J RES I SCI TECHNOLO, V142, P19
   Lamas-Pardo M, 2015, OCEAN ENG, V109, P677, DOI 10.1016/j.oceaneng.2015.09.012
   Maekawa M, 2019, J DISASTER RES, V14, P1277, DOI 10.20965/jdr.2019.p1277
   Marshall Islands Journal,, 2019, MARSHALL ISLANDS J, V50
   Marshall Islands Journal,, 2021, MARSHALL ISLANDS J, V52
   McAdam J., 2016, OXFORD HDB INT CLIMA, P519
   McCarney R, 2020, INT J-TORONTO, V75, P652, DOI 10.1177/0020702020968944
   McClain SN, 2022, J DISASTER RES, V17, P292, DOI 10.20965/jdr.2022.p0292
   Ministry of Foreign Affair of Japan, 2021, FIJ KYOW KIH DET
   Mohit M. A., 2018, ASIAN J ENV BEHAV ST, V3, P125
   Moriya K, 2019, J DISASTER RES, V14, P1293, DOI 10.20965/jdr.2019.p1293
   Mortreux C, 2009, GLOBAL ENVIRON CHANG, V19, P105, DOI 10.1016/j.gloenvcha.2008.09.006
   Nakayama M, 2019, J DISASTER RES, V14, P1246, DOI 10.20965/jdr.2019.p1246
   National Bureau of Statistics Ministry of National Planning Housing and Infrastructure Republic of Maldives, 2020, STAT POCK MALD 2020
   Pasifika Environews,, 2019, US 29000000 ALL NEW
   Radio New Zealand,, 2018, RAD NZ
   Regional Pacific NDC Hub,, EX SUMM STRAT 2030 B
   Rokoduru A, 2006, GLOBLISATION GOVERNA
   SAATY TL, 1990, EUR J OPER RES, V48, P9, DOI 10.1016/0377-2217(90)90057-I
   Sakamoto A, 2022, J DISASTER RES, V17, P327, DOI 10.20965/jdr.2022.p0327
   Shimbun Asahi, 2019, SEKAI ICHI SHIAWASE
   Shimizu Corporation, 2021, KANK AIR GREEN FLOAT
   Sovacool BK, 2012, CLIMATIC CHANGE, V114, P295, DOI 10.1007/s10584-011-0392-2
   SPREP, 2021, MARSH ISL TELLS COP2
   Suzuki K, 2009, OPERATIONS RES
   The Intergovernmental Panel on Climate Change (IPCC), GLOB WARM 1 5 C IMP
   The Seasteading Institute, 2021, WHO WE AR
   The World Bank, 2021, IND US INT POP MARSH
   The World Bank Maldives Urban Development and Resilience Project (P163957), 2019, P163957 WORLD BANK
   United Nations,, 2019, SUST FLOAT CIT CAN O
   Wheeler B.L., 2020, Marshallese migration: comparative well-being in U.S. Destination States. Policy Brief of the Marshall islands climate and migration project
   William S., 2020, MARSHALL ISLANDS CLI
   Willis DE, 2020, PUBLIC HEALTH NUTR, V23, P544, DOI 10.1017/S1368980019002647
   Wyman K. M., 2016, ELGAR ENCY ENV LAW, P637
   Yamamoto L, 2017, INT MIGR, V55, P144, DOI 10.1111/imig.12318
   Yoshioka N, 2019, J DISASTER RES, V14, P1287, DOI 10.20965/jdr.2019.p1287
NR 58
TC 4
Z9 4
U1 3
U2 17
PU FUJI TECHNOLOGY PRESS LTD
PI TOKYO
PA 1-15-7, UCHIKANDA, CHIYODA-KU, UNIZO UCHIKANDA 1-CHOME BLDG 2F, TOKYO,
   101-0047, JAPAN
SN 1881-2473
EI 1883-8030
J9 J DISASTER RES
JI J. Disaster Res.
PD APR
PY 2022
VL 17
IS 3
BP 315
EP 326
DI 10.20965/jdr.2022.p0315
PG 12
WC Geosciences, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Geology
GA 0J1PV
UT WOS:000779880200006
OA gold
DA 2025-01-10
ER

PT J
AU Oliveira, A
   Lopes, A
   Correia, E
   Niza, S
   Soares, A
AF Oliveira, Ana
   Lopes, Antonio
   Correia, Ezequiel
   Niza, Samuel
   Soares, Amilcar
TI An urban climate-based empirical model to predict present and future
   patterns of the Urban Thermal Signal
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Urban climate change adaptation; Heatwaves; Urban Heat Island; Urban
   health; Local climate zones; Linear-mixed models
ID HEAT-ISLAND; PORTUGAL; WAVES; IMPACT
AB Air temperature is a key aspect of urban environmental health, especially considering population and climate change prospects. While the urban heat island (UHI) effect may aggravate thermal exposure, city-level UHI regression studies are generally restricted to temporal-aggregated intensities (e.g., seasonal), as a function of time-fixed factors (e.g., urban density). Hence, such approaches do not disclose daily urban-rural air temperature changes, such as during heatwaves (HW). Here, summer data from Lisbons air temperature urban network (June to September 2005-2014), is used to develop a linear mixed-effects model (LMM) to predict the daily median and maximum Urban Thermal Signal (UTS) intensities, as a response to the interactions between the timevarying background weather variables (i.e., the regional/non-urban air temperature, 2-hours air temperature change, and wind speed), and time-fixed urban and geographic factors (local climate zones and directional topographic exposure). Results show that, in Lisbon, greatest temperatures and UTS intensities are found in 'Compact' areas of the city are proportional to the background air temperature change. In leeward locations, the UTS can be enhanced by the topographic shelter effect, depending on wind speed-i.e., as wind speed augments, the UTS intensity increases in leeward sites, even where sparsely built. The UTS response to a future urban densification scenario, considering climate change HW conditions (RCP8.5, 2081-2100 period), was also assessed, its results showing an UTS increase of circa 1.0 degrees C, in critical areas of the city, despite their upwind location. This LMM empirical approach provides a straightforward tool for local authorities to: (i) identify the short-term critical areas of the city, to prioritise public health measures, especially during HW events; and (ii) test the urban thermalperformance, in response to climate change and urban planning scenarios. While the model coefficient estimates are case-specific, the approach can be efficiently replicated in other locations with similar biogeographic conditions. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
C1 [Oliveira, Ana; Niza, Samuel] Univ Lisbon, Inst Super Tecn, IN Ctr Innovat Technol & Policy Res, Av Rovisco Pais 1, P-1049001 Lisbon, Portugal.
   [Lopes, Antonio; Correia, Ezequiel] Univ Lisbon, IGOT Inst Geog & Ordenamento Terr, Ctr Estudos Geog, Lisbon, Portugal.
   [Soares, Amilcar] Univ Lisbon, Inst Super Tecn, CERENA, Lisbon, Portugal.
C3 Universidade de Lisboa; Universidade de Lisboa; Universidade de Lisboa
RP Oliveira, A (corresponding author), Univ Lisbon, Inst Super Tecn, IN Ctr Innovat Technol & Policy Res, Av Rovisco Pais 1, P-1049001 Lisbon, Portugal.
EM anappmoliveira@tecnico.ulisboa.pt; antonio.lopes@campus.ul.pt;
   ezequielc@campus.ul.pt; samuel.niza@tecnico.ulisboa.pt;
   asoares@tecnico.ulisboa.pt
RI Oliveira, Ana/AAI-8860-2021; Correia, Ezequiel/AAI-3573-2021; Soares,
   Amilcar/H-9997-2012; Lopes, Antonio/F-3217-2010; Correia,
   Ezequiel/D-2959-2017; Niza, Samuel/A-6592-2009
OI soares, amilcar/0009-0009-0665-8149; Lopes, Antonio/0000-0002-9357-7639;
   Correia, Ezequiel/0000-0002-4026-7020; Niza, Samuel/0000-0003-0679-4027;
   Oliveira, Ana/0000-0003-1564-2180
FU Fundacao para a Ciencia e Tecnologia (FCT) - Portugal
   [PD/BD/52304/2013]; Fundação para a Ciência e a Tecnologia
   [PD/BD/52304/2013] Funding Source: FCT
FX This work was supported by the "Fundacao para a Ciencia e Tecnologia
   (FCT) -Portugal", [Ph.D. grant number PD/BD/52304/2013].
CR Alcoforado M.J, 1992, MEMORIAS CTR ESTUDOS
   Alcoforado M.J., 2013, Assessing and Modeling the Urban Climate in Lisbon', Geographical Information and Climatology Edition, DOI [DOI 10.1002/9781118557600.CH5, 10.1002/9781118557600.ch5]
   Alcoforado MJ, 2009, LANDSCAPE URBAN PLAN, V90, P56, DOI 10.1016/j.landurbplan.2008.10.006
   Alcoforado MJ, 2006, THEOR APPL CLIMATOL, V84, P151, DOI 10.1007/s00704-005-0152-1
   ALEXANDER L., 2016, ClimPACT2: Indices and software
   [Anonymous], 2015, DOCUMENT PREPARED BE
   [Anonymous], 2014, FINISTERRA 98
   [Anonymous], 2010, P 15 S MET OBS INSTR
   [Anonymous], 2012, Climate change, impacts and vulnerability in Europe 2012 - An indicator-based report
   [Anonymous], 2000, LINEAR MIXED MODELS
   [Anonymous], 2017, BUILD SERV ENG RES T
   Bates D., 2007, LINEAR MIXED MODEL I
   Bates D., 2007, R PACKAGE
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Beniston M, 2007, CLIMATIC CHANGE, V81, P71, DOI 10.1007/s10584-006-9226-z
   Chapman L, 2000, METEOROL APPL, V7, P335, DOI 10.1017/S1350482700001729
   Chrysoulakis N, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-29873-x
   CML,, 2012, PLAN MUN LISB DIAR R
   Correia E, 2018, PLANO METROPOLITANO, P71
   Correia E, 2019, MAPAS CLIMATICOS URB
   Droste AM, 2020, Q J ROY METEOR SOC, V146, P2671, DOI 10.1002/qj.3811
   Du SH, 2016, REMOTE SENS ENVIRON, V178, P84, DOI 10.1016/j.rse.2016.02.063
   EEA, 2018, TREE COV DENS
   European Environment Agency (EEA), 2018, IMP DENS
   European Environment Agency (EEA), 2018, BUILD HEIGHT 2012
   Feigenwinter C, 2018, IEEE J-STARS, V11, P2717, DOI 10.1109/JSTARS.2018.2807815
   Founda D, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-11407-6
   Fragoso M, 2020, LOCAL WEATHER TYPES, DOI [10.3390/ATMOS11080840, DOI 10.3390/ATMOS11080840]
   Geletic J, 2018, SCI TOTAL ENVIRON, V624, P385, DOI 10.1016/j.scitotenv.2017.12.076
   GELMAN A, 2006, DATA ANAL USING REGR, P503, DOI DOI 10.1017/CBO9780511790942.029
   Giorgi F, 2005, CLIMATIC CHANGE, V73, P239, DOI 10.1007/a10584-005-6857-4
   Heaviside C, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0100-9
   Ivajnsic D, 2014, APPL GEOGR, V53, P341, DOI 10.1016/j.apgeog.2014.07.001
   Koppen W., 1931, GRUNDRISSE KLIMAKUND
   Krayenhoff E. S, 2021, HIGHRESOLUTION MODEL, DOI [10.3390/atmos12020175, DOI 10.3390/ATMOS12020175]
   Krivoruchko K., 2023, Arcuser
   Levermore G, 2019, BUILD SERV ENG RES T, V40, P290, DOI 10.1177/0143624418822878
   Leys C, 2018, J EXP SOC PSYCHOL, V74, P150, DOI 10.1016/j.jesp.2017.09.011
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Li Y, 2019, FEATURES URBAN HEAT, DOI [10.3390/atmos10020067, DOI 10.3390/ATMOS10020067]
   Lindley S., 2015, BUILD SERV ENG RES T
   Lopes A, 2011, ENVIRON MODELL SOFTW, V26, P241, DOI 10.1016/j.envsoft.2010.05.015
   Lopes A., 2003, CHANGES LISBONS URBA
   Lopes A, 2013, ADV METEOROL, V2013, DOI 10.1155/2013/487695
   Lott J.N, 2004, B AM METEOROL SOC
   LOWRY WP, 1977, J APPL METEOROL, V16, P129, DOI 10.1175/1520-0450(1977)016<0129:EEOUEO>2.0.CO;2
   Meier F., 2015, ICUC9 9 INT C URB CL, V7
   Mihalakakou G, 2004, PURE APPL GEOPHYS, V161, P429, DOI 10.1007/s00024-003-2447-4
   Milosevic D, 2022, INT J BIOMETEOROL, V66, P371, DOI 10.1007/s00484-020-02058-w
   Napoly A, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00118
   Nipen TN, 2020, B AM METEOROL SOC, V101, pE43, DOI 10.1175/BAMS-D-18-0237.1
   Niza S., 2020, LOCAL CLIMATE ZONES, V31
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Oke T.R., 1987, BOUNDARY LAYER CLIMA, DOI DOI 10.1017/CBO9781107415324.004
   OKE TR, 1988, PROG PHYS GEOG, V12, P471, DOI 10.1177/030913338801200401
   Oliveira A, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12030292
   Oliveira A, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100631
   Oliveira S, 2007, GEOPHILIA SENTIR SEN
   Parente J, 2018, SCI TOTAL ENVIRON, V631-632, P534, DOI 10.1016/j.scitotenv.2018.03.044
   Parison S, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100651
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   R Core Team R, 2013, R: A language and environment for statistical computing
   Ramamurthy P, 2017, THEOR APPL CLIMATOL, V128, P89, DOI 10.1007/s00704-015-1703-8
   Reis C., 2020, IDENTIFICACAO ILHAS
   Reis C, 2020, LISBOA
   Santo FE, 2014, INT J CLIMATOL, V34, P1814, DOI 10.1002/joc.3803
   Shi Y, 2018, SCI TOTAL ENVIRON, V618, P891, DOI 10.1016/j.scitotenv.2017.08.252
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Szymanowski M, 2012, THEOR APPL CLIMATOL, V108, P53, DOI 10.1007/s00704-011-0517-6
   Tan JG, 2010, INT J BIOMETEOROL, V54, P75, DOI 10.1007/s00484-009-0256-x
   Team A, 2009, ASTER GLOBAL VALIDAT
   Tolika K, 2019, CLIMATE, V7, DOI 10.3390/cli7010009
   Vaughn BK, 2008, J EDUC MEAS, V45, P94, DOI 10.1111/j.1745-3984.2007.00053_2.x
   Wicki A, 2018, CLIMATE, V6, DOI 10.3390/cli6030055
   Wicki A, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9070684
   Zhou Y, 2010, NAT HAZARDS, V52, P639, DOI 10.1007/s11069-009-9406-z
   Zuur Alain F., 2009, P1
NR 77
TC 13
Z9 13
U1 1
U2 15
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD OCT 10
PY 2021
VL 790
AR 147710
DI 10.1016/j.scitotenv.2021.147710
EA JUN 2021
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA UA6QS
UT WOS:000685285400001
PM 34111797
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Schäfer, J
   Friedel, M
   Molitor, D
   Stoll, M
AF Schaefer, Jan
   Friedel, Matthias
   Molitor, Daniel
   Stoll, Manfred
TI Semi-Minimal-Pruned Hedge (SMPH) as a Climate Change Adaptation
   Strategy: Impact of Different Yield Regulation Approaches on Vegetative
   and Generative Development, Maturity Progress and Grape Quality in
   Riesling
SO APPLIED SCIENCES-BASEL
LA English
DT Article
DE SMPH; training systems; climate change; crop thinning; maturity
   progress; maturity delay; velocity of ripening; primary fruit components
ID LEAF REMOVAL; ELEVATED-TEMPERATURE; CANOPY ARCHITECTURE; EARLY
   DEFOLIATION; FRUIT COMPOSITION; WINE QUALITY; CLUSTER-ZONE; VINIFERA;
   BERRIES; ALTERS
AB The training system Semi-Minimal-Pruned Hedge (SMPH) blends features of traditional Vertical Shoot Positioning-type (VSP) trellising systems with the concept of minimal pruning. While saving labor, this training system results in relatively high crop load and a poor leaf area to fruit weight-ratio (LFR), and thus, needs to be able to ripen grapes in a cool to moderate climate. For these reasons the impact of yield regulation strategies, including (i) shoot thinning (Darwin-Rotor), (ii) biotechnological thinning (Gibberellic acid), and (iii) bunch thinning (harvest machine) were trialed in a three year study at Geisenheim, Germany between 2017 and 2019 using Riesling (Vitis vinifera L.). The average yield per vine in SMPH (5.34 +/- 1.10 kg) was 61.1% higher with a narrower LFR (14.01 cm(2) g(-1)), compared with VSP (3.32 +/- 1.02 kg, LFR: 16.99 cm(2) g(-1)). The yield was successfully reduced and LFR simultaneously increased with shoot thinning (-33.1%, LFR: 19.04 cm(2) g(-1)), biotechnological thinning (-18.3%, LFR: 16.69 cm(2) g(-1)) and bunch thinning (-37.3%, LFR: 21.49 cm(2) g(-1)). Ripening was delayed in SMPH. On average, two maturity thresholds (14.1 degrees Brix and 18.2 degrees Brix) were achieved 129 GDD (seven days according to the recorded daily mean temperatures, respectively) and 269 GDD (16 days) later in non-thinned SMPH, compared to VSP. All thinning treatments accelerated maturity progress ranging from 27 GDD (two days) to 58 GDD (three days) for 14.1 degrees Brix and 59 GDD (three days) to 105 GDD (six days) for 18.2 degrees Brix. Apart from immediate benefits on the economic efficiency, the adaption of the leaf area to fruit weight ratio using SMPH holds high potential to, (i) produce grapes targeting specific wine profiles and/or (ii) reducing the velocity of ripening under conditions of climatic change.
C1 [Schaefer, Jan; Friedel, Matthias; Stoll, Manfred] Hsch Geisenheim Univ, Dept Gen & Organ Viticulture, Von Lade Str 1, D-65366 Geisenheim, Germany.
   [Molitor, Daniel] Luxembourg Inst Sci & Technol, Environm Res & Innovat ERIN Dept, 41 Rue Brill, L-4422 Belvaux, Luxembourg.
C3 Luxembourg Institute of Science & Technology
RP Schäfer, J (corresponding author), Hsch Geisenheim Univ, Dept Gen & Organ Viticulture, Von Lade Str 1, D-65366 Geisenheim, Germany.
EM jan.schaefer@hs-gm.de; matthias.friedel@hs-gm.de;
   daniel.molitor@list.lu; manfred.stoll@hs-gm.de
RI Friedel, Matthias/AFV-1955-2022
OI Friedel, Matthias/0000-0003-4211-5327; Molitor,
   Daniel/0000-0001-7487-6740
FU BMBF (Federal Ministry of Education and Research) of the project NoViSys
   [Novel viticulture systems for sustainable production and products
   project] [031A349G]
FX We acknowledge the financial support by the BMBF (Federal Ministry of
   Education and Research) of the project NoViSys [Novel viticulture
   systems for sustainable production and products project; number
   031A349G]. Furthermore, we acknowledge the technical and laboratory team
   of the Department of General and Organic Viticulture and the Department
   of Beverage Technology of Geisenheim University for their indispensable
   help in conducting the experiments and supporting the analyses.
CR Becker T, 2012, VITIS, V51, P1
   Böttcher C, 2011, AUST J GRAPE WINE R, V17, P1, DOI 10.1111/j.1755-0238.2010.00110.x
   Clingeleffer PR, 2010, AUST J GRAPE WINE R, V16, P25, DOI 10.1111/j.1755-0238.2009.00075.x
   Coombe B. G., 1995, Australian Journal of Grape and Wine Research, V1, P104, DOI 10.1111/j.1755-0238.1995.tb00086.x
   Döring J, 2014, AM J ENOL VITICULT, V65, P153, DOI 10.5344/ajev.2013.13073
   Duchêne E, 2005, AGRON SUSTAIN DEV, V25, P93, DOI 10.1051/agro:2004057
   Duchêne E, 2010, CLIM RES, V41, P193, DOI 10.3354/cr00850
   Dukes BC, 1998, AM J ENOL VITICULT, V49, P125
   Fraga H, 2016, GLOBAL CHANGE BIOL, V22, P3774, DOI 10.1111/gcb.13382
   Friedel M, 2015, VITIS, V54, P107
   Friedel M, 2019, DTSCH WEINBAU JB, V2018, P76
   Gatti M, 2016, AUST J GRAPE WINE R, V22, P245, DOI 10.1111/ajgw.12212
   Hed B, 2021, PLANT DIS, V105, P339, DOI 10.1094/PDIS-06-20-1184-RE
   Hed B, 2011, PLANT DIS, V95, P269, DOI 10.1094/PDIS-05-10-0382
   Herzog K, 2015, SENSORS-BASEL, V15, P12498, DOI 10.3390/s150612498
   Hoppmann D., 2007, PERSPECTIVES CLIMATI, V106th
   Intrieri C, 2008, AUST J GRAPE WINE R, V14, P25, DOI 10.1111/j.1755-0238.2008.00004.x
   Intrieri C, 2001, VITIS, V40, P123
   Intrieri C, 2011, AM J ENOL VITICULT, V62, P312, DOI 10.5344/ajev.2011.10083
   Jones GV, 2005, CLIMATIC CHANGE, V73, P319, DOI 10.1007/s10584-005-4704-2
   Kliewer WM, 2005, AM J ENOL VITICULT, V56, P170
   Kraus C, 2018, VITIS, V57, P53, DOI 10.5073/vitis.2018.57.53-60
   Lopes C, 2000, ACTA HORTIC, P261, DOI 10.17660/ActaHortic.2000.526.27
   MARAIS J, 1992, South African Journal for Enology and Viticulture, V13, P23
   de Toda FM, 2019, VITIS, V58, P17, DOI 10.5073/vitis.2019.58.17-22
   MATTHEWS MA, 1988, AM J ENOL VITICULT, V39, P313
   Molitor D, 2011, J INT SCI VIGNE VIN, V45, P149
   Molitor D., 2016, RIESLING GRAPES OENO, V50, P244, DOI [10.20870/oeno-one.2016.50.3.36, DOI 10.20870/OENO-ONE.2016.50.3.36]
   Molitor D, 2019, OENO ONE, V53, P409, DOI 10.20870/oeno-one.2019.53.3.2329
   Molitor D, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9040173
   Molitor D, 2015, AM J ENOL VITICULT, V66, P164, DOI 10.5344/ajev.2014.14052
   Moran M, 2019, AM J ENOL VITICULT, V70, P9, DOI 10.5344/ajev.2018.18031
   Muller E., 2008, WEINBAU, V3rd
   NAIR NG, 1993, MYCOL RES, V97, P1012, DOI 10.1016/S0953-7562(09)80871-X
   Naor A, 2002, J AM SOC HORTIC SCI, V127, P628, DOI 10.21273/JASHS.127.4.628
   Ogle D. H  ..., 2020, FSA: Fisheries stock analysis
   Ollat N, 1998, AM J ENOL VITICULT, V49, P251
   Palliotti A, 2013, AUST J GRAPE WINE R, V19, P369, DOI 10.1111/ajgw.12033
   Palliotti A, 2017, AM J ENOL VITICULT, V68, P412, DOI 10.5344/ajev.2017.17011
   Parker AK, 2016, VITIS, V55, P1, DOI 10.5073/vitis.2016.55.1-9
   Parker AK, 2015, AUST J GRAPE WINE R, V21, P266, DOI 10.1111/ajgw.12132
   Parker AK, 2011, AUST J GRAPE WINE R, V17, P206, DOI 10.1111/j.1755-0238.2011.00140.x
   Poling EB, 2008, HORTSCIENCE, V43, P1652, DOI 10.21273/HORTSCI.43.6.1652
   Poni S, 2013, AUST J GRAPE WINE R, V19, P378, DOI 10.1111/ajgw.12040
   Poni S, 2006, AM J ENOL VITICULT, V57, P397
   Pons A, 2017, OENO ONE, V51, P141, DOI 10.20870/oeno-one.2016.0.0.1868
   Santos JA, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10093092
   Schüttler A, 2015, BIO WEB CONF, V5, DOI 10.1051/bioconf/20150501006
   Schultz H.R, 2016, GEOGR RUNDSCH, V3, P20
   Silvestroni O, 2018, AUST J GRAPE WINE R, V24, P478, DOI 10.1111/ajgw.12361
   Stoll M., 2010, Progres Agricole et Viticole, V127, P68
   Sweetman C, 2014, J EXP BOT, V65, P5975, DOI 10.1093/jxb/eru343
   Thim G, 2020, DTSCH WEINMAG, V26, P28
   van Leeuwen C, 2016, J WINE ECON, V11, P150, DOI 10.1017/jwe.2015.21
   Walg O., 2018, DTSCH WEINBAU, V12, P28
   Wang XY, 2019, AM J ENOL VITICULT, V70, P360, DOI 10.5344/ajev.2019.19007
   Weyand KA, 2006, J INT SCI VIGNE VIN, V40, P151
   Yuan F, 2015, ACS SYM SER, V1203, P147
   Zheng W, 2017, AM J ENOL VITICULT, V68, P136, DOI 10.5344/ajev.2016.16038
NR 59
TC 9
Z9 10
U1 0
U2 17
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2076-3417
J9 APPL SCI-BASEL
JI Appl. Sci.-Basel
PD APR
PY 2021
VL 11
IS 8
AR 3304
DI 10.3390/app11083304
PG 20
WC Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials
   Science, Multidisciplinary; Physics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Engineering; Materials Science; Physics
GA RS8DP
UT WOS:000644003900001
OA gold
DA 2025-01-10
ER

PT J
AU Abdulrasheed, M
   MacKenzie, AR
   Whyatt, JD
   Chapman, L
AF Abdulrasheed, M.
   MacKenzie, A. R.
   Whyatt, J. D.
   Chapman, L.
TI Allometric scaling of thermal infrared emitted from UK cities and its
   relation to urban form
SO CITY AND ENVIRONMENT INTERACTIONS
LA English
DT Article
DE Urban Heat Island (UHI); Land Surface Temperature (LST); Allometry;
   Urban size and population; Geographic information system (GIS); MODIS
   and emitted energy
ID CLIMATE-CHANGE ADAPTATION; LAND-SURFACE TEMPERATURE; HEAT-ISLAND;
   REGIONAL CLIMATE; TOWN CENTERS; URBANIZATION; GEOMETRY; IMPACTS; ENERGY;
   MODEL
AB As a result of differences in heat absorption and release between urban and rural landscapes, cities develop a climate different from their surroundings. The rise in global average surface temperature and high rates of urbanization, make it important to understand the energy balance of cities, including whether any energy-balance-related patterns emerge as a function of city size. In this study, images from the Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite instrument, covering the period between 2000 and 2017, were sampled to examine the seasonal (winter and summer) night-time clear-sky upwelling long-wave energy for 35 UK cities. Total (area-summed) emitted energy per overpass per city is shown to correlate closely (R-2 >= 0.79) with population on a log-log 'allometry' plot. The production of emitted energy from the larger cities is smaller than would be produced from a constellation of smaller cities housing the same population. The mean allometry slope over all overpasses sampled is 0.84 +/- 0.06, implying an 'economy (or parsimony) of scale' (i.e., a less-than-proportional increase) of about 21%(i.e. 100(2-10(0.84log(2)))) for each doubling of city population. City area shows a very similar economy of scale, so that the scaling of night-time emitted energy with urban area is close to linear (1.0 +/- 0.05). This linearity with area indicates that the urban forms used in UK cities to accommodate people more efficiently per unit area as the urban population grows, do not have a large effect on the thermal output per unit area in each city. Although often appearing superficially very different, UK cities appear to be similar in terms of the components of urban form that dictate thermal properties. The difference between the scaling of the heat source and literature reports of the scaling of urban-rural air (or surface) temperature difference is very marked, suggesting that the other factors affecting the temperature difference act to decrease strongly its scaling with population. (C) 2020 The Authors. Published by Elsevier Ltd.
C1 [Abdulrasheed, M.; MacKenzie, A. R.; Chapman, L.] Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham B15 2TT, W Midlands, England.
   [MacKenzie, A. R.] Univ Birmingham, Birmingham Inst Forest Res, Birmingham B15 2TT, W Midlands, England.
   [Whyatt, J. D.] Univ Lancaster, Lancaster Environm Ctr, Lancaster LA1 4YQ, England.
C3 University of Birmingham; University of Birmingham; Lancaster University
RP MacKenzie, AR (corresponding author), Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham B15 2TT, W Midlands, England.
EM a.r.mackenzie@bham.ac.uk
RI MacKenzie, Angus/ISS-0362-2023; Whyatt, James Duncan/D-8123-2014;
   MacKenzie, Angus Robert/B-1704-2009; chapman, lee/F-4674-2014
OI Whyatt, James Duncan/0000-0001-9329-4367; MacKenzie, Angus
   Robert/0000-0002-8227-742X; chapman, lee/0000-0002-2837-8334
FU WM Air project of the Natural Environment Research Council
   [NE/S003487/1]; Petroleum Technology Development Fund; NERC
   [NE/S003487/1] Funding Source: UKRI
FX We very gratefully acknowledge the substantial work of the referees and
   editor to improve the manuscript. ARMK and LC acknowledge support from
   the WM Air project of the Natural Environment Research Council
   (NE/S003487/1). MA gratefully acknowledges support from the Petroleum
   Technology Development Fund.
CR Abdulrasheed M, 2020, THESIS U BIRMINGHAM
   Aguado EJ.E. Burt., 2015, Understanding Weather and Climate, VSeventh
   Alexander Anthony., 2009, Britain's New Towns: Garden Cities to Sustainable Communities
   Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   Anguelovski I, 2014, GLOBAL ENVIRON CHANG, V27, P156, DOI 10.1016/j.gloenvcha.2014.05.010
   [Anonymous], Ehlektronnyj resurs
   Arifwidodo SD, 2015, WORLD CONFERENCE ON TECHNOLOGY, INNOVATION AND ENTREPRENEURSHIP, P423, DOI 10.1016/j.sbspro.2015.06.484
   Arnfield AJ, 1998, ENERG BUILDINGS, V27, P61, DOI 10.1016/S0378-7788(97)00026-1
   Arnfield AJ, 2003, INT J CLIMATOL, V23, P1, DOI 10.1002/joc.859
   Ball M, 2005, HOUSING STUD, V20, P9, DOI 10.1080/0267303042000308705
   Basu R, 2002, EPIDEMIOL REV, V24, P190, DOI 10.1093/epirev/mxf007
   Batty M, 2008, SCIENCE, V319, P769, DOI 10.1126/science.1151419
   Belcher SE, 2003, J FLUID MECH, V488, P369, DOI 10.1017/S0022112003005019
   Bettencourt L, 2010, NATURE, V467, P912, DOI 10.1038/467912a
   Bettencourt LMA, 2007, P NATL ACAD SCI USA, V104, P7301, DOI 10.1073/pnas.0610172104
   Bettencourt LMA, 2013, SCIENCE, V340, P1438, DOI 10.1126/science.1235823
   Bettencourt LMA, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0013541
   Bongaarts J, 2009, PHILOS T R SOC B, V364, P2985, DOI 10.1098/rstb.2009.0137
   Bornstein R.D., 1968, J APPL METEOR, V7, P575
   Bremner J, 2010, POPUL BULL, V65, P2
   Briney A, 2019, UK BECAME ISLAND NAT
   Broto VC, 2017, WORLD DEV, V93, P1, DOI 10.1016/j.worlddev.2016.12.031
   Brown RD, 2011, LANDSCAPE URBAN PLAN, V100, P372, DOI 10.1016/j.landurbplan.2011.01.010
   Buhaug H, 2013, GLOBAL ENVIRON CHANG, V23, P1, DOI 10.1016/j.gloenvcha.2012.10.016
   Burnett John., 1986, SOCIAL HIST HOUSING, V2nd
   Carmin J, 2012, J PLAN EDUC RES, V32, P18, DOI 10.1177/0739456X11430951
   Carmon N, 1999, GEOFORUM, V30, P145, DOI 10.1016/S0016-7185(99)00012-3
   CEDA, 2011, CEDA DAT SERV IND
   Chandler T.J., 1965, CLIMATE LONDON, P292, DOI 10.1002/qj.49709239230
   Chapman L, 2006, SCI TOTAL ENVIRON, V360, P68, DOI 10.1016/j.scitotenv.2005.08.025
   Chapman L, 2004, J ATMOS OCEAN TECH, V21, P730, DOI 10.1175/1520-0426(2004)021<0730:RSFCAA>2.0.CO;2
   Chapman L, 2018, B AM METEOROL SOC, V99, P1147, DOI 10.1175/BAMS-D-17-0214.1
   CHEN YG, 2010, DISCRETE DYN NAT SOC, P94715, DOI DOI 10.1155/2010/194715
   Chrysanthou A, 2014, GEOPHYS RES LETT, V41, P7716, DOI 10.1002/2014GL061154
   Clinton N, 2013, REMOTE SENS ENVIRON, V134, P294, DOI 10.1016/j.rse.2013.03.008
   Cohen B, 2006, TECHNOL SOC, V28, P63, DOI 10.1016/j.techsoc.2005.10.005
   Cottineau C, 2017, COMPUT ENVIRON URBAN, V63, P80, DOI 10.1016/j.compenvurbsys.2016.04.006
   CPRE, 2018, CAMP PROT RUR ENGL
   Davoudi S., 2009, Planning for Climate Change Strategies for Mitigation and Adaptation for Spatial Planners
   Davoudi S, 2014, ENVIRON PLANN C, V32, P360, DOI 10.1068/c12269
   Davoudi S, 2012, EUR PLAN STUD, V20, P49, DOI 10.1080/09654313.2011.638491
   Dawson RJ, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2017.0298
   DUCKWORTH F. S., 1954, BULL AMER METEOROL SOC, V35, P198
   EAGLEMAN JR, 1974, ATMOS ENVIRON, V8, P1131, DOI 10.1016/0004-6981(74)90047-X
   Eliasson I, 1996, ATMOS ENVIRON, V30, P379, DOI 10.1016/1352-2310(95)00033-X
   Fujii H, 2017, J CLEAN PROD, V168, P271, DOI 10.1016/j.jclepro.2017.08.221
   Fuller RA, 2009, BIOL LETTERS, V5, P352, DOI 10.1098/rsbl.2009.0010
   GOIST PD, 1974, J AM I PLANNERS, V40, P31, DOI 10.1080/01944367408977444
   Golden J.S., 2004, Environmental Sciences, V1, P321, DOI [10.1080/15693430412331291698, DOI 10.1080/15693430412331291698]
   GOULD SJ, 1966, BIOL REV, V41, P587, DOI 10.1111/j.1469-185X.1966.tb01624.x
   Grimmond S, 2007, GEOGR J, V173, P83, DOI 10.1111/j.1475-4959.2007.232_3.x
   Han JY, 2014, ASIA-PAC J ATMOS SCI, V50, P17, DOI 10.1007/s13143-014-0016-7
   Hasegawa J, 2013, PLAN PERSPECT, V28, P271, DOI 10.1080/02665433.2013.737712
   Heaviside C, 2015, Q J ROY METEOR SOC, V141, P1429, DOI 10.1002/qj.2452
   Hendrickson TP, 2016, J CLEAN PROD, V135, P1129, DOI 10.1016/j.jclepro.2016.06.075
   Hollow M, 2012, PLAN PERSPECT, V27, P569, DOI 10.1080/02665433.2012.705126
   Hondula DM, 2015, CURR CLIM CHANGE REP, V1, P144, DOI 10.1007/s40641-015-0016-4
   Hoornweg D, 2011, ENVIRON URBAN, V23, P207, DOI 10.1177/0956247810392270
   Hopkins MIW, 2012, URBAN MORPHOL, V16, P41
   Howard Luke., 1818, CLIMATE LONDON
   Inikori JE, 2002, AFR IND REVOLUT ENGL, DOI [10.1017/CBO9780511583940.004, DOI 10.1017/CBO9780511583940.004]
   Jabareen YR, 2006, J PLAN EDUC RES, V26, P38, DOI 10.1177/0739456X05285119
   Karp M, 2013, VERY OLD BOOK CASE E
   Kennedy J, 2017, WEATHER, V72, P219, DOI 10.1002/wea.3042
   Krayenhoff ES, 2018, NAT CLIM CHANGE, V8, P1097, DOI 10.1038/s41558-018-0320-9
   Landsberg H. E., 1981, The urban climate
   LEE HY, 1993, ATMOS ENVIRON B-URB, V27, P1, DOI 10.1016/0957-1272(93)90041-4
   LEE Y, 1989, ENVIRON PLANN A, V21, P463, DOI 10.1068/a210463
   [Lemmen DonaldS. Natural Resources Canada Natural Resources Canada], 2004, CLIMATE CHANGE IMPAC
   Li MC, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0124413
   Li RQ, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01882-w
   LONGLEY P, 1992, REG STUD, V26, P437, DOI 10.1080/00343409212331347101
   LONGLEY PA, 1991, T I BRIT GEOGR, V16, P75, DOI 10.2307/622907
   MacKenzie AR, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab50e3
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Martins PB, 2000, URBANIZING WORLD
   Middel A, 2019, SCI TOTAL ENVIRON, V687, P137, DOI 10.1016/j.scitotenv.2019.06.085
   Mills G, 2007, INT J CLIMATOL, V27, P1849, DOI 10.1002/joc.1604
   Morris A.E.J., 1974, HIST URBAN FORM
   Murray V, 2012, J EPIDEMIOL COMMUN H, V66, P759, DOI 10.1136/jech-2012-201045
   Naroll RS, 1956, PRINCIPLE ALLOMETRY
   NORDBECK S, 1971, GEOGR ANAL, VB 53, P54, DOI 10.2307/490887
   NUNEZ M, 1977, J APPL METEOROL, V16, P11, DOI 10.1175/1520-0450(1977)016<0011:TEBOAU>2.0.CO;2
   OECD, 2014, OECD BLOOMB PHIL CIT
   OKE TR, 1975, ATMOS ENVIRON, V9, P191, DOI 10.1016/0004-6981(75)90067-0
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   OKE TR, 1981, J CLIMATOL, V1, P237, DOI 10.1002/joc.3370010304
   OKE TR, 1973, ATMOS ENVIRON, V7, P769, DOI 10.1016/0004-6981(73)90140-6
   OKE TR, 1995, NATO ADV SCI INST SE, V277, P81
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Rosenzweig Cynthia., 2011, CLIMATE CHANGE CITIE
   RUBIN N., 2009, Planning Perspectives, V24, P349, DOI DOI 10.1080/02665430902933986
   Rybski D, 2017, ENVIRON PLAN B-URBAN, V44, P425, DOI 10.1177/0265813516638340
   Sarkar S, 2018, ENVIRON PLAN B-URBAN, V45, P603, DOI 10.1177/0265813516676488
   Schmidt-Nielsen K., 1984, Scaling why is animal size so important?
   Schwarz N, 2015, J URBAN PLAN DEV, V141, DOI 10.1061/(ASCE)UP.1943-5444.0000263
   Schwarz N, 2011, REMOTE SENS ENVIRON, V115, P3175, DOI 10.1016/j.rse.2011.07.003
   Seto KC, 2012, P NATL ACAD SCI USA, V109, P16083, DOI 10.1073/pnas.1211658109
   Seto KC, 2010, ANNU REV ENV RESOUR, V35, P167, DOI 10.1146/annurev-environ-100809-125336
   Sheng L, 2017, ECOL INDIC, V72, P738, DOI 10.1016/j.ecolind.2016.09.009
   SHORT J.R., 1982, HOUSING BRITAIN POST
   Small C G., 2012, The statistical theory of shape
   Smith CL, 2011, CLIMATIC CHANGE, V109, P269, DOI 10.1007/s10584-011-0021-0
   SolarGIS, 2019, GLOB SOL ALT
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Stewart ID, 2014, INT J CLIMATOL, V34, P1062, DOI 10.1002/joc.3746
   TERJUNG WH, 1974, GEOGR ANAL, V6, P341
   Tizot JY, 2018, CAH VICTOR EDOUARD, DOI 10.4000/cve.3605
   Tomlinson CJ, 2012, INT J CLIMATOL, V32, P214, DOI 10.1002/joc.2261
   Torok SJ, 2001, AUST METEOROL MAG, V50, P1
   Tsubaki T, 2000, CONTEMP BR HIST, V14, P81, DOI [10.1080/13619460008581573, DOI 10.1080/13619460008581573]
   Voogt J, 2019, JOINT URB REMOTE SEN, P1, DOI 10.1109/JURSE.2019.8808982
   Voogt JA, 1998, INT J REMOTE SENS, V19, P895, DOI 10.1080/014311698215784
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wan Z, 2015, MOD11A1 MODIS/Terra Land surface temperature/Emissivity Daily L3 Global 1km SIN Grid V006, DOI [10.5067/MODIS/MOD11A1.006, DOI 10.5067/MODIS/MOD11A1.006]
   Wan ZM, 2008, REMOTE SENS ENVIRON, V112, P59, DOI 10.1016/j.rse.2006.06.026
   Wan ZM, 1996, IEEE T GEOSCI REMOTE, V34, P892, DOI 10.1109/36.508406
   Webb MS, 2018, URBAN HIST, V45, P635, DOI 10.1017/S0963926818000019
   West GB, 2005, J EXP BIOL, V208, P1575, DOI 10.1242/jeb.01589
   WHITEHAND JWR, 1983, T I BRIT GEOGR, V8, P483, DOI 10.2307/621964
   WHITEHAND JWR, 1984, T I BRIT GEOGR, V9, P231, DOI 10.2307/622170
   Wouters H, 2017, GEOPHYS RES LETT, V44, P8997, DOI 10.1002/2017GL074889
   Yang JX, 2015, ISPRS J PHOTOGRAMM, V105, P211, DOI 10.1016/j.isprsjprs.2015.04.006
   Yow DM, 2007, GEOGR COMPASS, V1, P1227, DOI 10.1111/j.1749-8198.2007.00063.x
   Zhao L, 2014, NATURE, V511, P216, DOI 10.1038/nature13462
   Zhou B, 2013, GEOPHYS RES LETT, V40, P5486, DOI 10.1002/2013GL057320
   Zhou B, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-04242-2
   Zhou B, 2016, J APPL METEOROL CLIM, V55, P493, DOI 10.1175/JAMC-D-15-0041.1
   Zhou DC, 2014, REMOTE SENS ENVIRON, V152, P51, DOI 10.1016/j.rse.2014.05.017
NR 130
TC 5
Z9 5
U1 2
U2 7
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2590-2520
J9 CITY ENVIRON INTERAC
JI City Environ. Interact.
PD MAR
PY 2020
VL 5
AR 100037
DI 10.1016/j.cacint.2020.100037
PG 10
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA SN5CX
UT WOS:000658308700003
OA Green Accepted, Green Published, gold
DA 2025-01-10
ER

PT J
AU Lal, R
AF Lal, Rattan
TI Promoting "4 Per Thousand" and "Adapting African Agriculture" by
   south-south cooperation: Conservation agriculture and sustainable
   intensification
SO SOIL & TILLAGE RESEARCH
LA English
DT Article
DE Soil restoration; Multilateral cooperation; Food security
ID CLIMATE-CHANGE ADAPTATION; FOOD SECURITY; SOIL-EROSION;
   DEVELOPING-COUNTRIES; ORGANIC-MATTER; GLOBAL FOOD; CARBON; WATER;
   MANAGEMENT; SYSTEMS
AB The "4 per Thousand" and "Adapting African Agriculture" are bold and innovative initiatives adopted at COP21 in Paris and COP22 in Marrakesh, respectively. These initiatives are soil-centric and based on adoption of soil-restorative and improved agricultural practices. The objective of this article is to discuss the merits and challenges of South-South Cooperation (SSC) in promoting the adoption of best management practices (BMPs) such as conservation agriculture (CA) and sustainable intensification (SI). Basic principles of CA are: retention of crop residue mulch, incorporation of cover crops and complex rotations, integrated nutrient management and elimination of soil disturbance. The strategy of SI is to produce more from less by enhancing the eco-efficiency, reducing waste, and restoring soil health. Whereas CA has been successfully adopted in Brazil, Argentina, Chile and other regions of South America, its potential of harnessing agronomic and ecologic benefits has not been realized in Sub-Saharan Africa, South Asia, and elsewhere in The Global South. The strategy of SSC is pertinent because of the ten basic principles or tenets: lack of hierarchy, equal participation in all decision-making processes along with transparency, trust, mutual respect, and accountability. However, several concerns have been raised regarding issues such as land grab, and access to resources etc. Based on the scientific concepts of SI, producing more from less, even a triangular cooperation (TAC) or South-South-North (SSNC) cooperation can be developed to achieve adaptation and mitigation of climate change, advance food security, improve degraded soils and restore soil health through soil organic carbon (SOC) sequestration, and advance Sustainable Development Goals (SDGs) of the U.N. A widespread adoption of CA and SI through SSC, TAC or SSNC can advance SDGs including #1 (end poverty), #2 (eliminate hunger), #6 (clean water), #13 (climate action), and #15 (life on land). Of the global cropland area under CA estimated at similar to 180 million hectare (Mha) in 2015-16, land area under CA is only 2.7 Mha in Africa and 13.2 Mha in Asia. SSC, TAC and SSNC can build upon the existing and on-going initiatives by national and international organizations.
C1 [Lal, Rattan] Ohio State Univ, Carbon Management & Sequestrat Ctr, Columbus, OH 43210 USA.
C3 University System of Ohio; Ohio State University
RP Lal, R (corresponding author), Ohio State Univ, Carbon Management & Sequestrat Ctr, Columbus, OH 43210 USA.
EM lal.1@osu.edu
RI Lal, Rattan/D-2505-2013
CR Adhikari U, 2015, T ASABE, V58, P1493
   Adhikari U., 2016, American Society of Agricultural and Biological Engineers, V58, P1493
   Adhikari U, 2015, FOOD ENERGY SECUR, V4, P110, DOI 10.1002/fes3.61
   Aggarwal PK, 2011, CLIMATE CHANGE AND FOOD SECURITY IN SOUTH ASIA, P253, DOI 10.1007/978-90-481-9516-9_16
   Almeida J, 2014, SUSTAIN DEV, V22, P349, DOI 10.1002/sd.1553
   Amanor K. S., 2013, IDS B, V44, P4
   Ananda J, 2003, J ENVIRON MANAGE, V68, P343, DOI 10.1016/S0301-4797(03)00082-3
   Annan K., 2016, TAN HIGH LEV FOR SEC
   [Anonymous], 2017, 7 WORLD C CONS AGR 1
   [Anonymous], 2007, 562007 DESA
   [Anonymous], 2016, The Sustainable Development Goals Report 2016, P1, DOI DOI 10.18356/3405D09F-EN
   [Anonymous], 2015, The State of Food Insecurity in the World Meeting the 2015 interation hunger targets: taking stock of uneven progress
   Bates-Amer N., 2015, POST 2015 DEV AGENDA
   Brown O, 2007, INT AFF, V83, P1141, DOI 10.1111/j.1468-2346.2007.00678.x
   Bruntland G., 1987, The Brundtland Report: Our Common Future
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Busscher WJ, 1996, J SOIL WATER CONSERV, V51, P188
   Carter MR, 2002, AGRON J, V94, P38, DOI 10.2134/agronj2002.0038
   Cesarino Letícia Maria Costa da Nóbrega, 2012, Vibrant, Virtual Braz. Anthr., V9, P507
   Challinor A, 2007, CLIMATIC CHANGE, V83, P381, DOI 10.1007/s10584-007-9249-0
   Claussen M, 2003, CLIMATIC CHANGE, V57, P99, DOI 10.1023/A:1022115604225
   Conant RT, 2008, GLOBAL CHANGE BIOL, V14, P868, DOI 10.1111/j.1365-2486.2008.01541.x
   Cook C. C., 1989, 12 WORLD BANK
   Corson Catherine., 2013, Human Geography, V6, P1
   Cost Leite I., 2013, 2013022 WIDER UNU
   Cowie AL, 2018, ENVIRON SCI POLICY, V79, P25, DOI 10.1016/j.envsci.2017.10.011
   Dasgupta S, 2015, AMBIO, V44, P815, DOI 10.1007/s13280-015-0681-5
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   de Freitas PL, 2014, INT SOIL WATER CONSE, V2, P35
   Sá JCD, 2017, ENVIRON INT, V98, P102, DOI 10.1016/j.envint.2016.10.020
   Donagemma GK, 2016, PESQUI AGROPECU BRAS, V51, P1003, DOI [10.1590/s0100-204x2016000900001, 10.1590/S0100-204X2016000900001]
   Erenstein O, 2012, J SUSTAIN AGR, V36, P180, DOI 10.1080/10440046.2011.620230
   Garrity Dennis., 2012, Food Security in Africa: Bridging research and practice
   Garrity DP, 2010, FOOD SECUR, V2, P197, DOI 10.1007/s12571-010-0070-7
   Hansen LT, 2002, J SOIL WATER CONSERV, V57, P205
   Holgate C, 2007, LOCAL ENVIRON, V12, P471, DOI 10.1080/13549830701656994
   Jat RA, 2012, CURR SCI INDIA, V102, P1650
   Jiang B, 2014, GEO-SPAT INF SCI, V17, P39, DOI 10.1080/10095020.2014.889271
   Jungcurt S., 2017, FAO ASSESSES FOOD SE
   Kadyampakeni DM, 2014, AGRON J, V106, P100, DOI 10.2134/agronj2013.0307
   KANG BT, 1981, PLANT SOIL, V63, P165, DOI 10.1007/BF02374595
   Kassam A., 2015, FIELD ACTION SCI REP, V8
   KEESSTRA SD, 2016, SOIL, V2, P111, DOI DOI 10.5194/SOIL-2-111-2016
   Kemper KJ, 2017, COMPLEMENT THER MED, V32, pA1, DOI 10.1016/j.ctim.2017.04.005
   KHADKA N, 1990, FOOD POLICY, V15, P492, DOI 10.1016/0306-9192(90)90040-7
   Kilroy G, 2015, REG ENVIRON CHANGE, V15, P771, DOI 10.1007/s10113-014-0709-6
   Knox J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/3/034032
   Koning N, 2009, FOOD SECUR, V1, P291, DOI 10.1007/s12571-009-0024-0
   Labrière N, 2015, AGR ECOSYST ENVIRON, V203, P127, DOI 10.1016/j.agee.2015.01.027
   Lal R, 2004, SCIENCE, V304, P1623, DOI 10.1126/science.1097396
   LAL R, 1989, AGROFOREST SYST, V8, P217, DOI 10.1007/BF00129650
   Lal R., 2011, PEDOLOGIST, P315
   Lal R., 1975, ETA TECH B, V1
   Lal R., 2012, ZERO NET LAND DEGRAD
   Lal R., 2017, CURR SUSTAIN RENEW E, V4, P1
   Lal R., 2010, J SOIL SALINITY WATE, V1, P30
   Lal R., 1983, IITA TECHNICAL B SER, V2
   Lal R, 2017, ADV AGRON, V145, P167, DOI 10.1016/bs.agron.2017.05.003
   Lal R, 2015, J SOIL WATER CONSERV, V70, p82A, DOI 10.2489/jswc.70.4.82A
   Lal R, 2015, J SOIL WATER CONSERV, V70, p55A, DOI 10.2489/jswc.70.3.55A
   Leach M, 2012, J PEASANT STUD, V39, P285, DOI 10.1080/03066150.2012.658042
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Marcondes G, 2015, FOOD SECUR, V7, P1153, DOI 10.1007/s12571-015-0503-4
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P8, DOI 10.1016/j.cosust.2013.09.002
   Montanarella L, 2016, SOIL-GERMANY, V2, P79, DOI 10.5194/soil-2-79-2016
   Mrabet R, 2012, FIELD CROP RES, V132, P84, DOI 10.1016/j.fcr.2011.11.017
   Müller C, 2011, P NATL ACAD SCI USA, V108, P4313, DOI 10.1073/pnas.1015078108
   Nellemann C., 2009, The Environmental Food Crisis - The environment's role in averting future food crises
   Orr B.J., 2017, Scientific Conceptual Framework for Land Degradation Neutrality. A Report of the Science-Policy Interface
   Palm CA, 2010, P NATL ACAD SCI USA, V107, P19661, DOI 10.1073/pnas.0912248107
   Panagos P, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-04282-8
   Parks BC, 2008, CAMB REV INT AFF, V21, P621, DOI 10.1080/09557570802452979
   Pfister S, 2011, SCI TOTAL ENVIRON, V409, P4206, DOI 10.1016/j.scitotenv.2011.07.019
   Rattan Lal Rattan Lal, 2016, CAB Reviews, V11, P1, DOI 10.1079/PAVSNNR201611009
   Ringler C., 2010, Climate change impacts on food security in sub-Saharan Africa: insights from comprehensive climate change scenarios
   Schaaf R, 2015, GEOGR COMPASS, V9, P68, DOI 10.1111/gec3.12198
   Sebastian Antoinette G., 2013, African Identities, P1, DOI DOI 10.1080/14725843.2013.868669
   SHARIF N, 1992, TECHNOL FORECAST SOC, V42, P367, DOI 10.1016/0040-1625(92)90080-D
   Smyth AJ, 1995, CAN J SOIL SCI, V75, P401, DOI 10.4141/cjss95-059
   Sommerville M, 2014, GEOPOLITICS, V19, P239, DOI 10.1080/14650045.2013.811641
   Speratti A., 2014, CONSERVATION AGR, P391
   Srivastava AK, 2012, AGR ECOSYST ENVIRON, V153, P57, DOI 10.1016/j.agee.2012.03.004
   Stokes LC, 2016, GLOBAL ENVIRON POLIT, V16, P12, DOI 10.1162/GLEP_a_00378
   Stolte C., 2012, AFPAMPBP201201 ROYAL
   Sultan B, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104006
   Sultan B, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01262
   Swaminathan MS, 2012, ADV AGROFOR, V9, p7 
   TACCONI L, 1993, THIRD WORLD PLAN REV, V15, P411
   Teh S. Y., 2016, INT J AGR FORESTRY P, V2
   Telles TS, 2011, REV BRAS CIENC SOLO, V35, P287, DOI 10.1590/S0100-06832011000200001
   Thierfelder C., 2014, RENEW ENERGY FOOD SY, DOI [10.1017/S1742/70513000550, DOI 10.1017/S1742/70513000550]
   Thompson H. E., 2010, Sustainability, V2, P2719, DOI 10.3390/su2082719
   Thornton PK, 2009, GLOBAL ENVIRON CHANG, V19, P54, DOI 10.1016/j.gloenvcha.2008.08.005
   U. N, 1992, 1992 C ENV DEV RIO D
   U. N, 2012, UN HIGH LEV COMM SOU
   United Nations, 2015, No.A/RES/70/1.
   Urban F, 2015, SUSTAIN DEV, V23, P232, DOI 10.1002/sd.1590
   Wall PC, 2007, J CROP IMPROV, V19, P137, DOI 10.1300/J411v19n01_07
   Warner J, 2015, FOOD SECUR, V7, P1175, DOI 10.1007/s12571-015-0505-2
   Warren A, 2001, GLOBAL ENVIRON CHANG, V11, P79, DOI 10.1016/S0959-3780(00)00047-9
   Webber H, 2014, AGR SYST, V127, P161, DOI 10.1016/j.agsy.2013.12.006
   World Bank, 2017, INT APPR MAN REST LA
   World Bank, 2016, AFR BOLD AMB END RES
   World Bank, 2014, REST LANDS LIV LIV A
   Yang YCE, 2016, GLOBAL ENVIRON CHANG, V37, P16, DOI 10.1016/j.gloenvcha.2016.01.002
   Yang ZL, 1999, RESOUR ENERGY ECON, V21, P67, DOI 10.1016/S0928-7655(98)00028-1
   Zewdie A., 2014, Journal of Earth Science & Climatic Change, V5, P225
NR 107
TC 55
Z9 57
U1 1
U2 115
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0167-1987
EI 1879-3444
J9 SOIL TILL RES
JI Soil Tillage Res.
PD MAY
PY 2019
VL 188
SI SI
BP 27
EP 34
DI 10.1016/j.still.2017.12.015
PG 8
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture
GA HM5MV
UT WOS:000459520700004
DA 2025-01-10
ER

PT J
AU Thomson, MC
   Muñoz, AG
   Cousin, R
   Shumake-Guillemot, J
AF Thomson, Madeleine C.
   Munoz, Angel G.
   Cousin, Remi
   Shumake-Guillemot, Joy
TI Climate drivers of vector-borne diseases in Africa and their relevance
   to control programmes
SO INFECTIOUS DISEASES OF POVERTY
LA English
DT Article
DE Vector-borne diseases; Climate variability; Climate change; El Nino
   southern oscillation; Climate services; Adaptation; Africa
ID SEA-SURFACE TEMPERATURE; INDIAN-OCEAN DIPOLE; SUMMER RAINFALL; SOUTHERN
   AFRICA; EL-NINO; MALARIA; SAHEL; ENSO; ANOMALIES; DROUGHT
AB Background: Climate-based disease forecasting has been proposed as a potential tool in climate change adaptation for the health sector. Here we explore the relevance of climate data, drivers and predictions for vector-borne disease control efforts in Africa.
   Methods: Using data from a number of sources we explore rainfall and temperature across the African continent, from seasonality to variability at annual, multi-decadal and timescales consistent with climate change. We give particular attention to three regions defined as WHO-TDR study zones in Western, Eastern and Southern Africa. Our analyses include 1) time scale decomposition to establish the relative importance of year-to-year, decadal and long term trends in rainfall and temperature; 2) the impact of the El Nino Southern Oscillation (ENSO) on rainfall and temperature at the Pan African scale; 3) the impact of ENSO on the climate of Tanzania using high resolution climate products and 4) the potential predictability of the climate in different regions and seasons using Generalized Relative Operating Characteristics. We use these analyses to review the relevance of climate forecasts for applications in vector borne disease control across the continent.
   Results: Timescale decomposition revealed long term warming in all three regions of Africa - at the level of 0.1-0.3 degrees C per decade. Decadal variations in rainfall were apparent in all regions and particularly pronounced in the Sahel and during the East African long rains (March-May). Year-to-year variability in both rainfall and temperature, in part associated with ENSO, were the dominant signal for climate variations on any timescale. Observed climate data and seasonal climate forecasts were identified as the most relevant sources of climate information for use in early warning systems for vector-borne diseases but the latter varied in skill by region and season.
   Conclusions: Adaptation to the vector-borne disease risks of climate variability and change is a priority for government and civil society in African countries. Understanding rainfall and temperature variations and trends at multiple timescales and their potential predictability is a necessary first step in the incorporation of relevant climate information into vector-borne disease control decision-making.
C1 [Thomson, Madeleine C.; Munoz, Angel G.; Cousin, Remi] Columbia Univ, Int Res Inst Climate & Soc IRI, Earth Inst, New York, NY 10027 USA.
   [Thomson, Madeleine C.] Columbia Univ, Dept Environm Hlth Sci, Mailman Sch Publ Hlth, New York, NY 10027 USA.
   [Thomson, Madeleine C.] IRI World Hlth Org WHO, Collaborating Ctr US Early Warning Syst Malaria &, Palisades, NY 10964 USA.
   [Munoz, Angel G.] Princeton Univ, Atmospher & Ocean Sci, Princeton, NJ 08544 USA.
   [Shumake-Guillemot, Joy] WHO, World Hlth Org World Meteorol Org Joint Climate &, Geneva, Switzerland.
   [Thomson, Madeleine C.] LDEO, Int Res Inst Climate & Soc, Palisades, NY 10964 USA.
C3 Columbia University; Columbia University; Princeton University; World
   Health Organization
RP Thomson, MC (corresponding author), Columbia Univ, Int Res Inst Climate & Soc IRI, Earth Inst, New York, NY 10027 USA.; Thomson, MC (corresponding author), Columbia Univ, Dept Environm Hlth Sci, Mailman Sch Publ Hlth, New York, NY 10027 USA.; Thomson, MC (corresponding author), IRI World Hlth Org WHO, Collaborating Ctr US Early Warning Syst Malaria &, Palisades, NY 10964 USA.; Thomson, MC (corresponding author), LDEO, Int Res Inst Climate & Soc, Palisades, NY 10964 USA.
EM mthomson@iri.columbia.edu
OI COUSIN, Remi/0000-0001-5425-7387
FU WHO-TDR IDRC [WHO PO 21353027, WHO PO 201487225]; Atmospheric and
   Oceanic Sciences (AOS) Program at Princeton University
FX Funding for the work came from WHO PO 21353027 (PI MCT) in support of
   WHO-TDR IDRC-funded project: "Population health vulnerabilities to
   vector-borne diseases: increasing resilience under climate change
   conditions in Africa" and WHO PO 201487225 (PI MCT) as a technical
   contribution to the Global Framework for Climate Services. AM was
   supported via the Atmospheric and Oceanic Sciences (AOS) Program at
   Princeton University.
CR ACPC, 2011, ASS AFR CLIM REC REC, P25
   [Anonymous], 2014, EARTH PERSPECT, DOI DOI 10.1186/2194-6434-1-19
   [Anonymous], HLTH EXEMPLAR ANNEX
   [Anonymous], CLIM DYN
   Bai L, 2013, GLOBALIZATION HEALTH, V9, DOI 10.1186/1744-8603-9-10
   Barnston AG, 2010, J APPL METEOROL CLIM, V49, P493, DOI 10.1175/2009JAMC2325.1
   Beck-Johnson LM, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0079276
   Behera SK, 2005, J CLIMATE, V18, P4514, DOI 10.1175/JCLI3541.1
   Camberlin P, 2001, INT J CLIMATOL, V21, P973, DOI 10.1002/joc.673
   Campbell-Lendrum D, 2005, GLOBAL ENVIRON CHANG, V15, P296, DOI 10.1016/j.gloenvcha.2005.09.001
   Campbell-Lendrum D, 2015, PHILOS T R SOC B, V370, DOI 10.1098/rstb.2013.0552
   Ceccato P., 2010, GEO TASK US 09 01A C, P149
   Chiang JCH, 2002, J CLIMATE, V15, P2616, DOI 10.1175/1520-0442(2002)015<2616:TTTVCB>2.0.CO;2
   Christy JR, 2009, J CLIMATE, V22, P3342, DOI 10.1175/2008JCLI2726.1
   Cox J, 2007, EMERG INFECT DIS, V13, P779, DOI 10.3201/eid1305.061410
   del Corral J, 2012, GEOSPATIAL HEALTH, V6, pS15
   Dinku T, 2016, WORLD POLICY J
   Giannini A, 2003, SCIENCE, V302, P1027, DOI 10.1126/science.1089357
   Gill C. A., 1923, Indian Journal of Medical Research, V10, P1136
   Goddard L, 2013, CLIM DYNAM, V40, P245, DOI 10.1007/s00382-012-1481-2
   Greene A.M., 2011, Eos, Transactions American Geophysical Union, V92, P397, DOI DOI 10.1029/2011EO450001
   Harris I., 2014, International Journal of Climatology, V34, P623, DOI 10.1002/joc.3711
   Hellmuth ME, 2007, CLIMATE SOC SERIES, P97
   HIRST AC, 1983, J PHYS OCEANOGR, V13, P1146, DOI 10.1175/1520-0485(1983)013<1146:AOMOCA>2.0.CO;2
   Kelly-Hope L, 2008, ADV GLOB CHANGE RES, V30, P31, DOI 10.1007/978-1-4020-6877-5_3
   Kousky VE, 2007, WEATHER FORECAST, V22, P353, DOI 10.1175/WAF987.1
   Labbo R, 2004, LANCET, V363, P660, DOI 10.1016/S0140-6736(04)15606-7
   Landman WA, 1999, INT J CLIMATOL, V19, P1477, DOI 10.1002/(SICI)1097-0088(19991115)19:13<1477::AID-JOC432>3.0.CO;2-W
   Lowe R, 2013, STAT MED, V32, P864, DOI 10.1002/sim.5549
   Lyon B, 2007, J CLIMATE, V20, P5134, DOI 10.1175/JCLI4225.1
   Lyon B, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa64e6
   Lyon B, 2017, GEOPHYS MONOGR SER, V226, P265
   Lyon B, 2014, J CLIMATE, V27, P7953, DOI 10.1175/JCLI-D-13-00459.1
   Lyon B, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050337
   Mabaso MLH, 2007, T ROY SOC TROP MED H, V101, P326, DOI 10.1016/j.trstmh.2006.07.009
   Malhi Y, 2013, PHILOS T R SOC B, V368, DOI [10.1098/rstb.2012.0312, 10.1098/rstb.2012.0293]
   Mason SJ, 2009, MON WEATHER REV, V137, P331, DOI 10.1175/2008MWR2553.1
   Mason SJ, 1997, PROG PHYS GEOG, V21, P23, DOI 10.1177/030913339702100103
   Mason SJ, 2001, B AM METEOROL SOC, V82, P619, DOI 10.1175/1520-0477(2001)082<0619:PPAAWE>2.3.CO;2
   Mitchell TD, 2005, INT J CLIMATOL, V25, P693, DOI 10.1002/joc.1181
   Mouchet J, 1996, LANCET, V348, P1735, DOI 10.1016/S0140-6736(05)65860-6
   Muñoz AG, 2017, FRONT MICROBIOL, V8, DOI 10.3389/fmicb.2017.01291
   Muñoz AG, 2016, GIGASCIENCE, V5, DOI 10.1186/s13742-016-0146-1
   Nicholson SE, 2017, REV GEOPHYS, V55, P590, DOI 10.1002/2016RG000544
   Omumbo JA, 2011, MALARIA J, V10, DOI 10.1186/1475-2875-10-12
   Parhi P, 2016, J CLIMATE, V29, P1461, DOI 10.1175/JCLI-D-15-0071.1
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Ramirez B, 2017, INFECT DIS POVERTY, V6, DOI 10.1186/s40249-017-0378-z
   ROPELEWSKI CF, 1985, MON WEATHER REV, V113, P1101, DOI 10.1175/1520-0493(1985)113<1101:TAADOR>2.0.CO;2
   Saji NH, 1999, NATURE, V401, P360, DOI 10.1038/43855
   Shaaban AA, 2017, Q J ROY METEOR SOC, V143, P1828, DOI 10.1002/qj.3045
   Stratton MD, 2017, SCI REP-UK, V7, DOI 10.1038/srep40186
   Thomson MC, 2017, AM J TROP MED HYG, V97, P32, DOI 10.4269/ajtmh.16-0696
   Thomson MC, 2006, NATURE, V439, P576, DOI 10.1038/nature04503
   Thomson MC, 2005, AM J TROP MED HYG, V73, P214, DOI 10.4269/ajtmh.2005.73.214
   Todd MC, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2004GL020975
   WHO-TDR, 2012, ASS RES NEEDS PUBL H
   Xie PP, 1998, J CLIMATE, V11, P137, DOI 10.1175/1520-0442(1998)011<0137:GMPEFS>2.0.CO;2
   Zebiak SE, 2015, WIRES CLIM CHANGE, V6, P17, DOI 10.1002/wcc.294
NR 60
TC 40
Z9 42
U1 4
U2 35
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 2095-5162
EI 2049-9957
J9 INFECT DIS POVERTY
JI Infect. Dis. Poverty
PD AUG 10
PY 2018
VL 7
AR 81
DI 10.1186/s40249-018-0460-1
PG 22
WC Infectious Diseases; Parasitology; Tropical Medicine
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Infectious Diseases; Parasitology; Tropical Medicine
GA GP9MC
UT WOS:000441240100001
PM 30092816
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Op de Hipt, F
   Diekkrüger, B
   Steup, G
   Yira, Y
   Hoffmann, T
   Rode, M
AF Op de Hipt, Felix
   Diekkrueger, Bernd
   Steup, Gero
   Yira, Yacouba
   Hoffmann, Thomas
   Rode, Michael
TI Modeling the impact of climate change on water resources and soil
   erosion in a tropical catchment in Burkina Faso, West Africa
SO CATENA
LA English
DT Article
DE Hydrological modeling; Erosion modeling; Climate change
ID LAND-USE; BIAS CORRECTION; SEDIMENT YIELD; RIVER-BASIN; FUTURE CLIMATE;
   PRECIPITATION; DISCHARGE; ENSEMBLE; RUNOFF; SIMULATIONS
AB Soil erosion is recognized as one main reason for soil degradation in West Africa. However, predictions on the impact of climate change on soil erosion are rare for most West African countries including Burkina Faso.
   This study assesses the impact of climate change on water resources and soil erosion in a small catchment (126 km(2)) in southwestern Burkina Faso. Climate data from an ensemble of six regional (RCM) and global (GCM) climate models were used to run the physically based spatially distributed hydrological and soil erosion model SHETRAN. The Representative Concentration Pathways (RCPs) 4.5 and 8.5 were selected as future climate scenarios.
   Bias corrected precipitation and temperature required for the calculation of potential evapotranspiration were used as input for the SHETRAN model to simulate total discharge and specific suspended sediment yield (SSY). Discharge and SSY from simulations run with climate data were able to reproduce discharge and SSY from a simulation that used observed precipitation and temperature from the historical period (1971-2000).
   The impact of climate change on hydrology and soil erosion was assPssi-d by comparing the historical period with the future climate scenarios (2021-2050). Most of the used climate models predict an increase of temperature between 0.9 degrees C and 2.0 degrees C. The bias correction did not alter the climate change signal of temperature. Large uncertainties among the RCMs-GCMs exist regarding the climate change signal of future precipitation. Some climate models predict an increased (5.9%-36.5%) others a decreased (6.4%-10.9%) or mixed signal. The applied bias correction did not reverse the climate change signal in most cases but it influenced magnitude and timing of precipitation. The ensemble mean suggests an increased discharge between 19.5% (RCP 8.5) and 36.5% (RCP4.5) and an increased SSY of the same order. In general, the climate change signal and the corresponding discharge and SSY predictions are afflicted with large uncertainties. These uncertainties impede direct conclusions regarding future development of discharge and erosion. As a consequence of the mixed signals, potential increase and decrease of future discharge and soil erosion have to be incorporated in climate change adaption strategies.
C1 [Op de Hipt, Felix; Diekkrueger, Bernd; Steup, Gero; Yira, Yacouba] Univ Bonn, Dept Geog, Meckenheimer Allee 166, D-53115 Bonn, Germany.
   [Hoffmann, Thomas] German Fed Inst Hydrol, Am Mainzer Tor 1, D-56068 Koblenz, Germany.
   [Rode, Michael] UFZ Helmholtz Ctr Environm Res, Bruckstr 3a, D-39114 Magdeburg, Germany.
C3 University of Bonn; Helmholtz Association; Helmholtz Center for
   Environmental Research (UFZ)
RP Op de Hipt, F (corresponding author), Univ Bonn, Dept Geog, Meckenheimer Allee 166, D-53115 Bonn, Germany.
EM felixodh@uni-bonn.de
RI Rode, Michael/ABA-4786-2021; Diekkruger, Bernd/D-9410-2013
OI Diekkruger, Bernd/0000-0001-9234-7850; Rode, Michael/0000-0003-0086-2033
FU German Federal Ministry of Education and Research (BMBF) under the West
   Afr can Science Service Centre for Climate Change and Adapted Land Use
   (WASCAL) project [01LG1202E]
FX The authors are grateful for the financial support provided by the
   German Federal Ministry of Education and Research (BMBF) (Grant No.
   01LG1202E) under the auspices of the West Afr can Science Service Centre
   for Climate Change and Adapted Land Use (WASCAL) project. Furthermore,
   we thank Stephen Birkinshaw (School of Civil Engineering and
   Geosciences, Newcastle University) for his kind support regarding the
   set-up of SHETRAN. We acknowledge the soil sampling and mapping done by
   Ozias Hounkpatin (Soil Science of Institute of Crop Science and Resource
   Conservation, University Bonn). We also thank the CORDEX project and
   partner institutions for making climate data available and D. Wisser for
   providing a R-code for bias correction. Finally, we thank the anonymous
   reviewers and the editor Erik Cammeraat for their helpful comments and
   suggestions.
CR ABBOTT MB, 1986, J HYDROL, V87, P45, DOI 10.1016/0022-1694(86)90114-9
   Abiodun BJ, 2013, REG ENVIRON CHANGE, V13, P477, DOI 10.1007/s10113-012-0381-7
   Aguilar E, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2008JD011010
   Aich V, 2014, HYDROL EARTH SYST SC, V18, P1305, DOI 10.5194/hess-18-1305-2014
   [Anonymous], 2010, Handbook of erosion modelling
   [Anonymous], 1996, A three-dimensional variably-saturated subsurface modelling system for river basins
   [Anonymous], 1995, HYDROL PROCESS, DOI DOI 10.1002/hyp.3360090305
   [Anonymous], P PUB KICK OFF M PRE
   [Anonymous], INT ADV RES J SCI EN
   [Anonymous], ENERG CONVERS MANAGE, DOI DOI 10.1016/J.ENCONMAN.2015.11.063
   [Anonymous], EXTREME VALUE ANAL W
   [Anonymous], 2008, THESIS
   [Anonymous], 2009, IMPACT GLOBAL CHANGE
   [Anonymous], THESIS
   [Anonymous], 2016, THESIS
   [Anonymous], REG ENV CHANG
   [Anonymous], 2015, INTEGRATED MODELLING
   [Anonymous], THESIS
   [Anonymous], 2012, MANAGING RISKS EXTRE
   [Anonymous], THESIS
   Ardoin-Bardin S, 2009, HYDROLOG SCI J, V54, P77, DOI 10.1623/hysj.54.1.77
   Beven K., 2008, RAINFALL RUNOFF MODE
   Birkinshaw SJ, 2010, HYDROL EARTH SYST SC, V14, P1767, DOI 10.5194/hess-14-1767-2010
   Birkinshaw SJ, 2014, J HYDROL, V519, P559, DOI 10.1016/j.jhydrol.2014.07.050
   Birkinshaw SJ, 2017, HYDROL EARTH SYST SC, V21, P1911, DOI 10.5194/hess-21-1911-2017
   Boé J, 2007, INT J CLIMATOL, V27, P1643, DOI 10.1002/joc.1602
   Bossa AY, 2014, WATER-SUI, V6, P3152, DOI 10.3390/w6103152
   BRUNEAU P, 1995, HYDROL PROCESS, V9, P69, DOI 10.1002/hyp.3360090107
   Chaplot V, 2007, J HYDROL, V337, P159, DOI 10.1016/j.jhydrol.2007.01.026
   CILSS, 2016, W AFRICAN LANDSCAPES
   Cook KH, 2008, NAT GEOSCI, V1, P647, DOI 10.1038/ngeo320
   Cook KH, 2006, J CLIMATE, V19, P3681, DOI 10.1175/JCLI3814.1
   Cornelissen T, 2013, J HYDROL, V498, P221, DOI 10.1016/j.jhydrol.2013.06.016
   de Vente J, 2013, EARTH-SCI REV, V127, P16, DOI 10.1016/j.earscirev.2013.08.014
   Dosio A, 2015, CLIM DYNAM, V44, P2637, DOI 10.1007/s00382-014-2262-x
   Druyan LM, 2011, INT J CLIMATOL, V31, P1415, DOI 10.1002/joc.2180
   Druyan LM, 2010, CLIM DYNAM, V35, P175, DOI 10.1007/s00382-009-0676-7
   Dukic V, 2016, WATER RESOUR MANAG, V30, P1669, DOI 10.1007/s11269-016-1243-8
   Dukic V, 2014, WATER RESOUR MANAG, V28, P4567, DOI 10.1007/s11269-014-0751-7
   Ehret U, 2012, HYDROL EARTH SYST SC, V16, P3391, DOI 10.5194/hess-16-3391-2012
   Elliott AH, 2012, HYDROL PROCESS, V26, P3645, DOI 10.1002/hyp.8445
   Emori S, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023272
   Ewen J, 2000, J HYDROL ENG, V5, P250, DOI 10.1061/(ASCE)1084-0699(2000)5:3(250)
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Forkuor G., 2014, AGR LAND USE MAPPING
   Forster P, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P129
   Gbobaniyi E, 2014, INT J CLIMATOL, V34, P2241, DOI 10.1002/joc.3834
   Giorgi F, 2014, CLIMATIC CHANGE, V125, P39, DOI 10.1007/s10584-014-1117-0
   Gudmundsson L, 2012, HYDROL EARTH SYST SC, V16, P3383, DOI 10.5194/hess-16-3383-2012
   Gupta HV, 2009, J HYDROL, V377, P80, DOI 10.1016/j.jhydrol.2009.08.003
   Haddeland I, 2012, HYDROL EARTH SYST SC, V16, P305, DOI 10.5194/hess-16-305-2012
   Hagemann S, 2011, J HYDROMETEOROL, V12, P556, DOI 10.1175/2011JHM1336.1
   Hessell R, 2005, HYDROL PROCESS, V19, P3037, DOI 10.1002/hyp.5815
   Hogg R.V., 2015, Probability and Statistical Inference
   Hounkpè J, 2016, CLIMATE, V4, DOI 10.3390/cli4010015
   Itiveh KO, 2008, INT J CLIMATOL, V28, P659, DOI 10.1002/joc.1568
   Jetten V, 1999, CATENA, V37, P521, DOI 10.1016/S0341-8162(99)00037-5
   Johnson F, 2015, J HYDROL, V525, P472, DOI 10.1016/j.jhydrol.2015.04.002
   Kasei R, 2010, SUSTAIN SCI, V5, P89, DOI 10.1007/s11625-009-0101-5
   Kingston DG, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL040267
   Klein C, 2015, CLIM DYNAM, V45, P2733, DOI 10.1007/s00382-015-2505-5
   Kling H, 2012, J HYDROL, V424, P264, DOI 10.1016/j.jhydrol.2012.01.011
   Kunstmann H, 2008, PHYS CHEM EARTH, V33, P165, DOI 10.1016/j.pce.2007.04.010
   Latocha A, 2016, CATENA, V145, P128, DOI 10.1016/j.catena.2016.05.027
   Li ZY, 2016, EARTH-SCI REV, V163, P94, DOI 10.1016/j.earscirev.2016.10.004
   Lintner BR, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2012JD017499
   Ly M, 2013, WEATHER CLIM EXTREME, V1, P19, DOI 10.1016/j.wace.2013.07.005
   M'Po YekambessounN'Tcha., 2016, Hydrology, V4, P58
   Maraun D, 2010, REV GEOPHYS, V48, DOI 10.1029/2009RG000314
   Mbaye M.L., 2015, AM J CLIM CHANG, V4, P77, DOI [10.4236/ajcc.2015.41008, DOI 10.4236/AJCC.2015.41008]
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Mourato S, 2015, WATER RESOUR MANAG, V29, P2377, DOI 10.1007/s11269-015-0947-5
   Muerth MJ, 2013, HYDROL EARTH SYST SC, V17, P1189, DOI 10.5194/hess-17-1189-2013
   Mullan D, 2012, AGR FOREST METEOROL, V156, P18, DOI 10.1016/j.agrformet.2011.12.004
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Nearing MA, 2004, J SOIL WATER CONSERV, V59, P43
   New M, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006289
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Nikulin G, 2012, J CLIMATE, V25, P6057, DOI 10.1175/JCLI-D-11-00375.1
   Nunes JP, 2013, CATENA, V102, P27, DOI 10.1016/j.catena.2011.04.001
   O'Gorman PA, 2009, P NATL ACAD SCI USA, V106, P14773, DOI 10.1073/pnas.0907610106
   Oguntunde PG, 2013, CLIM DYNAM, V40, P81, DOI 10.1007/s00382-012-1498-6
   Op de Hipt F, 2017, WATER-SUI, V9, DOI 10.3390/w9020101
   Oudin L, 2005, J HYDROL, V303, P290, DOI 10.1016/j.jhydrol.2004.08.026
   Oyerinde GT, 2017, CLIMATE, V5, DOI 10.3390/cli5010008
   Paeth H, 2011, ATMOS SCI LETT, V12, P75, DOI 10.1002/asl.306
   Pandey A, 2016, CATENA, V147, P595, DOI 10.1016/j.catena.2016.08.002
   Piani C, 2010, J HYDROL, V395, P199, DOI 10.1016/j.jhydrol.2010.10.024
   Ruelland D, 2012, J HYDROL, V424, P207, DOI 10.1016/j.jhydrol.2012.01.002
   Scoccimarro E, 2013, J CLIMATE, V26, P7902, DOI 10.1175/JCLI-D-12-00850.1
   Sharma D, 2007, HYDROL EARTH SYST SC, V11, P1373, DOI 10.5194/hess-11-1373-2007
   Slaymaker O, 2001, CAN GEOGR-GEOGR CAN, V45, P71, DOI 10.1111/j.1541-0064.2001.tb01169.x
   Sylla M.B., 2016, ADAPT CLIM CHANGE VA, P25, DOI DOI 10.1007/978-3-319-31499-0_3
   Sylla MB, 2016, CLIMATIC CHANGE, V134, P241, DOI 10.1007/s10584-015-1522-z
   Teutschbein C, 2012, J HYDROL, V456, P12, DOI 10.1016/j.jhydrol.2012.05.052
   Villani V., 2014, J. Urban Environ. Eng., V8, P142
   Vizy EK, 2012, J CLIMATE, V25, P5748, DOI 10.1175/JCLI-D-11-00693.1
   Wicks J.M., 1988, Physically-based mathematical modelling of catchment sediment yield
   Wicks JM, 1996, J HYDROL, V175, P213, DOI 10.1016/S0022-1694(96)80012-6
   Yang DW, 2003, HYDROL PROCESS, V17, P2913, DOI 10.1002/hyp.1441
   Yira Y, 2016, J HYDROL, V537, P187, DOI 10.1016/j.jhydrol.2016.03.052
   Yira Y, 2017, HYDROL EARTH SYST SC, V21, P2143, DOI 10.5194/hess-21-2143-2017
   Zhang H, 2011, J HYDROL, V396, P94, DOI 10.1016/j.jhydrol.2010.10.037
NR 103
TC 43
Z9 43
U1 3
U2 49
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0341-8162
EI 1872-6887
J9 CATENA
JI Catena
PD APR
PY 2018
VL 163
BP 63
EP 77
DI 10.1016/j.catena.2017.11.023
PG 15
WC Geosciences, Multidisciplinary; Soil Science; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Agriculture; Water Resources
GA FZ1JD
UT WOS:000427332000007
DA 2025-01-10
ER

PT J
AU Mazziotta, A
   Triviño, M
   Tikkanen, OP
   Kouki, J
   Strandman, H
   Mönkkönen, M
AF Mazziotta, Adriano
   Trivino, Maria
   Tikkanen, Olli-Pekka
   Kouki, Jari
   Strandman, Harri
   Monkkonen, Mikko
TI Applying a framework for landscape planning under climate change for the
   conservation of biodiversity in the Finnish boreal forest
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE climate change adaptation; climate vulnerability; conservation strategy;
   emission scenarios; forest ecosystem model; forest gap model; forest
   management; landscape conservation capacity; systematic conservation
   planning; woody debris
ID WOODLAND KEY HABITATS; NORWAY SPRUCE; SCOTS PINE; LAND-USE; SAPROXYLIC
   BEETLES; SPECIES RICHNESS; CHANGE IMPACTS; MANAGEMENT; FUTURE;
   VULNERABILITY
AB Conservation strategies are often established without consideration of the impact of climate change. However, this impact is expected to threaten species and ecosystem persistence and to have dramatic effects towards the end of the 21st century. Landscape suitability for species under climate change is determined by several interacting factors including dispersal and human land use. Designing effective conservation strategies at regional scales to improve landscape suitability requires measuring the vulnerabilities of specific regions to climate change and determining their conservation capacities. Although methods for defining vulnerability categories are available, methods for doing this in a systematic, cost-effective way have not been identified. Here, we use an ecosystem model to define the potential resilience of the Finnish forest landscape by relating its current conservation capacity to its vulnerability to climate change. In applying this framework, we take into account the responses to climate change of a broad range of red-listed species with different niche requirements. This framework allowed us to identify four categories in which representation in the landscape varies among three IPCC emission scenarios (B1, low; A1B, intermediate; A2, high emissions): (i) susceptible (B1=24.7%, A1B=26.4%, A2=26.2%), the most intact forest landscapes vulnerable to climate change, requiring management for heterogeneity and resilience; (ii) resilient (B1=2.2%, A1B=0.5%, A2=0.6%), intact areas with low vulnerability that represent potential climate refugia and require conservation capacity maintenance; (iii) resistant (B1=6.7%, A1B=0.8%, A2=1.1%), landscapes with low current conservation capacity and low vulnerability that are suitable for restoration projects; (iv) sensitive (B1=66.4%, A1B=72.3%, A2=72.0%), low conservation capacity landscapes that are vulnerable and for which alternative conservation measures are required depending on the intensity of climate change. Our results indicate that the Finnish landscape is likely to be dominated by a very high proportion of sensitive and susceptible forest patches, thereby increasing uncertainty for landscape managers in the choice of conservation strategies.
C1 [Mazziotta, Adriano; Trivino, Maria; Monkkonen, Mikko] Univ Jyvaskyla, Dept Biol & Environm Sci, Jyvaskyla 40014, Finland.
   [Tikkanen, Olli-Pekka] Finnish Forest Res Inst, Joensuu Unit, FI-80101 Joensuu, Finland.
   [Tikkanen, Olli-Pekka; Kouki, Jari; Strandman, Harri] Univ Eastern Finland, Sch Forest Sci, FI-80101 Joensuu, Finland.
C3 University of Jyvaskyla; Natural Resources Institute Finland (Luke);
   University of Eastern Finland
RP Mazziotta, A (corresponding author), Univ Jyvaskyla, Dept Biol & Environm Sci, POB 35, Jyvaskyla 40014, Finland.
EM adriano.mazziotta@jyu.fi
RI Kouki, Jari/B-6241-2008; Triviño, María/H-7740-2019; Mönkkönen,
   Mikko/A-2821-2011; Mazziotta, Adriano/C-1538-2018
OI Monkkonen, Mikko/0000-0001-8897-3314; Mazziotta,
   Adriano/0000-0003-2088-3798; Trivino, Maria/0000-0002-2420-3537;
   Strandman, Harri/0000-0002-9400-6424; Kouki, Jari/0000-0003-2624-8592
FU Academy of Finland [138032]; ongoing consortium project ADAPT - Academy
   of Finland, University of Eastern Finland [14907]; Finnish
   Meteorological Institute; Academy of Finland (AKA) [138032] Funding
   Source: Academy of Finland (AKA)
FX A.M., M.T. and M.M. thank the Academy of Finland (project 138032) for
   financial support. This work was also supported by the ongoing
   consortium project ADAPT (proj. 14907, 2012-2016), funded by the Academy
   of Finland, University of Eastern Finland (consortium project and team 1
   led by Prof. Heli Peltola) and Finnish Meteorological Institute (team 2
   led by Dr Jussi Kaurola). We thank Finnish Meteorological Institute for
   providing the grid based ACCLIM climate scenarios throughout Finland and
   Metla, the Finnish Forest Research Institute, for the perusal of the
   sub-sample of data on from the 9th National Forest Inventory.
   Furthermore, we gratefully acknowledge Prof. S. Kellomaki (School of
   Forest Sciences, University of Eastern Finland) for further development
   of SIMA model and instructions given for its use, which were needed for
   implementation of this research work. We thank SYKE, the Finnish
   Environment Institute, for the perusal of the data from the Hertta
   database. Finally, we are grateful to P. Halme, D. Podkopaev, T.
   Pohjanmies, K. Raatikainen and S. Varga for improving the manuscript
   with their comments and discussions.
CR Alagador D, 2014, J APPL ECOL, V51, P703, DOI 10.1111/1365-2664.12230
   ALBERT PS, 1995, BIOMETRICS, V51, P627, DOI 10.2307/2532950
   [Anonymous], THESIS U OULU
   [Anonymous], 1981, Fennia
   [Anonymous], 2011, SPSS statistics for windows
   [Anonymous], ILMATIETEEN LAITOS R
   [Anonymous], FINN STAT YB FOR
   [Anonymous], 2002, 11 EUR FOR I
   [Anonymous], 2013, Generalized Estimating Equations: GEE
   Barbet-Massin M, 2012, GLOBAL CHANGE BIOL, V18, P881, DOI 10.1111/j.1365-2486.2011.02552.x
   Bellard C, 2012, ECOL LETT, V15, P365, DOI 10.1111/j.1461-0248.2011.01736.x
   Bomhard B, 2005, GLOBAL CHANGE BIOL, V11, P1452, DOI 10.1111/j.1365-2486.2005.00997.x
   Bouget C, 2012, CAN J FOREST RES, V42, P1421, DOI [10.1139/X2012-078, 10.1139/x2012-078]
   Briceño-Elizondo E, 2006, FOREST ECOL MANAG, V232, P152, DOI 10.1016/j.foreco.2006.05.062
   Brook BW, 2008, TRENDS ECOL EVOL, V23, P453, DOI 10.1016/j.tree.2008.03.011
   CAJANDER A. K., 1949, ACTA FOREST FENNICA, V56, P1
   Chapin FS, 2007, AMBIO, V36, P528, DOI 10.1579/0044-7447(2007)36[528:MCCITE]2.0.CO;2
   Cramer W, 2001, GLOBAL CHANGE BIOL, V7, P357, DOI 10.1046/j.1365-2486.2001.00383.x
   Crossman ND, 2012, DIVERS DISTRIB, V18, P60, DOI 10.1111/j.1472-4642.2011.00851.x
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Bui DT, 2019, J ENVIRON MANAGE, V237, P476, DOI 10.1016/j.jenvman.2019.01.108
   Driscoll DA, 2012, CLIMATIC CHANGE, V111, P533, DOI [10.1007/s10584-011-0170-1, 10.1007/S10584-011-0170-1]
   Eggers J, 2008, GLOBAL CHANGE BIOL, V14, P2288, DOI 10.1111/j.1365-2486.2008.01653.x
   Engler R, 2004, J APPL ECOL, V41, P263, DOI 10.1111/j.0021-8901.2004.00881.x
   ESRI, 2011, ArcGIS Desktop: Release 10
   Garcia RA, 2012, GLOBAL CHANGE BIOL, V18, P1253, DOI 10.1111/j.1365-2486.2011.02605.x
   Garcia-Gonzalo J, 2007, CLIMATIC CHANGE, V81, P431, DOI 10.1007/s10584-006-9149-8
   Gillson L, 2013, TRENDS ECOL EVOL, V28, P135, DOI 10.1016/j.tree.2012.10.008
   Gossner MM, 2013, CONSERV BIOL, V27, P605, DOI 10.1111/cobi.12023
   Gustafsson L, 2015, CONSERV LETT, V8, P50, DOI 10.1111/conl.12087
   Halme P, 2013, BIOL CONSERV, V167, P248, DOI 10.1016/j.biocon.2013.08.029
   Hanski I, 2000, NATURE, V404, P755, DOI 10.1038/35008063
   Hautala H, 2011, RESTOR ECOL, V19, P418, DOI 10.1111/j.1526-100X.2009.00545.x
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hickler T, 2012, GLOBAL ECOL BIOGEOGR, V21, P50, DOI 10.1111/j.1466-8238.2010.00613.x
   Hjältén J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0041100
   Hynynen J, 2005, FOREST ECOL MANAG, V207, P5, DOI 10.1016/j.foreco.2004.10.015
   Junninen K, 2006, ECOGRAPHY, V29, P75, DOI 10.1111/j.2005.0906-7590.04358.x
   Kellomaki S., 1992, Sima: a Model for Forest Succession Based on the Carbon and Nitrogen Cycles with Application to Silvicultural Management of the Forest Ecosystem
   Kellomäki S, 2008, PHILOS T R SOC B, V363, P2341, DOI 10.1098/rstb.2007.2204
   Kellomaki Seppo, 1992, Silva Fennica, V26, P1
   Klausmeyer KR, 2011, ECOSPHERE, V2, DOI 10.1890/ES11-00044.1
   Kolstrom M, 1998, ECOL MODEL, V111, P17, DOI 10.1016/S0304-3800(98)00102-1
   Kouki J, 2007, UHANALAISTEN LAHOPUU
   Kujala H, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0053315
   Laita A, 2010, BIOL CONSERV, V143, P1212, DOI 10.1016/j.biocon.2010.02.029
   Lassauce A, 2011, ECOL INDIC, V11, P1027, DOI 10.1016/j.ecolind.2011.02.004
   Lehtomäki J, 2009, FOREST ECOL MANAG, V258, P2439, DOI 10.1016/j.foreco.2009.08.026
   Lindenmayer DB, 2007, OIKOS, V116, P1220, DOI 10.1111/j.2007.0030-1299.15683.x
   Lindner M, 2010, FOREST ECOL MANAG, V259, P698, DOI 10.1016/j.foreco.2009.09.023
   Mantyka-Pringle CS, 2012, GLOBAL CHANGE BIOL, V18, P1239, DOI 10.1111/j.1365-2486.2011.02593.x
   Martikainen P, 2000, BIOL CONSERV, V94, P199, DOI 10.1016/S0006-3207(99)00175-5
   Martikainen Petri, 2001, Ecological Bulletins, V49, P205
   Mazziotta A, 2014, EUR J FOREST RES, V133, P405, DOI 10.1007/s10342-013-0773-3
   Mönkkönen M, 1999, BIODIVERS CONSERV, V8, P85, DOI 10.1023/A:1008813225086
   Mönkkönen M, 2014, J ENVIRON MANAGE, V134, P80, DOI 10.1016/j.jenvman.2013.12.021
   Mönkkönen M, 2011, EUR J FOREST RES, V130, P717, DOI 10.1007/s10342-010-0461-5
   Mori AS, 2013, BIOL CONSERV, V165, P115, DOI 10.1016/j.biocon.2013.05.020
   Nabuurs GJ, 2007, EUR J FOREST RES, V126, P391, DOI 10.1007/s10342-006-0158-y
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Oliver TH, 2012, J APPL ECOL, V49, P1247, DOI 10.1111/1365-2664.12003
   Pakkala T, 2002, SILVA FENN, V36, P279, DOI 10.14214/sf.563
   PASTOR J, 1986, BIOGEOCHEMISTRY, V2, P3, DOI 10.1007/BF02186962
   Penttilä R, 2004, BIOL CONSERV, V117, P271, DOI 10.1016/j.biocon.2003.12.007
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Rabinowitsch-Jokinen R, 2010, SILVA FENN, V44, P51, DOI 10.14214/sf.162
   Ranius T, 2011, BIODIVERS CONSERV, V20, P2867, DOI 10.1007/s10531-011-0143-8
   Rassi P., 2001, The 2000 Red List of Finnish Species
   Raupach MR, 2007, P NATL ACAD SCI USA, V104, P10288, DOI 10.1073/pnas.0700609104
   Riffell S, 2011, FOREST ECOL MANAG, V261, P878, DOI 10.1016/j.foreco.2010.12.021
   Routa J, 2011, FORESTRY, V84, P159, DOI 10.1093/forestry/cpr003
   Ruckstuhl KE, 2008, PHILOS T R SOC B, V363, P2245, DOI 10.1098/rstb.2007.2196
   Schmitz OJ, 2003, BIOSCIENCE, V53, P1199, DOI 10.1641/0006-3568(2003)053[1199:ERTGCC]2.0.CO;2
   Shorohova E, 2008, FOREST ECOL MANAG, V255, P3606, DOI 10.1016/j.foreco.2008.02.042
   Similä M, 2003, FOREST ECOL MANAG, V174, P365, DOI 10.1016/S0378-1127(02)00061-0
   Snover AK, 2013, CONSERV BIOL, V27, P1147, DOI 10.1111/cobi.12163
   Stokland J., 2012, Biodiversity in Dead Wood
   Stokland JN., 2001, Ecol. Bull., V49, P71
   Stokland JN, 2011, FOREST ECOL MANAG, V261, P1707, DOI 10.1016/j.foreco.2011.01.003
   Summers DM, 2012, GLOBAL CHANGE BIOL, V18, P2335, DOI 10.1111/j.1365-2486.2012.02700.x
   Thuiller W, 2005, GLOBAL ECOL BIOGEOGR, V14, P347, DOI 10.1111/j.1466-822x.2005.00162.x
   Thuiller W, 2007, NATURE, V448, P550, DOI 10.1038/448550a
   Tikkanen OP, 2007, BIOL CONSERV, V140, P359, DOI 10.1016/j.biocon.2007.08.020
   Tikkanen OP, 2006, ANN ZOOL FENN, V43, P373
   Tikkanen OP, 2012, EUR J FOREST RES, V131, P1411, DOI 10.1007/s10342-012-0607-8
   Tikkanen OP, 2009, DIVERS DISTRIB, V15, P852, DOI 10.1111/j.1472-4642.2009.00590.x
   Timonen J, 2010, SCAND J FOREST RES, V25, P309, DOI 10.1080/02827581.2010.497160
   Travis JMJ, 2003, P ROY SOC B-BIOL SCI, V270, P467, DOI 10.1098/rspb.2002.2246
   Tuomi M, 2011, ECOL MODEL, V222, P709, DOI 10.1016/j.ecolmodel.2010.10.025
   Walther GR, 2005, P ROY SOC B-BIOL SCI, V272, P1427, DOI 10.1098/rspb.2005.3119
   Walther GR, 2002, NATURE, V416, P389, DOI 10.1038/416389a
   Watson JEM, 2013, NAT CLIM CHANGE, V3, P989, DOI [10.1038/NCLIMATE2007, 10.1038/nclimate2007]
   Wisz MS, 2008, DIVERS DISTRIB, V14, P763, DOI 10.1111/j.1472-4642.2008.00482.x
NR 93
TC 20
Z9 22
U1 0
U2 7
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1354-1013
EI 1365-2486
J9 GLOBAL CHANGE BIOL
JI Glob. Change Biol.
PD FEB
PY 2015
VL 21
IS 2
BP 637
EP 651
DI 10.1111/gcb.12677
PG 15
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA CA1DE
UT WOS:000348652400013
PM 25044467
OA Green Accepted, Green Published
DA 2025-01-10
ER

PT C
AU Vrolijks, L
   Spatafore, A
   Mittal, AS
AF Vrolijks, Luc
   Spatafore, Ashley
   Mittal, Anisha S.
BE OttoZimmermann, K
TI Comparative Research on the Adaptation Strategies of Ten Urban Climate
   Plans
SO RESILIENT CITIES: CITIES AND ADAPTATION TO CLIMATE CHANGE - PROCEEDINGS
   OF THE GLOBAL FORUM 2010
SE Local Sustainability
LA English
DT Proceedings Paper
CT 1st Annual Global Forum on Cities and Adaptation to Climate Change.
   Resilient Cities 2010
CY MAY 28-30, 2010
CL ICLEI, Bonn, GERMANY
SP EU European Regional Dev Fund, State N Rhine Westphalia, Fdn Int Dialogue Savings Bank Bonn, Solar World, Rockefeller Fdn, UNISDR, USAID, World Bank Inst
HO ICLEI
DE Climate adaptation strategies; Climate proofing; City climate plan
   analysis; Urban vulnerability analysis; Risk appraisal
AB Urban climate plans often focus primarily on reducing greenhouse gases. However, some plans are evolving from technical CO, emissions reduction strategies towards strategies that cover a broader range of issues. Adaptation or climate-proofing components are becoming a major focus of attention for climate plans. This study analyses the climate plans of ten cities and examines the adaptation requirements and strategies that each have included within their plans. It examines how each city perceives its hazard profile, and analyses what changes are to be expected under the influence of climate change. The paper also reviews each city's urban vulnerability and discusses the current and expected future vulnerability as explained in their climate plans. The interpretation of the climate risk of each city provides the analytical framework for the analysis of the adaptation strategies. The study reviews how the various components of the climate risk are being addressed. It carries out this strategic analysis across the ten cities globally, and analyses the differences and similarities between each. The paper concludes with recommendations for future urban climate plans and highlights how climate adaptation strategies can be mainstreamed.
C1 [Vrolijks, Luc; Spatafore, Ashley; Mittal, Anisha S.] Urban Progress Design, New York, NY 10013 USA.
EM luc@urbanprogress.com; ashley@urbanprogress.com;
   anisha@urbanprogress.com
CR [Anonymous], age of climate change
   [Anonymous], 2007 KING COUNT CLIM
   [Anonymous], 2007, PlaNYC: A Greener, Greater New York
   [Anonymous], 2006, SEATTLE CLIMATE CHAN
   [Anonymous], 2008, Chicago climate action plan
   City of Madrid, 2008, CITY MADRID PLAN SUS
   City of Miami, 2008, MIPLAN CITY MIAMI CL
   *DUTCH DELT COMM, 2008, WORK TOG WAT LIV LAN
   HAYHOE K, 2007, CLIMATE CHANGE CHICA
   New York City Department of Environmental Protection (NYC DEP), 2008, 1 NYC DEP
   *NYC DEP, 2009, CLIM RISK INF
   *SF DOE SAN FRANC, 2004, CLIM ACT PLAN SAN FR
   *SFB CDC, 2009, LIV RIS BAY VULN AD
   Snover A.K., 2007, PREPARING CLIMATE CH
   *TOK METR GOV, 2008, TOK METR ENV MAST PL
   *TOK METR GOV, 2007, TOK CLIM CHANG STRAT
   *UNISDR, 2008, CLIM RES CIT 2008 PR
   *US C MAYORS, 2009, US MAYORS CLIM PROT
   2008, SEOUL CLIMATE CHANGE
   2009, NEW AMSTERDAM CLIMAT
NR 20
TC 2
Z9 2
U1 1
U2 26
PU SPRINGER
PI NEW YORK
PA 233 SPRING STREET, NEW YORK, NY 10013, UNITED STATES
BN 978-94-007-0784-9
J9 LOCAL SUSTAIN
PY 2011
VL 1
BP 193
EP 203
DI 10.1007/978-94-007-0785-6_20
PG 11
WC Environmental Sciences; Environmental Studies; Urban Studies
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Environmental Sciences & Ecology; Urban Studies
GA BVQ12
UT WOS:000292277300020
DA 2025-01-10
ER

PT J
AU Porth, I
   Klápste, J
   McKown, AD
   La Mantia, J
   Guy, RD
   Ingvarsson, PK
   Hamelin, R
   Mansfield, SD
   Ehlting, J
   Douglas, CJ
   El-Kassaby, YA
AF Porth, Ilga
   Klapste, Jaroslav
   McKown, Athena D.
   La Mantia, Jonathan
   Guy, Robert D.
   Ingvarsson, Par K.
   Hamelin, Richard
   Mansfield, Shawn D.
   Ehlting, Juergen
   Douglas, Carl J.
   El-Kassaby, Yousry A.
TI Evolutionary Quantitative Genomics of <i>Populus</i> <i>trichocarpa</i>
SO PLOS ONE
LA English
DT Article
ID SINGLE NUCLEOTIDE POLYMORPHISMS; SPRUCE PICEA-SITCHENSIS; LOCAL
   ADAPTATION; TRAIT VARIATION; GENE FLOW; ARABIDOPSIS-THALIANA;
   POPULATION-STRUCTURE; NATURAL-POPULATIONS; BLACK COTTONWOOD;
   CLIMATE-CHANGE
AB Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing Q(ST)-F-ST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense QST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant QST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species' potential adaptive capacity to future climatic scenarios.
C1 [Porth, Ilga; Klapste, Jaroslav; McKown, Athena D.; La Mantia, Jonathan; Guy, Robert D.; Hamelin, Richard; El-Kassaby, Yousry A.] Univ British Columbia, Dept Forest & Conservat Sci, Vancouver, BC V6T 1Z4, Canada.
   [Porth, Ilga] Univ Laval, Fac Foresterie Geog & Geomat, Dept Sci Bois & Foret, Quebec City, PQ G1V 0A6, Canada.
   [Klapste, Jaroslav] Czech Univ Life Sci, Dept Genet & Physiol Forest Trees, Prague 16521, Czech Republic.
   [La Mantia, Jonathan] USDA, Corn Soybean & Wheat Qual Res Unit, Wooster, OH 44691 USA.
   [Ingvarsson, Par K.] Umea Univ, Dept Ecol & Environm Sci, SE-90187 Umea, Sweden.
   [Mansfield, Shawn D.] Univ British Columbia, Dept Wood Sci, Vancouver, BC V6T 1Z4, Canada.
   [Ehlting, Juergen] Univ Victoria, Dept Biol, Victoria, BC V8W 3N5, Canada.
   [Ehlting, Juergen] Univ Victoria, Ctr Forest Biol, Victoria, BC V8W 3N5, Canada.
   [Douglas, Carl J.] Univ British Columbia, Dept Bot, Vancouver, BC V6T 1Z4, Canada.
C3 University of British Columbia; Laval University; Czech University of
   Life Sciences Prague; United States Department of Agriculture (USDA);
   Umea University; University of British Columbia; University of Victoria;
   University of Victoria; University of British Columbia
RP El-Kassaby, YA (corresponding author), Univ British Columbia, Dept Forest & Conservat Sci, Vancouver, BC V6T 1Z4, Canada.
EM y.el-kassaby@ubc.ca
RI Ingvarsson, Pär/G-2748-2010; Mansfield, Shawn/AFT-9117-2022; El-Kassaby,
   Yousry/K-9856-2016; Guy, Robert/GPX-8421-2022; Porth, Ilga/N-4862-2015;
   Hamelin, Richard/F-7006-2010; Klapste, Jaroslav/B-6668-2016
OI Porth, Ilga/0000-0002-9344-6348; Ingvarsson, Par/0000-0001-9225-7521;
   Mansfield, Shawn/0000-0002-0175-554X; Hamelin,
   Richard/0000-0003-4006-532X; McKown, Athena/0000-0002-7402-9952;
   Ehlting, Jurgen/0000-0003-2302-696X; Klapste,
   Jaroslav/0000-0001-5504-3735
FU Genome British Columbia Applied Genomics Innovation Program [103BIO];
   Genome Canada Large-Scale Applied Research Project [168BIO]
FX This work was supported by Genome British Columbia Applied Genomics
   Innovation Program (Project 103BIO) and Genome Canada Large-Scale
   Applied Research Project (Project 168BIO), funds to RDG, RCH, JE, SDM,
   CJD, and YE-K.
CR Aitken S.N., 2013, ANNU REV ECOL EVOL S, V44, P367, DOI DOI 10.1146/annurev-ecolsys-110512-135747
   Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   Allendorf FW, 2010, NAT REV GENET, V11, P697, DOI 10.1038/nrg2844
   Anderson JT, 2011, TRENDS GENET, V27, P258, DOI 10.1016/j.tig.2011.04.001
   [Anonymous], 2010, NAT GENET, V42, P551, DOI 10.1038/ng0710-551
   [Anonymous], 1998, Genetics and Analysis of Quantitative Traits (Sinauer)
   Antao T, 2008, BMC BIOINFORMATICS, V9, DOI 10.1186/1471-2105-9-323
   Bai H, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0072126
   Beaumont MA, 1996, P ROY SOC B-BIOL SCI, V263, P1619, DOI 10.1098/rspb.1996.0237
   Bivand R, 2014, SPDEP SPATIAL DEPEND
   Black BL, 2002, TREE PHYSIOL, V22, P717, DOI 10.1093/treephys/22.10.717
   Camañes G, 2012, PLANT PHYSIOL, V158, P1054, DOI 10.1104/pp.111.184424
   Carroll A, 2009, ANNU REV PLANT BIOL, V60, P165, DOI 10.1146/annurev.arplant.043008.092125
   Carter AJR, 2005, THEOR POPUL BIOL, V68, P179, DOI 10.1016/j.tpb.2005.05.002
   CHANDRASHEKAR M, 1981, PHYTOPATHOLOGY, V71, P421, DOI 10.1094/Phyto-71-421
   Chen J, 2012, GENETICS, V191, P865, DOI 10.1534/genetics.112.140749
   Cronk QCB, 2005, NEW PHYTOL, V166, P39, DOI 10.1111/j.1469-8137.2005.01369.x
   Di Giuseppe E, 2013, THEOR APPL CLIMATOL, V114, P39, DOI 10.1007/s00704-012-0801-0
   Duarte JM, 2006, MOL BIOL EVOL, V23, P469, DOI 10.1093/molbev/msj051
   Eckenwalder J.E., 1996, Systematics and Evolution of Populus. Biology of Populus and its Implications for Management and Conservation. Part I
   Eckert AJ, 2010, MOL ECOL, V19, P3789, DOI 10.1111/j.1365-294X.2010.04698.x
   Endler J.A., 1977, Monographs in Population Biology, pi
   Epperson BK., 2003, GEOGRAPHICAL GENETIC
   Evans LM, 2014, NAT GENET, V46, P1089, DOI 10.1038/ng.3075
   Eveno E, 2008, MOL BIOL EVOL, V25, P417, DOI 10.1093/molbev/msm272
   Fabbrini F, 2012, BMC PLANT BIOL, V12, DOI 10.1186/1471-2229-12-47
   Fournier-Level A, 2011, SCIENCE, V334, P86, DOI 10.1126/science.1209271
   Fracheboud Y, 2009, PLANT PHYSIOL, V149, P1982, DOI 10.1104/pp.108.133249
   Frentiu FD, 2008, P R SOC B, V275, P639, DOI 10.1098/rspb.2007.1032
   Geraldes A, 2013, MOL ECOL RESOUR, V13, P306, DOI 10.1111/1755-0998.12056
   Geraldes A, 2014, EVOLUTION, V68, P3260, DOI 10.1111/evo.12497
   Geraldes A, 2011, MOL ECOL RESOUR, V11, P81, DOI 10.1111/j.1755-0998.2010.02960.x
   Gilmour A.R., 2015, ASREML USER GUIDE RE
   Hancock AM, 2011, SCIENCE, V334, P83, DOI 10.1126/science.1209244
   Hänninen H, 2011, TRENDS PLANT SCI, V16, P412, DOI 10.1016/j.tplants.2011.05.001
   Hansen MM, 2012, MOL ECOL, V21, P1311, DOI 10.1111/j.1365-294X.2011.05463.x
   Hemani G, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003295
   Henderson C. R., 1984, APPL LINEAR MODELS A
   Himelblau E, 2001, J PLANT PHYSIOL, V158, P1317, DOI 10.1078/0176-1617-00608
   Holliday JA, 2008, NEW PHYTOL, V178, P103, DOI 10.1111/j.1469-8137.2007.02346.x
   Holliday JA, 2012, P ROY SOC B-BIOL SCI, V279, P1675, DOI 10.1098/rspb.2011.1805
   HOWE GT, 1995, PHYSIOL PLANTARUM, V93, P695, DOI 10.1111/j.1399-3054.1995.tb05119.x
   Jannink JL, 2007, GENETICS, V176, P553, DOI 10.1534/genetics.106.062992
   Jombart T, 2008, BIOINFORMATICS, V24, P1403, DOI 10.1093/bioinformatics/btn129
   Joost S, 2007, MOL ECOL, V16, P3955, DOI 10.1111/j.1365-294X.2007.03442.x
   Kalcsits LA, 2009, TREES-STRUCT FUNCT, V23, P971, DOI 10.1007/s00468-009-0339-7
   Keller SR, 2012, MOL BIOL EVOL, V29, P3143, DOI 10.1093/molbev/mss121
   Kremer A, 2012, HEREDITY, V108, P375, DOI 10.1038/hdy.2011.81
   Kremer A, 2012, ECOL LETT, V15, P378, DOI 10.1111/j.1461-0248.2012.01746.x
   La Mantia J, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0078423
   Larisch C, 2012, PLANT PHYSIOL, V160, P1515, DOI 10.1104/pp.112.202291
   Le Corre V, 2012, MOL ECOL, V21, P1548, DOI 10.1111/j.1365-294X.2012.05479.x
   Lefevre F, 2013, ANN FOREST SCI, P1
   LEWONTIN RC, 1973, GENETICS, V74, P175
   Lexer C, 2012, NEW PHYTOL, V196, P652, DOI 10.1111/j.1469-8137.2012.04362.x
   Lind MI, 2011, EVOLUTION, V65, P684, DOI 10.1111/j.1558-5646.2010.01122.x
   Lippert C, 2013, SCI REP-UK, V3, DOI 10.1038/srep01815
   Luikart G, 2003, NAT REV GENET, V4, P981, DOI 10.1038/nrg1226
   Luquez V, 2008, TREE GENET GENOMES, V4, P279, DOI 10.1007/s11295-007-0108-y
   McKay JK, 2002, TRENDS ECOL EVOL, V17, P285, DOI 10.1016/S0169-5347(02)02478-3
   McKown AD, 2014, MOL ECOL, V23, P5771, DOI 10.1111/mec.12969
   McKown AD, 2014, NEW PHYTOL, V203, P535, DOI 10.1111/nph.12815
   McKown AD, 2014, NEW PHYTOL, V201, P1263, DOI 10.1111/nph.12601
   McKown AD, 2013, OECOLOGIA, V172, P653, DOI 10.1007/s00442-012-2531-5
   Mimura M, 2007, HEREDITY, V99, P224, DOI 10.1038/sj.hdy.6800987
   MORAN PAP, 1950, BIOMETRIKA, V37, P17, DOI 10.2307/2332142
   Namroud MC, 2008, MOL ECOL, V17, P3599, DOI 10.1111/j.1365-294X.2008.03840.x
   Petterle A, 2013, CURR OPIN PLANT BIOL, V16, P301, DOI 10.1016/j.pbi.2013.02.006
   Porth I., 2014, Diversity, V6, P283, DOI 10.3390/d6020283
   Porth I, 2015, BIOTECHNOL J, V10, P510, DOI 10.1002/biot.201400194
   Porth I, 2013, NEW PHYTOL, V200, P710, DOI 10.1111/nph.12422
   Porth I, 2013, NEW PHYTOL, V197, P777, DOI 10.1111/nph.12014
   Prunier J, 2011, MOL ECOL, V20, P1702, DOI 10.1111/j.1365-294X.2011.05045.x
   Pujol B, 2008, MOL ECOL, V17, P4782, DOI 10.1111/j.1365-294X.2008.03958.x
   Ritland K, 1996, EVOLUTION, V50, P1074, DOI [10.2307/2410648, 10.1111/j.1558-5646.1996.tb02348.x]
   Rohde A, 2011, TREE PHYSIOL, V31, P472, DOI 10.1093/treephys/tpr038
   Ruttink T, 2007, PLANT CELL, V19, P2370, DOI 10.1105/tpc.107.052811
   Saether SA, 2007, J EVOLUTION BIOL, V20, P1563, DOI 10.1111/j.1420-9101.2007.01328.x
   Sannigrahi P, 2010, BIOFUEL BIOPROD BIOR, V4, P209, DOI 10.1002/bbb.206
   Savolainen O, 2013, NAT REV GENET, V14, P807, DOI 10.1038/nrg3522
   SCHNEE FB, 1984, EVOLUTION, V38, P42, DOI 10.1111/j.1558-5646.1984.tb00258.x
   Schnute Jon T., 2004, Canadian Technical Report of Fisheries and Aquatic Sciences, V2549, P1
   Slavov GT, 2010, HEREDITY, V105, P348, DOI 10.1038/hdy.2010.73
   Slavov GT, 2012, NEW PHYTOL, V196, P713, DOI 10.1111/j.1469-8137.2012.04258.x
   Slavov GT, 2010, PLANT GENET GENOMICS, V8, P15, DOI 10.1007/978-1-4419-1541-2_2
   Soolanayakanahally RY, 2013, PLANT CELL ENVIRON, V36, P116, DOI 10.1111/j.1365-3040.2012.02560.x
   Sork VL, 2013, TREE GENET GENOMES, P1
   Stanton BJ, 2010, PLANT GENET GENOMICS, V8, P309, DOI 10.1007/978-1-4419-1541-2_14
   Stinchcombe JR, 2008, HEREDITY, V100, P158, DOI 10.1038/sj.hdy.6800937
   Tsumura Y, 2012, HEREDITY, V109, P349, DOI 10.1038/hdy.2012.50
   VanRaden PM, 2008, J DAIRY SCI, V91, P4414, DOI 10.3168/jds.2007-0980
   Wang TL, 2012, J APPL METEOROL CLIM, V51, P16, DOI 10.1175/JAMC-D-11-043.1
   Wang YY, 2011, PLANT CELL, V23, P1945, DOI 10.1105/tpc.111.083618
   Whitlock MC, 2008, MOL ECOL, V17, P1885, DOI 10.1111/j.1365-294X.2008.03712.x
   Whitlock MC, 2009, GENETICS, V183, P1055, DOI 10.1534/genetics.108.099812
   Wimmer V, 2012, BIOINFORMATICS, V28, P2086, DOI 10.1093/bioinformatics/bts335
   Xie CY, 2009, CAN J FOREST RES, V39, P519, DOI 10.1139/X08-190
   Yang WY, 2012, NAT GENET, V44, P725, DOI 10.1038/ng.2285
   Yeaman S, 2013, P NATL ACAD SCI USA, V110, pE1743, DOI 10.1073/pnas.1219381110
NR 99
TC 20
Z9 24
U1 2
U2 49
PU PUBLIC LIBRARY SCIENCE
PI SAN FRANCISCO
PA 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA
SN 1932-6203
J9 PLOS ONE
JI PLoS One
PD NOV 23
PY 2015
VL 10
IS 11
AR e0142864
DI 10.1371/journal.pone.0142864
PG 25
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA CX7AW
UT WOS:000365853900043
PM 26599762
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Elwahsh, H
   Allakany, A
   Alsabaan, M
   Ibrahem, MI
   El-Shafeiy, E
AF Elwahsh, Haitham
   Allakany, Alaa
   Alsabaan, Maazen
   Ibrahem, Mohamed I.
   El-Shafeiy, Engy
TI A Deep Learning Technique to Improve Road Maintenance Systems Based on
   Climate Change
SO APPLIED SCIENCES-BASEL
LA English
DT Article
DE deep learning; road maintenance systems; climate change; sensors data;
   RMSDC technique; multivariate classification; ConvLSTM
ID PAVEMENT MAINTENANCE; OPTIMIZATION; PERFORMANCE
AB Road maintenance systems (RMS) are crucial for maintaining safe and efficient road networks. The impact of climate change on road maintenance systems is a concern as it makes them more susceptible to weather events and subsequent damages. To tackle this issue, we propose an RMSDC (Road Maintenance Systems Using Deep Learning and Climate Adaptation) technique to improve road maintenance systems based on Deep learning and Climate Adaptation. RMSDC aims to use the multivariate classification technique and divides the dataset into training and test datasets. The RMSDC combines Convolutional Long Short-Term Memory (ConvLSTM) techniques with road weather information and sensor data. However, in emerging nations, the effects of climate change are already apparent, which makes road networks particularly susceptible to extreme weather, floods, and landslides. Therefore, climate adaptation of road networks is essential, especially in developing nations with limited financial resources. To address this issue, we propose an intelligent and effective RMSDC that utilizes deep learning algorithms based on climate change predictions. The ConvLSTM block effectively captures the relationship between input features over time to calculate the root-mean deviation (RMSD). We evaluate RMSDC performance against frameworks for downscaling climate variables using two metrics: root-mean-square error (RMSE) and mean absolute difference. Through real evaluations, RMSDC consistently outperforms approaches with a reduced RMSE of 0.26. These quantitative results highlight how effective RMSDC is in addressing maintenance systems on road networks leading to proactive road maintenance strategies that enhance traffic safety, reduce costs, and improve environmental sustainability.
C1 [Elwahsh, Haitham; Allakany, Alaa] Kafrelsheikh Univ, Fac Comp & Informat, Comp Sci Dept, Kafrelsheikh 33516, Egypt.
   [Alsabaan, Maazen] King Saud Univ, Coll Comp & Informat Sci, Dept Comp Engn, Riyadh 11543, Saudi Arabia.
   [Ibrahem, Mohamed I.] Augusta Univ, Sch Comp & Cyber Sci, Augusta, GA 30912 USA.
   [Ibrahem, Mohamed I.] Benha Univ, Fac Engn Shoubra, Dept Elect Engn, Cairo 11672, Egypt.
   [El-Shafeiy, Engy] Univ Sadat City, Fac Comp & Artificial Intelligence, Dept Comp Sci, Sadat City 32897, Monufia, Egypt.
C3 Egyptian Knowledge Bank (EKB); Kafrelsheikh University; King Saud
   University; University System of Georgia; Augusta University; Egyptian
   Knowledge Bank (EKB); Benha University; Egyptian Knowledge Bank (EKB);
   University of Sadat City
RP Elwahsh, H (corresponding author), Kafrelsheikh Univ, Fac Comp & Informat, Comp Sci Dept, Kafrelsheikh 33516, Egypt.
EM haitham.elwahsh@gmail.com; alaa.ellakani@kfs.edu.eg;
   malsabaan@ksu.edu.sa; engy.elshafeiy@fcai.usc.edu.eg
RI El-Shafeiy, Engy/AAS-5388-2020; Allakany, Alaa/GQY-8770-2022; ELWAHSH,
   HAITHAM/G-9493-2018
OI Ibrahem, Mohamed/0000-0002-8000-4161; Allakany,
   Alaa/0000-0001-6451-5407; Alsabaan, Maazen/0000-0001-8601-3184; ELWAHSH,
   HAITHAM/0000-0003-0920-2445
FU King Saud University, Riyadh, Saudi Arabia [RSPD2023R636]
FX This work was supported by Researchers Supporting Project number
   (RSPD2023R636), King Saud University, Riyadh, Saudi Arabia.
CR Aguilera-Martos I, 2022, Arxiv, DOI arXiv:2206.03179
   Alam MR, 2020, J CLEAN PROD, V273, DOI 10.1016/j.jclepro.2020.123106
   Angulo A., 2019, P MEX INT C ART INT
   [Anonymous], 2014, WORKING GROUP 2 CONT
   Asghari V, 2022, J CONSTR ENG M, V148, DOI 10.1061/(ASCE)CO.1943-7862.0002221
   Assaad R, 2020, J INFRASTRUCT SYST, V26, DOI 10.1061/(ASCE)IS.1943-555X.0000572
   Athanasiou A, 2020, COMPUT-AIDED CIV INF, V35, P565, DOI 10.1111/mice.12509
   Attari N, 2017, PR INT CONF DATA SC, P50, DOI 10.1109/DSAA.2017.72
   Azimi M, 2020, COMPUT-AIDED CIV INF, V35, P597, DOI 10.1111/mice.12517
   Bahdanau D, 2016, Arxiv, DOI [arXiv:1409.0473, DOI 10.48550/ARXIV.1409.0473]
   Cartwright E.D., 2021, Climate Energy, V38, P11
   Cheng CS, 2021, COMPUT-AIDED CIV INF, V36, P695, DOI 10.1111/mice.12658
   Cheng JX, 2020, IEEE ACCESS, V8, P39623, DOI 10.1109/ACCESS.2020.2974785
   Chopra P, 2018, ADV CIV ENG, V2018, DOI 10.1155/2018/5481705
   Climate Change Impacts, CLIM CHANG IMP CLIM
   Conell J., 2015, CONTEMP PACIFIC, VVolume 27
   COP22 Declaration on Accelerating Action on Transport Adaptation, COP22 DECL ACC ACT T
   Deka P.C., 2019, A Primer on Machine Learning Applications in Civil Engineering
   Donev V, 2020, INT J PAVEMENT ENG, V21, P583, DOI 10.1080/10298436.2018.1502433
   Dong C., 2015, arXiv, DOI 10.1109/TPAMI.2015.2439281
   Drees-Gross F., RESILIENT TRANSPORT
   France-Mensah J, 2018, J MANAGE ENG, V34, DOI 10.1061/(ASCE)ME.1943-5479.0000599
   Han CJ, 2021, CONSTR BUILD MATER, V299, DOI 10.1016/j.conbuildmat.2021.124278
   Hochreiter S, 1997, ADV NEUR IN, V9, P473
   Huang MY, 2021, J CLEAN PROD, V283, DOI 10.1016/j.jclepro.2020.124583
   Huang TG, 2023, INT J TRANSP SCI TEC, V12, P1, DOI 10.1016/j.ijtst.2021.10.007
   International Transport Forum, 2015, AD TRANSP INFR CLIM
   Irfan M, 2012, ENG OPTIMIZ, V44, P565, DOI 10.1080/0305215X.2011.588226
   Jahin MA, 2023, Arxiv, DOI arXiv:2107.06755
   Jiang S, 2020, COMPUT-AIDED CIV INF, V35, P549, DOI 10.1111/mice.12519
   Latifi M, 2023, Arxiv, DOI arXiv:2112.12589
   Li F., 2021, CARBON, V16, DOI [10.1007/978-981-15-6206-8, DOI 10.1007/978-981-15-6206-8]
   Liu YQ, 2020, EXPERT SYST APPL, V143, DOI 10.1016/j.eswa.2019.113082
   Liu Y, 2020, EUR J OPER RES, V283, P166, DOI 10.1016/j.ejor.2019.10.049
   Mann ME, 2017, SCI REP-UK, V7, DOI 10.1038/srep45242
   Mnih V, 2015, NATURE, V518, P529, DOI 10.1038/nature14236
   Naranjo-Pérez J, 2020, ENG STRUCT, V225, DOI 10.1016/j.engstruct.2020.111327
   NASA Global Climate Change, NASA GLOB CLIM CHANG
   Neves A.C., 2017, P INT C EXP VIBR AN
   Osorio-Lird A, 2018, STRUCT INFRASTRUCT E, V14, P1169, DOI 10.1080/15732479.2017.1402064
   Pellicer E, 2016, J CLEAN PROD, V113, P884, DOI 10.1016/j.jclepro.2015.11.010
   Piryonesi SM, 2020, J INFRASTRUCT SYST, V26, DOI 10.1061/(ASCE)IS.1943-555X.0000512
   Qiao JY, 2021, TRANSPORT RES A-POL, V148, P79, DOI 10.1016/j.tra.2021.02.021
   Qin Y, 2017, Arxiv, DOI arXiv:1704.02971
   Renard S, 2021, RESOUR CONSERV RECY, V167, DOI 10.1016/j.resconrec.2020.105240
   Sabour MR, 2021, ENVIRON PROCESS, V8, P1601, DOI 10.1007/s40710-021-00542-y
   Santero NJ, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/034011
   Santos J, 2022, INT J PAVEMENT ENG, V23, P425, DOI 10.1080/10298436.2020.1751161
   Saravi S, 2019, WATER-SUI, V11, DOI 10.3390/w11050973
   The Government of the Republic of Fiji, 2017, WORLD BANK CLIM VULN
   The World Bank, 2017, CLIM DIS RES TRANSP
   Torres-Machi C, 2017, J CLEAN PROD, V148, P90, DOI 10.1016/j.jclepro.2017.01.100
   United Nations UN and Climate Change, SCIENCE
   Vandal T, 2017, KDD'17: PROCEEDINGS OF THE 23RD ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P1663, DOI 10.1145/3097983.3098004
   Wang F, 2020, ENERG CONVERS MANAGE, V212, DOI 10.1016/j.enconman.2020.112766
   Wang H.Gangaram., 2014, Life Cycle Assessment of Asphalt Pavement Maintenance
   Watts N, 2018, LANCET, V392, P2479, DOI 10.1016/S0140-6736(18)32594-7
   Yamany MS, 2020, J INFRASTRUCT SYST, V26, DOI 10.1061/(ASCE)IS.1943-555X.0000542
   Yao LY, 2020, COMPUT-AIDED CIV INF, V35, P1230, DOI 10.1111/mice.12558
   Yu B, 2015, TRANSPORT RES D-TR E, V41, P64, DOI 10.1016/j.trd.2015.09.016
NR 60
TC 2
Z9 2
U1 6
U2 25
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2076-3417
J9 APPL SCI-BASEL
JI Appl. Sci.-Basel
PD AUG
PY 2023
VL 13
IS 15
AR 8899
DI 10.3390/app13158899
PG 18
WC Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials
   Science, Multidisciplinary; Physics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Engineering; Materials Science; Physics
GA O7BT6
UT WOS:001045325700001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Clarke, BJ
   Otto, FEL
   Jones, RG
AF Clarke, Ben J.
   Otto, Friederike E. L.
   Jones, Richard G.
TI Inventories of extreme weather events and impacts: Implications for loss
   and damage from and adaptation to climate extremes
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Extreme weather; Impacts; Disaster risk reduction; Vulnerability;
   Climate adaptation; Stocktaking
AB Extreme and impactful weather events of the recent past provide a vital but under-utilised data source for understanding present and future climate risks. Extreme event attribution (EEA) enables us to quantify the influence of anthropogenic climate change (ACC) on a given event in a way that can be tailored to stakeholder needs, thereby enhancing the potential utility of studying past events. Here we set out a framework for systematically recording key details of high-impact events on a national scale (using the UK and Puerto Rico as examples), combining recent advances in event attribution with the risk framework. These `inventories' inherently provide useful information depending on a user's interest. For example, as a compilation of the impacts of ACC, we find that in the UK since 2000, at least 1500 excess deaths are directly attributable to human-induced climate change, while in Puerto Rico the increased intensity of Hurricane Maria alone led to the deaths of up to 3670 people. We also explore how inventories form a foundation for further analysis, learning from past events. This involves identifying the most damaging hazards and crucially also vulnerabilities and exposure characteristics over time. To build a risk assessment for heat-related mortality in the UK we focus on a vulnerable group, elderly urban populations, and project changes in the hazard and exposure within the same framework. Without improved preparedness, the risk to this group is likely to increase by similar to 50% by 2028 and similar to 150% by 2043. In addition, the framework allows the exploration of the likelihood of otherwise unprecedented events, or 'Black Swans'. Finally, not only does it aid disaster preparedness and adaptation at local and national scales, such inventories also provide a new source of evidence for global stocktakes on adaptation and loss and damage such as mandated by the Paris Climate Agreement.
C1 [Clarke, Ben J.; Jones, Richard G.] Univ Oxford, Sch Geog & Environm, Oxford, England.
   [Otto, Friederike E. L.] Univ Oxford, Environm Change Inst, Oxford, England.
   [Jones, Richard G.] Met Off Hadley Ctr, Exeter, Devon, England.
C3 University of Oxford; University of Oxford; Met Office - UK; Hadley
   Centre
RP Clarke, BJ (corresponding author), Univ Oxford, Sch Geog & Environm, Oxford, England.
EM ben.clarke@jesus.ox.ac.uk
OI Jones, Richard/0000-0002-0904-3141
FU NERC Doctoral Training Partnership grant [NE/L002612/1]
FX Funding This work was supported by a NERC Doctoral Training Partnership
   grant NE/L002612/1. This funding body had no direct involvement in the
   conduct of the research or production of the article.
CR AghaKouchak A, 2014, GEOPHYS RES LETT, V41, P8847, DOI 10.1002/2014GL062308
   Ahmadalipour A, 2018, SCI TOTAL ENVIRON, V644, P520, DOI 10.1016/j.scitotenv.2018.07.023
   Allen M, 2003, NATURE, V421, P891, DOI 10.1038/421891a
   [Anonymous], 2018, SPECIAL REPORT GLOBA, DOI DOI 10.1002/EJOC.201200111
   [Anonymous], 2013, Heatwave Plan for England 2013'
   Arbuthnott KG, 2017, ENVIRON HEALTH-GLOB, V16, P1, DOI 10.1186/s12940-017-0322-5
   Baccini M, 2008, EPIDEMIOLOGY, V19, P711, DOI 10.1097/EDE.0b013e318176bfcd
   Birkmann J, 2010, SUSTAIN SCI, V5, P171, DOI 10.1007/s11625-010-0108-y
   Boyd E, 2017, NAT CLIM CHANGE, V7, P723, DOI 10.1038/NCLIMATE3389
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Byers E, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabf45
   Cardona OD, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P65
   Chartteron J., 2016, COSTS IMPACTS WINTER
   Christidis N, 2015, NAT CLIM CHANGE, V5, P46, DOI [10.1038/nclimate2468, 10.1038/NCLIMATE2468]
   Committee on Climate Change, 2016, UK CLIMATE CHANGE RI, P24
   Coumou D, 2012, NAT CLIM CHANGE, V2, P491, DOI 10.1038/NCLIMATE1452
   D'Ippoliti D, 2010, ENVIRON HEALTH-GLOB, V9, DOI 10.1186/1476-069X-9-37
   Daron J, 2019, INT J CLIMATOL, V39, P4784, DOI 10.1002/joc.6106
   de Bruijn K, 2017, ENVIRON SCI POLICY, V70, P21, DOI 10.1016/j.envsci.2017.02.001
   Dole R, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL046582
   Duvat VKE, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.478
   Eckstein D., 2019, Weather-related loss events in 2018 and 1999 to 2018: Global climate risk index 2020
   Fernandez A, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0119929
   Fischer EM, 2015, NAT CLIM CHANGE, V5, P560, DOI 10.1038/nclimate2617
   Frame DJ, 2020, CLIMATIC CHANGE, V160, P271, DOI 10.1007/s10584-020-02692-8
   Frame DJ, 2020, CLIMATIC CHANGE, V162, P781, DOI 10.1007/s10584-020-02729-y
   Gall M, 2015, INT J GLOBAL WARM, V8, P170, DOI 10.1504/IJGW.2015.071966
   Glotter M, 2017, NAT PLANTS, V3, DOI 10.1038/nplants.2016.193
   Guha-Sapir D., 2014, EM DAT INT DISASTER
   Guillod BP, 2018, HYDROL EARTH SYST SC, V22, P611, DOI 10.5194/hess-22-611-2018
   Guillod BP, 2017, GEOSCI MODEL DEV, V10, P1849, DOI 10.5194/gmd-10-1849-2017
   Hansen J, 2010, REV GEOPHYS, V48, DOI 10.1029/2010RG000345
   Harrington LJ, 2020, NAT CLIM CHANGE, V10, P796, DOI 10.1038/s41558-020-0851-8
   Haylock MR, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2008JD010201
   Hazeleger W, 2015, NAT CLIM CHANGE, V5, P107, DOI 10.1038/NCLIMATE2450
   Hazeleger W, 2012, CLIM DYNAM, V39, P2611, DOI 10.1007/s00382-011-1228-5
   Heaviside C, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0100-9
   Herring S., 2014, B AM METEOROL SOC
   Herring S.C., 2015, B AM METEOROL SOC
   Herring S.C., 2016, AM METEOROLOGICAL SO
   Herring S.C., 2020, B AM METEOROL SOC, DOI [10.1175/BAMS-explainingextremeevents2018.s1, DOI 10.1175/BAMS-EXPLAININGEXTREMEEVENTS2018.S1]
   Herring SC, 2019, B AM METEOROL SOC, V100, pS1, DOI 10.1175/BAMS-D-18-0307.1
   Herring SC, 2018, B AM METEOROL SOC, V99, pS1, DOI 10.1175/BAMS-D-17-0284.1
   Houze RA, 2011, B AM METEOROL SOC, V92, P291, DOI 10.1175/2010BAMS3173.1
   Huggel C, 2016, NAT CLIM CHANGE, V6, P901, DOI 10.1038/NCLIMATE3104
   James RA, 2019, CLIM RISK MANAGE POL, P113, DOI 10.1007/978-3-319-72026-5_5
   Jézéquel A, 2019, WEATHER CLIM EXTREME, V26, DOI 10.1016/j.wace.2019.100231
   Kalkuhl M, 2020, J ENVIRON ECON MANAG, V103, DOI 10.1016/j.jeem.2020.102360
   Kishore N, 2018, NEW ENGL J MED, V379, P162, DOI [10.1056/nejmsa1803972, 10.1056/NEJMsa1803972]
   Leach NJ, 2020, B AM METEOROL SOC, V101, pS41, DOI 10.1175/BAMS-D-19-0201.1
   Leonard M, 2014, WIRES CLIM CHANGE, V5, P113, DOI 10.1002/wcc.252
   Martín Y, 2017, NAT HAZARDS, V89, P367, DOI 10.1007/s11069-017-2969-1
   Massey N, 2015, Q J ROY METEOR SOC, V141, P1528, DOI 10.1002/qj.2455
   McCarthy M, 2019, WEATHER, V74, P390, DOI 10.1002/wea.3628
   Mitchell D, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/7/074006
   Muller JCY, 2014, WEATHER CLIM EXTREME, V3, P31, DOI 10.1016/j.wace.2014.03.009
   Munich R.E., 2018, STORMY YEAR TOPICS G
   Munich RE, 2016, Natural Catastrophes 2015 analyses, assessments, positions
   *OFF NAT STAT, 2019, NAT POP PROJ 2018 BA
   Osaka S, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102070
   Otto FEL, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050422
   Otto FEL, 2020, B AM METEOROL SOC, V101, pE1851, DOI 10.1175/BAMS-D-19-0317.1
   Otto FEL, 2020, B AM METEOROL SOC, V101, pE1972, DOI 10.1175/BAMS-D-20-0027.1
   Otto FEL, 2016, NAT CLIM CHANGE, V6, P813, DOI 10.1038/nclimate3089
   Otto FEL, 2015, CLIMATIC CHANGE, V132, P531, DOI 10.1007/s10584-015-1432-0
   Paranjothy S, 2011, BMC PUBLIC HEALTH, V11, DOI 10.1186/1471-2458-11-145
   Parker HR, 2017, CLIM POLICY, V17, P533, DOI 10.1080/14693062.2015.1124750
   Paté-Cornell E, 2012, RISK ANAL, V32, P1823, DOI 10.1111/j.1539-6924.2011.01787.x
   Peterson TC, 2013, B AM METEOROL SOC, V94, pS1, DOI 10.1175/BAMS-D-13-00085.1
   Peterson TC, 2012, B AM METEOROL SOC, V93, P1041, DOI 10.1175/BAMS-D-12-00021.1
   Pregnolato M, 2017, TRANSPORT RES D-TR E, V55, P67, DOI 10.1016/j.trd.2017.06.020
   Public Health England, 2019, HEATW MORT MON SUMM
   Rahmstorf S, 2011, P NATL ACAD SCI USA, V108, P17905, DOI 10.1073/pnas.1101766108
   Rasmijn LM, 2018, NAT CLIM CHANGE, V8, P381, DOI 10.1038/s41558-018-0114-0
   Schaller N, 2016, NAT CLIM CHANGE, V6, P627, DOI [10.1038/nclimate2927, 10.1038/NCLIMATE2927]
   Serdeczny O., 2019, CLIM RISK MANAGE POL, DOI 10.1007/978-3-319-72026-5_8
   Shaposhnikov D, 2014, EPIDEMIOLOGY, V25, P359, DOI 10.1097/EDE.0000000000000090
   Shepherd TG, 2016, CURR CLIM CHANGE REP, V2, P28, DOI 10.1007/s40641-016-0033-y
   Shepherd TG, 2015, NATURE, V522, P422, DOI 10.1038/522425a
   Sippel S, 2015, WEATHER CLIM SOC, V7, P224, DOI 10.1175/WCAS-D-14-00045.1
   Sornette D, 2009, SSRN Scholarly Paper 1596032, V2, P1, DOI [DOI 10.2139/SSRN.1596032, 10.2139/ssrn.1596032]
   Stott PA, 2004, NATURE, V432, P610, DOI 10.1038/nature03089
   Stott PA, 2016, WIRES CLIM CHANGE, V7, P23, DOI 10.1002/wcc.380
   Taleb N.N., 2007, The Black Swan: The Impact of the Highly Improbable, V2nd
   Tompkins EL, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.545
   van der Schrier G, 2018, CLIMATIC CHANGE, V148, P205, DOI 10.1007/s10584-018-2173-7
   Van Oldenborgh G. J., 2019, HUMAN CONTRIBUTION R
   van Oldenborgh GJ, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa9ef2
   Vautard R., 2019, WORLD WEATHER ATTRIB
   Welton G., 2011, The impact of Russia's 2010 grain export ban
   Wheatley S., 2017, RISK ANAL, DOI 10.1111/risa:12587
   Woo G., 2016, VARIANCE, V10, P1
   Woo G, 2019, FRONT EARTH SC-SWITZ, V7, DOI 10.3389/feart.2019.00340
   Zscheischler J, 2020, NAT REV EARTH ENV, V1, P333, DOI 10.1038/s43017-020-0060-z
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 95
TC 38
Z9 44
U1 5
U2 28
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2021
VL 32
AR 100285
DI 10.1016/j.crm.2021.100285
EA FEB 2021
PG 15
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA SU8EH
UT WOS:000663363000003
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU McElwee, P
   Nguyen, VHT
   Nguyen, DV
   Tran, NH
   Le, HVT
   Nghiem, TP
   Vu, HDT
AF McElwee, Pamela
   Van Hai Thi Nguyen
   Dung Viet Nguyen
   Nghi Huu Tran
   Hue Van Thi Le
   Tuyen Phuong Nghiem
   Huong Dieu Thi Vu
TI Using REDD plus Policy to Facilitate Climate Adaptation at the Local
   Level: Synergies and Challenges in Vietnam
SO FORESTS
LA English
DT Article
DE REDD; household livelihoods; climate adaptation; vulnerability; forest
   policy; land
ID ECOSYSTEM SERVICES; MITIGATION; FOREST; CARBON; VULNERABILITY; LESSONS;
   DEFORESTATION; COORDINATION; DEGRADATION; INTEGRATION
AB Attention has recently been paid to how REDD+ mitigation policies are integrated into other sectoral policies, particularly those dealing with climate adaptation at the national level. But there is less understanding of how subnational policy and local projects are able to incorporate attention to adaptation; therefore, we use a case study in Vietnam to discuss how REDD+ projects and policies address both concerns of mitigation and adaptation together at subnational levels. Through stakeholder interviews, focus groups, and household surveys in three provinces of Vietnam with REDD+ activities, our research sought to understand if REDD+ policies and projects on the ground acknowledge that climate change is likely to impact forests and forest users; if this knowledge is built into REDD+ policy and activities; how households in forested areas subject to REDD+ policy are vulnerable to climate change; and how REDD+ activities can help or hinder needed adaptations. Our findings indicate that there continues to be a lack of coordination between mitigation and adaptation policies in Vietnam, particularly with regard to REDD+. Policies for forest-based climate mitigation at the national and subnational level, as well as site-based projects, have paid little attention to the adaptation needs of local communities, many of whom are already suffering from noticeable weather changes in their localities, and there is insufficient discussion of how REDD+ activities could facilitate increased resilience. While there were some implicit and coincidental adaptation benefits of some REDD+ activities, most studied projects and policies did not explicitly target their activities to focus on adaptation or resilience, and in at least one case, negative livelihood impacts that have increased household vulnerability to climate change were documented. Key barriers to integration were identified, such as sectoral specialization; a lack of attention in REDD+ projects to livelihoods; and inadequate support for ecosystem-based adaptation.
C1 [McElwee, Pamela] Rutgers State Univ, Sch Environm & Biol Sci, Dept Human Ecol, New Brunswick, NJ 08901 USA.
   [Van Hai Thi Nguyen; Dung Viet Nguyen] People & Nat Reconciliat PanNat, Hanoi 10000, Vietnam.
   [Nghi Huu Tran] Tropenbos Int Vietnam TBI, Hue 530000, Vietnam.
   [Hue Van Thi Le; Tuyen Phuong Nghiem; Huong Dieu Thi Vu] Vietnam Natl Univ, Ctr Nat Resources & Environm Studies CRES, Hanoi 10000, Vietnam.
C3 Rutgers University System; Rutgers University New Brunswick; Vietnam
   National University Hanoi (VNU Hanoi) System
RP McElwee, P (corresponding author), Rutgers State Univ, Sch Environm & Biol Sci, Dept Human Ecol, New Brunswick, NJ 08901 USA.
EM pamela.mcelwee@rutgers.edu; van@nature.org.vn; dungnv@nature.org.vn;
   nghi@tropenbos.vn; thivanhue@gmail.com; tuyennghiem_cres@yahoo.com;
   huongvudieu@yahoo.com
RI McElwee, Pamela/AAP-1695-2020; McElwee, Pamela/A-9442-2009
OI NGUYEN, VAN THI HAI/0000-0003-4153-1150; McElwee,
   Pamela/0000-0003-3525-9285
FU National Science Foundation Geography and Regional Science Division
   [11028793]; Hatch funding of the US National Institute for Food and
   Agriculture (NIFA); US Agency for International Development (USAID);
   Tropenbos; PanNature
FX This research was made possible by a grant from the National Science
   Foundation Geography and Regional Science Division for the project
   "Downscaling REDD+ policies in developing countries: Assessing the
   impact of carbon payments on household decision-making and vulnerability
   to climate change in Vietnam" (grant #11028793) to McElwee, support to
   McElwee from Hatch funding of the US National Institute for Food and
   Agriculture (NIFA), and a US Agency for International Development
   (USAID) Partnerships for Enhanced Engagement in Research grant to the
   CRES, Tropenbos and PanNature for the project: "Research and capacity
   building on REDD+, livelihoods, and vulnerability in Vietnam: developing
   tools for social analysis of development planning". Dao Minh Truong
   contributed the figures. Additional people who contributed to the
   collection of data include Dao Minh Truong, Le Trong Toan, Ha Thi Thu
   Hue, Ha Thi Tu Anh, and Nguyen Xuan Lam. Thanks are due to Lo Quang
   Chieu, Vice-Director of Department of Agriculture and Rural Development
   in Dien Bien, the Hieu Commune People's Committee in Kon Tum, and Doan
   Van Thanh, Le Thi Kim Anh, Ho Tuan Quang, Nguyen Minh Tan and Nguyen Van
   Thieu in Kien Giang who facilitated fieldwork in these provinces.
CR Adger W.N., 2001, Living with Environmental Change
   Adger WN, 1999, WORLD DEV, V27, P249, DOI 10.1016/S0305-750X(98)00136-3
   [Anonymous], PAR AGR
   [Anonymous], RIVF
   [Anonymous], SYNERGIES REDD ADAPT
   [Anonymous], CLIMATE CHANGE 2007
   [Anonymous], 2015, CARBON CLIMATE LAW R
   [Anonymous], INT UNION FOREST RES
   Asian Disaster Preparedness Center, 2015, EC BAS APPR ADDR CLI, P1
   Atela JO, 2016, FOREST POLICY ECON, V65, P37, DOI 10.1016/j.forpol.2016.01.003
   Atela JO, 2015, J ENVIRON MANAGE, V157, P238, DOI 10.1016/j.jenvman.2015.04.015
   Ayers JM, 2009, ENVIRON MANAGE, V43, P753, DOI 10.1007/s00267-008-9223-2
   Beckman M, 2011, CLIM DEV, V3, P32, DOI 10.3763/cdev.2010.0065
   Bruun O., 2013, FRONTIERS CLIMATE EN
   Bruun O, 2012, WEATHER CLIM SOC, V4, P250, DOI 10.1175/WCAS-D-11-00040.1
   Cerbu GA, 2011, ENVIRON SCI POLICY, V14, P168, DOI 10.1016/j.envsci.2010.09.007
   Chong J, 2014, INT ENVIRON AGREEM-P, V14, P391, DOI 10.1007/s10784-014-9242-9
   Corbera E, 2010, ENVIRON PLANN A, V42, P1739, DOI 10.1068/a42437
   Dang HH, 2003, CLIM POLICY, V3, pS81, DOI 10.1016/j.clipol.2003.10.006
   Delisle S., 2016, ASIA PAC VIEWPO
   Dilley M, 2005, DISAST RISK MANAGE, P1
   Dung Le NgOc, 2016, 205 CIFOR
   Dung N.V, 2015, COMMUNICATION
   Fankhauser S, 2011, CLIM DEV, V3, P94, DOI 10.1080/17565529.2011.582267
   Fischer R, 2016, FOREST POLICY ECON, V66, P47, DOI 10.1016/j.forpol.2015.11.003
   Forsius M, 2013, CURR OPIN ENV SUST, V5, P26, DOI 10.1016/j.cosust.2013.01.001
   Fry I., 2008, REV EUR COMMUNITY IN, V17, P166, DOI [10.1111/j.1467-9388.2008.00597.x, DOI 10.1111/J.1467-9388.2008.00597.X]
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Fujisaki T, 2016, FORESTS, V7, DOI 10.3390/f7090195
   Garschagen M, 2013, NAT HAZARDS, V67, P25, DOI 10.1007/s11069-011-9753-4
   Gupta J., 2013, Climate Change, Forests and REDD: Lessons for Institutional Design
   Hoa N.T., 2012, MITIG ADAPT STRAT GL, V19, P15
   Huynh PTA, 2014, CLIM DEV, V6, P226, DOI 10.1080/17565529.2014.886989
   Ingalls ML, 2016, CLIMATIC CHANGE, V136, P353, DOI 10.1007/s10584-016-1612-6
   Innes JL, 2006, INT FOREST REV, V8, P406, DOI 10.1505/ifor.8.4.406
   Institute for Strategy and Planning on Natural Resources and Environment, 2013, MAINSTR EC BAS AD VI
   Jagger P, 2010, 56 CIFOR
   Kalame FB, 2009, MITIG ADAPT STRAT GL, V14, P135, DOI 10.1007/s11027-008-9155-4
   Kashwan P, 2015, GLOBAL ENVIRON POLIT, V15, P95, DOI 10.1162/GLEP_a_00313
   Kengoum F., 2015, 135 CIFOR
   Kongsager Rico, 2016, Environ Manage, V57, P271, DOI 10.1007/s00267-015-0605-y
   Kongsager R, 2015, WORLD DEV, V76, P132, DOI 10.1016/j.worlddev.2015.07.003
   Korhonen-Kurki K, 2016, CLIM DEV, V8, P458, DOI 10.1080/17565529.2015.1050979
   Leach M, 1999, WORLD DEV, V27, P225, DOI 10.1016/S0305-750X(98)00141-7
   Locatelli B, 2011, FORESTS, V2, P431, DOI 10.3390/f2010431
   Locatelli T, 2014, AMBIO, V43, P981, DOI 10.1007/s13280-014-0530-y
   Matocha J., 2012, Agroforestry-the Future of Global Land use, P105
   Mbatu RS, 2016, FOREST POLICY ECON, V73, P140, DOI 10.1016/j.forpol.2016.09.010
   McElwee P.D., 2015, REV 3 YEARS POLICY P
   McElwee Pamela., 2010, Social Dimensions of Adaptation to Climate Change in Vietnam
   Mcelwee PD, 2008, ENVIRON CONSERV, V35, P147, DOI 10.1017/S0376892908004736
   Minang PA, 2014, CLIM POLICY, V14, P685, DOI 10.1080/14693062.2014.905822
   Ministry of Agriculture and Natural Resources and Japanese International Cooperation Agency, 2014, PRAP PREP HDB
   Ministry of Agriculture and Rural Development, 2009, ACT PLAN FRAM AD MIT
   Munang R, 2013, CURR OPIN ENV SUST, V5, P67, DOI 10.1016/j.cosust.2012.12.001
   Munang R, 2013, CURR OPIN ENV SUST, V5, P47, DOI 10.1016/j.cosust.2013.02.002
   Murdiyarso D, 2012, CURR OPIN ENV SUST, V4, P678, DOI 10.1016/j.cosust.2012.10.014
   Nguyen H. V, 2014, EMBEDDING FOREST CAR
   Nkem J, 2010, ENVIRON SCI POLICY, V13, P498, DOI 10.1016/j.envsci.2010.06.004
   Olander LP, 2012, CURR OPIN ENV SUST, V4, P661, DOI 10.1016/j.cosust.2012.07.003
   Osborne T, 2015, GEOFORUM, V67, P64, DOI 10.1016/j.geoforum.2015.10.007
   Pham T.T, 2011, REDD POLITICS MEDIA, P1
   Pham T. T., 2016, 155 CIFOR
   Thuy PT, 2014, FORESTS, V5, P2016, DOI 10.3390/f5082016
   Pham TT, 2014, ECOL SOC, V19, DOI 10.5751/ES-06389-190222
   Pistorius T, 2012, CURR OPIN ENV SUST, V4, P638, DOI 10.1016/j.cosust.2012.07.002
   Poudyal M, 2016, GLOBAL ENVIRON CHANG, V37, P31, DOI 10.1016/j.gloenvcha.2016.01.004
   Pramova E., 2015, INTEGRATING ADAPTATI
   Pramova E., 2013, INTEGRATING ADAPTATI
   Pramova E, 2012, WIRES CLIM CHANGE, V3, P581, DOI 10.1002/wcc.195
   Ravindranath N. H., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P843, DOI 10.1007/s11027-007-9102-9
   Red Cross, 2012, MANGR PLANT VIET NAM
   Ribot JC, 2003, RURAL SOCIOL, V68, P153, DOI 10.1111/j.1549-0831.2003.tb00133.x
   Robledo C., 2005, Tropical forests and adaptation to climate change: search of synergies
   Schmitt K., 2015, PROTECTION SUSTAINAB
   Schoene DHF, 2012, FOREST POLICY ECON, V24, P12, DOI 10.1016/j.forpol.2011.04.007
   Sikor T., 2013, The justices and injustices of ecosystem services, P15
   Socialist Republic of Vietnam, 2016, VIETN SUBM REF LEV R
   Socialist Republic of Vietnam, 2011, NAT STRAT CLIM CHANG
   Socialist Republic of Vietnam, 2012, NAT REDD ACT PLAN VI, P1
   Somorin OA, 2016, ENVIRON PLANN C, V34, P415, DOI 10.1177/0263774X16645341
   Somorin OA, 2012, GLOBAL ENVIRON CHANG, V22, P288, DOI 10.1016/j.gloenvcha.2011.08.001
   Stromberg PM, 2011, ENVIRON SCI POLICY, V14, P1079, DOI 10.1016/j.envsci.2011.06.004
   Takacs David., 2009, Hastings West-Northwest Journal of Environmental Law Policy, V15, P39
   Thornbush M, 2013, SUSTAIN CITIES SOC, V9, P1, DOI 10.1016/j.scs.2013.01.003
   Pham TT, 2014, HUM ECOL, V42, P885, DOI 10.1007/s10745-014-9703-3
   Tran T., 2015, VIETNAM SPECIAL REPO, P1
   Nam VN, 2016, WETL ECOL MANAG, V24, P231, DOI 10.1007/s11273-015-9479-2
   Vignola R, 2009, MITIG ADAPT STRAT GL, V14, P691, DOI 10.1007/s11027-009-9193-6
   Wang G., 2015, J GEOGR RES, V63, P1
   Wang GY, 2016, J FORESTRY RES, V27, P469, DOI 10.1007/s11676-016-0218-1
   West S., 2012, REDD+ and Adaptation in Nepal
   [No title captured]
NR 93
TC 25
Z9 25
U1 4
U2 28
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1999-4907
J9 FORESTS
JI Forests
PD JAN
PY 2017
VL 8
IS 1
AR 11
DI 10.3390/f8010011
PG 24
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Forestry
GA EM7QI
UT WOS:000395506900010
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Marcus, H
AF Marcus, Hannah
TI Engaging the health sector in climate-resilient WASH development
SO JOURNAL OF WATER AND HEALTH
LA English
DT Article
AB The impact of climate change on water, sanitation, and hygiene (WASH) has driven an increased focus on climate-resilient WASH development. Evidence suggests that adaptation in the WASH sector is underway, but the progress is limited in certain domains and the participation of the public health community may be lacking. Using the Lake Victoria Basin (LVB) as a climate vulnerability setting for this analysis, this study aimed to identify factors that impede full engagement of the health sector in climate-resilient WASH development. In-depth semi-structured interviews were conducted with 13 WASH sector stakeholders across lakeside urban centers in Kenya, Uganda, and Tanzania. Several barriers to health sector engagement were identified including factors related to donor-driven financing and priority setting, a relative neglect of climate vulnerabilities associated with sanitation and hygiene, ministerial siloes, and broader systems of adaptation governance which compromise health sector leadership in climate adaptation. These results suggest room for expansion of interdisciplinary collaborations and deepened involvement of the health sector in WASH-related climate adaptation, which starts with addressing these and other barriers to full health sector engagement.
C1 [Marcus, Hannah] World Federat Publ Hlth Assoc, Thornhill, ON L4J 5J6, Canada.
RP Marcus, H (corresponding author), World Federat Publ Hlth Assoc, Thornhill, ON L4J 5J6, Canada.
EM hannahmarcus6@hotmail.com
CR Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Chia EL, 2016, FORESTS, V7, DOI 10.3390/f7010024
   Duus-Otterström G, 2016, INT ENVIRON AGREEM-P, V16, P655, DOI 10.1007/s10784-015-9288-3
   Fox M, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16183232
   German Agency for International Cooperation, 2018, FIN OPT INSTR EC BAS
   Global Water Partnership and UNICEF, 2017, WASH CLIM RES DEV ST
   Gordon Tallulah, 2021, Waterlines, V40, P107, DOI 10.3362/1756-3488.20-00012
   Howard G., 2010, Vision 2030: The resilience of water supply and sanitation in
   Jun J., 2021, SIWI COP26
   Kohlitz J., 2021, RURAL SANITATION CLI
   Kohlitz JP, 2017, J WATER SANIT HYG DE, V7, P181, DOI 10.2166/washdev.2017.134
   Nhamo G, 2019, JAMBA-J DISASTER RIS, V11, DOI 10.4102/jamba.v11i1.644
   Pardoe J, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01693-8
   Rahman MS, 2020, CLIMATE, V8, DOI 10.3390/cli8100118
   UN Water, 2019, CLIMATE CHANGE WATER
   UNICEF, WATER SANITATION HYG
NR 16
TC 0
Z9 0
U1 0
U2 2
PU IWA PUBLISHING
PI LONDON
PA REPUBLIC-EXPORT BLDG, UNITS 1 04 & 1 05, 1 CLOVE CRESCENT, LONDON,
   ENGLAND
SN 1477-8920
EI 1996-7829
J9 J WATER HEALTH
JI J. Water Health
PD JUL
PY 2023
VL 21
IS 7
BP 851
EP 855
DI 10.2166/wh.2023.207
EA JUL 2023
PG 5
WC Environmental Sciences; Public, Environmental & Occupational Health;
   Microbiology; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health; Microbiology; Water Resources
GA N1GL8
UT WOS:001024429900001
PM 37515557
OA gold
DA 2025-01-10
ER

PT J
AU Wu, CL
   Herrington, SJ
   Charry, B
   Chu, ML
   Knouft, JH
AF Wu, Chin-Lung
   Herrington, Steven J.
   Charry, Barbara
   Chu, Maria L.
   Knouft, Jason H.
TI Assessing the potential of riparian reforestation to facilitate
   watershed climate adaptation
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Best management practice; Climate change; Critical source area; Riparian
   buffer; Sediment; Freshwater ecosystems
ID MANAGEMENT-PRACTICES; SOIL-EROSION; SEDIMENT; QUALITY; IMPACTS;
   IMPLEMENTATION; CALIBRATION; MITIGATION; HYDROLOGY; POLLUTION
AB Transformations of forested areas to agricultural and urban uses are known to degrade freshwater ecosystems, in part, because of increased surface runoff and soil erosion. Changes in climate are expected to exacerbate these impacts, particularly through increases and intensification of precipitation events during various times of the year. While decreases in greenhouse gas emissions are ultimately necessary to minimize changes in climate, best management practices (BMPs), such as reforestation, can serve as watershed climate adaptation strategies to mitigate the impacts of changes in air temperature and precipitation. The Meramec River Basin (MRB) in eastern Missouri is of economic and recreational importance and supports high levels of biodiversity. While much of the MRB is forested, various land transformations are increasing sediment inputs throughout the basin, and these contributions are expected to increase as climate changes. To address the potential of riparian reforestation to serve as a climate adaptation strategy in the MRB, we developed a Soil and Water Assessment Tool model to simulate streamflow and sediment transport throughout the basin. We then used model outputs characterizing spatial variation in sediment yields to identify critical source areas (CSAs) at the subbasin level. The application of a riparian buffer BMP was simulated in each CSA to quantify the effectiveness of this strategy in reducing sediment for contemporary conditions (1990-2009) as well as under three future climate scenarios for two time periods, 2040-2059 (mid-century) and 2080-2099 (late-century). For the contemporary period, the simulated addition of a riparian buffer BMP resulted in a projected 12.1% average reduction in surface sediment yield among CSAs. For the mid-century projection, subbasin surface sediment output is projected to increase by an average of 277.5% and 221.8% for the climate change scenario and the climate change + BMP scenario, respectively. In the late-century, respective increases in sediment for CSAs are estimated to be, on average, 690.7% and 528.3% for the climate change scenario and the climate change + BMP scenario. Results suggest that surface sediment yields will increase with climate change even with riparian buffer BMP applications. While adding a riparian buffer can potentially reduce sediment outputs, the reduction, on average, is likely inadequate to fully offset the impacts from changes in climate.
C1 [Wu, Chin-Lung; Knouft, Jason H.] St Louis Univ, Dept Biol, 3507 Laclede Ave, St Louis, MO 63103 USA.
   [Herrington, Steven J.; Charry, Barbara] Nature Conservancy, POB 440400, St Louis, MO 63144 USA.
   [Chu, Maria L.] Univ Illinois, Dept Agr & Biol Engn, 1304 W Penn Ave, Urbana, IL 61801 USA.
C3 Saint Louis University; University of Illinois System; University of
   Illinois Urbana-Champaign
RP Wu, CL (corresponding author), St Louis Univ, Dept Biol, 3507 Laclede Ave, St Louis, MO 63103 USA.
EM chinlung.wu@stu.edu
RI WU, CHIN-LUNG/J-2659-2019
OI WU, CHIN-LUNG/0000-0003-2222-3398
FU Nature Conservancy grant [06171601]
FX This project was funded by The Nature Conservancy grant (06171601).
CR Abbaspour KC, 2007, J HYDROL, V333, P413, DOI 10.1016/j.jhydrol.2006.09.014
   Abbaspour KC, 2004, VADOSE ZONE J, V3, P1340
   Ahmadi M, 2013, WATER RESOUR RES, V49, P8344, DOI 10.1002/2013WR013656
   Arabi M, 2006, J AM WATER RESOUR AS, V42, P513, DOI 10.1111/j.1752-1688.2006.tb03854.x
   Arnell NW, 2013, J HYDROL, V486, P351, DOI 10.1016/j.jhydrol.2013.02.010
   Arnold JG, 2012, T ASABE, V55, P1491
   Arnold JG, 2010, T ASABE, V53, P1433
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   BEVEN K, 1992, HYDROL PROCESS, V6, P279, DOI 10.1002/hyp.3360060305
   Brown D.G., 2014, Climate Change Impacts in the United States: The Third National Climate Assessment, P318, DOI [10.7930/J05Q4T1Q, DOI 10.7930/J05Q4T1Q]
   Cerco CF, 2016, J ENVIRON QUAL, V45, P882, DOI 10.2134/jeq2015.05.0230
   Chapman JM, 2014, WATER RES, V56, P190, DOI 10.1016/j.watres.2014.02.047
   Chaubey I, 2010, J SOIL WATER CONSERV, V65, P424, DOI 10.2489/jswc.65.6.424
   Cooper SD, 2013, HYDROBIOLOGIA, V719, P383, DOI 10.1007/s10750-012-1333-4
   Cousino LK, 2015, J HYDROL-REG STUD, V4, P762, DOI 10.1016/j.ejrh.2015.06.017
   Giri S, 2014, HYDROL PROCESS, V28, P431, DOI 10.1002/hyp.9577
   Giri S, 2012, J ENVIRON MANAGE, V103, P24, DOI 10.1016/j.jenvman.2012.02.033
   Gitau MW, 2006, J AM WATER RESOUR AS, V42, P1565, DOI 10.1111/j.1752-1688.2006.tb06021.x
   Gökbulak F, 2008, EUR J FOREST RES, V127, P203, DOI 10.1007/s10342-007-0195-1
   Guzman JA, 2013, ENVIRON MODELL SOFTW, V48, P163, DOI 10.1016/j.envsoft.2013.06.014
   Harris JA, 2006, RESTOR ECOL, V14, P170, DOI 10.1111/j.1526-100X.2006.00136.x
   Hawley RJ, 2019, GEOMORPHOLOGY, V343, P81, DOI 10.1016/j.geomorph.2019.06.021
   Jayakody P., 2014, HYDROL, DOI [10.1002/hyp.10088, DOI 10.1002/HYP.10088]
   Knouft JH, 2017, ANNU REV ECOL EVOL S, V48, P111, DOI 10.1146/annurev-ecolsys-110316-022803
   Knouft JH, 2015, ECOHYDROLOGY, V8, P273, DOI 10.1002/eco.1506
   Krause KP, 2019, FRESHWATER BIOL, V64, P632, DOI 10.1111/fwb.13248
   Krzeminska D, 2019, CATENA, V172, P87, DOI 10.1016/j.catena.2018.08.014
   Liu YZ, 2017, SCI TOTAL ENVIRON, V601, P580, DOI 10.1016/j.scitotenv.2017.05.212
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Neitsch S.L., 2011, 406 TEX A M U USDAAR
   Niu SQ, 2017, ECOHYDROLOGY, V10, DOI 10.1002/eco.1770
   Parajuli PB, 2008, AGR WATER MANAGE, V95, P1189, DOI 10.1016/j.agwat.2008.05.006
   Paul MJ, 2001, ANNU REV ECOL SYST, V32, P333, DOI 10.1146/annurev.ecolsys.32.081501.114040
   Pruski FF, 2002, WATER RESOUR RES, V38, DOI 10.1029/2001WR000493
   Rickson RJ, 2014, SCI TOTAL ENVIRON, V468, P1187, DOI 10.1016/j.scitotenv.2013.05.057
   Sharpley A, 2013, J ENVIRON QUAL, V42, P1308, DOI 10.2134/jeq2013.03.0098
   Stott T, 2001, J ENVIRON MANAGE, V63, P3, DOI 10.1006/jema.2001.0459
   Sunde MG, 2018, J ENVIRON MANAGE, V220, P149, DOI 10.1016/j.jenvman.2018.05.025
   Sweeney BW, 2014, J AM WATER RESOUR AS, V50, P560, DOI 10.1111/jawr.12203
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Teshager AD, 2016, HYDROL EARTH SYST SC, V20, P3325, DOI 10.5194/hess-20-3325-2016
   Teshager AD, 2017, SCI TOTAL ENVIRON, V607, P1188, DOI 10.1016/j.scitotenv.2017.07.048
   Wagena MB, 2018, SCI TOTAL ENVIRON, V635, P132, DOI 10.1016/j.scitotenv.2018.04.110
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Zhang Q, 2016, SCI TOTAL ENVIRON, V563, P1016, DOI 10.1016/j.scitotenv.2016.03.104
   Zhang XC, 2007, CLIMATIC CHANGE, V84, P337, DOI 10.1007/s10584-007-9256-1
   Zhang Y, 2012, J SOIL WATER CONSERV, V67, P390, DOI 10.2489/jswc.67.5.390
NR 48
TC 11
Z9 12
U1 0
U2 35
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD JAN 1
PY 2021
VL 277
AR 111431
DI 10.1016/j.jenvman.2020.111431
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA OY0WA
UT WOS:000593974000009
PM 33032001
DA 2025-01-10
ER

PT J
AU Peng, LZL
   Stewart, MG
AF Peng, Lizhengli
   Stewart, Mark G.
TI Spatial time-dependent reliability analysis of corrosion damage to RC
   structures with climate change
SO MAGAZINE OF CONCRETE RESEARCH
LA English
DT Article
ID REINFORCED-CONCRETE STRUCTURES; COVER CRACKING; CARBONATION; MODELS;
   PREDICTION; MAINTENANCE; BEAMS; INFRASTRUCTURE; PROPAGATION; VARIABILITY
AB The environment around concrete structures may be influenced by a changing climate, especially in the long run, leading to an acceleration of deterioration. Therefore, the safety, serviceability and durability of concrete infrastructure may decline at a faster rate than expected. Carbonation-induced deterioration to concrete structures constructed in Sydney, Australia and Kunming, China under a changing climate is investigated in this paper. Two emissions scenarios are considered - RCP 8.5 and RCP 4.5, representing high and medium greenhouse gas emissions scenarios respectively. The spatial time-dependent reliability analysis includes time-dependent climate scenarios and deterioration processes, as well as a large number of random variables and spatial random fields of material properties and dimensions. The surface of concrete structures is discretised into a large number of elements and the likelihood and extent of corrosion damage is calculated by tracking the evolution of the corrosion process of each element using Monte Carlo simulations. The results show that a changing climate could cause the extent of damage to increase by up to 6% for reinforced concrete infrastructure in Kunming. The findings may be used to assess climate adaptation measures in the design stage, as well as a cost-benefit analysis of climate adaptation measures.
C1 [Peng, Lizhengli; Stewart, Mark G.] Univ Newcastle, Ctr Infrastruct Performance & Reliabil, Callaghan, NSW 2308, Australia.
C3 University of Newcastle
RP Peng, LZL (corresponding author), Univ Newcastle, Ctr Infrastruct Performance & Reliabil, Callaghan, NSW 2308, Australia.
RI Stewart, Mark/G-7415-2013
OI Stewart, Mark/0000-0001-6887-6533
CR Al-Harthy AS, 2011, MAG CONCRETE RES, V63, P655, DOI 10.1680/macr.2011.63.9.655
   [Anonymous], 2000, STAT QUANT VAR LIM S
   [Anonymous], 2006, BULLETIN
   [Anonymous], 1983, Random fields: analysis & synthesis
   [Anonymous], 2014, CLIMATE CHANGE 2014, V80, P1
   [Anonymous], 2007, 4 ASSESSMENT REPORT, DOI DOI 10.1038/446727A
   BREYSSE D, 2013, PROCEEDINGS OF SAFET
   Chernin L, 2012, MAG CONCRETE RES, V64, P95, DOI 10.1680/macr.10.00108
   Darmawan MS, 2007, STRUCT SAF, V29, P16, DOI 10.1016/j.strusafe.2005.11.002
   de Larrard F., 1999, Concrete mixture proportioning: A scientific approach
   Der Kiureghian A, 1988, Probabilistic Eng Mech, V3, P83, DOI DOI 10.1016/0266-8920(88)90019-7
   *DURACRETE, 1998, MOD DEGR DURCRETE PR
   El Maaddawy T, 2007, CEMENT CONCRETE COMP, V29, P168, DOI 10.1016/j.cemconcomp.2006.11.004
   Fang CQ, 2011, MAG CONCRETE RES, V63, P941, DOI 10.1680/macr.10.00165
   FOSTER S, 2013, P CONCRETE 2013
   GONZALEZ JA, 1980, BRIT CORROS J, V15, P135, DOI 10.1179/000705980798275535
   Inman M, 2011, NAT CLIM CHANGE, V1, P7, DOI 10.1038/nclimate1058
   Kada-Benameur H, 2000, CEMENT CONCRETE RES, V30, P301, DOI 10.1016/S0008-8846(99)00250-1
   Li Y., 2004, Journal of Structural Concrete, V5, P121, DOI DOI 10.1680/STCO.2004.5.3.121
   Malumbela G, 2011, MAG CONCRETE RES, V63, P797, DOI 10.1680/macr.2011.63.11.797
   MCGEE R, 1999, ICASP8 APPL STAT PRO
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Melchers RE, 2006, MAG CONCRETE RES, V58, P575, DOI 10.1680/macr.2006.58.9.575
   MIRZA SA, 1979, J STRUCT DIV-ASCE, V105, P1021
   *MOCPRC, 2002, COD DES CONCR STRUCT
   *MOCPRC, 2010, 500102010 MOCPRC
   Mullard JA, 2009, J STRUCT ENG, V135, P887, DOI 10.1061/(ASCE)0733-9445(2009)135:8(887)
   Mullard JA, 2012, J BRIDGE ENG, V17, P353, DOI 10.1061/(ASCE)BE.1943-5592.0000248
   Mullard JA, 2011, ACI STRUCT J, V108, P71
   Na UJ, 2012, KSCE J CIV ENG, V16, P133, DOI 10.1007/s12205-012-1248-7
   NEVILLE A, 1995, MATER STRUCT, V28, P63, DOI 10.1007/BF02473172
   O'Connor AJ, 2013, J BRIDGE ENG, V18, P3, DOI 10.1061/(ASCE)BE.1943-5592.0000370
   Papakonstantinou KG, 2013, ENG STRUCT, V57, P306, DOI 10.1016/j.engstruct.2013.06.038
   Peng L, 2014, ANAL LETT, V47, P2341, DOI 10.1080/00032719.2014.905952
   Peters GP, 2013, NAT CLIM CHANGE, V3, P4, DOI 10.1038/nclimate1783
   Raupach M, 2006, MATER CORROS, V57, P605, DOI 10.1002/maco.200603991
   Reale T, 2012, CONSTR BUILD MATER, V36, P475, DOI 10.1016/j.conbuildmat.2012.06.033
   *RGRRCSM, 1985, J BUILDING STRUCTURE, V6, P2
   Richardson M., 1988, CARBONATION REINFORC
   Rogelj J, 2012, NAT CLIM CHANGE, V2, P248, DOI [10.1038/NCLIMATE1385, 10.1038/nclimate1385]
   Roy SK, 1996, MAG CONCRETE RES, V48, P293, DOI 10.1680/macr.1996.48.177.293
   Russell D, 2001, P I CIVIL ENG-STR B, V146, P319
   SHI Y, 2014, STRUCTURAL IN PRESS
   *STAND AUSTR, 2004, 51005 AS 5
   Standards Australia, 2009, AS 3600-2009 Concrete Structures
   Sterritt G, 2001, SAFETY RISK IN ENG, V32, P3279
   Stewart MG, 2006, STRUCT INFRASTRUCT E, V2, P79, DOI 10.1080/15732470500253230
   Stewart M.G., 2010, Int. J. Eng. Under Uncertainty, V2, P35
   Stewart MG, 2007, ENG STRUCT, V29, P1457, DOI 10.1016/j.engstruct.2006.09.004
   Stewart MG, 2012, STRUCT SAF, V35, P29, DOI 10.1016/j.strusafe.2011.10.002
   Stewart MG, 2011, ENG STRUCT, V33, P1326, DOI 10.1016/j.engstruct.2011.01.010
   Stewart MG, 1996, J STRUCT ENG, V122, P794, DOI 10.1061/(ASCE)0733-9445(1996)122:7(794)
   Sudret B, 2008, RELIAB ENG SYST SAFE, V93, P410, DOI 10.1016/j.ress.2006.12.019
   Talukdar S, 2012, CEMENT CONCRETE COMP, V34, P924, DOI 10.1016/j.cemconcomp.2012.04.011
   Vu KAT, 2000, STRUCT SAF, V22, P313, DOI 10.1016/S0167-4730(00)00018-7
   Vu KAT, 2005, J STRUCT ENG, V131, P1681, DOI 10.1061/(ASCE)0733-9445(2005)131:11(1681)
   WANG J, 2007, ENG MECH, V24, P94
   Wisniewski DF, 2012, STRUCT INFRASTRUCT E, V8, P111, DOI 10.1080/15732470903363164
   Worrell E, 2001, ANNU REV ENERG ENV, V26, P303, DOI 10.1146/annurev.energy.26.1.303
   Yoon IS, 2007, ATMOS ENVIRON, V41, P7274, DOI 10.1016/j.atmosenv.2007.05.028
   Zhu WZ, 2001, CEMENT CONCRETE COMP, V23, P57, DOI 10.1016/S0958-9465(00)00053-6
NR 61
TC 34
Z9 34
U1 1
U2 31
PU ICE PUBLISHING
PI WESTMINISTER
PA INST CIVIL ENGINEERS, 1 GREAT GEORGE ST, WESTMINISTER SW 1P 3AA, ENGLAND
SN 0024-9831
EI 1751-763X
J9 MAG CONCRETE RES
JI Mag. Concr. Res.
PY 2014
VL 66
IS 22
BP 1154
EP 1169
DI 10.1680/macr.14.00098
PG 16
WC Construction & Building Technology; Materials Science, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Materials Science
GA AU8NT
UT WOS:000345853900003
OA Green Published
DA 2025-01-10
ER

PT J
AU Huynh, PTA
   Resurreccion, BP
AF Huynh, Phuong T. A.
   Resurreccion, Bernadette P.
TI Women's differentiated vulnerability and adaptations to climate-related
   agricultural water scarcity in rural Central Vietnam
SO CLIMATE AND DEVELOPMENT
LA English
DT Article
DE social differentiation; agricultural water scarcity; differentiated
   vulnerability; adaptation
ID GENDER
AB This field-based study applies a mixed methods approach that combines both qualitative and quantitative analyses to investigate the differences in women's vulnerability and adaptations to climate-related agricultural water scarcity in Ky Nam commune, Central Vietnam. The study highlights the heterogeneity of women as a group and their intersectional dynamics as they adapt to increasing agricultural water scarcity on their rural livelihoods. The findings show that social differences including gender, class, household headship, age and stage of life shape women's differentiated experiences in vulnerability in access to water, to forestland and credit; in turn mark their adaptation differentiation to climate-related agricultural water scarcity. It also stresses that existing development policies can cause inequality in resource access in practice, running the risk of further marginalizing certain groups of women, especially female heads of household. Meanwhile, the current National Target Program to Respond to Climate Change of Vietnam is blind to issues of women's differentiated vulnerability and adaptive capacity. This study suggests that if these current development and adaptation measures do not pay proper attention to differentiated gender experience, it is likely to exacerbate the vulnerabilities of those affected, particularly female heads of household, rather than help them. In addition, these development and climate programmes have to be redesigned to accommodate more context-specific policies instead of one-size-fits-all packages that will effectively address women's (and men's) differential needs and unequal relations and circumstances.
C1 [Huynh, Phuong T. A.; Resurreccion, Bernadette P.] Asian Inst Technol, Sch Environm Resources & Dev, Klongluang 12120, Pathumthani, Thailand.
C3 Asian Institute of Technology
RP Huynh, PTA (corresponding author), Asian Inst Technol, Sch Environm Resources & Dev, POB 4, Klongluang 12120, Pathumthani, Thailand.
EM huynh.thi.anh.phuong@ait.ac.th
CR Acharya K., 2009, IPS NEWS
   Adger W. N., 1999, MITIG ADAPT STRAT GL, V4, P253
   Adger WN, 1999, WORLD DEV, V27, P249, DOI 10.1016/S0305-750X(98)00136-3
   Ahmed S., 2009, Gender and Development, V17, P33, DOI 10.1080/13552070802696896
   [Anonymous], 2009, JOURNAL OF FOREST AN, DOI DOI 10.1088/1755-1307/6/7/572015
   [Anonymous], 2007, CLIMATE CHANGE 2007
   Arora-Jonsson S, 2011, GLOBAL ENVIRON CHANG, V21, P744, DOI 10.1016/j.gloenvcha.2011.01.005
   Beckman M, 2011, CLIM DEV, V3, P32, DOI 10.3763/cdev.2010.0065
   Campell B., 2009, RESPONDING CLIMATE C
   Chant S, 2004, IDS BULL-I DEV STUD, V35, P19, DOI 10.1111/j.1759-5436.2004.tb00151.x
   Corral Thais, 2010, GENDER CLIMATE CHANG, P138
   Crenshaw Kimberle., 1989, University of Chicago Legal Forum, V1989
   Dankelman I., 2010, Gender and Climate Change: An Introduction, P1
   Dankelman I.E. M., 2008, Gender, climate change and human security: Lessons from Bangladesh, Ghana and Senegal
   Djoudi H, 2011, INT FOREST REV, V13, P123, DOI 10.1505/146554811797406606
   Enarson E., 2001, ENVIRON HAZARDS-UK, V3, P133, DOI [DOI 10.1016/S1464-2867(02)00006-2, DOI 10.3763/EHAZ.2001.0314]
   Glazebrook T, 2011, HYPATIA, V26, P762, DOI 10.1111/j.1527-2001.2011.01212.x
   Hyndman J., 2010, GENDER TECHNOLOGY DE, V12, P101
   IPONRE, 2009, HA TINH ASSESSMENT R
   Kelkar U, 2008, GLOBAL ENVIRON CHANG, V18, P564, DOI 10.1016/j.gloenvcha.2008.09.003
   Marino E, 2012, GLOBAL ENVIRON CHANG, V22, P323, DOI 10.1016/j.gloenvcha.2012.03.001
   McCall L, 2005, SIGNS, V30, P1771, DOI 10.1086/426800
   MoNRE, 2011, SCENARIOS FOR CLIMAT
   MoNRE, 2008, NATIONAL TARGET PROG
   Moser SC, 2008, CLIMATIC CHANGE, V87, pS309, DOI 10.1007/s10584-007-9384-7
   Nelson V., 2002, Gender and Development, V10, P51, DOI 10.1080/13552070215911
   Northern Central Meteorological Station, 2011, METEOROLOGICAL DATAB
   Odigie-Emmanuel O., 2010, GENDER AND CLIMATE C, P247
   Ray-Bennett NS, 2009, ENVIRON HAZARDS-UK, V8, P5, DOI 10.3763/ehaz.2009.0001
   Resurreccion B. P., 2012, HUMAN SECURITY AND C, P95
   Rodenberg B., 2009, DISCUSSION PAPER
   Ruysschaert G., 2007, OCCASIONAL PAPER
   Speranza I. C., 2010, GLOBAL CHANGE AND SU, V5, P107
   WEDO, 2008, THIS REPORT IS PREPA
   White Benjamin., 1989, AGRARIAN TRANSFORMAT, P15
   World Bank, 2010, DISCUSSION PAPER NO
   Young G, 2010, CLIMATIC CHANGE, V98, P245, DOI 10.1007/s10584-009-9665-4
NR 37
TC 47
Z9 50
U1 2
U2 53
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1756-5529
EI 1756-5537
J9 CLIM DEV
JI Clim. Dev.
PY 2014
VL 6
IS 3
BP 226
EP 237
DI 10.1080/17565529.2014.886989
PG 12
WC Development Studies; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Development Studies; Environmental Sciences & Ecology
GA AN1UD
UT WOS:000340368200003
DA 2025-01-10
ER

PT J
AU Taillandier, C
   Cörvers, R
   Stringer, LC
AF Taillandier, Chloe
   Corvers, Ron
   Stringer, Lindsay C.
TI Growing resilient futures: agroforestry as a pathway towards climate
   resilient development for smallholder farmers
SO FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
LA English
DT Article
DE sustainable agriculture; rural livelihoods; climate adaptation; climate
   mitigation; project development
ID FOOD; AGRICULTURE
AB Climate change is increasing pressure on communities that are already experiencing high levels of vulnerability and poverty, threatening their subsistence. Among the most vulnerable are smallholder farmers in the Global South, who rely on their yields for food and income. Smallholders need to adapt to changes in rainfall, temperature, and weather patterns and their knock-on effects, and at the same time, ensure that their on-farm climate adaptations do not make climate change worse by increasing greenhouse gas emissions. The Intergovernmental Panel on Climate Change (IPCC) emphasises the need for Climate Resilient Development Pathways (CRDPs) to support vulnerable communities, including smallholder farmers, in balancing climate adaptation, mitigation and development. CRDPs comprise reactive and/or preventive actions that key stakeholders (e.g., government, business, civil society and individuals, including smallholder farmers) can take to become more resilient in the context of a changing climate while not compromising their development or increasing emissions. The CRDP framework has so far remained conceptual, providing little information on how to actually create these pathways in practice. This paper addresses this gap, and with a focus on agroforestry projects and smallholders in the Global South, assesses how CRDPs can become more concrete and actionable through a focus on agroforestry: the voluntary combination of crop and/or pasture with trees and/or shrubs, considering its contribution to climate adaptation, mitigation and development. We draw on literature review and focus group data, analysed using Atlas.ti 23 and a coding process to present a tool relevant to project designers, policymakers and researchers to assess agroforestry projects according to different aspects of climate resilient development, with particular focus on smallholder farmers in the Global South. Evaluation of the tool found it is relevant and useful for project developers and funders to check that their projects follow the components of CRD, but the tool needs to be translated to the local context to better address local demands and reflect regional specificities, which focus group participants deemed possible.
C1 [Taillandier, Chloe; Corvers, Ron] Maastricht Univ, Maastricht Sustainabil Inst, Maastricht, Netherlands.
   [Taillandier, Chloe; Stringer, Lindsay C.] Univ York, York Environm Sustainabil Inst, York, England.
   [Stringer, Lindsay C.] Univ York, Dept Environm & Geog, York, England.
C3 Maastricht University; University of York - UK; University of York - UK
RP Taillandier, C (corresponding author), Maastricht Univ, Maastricht Sustainabil Inst, Maastricht, Netherlands.; Taillandier, C (corresponding author), Univ York, York Environm Sustainabil Inst, York, England.
EM chloe.taillandier@ou.nl
RI Taillandier, Chloé/JJE-8793-2023
OI Taillandier, Chloe/0009-0003-1970-7487
FU York-Maastricht Partnership
FX The author(s) declare financial support was received for the research,
   authorship, and/or publication of this article. This research was fully
   funded by the York-Maastricht Partnership
   (https://www.maastrichtuniversity.nl/york-maastricht-partnership).
CR Altieri MA, 2015, AGRON SUSTAIN DEV, V35, P869, DOI 10.1007/s13593-015-0285-2
   [Anonymous], 2019, Agroforestry Strategic Framework: Fiscal Years 2019-2024
   [Anonymous], 2012, SMALLHOLDERS FAMILY
   Baker E, 2023, CURR OPIN ENV SUST, V62, DOI 10.1016/j.cosust.2023.101270
   Birkmann J., 2022, CLIMATE CHANGE 2022
   Bisht IS, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su122410690
   Borelli S., 2019, FAO and ICRAF, V8, P42
   Brown SE, 2018, ENVIRON EVID, V7, DOI 10.1186/s13750-018-0136-0
   Chamberlin J., 2008, IFPRI discussion papers, V23
   Chandra A, 2017, WORLD DEV, V98, P214, DOI 10.1016/j.worlddev.2017.04.028
   Coe R, 2014, CURR OPIN ENV SUST, V6, P73, DOI 10.1016/j.cosust.2013.10.013
   Colbert E., 2019, Biovision
   Cousins B., 2011, REFORMING LAND RESOU, P86
   de Scally D, 2022, CLIM DEV, V14, P360, DOI 10.1080/17565529.2021.1927658
   Duffy C, 2021, AGROFOREST SYST, V95, P1109, DOI 10.1007/s10457-021-00632-8
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   Farm Tree, 2022, Farms. Trees. Crops. Quantified
   Franzel S, 2014, CURR OPIN ENV SUST, V6, P98, DOI 10.1016/j.cosust.2013.11.008
   Garrity DP, 2010, FOOD SECUR, V2, P197, DOI 10.1007/s12571-010-0070-7
   Gold M. A., 2004, New vistas in agroforestry. Advances in agroforestry, V1
   Government of India. Department of Agriculture and Cooperation Ministry of Agriculture new Delhi, 2014, National Agroforestry Policy
   Hadju F., 2019, SLU
   Jose S, 2012, AGROFOREST SYST, V85, P1, DOI 10.1007/s10457-012-9517-5
   Kalanzi F, 2021, SMALL-SCALE FOR, V20, P605, DOI 10.1007/s11842-021-09483-8
   Kansanga MM, 2021, LAND USE POLICY, V108, DOI 10.1016/j.landusepol.2021.105477
   Keur J., 2020, Klimaatcompensatie met agroforestry, wat is mogelijk? - Factsheet agroforestry 3. WUR
   Lasco RD, 2016, AGROFOREST SYST, V90, P521, DOI 10.1007/s10457-015-9874-y
   Lojka B, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12010069
   Mathez-Stiefel SL, 2016, MT RES DEV, V36, P417, DOI 10.1659/MRD-JOURNAL-D-16-00051.1
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P8, DOI 10.1016/j.cosust.2013.09.002
   Meybeck A., 2021, Adaptation to climate change with forests, trees and agroforestry: FTA highlights of a decade 2011-2021
   Miller AW, 2001, AGROFOREST SYST, V53, P247, DOI 10.1023/A:1013327510748
   Nyasimi M, 2017, CLIMATE, V5, DOI 10.3390/cli5030063
   Ollinaho OI, 2021, J RURAL STUD, V82, P210, DOI 10.1016/j.jrurstud.2021.01.016
   Quandt A, 2023, CURR OPIN ENV SUST, V60, DOI 10.1016/j.cosust.2022.101244
   Regmi Bishwa Nath., 2003, INT C RUR LIV FOR BI
   Ricciardi V, 2018, GLOB FOOD SECUR-AGR, V17, P64, DOI 10.1016/j.gfs.2018.05.002
   Salvini G, 2016, ENVIRON SCI POLICY, V63, P113, DOI 10.1016/j.envsci.2016.05.016
   Santos R, 2012, J SUSTAIN AGR, V36, P54, DOI 10.1080/10440046.2011.608468
   Schipper E. L. F., 2022, IPCC WGII sixth assessment report
   Singh R, 2017, ENERGY ECOL ENVIRON, V2, P296, DOI 10.1007/s40974-017-0074-7
   Snyder H, 2019, J BUS RES, V104, P333, DOI 10.1016/j.jbusres.2019.07.039
   SOMARRIBA E, 1992, AGROFOREST SYST, V19, P233, DOI 10.1007/BF00118781
   Stringer L. C., 2022, Science, p1, 311, DOI [10.1007/s44177-022-00027-z, DOI 10.1007/S44177-022-00027-Z]
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Toensmeier E., 2016, CARBON FARMING SOLUT
   Tubiello FN, 2022, EARTH SYST SCI DATA, V14, P1795, DOI 10.5194/essd-14-1795-2022
   UN, 2022, Day of Eight Billion
   van Noordwijk M, 2021, MITIG ADAPT STRAT GL, V26, DOI 10.1007/s11027-021-09954-5
   Verchot L. V., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P901, DOI 10.1007/s11027-007-9105-6
   Waldén P, 2020, AGROFOREST SYST, V94, P15, DOI 10.1007/s10457-019-00355-x
NR 51
TC 2
Z9 2
U1 4
U2 13
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2571-581X
J9 FRONT SUSTAIN FOOD S
JI Front. Sustain. Food Syst.
PD NOV 9
PY 2023
VL 7
AR 1260291
DI 10.3389/fsufs.2023.1260291
PG 15
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA Y4NI4
UT WOS:001105041500001
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Prober, SM
   Hilbert, DW
   Ferrier, S
   Dunlop, M
   Gobbett, D
AF Prober, Suzanne M.
   Hilbert, D. W.
   Ferrier, S.
   Dunlop, M.
   Gobbett, D.
TI Combining community-level spatial modelling and expert knowledge to
   inform climate adaptation in temperate grassy eucalypt woodlands and
   related grasslands
SO BIODIVERSITY AND CONSERVATION
LA English
DT Article
DE Artificial neural networks; Climate change; Community-level modelling;
   Global warming; Generalized dissimilarity modelling; Savannah
ID HERB-RICH WOODLANDS; WHITE BOX WOODLANDS; FIRE FREQUENCY; SPECIES
   DISTRIBUTIONS; CHANGE IMPACTS; BIODIVERSITY; CONSERVATION; RESTORATION;
   AUSTRALIA; FRAMEWORK
AB Many studies predict effects of future climate scenarios on species distributions, but few predict impacts on landscapes or ecological communities, the scales most relevant to conservation management. We combined expert knowledge with community-level spatial modelling (using artificial neural networks, ANN, and generalised dissimilarity modelling, GDM) to inform climate adaptation management in widespread but highly threatened temperate grassy ecosystems (TGE) of Australian agricultural landscapes. GDM predicted high levels of 'biotically-scaled environmental stress' (scaled in terms of potential change in species composition of communities) for plants, reptiles and snails within the TGE under medium, and especially high, 2070 climate scenarios. Predicted stress was lower for birds, mammals and frogs, possibly owing to generally wider species distributions, but these models do not account for changing habitat characteristics. ANN predicted environments within the current TGE biome will become increasingly favourable for formations such as chenopod shrublands, L. forests and Vent. forests by 2070, although classification error for eucalypt woodland in current climates was high. Expert knowledge and GDM suggest these predictions may be mediated by attributes such as environmental heterogeneity that confer resilience, but GDM confirms that widespread degradation has greatly compromised the capacity of TGE to adapt to change. Based on model predictions and expert knowledge we discuss five potential climate change outcomes for TGE: decreasing fire frequency, structural change, altered functional composition, exotic invasion, and cascading changes in ecological interactions. Although significant ecological change in TGE is likely, it is feasible to ameliorate non-climatic limits to adaptation and promote reassembly by native rather than exotic species. Current conservation efforts already target similar goals, and reinforcing and adjusting these approaches offer the highest priority, lowest risk climate adaptation options. We conclude that despite high uncertainties, combining community-level modelling with expert knowledge can guide climate adaptation management.
C1 [Prober, Suzanne M.] CSIRO Ecosyst Sci, Wembley, WA 6913, Australia.
   [Hilbert, D. W.] CSIRO Ecosyst Sci, Atherton, Qld 4883, Australia.
   [Ferrier, S.; Dunlop, M.] CSIRO Ecosyst Sci, Canberra, ACT 2601, Australia.
   [Gobbett, D.] CSIRO Ecosyst Sci, Osmond, SA 5064, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Ecosystem Sciences; Commonwealth Scientific & Industrial Research
   Organisation (CSIRO)
RP Prober, SM (corresponding author), CSIRO Ecosyst Sci, Private Bag 5, Wembley, WA 6913, Australia.
EM suzanne.prober@csiro.au
RI Gobbett, David/F-8910-2010; Hilbert, David/A-3796-2008; Dunlop,
   Michael/D-5361-2011; Ferrier, Simon/C-1490-2009; Prober,
   Suzanne/G-6465-2010
OI Dunlop, Michael/0000-0001-8032-9196; Gobbett, David/0000-0003-3982-3162;
   Prober, Suzanne/0000-0002-6518-239X
FU Department of Environment, Water, Heritage and Arts; CSIRO Climate
   Adaptation Flagship
FX We thank Cameron Fletcher, Tom Harwood, Kristin Williams and Georg Wiehl
   (CSIRO) for modelling and GIS support, Janet Stein (Australian National
   University) for providing environmental data for modelling, and Alan
   House, Adam Liedloff, Anita Smyth, Tara Martin and Helen Murphy (CSIRO)
   for comments and discussion. Financial support was provided by the
   Department of Environment, Water, Heritage and Arts, and the CSIRO
   Climate Adaptation Flagship. We are grateful for the valuable input
   provided by workshop attendees: Greg Baines (Department of Territory and
   Municipal Services, ACT), Justin Billings (Department of Environment,
   Water, Heritage and Arts), Ross Bradstock (University of Wollongong),
   Kerry Bridle (CSIRO/University of Tasmania), Sue Briggs (Department of
   Environment and Climate Change, NSW), Don Butler (Macquarie University,
   Environment Protection Authority, Qld), Oberon Carter (Department of
   Primary Industries, Parks, Water and Environment, Tasmania), Saul
   Cunningham (CSIRO), Liz Dovey (Department of Climate Change), Angela
   Duffy (Department of Environment and Heritage, SA), Louise Gilfedder
   (Department of Primary Industries, Parks, Water and Environment,
   Tasmania), David Keith (Department of Environment and Climate Change,
   NSW), Ian Lunt (Charles Sturt University), Sue McIntyre (CSIRO), Tim
   Milne (Nature Conservation Society, SA), Karel Mokany (CSIRO), Jim
   Radford (Australian Bush Heritage), Rainer Rehwinkel (National Parks and
   Wildlife Service, NSW), Vivienne Turner (Arthur Rylah Institute for
   Environmental Research), Kristen Williams (CSIRO).
CR Allnutt TF, 2008, CONSERV LETT, V1, P173, DOI 10.1111/j.1755-263X.2008.00027.x
   [Anonymous], NATIVE NATURAL PASTU
   BALLING JD, 1982, ENVIRON BEHAV, V14, P5, DOI 10.1177/0013916582141001
   Bond WJ, 2000, GLOBAL CHANGE BIOL, V6, P865, DOI 10.1046/j.1365-2486.2000.00365.x
   Bradstock RA, 2010, GLOBAL ECOL BIOGEOGR, V19, P145, DOI 10.1111/j.1466-8238.2009.00512.x
   Calder JA, 2008, AUST J BOT, V56, P684, DOI 10.1071/BT08105
   Department of the Environment and Water Resources, 2007, AUSTR NAT VEG SUMM A
   Dorrough J, 2008, J APPL ECOL, V45, P1274, DOI 10.1111/j.1365-2664.2008.01501.x
   Dunlop Michael., 2008, Implications of Climate Change for Australia's National Reserve System - A Preliminary Assessment
   Eldridge DJ, 2005, AUSTRAL ECOL, V30, P336, DOI 10.1111/j.1442-9993.2005.01478.x
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   ESRI, 2009, ARCGIS 9 3 ENV SYSTE
   Ferrier S, 2002, BIODIVERS CONSERV, V11, P2309, DOI 10.1023/A:1021374009951
   Ferrier S, 2010, ASSESSING POTENTIAL
   Ferrier S, 2007, DIVERS DISTRIB, V13, P252, DOI 10.1111/j.1472-4642.2007.00341.x
   Ferrier S, 2006, J APPL ECOL, V43, P393, DOI 10.1111/j.1365-2664.2006.01149.x
   Fischlin A, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P211
   Fletcher C, 2010, USING ARTIFICIAL NEU
   Hagerman S, 2010, GLOBAL ENVIRON CHANG, V20, P192, DOI 10.1016/j.gloenvcha.2009.10.005
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hilbert David W., 1999, Diversity and Distributions, V5, P263, DOI 10.1046/j.1472-4642.1999.00060.x
   Hilbert DW, 2001, ECOL MODEL, V146, P311, DOI 10.1016/S0304-3800(01)00323-4
   Hilbert DW, 2001, AUSTRAL ECOL, V26, P590, DOI 10.1046/j.1442-9993.2001.01137.x
   Hobbs R.J., 2000, Temperate Eucalypt Woodlands in Australia. Biology, Conservation
   Hovenden MJ, 2008, GLOBAL CHANGE BIOL, V14, P1018, DOI 10.1111/j.1365-2486.2008.01558.x
   Hovenden MJ, 2007, AUST J BOT, V55, P780, DOI 10.1071/BT07107
   Hovenden MJ, 2010, AUSTRAL ECOL, V35, P665, DOI 10.1111/j.1442-9993.2009.02074.x
   Keith D., 2004, Ocean shores to desert dunes: the native vegetation of NSW and the ACT
   Knox KJE, 2006, OECOLOGIA, V149, P730, DOI 10.1007/s00442-006-0480-6
   Lambert J, 2000, TEMPERATE EUCALYPT WOODLANDS IN AUSTRALIA, P359
   Lentini Pia, 2011, Ecological Management & Restoration, V12, P148, DOI 10.1111/j.1442-8903.2011.00585.x
   Lunt I, 2000, TEMPERATE EUCALYPT WOODLANDS IN AUSTRALIA, P17
   Lunt ID, 2007, AUST J BOT, V55, P401, DOI 10.1071/BT06178
   Lunt ID, 2012, FLAMMABLE AUSTRALIA: FIRE REGIMES, BIODIVERSITY AND ECOSYSTEMS IN A CHANGING WORLD, P253
   Lunt ID, 1997, PLANT ECOL, V130, P21, DOI 10.1023/A:1009780301775
   LUNT ID, 1990, AUST J ECOL, V15, P155, DOI 10.1111/j.1442-9993.1990.tb01524.x
   Martin Greg, 2003, Ecological Management & Restoration, V4, P114, DOI 10.1046/j.1442-8903.2003.00145.x
   Martin TG, 2010, BUFFEL GRASS CLIMATE
   McIntyre S, 2007, AGR ECOSYST ENVIRON, V119, P11, DOI 10.1016/j.agee.2006.06.013
   McIntyre S., 2002, Managing and Conserving Grassy Woodlands
   McIntyre S, 2011, BIOL CONSERV, V144, P1781, DOI 10.1016/j.biocon.2011.03.023
   Morgan JW, 1998, J VEG SCI, V9, P181, DOI 10.2307/3237117
   Morgan JW, 2001, J ECOL, V89, P908, DOI 10.1111/j.1365-2745.2001.00617.x
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Pearce K., 2007, Climate Change in Australia: technical report 2007
   Peppler-Lisbach C, 2004, J VEG SCI, V15, P623
   Poorter H, 2003, NEW PHYTOL, V157, P175, DOI 10.1046/j.1469-8137.2003.00680.x
   Price JN, 2008, AUSTRAL ECOL, V33, P278, DOI 10.1111/j.1442-9993.2007.01815.x
   Prober SM, 1996, AUST J BOT, V44, P57, DOI 10.1071/BT9960057
   PROBER SM, 1994, CONSERV BIOL, V8, P1003, DOI 10.1046/j.1523-1739.1994.08041003.x
   Prober SM, 2002, AUST J BOT, V50, P687, DOI 10.1071/BT02043
   Prober SM, 2008, INT J WILDLAND FIRE, V17, P586, DOI 10.1071/WF07077
   Prober SM, 2007, AUSTRAL ECOL, V32, P808, DOI 10.1111/j.1442-9993.2007.01762.x
   Prober Suzanne M., 2005, Ecological Management & Restoration, V6, P16, DOI 10.1111/j.1442-8903.2005.00215.x
   Prober SM, 2012, DIVERS DISTRIB, V18, P795, DOI 10.1111/j.1472-4642.2011.00872.x
   Prober SM, 2012, CLIMATIC CHANGE, V110, P227, DOI 10.1007/s10584-011-0092-y
   Prober SM, 2009, AGR ECOSYST ENVIRON, V132, P173, DOI 10.1016/j.agee.2009.04.005
   Prober SM, 2009, BIOL INVASIONS, V11, P171, DOI 10.1007/s10530-008-9222-5
   Prober Suzanne M., 2004, Cunninghamia, V8, P306
   Radford JQ, 2005, BIOL CONSERV, V124, P317, DOI 10.1016/j.biocon.2005.01.039
   Sankaran M, 2005, NATURE, V438, P846, DOI 10.1038/nature04070
   Shea K, 2002, TRENDS ECOL EVOL, V17, P170, DOI 10.1016/S0169-5347(02)02495-3
   Smallbone LT, 2007, AUST J BOT, V55, P818, DOI 10.1071/BT07106
   Smith FP, 2013, AGR ECOSYST ENVIRON, V166, P35, DOI 10.1016/j.agee.2012.01.014
   Thiele KR, 2000, TEMPERATE EUCALYPT WOODLANDS IN AUSTRALIA, P351
   Thuiller W, 2008, PERSPECT PLANT ECOL, V9, P137, DOI 10.1016/j.ppees.2007.09.004
   Vesk PA, 2006, AUST J BOT, V54, P509, DOI 10.1071/BT05188
   Walker B, 1999, ECOSYSTEMS, V2, P95, DOI 10.1007/s100219900062
   Watson PJ, 2009, AUSTRAL ECOL, V34, P218, DOI 10.1111/j.1442-9993.2008.01924.x
   Williams AL, 2007, NEW PHYTOL, V176, P365, DOI 10.1111/j.1469-8137.2007.02170.x
   Williams JW, 2007, P NATL ACAD SCI USA, V104, P5738, DOI 10.1073/pnas.0606292104
   Williams K., 2010, Harnessing continent‐wide biodiversity datasets for prioritising national conservation investment: 2. Appendices
   Yates CJ, 2010, AUSTRAL ECOL, V35, P374, DOI 10.1111/j.1442-9993.2009.02044.x
NR 73
TC 33
Z9 37
U1 4
U2 87
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0960-3115
EI 1572-9710
J9 BIODIVERS CONSERV
JI Biodivers. Conserv.
PD JUN
PY 2012
VL 21
IS 7
BP 1627
EP 1650
DI 10.1007/s10531-012-0268-4
PG 24
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 944AY
UT WOS:000304171900001
DA 2025-01-10
ER

PT J
AU You, MZ
   Guan, CH
AF You, Meizi
   Guan, Chenghe
TI Does self-containment of spatial scale and land use function contribute
   to mitigate urban heat island effects? Lessons from new towns in
   Shanghai
SO LAND USE POLICY
LA English
DT Article
DE New town; Land use diversity; Urban heat island; Climate adaptative;
   Sustainable development; China
ID JOBS-HOUSING BALANCE; POLICY; GREENBELTS; POLITICS
AB The concept of self-containment in new towns has been widely discussed from social and economic perspectives. However, localized interpretations within the context of China's development, particularly regarding climate adaptability and urban heat island (UHI) mitigation, are scarce. To fill this gap, our research analyzed selfcontainment from the perspectives of urban spatial scale and land use function. Focusing on Shanghai's five new towns, we empirically demonstrated how self-containment influenced the UHI effects from 2005 to 2020, employing the Geodetector method. The findings reveal that during the daytime, the intensity of UHI in new towns decreased, serving as vital connectivity nodes of UHI within the region. Conversely, during the nighttime, both the intensity and area of UHI showed an increasing trend. The research confirmed that expanding the urban scale and functional diversity are effective strategies for mitigating the UHI. Based on these findings, we offer practical suggestions for the development of new towns: Increase population size while ensuring coordination with development scale; enhance mixed-use functions in large-scale development projects like university towns and industrial parks; and be vigilant of potential functional decline in central areas and increasing thermal impact due to new town development. Overall, this study enriches our understanding of self-containment in Chinese new towns and provides valuable insights for mitigating UHI in other similar contexts.
C1 [You, Meizi; Guan, Chenghe] NYU Shanghai, Shanghai Key Lab Urban Design & Urban Sci, Shanghai, Peoples R China.
   [You, Meizi] East China Normal Univ, Sch Ecol & Environm Sci, Shanghai, Peoples R China.
   [Guan, Chenghe] NYU Shanghai, Div Arts & Sci, Shanghai, Peoples R China.
C3 NYU Shanghai; East China Normal University; NYU Shanghai
RP Guan, CH (corresponding author), NYU Shanghai, Shanghai Key Lab Urban Design & Urban Sci, Shanghai, Peoples R China.
EM cg157@nyu.edu
RI Guan, ChengHe/AAM-9581-2020
OI You, Meizi/0000-0002-5521-5290
FU Foreign Young Talents Program from the State Administration of Foreign
   Experts Affairs [10109]; Pudong New District Development and Reform
   Commission [20221103257 PDRC]; Pudong Comprehensive Economic Society
   [20230410 PCES]; Shanghai Tongmu Architecture Consulting and Shanghai
   Tech-nology Exchange [20240529 TONGMU]; Spring 2022 Climate Change
   Initiative Seed Grants [22-2126]; New York University
FX This research is funded by the Shanghai Nature and Health Foundation
   (Grant No. 20230701 SNHF), Shanghai, China; Pudong Pearl Program Leading
   Scheme 2023, Pudong Talents Office; Program for Professor of Special
   Appointment (Eastern Scholar) at Shanghai Institutions of Higher
   Learning (Grant No. 20230111 SMEC); National Foreign Young Talents
   Program from the State Administration of Foreign Experts Affairs (Grant
   No. 10109_ Special Grant); Pudong New District Development and Reform
   Commission (Grant No. 20221103257 PDRC); Pudong Comprehensive Economic
   Society (Grant No. 20230410 PCES); Shanghai Tongmu Architecture
   Consulting and Shanghai Technology Exchange (Grant No. 20240529 TONGMU);
   the Spring 2022 Climate Change Initiative Seed Grants (Grant No.
   22-2126), New York University.r Foreign Young Talents Program from the
   State Administration of Foreign Experts Affairs (Grant No. 10109_
   Special Grant) ; Pudong New District Development and Reform Commission
   (Grant No. 20221103257 PDRC) ; Pudong Comprehensive Economic Society
   (Grant No. 20230410 PCES) ; Shanghai Tongmu Architecture Consulting and
   Shanghai Tech-nology Exchange (Grant No. 20240529 TONGMU) ; the Spring
   2022 Climate Change Initiative Seed Grants (Grant No. 22-2126) , New
   York University.
CR Alexander A., 2009, Britain's new towns: garden cities to sustainable communities, DOI [10.4324/9780203875650, DOI 10.4324/9780203875650]
   Almulhim AI, 2023, HABITAT INT, V139, DOI 10.1016/j.habitatint.2023.102884
   Bonafoni S, 2017, SUSTAIN CITIES SOC, V29, P211, DOI 10.1016/j.scs.2016.11.005
   Budhiraja B, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100634
   Chen H, 2015, SUSTAINABILITY-BASEL, V7, P5682, DOI 10.3390/su7055682
   Chen TL, 2021, SUSTAIN CITIES SOC, V72, DOI 10.1016/j.scs.2021.103005
   Cheng Y, 2018, CITIES, V77, P81, DOI 10.1016/j.cities.2018.01.015
   Cho SE, 2017, HABITAT INT, V66, P32, DOI 10.1016/j.habitatint.2017.05.009
   Choi CG, 2019, LAND USE POLICY, V80, P195, DOI 10.1016/j.landusepol.2018.09.027
   De Pieri F, 2019, J URBAN HIST, V45, P177, DOI 10.1177/0096144218806851
   Eliasson I, 2000, LANDSCAPE URBAN PLAN, V48, P31, DOI 10.1016/S0169-2046(00)00034-7
   Em PP, 2024, CITIES, V151, DOI 10.1016/j.cities.2024.105106
   Fitzgerald J, 2022, J AM PLANN ASSOC, V88, P508, DOI 10.1080/01944363.2021.2013301
   Forsyth A, 2021, LANDSCAPE URBAN PLAN, V205, DOI 10.1016/j.landurbplan.2020.103957
   Godschalk D, 2021, Environmental Concerns and New Towns: Four Paths, DOI [10.9783/9780812297317-022, DOI 10.9783/9780812297317-022]
   Governa F, 2020, URBAN STUD, V57, P366, DOI 10.1177/0042098019860807
   Grant JL, 2024, J AM PLANN ASSOC, V90, P213, DOI 10.1080/01944363.2023.2207619
   Guan CH, 2022, CITIES, V130, DOI 10.1016/j.cities.2022.103869
   Guan CH, 2016, CITIES, V55, P22, DOI 10.1016/j.cities.2016.03.012
   He BJ, 2023, LANDSCAPE URBAN PLAN, V237, DOI 10.1016/j.landurbplan.2023.104800
   He BJ, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103361
   He SY, 2020, J AM PLANN ASSOC, V86, P324, DOI 10.1080/01944363.2020.1725602
   He SY, 2023, J PLAN EDUC RES, DOI 10.1177/0739456X231188301
   Hu D, 2020, SCI TOTAL ENVIRON, V706, DOI 10.1016/j.scitotenv.2019.135244
   Huang BZ, 2024, NAT HAZARDS, V120, P2005, DOI 10.1007/s11069-023-06266-6
   Huang JX, 2023, ENVIRON PLAN B-URBAN, V50, P76, DOI 10.1177/23998083221106186
   Hui ECM, 2005, HABITAT INT, V29, P421, DOI 10.1016/j.habitatint.2004.01.001
   Ke X, 2024, SUSTAIN CITIES SOC, V101, DOI 10.1016/j.scs.2024.105183
   Kirby MG, 2023, LANDSCAPE URBAN PLAN, V230, DOI 10.1016/j.landurbplan.2022.104635
   Klopp JM, 2017, CITIES, V63, P92, DOI 10.1016/j.cities.2016.12.019
   Krishnan S, 2023, CITIES, V141, DOI 10.1016/j.cities.2023.104464
   Kwak Y, 2020, SUSTAIN CITIES SOC, V61, DOI 10.1016/j.scs.2020.102341
   Lee K, 2022, ENVIRON MONIT ASSESS, V194, DOI 10.1007/s10661-022-09967-w
   Lee S, 2019, URBAN FOR URBAN GREE, V41, P55, DOI 10.1016/j.ufug.2019.03.001
   Lee YS, 2012, URBAN STUD, V49, P1333, DOI 10.1177/0042098011411947
   Li KQ., 2024, Evidence from China. Land Use Policy, V144, P1
   Li SX, 2022, HABITAT INT, V124, DOI 10.1016/j.habitatint.2022.102558
   Li WZ, 2024, ENVIRON PLAN B-URBAN, V51, P1948, DOI 10.1177/23998083241227500
   Li YF, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103146
   Liu HM, 2023, REMOTE SENS ENVIRON, V296, DOI 10.1016/j.rse.2023.113735
   Liu HM, 2021, SUSTAIN CITIES SOC, V71, DOI 10.1016/j.scs.2021.102987
   Liu Y, 2022, CATENA, V214, DOI 10.1016/j.catena.2022.106265
   Mace A, 2018, PROG PLANN, V121, P1, DOI 10.1016/j.progress.2017.01.001
   Mentaschi L, 2022, GLOBAL ENVIRON CHANG, V72, DOI 10.1016/j.gloenvcha.2021.102441
   Park GH, 2018, SOCIO-ECON PLAN SCI, V63, P47, DOI 10.1016/j.seps.2017.06.005
   Qi JD, 2023, URBAN CLIM, V47, DOI 10.1016/j.uclim.2022.101372
   Qi JD, 2022, RESOUR CONSERV RECY, V184, DOI 10.1016/j.resconrec.2022.106420
   Rumbach A, 2014, HABITAT INT, V43, P117, DOI 10.1016/j.habitatint.2014.03.005
   Sharifi A, 2023, PROG PLANN, V173, DOI 10.1016/j.progress.2023.100740
   Sharifi A, 2019, CITIES, V85, P1, DOI 10.1016/j.cities.2018.11.023
   Shi YN, 2022, CITIES, V127, DOI 10.1016/j.cities.2022.103737
   Song YB, 2005, J ENVIRON SCI-CHINA, V17, P641
   Song YZ, 2020, GISCI REMOTE SENS, V57, P593, DOI 10.1080/15481603.2020.1760434
   Stuhlmacher M, 2022, CITIES, V126, DOI 10.1016/j.cities.2022.103705
   Tan XW, 2010, CHIN ECON, V43, P47, DOI 10.2753/CES1097-1475430304
   Tao S, 2023, CITIES, V137, DOI 10.1016/j.cities.2023.104324
   Vongpraseuth T, 2020, CITIES, V102, DOI 10.1016/j.cities.2020.102699
   Wang SB, 2022, LAND USE POLICY, V114, DOI 10.1016/j.landusepol.2021.105973
   Wang YW, 2010, PLAN PERSPECT, V25, P141, DOI 10.1080/02665431003612917
   Williams S, 2019, CITIES, V94, P275, DOI 10.1016/j.cities.2019.05.006
   Woodworth MD, 2022, GEOGR COMPASS, V16, DOI 10.1111/gec3.12612
   Wu C, 2023, ENVIRON PLAN B-URBAN, V50, P130, DOI 10.1177/23998083221108191
   Wu WP, 2021, CITIES, V113, DOI 10.1016/j.cities.2021.103142
   Xu BQ, 2022, J PLAN LIT, V37, P236, DOI 10.1177/08854122211051614
   Yan LX, 2021, CITIES, V113, DOI 10.1016/j.cities.2021.103156
   Yang SG, 2015, CITIES, V47, P23, DOI 10.1016/j.cities.2014.12.008
   Yokohari M, 2000, LANDSCAPE URBAN PLAN, V47, P159, DOI 10.1016/S0169-2046(99)00084-5
   You MZ, 2023, SUSTAIN CITIES SOC, V99, DOI 10.1016/j.scs.2023.104939
   You MZ, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph182413088
   Zeng P, 2024, CITIES, V150, DOI 10.1016/j.cities.2024.105028
   Zhang ZF, 2019, LAND USE POLICY, V82, P620, DOI 10.1016/j.landusepol.2018.12.040
   Zhao HB, 2023, ISCIENCE, V26, DOI 10.1016/j.isci.2023.106479
   Zheng ZF, 2024, SUSTAIN CITIES SOC, V102, DOI 10.1016/j.scs.2024.105233
   Zhou XG, 2022, LAND USE POLICY, V119, DOI 10.1016/j.landusepol.2022.106201
   Zhou XG, 2018, J TRANSP GEOGR, V68, P102, DOI 10.1016/j.jtrangeo.2017.12.006
   Zhu Y, 2022, CITIES, V131, DOI 10.1016/j.cities.2022.104029
NR 76
TC 0
Z9 0
U1 13
U2 13
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0264-8377
EI 1873-5754
J9 LAND USE POLICY
JI Land Use Pol.
PD NOV
PY 2024
VL 146
AR 107323
DI 10.1016/j.landusepol.2024.107323
EA AUG 2024
PG 13
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA E1I5Q
UT WOS:001300615200001
DA 2025-01-10
ER

PT J
AU McOmber, C
   Audia, C
   Crowley, F
AF McOmber, Chesney
   Audia, Camilla
   Crowley, Frances
TI Building resilience by challenging social norms: integrating a
   transformative approach within the BRACED consortia
SO DISASTERS
LA English
DT Article
DE BRACED (Building Resilience and Adaptation to Climate Extremes and
   Disasters); climate change; gender; gender transformative approach;
   resilience; transformation
ID CLIMATE-CHANGE; GENDER; ADAPTATION
AB Resilience is a complex phenomenon whereby a multitude of social and environmental factors, including gender, combine to shape the ways that shocks affect people. Looking at two BRACED (Building Resilience and Adaptation to Climate Extremes and Disasters) projects, in Burkina Faso and in Ethiopia, this article uses a desk review and primary data from partners and people at risk to explore how a gender-transformative approach can be an integral part of resilience-building projects, particularly those implemented by multi-stakeholder consortia. It also suggests ways to incorporate a stronger gender component in similar future projects. The article argues that donors and programme managers must provide clear principles and guidelines for achieving gender equity within resilience-building efforts. However, these must allow flexibility to adapt to norms, needs and resources as determined by implementing partners. The right balance can be achieved by facilitating spaces for individual and collective goal-setting; assessing current capacity and trajectories; and lesson-sharing as an iterative process for institutional learning.
C1 [McOmber, Chesney] Univ Florida, Gainesville, FL 32611 USA.
   [Audia, Camilla] Univ Sussex, Sch Global Studies, Geog, Sussex House, Brighton BN1 9RH, E Sussex, England.
   [Crowley, Frances] Kings Coll London, London, England.
C3 State University System of Florida; University of Florida; University of
   Sussex; University of London; King's College London
RP McOmber, C (corresponding author), Univ Florida, Gainesville, FL 32611 USA.; Audia, C (corresponding author), Univ Sussex, Sch Global Studies, Geog, Sussex House, Brighton BN1 9RH, E Sussex, England.
EM chesneymcomber@gmail.com; camillaudia@gmail.com
OI McOmber, Chesney/0000-0001-9741-5760; Audia, Camilla/0000-0002-1504-9750
FU DFID
FX This research emerges from the BRACED Building Resilience and Adaptation
   to Climate Extremes and Disasters programme funded by DFID and more
   specifically the Burkina Faso and Ethiopia Christian Aid-led projects.
   We would like to thank our partners and all the participants who
   accepted to share their insights by taking part in interviews as well as
   the reviewers. The views expressed in this paper are in the authors'
   personal capacity, and do not represent the views of their respective
   institutions. Any errors or omissions remain our own.
CR Agarwal B, 2018, CURR OPIN ENV SUST, V34, P26, DOI 10.1016/j.cosust.2018.07.002
   [Anonymous], 2011, ESA Working Paper No. 11-02 March 2011
   [Anonymous], 2012, LIT REV GENDER DIFFE
   Bahadur A. V., 2015, WORKING PAPER
   Batliwala S., 2010, CAPTURING CHANGE WOM
   Bene C., 2012, WORKING PAPERS IDS, V2012 (405)
   Berkes F., 2007, International Journal of the Commons, V2, P1
   Berkes F, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9071232
   Blaikie P., 2003, At risk - Natural hazards, people's vulnerability and disasters
   Bob U, 2014, AGENDA-EMPOWER WOMEN, V28, P3, DOI 10.1080/10130950.2014.958907
   Cannon T, 2010, NAT HAZARDS, V55, P621, DOI 10.1007/s11069-010-9499-4
   Carr ER, 2014, GEOGR COMPASS, V8, P182, DOI 10.1111/gec3.12121
   Christian Aid, 2014, BUILD RES AD CLIM EX
   Christian Aid, 2018, ZAM LEB FIN EV
   Cole S.M., 2014, AAS201442 CGIAR RES
   Cornwall A, 2007, DEV CHANGE, V38, P1, DOI 10.1111/j.1467-7660.2007.00400.x
   Crowley F., 2018, 8 CHRIST AID KCL
   Dankelman I., 2010, Gender and Climate change: An introduction, P21
   Deere CD, 2003, WORLD DEV, V31, P925, DOI 10.1016/S0305-750X(03)00046-9
   Denton F., 2002, Gender and Development, V10, P10, DOI 10.1080/13552070215903
   Duckett D, 2016, LANDSCAPE URBAN PLAN, V154, P44, DOI 10.1016/j.landurbplan.2016.03.015
   Edenhofer O., 2014, IPCC: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
   Ferdous N., 2015, 99 CCAFS
   Ginige K, 2009, DISASTER PREV MANAG, V18, P23, DOI 10.1108/09653560910938510
   Hillenbrand E., 2015, Measuring Gender Transformative Change: A Review of Literature and Promising Practices
   Jost C, 2016, CLIM DEV, V8, P133, DOI 10.1080/17565529.2015.1050978
   Kabeer Naila., 2005, Gender Development, V13, P13, DOI DOI 10.1080/13552070512331332273
   Kantor P, 2015, GEND TECHNOL DEV, V19, P292, DOI 10.1177/0971852415596863
   Le Masson V., 2016, Gender and resilience: From theory to practice
   Martin-Breen P., 2011, Resilience: A literature review
   McDaniels T, 2008, GLOBAL ENVIRON CHANG, V18, P310, DOI 10.1016/j.gloenvcha.2008.03.001
   McDougall C, 2015, Research in Development: Learning from the CGIAR Research Program on Aquatic Agricultural Systems
   Meinzen-Dick R, 2014, ANNU REV ENV RESOUR, V39, P29, DOI 10.1146/annurev-environ-101813-013240
   Moser C.O.N., 1993, GENDER PLANNING DEV
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Perez C, 2015, GLOBAL ENVIRON CHANG, V34, P95, DOI 10.1016/j.gloenvcha.2015.06.003
   Pike A, 2010, CAMB J REG ECON SOC, V3, P59, DOI 10.1093/cjres/rsq001
   Promundo-US & CGIAR Research Program on Aquatic Agricultural Systems, 2016, PROM GEND TRANSF CHA
   Rigg S., 2015, 1 CHRIST AID KCL
   Smyth I., 2015, Gender Development, V23, P405, DOI DOI 10.1080/13552074.2015.1113769
   Visman E., 2018, 7 CHRIST AID KCL
   Walker B, 2004, ECOL SOC, V9
NR 43
TC 4
Z9 4
U1 2
U2 17
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0361-3666
EI 1467-7717
J9 DISASTERS
JI Disasters
PD APR
PY 2019
VL 43
SU 3
SI SI
BP S271
EP S294
DI 10.1111/disa.12341
PG 24
WC Environmental Studies; Social Sciences, Interdisciplinary
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Social Sciences - Other Topics
GA IA2JX
UT WOS:000469388600003
PM 30945766
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Zhang, ZY
   Zhang, WH
   Wu, QY
   Liu, JH
   Jiang, L
AF Zhang, Zhiyue
   Zhang, Wenhao
   Wu, Qingyang
   Liu, Jiahe
   Jiang, Lei
TI Climate Adaptation through Trade: Evidence and Mechanism from Heatwaves
   on Firms' Imports
SO CHINA ECONOMIC REVIEW
LA English
DT Article
DE Climate change; Adaptation; Extreme heat; Imports; Trade
ID POLICY BURDENS; TEMPERATURE; WEATHER; IMPACT
AB Firms can adapt causally to heat waves by altering their import behaviors. Utilizing matched data from the China Customs Database, the China Industrial Enterprise Database, and the China National Meteorological Science Data Center, this paper investigates variations in firm -level imports on days marked by extreme heat. The study robustly establishes that, in comparison to the temperature range of [12 degrees C, 15 degrees C), extreme heat leads to increased imports by industrial firms. Additionally, for each additional day within a month featuring an average daily temperature falling within the ranges [24 degrees C, 27 degrees C), [27 degrees C, 30 degrees C), or [30 degrees C, +infinity), monthly imports for firms increase cumulatively by 0.35%, 0.57%, and 0.56%, respectively. Notably, the impact of hot weather on non -state-owned labor-intensive firms is particularly pronounced. Our mechanistic analysis suggests that firms resort to heightened imports as a strategy for adapting to the warming climate, mitigating the elevated domestic production costs identified in existing studies. These findings bear relevance to the formulation of future "bottom -up" climate adaptation policies.
C1 [Zhang, Zhiyue] Capital Univ Econ & Business, Sch Econ, Beijing 100070, Peoples R China.
   [Zhang, Wenhao] Nankai Univ, Sch Finance, Tianjin 300071, Peoples R China.
   [Wu, Qingyang] Univ Calif Los Angeles, Fielding Sch Publ Hlth, Los Angeles, CA 90095 USA.
   [Liu, Jiahe; Jiang, Lei] Nankai Univ, Sch Econ, Tianjin 300071, Peoples R China.
C3 Capital University of Economics & Business; Nankai University;
   University of California System; University of California Los Angeles;
   Nankai University
RP Jiang, L (corresponding author), Nankai Univ, Sch Econ, Tianjin 300071, Peoples R China.
EM jianglei@nankai.edu.cn
FU Tianjin Philosophy and Social Science Planning Program [TJLJ22-001];
   Asia Research Center in Nankai University [AS2304]
FX Thanks to the Tianjin Philosophy and Social Science Planning Program
   (TJLJ22-001) and the Asia Research Center in Nankai University (AS2304)
   .
CR Bas M, 2012, J DEV ECON, V97, P481, DOI 10.1016/j.jdeveco.2011.05.010
   Buggle JC, 2021, ECON J, V131, P1947, DOI 10.1093/ej/ueaa127
   Chen XG, 2019, J ENVIRON ECON MANAG, V95, P257, DOI 10.1016/j.jeem.2017.07.009
   Dallmann I, 2019, ENVIRON RESOUR ECON, V72, P155, DOI 10.1007/s10640-018-0268-2
   Dell M, 2014, J ECON LIT, V52, P740, DOI 10.1257/jel.52.3.740
   Dell M, 2012, AM ECON J-MACROECON, V4, P66, DOI 10.1257/mac.4.3.66
   Diewert WErwin., 1989, Flexible functional forms and global curvature conditions
   Feng L, 2016, J INT ECON, V101, P86, DOI 10.1016/j.jinteco.2016.03.004
   Jagnani M, 2021, ECON J, V131, P392, DOI 10.1093/ej/ueaa063
   Jiang L, 2024, ENERG ECON, V130, DOI 10.1016/j.eneco.2023.107291
   Jin Z., 2021, Evidence from establishment-level data
   Lai WY, 2022, NAT HUM BEHAV, V6, P837, DOI 10.1038/s41562-022-01315-9
   Leonardsson H, 2021, WORLD DEV, V147, DOI 10.1016/j.worlddev.2021.105656
   Li CZ, 2021, CHINA ECON REV, V66, DOI 10.1016/j.chieco.2021.101593
   Lin JYF, 1999, AM ECON REV, V89, P426, DOI 10.1257/aer.89.2.426
   Lin JYF, 1998, AM ECON REV, V88, P422
   Liu XQ, 2023, APPL ECON, V55, P2801, DOI 10.1080/00036846.2022.2106033
   Ludema RD, 2021, J INT ECON, V131, DOI 10.1016/j.jinteco.2021.103479
   Masson-Delmotte V., 2021, Climate change 2021: The physical science basis, DOI [DOI 10.1017/9781009157896, 10.1017/9781009157896.002, DOI 10.1017/9781009157896.002]
   Mohammadi T., 2011, The effect of exchange rate uncertainty on import: TARCH approach
   Quiroga S, 2020, WORLD DEV, V126, DOI 10.1016/j.worlddev.2019.104733
   ROSENZWEIG C, 1994, NATURE, V367, P133, DOI 10.1038/367133a0
   Serletis A, 2015, ECONOMET REV, V34, P198, DOI 10.1080/07474938.2014.945385
   Somanathan E, 2021, J POLIT ECON, V129, P1797, DOI 10.1086/713733
   Wagner J, 2015, APPL ECON, V47, P415, DOI 10.1080/00036846.2014.969829
   Waldinger M, 2022, J POLIT ECON, DOI 10.1086/720393
   Wang CG, 2023, APPL ECON, V55, P4678, DOI 10.1080/00036846.2022.2130870
   Wang YQ, 2021, J ECON BEHAV ORGAN, V187, P470, DOI 10.1016/j.jebo.2021.04.039
   Wolf J, 1996, CLIMATE RES, V7, P253, DOI 10.3354/cr007253
   Yu MJ, 2015, ECON J, V125, P943, DOI 10.1111/ecoj.12127
   Zhang P, 2018, J ENVIRON ECON MANAG, V88, P1, DOI 10.1016/j.jeem.2017.11.001
   Zivin JG, 2014, J LABOR ECON, V32, P1, DOI 10.1086/671766
   Zivin JG, 2012, AM ECON REV, V102, P3652, DOI 10.1257/aer.102.7.3652
NR 33
TC 4
Z9 4
U1 10
U2 14
PU ELSEVIER SCIENCE INC
PI NEW YORK
PA STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA
SN 1043-951X
EI 1873-7781
J9 CHINA ECON REV
JI China Econ. Rev.
PD APR
PY 2024
VL 84
AR 102133
DI 10.1016/j.chieco.2024.102133
EA MAR 2024
PG 19
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA NS6T3
UT WOS:001202489400001
DA 2025-01-10
ER

PT J
AU Pathak, A
   van Beynen, PE
   Akiwumi, FA
   Lindeman, KC
AF Pathak, Arsum
   van Beynen, Philip E.
   Akiwumi, Fenda A.
   Lindeman, Kenyon C.
TI Climate adaptation within the tourism sector of a small island
   developing state: A case study from the coastal accommodations subsector
   in the Bahamas
SO BUSINESS STRATEGY AND DEVELOPMENT
LA English
DT Article
DE adaptive capacity; climate adaptation; resilience; small island
   developing states; the Bahamas; tourism
ID ECOSYSTEM-BASED ADAPTATION; ADAPTIVE CAPACITY; FRAMEWORK; RESILIENCE;
   RISK; VULNERABILITY; PERCEPTIONS; DRIVERS
AB Tourism in Small Island Developing States (SIDS) is vulnerable to climate change. Using the Bahamas as a case study, this study presents findings from a survey administered with property managers from the coastal accommodations sector to identify their adaptation strategies to tackle climate change. We also evaluate their adaptive capacity by developing SIDS-specific indicators based on a capitals approach. Findings indicate that efforts toward adaptation were limited to disaster preparedness for hurricanes, reflecting a short-term focus in the face of climate change uncertainties. In addition to the lack of finances and knowledge for incorporating adaptation measures, their capacity to adapt is diminished due to a lack of access to climate change information, skilled staff, and specific climate change planning reflecting limited human and institutional capitals. Recommendations are provided for strategies synergistic with the resilience focus of our paper such as ecosystem-based adaptation and green jobs. The study informs tourism resilience and adaptation planning in the Bahamas which may apply to other SIDS.
C1 [Pathak, Arsum; van Beynen, Philip E.; Akiwumi, Fenda A.] Univ S Florida, Sch Geosci, Geog Environm Sci & Policy Program, 4202 E Fowler Ave, Tampa, FL 33620 USA.
   [Lindeman, Kenyon C.] Florida Inst Technol, Program Sustainabil, Melbourne, FL 32901 USA.
C3 State University System of Florida; University of South Florida; Florida
   Institute of Technology
RP Pathak, A (corresponding author), Univ S Florida, Sch Geosci, Geog Environm Sci & Policy Program, 4202 E Fowler Ave, Tampa, FL 33620 USA.
EM arsumpathak@usf.edu
RI van Beynen, Philip/G-5653-2017; Pathak, Arsum/AAJ-9116-2021
OI Lindeman, Ken/0000-0003-4098-4158; Pathak, Arsum/0000-0001-5237-7166
FU Tharp Research Endowed Scholarship, School of Geosciences, University of
   South Florida, Tampa, FL, USA
FX Tharp Research Endowed Scholarship, School of Geosciences, University of
   South Florida, Tampa, FL, USA
CR [Anonymous], 2014, CLIM CHANG 2014 IMP
   [Anonymous], 2016, ASEE ANN C EXP NEW O
   [Anonymous], 2011, Reefs at Risk Revisited
   [Anonymous], 2019, Assessment of the Effects and Impacts of Hurricane Matthew - The Bahamas
   Bahadur AV, 2013, CLIM DEV, V5, P55, DOI 10.1080/17565529.2012.762334
   Barnett J., 2016, The Palgrave handbook of international development, P731, DOI DOI 10.1057/978-1-137-42724-3-40
   Becken S, 2005, GLOBAL ENVIRON CHANG, V15, P381, DOI 10.1016/j.gloenvcha.2005.08.001
   Becken S, 2014, NAT HAZARDS, V71, P955, DOI 10.1007/s11069-013-0946-x
   Becken S, 2013, ANN TOURISM RES, V43, P506, DOI 10.1016/j.annals.2013.06.002
   Bender MA, 2010, SCIENCE, V327, P454, DOI 10.1126/science.1180568
   Beneby Katherine, 2014, BAHAMAS WEEKLY 0613
   Betzold C, 2015, CLIMATIC CHANGE, V133, P481, DOI 10.1007/s10584-015-1408-0
   Biggs D, 2012, J SUSTAIN TOUR, V20, P645, DOI 10.1080/09669582.2011.630080
   Brown NA, 2019, INT J DISAST RISK RE, V33, P108, DOI 10.1016/j.ijdrr.2018.09.014
   Brown NA, 2018, J HOSP TOUR MANAG, V36, P67, DOI 10.1016/j.jhtm.2018.07.004
   CBD, 2009, CBD TECHNICAL SERIES, V41
   Central Intelligence Agency (CIA), 2018, WORLD FACTBOOK BAHAM
   Chan E.K. H., 2014, Encyclopedia of Quality of Life and Well-Being Research
   Chen XD, 2013, AMBIO, V42, P52, DOI 10.1007/s13280-012-0335-9
   Chin N, 2019, J DESTIN MARK MANAGE, V12, P125, DOI 10.1016/j.jdmm.2018.12.009
   Cochrane J, 2010, TOUR RECREAT RES, V35, P173, DOI 10.1080/02508281.2010.11081632
   Dolnicar S, 2012, INT J CULT TOUR HOSP, V6, P316, DOI 10.1108/17506181211265059
   Ellis F., 2000, RURAL LIVELIHOODS DI, DOI DOI 10.1093/OSO/9780198296959.001.0001
   Engle NL, 2014, MITIG ADAPT STRAT GL, V19, P1295, DOI 10.1007/s11027-013-9475-x
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   Esposto A.S., 2016, SKILLS NEEDS EMERGIN
   Fang Y., 2018, J SUSTAIN TOUR, V26, P108, DOI DOI 10.1080/09669582.2017.1329310
   Hayes MC, 2015, OCEAN COAST MANAGE, V106, P118, DOI 10.1016/j.ocecoaman.2015.01.007
   Hendrickson M., 2020, Industrial upgrading and diversification to address competitiveness challenges in the Caribbean: The case of tourism
   Hess JantoS., 2017, Climate, Disaster and Development Journal, V2, P34, DOI [DOI 10.18783/CDDJ.V002.I02.A04, 10.18783/cddj.v002.i02.a04]
   Hinds D., 2017, Coastal tourism, sustainability, and climate change in the Caribbean, volume I: Beaches and hotels, P85
   Holladay P. J., 2018, COASTAL RESILIENCE S
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Holmes T., 2017, Tourism Resilience and Adaptation to Environmental Change, P85
   Honey M., 2017, Coastal Tourism, Sustainability, and Climate Change in the Caribbean, Volume i: Beaches and Hotels, Vi
   Kaján E, 2013, CURR ISSUES TOUR, V16, P286, DOI 10.1080/13683500.2012.685704
   Klöck C, 2019, J ENVIRON DEV, V28, P196, DOI 10.1177/1070496519835895
   Lee AV, 2013, NAT HAZARDS REV, V14, P29, DOI 10.1061/(ASCE)NH.1527-6996.0000075
   Lew A.A., 2017, Tourism resilience and adaptation to environmental change, P102
   Madsen HM, 2019, ENVIRON SCI POLICY, V98, P30, DOI 10.1016/j.envsci.2019.04.004
   Ministry of Finance (MOF), 2018, OCC WAG HOSP SECT NE
   Ministry of Tourism (MOT), 2018, DIRECTORY HOTELS JUN
   Ministry of Tourism (MOT), 2016, YEARLY EXPENDITURE C
   Ministry of Works & Utilities, 2003, BAHAMAS BUILDING COD, V3 rd
   Moore W.R., 2010, The supply side effects of climate change on tourism
   Munang R, 2013, CURR OPIN ENV SUST, V5, P67, DOI 10.1016/j.cosust.2012.12.001
   Mycoo MA, 2018, REG ENVIRON CHANGE, V18, P2341, DOI 10.1007/s10113-017-1248-8
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Njoroge JM, 2015, TOUR HOSP MANAG-CROA, V21, P95
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   Orchiston C, 2013, CURR ISSUES TOUR, V16, P477, DOI 10.1080/13683500.2012.741115
   Parsons M, 2018, CLIM DEV, V10, P644, DOI 10.1080/17565529.2017.1410082
   Pathak A., 2020, ENVIRON DEV, V100556
   Pathak A., 2021, BUS STRATEGY DEV, P1
   Petzold J, 2015, OCEAN COAST MANAGE, V112, P36, DOI 10.1016/j.ocecoaman.2015.05.003
   Robinson SA, 2017, MITIG ADAPT STRAT GL, V22, P669, DOI 10.1007/s11027-015-9693-5
   Saarinen J, 2012, DEV SO AFR, V29, P273, DOI 10.1080/0376835X.2012.675697
   Scarano FR, 2017, PERSPECT ECOL CONSER, V15, P65, DOI 10.1016/j.pecon.2017.05.003
   SCOTT D., 2012, TOURISM CLIMATE CHAN
   Scott D., 2008, CLIMATE CHANGE TOURI, V230, P1
   Scott D, 2012, J SUSTAIN TOUR, V20, P883, DOI 10.1080/09669582.2012.699063
   Shakeela A, 2015, J SUSTAIN TOUR, V23, P65, DOI 10.1080/09669582.2014.918135
   Spencer A., 2019, Travel and tourism in the Caribbean, P27, DOI [DOI 10.1007/978-3-319-69581-5_2, DOI 10.1007/978-3-319-69581-52]
   Su YP, 2013, ASIA PAC J TOUR RES, V18, P92, DOI 10.1080/10941665.2012.688513
   Thomas A.D., 2012, An integrated view: Multiple stressors and small tourism enterprises in the Bahamas
   Thomas A, 2018, J ENVIRON STUD SCI, V8, P63, DOI 10.1007/s13412-017-0429-6
   UN-OHRLLS, 2020, SIDS UN OHRLLS
   Van Beynen P, 2018, INT J SUST DEV WORLD, V25, P99, DOI 10.1080/13504509.2017.1317673
   van der Linden S, 2014, EUR J SOC PSYCHOL, V44, P430, DOI 10.1002/ejsp.2008
   van der Veeken S, 2016, TOUR HOSP RES, V16, P50, DOI 10.1177/1467358415611068
   Walker B, 2004, ECOL SOC, V9
   Walsh KJE, 2016, WIRES CLIM CHANGE, V7, P65, DOI 10.1002/wcc.371
   Warrick O, 2017, REG ENVIRON CHANGE, V17, P1039, DOI 10.1007/s10113-016-1036-x
   Whitney CK, 2017, ECOL SOC, V22, DOI 10.5751/ES-09325-220222
   Williams KM., 2015, ELECT THESES DISSERT
   World Tourism Organization, 2019, GLOB REP WOM TOUR, V2nd, DOI [10.18111/9789284420384, DOI 10.18111/9789284420384]
   WTTC, 2018, TRAVEL TOURISM EC IM
NR 77
TC 3
Z9 3
U1 4
U2 28
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
EI 2572-3170
J9 BUS STRATEGY DEV
JI Bus. Strategy Dev.
PD SEP
PY 2021
VL 4
IS 3
BP 313
EP 325
DI 10.1002/bsd2.160
EA FEB 2021
PG 13
WC Business; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Business & Economics; Environmental Sciences & Ecology
GA US0CF
UT WOS:000616660300001
DA 2025-01-10
ER

PT J
AU Liang, YJ
   He, YT
   Liu, LJ
AF Liang, Youjia
   He, Yating
   Liu, Lijun
TI Integrated assessment of land-use management effects on ecosystem
   services under climate-adaptive scenarios in the Loess Plateau region of
   China
SO GEOJOURNAL
LA English
DT Article
DE LULC simulation; Scenarios; Carbon storage; Crop production; Water-soil
   conservation; Trade-offs
ID SOIL-EROSION; CATCHMENT; PATTERNS; GIS
AB Assessing the impacts of land-use management on the specific ecosystem services (ESs) is very important in eco-fragile regions. This study simulates the combined effects of future land-use management on ESs typical in the Chinese Loess Plateau to examine the different ecological effects of a climate adaptation scenario versus two reference scenarios (agroforestry development and business-as-usual). We integrated spatially explicit land-use modeling and biophysical simulation methods to map ecosystem service provisioning for food production, carbon storage, water conservation, and soil conservation, supported by multiple data sources. Based on our results, the BAU and agroforestry development scenarios all show declining trends in service provision compared to the base period. Conversely, climate adaptation strategies can synergistically increase existing ecosystem service provision. We believe that land management oriented towards climate resilience strategies can promote ecological restoration and ESs supply synergically in the Loess Plateau region and benefit regional. At the same time, we recommend that further attention is paid to the differentiated ecological and environmental conditions of different sub-basins. Moreover, regional agroforestry complex system models could promote local agriculture development and increase of ESs supply. Our research methods and results can support the local integrated land-use management in the Loess Plateau region, and provide useful references of policy-making for land-use issue in similar ecologically fragile areas.
C1 [Liang, Youjia; He, Yating] Wuhan Univ Technol, Sch Resources & Environm Engn, Wuhan 430070, Peoples R China.
   [Liang, Youjia] Minist Nat Resources, Observat Res Stn Land Ecol & Land Use Yangtze Rive, Nanjing 210017, Peoples R China.
   [Liu, Lijun] China Meteorol Adm, Inst Desert Meteorol, Taklimakan Desert Meteorol Field Expt Stn, Urumqi 830002, Peoples R China.
   [Liu, Lijun] China Meteorol Adm, Inst Desert Meteorol, Xinjiang Cloud Precipitat Phys & Cloud Water Resou, Urumqi 830002, Peoples R China.
C3 Wuhan University of Technology; Ministry of Natural Resources of the
   People's Republic of China; China Meteorological Administration; China
   Meteorological Administration
RP Liang, YJ (corresponding author), Wuhan Univ Technol, Sch Resources & Environm Engn, Wuhan 430070, Peoples R China.; Liang, YJ (corresponding author), Minist Nat Resources, Observat Res Stn Land Ecol & Land Use Yangtze Rive, Nanjing 210017, Peoples R China.; Liu, LJ (corresponding author), China Meteorol Adm, Inst Desert Meteorol, Taklimakan Desert Meteorol Field Expt Stn, Urumqi 830002, Peoples R China.; Liu, LJ (corresponding author), China Meteorol Adm, Inst Desert Meteorol, Xinjiang Cloud Precipitat Phys & Cloud Water Resou, Urumqi 830002, Peoples R China.
EM yjliang@whut.edu.cn; heyating@whut.edu.cn; liulijun_atm@163.com
OI Liang, Youjia/0000-0002-1503-3417
FU Open Fund of Observation Research Station of Land Ecology and Land Use
   in the Yangtze River Delta, MNR [2023YRDLELU04]; State Key Laboratory of
   Soil Erosion and Dryland Farming on the Loess Plateau
   [F2010121002-202421]; China Desert Meteorology Science Foundation
   [Sqj2023021]; China Postdoctoral Science Foundation [2023M730363]
FX This study was supported by the Open Fund of Observation Research
   Station of Land Ecology and Land Use in the Yangtze River Delta, MNR
   (2023YRDLELU04), the State Key Laboratory of Soil Erosion and Dryland
   Farming on the Loess Plateau (F2010121002-202421), the China Desert
   Meteorology Science Foundation (Sqj2023021), and the China Postdoctoral
   Science Foundation (2023M730363). The authors would like to thank the
   anonymous reviewers and editors for their invaluable comments to improve
   this paper.
CR Adeyeri OE, 2023, RENEW SUST ENERG REV, V179, DOI 10.1016/j.rser.2023.113274
   Archibald CL, 2021, ENVIRON SCI POLICY, V115, P99, DOI 10.1016/j.envsci.2020.08.016
   Bagstad KJ, 2014, ECOL SOC, V19, DOI 10.5751/ES-06523-190264
   Bryan BA, 2018, NATURE, V559, P193, DOI 10.1038/s41586-018-0280-2
   Ceausu S, 2021, ECOSYST SERV, V48, DOI 10.1016/j.ecoser.2021.101259
   [柴麒敏 Chai Qimin], 2019, [中国人口·资源与环境, China Population Resources and Environment], V29, P1
   Chen S, 2023, LAND USE POLICY, V131, DOI 10.1016/j.landusepol.2023.106697
   Chen WX, 2020, LAND USE POLICY, V90, DOI 10.1016/j.landusepol.2019.104263
   Cowling RM, 2008, P NATL ACAD SCI USA, V105, P9483, DOI 10.1073/pnas.0706559105
   Di Pirro E, 2021, ECOL MODEL, V448, DOI 10.1016/j.ecolmodel.2021.109533
   Díaz S, 2018, SCIENCE, V359, P270, DOI 10.1126/science.aap8826
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Fu BJ, 2005, LAND DEGRAD DEV, V16, P73, DOI 10.1002/ldr.646
   Fu BJ, 2017, ANNU REV EARTH PL SC, V45, P223, DOI 10.1146/annurev-earth-063016-020552
   Fu BJ, 2011, ECOL COMPLEX, V8, P284, DOI 10.1016/j.ecocom.2011.07.003
   Guerry AD, 2015, P NATL ACAD SCI USA, V112, P7348, DOI 10.1073/pnas.1503751112
   He YT, 2023, RESOUR CONSERV RECY, V199, DOI 10.1016/j.resconrec.2023.107228
   Huang QP, 2019, SUSTAIN CITIES SOC, V44, P666, DOI 10.1016/j.scs.2018.10.016
   Jia XQ, 2014, ECOL INDIC, V43, P103, DOI 10.1016/j.ecolind.2014.02.028
   Jiang C, 2018, GLOBAL PLANET CHANGE, V161, P41, DOI 10.1016/j.gloplacha.2017.11.014
   Kindu M, 2018, SCI TOTAL ENVIRON, V622, P534, DOI 10.1016/j.scitotenv.2017.11.338
   Li JJ, 2017, AGR FOREST METEOROL, V247, P260, DOI 10.1016/j.agrformet.2017.08.005
   Li Z, 2009, J HYDROL, V377, P35, DOI 10.1016/j.jhydrol.2009.08.007
   Liang YJ, 2021, J MT SCI-ENGL, V18, P683, DOI 10.1007/s11629-019-5846-4
   Liang YJ, 2021, ECOL INDIC, V120, DOI 10.1016/j.ecolind.2020.106939
   Liang YJ, 2017, ECOSYST HEALTH SUST, V3, DOI 10.1080/20964129.2017.1335933
   Liang YJ, 2017, J LAND USE SCI, V12, P154, DOI [10.1080/1747423X.2017.1308024, 10.1080/1747423x.2017.1308024]
   Liu JY, 2014, J GEOGR SCI, V24, P195, DOI 10.1007/s11442-014-1082-6
   Liu LJ, 2021, J CLEAN PROD, V293, DOI 10.1016/j.jclepro.2021.125991
   Lufafa A, 2003, AGR SYST, V76, P883, DOI 10.1016/S0308-521X(02)00012-4
   NDRC, 2010, OUTLINE COMPREHENSIV
   Pandey S, 2021, INT SOIL WATER CONSE, V9, P305, DOI 10.1016/j.iswcr.2021.03.001
   Patel S, 2024, BUILD ENVIRON, V249, DOI 10.1016/j.buildenv.2023.111130
   Raupach MR, 2014, NAT CLIM CHANGE, V4, P873, DOI 10.1038/NCLIMATE2384
   Reader MO, 2024, ECOSYST SERV, V66, DOI 10.1016/j.ecoser.2023.101593
   Sahle M, 2019, SUSTAIN SCI, V14, P175, DOI 10.1007/s11625-018-0585-y
   Santos MJ, 2021, LANDSCAPE ECOL, V36, P3367, DOI 10.1007/s10980-021-01276-w
   Sharp R., 2015, InVEST 3.2.0 User's Guide
   Sibanda S, 2021, MODEL EARTH SYST ENV, V7, P57, DOI 10.1007/s40808-020-00963-y
   Song W, 2017, SCI TOTAL ENVIRON, V576, P705, DOI 10.1016/j.scitotenv.2016.07.078
   Summers JK, 2012, AMBIO, V41, P327, DOI 10.1007/s13280-012-0256-7
   Sun DZ, 2022, J ARID LAND, V14, P390, DOI 10.1007/s40333-022-0054-4
   [孙定钊 Sun Dingzhao], 2021, [地球信息科学学报, Journal of Geo-Information Science], V23, P825
   [唐夫凯 Tang Fukai], 2016, [自然资源学报, Journal of Natural Resources], V31, P1429
   Wang B, 2022, LAND USE POLICY, V122, DOI 10.1016/j.landusepol.2022.106395
   Wang D, 2022, ECOSYST HEALTH SUST, V8, DOI 10.1080/20964129.2022.2130093
   Wang LL, 2021, SCI TOTAL ENVIRON, V768, DOI 10.1016/j.scitotenv.2021.145280
   WISCHMEIER WH, 1976, J SOIL WATER CONSERV, V31, P5
   Yang Y, 2024, J CLEAN PROD, V452, DOI 10.1016/j.jclepro.2024.142077
   Zhang JH., 2000, Journal of Natural Resource, V15, P170
   [赵文武 Zhao Wenwu], 2018, [地理科学进展, Progress in Geography], V37, P139
NR 51
TC 0
Z9 0
U1 7
U2 7
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0343-2521
EI 1572-9893
J9 GEOJOURNAL
JI GeoJournal
PD AUG 26
PY 2024
VL 89
IS 5
AR 195
DI 10.1007/s10708-024-11201-8
PG 16
WC Geography
WE Emerging Sources Citation Index (ESCI)
SC Geography
GA D7G6P
UT WOS:001297833800001
DA 2025-01-10
ER

PT J
AU McLeman, R
AF McLeman, Robert
TI Thresholds in climate migration
SO POPULATION AND ENVIRONMENT
LA English
DT Article
DE Climate migration; Climate adaptation; Threshold; Tipping point;
   Non-linear behavior; Migration dynamics; Residential preference; Risk
   perception
ID RURAL EASTERN OKLAHOMA; ENVIRONMENTAL-CHANGE; POTENTIAL ROLE;
   ADAPTATION; 1930S; PERCEPTIONS; DYNAMICS; INSIGHTS; FUTURES; CONTEXT
AB Migration in response to climatic hazards or changes in climatic conditions can unfold in a variety of ways, ranging from barely observable, incremental changes in pre-existing migration flows to abrupt, non-linear population movements. The adoption of migration instead of in situ adaptation responses, and the high degree of variability in potential migration outcomes, in part reflects the presence of thresholds or tipping points within the processes of human-environment interaction through which climate adaptation and migration take place. This article reviews and makes linkages between existing research in climate adaptation, migration system dynamics, residential preferences, and risk perception to identify and explore the functioning and importance of thresholds. Parochial examples from the author's published research on climate adaptation and migration in rural North America are used to illustrate. Six types of thresholds in response to climate hazards are identified: (1) Adaptation becomes necessary; (2) Adaptation becomes ineffective; (3) Substantive changes in land use/livelihoods become necessary; (4) In situ adaptation fails, migration ensues; (5) Migration rates become non-linear; and (6) Migration rates cease to be non-linear. Movement across thresholds is driven by context-specific characteristics of climate events, natural systems, and/or human systems. Transition from incremental to non-linear migration can be accelerated by people's perceptions, by actions of influential individuals or groups, and by changes in key infrastructure, services, or other community assets. Non-linear climate migration events already occur at local and sub-regional scales. The potential for global scale, non-linear population movements later this century depends heavily on future greenhouse gas emission trends. The ability to identify and avoid thresholds that tip climate migration into a non-linear state will be of growing concern to policy makers and planners at all levels in coming decades. This article forms part of a special issue of this journal dedicated to the late Graeme Hugo, and the author draws heavily on past research by Professor Hugo and colleagues.
C1 [McLeman, Robert] Wilfrid Laurier Univ, Dept Geog & Environm Studies, 75 Univ Ave W, Waterloo, ON N2L 3C5, Canada.
C3 Wilfrid Laurier University
RP McLeman, R (corresponding author), Wilfrid Laurier Univ, Dept Geog & Environm Studies, 75 Univ Ave W, Waterloo, ON N2L 3C5, Canada.
EM rmcleman@wlu.ca
OI McLeman, Robert/0000-0001-9593-1606
CR ADB, 2012, Addressing climate change and migration in Asia and the Pacifc, P23
   Adger WN, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P1, DOI 10.1017/CBO9780511596667.002
   Ahamad MG., 2011, MOD EC, V2, P174, DOI [10.4236/me.2011.22023, DOI 10.4236/ME.2011.22023]
   [Anonymous], DISENTANGLING MIGRAT
   [Anonymous], 2011, Final Project Report
   [Anonymous], 2020, The Age of Migration. International Population Movements in the Modern World
   [Anonymous], POPULATION TRENDS OK
   [Anonymous], 1978, Micromotives and Macrobehavior
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Bardsley DK, 2010, POPUL ENVIRON, V32, P238, DOI 10.1007/s11111-010-0126-9
   Behringer Wolfgang, 2010, A Cultural History of Climate
   Birkmann J, 2010, SUSTAIN SCI, V5, P171, DOI 10.1007/s11625-010-0108-y
   Black R, 2013, ENVIRON SCI POLICY, V27, pS32, DOI 10.1016/j.envsci.2012.09.001
   Black R, 2011, GLOBAL ENVIRON CHANG, V21, pS3, DOI 10.1016/j.gloenvcha.2011.10.001
   Black R, 2011, NATURE, V478, P447, DOI 10.1038/478477a
   Carson M, 2016, CLIMATIC CHANGE, V134, P269, DOI 10.1007/s10584-015-1520-1
   de Haas H, 2010, J ETHN MIGR STUD, V36, P1587, DOI 10.1080/1369183X.2010.489361
   de Sherbinin A, 2014, CLIMATIC CHANGE, V123, P23, DOI 10.1007/s10584-013-0900-7
   DeConto RM, 2016, NATURE, V531, P591, DOI 10.1038/nature17145
   DeWaard J, 2016, POPUL ENVIRON, V37, P449, DOI 10.1007/s11111-015-0250-7
   Dieng HB, 2017, GEOPHYS RES LETT, V44, P3744, DOI 10.1002/2017GL073308
   Epstein GS, 2008, J ETHN MIGR STUD, V34, P567, DOI 10.1080/13691830801961597
   FAWCETT JT, 1989, INT MIGR REV, V23, P671, DOI 10.2307/2546434
   Füssel HM, 2007, SUSTAIN SCI, V2, P265, DOI 10.1007/s11625-007-0032-y
   Fussell E, 2010, POPUL ENVIRON, V31, P20, DOI 10.1007/s11111-009-0092-2
   Garschagen M, 2015, CLIMATIC CHANGE, V133, P37, DOI 10.1007/s10584-013-0812-6
   Gilbert G, 2010, POPUL ENVIRON, V32, P3, DOI 10.1007/s11111-010-0112-2
   Gladwell M., 2000, TIPPING POINT LITTLE
   GRANOVETTER M, 1978, AM J SOCIOL, V83, P1420, DOI 10.1086/226707
   Gray CL, 2012, P NATL ACAD SCI USA, V109, P6000, DOI 10.1073/pnas.1115944109
   Gregory JamesN., 1989, American Exodus: The Dust Bowl Migration and Okie Culture in California
   Grodzins M., 1958, METROPOLITAN AREA RA
   Gunderson LH, 2000, ANNU REV ECOL SYST, V31, P425, DOI 10.1146/annurev.ecolsys.31.1.425
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Hugo G, 1998, Asian Pac Migr J, V7, P1
   Hugo G, 1996, INT MIGR REV, V30, P105, DOI 10.2307/2547462
   Hugo G., 2008, MIGRATION DEV ENV GE
   Hugo G., 2009, CLIMATE CHANGE UNPUB
   Hugo G, 2014, GLOB MIGRAT ISS, V2, P21, DOI 10.1007/978-94-007-6985-4_2
   Hugo G, 2011, GLOBAL ENVIRON CHANG, V21, pS21, DOI 10.1016/j.gloenvcha.2011.09.008
   Hugo Graeme., 2005, ASIAN POPUL STUD, V1, P93, DOI [DOI 10.1080/17441730500125953, 10.1080/17441730500125953]
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jordan A, 2013, CLIM POLICY, V13, P751, DOI 10.1080/14693062.2013.835705
   Keizer PS, 2015, REV PALAEOBOT PALYNO, V219, P106, DOI 10.1016/j.revpalbo.2015.04.001
   Khandker SR, 2012, J DEV STUD, V48, P1063, DOI 10.1080/00220388.2011.561325
   Kiem AS, 2013, GLOBAL ENVIRON CHANG, V23, P1307, DOI 10.1016/j.gloenvcha.2013.06.003
   King R, 2010, J ETHN MIGR STUD, V36, P1619, DOI 10.1080/1369183X.2010.489380
   Kniveton D, 2011, GLOBAL ENVIRON CHANG, V21, pS34, DOI 10.1016/j.gloenvcha.2011.09.006
   Koubi V, 2016, POPUL ENVIRON, V38, P134, DOI 10.1007/s11111-016-0258-7
   Laforge JML, 2013, CAN GEOGR-GEOGR CAN, V57, P488, DOI 10.1111/j.1541-0064.2013.12045.x
   Lamb H.H., 2002, CLIMATE HIST MODERN
   Lee TM, 2015, NAT CLIM CHANGE, V5, P1014, DOI 10.1038/NCLIMATE2728
   MABOGUNJE AL, 1970, GEOGR ANAL, V2, P1, DOI 10.1111/j.1538-4632.1970.tb00140.x
   Mallick B, 2012, INT DEV PLANN REV, V34, P217, DOI 10.3828/idpr.2012.16
   MASSEY DS, 1990, POPUL INDEX, V56, P3, DOI 10.2307/3644186
   Massey DS, 1997, AM J SOCIOL, V102, P939, DOI 10.1086/231037
   McLeman R, 2006, CLIMATIC CHANGE, V76, P31, DOI 10.1007/s10584-005-9000-7
   McLeman R, 2006, GREAT PLAINS QUART, V26, P27
   McLeman RA, 2014, CLIMATE AND HUMAN MIGRATION: PAST EXPERIENCES, FUTURE CHALLENGES, P1
   McLeman R, 2008, MITIG ADAPT STRAT GL, V13, P379, DOI 10.1007/s11027-007-9118-1
   McLeman R, 2010, POPUL ENVIRON, V31, P286, DOI 10.1007/s11111-009-0087-z
   McLeman R, 2010, J HIST GEOGR, V36, P43, DOI 10.1016/j.jhg.2009.04.003
   McLeman RA, 2012, POPUL ENVIRON, V33, P304, DOI 10.1007/s11111-011-0148-y
   McLeman RA, 2011, GLOBAL ENVIRON CHANG, V21, pS108, DOI 10.1016/j.gloenvcha.2011.08.004
   McLeman RA, 2011, ADV GLOB CHANGE RES, V42, P449, DOI 10.1007/978-94-007-0567-8_33
   Meze-Hausken E, 2008, CLIMATIC CHANGE, V89, P299, DOI 10.1007/s10584-007-9392-7
   Morris SS, 2003, WORLD DEV, V31, P1279, DOI 10.1016/S0305-750X(03)00072-X
   Mortreux C, 2009, GLOBAL ENVIRON CHANG, V19, P105, DOI 10.1016/j.gloenvcha.2008.09.006
   Murphy C, 2017, WEATHER, V72, P151, DOI 10.1002/wea.2904
   Nawrotzki RJ, 2017, CLIMATIC CHANGE, V140, P243, DOI 10.1007/s10584-016-1849-0
   Nawrotzkil RJ, 2016, POPUL ENVIRON, V38, P72, DOI 10.1007/s11111-016-0255-x
   Nelson R, 2010, ENVIRON SCI POLICY, V13, P8, DOI 10.1016/j.envsci.2009.09.006
   Pandolfi JM, 2011, SCIENCE, V333, P418, DOI 10.1126/science.1204794
   Preston BL, 2013, SUSTAINABILITY-BASEL, V5, P1011, DOI 10.3390/su5031011
   Romero-Lankao P, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1439
   Saha SK, 2017, DISASTERS, V41, P505, DOI 10.1111/disa.12214
   Sander-Regier R., 2010, Environments, V37, P35
   Schade J., 2015, ENV MIGRATION SOCIAL, P203
   Semenza JC, 2008, AM J PREV MED, V35, P479, DOI 10.1016/j.amepre.2008.08.020
   Shen S, 2011, INT MIGR, V49, pe224, DOI 10.1111/j.1468-2435.2010.00635.x
   Smit B., 2002, Mitigation and Adaptation Strategies for Global Change, V7, P85, DOI 10.1023/A:1015862228270
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smith CD, 2014, CLIM DEV, V6, P77, DOI 10.1080/17565529.2013.872593
   SPEARE A, 1974, DEMOGRAPHY, V11, P173, DOI 10.2307/2060556
   STARK O, 1985, AM ECON REV, V75, P173
   Tacoli C, 2009, ENVIRON URBAN, V21, P513, DOI 10.1177/0956247809342182
   van Aalst MK, 2008, GLOBAL ENVIRON CHANG, V18, P165, DOI 10.1016/j.gloenvcha.2007.06.002
   Warner K, 2014, CLIM DEV, V6, P1, DOI 10.1080/17565529.2013.835707
   Weber EU, 2010, WIRES CLIM CHANGE, V1, P332, DOI 10.1002/wcc.41
   WOLPERT J, 1966, J SOC ISSUES, V22, P92, DOI 10.1111/j.1540-4560.1966.tb00552.x
NR 90
TC 99
Z9 105
U1 3
U2 75
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0199-0039
EI 1573-7810
J9 POPUL ENVIRON
JI Popul. Env.
PD JUN
PY 2018
VL 39
IS 4
SI SI
BP 319
EP 338
DI 10.1007/s11111-017-0290-2
PG 20
WC Demography; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Demography; Environmental Sciences & Ecology
GA GJ1HP
UT WOS:000435006000003
DA 2025-01-10
ER

PT J
AU Klopfer, F
AF Klopfer, Florian
TI The thermal performance of urban form-An analysis on urban structure
   types in Berlin
SO APPLIED GEOGRAPHY
LA English
DT Article
DE Climate adaptation; Geographically weighted regression (GWR); Land
   surface temperature (LST); Urban form; Urban heat island (UHI); Urban
   structure types (USTs)
ID LAND-SURFACE TEMPERATURE; HEAT-ISLAND; CITY; CITIES; WAVE
AB Increasing urban heat issues induced by climatic changes and growing urban populations exacerbate the need for adaptation. The present study intends to foster the so far quite rarely realized transfer from research to real-world planning. Subject of investigation is the thermal performance and characterization of urban structure types (USTs) in Berlin, Germany. Applying Landsat 8 derived land surface temperatures (LSTs), we first determine differences in the temperature patterns of the regarded USTs. Second, after running correlation analyses with LST and potentially influencing factors (NDVI - normalized difference vegetation index, imperviousness, building ratio, and building height), we fit ordinary least square (OLS) and geographically weighted regression (GWR) models. Finally, we relate the GWR results to the USTs and determine the effect of each variable on the respective LST regime. We find significant differences in the thermal performance of USTs, strong correlations between explaining variables and LST, and a sophisticated picture concerning GWR coefficients at various locations. Quasi-global r2 for the GWR (0.83) improves the OLS model value (0.53) considerably. The spatially explicit GWR method in combination with results aggregated on the planning-relevant UST-level provides crucially important information for climate adaptation and planning while being adaptable and transferable to other urban areas.
C1 [Klopfer, Florian] TU Dortmund Univ, Dept Spatial Planning, August Schmidt Str 10, D-44227 Dortmund, Germany.
C3 Dortmund University of Technology
RP Klopfer, F (corresponding author), TU Dortmund Univ, Dept Spatial Planning, August Schmidt Str 10, D-44227 Dortmund, Germany.
EM florian.klopfer@tu-dortmund.de
OI Klopfer, Florian/0000-0001-7386-5492
CR Agathangelidis I, 2020, CLIMATE, V8, DOI 10.3390/cli8110131
   Alhawiti R.H., 2016, International Journal of Research in Engineering and Technology, V5, P457, DOI [10.15623/ijret.2016.0503083, DOI 10.15623/IJRET.2016.0503083]
   Avdan U, 2016, J SENSORS, V2016, DOI 10.1155/2016/1480307
   Bechtel B, 2019, URBAN CLIM, V28, DOI 10.1016/j.uclim.2019.01.005
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Chakraborty T, 2020, ISPRS J PHOTOGRAMM, V168, P74, DOI 10.1016/j.isprsjprs.2020.07.021
   Chen MX, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213491
   COHEN J, 1992, PSYCHOL BULL, V112, P155, DOI 10.1037/0033-2909.112.1.155
   Cohen J., 1988, STAT POWER ANAL BEHA
   Comber A, 2023, GEOGR ANAL, V55, P155, DOI 10.1111/gean.12316
   Debbage N, 2015, COMPUT ENVIRON URBAN, V54, P181, DOI 10.1016/j.compenvurbsys.2015.08.002
   Demuzere M., 2021, EUROPEAN LCZ MAP, DOI [10.6084/m9.figshare.13322450, DOI 10.6084/M9.FIGSHARE.13322450]
   Dialesandro J, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18030941
   dwd, 2022, HOT DAYS
   Echenique MH, 2012, J AM PLANN ASSOC, V78, P121, DOI 10.1080/01944363.2012.666731
   EEA, 2018, IMP DENS IMD
   Esri, 2016, ARCMAP 10 4
   Fotheringham A., 2002, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
   Franck U, 2013, METEOROL Z, V22, P167, DOI 10.1127/0941-2948/2013/0384
   Gabriel KMA, 2011, ENVIRON POLLUT, V159, P2044, DOI 10.1016/j.envpol.2011.01.016
   Gao YJ, 2022, BUILD ENVIRON, V216, DOI 10.1016/j.buildenv.2022.109037
   Georgescu M, 2013, NAT CLIM CHANGE, V3, P37, DOI 10.1038/nclimate1656
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Heldens W., 2013, Thermal infrared remote sensing - sensors, methods, applications, P475, DOI [DOI 10.1007/978-94-007, 10.1007/978-94-007-6639-6_23]
   Hoffman JS, 2020, CLIMATE, V8, DOI 10.3390/cli8010012
   Hsu A, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22799-5
   Imhoff ML, 2010, REMOTE SENS ENVIRON, V114, P504, DOI 10.1016/j.rse.2009.10.008
   IPCC, 2022, FULL REP 3 MIT CLIM
   IPCC, 2022, FULL REP 2 IMP AD VU
   Jin H, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10010206
   Jusuf SK, 2007, HABITAT INT, V31, P232, DOI 10.1016/j.habitatint.2007.02.006
   Kaplan G., 2018, Proceedings, V2, P358, DOI [DOI 10.3390/ECRS-2-05171, 10.3390/ecrs-2-05171]
   Kazmierczak A., 2016, CLIMATE CHANGE MANAG, P43, DOI [10.1007/978-3-319-25814-0_4, DOI 10.1007/978-3-319-25814-0_4]
   Kim JP, 2014, ENVIRON PLANN B, V41, P1077, DOI 10.1068/b130091p
   Larondelle N, 2014, APPL GEOGR, V53, P427, DOI 10.1016/j.apgeog.2014.07.004
   Lehnert M, 2021, ISPRS INT J GEO-INF, V10, DOI 10.3390/ijgi10040260
   Li YF, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-16461-9
   Liang Z, 2020, SCI TOTAL ENVIRON, V708, DOI 10.1016/j.scitotenv.2019.135011
   Lu YP, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18199987
   Marshall JD, 2008, ENVIRON SCI TECHNOL, V42, P3133, DOI 10.1021/es087047l
   Masson-Delmotte V., 2021, Climate Change 2021: the physical science basis, P3
   Mitchell BC, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18094800
   Morabito M, 2016, SCI TOTAL ENVIRON, V551, P317, DOI 10.1016/j.scitotenv.2016.02.029
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   OKE TR, 1973, ATMOS ENVIRON, V7, P769, DOI 10.1016/0004-6981(73)90140-6
   OKE TR, 1988, ENERG BUILDINGS, V11, P103, DOI 10.1016/0378-7788(88)90026-6
   Oliveira A, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100631
   Oliveira V, 2016, URBAN BOOK SERIES, P1, DOI 10.1007/978-3-319-32083-0
   Ord JK, 2012, ANN REGIONAL SCI, V48, P529, DOI 10.1007/s00168-011-0492-y
   Osberghaus D, 2022, GLOBAL ENVIRON CHANG, V72, DOI 10.1016/j.gloenvcha.2021.102446
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Pramanik S, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103808
   RStudio Team, 2021, RSTUDIO COMP SOFTW
   Schwarz N, 2015, J URBAN PLAN DEV, V141, DOI 10.1061/(ASCE)UP.1943-5444.0000263
   Senatsverwaltung fur Stadtentwicklung, 2022, BAUEN WOHN UMW BERL
   Senatsverwaltung fur Stadtentwicklung, 2021, BAUEN WOHN FLACH STA
   Senatsverwaltung fur Stadtentwicklung Bauen und Wohnen, 2022, UMW BERL GEB DL DE B
   Shandas V, 2020, SPRINGERBR ENV SCI, P93, DOI 10.1007/978-3-030-26586-1_7
   Shandas V, 2019, CLIMATE, V7, DOI 10.3390/cli7010005
   Sida J., 2021, MAPPING LOCAL CLIMAT, DOI [10.31219/osf.io/c2bez, DOI 10.31219/OSF.IO/C2BEZ]
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Stone B, 2010, ENVIRON HEALTH PERSP, V118, P1425, DOI 10.1289/ehp.0901879
   UNDESA, 2018, World Urbanization Prospects: The 2018 Revision
   Unger J, 2004, CLIM RES, V27, P253, DOI 10.3354/cr027253
   USGS, 2022, LANDS NORM DIFF VEG
   USGS, 2022, LANDS 8 OLI TIRS C2
   Vandentorren S, 2006, EUR J PUBLIC HEALTH, V16, P583, DOI 10.1093/eurpub/ckl063
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wende W., 2014, PUBLIKATIONSREIHE BM, V6
   Wendnagel-Beck A, 2021, URBAN PLAN, V6, P321, DOI 10.17645/up.v6i4.4515
   Westerholt R., 2021, EXPLORING CHARACTERI, DOI [10.5281/zenodo.4665575, DOI 10.5281/ZENODO.4665575]
   Wickop E., 1999, Z ANGEW UMWELTFORSCH, V12, P98
   Yin CH, 2018, SCI TOTAL ENVIRON, V634, P696, DOI 10.1016/j.scitotenv.2018.03.350
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Yuan F, 2007, REMOTE SENS ENVIRON, V106, P375, DOI 10.1016/j.rse.2006.09.003
   Zhang X, 2009, INT J REMOTE SENS, V30, P2105, DOI 10.1080/01431160802549252
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
   Zuvela-Aloise M, 2016, CLIMATIC CHANGE, V135, P425, DOI 10.1007/s10584-016-1596-2
NR 78
TC 9
Z9 9
U1 6
U2 30
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0143-6228
EI 1873-7730
J9 APPL GEOGR
JI Appl. Geogr.
PD MAR
PY 2023
VL 152
AR 102890
DI 10.1016/j.apgeog.2023.102890
EA FEB 2023
PG 11
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA M3SB0
UT WOS:001029405600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Gallegos, C
   Hodgins, KA
   Monro, K
AF Gallegos, Cristobal
   Hodgins, Kathryn A.
   Monro, Keyne
TI Climate adaptation and vulnerability of foundation species in a global
   change hotspot
SO MOLECULAR ECOLOGY
LA English
DT Article
DE climate change; genetic offset; genomic vulnerability;
   genotype-environment association; seascape genomics; thermal adaptation
ID LOCAL ADAPTATION; GENE FLOW; AUSTRALIAN MARINE; IN-SITU; EVOLUTION;
   SELECTION; GENOMICS; TEMPERATURE; PACKAGE; LIMITS
AB Climate change is altering species ranges, and relative abundances within ranges, as populations become differentially adapted and vulnerable to the climates they face. Understanding present species ranges, whether species harbour and exchange adaptive variants, and how variants are distributed across landscapes undergoing rapid change, is therefore crucial to predicting responses to future climates and informing conservation strategies. Such insights are nonetheless lacking for most species of conservation concern. We assess genomic patterns of neutral variation, climate adaptation and climate vulnerability (offsets in predicted distributions of putatively adaptive variants across present and future landscapes) for sister foundation species, the marine tubeworms Galeolaria caespitosa and Galeolaria gemineoa, in a sentinel region for climate change impacts. We find that species are genetically isolated despite uncovering sympatry in their ranges, show parallel and nonparallel signals of thermal adaptation on spatial scales smaller than gene flow across their ranges, and are predicted to face different risks of maladaptation under future temperatures across their ranges. Our findings have implications for understanding local adaptation in the face of gene flow, and generate spatially explicit predictions for climatic disruption of adaptation and species distributions in coastal ecosystems that could guide experimental validation and conservation planning.
C1 [Gallegos, Cristobal; Hodgins, Kathryn A.; Monro, Keyne] Monash Univ, Sch Biol Sci, Melbourne, Vic, Australia.
C3 Monash University
RP Gallegos, C (corresponding author), Monash Univ, Sch Biol Sci, Melbourne, Vic, Australia.
EM cris.gallegossanchez@monash.edu
RI Monro, Keyne/J-7418-2019
OI Gallegos, Cristobal/0000-0002-0454-0552
FU Australian Research Council; Holsworth Wildlife Research Endowment
FX Australian Research Council; Holsworth Wildlife Research Endowment
CR Adam AAS, 2022, MOL ECOL, V31, P3533, DOI 10.1111/mec.16498
   Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   Andrews KR, 2016, NAT REV GENET, V17, P81, DOI 10.1038/nrg.2015.28
   [Anonymous], 2006, DNeasy Blood and Tissue Handbook
   Ardura A, 2017, SCI REP-UK, V7, DOI 10.1038/srep42193
   Assis J, 2018, GLOBAL ECOL BIOGEOGR, V27, P277, DOI 10.1111/geb.12693
   Barrett RDH, 2008, TRENDS ECOL EVOL, V23, P38, DOI 10.1016/j.tree.2007.09.008
   Bay RA, 2018, SCIENCE, V359, P83, DOI 10.1126/science.aan4380
   Bitter MC, 2021, P ROY SOC B-BIOL SCI, V288, DOI 10.1098/rspb.2021.0727
   Bitter MC, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-13767-1
   Blount ZD, 2018, SCIENCE, V362, DOI 10.1126/science.aam5979
   Borrell JS, 2020, EVOL APPL, V13, P161, DOI 10.1111/eva.12883
   Capblancq T, 2020, ANNU REV ECOL EVOL S, V51, P245, DOI 10.1146/annurev-ecolsys-020720-042553
   Catchen J, 2013, MOL ECOL, V22, P3124, DOI 10.1111/mec.12354
   Catchen JM, 2011, G3-GENES GENOM GENET, V1, P171, DOI 10.1534/g3.111.000240
   Charlesworth B, 1997, GENET RES, V70, P155, DOI 10.1017/S0016672397002954
   Chirgwin E, 2021, EVOL LETT, V5, P154, DOI 10.1002/evl3.215
   Chirgwin E, 2020, FUNCT ECOL, V34, P646, DOI 10.1111/1365-2435.13483
   Cole V. J., 2017, Australian Zoologist, V39, P194, DOI 10.7882/AZ.2015.034
   Dahlke FT, 2020, SCIENCE, V369, P65, DOI 10.1126/science.aaz3658
   Dawson MN, 2005, J BIOGEOGR, V32, P515, DOI 10.1111/j.1365-2699.2004.01193.x
   Dent R, 2012, PLOS ONE, V7, DOI [10.1371/journal.pone.0037135, 10.1371/journal.pone.0036889]
   Eckert CG, 2008, MOL ECOL, V17, P1170, DOI 10.1111/j.1365-294X.2007.03659.x
   Ellis N, 2012, ECOLOGY, V93, P156, DOI 10.1890/11-0252.1
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Fierst JL, 2010, EVOLUTION, V64, P675, DOI 10.1111/j.1558-5646.2009.00861.x
   Fischer EM, 2015, NAT CLIM CHANGE, V5, P560, DOI 10.1038/nclimate2617
   Fitzpatrick MC, 2021, MOL ECOL RESOUR, V21, P2749, DOI 10.1111/1755-0998.13374
   Fitzpatrick MC, 2015, ECOL LETT, V18, P1, DOI 10.1111/ele.12376
   Fitzpatrick SW, 2020, CURR BIOL, V30, P517, DOI 10.1016/j.cub.2019.11.062
   Foden WB, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.551
   Forester BR, 2016, MOL ECOL, V25, P104, DOI 10.1111/mec.13476
   Frankham R, 2015, MOL ECOL, V24, P2610, DOI 10.1111/mec.13139
   Gallegos C., 2022, CLIMATE ADAPTATION V
   Galpern P, 2014, METHODS ECOL EVOL, V5, P1116, DOI 10.1111/2041-210X.12240
   GarciaRamos G, 1997, EVOLUTION, V51, P21, DOI [10.2307/2410956, 10.1111/j.1558-5646.1997.tb02384.x]
   Gautier M, 2015, GENETICS, V201, P1555, DOI 10.1534/genetics.115.181453
   Gaylord B, 2000, AM NAT, V155, P769, DOI 10.1086/303357
   Goudet J, 2005, MOL ECOL NOTES, V5, P184, DOI 10.1111/j.1471-8286.2004.00828.x
   Grant PR, 2019, P NATL ACAD SCI USA, V116, P23216, DOI 10.1073/pnas.1913534116
   Grummer JA, 2019, TRENDS ECOL EVOL, V34, P641, DOI 10.1016/j.tree.2019.02.013
   Haldane JBS, 1930, J GENET, V22, P359, DOI 10.1007/BF02984197
   Halt MN, 2009, INVERTEBR SYST, V23, P205, DOI 10.1071/IS09003
   Hartke J, 2021, J EVOLUTION BIOL, V34, P937, DOI 10.1111/jeb.13742
   Hijmans, 2022, RASTER GEOGRAPHIC DA
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hoban S, 2016, AM NAT, V188, P379, DOI 10.1086/688018
   Hobday AJ, 2014, REV FISH BIOL FISHER, V24, P415, DOI 10.1007/s11160-013-9326-6
   Hobday AJ, 2011, MAR FRESHWATER RES, V62, P1000, DOI 10.1071/MF10302
   Hoffmann AA, 2021, CELL, V184, P1420, DOI 10.1016/j.cell.2021.02.006
   Hoffmann AA, 2011, NATURE, V470, P479, DOI 10.1038/nature09670
   Hohenlohe PA, 2021, MOL ECOL, V30, P62, DOI 10.1111/mec.15720
   Howard DJ, 1999, ANNU REV ECOL SYST, V30, P109, DOI 10.1146/annurev.ecolsys.30.1.109
   Ingvarsson PK, 2020, EVOL APPL, V13, P132, DOI 10.1111/eva.12792
   Jia KH, 2020, EVOL APPL, V13, P665, DOI 10.1111/eva.12891
   Jombart T, 2008, BIOINFORMATICS, V24, P1403, DOI 10.1093/bioinformatics/btn129
   Kardos M, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2104642118
   Kingsolver JG, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0147
   Knaus BJ, 2017, MOL ECOL RESOUR, V17, P44, DOI 10.1111/1755-0998.12549
   Lande R, 2014, J EVOLUTION BIOL, V27, P866, DOI 10.1111/jeb.12360
   Láruson AJ, 2022, EVOL APPL, V15, P403, DOI 10.1111/eva.13354
   Lathlean JA, 2011, MAR ECOL PROG SER, V439, P83, DOI 10.3354/meps09317
   Lee KM, 2017, GENETICS, V207, P1591, DOI 10.1534/genetics.117.300417
   Legendre P, 2010, MOL ECOL RESOUR, V10, P831, DOI 10.1111/j.1755-0998.2010.02866.x
   Lenormand T, 2002, TRENDS ECOL EVOL, V17, P183, DOI 10.1016/S0169-5347(02)02497-7
   Lenormand T., 2016, CHANCE IN EVOLUTION, P96, DOI DOI 10.7208/CHICAGO/9780226401911.003.0009
   Liggins L., 2020, Population Genomics: Marine Organisms, P171
   Lotterhos KE, 2021, P ROY SOC B-BIOL SCI, V288, DOI 10.1098/rspb.2021.2443
   Lotterhos Katie E., 2010, P99
   Miller AD, 2020, EVOL APPL, V13, P918, DOI 10.1111/eva.12909
   Mitchell N, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-43119-4
   Nazareno AG, 2017, MOL ECOL RESOUR, V17, P1136, DOI 10.1111/1755-0998.12654
   Nielsen ES, 2021, GLOBAL CHANGE BIOL, V27, P3415, DOI 10.1111/gcb.15651
   O'Hara TD, 2000, J BIOGEOGR, V27, P1321, DOI 10.1046/j.1365-2699.2000.00499.x
   Olsen KC, 2020, EVOLUTION, V74, P871, DOI 10.1111/evo.13951
   Paris JR, 2017, METHODS ECOL EVOL, V8, P1360, DOI 10.1111/2041-210X.12775
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Penn JL, 2022, SCIENCE, V376, P524, DOI 10.1126/science.abe9039
   PETRY D, 1983, THEOR POPUL BIOL, V23, P300, DOI 10.1016/0040-5809(83)90020-5
   Pina-Martins F, 2019, GLOBAL CHANGE BIOL, V25, P337, DOI 10.1111/gcb.14497
   Pinsky ML, 2022, SCIENCE, V376, P452, DOI 10.1126/science.abo4259
   Plough LV, 2016, CURR ZOOL, V62, P567, DOI 10.1093/cz/zow096
   Poland JA, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0032253
   Polechová J, 2018, PLOS BIOL, V16, DOI 10.1371/journal.pbio.2005372
   Polechová J, 2015, P NATL ACAD SCI USA, V112, P6401, DOI 10.1073/pnas.1421515112
   Pootakham W, 2016, MOL BREEDING, V36, DOI 10.1007/s11032-016-0572-x
   Pournelle G. H., 1953, Journal of Mammalogy, V34, P133
   Ramírez F, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1601198
   Rautsaw RM, 2021, MOL BIOL EVOL, V38, P745, DOI 10.1093/molbev/msaa266
   Rebolledo AP, 2020, J EXP BIOL, V223, DOI 10.1242/jeb.233254
   Reed DH, 2003, CONSERV BIOL, V17, P230, DOI 10.1046/j.1523-1739.2003.01236.x
   Rellstab C, 2021, EVOL APPL, V14, P1202, DOI 10.1111/eva.13205
   Rellstab C, 2015, MOL ECOL, V24, P4348, DOI 10.1111/mec.13322
   Rescan M, 2021, PLOS GENET, V17, DOI 10.1371/journal.pgen.1009611
   Ridgway KR, 2007, J GEOPHYS RES-OCEANS, V112, DOI 10.1029/2006JC003898
   Ridgway K R., 2009, The East Australian Current
   Riginos C, 2016, CURR ZOOL, V62, P581, DOI 10.1093/cz/zow067
   Ripa J, 1996, P ROY SOC B-BIOL SCI, V263, P1751, DOI 10.1098/rspb.1996.0256
   Rochette NC, 2017, NAT PROTOC, V12, P2640, DOI 10.1038/nprot.2017.123
   Román-Palacios C, 2020, P NATL ACAD SCI USA, V117, P4211, DOI 10.1073/pnas.1913007117
   Ruokolainen L, 2009, TRENDS ECOL EVOL, V24, P555, DOI 10.1016/j.tree.2009.04.009
   Savolainen O, 2013, NAT REV GENET, V14, P807, DOI 10.1038/nrg3522
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Seehausen O, 2014, NAT REV GENET, V15, P176, DOI 10.1038/nrg3644
   Sexton JP, 2009, ANNU REV ECOL EVOL S, V40, P415, DOI 10.1146/annurev.ecolsys.110308.120317
   Sgrò CM, 2011, EVOL APPL, V4, P326, DOI 10.1111/j.1752-4571.2010.00157.x
   Sinervo B, 2003, INTEGR COMP BIOL, V43, P419, DOI 10.1093/icb/43.3.419
   Smith TB, 2014, ANNU REV ECOL EVOL S, V45, P1, DOI 10.1146/annurev-ecolsys-120213-091747
   Stern DL, 2013, NAT REV GENET, V14, P751, DOI 10.1038/nrg3483
   Stobart B, 2016, MAR FRESHWATER RES, V67, P612, DOI 10.1071/MF14340
   STRATHMANN RR, 1990, AM ZOOL, V30, P197
   Styan CA, 2008, EVOLUTION, V62, P3041, DOI 10.1111/j.1558-5646.2008.00521.x
   Sunday JM, 2015, ECOL LETT, V18, P944, DOI 10.1111/ele.12474
   Teixeira JC, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2015096118
   Thomsen MS, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28194-y
   Tigano A, 2016, MOL ECOL, V25, P2144, DOI 10.1111/mec.13606
   Todesco M, 2016, EVOL APPL, V9, P892, DOI 10.1111/eva.12367
   Torrado H, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-69160-2
   Tyberghein L, 2012, GLOBAL ECOL BIOGEOGR, V21, P272, DOI 10.1111/j.1466-8238.2011.00656.x
   Vranken S, 2021, MOL ECOL, V30, P3730, DOI 10.1111/mec.15993
   Waldock C, 2018, BIOSCIENCE, V68, P873, DOI 10.1093/biosci/biy096
   Waters JM, 2008, DIVERS DISTRIB, V14, P692, DOI 10.1111/j.1472-4642.2008.00481.x
   Willi Y, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2105076119
   Wood G, 2021, GLOBAL CHANGE BIOL, V27, P2200, DOI 10.1111/gcb.15534
   Wood TE, 2005, GENETICA, V123, P157, DOI 10.1007/s10709-003-2738-9
   Wright JT, 2017, ECOLOGY, V98, P2425, DOI 10.1002/ecy.1932
   Yeaman S, 2016, SCIENCE, V353, P1431, DOI 10.1126/science.aaf7812
   Yeaman S, 2011, EVOLUTION, V65, P2123, DOI 10.1111/j.1558-5646.2011.01277.x
   Yeaman S, 2011, EVOLUTION, V65, P1897, DOI 10.1111/j.1558-5646.2011.01269.x
NR 129
TC 5
Z9 5
U1 10
U2 60
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0962-1083
EI 1365-294X
J9 MOL ECOL
JI Mol. Ecol.
PD APR
PY 2023
VL 32
IS 8
BP 1990
EP 2004
DI 10.1111/mec.16848
EA JAN 2023
PG 15
WC Biochemistry & Molecular Biology; Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Environmental Sciences & Ecology;
   Evolutionary Biology
GA D4XH2
UT WOS:000919908300001
PM 36645732
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Correia, P
   Barbosa, C
   Simunek, Z
   Muchagata, J
   Sá, AA
AF Correia, Pedro
   Barbosa, Catarina
   Simunek, Zbynek
   Muchagata, Joao
   Sa, Artur A.
TI A new species of <i>Lesleya</i> (Spermatopsida) from the Carboniferous
   of Iberia and its palaeoecological and evolutionary significance
SO HISTORICAL BIOLOGY
LA English
DT Article
DE Herbarium collections; Douro Carboniferous Basin; late Palaeozoic
   climate change; Late Pennsylvanian; dry-climate adapted flora
   ('drought-tolerant flora'); xeromorphic adaptations
ID ILLINOIS BASIN; LEAF SIZE; CLIMATE; VEGETATION; SHAPE
AB Plant adaptations to environmental and climatic changes in Pangaean intramontane basins are poorly understood. Here, we document a previously unknown primitive gymnosperm species, Lesleya ceriacoi sp. nov., from the Douro Carboniferous Basin (DCB; lower Gzhelian, Upper Pennsylvanian; NW Portugal) of the Variscan Iberian Massif (Iberia). This new species is described from a 303 million-years-old fossil rediscovered at the U.Porto's Herbarium PO, stored at the Museu de Historia Natural e da Ciencia da Universidade do Porto (MHNC-UP; Portugal). L. ceriacoi sp. nov. displays an exquisite leaf shape with morphological traits adapted to specific ecological conditions of the DCB. These leaf morphological traits comprise toothed and dissected margins, which represent specialised adaptations to drier (xerophytic) conditions of the DCB during the Gzhelian (ca. 304-299 Ma), at the end of the Late Pennsylvanian. The xeromorphic traits of the new species represent an evolutionary novelty for the Pennsylvanian Euramerican dry-climate adapted floras, and are evidence of evolutionary adaptation to environmental and climatic change in intramontane basins like DCB within central tropical Pangaea. Such an adaptation occurred during an interval of wet to dry climate transition after the end of one late Palaeozoic Gondwana Ice Age (glaciation) in Gzhelian time.
C1 [Correia, Pedro; Sa, Artur A.] Univ Coimbra Polo II, Geosci Ctr, Rua Silvio Lima, P-3030790 Coimbra, Portugal.
   [Barbosa, Catarina] Univ Evora, Dept Geosci, Evora, Portugal.
   [Simunek, Zbynek] Czech Geol Survey, Prague, Czech Republic.
   [Muchagata, Joao] Univ Porto MHNC UP, Museu Hist Nat & Ciencia, Porto, Portugal.
   [Sa, Artur A.] Univ Tras Os Montes & Alto Douro, Dept Geol, Vila Real, Portugal.
C3 Universidade de Coimbra; University of Evora; Czech Geological Survey;
   University of Tras-os-Montes & Alto Douro
RP Correia, P (corresponding author), Univ Coimbra Polo II, Geosci Ctr, Rua Silvio Lima, P-3030790 Coimbra, Portugal.
EM pedro.correia@dct.uc.pt
RI A, Artur/N-7826-2013; Correia, Pedro/LMN-5435-2024
OI Barbosa, Catarina/0000-0003-1179-6553; Correia,
   Pedro/0000-0002-0573-7138
FU Fundacao para a Ciencia e a Tecnologia, I.P. (Portugal)
   [UIDB/00073/2020, UIDP/00073/2020]; Strategic Research Plan of the Czech
   Geological Survey (DKRVO/CGS/2018-2022) [311000]; Fundação para a
   Ciência e a Tecnologia [UIDB/00073/2020, UIDP/00073/2020] Funding
   Source: FCT; European Research Council (ERC) [311000] Funding Source:
   European Research Council (ERC); Academy of Finland (AKA) [311000]
   Funding Source: Academy of Finland (AKA)
FX We thank the MHNC-UP for laboratory support that permitted the fossil
   sample preparation and its photographic documentation. We are also
   grateful to scientific illustrator Vitor Silva for the reconstruction of
   Figure 7, and to J. B. Murphy (St. Francis Xavier University) and C.
   Vila-Vicosa (MHNCUP) for the improvement to the English of the original
   manuscript. Finally, we thank to Mihai Popa (University of Bucharest)
   and to one anonymous reviewer for their constructive comments on the
   submitted manuscript. The authors also would like to thank William A.
   DiMichele (Smithsonian National Museum of Natural History) for his
   useful comments on the systematic and paleoecological issues of the new
   Lesleya species. This study was supported by Portuguese funds by
   Fundacao para a Ciencia e a Tecnologia, I.P. (Portugal) in the frame of
   the UIDB/00073/2020 and UIDP/00073/2020 projects of the I&D unit
   Geosciences Center (CGeo). The research of Z. S. was subsidised by the
   Research Project no. 311000, which is a part of the Strategic Research
   Plan of the Czech Geological Survey (DKRVO/CGS/2018-2022).
CR Alvarez-Ramis C., 1997, P 13 INT C CARB PERM, V1, P207
   Anderson H M., 2008, STRELITZIA, V21, P1
   [Anonymous], 1977, Die floren des erdaltertums
   [Anonymous], 1877, ACAD SCI I FR PARIS
   Ausich WI, 2007, J PALEONTOL, V81, P1374, DOI 10.1666/05-038.1
   Bashforth AR, 2021, GEOBIOS-LYON, V68, P1, DOI 10.1016/j.geobios.2021.04.002
   Bashforth AR, 2016, J PALEONTOL, V90, P785, DOI 10.1017/jpa.2016.25
   Bashforth AR, 2014, REV PALAEOBOT PALYNO, V200, P229, DOI 10.1016/j.revpalbo.2013.09.006
   Cecil CB, 2013, INT J COAL GEOL, V119, P21, DOI 10.1016/j.coal.2013.07.012
   Correia P, 2020, INT J PLANT SCI, V181, P387, DOI 10.1086/707105
   Correia P, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-59461-x
   Correia P, 2018, GEOL J, V53, P2507, DOI 10.1002/gj.3086
   Correia P, 2016, CAN J EARTH SCI, V53, P883, DOI 10.1139/cjes-2015-0213
   Crane PR, 2004, AM J BOT, V91, P1683, DOI 10.3732/ajb.91.10.1683
   de Jesus A.Pinto., 2003, Caderno do Laboratorio Xeoloxico de Laxe Coruna, V28, P107
   De Stefani C., 1901, PUBBLICAZIONI REGION
   Dimichele William A., 2016, Spanish Journal of Palaeontology, V31, P41
   DiMichele WA, 2010, INT J COAL GEOL, V83, P329, DOI 10.1016/j.coal.2010.01.007
   Domingos L.C.G., 1983, The Carboniferous of Portugal, V29, P187
   Doweld A., 2001, Prosyllabus Tracheophylum: Tentamen Systematis Plantarum Vascularium (Tracheophyta), P1
   FARRIS MA, 1984, AM MIDL NAT, V111, P358, DOI 10.2307/2425330
   Fielding CR, 2008, J GEOL SOC LONDON, V165, P129, DOI 10.1144/0016-76492007-036
   FLORIN RUDOLF, 1933, ARKIV BOT [STOCKHOLM], V25 A, P1
   Givnish TJ, 2017, AM J BOT, V104, P354, DOI 10.3732/ajb.1600287
   Grand'Eury CF., 1890, GEOLOGIE PALEONTOLOG
   Guerin GR, 2012, BIOL LETTERS, V8, P882, DOI 10.1098/rsbl.2012.0458
   Isbell JL, 2003, GEOLOGY, V31, P977, DOI 10.1130/G19810.1
   Kenrick P., 1997, ORIGIN EARLY DIVERSI
   Leary R.L., 1993, Comptes Rendus 12e Congres Carbonifere, Buenos Aires, 1993, V2, P107
   Leary R.L., 1985, Illinois State Geological Survey, Guidebook, V18, P1, DOI DOI 10.5962/BHL.TITLE.60739
   Leary R.L., 1998, Palaebotanist, V47, P16, DOI [10.54991/jop.1998.1268, DOI 10.54991/JOP.1998.1268]
   Leary R.L., 1981, Illinois State Museum Reports of Investigations, V37, P1
   LEARY RL, 1980, REV PALAEOBOT PALYNO, V30, P27, DOI 10.1016/0034-6667(80)90004-4
   LEARY RL, 1990, SCIENCE, V249, P1152, DOI 10.1126/science.249.4973.1152
   Leary RL., 1974, EXPLORER, V16, P27
   Leary RL., 1977, 500 ILL STAT GEOL SU
   Lendemer J., 2002, Bartonia, V61, P54
   Lesquereux L., 1879, Second Geological Survey of Pennsylvania, Report of Progress, V1, P1
   Lesquereux L., 1884, 2 GEOLOGICAL SURVEY, V3
   Pinto de Jesus A., 2001, THESIS U PORTO PORTU
   PRICE PW, 1987, ENVIRON ENTOMOL, V16, P15, DOI 10.1093/ee/16.1.15
   Pryer KM, 2004, AM J BOT, V91, P1582, DOI 10.3732/ajb.91.10.1582
   Psenicka J, 2017, REV PALAEOBOT PALYNO, V236, P59, DOI 10.1016/j.revpalbo.2016.09.001
   RAMAN A, 2005, BIOL ECOLOGY EVOLUTI, V1, P1
   Remy W., 1975, Argumenta Palaeobotanica, V4, P1
   Remy W., 1978, Argumenta Palaeobotanica, V5, P195
   Royer DL, 2005, AM J BOT, V92, P1141, DOI 10.3732/ajb.92.7.1141
   Schachat SR, 2014, INT J PLANT SCI, V175, P855, DOI 10.1086/677679
   Schmerler SB, 2012, P ROY SOC B-BIOL SCI, V279, P3905, DOI 10.1098/rspb.2012.1110
   Shute CH., 1996, GEOL CURATOR, V4, P553
   Simu˚nek Z., 1996, Patterns in Paleobotany: Proceedings of a Czech-U.S. Carboniferous Paleobotany Workshop, Springfield, V26, P43
   Smith AS, 2012, ACTA PALAEONTOL POL, V57, P257, DOI 10.4202/app.2011.0023
   Taylor TN, 2009, PALEOBOTANY: THE BIOLOGY AND EVOLUTION OF FOSSIL PLANTS, 2ND EDITION, P1
   Wagner R.H., 1983, The Carboniferous of Portugal, V29, P127
   Wagner R.H., 1983, The Carboniferous of Portugal, V29, P153
   Wagner R.H., 2004, Monografias del Jardin Botanico de Cordoba, V39, P29
   Wagner RH, 1997, REV PALAEOBOT PALYNO, V95, P255, DOI 10.1016/S0034-6667(96)00037-1
   Wagner RH, 2010, REV PALAEOBOT PALYNO, V162, P239, DOI 10.1016/j.revpalbo.2010.06.005
   Watt AD., 1974, PALEOBOTANICAL SECTI
   Willkomm M., 1854, Anleitung zum Studium der wissenschaftlichen Botanik nach den neuesten Forschungen, Band 2
   Xu F, 2009, PROG NAT SCI-MATER, V19, P1789, DOI 10.1016/j.pnsc.2009.10.001
   Xu F, 2008, ACTA BIOL CRACOV BOT, V50, P19
   Zeiller R., 1888, Livre, V2, P1
   Zeiller R., 1906, BASSIN HOUILLER PERM
   Zeiller R., 1890, BASSIN HOUILLER PE 1
NR 65
TC 4
Z9 4
U1 1
U2 3
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 0891-2963
EI 1029-2381
J9 HIST BIOL
JI Hist. Biol.
PD FEB 1
PY 2023
VL 35
IS 2
BP 185
EP 196
DI 10.1080/08912963.2021.2025364
EA JAN 2022
PG 12
WC Biology; Paleontology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Paleontology
GA 8F5MI
UT WOS:000750127700001
DA 2025-01-10
ER

PT J
AU Lomax, J
   Osborne, M
   Aminga, V
   Mirumachi, N
   Johnson, O
AF Lomax, Jake
   Osborne, Matthew
   Aminga, Vane
   Mirumachi, Naho
   Johnson, Oliver
TI Casual pathways in the political economy of climate adaptation: Winners
   and losers in Turkana, Kenya solar mini-grid projects
SO ENERGY RESEARCH & SOCIAL SCIENCE
LA English
DT Article
DE Climate; Adaptation; Energy; Political Economy; Mini-grids; Kenya
ID SOCIAL-ECOLOGICAL SYSTEMS; SUSTAINABILITY; FRAMEWORK
AB International development aid is widely considered essential to support climate adaptation efforts in low-income countries. There has been a rapid increase in the number and geographic range of case studies reporting outcomes of low-carbon development projects, while a limited number of complementary analytical frameworks have also been produced to enable insights to be translated into tangible guidelines and recommendations for policy makers. A particularly important outcome from this body of research has been to demonstrate how poor design and implementation of these projects can create significant negative socio-economic and ecological outcomes at a local level. However, unpicking the causal mechanisms through which these unintended outcomes are created within complex systems remains a challenge. Making use of Sovacool et al.'s (2015) influential 4Es framework and combining it with the 'Mechanisms of Social Change' (MOSC) language for analysing systems, our study aims to provide an approach for setting out casual pathways that explain how the implementation of adaptation projects creates negative as well as positive impacts. To illustrate this approach, we map the system of solar mini-grid projects in northern Kenya and use this to analyse impact on local communities. We suggest that this approach can strengthen analysis of existing climate change programmes and support better design of future adaptation interventions.
C1 [Osborne, Matthew; Johnson, Oliver] Stockholm Environm Inst SEI, Stockholm, Sweden.
   [Aminga, Vane] Swedish Peace Res Inst SIPRI, Solna, Sweden.
   [Mirumachi, Naho] Kings Coll London, London, England.
C3 Stockholm Environment Institute; University of London; King's College
   London
RP Osborne, M (corresponding author), Stockholm Environm Inst SEI, Stockholm, Sweden.
RI Mirumachi, Naho/J-8811-2016
OI Osborne, Matthew/0000-0003-0272-1496; Johnson,
   Oliver/0000-0003-4219-4782
FU Integrering av konfliktanalys i projekt for fornybar energi: mojligheter
   att framja och uppratthalla fred [2017-01941]; Vinnova [2017-01941]
   Funding Source: Vinnova; Formas [2017-01941] Funding Source: Formas;
   Swedish Research Council [2017-01941] Funding Source: Swedish Research
   Council
FX This work was supported by 2017-01941 Integrering av konfliktanalys i
   projekt for fornybar energi: mojligheter att framja och uppratthalla
   fred.
CR Anderies JM, 2004, ECOL SOC, V9
   Barasa M., 2021, PROBLEM KENYAS POWER
   Basurto Xavier., 2009, Beyond the Tragedy of the Commons
   Bebbington A, 1999, WORLD DEV, V27, P2021, DOI 10.1016/S0305-750X(99)00104-7
   Berkes F., 2003, Navigating social and ecological systems: building resilience for complexity and change, DOI DOI 10.1017/CBO9780511541957
   Bhatasara S, 2018, J INTEGR ENVIRON SCI, V15, P87, DOI 10.1080/1943815X.2018.1450766
   Boamah F, 2020, ENERGY RES SOC SCI, V62, DOI 10.1016/j.erss.2019.101390
   Brod en V., 2020, FRAMING RESPONDING C
   Butler JRA, 2017, SOCIAL SCIENCE AND SUSTAINABILITY, P51
   Chu E, 2016, CLIM POLICY, V16, P372, DOI 10.1080/14693062.2015.1019822
   Copestake J, 2014, DEV POLICY REV, V32, P133, DOI 10.1111/dpr.12047
   Donner SD, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/5/054006
   Energy Regulatory Commission (ERC), 2018, UPD LEAST COST POW D
   Forrester J. W., 1961, Industrial dynamics
   Gibson ClarkC., 2005, SAMARITANS DILEMMA P
   Hines P, 1997, INT J OPER PROD MAN, V17, P46, DOI 10.1108/01443579710157989
   Hudson D, 2015, GOV PRACT NOTEB, P67
   Humphrey J., 2014, CREAT COMMONS ATTRIB, V4, P3
   Johnson OW, 2020, ENERGY RES SOC SCI, V70, DOI 10.1016/j.erss.2020.101774
   Johnson OW, 2019, ENERGY RES SOC SCI, V49, P169, DOI 10.1016/j.erss.2018.11.004
   Juhola S, 2016, ENVIRON SCI POLICY, V55, P135, DOI 10.1016/j.envsci.2015.09.014
   Kates RW, 2000, CLIMATIC CHANGE, V45, P5, DOI 10.1023/A:1005672413880
   Keen David., 2008, The Benefits of Famine: A Political Economy of Famine and Relief in Southwestern Sudan, 1983-1989
   Kenya Power, 2021, KEN POW WHO WE AR
   Krumme K., 2016, Renew. Energy Sustain. Dev., V2, P70, DOI DOI 10.21622/RESD.2016.02.2.070
   Leach M, 1999, WORLD DEV, V27, P225, DOI 10.1016/S0305-750X(98)00141-7
   Levin S, 2013, ENVIRON DEV ECON, V18, P111, DOI 10.1017/S1355770X12000460
   Lomax J., 2018, SPRINGF BRIEF PAP
   Lomax Jake, IN PRESS
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Mayring P., 2019, Forum: Qualitative Social Research, V20, P16, DOI DOI 10.17169/FQS-1.2.1089
   McGray H., 2007, Weathering the Storm: Options for Framing Adaptation and Development
   Ministry of Energy, 2018, KEN NAT EL STRAT KNE
   Mirumachi N, 2020, CLIM DEV, V12, P97, DOI 10.1080/17565529.2019.1604310
   Newell P., 2014, IDS Working Paper 445
   Njau K., GEOTHERMAL EXPLORATI
   Ostrom E, 1999, ANNU REV POLIT SCI, V2, P493, DOI 10.1146/annurev.polisci.2.1.493
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Partelow S, 2018, ECOL SOC, V23, DOI [10.5751/ES-10594-230436, 10.5751/es-10594-230436]
   Pawson R., 1997, Realistic evaluation
   Pedersen MB, 2020, ENERGY RES SOC SCI, V68, DOI 10.1016/j.erss.2020.101588
   Pedersen MB, 2018, ENERGY RES SOC SCI, V42, P211, DOI 10.1016/j.erss.2018.03.010
   Porter M., 2011, COMPETITIVE ADVANTAG
   Poteete AR, 2010, WORKING TOGETHER: COLLECTIVE ACTION, THE COMMONS, AND MULTIPLE METHODS IN PRACTICE, P1
   Radosavljevic S, 2021, WORLD DEV, V144, DOI 10.1016/j.worlddev.2021.105437
   Reinholz DL, 2020, INT J STEM EDUC, V7, DOI 10.1186/s40594-020-0202-3
   Samarakoon S, 2020, ENERGY RES SOC SCI, V69, DOI 10.1016/j.erss.2020.101712
   Sartorius R., 1991, AM J EVAL, V12, P139
   Schilling J, 2018, CONFL SECUR DEV, V18, P571, DOI 10.1080/14678802.2018.1532642
   Siciliano G, 2018, ENERGY RES SOC SCI, V41, P199, DOI 10.1016/j.erss.2018.03.029
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Sovacool BK, 2017, ENERG POLICY, V105, P677, DOI 10.1016/j.enpol.2017.03.005
   Sovacool BK, 2015, NAT CLIM CHANGE, V5, P616, DOI 10.1038/nclimate2665
   Springfield Centre, 2015, OP GUID MAK MARK WOR
   Tanner T, 2011, IDS BULL-I DEV STUD, V42, P1, DOI 10.1111/j.1759-5436.2011.00217.x
   ThinkGeo Energy, 2017, TURK GEOTH PROJ KEN
   Tingori Consultancy Limited, 2017, ENV SOCIAL IMPACT AS
   Tomei J, 2020, ENERGY RES SOC SCI, V59, DOI 10.1016/j.erss.2019.101302
   Turkana County Government, 2012, COUNT INT DEV PLAN
   Turkana County Government, 2017, COUNT INT DEV PLAN
   Ulsrud K, 2020, NORSK GEOGR TIDSSKR, V74, P54, DOI 10.1080/00291951.2020.1736145
   Virapongse A, 2016, J ENVIRON MANAGE, V178, P83, DOI 10.1016/j.jenvman.2016.02.028
   Weiss Carol Hirschon, 1995, New Approaches to Evaluating Community Initiatives: Concepts, Methods, and Contexts, P65, DOI DOI 10.1177/1356389003094007
   Weiss CH, 2000, EVALUATION AND POVERTY REDUCTION: PROCEEDINGS FROM A WORLD BANK CONFERENCE, P104
   Winther T, 2018, ENERGY RES SOC SCI, V44, P61, DOI 10.1016/j.erss.2018.04.017
   World Bank, 2021, ACC EL POP KEN
NR 66
TC 2
Z9 2
U1 1
U2 3
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2214-6296
EI 2214-6326
J9 ENERGY RES SOC SCI
JI Energy Res. Soc. Sci.
PD DEC
PY 2021
VL 82
AR 102296
DI 10.1016/j.erss.2021.102296
EA SEP 2021
PG 11
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA WC8JV
UT WOS:000704499200004
OA hybrid
DA 2025-01-10
ER

PT J
AU Rheinheimer, DE
   Null, SE
   Viers, JH
AF Rheinheimer, David E.
   Null, Sarah E.
   Viers, Joshua H.
TI Climate-Adaptive Water Year Typing for Instream Flow Requirements in
   California's Sierra Nevada
SO JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
LA English
DT Article
DE Climate change; Water resources management; Adaptation; Hydropower;
   Environmental flows
ID BIODIVERSITY; MANAGEMENT; VARIABILITY; IMPACTS; DAMS; INFORMATION;
   ADAPTATION; HYDROLOGY; DRIVEN; REGIME
AB Water year types (WYTs), whereby years are classified by river runoff quantity compared to historical runoff, are one tool to help make major water management decisions. Increasingly, these decisions include instream flow requirements (IFRs) below dams for river ecosystem management. However, WYTs are typically based on assumptions of stationarity, and are thus rendered less meaningful with climate change. Hydrologic alteration resulting from climate change means that a WYT-based IFR scheme using stationary historical observations might inadvertently result in long-term river management outcomes inconsistent with original water management goals. This study assesses the management implications of assuming hydrologic nonstationarity in a WYT-based IFR scheme in California's upper Yuba River and demonstrates a rolling period of record as a climate adaptation strategy. The existing, nonadaptive water management scheme leads to vastly different possible water allocation outcomes than originally planned for. Results indicate that water year types, if regularly updated, can help maintain historical instream flow distributions. However, gains toward maintaining desired IFRs are obfuscated by future increases in unmanaged reservoir spill. These findings indicate that hydroclimatic uncertainty can partially be accounted for with simple modifications to existing operating rules for reservoirs, though other, risk-based management approaches are also likely needed. (C) 2016 American Society of Civil Engineers.
C1 [Rheinheimer, David E.; Viers, Joshua H.] Univ Calif Merced, Sch Engn, Merced, CA 95343 USA.
   [Null, Sarah E.] Utah State Univ, Dept Watershed Sci, Logan, UT 84322 USA.
C3 University of California System; University of California Merced; Utah
   System of Higher Education; Utah State University
RP Rheinheimer, DE (corresponding author), Univ Calif Merced, Sch Engn, Merced, CA 95343 USA.
EM drheinheimer@ucmerced.edu; sarah.null@usu.edu; jviers@ucmerced.edu
RI Viers, Joshua/ABC-1851-2020; Rheinheimer, David/K-7437-2015; Null,
   Sarah/E-4422-2011
OI Rheinheimer, David/0000-0003-1525-9069; Null, Sarah/0000-0001-7451-7908;
   Viers, Joshua/0000-0001-7957-7942
FU Guido Franco; California Energy Commission (CEC) [500-10-030];
   University of California Center for Information Technology Research in
   the Interest of Society (CITRIS); Office Of The Director; Office of
   Integrative Activities [1208732] Funding Source: National Science
   Foundation
FX The authors gratefully acknowledge Guido Franco and the California
   Energy Commission for funding portions of this research (CEC#
   500-10-030), as well as the University of California Center for
   Information Technology Research in the Interest of Society (CITRIS).
CR Borgomeo E, 2014, WATER RESOUR RES, V50, P6850, DOI 10.1002/2014WR015558
   Brekke L., 2013, DOWN SCALED CMIP3 CM
   Brown C, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011212
   Doherty John., 2010, WATERMARK NUMERICAL
   DTA Sacramento, 2007, MOD EV REP IN PRESS
   Fung F, 2013, WATER RESOUR MANAG, V27, P1063, DOI 10.1007/s11269-012-0080-7
   Georgakakos AP, 2012, J HYDROL, V412, P34, DOI 10.1016/j.jhydrol.2011.04.038
   Grantham TE, 2014, BIOSCIENCE, V64, P1006, DOI 10.1093/biosci/biu159
   Heino J, 2009, BIOL REV, V84, P39, DOI 10.1111/j.1469-185X.2008.00060.x
   Cisneros BEJ, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P229
   Johnson T. E., 2008, ENVIRON MANAGE, V43, P118
   Knutti R, 2013, NAT CLIM CHANGE, V3, P369, DOI [10.1038/nclimate1716, 10.1038/NCLIMATE1716]
   Livneh B., 2015, SCI DATA IN PRESS, V2
   Madani K, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR007206
   Maurer EP, 2010, HYDROL EARTH SYST SC, V14, P1125, DOI 10.5194/hess-14-1125-2010
   Mehta VK, 2011, J WATER CLIM CHANGE, V2, P29, DOI 10.2166/wcc.2011.054
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Nevada Irrigation District, 2006, 2266 FERC NEV IRR DI
   Null SE, 2013, J AM WATER RESOUR AS, V49, P1456, DOI 10.1111/jawr.12102
   Null SE, 2013, WATER RESOUR RES, V49, P1137, DOI 10.1002/wrcr.20097
   Null SE, 2013, CLIMATIC CHANGE, V116, P149, DOI 10.1007/s10584-012-0459-8
   Olivares MA, 2012, J WATER RES PL-ASCE, V138, P606, DOI 10.1061/(ASCE)WR.1943-5452.0000214
   Pacific Gas & Electric Company, 2007, 2310 FERC PAC GAS EL
   Palmer MA, 2008, FRONT ECOL ENVIRON, V6, P81, DOI 10.1890/060148
   Petts GE, 2009, J AM WATER RESOUR AS, V45, P1071, DOI 10.1111/j.1752-1688.2009.00360.x
   Poff NL, 2007, P NATL ACAD SCI USA, V104, P5732, DOI 10.1073/pnas.0609812104
   Poff NL, 1997, BIOSCIENCE, V47, P769, DOI 10.2307/1313099
   Rheinheimer DE, 2015, RIVER RES APPL, V31, P269, DOI 10.1002/rra.2749
   Rheinheimer DE, 2013, RIVER RES APPL, V29, P1291, DOI 10.1002/rra.2612
   Rheinheimer DE, 2014, J WATER RES PLAN MAN, V140, P714, DOI 10.1061/(ASCE)WR.1943-5452.0000373
   Rupp DE, 2013, J GEOPHYS RES-ATMOS, V118, P10884, DOI 10.1002/jgrd.50843
   Singh R, 2014, WATER RESOUR RES, V50, P3409, DOI 10.1002/2013WR014988
   Stainforth DA, 2007, PHILOS T R SOC A, V365, P2163, DOI 10.1098/rsta.2007.2073
   Stakhiv EZ., 1998, WATER POLICY, V1, P159, DOI DOI 10.1016/S1366-7017(98)00018-X
   Strayer DL, 2010, J N AM BENTHOL SOC, V29, P344, DOI 10.1899/08-171.1
   SWRCB (California State Water Resources Control Board), 1999, WAT RIGHT DEC 1641
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Towler E, 2013, WATER RESOUR RES, V49, P4997, DOI 10.1002/wrcr.20378
   U. S. Fish and Wildlife Service, 2008, 814202008F14815 US F
   U. S. Forest Service, 2012, 2310 FERC US FOR SER
   Viers JH, 2011, J AM WATER RESOUR AS, V47, P655, DOI 10.1111/j.1752-1688.2011.00531.x
   Vörösmarty CJ, 2010, NATURE, V467, P555, DOI 10.1038/nature09440
   Weaver CP, 2013, WIRES CLIM CHANGE, V4, P39, DOI 10.1002/wcc.202
   Wilby RL, 2011, WATER RESOUR RES, V47, DOI 10.1029/2011WR011194
   Wilby RL, 2009, INT J CLIMATOL, V29, P1193, DOI 10.1002/joc.1839
   Wilby RL, 2010, WEATHER, V65, P180, DOI 10.1002/wea.543
   Worrall TP, 2014, HYDROLOG SCI J, V59, P645, DOI 10.1080/02626667.2013.825722
   Xenopoulos MA, 2005, GLOBAL CHANGE BIOL, V11, P1557, DOI 10.1111/j.1365-2486.2005.001008.x
   Yarnell SM, 2015, BIOSCIENCE, V65, P963, DOI 10.1093/biosci/biv102
   Yarnell SM, 2010, BIOSCIENCE, V60, P114, DOI 10.1525/bio.2010.60.2.6
   Yates D, 2005, WATER INT, V30, P487, DOI 10.1080/02508060508691893
   Young CA, 2009, J AM WATER RESOUR AS, V45, P1409, DOI 10.1111/j.1752-1688.2009.00375.x
NR 54
TC 17
Z9 19
U1 0
U2 21
PU ASCE-AMER SOC CIVIL ENGINEERS
PI RESTON
PA 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
SN 0733-9496
EI 1943-5452
J9 J WATER RES PLAN MAN
JI J. Water Resour. Plan. Manage.-ASCE
PD NOV
PY 2016
VL 142
IS 11
AR 04016049
DI 10.1061/(ASCE)WR.1943-5452.0000693
PG 10
WC Engineering, Civil; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Water Resources
GA EA1NZ
UT WOS:000386360300011
DA 2025-01-10
ER

PT C
AU Cole, A
   Parshotam, A
   Roth, H
   Webby, R
   Botha, N
AF Cole, A
   Parshotam, A
   Roth, H
   Webby, R
   Botha, N
GP MSSANZI
TI Modelling human adaptation to climate variability with the aid of an
   influence matrix
SO MODSIM 2003: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION, VOLS
   1-4: VOL 1: NATURAL SYSTEMS, PT 1; VOL 2: NATURAL SYSTEMS, PT 2; VOL 3:
   SOCIO-ECONOMIC SYSTEMS; VOL 4: GENERAL SYSTEMS
LA English
DT Proceedings Paper
CT International Congress on Modelling and Simulation
CY JUL 14-17, 2003
CL Townsville, AUSTRALIA
SP Modelling & Simulat Soc Australia & New Zealand, Environm Modelling & Software, CSIRO, James Cook Univ, Japan Soc Simulat Technol, IMACS, SCS
DE climate variability; resilience; influence matrix; complexity;
   simulation game
ID ECOLOGICAL DISTURBANCE; SYSTEMS
AB Human ability to adapt to climate variability may help alleviate the effects of predicted longer-term climate variability on our social, ecological and economic systems. It is not possible to model human adaptation to climate variability without considering a bewildering array of variables. The stochastic, reflexive, threshold-sensitive, time-dependent and system-wide nature of the variables usually associated with human coping and learning responses to climate variability implies the existence of a resilient-centred, complex system. The reflexive character of a resilient system especially complicates modelling approaches based on traditional deterministic and stochastic modelling paradigms. We are interested in the use of participatory game simulation models that overcome the probabilistic element of human decision-making by including it as a key variable. Our approach is based on a 2 stage-modelling project that combines the benefits of a whole-system approach with participatory modelling. In this paper we explore the role of an influence matrix in scoping, reducing and formulating the structure of a future game simulation model. Our stakeholders are farm managers from New Zealand East Coast, North Island rural communities that are currently participating in a government funded sustainable management farm study group.
C1 Landcare Res, Palmerston North, New Zealand.
C3 Landcare Research - New Zealand
RP Cole, A (corresponding author), Landcare Res, Private Bag 11052, Palmerston North, New Zealand.
RI Webby, Richard/N-5657-2018
OI Cole, Anthony/0000-0001-8519-8172
CR COLE AO, 2003, P INT RANG C NAT BOT
   COSTANZA R, 1993, BIOSCIENCE, V43, P545, DOI 10.2307/1311949
   DEANGELIS DL, 1985, ECOL MODEL, V29, P399, DOI 10.1016/0304-3800(85)90063-8
   GERRITSEN J, 1985, ECOL MODEL, V29, P383, DOI 10.1016/0304-3800(85)90062-6
   MUNASINGHE M, CONSERVATION ECOLOGY, V5
   PETERSON G, CONSERVATION ECOLOGY, V1
   PICKETT STA, 1989, OIKOS, V54, P129, DOI 10.2307/3565258
   RYKIEL EJ, 1985, AUST J ECOL, V10, P361, DOI 10.1111/j.1442-9993.1985.tb00897.x
   SOUSA WP, 1979, ECOLOGY, V60, P1225, DOI 10.2307/1936969
   STERMAN JD, 1989, MANAGE SCI, V35, P321, DOI 10.1287/mnsc.35.3.321
   VESTOR F, 1976, URBAN SYSTEMS CRISIS
   Walker B, 2002, CONSERV ECOL, V6
NR 12
TC 0
Z9 0
U1 0
U2 3
PU UNIV WESTERN AUSTRALIA
PI NEDLANDS
PA NEDLANDS, WA, AUSTRALIA
BN 1-74052-098-X
PY 2003
BP 29
EP 34
PG 6
WC Computer Science, Interdisciplinary Applications; Ecology; Environmental
   Sciences; Meteorology & Atmospheric Sciences; Water Resources
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science; Environmental Sciences & Ecology; Meteorology &
   Atmospheric Sciences; Water Resources
GA BY81Z
UT WOS:000189470800005
DA 2025-01-10
ER

PT J
AU Sun, JT
   Jin, PY
   Hoffmann, AA
   Duan, XZ
   Dai, J
   Hu, G
   Xue, XF
   Hong, XY
AF Sun, J. -T.
   Jin, P. -Y.
   Hoffmann, A. A.
   Duan, X. -Z.
   Dai, J.
   Hu, G.
   Xue, X. -F.
   Hong, X. -Y.
TI Evolutionary divergence of mitochondrial genomes in two
   <i>Tetranychus</i> species distributed across different climates
SO INSECT MOLECULAR BIOLOGY
LA English
DT Article
DE mitochondrial DNA; d(N)/d(S); positive selection; purifying selection;
   climate
ID PHYLOGENETIC ANALYSIS; PURIFYING SELECTION; NATURAL-SELECTION; DNA;
   HISTORY; CONSTRAINTS; GENETICS; TOOLS
AB There is increasing evidence that mitochondrial genomes (mitogenomes) can be under selection, whereas the selective regimes shaping mitogenome evolution remain largely unclear. To test for mitogenome evolution in relation to the climate adaptation, we explored mtDNA variation in two spider mite (Tetranychus) species that distribute across different climates. We sequenced 26 complete mitogenomes of Tetranychus truncates, which occurs in both warm and cold regions, and nine complete mitogenomes of Tetranychus pueraricola, which is restricted to warm regions. Patterns of evolution in the two species' mitogenomes were compared through a series of d(N)/d(S) methods and physicochemical profiles of amino acid replacements. We found that: (1) the mitogenomes of both species were under widespread purifying selection; (2) elevated directional adaptive selection was observed in the T. truncatus mitogenome, perhaps linked to the cold climates adaptation of T. truncatus; and (3) the strength of selection varied across genes, and diversifying positive selection detected on ND4 and ATP6 pointed to their crucial roles during adaptation to different climatic conditions. This study gained insight into the mitogenome evolution in relation to the climate adaptation.
C1 [Sun, J. -T.; Jin, P. -Y.; Duan, X. -Z.; Dai, J.; Hu, G.; Xue, X. -F.; Hong, X. -Y.] Nanjing Agr Univ, Dept Entomol, Nanjing 210095, Jiangsu, Peoples R China.
   [Hoffmann, A. A.] Univ Melbourne, Inst Bio21, Sch BioSci, Melbourne, Vic, Australia.
C3 Nanjing Agricultural University; University of Melbourne
RP Hong, XY (corresponding author), Nanjing Agr Univ, Dept Entomol, Nanjing 210095, Jiangsu, Peoples R China.
EM xyhong@njau.edu.cn
RI Jin, Peng-Yu/LPP-4273-2024; Xue, Xiao-Feng/P-2046-2015; Hoffmann,
   Ary/C-2961-2011; Hong, Xiao-Yue/AAF-4759-2020
OI Hu, Gao/0000-0002-1000-5687; Hong, Xiao-Yue/0000-0002-5209-3961; Duan,
   Xing-Zhi/0009-0004-9260-0659; Hoffmann, Ary/0000-0001-9497-7645; Jin,
   Peng-Yu/0000-0003-1310-2711
FU National Key Research and Development Project of China [2016YFC1201200];
   National Natural Science Foundation of China [31300346, 31672035]
FX We thank Li-Wei Kong of the Department of Entomology, Nanjing
   Agricultural University (NJAU), for help with the collection of samples.
   We thank Hernan Morales of Monash University (Melbourne) for his kind
   help in use of the TreesSAAP software. We thank Hao-Sen Li of Sun
   Yat-sen University for reviewing an early draft of the manuscript and
   for providing suggestions. We are also grateful to Dr Feng Zhang of the
   Department of Entomology, NJAU, for his kind help with data analyses.
   This work was supported by a grant-in-aid from the National Key Research
   and Development Project of China (2016YFC1201200), and a grant-in-aid
   from the National Natural Science Foundation of China (31300346,
   31672035).
CR [Anonymous], 2012, BIOENERGETICS
   AVISE JC, 1987, ANNU REV ECOL SYST, V18, P489, DOI 10.1146/annurev.es.18.110187.002421
   Ballard JWO, 2007, EVOLUTION, V61, P1735, DOI 10.1111/j.1558-5646.2007.00133.x
   Ballard JWO, 2014, FUNCT ECOL, V28, P218, DOI 10.1111/1365-2435.12177
   Balloux F, 2009, P ROY SOC B-BIOL SCI, V276, P3447, DOI 10.1098/rspb.2009.0752
   Bandelt HJ, 1999, MOL BIOL EVOL, V16, P37, DOI 10.1093/oxfordjournals.molbev.a026036
   Bazin E, 2006, SCIENCE, V312, P570, DOI 10.1126/science.1122033
   Bélanger-Deschênes S, 2013, ECOTOXICOLOGY, V22, P938, DOI 10.1007/s10646-013-1083-8
   Boore JL, 1999, NUCLEIC ACIDS RES, V27, P1767, DOI 10.1093/nar/27.8.1767
   Brand MD, 2000, EXP GERONTOL, V35, P811, DOI 10.1016/S0531-5565(00)00135-2
   Camus MF, 2015, CURR BIOL, V25, P2717, DOI 10.1016/j.cub.2015.09.012
   Chen DS, 2016, MITOCHONDRIAL DNA A, V27, P1480, DOI 10.3109/19401736.2014.953101
   Chen DS, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0110625
   Chong RA, 2013, EVOLUTION, V67, P894, DOI 10.1111/j.1558-5646.2012.01830.x
   da Fonseca RR, 2008, BMC GENOMICS, V9, DOI 10.1186/1471-2164-9-119
   Dalziel AC, 2006, J MOL EVOL, V62, P319, DOI 10.1007/s00239-005-0110-7
   Das J, 2006, BIOESSAYS, V28, P890, DOI 10.1002/bies.20463
   Delport W, 2010, BIOINFORMATICS, V26, P2455, DOI 10.1093/bioinformatics/btq429
   Detmer SA, 2007, NAT REV MOL CELL BIO, V8, P870, DOI 10.1038/nrm2275
   Egea R, 2008, NUCLEIC ACIDS RES, V36, pW157, DOI 10.1093/nar/gkn337
   Ehara Shozo, 1996, Journal of the Acarological Society of Japan, V5, P17
   Elson JL, 2004, AM J HUM GENET, V74, P229, DOI 10.1086/381505
   Fiedorczuk K, 2016, NATURE, V538, P406, DOI 10.1038/nature19794
   Fontanillas P, 2005, MOL ECOL, V14, P661, DOI 10.1111/j.1365-294X.2004.02414.x
   Foote AD, 2011, BIOL LETTERS, V7, P116, DOI 10.1098/rsbl.2010.0638
   Franks SJ, 2012, ANNU REV GENET, V46, P185, DOI 10.1146/annurev-genet-110711-155511
   Gagnaire PA, 2012, MOL BIOL EVOL, V29, P2909, DOI 10.1093/molbev/mss076
   Garvin MR, 2015, J ZOOL SYST EVOL RES, V53, P1, DOI 10.1111/jzs.12079
   Garvin MR, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0024127
   Harrisson K, 2016, HEREDITY, V116, P506, DOI 10.1038/hdy.2016.8
   Jacobsen MW, 2014, HEREDITY, V113, P432, DOI 10.1038/hdy.2014.44
   Jacobsen MW, 2016, MOL PHYLOGENET EVOL, V95, P161, DOI 10.1016/j.ympev.2015.11.008
   Jacobsen MW, 2015, BIOL LETTERS, V11, DOI 10.1098/rsbl.2015.0014
   JUKES T H, 1969, P21
   Lanfear R, 2012, MOL BIOL EVOL, V29, P1695, DOI 10.1093/molbev/mss020
   Librado P, 2009, BIOINFORMATICS, V25, P1451, DOI 10.1093/bioinformatics/btp187
   Matsuda T, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0108672
   McClellan David A, 2010, Int J Bioinform Res Appl, V6, P120, DOI 10.1504/IJBRA.2010.032116
   MCDONALD JH, 1991, NATURE, V351, P652, DOI 10.1038/351652a0
   Meiklejohn CD, 2007, TRENDS GENET, V23, P259, DOI 10.1016/j.tig.2007.03.008
   Melo-Ferreira J, 2014, GENOME BIOL EVOL, V6, P886, DOI 10.1093/gbe/evu059
   Mishmar D, 2003, P NATL ACAD SCI USA, V100, P171, DOI 10.1073/pnas.0136972100
   Morales HE, 2015, MOL ECOL, V24, P2820, DOI 10.1111/mec.13203
   Murrell B, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002764
   Nielsen R, 2005, ANNU REV GENET, V39, P197, DOI 10.1146/annurev.genet.39.073003.112420
   Peck LS, 2002, POLAR BIOL, V25, P31, DOI 10.1007/s003000100308
   R Core Team, 2019, R: A Language and Environment for Statistical Computing
   Rand DM, 2004, TRENDS ECOL EVOL, V19, P645, DOI 10.1016/j.tree.2004.10.003
   Ronquist F, 2012, SYST BIOL, V61, P539, DOI 10.1093/sysbio/sys029
   Ruiz-Pesini E, 2004, SCIENCE, V303, P223, DOI 10.1126/science.1088434
   Seeman OD, 2011, ZOOTAXA, P1
   Silva G, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2014.1093
   Sommer A, 1999, MAR ECOL PROG SER, V181, P215, DOI 10.3354/meps181215
   Sun JT, 2015, SCI REP-UK, V5, DOI 10.1038/srep08045
   Sun YB, 2011, MOL BIOL EVOL, V28, P39, DOI 10.1093/molbev/msq256
   Tamura K, 2011, MOL BIOL EVOL, V28, P2731, DOI 10.1093/molbev/msr121
   Vitti JJ, 2013, ANNU REV GENET, V47, P97, DOI 10.1146/annurev-genet-111212-133526
   Wallace DC, 2005, ANNU REV GENET, V39, P359, DOI 10.1146/annurev.genet.39.110304.095751
   White CR, 2012, P ROY SOC B-BIOL SCI, V279, P1740, DOI 10.1098/rspb.2011.2060
   Woolley S, 2003, BIOINFORMATICS, V19, P671, DOI 10.1093/bioinformatics/btg043
   Xia XH, 2003, MOL PHYLOGENET EVOL, V26, P1, DOI 10.1016/S1055-7903(02)00326-3
   Xia XH, 2017, J HERED, V108, P431, DOI 10.1093/jhered/esx033
   Xue XF, 2017, MOL PHYLOGENET EVOL, V109, P271, DOI 10.1016/j.ympev.2017.01.009
   Xue XF, 2016, SCI REP-UK, V6, DOI 10.1038/srep18920
   Yang ZH, 2007, MOL BIOL EVOL, V24, P1586, DOI 10.1093/molbev/msm088
   Zhang FF, 2013, GENOME BIOL EVOL, V5, P1781, DOI 10.1093/gbe/evt129
   [郑景云 ZHENG Jingyun], 2010, [地理学报, Acta Geographica Sinica], V65, P3
NR 67
TC 28
Z9 28
U1 2
U2 49
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0962-1075
EI 1365-2583
J9 INSECT MOL BIOL
JI Insect Mol. Biol.
PD DEC
PY 2018
VL 27
IS 6
BP 698
EP 709
DI 10.1111/imb.12501
PG 12
WC Biochemistry & Molecular Biology; Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Entomology
GA HA0FW
UT WOS:000449884300003
PM 29797479
OA Green Published
DA 2025-01-10
ER

PT J
AU Ryghaug, M
   Solli, J
AF Ryghaug, Marianne
   Solli, Joran
TI The appropriation of the climate change problem among road managers:
   fighting in the trenches of the real world
SO CLIMATIC CHANGE
LA English
DT Article
ID SCIENCE; POLICY; ADAPTATION; KNOWLEDGE; TRANSPORTATION; INFORMATION;
   NEED
AB This paper investigates how transportation sector managers perceive and utilize climate science, and subsequently, how they appropriate the climate change problem. The analysis focuses on which devices they qualify as useful for translating between knowledge, policy and practice concluding with a discussion of what this suggests in the development of efficient climate adaptation strategies. The paper demonstrates that although transportation sector managers accept the findings of climate science knowledge presented to them, their understanding of the climate change problem and the range of qualifying anchoring devices used in the development of climate adaption strategies are differentiated according to where they are located in the institutional context. For transportation sector managers on the regional and district level, the climate problem is largely perceived through the occurrence of extreme weather rather than through climate science. However, this knowledge basis is not considered sufficient to support 'knowing how to act' and has resulted in waiting for the authorities to make standards and regulations that would translate climate change knowledge into methods of practice. We argue that the development of standards and regulations might be underestimated in relation to user demands in climate adaptation work that involves reconciling scientific information.
C1 [Ryghaug, Marianne; Solli, Joran] Norwegian Univ Sci & Technol NTNU, Dept Interdisciplinary Studies Culture, Ctr Technol & Soc, N-7491 Trondheim, Norway.
C3 Norwegian University of Science & Technology (NTNU)
RP Solli, J (corresponding author), Norwegian Univ Sci & Technol NTNU, Dept Interdisciplinary Studies Culture, Ctr Technol & Soc, N-7491 Trondheim, Norway.
EM marianne.ryghaug@ntnu.no; joran.solli@ntnu.no
FU Norwegian Research Council through the NORKLIMA-programme
FX The research was funded by the Norwegian Research Council through the
   NORKLIMA-programme. We thank Knut H. Sorensen, Stephen Schneider and one
   anonymous reviewer for helpful comments.
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Church RL, 2000, TRANSPORT RES C-EMER, V8, P321, DOI 10.1016/S0968-090X(00)00019-X
   Dessai S, 2004, CLIM POLICY, V4, P107
   Dessai S, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P64
   Edwards JB, 1999, METEOROL APPL, V6, P59, DOI 10.1017/S1350482799001139
   Fussel HM, 2007, GLOB ENV CHANG, V17, P59
   Guston DH, 2001, SCI TECHNOL HUM VAL, V26, P399, DOI 10.1177/016224390102600401
   Intergovernmental Panel on Climate Change, 2007, IPCC 4 ASS REP WORK
   IPC Change, 2000, SPECIAL REPORT EMISS
   Martin Emily., 1994, Flexible Bodies: Tracking Immunity in American CultureFrom the Days of Polio to the Age of AIDS
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   Næss R, 2011, TIDSSKR SAMFUNNSFOR, V52, P329
   Organisation for Economic Co-operation and Development/International Energy Agency, 2000, ROAD KYOT CURR CO2 T
   Pielke Jr RA, 2005, POPUL ENVIRON, V26, P3
   Pisano P., 2002, P POT IMP CLIM CHANG
   Ryghaug M, 2011, PUBLIC UNDERST SCI, V20, P778, DOI 10.1177/0963662510362657
   Sarewitz D, 2007, ENVIRON SCI POLICY, V10, P5, DOI 10.1016/j.envsci.2006.10.001
   Schneider Stephen., 2009, Science as a Contact Sport: Inside the Battle to Save Earth's Climate
   Solli J, 2009, 9 NORD ENV SOC SCI C
   Sorensen K., 2000, Between Understanding and Trust. The Public, P237, DOI DOI 10.4324/9780203988978
   Sorensen K.H., 2006, Domestication of Media and Technology, P40
   Strauss E, 1998, CLIN ORTHOP RELAT R, P2
   Suarez P, 2005, TRANSPORT RES D-TR E, V10, P231, DOI 10.1016/j.trd.2005.04.007
   Transportation Research Board and National Research Council, 2008, 290 TRANSP RES BOARD
   Tribbia J, 2008, ENVIRON SCI POLICY, V11, P315, DOI 10.1016/j.envsci.2008.01.003
   van der Sluijs J, 1998, SOC STUD SCI, V28, P291, DOI 10.1177/030631298028002004
   Vogel C, 2007, GLOBAL ENVIRON CHANG, V17, P349, DOI 10.1016/j.gloenvcha.2007.05.002
   Wynne Brian., 1995, HDB SCI TECHNOLOGY S, V2nd, P361, DOI [10.4135/9781412990127.n17, DOI 10.4135/9781412990127]
NR 29
TC 13
Z9 15
U1 1
U2 18
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0165-0009
EI 1573-1480
J9 CLIMATIC CHANGE
JI Clim. Change
PD OCT
PY 2012
VL 114
IS 3-4
BP 427
EP 440
DI 10.1007/s10584-012-0449-x
PG 14
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 998NH
UT WOS:000308246300002
DA 2025-01-10
ER

PT J
AU Jekabsone, A
   Marín, JPD
   Martins, S
   Rosa, M
   Kamenders, A
AF JEKABSONE, Anda
   DELGADO MARIN, Jose Pablo
   MARTINS, Sofia
   ROSA, Marika
   KAMENDERS, Agris
TI Upgrade from SEAP to SECAP: Experience of 6 European Municipalities
SO ENVIRONMENTAL AND CLIMATE TECHNOLOGIES
LA English
DT Article
DE Adaptation strategies; SECAPs; urban resilience
ID ENERGY ACTION PLANS; CLIMATE-CHANGE; MITIGATION; FRAMEWORK; CITIES
AB Since 2008 many municipalities in the European Union have taken part in the Covenant of Mayors (CoM) initiative and have developed Sustainable Energy Action Plans (SEAP) to contribute to climate change mitigation. To respond to new policy goals for 2030, the CoM has expanded its focus and since 2018 requires municipalities to cover climate adaptation actions. The main aim of this paper is to analyse the first experiences of six municipalities from Spain, Portugal and Latvia in upgrading their existing Sustainable Energy Actions Plans to Sustainable Energy and Climate Action Plans (SECAP). SECAPs were developed through a participatory process involving all relevant local stakeholders, to gain maximum understanding and acceptance. Each municipality implemented climate adaption actions to demonstrate the need for adaptation and the ways it can be accomplished.
C1 [JEKABSONE, Anda; ROSA, Marika; KAMENDERS, Agris] Riga Tech Univ, Inst Energy Syst & Environm, Azenes Iela 12-1, LV-1048 Riga, Latvia.
   [DELGADO MARIN, Jose Pablo] EuroVertice Consultores SL, Km 388 Complejo Espinardo,Edificio T, Murcia 30100, Spain.
   [MARTINS, Sofia] IrRADIARE, Ua Goa 16,2 Esq, P-2795089 Lisbon, Portugal.
C3 Riga Technical University
RP Jekabsone, A (corresponding author), Riga Tech Univ, Inst Energy Syst & Environm, Azenes Iela 12-1, LV-1048 Riga, Latvia.
EM anda.jekabsone@edu.rtu.lv
RI Kamenders, Agris/GOV-5818-2022
OI Delgado Marin, Jose Pablo/0000-0003-2286-6481; Kamenders,
   Agris/0000-0002-4695-6775
FU EU Life program [LIFE16 CCA/ES/000049]
FX This paper has been produced within the project Life Adaptate LIFE16
   CCA/ES/000049, which is funded by EU Life program. We are thankful to
   colleagues from EuroVertice Consultores S. L., Instituto de Fomento de
   la Region de Murcia, IrRADIARE, Autonomous Community of the Murcia
   Region (CARM) and Ekodoma Ltd. for implementing all the project
   activities and supporting municipalities in the SECAP and adaptation
   process. We are grateful for reviewers' comments, as they helped to
   improve the article.
CR Alberico I, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101893
   Alhindawi I, 2020, ENVIRON CLIM TECHNOL, V24, P119, DOI 10.2478/rtuect-2020-0091
   [Anonymous], 2020, Stepping up Europe's 2030 Climate Ambition - Investing in a Climate-Neutral Future for the Benefit of Our People
   [Anonymous], 1992, United Nations Framework Convention on Climate Change
   [Anonymous], EU CLIMATE ADAPT PLA
   Bertoldi P., 2018, GUIDEBOOK DEV SUSTAI, DOI [10.2760/118857, DOI 10.2760/118857]
   Bertoldi P, 2018, ENERG EFFIC, V11, P1913, DOI 10.1007/s12053-018-9760-3
   Cipriano X, 2017, SUSTAIN CITIES SOC, V32, P263, DOI 10.1016/j.scs.2017.03.004
   Coelho S, 2018, J CLEAN PROD, V176, P1223, DOI 10.1016/j.jclepro.2017.11.247
   Covenant of Mayors, 2018, COV MAYORS ANN REP
   Delgado Marin J.P., 2019, GUIDE ELABORATION SU
   deLlano-Paz F, 2016, ENERGY, V115, P1347, DOI 10.1016/j.energy.2016.01.068
   Fazey I, 2018, CURR OPIN ENV SUST, V31, P30, DOI 10.1016/j.cosust.2017.12.006
   Feldmeyer D, 2020, ECOL INDIC, V119, DOI 10.1016/j.ecolind.2020.106861
   Feofilovs M, 2020, ENVIRON CLIM TECHNOL, V24, P249, DOI 10.2478/rtuect-2020-0101
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Kamenders A, 2017, ENRGY PROCED, V128, P172, DOI 10.1016/j.egypro.2017.09.038
   Kona A., 2016, Covenant of Mayors: Greenhouse Gas Emissions Achievements and Projections, DOI [10.2790/11008, DOI 10.2790/11008]
   Kona A, 2018, SUSTAIN CITIES SOC, V41, P568, DOI 10.1016/j.scs.2018.05.017
   Messori G, 2020, J ENVIRON MANAGE, V260, DOI 10.1016/j.jenvman.2019.110024
   Pablo-Romero MD, 2015, REV POLICY RES, V32, P576, DOI 10.1111/ropr.12135
   Pasimeni MR, 2019, ENVIRON SCI POLICY, V95, P20, DOI 10.1016/j.envsci.2019.02.002
   Perez-Bezos S, 2020, ENVIRON CLIM TECHNOL, V24, P66, DOI 10.2478/rtuect-2020-0086
   Pietrapertosa F, 2019, CITIES, V91, P93, DOI 10.1016/j.cities.2018.11.009
   Reckien D, 2018, J CLEAN PROD, V191, P207, DOI 10.1016/j.jclepro.2018.03.220
   UN -Habitat, 2016, WORLD CIT REP 2016
   Wallemacq P., 2017, CRED UNISDR, P6
   World Economic Forum, COMPUT FRAUD SECUR, V2019, P4, DOI [10.1016/S1361-3723(19)30016-8, DOI 10.1016/S1361-3723(19)30016-8]
NR 28
TC 5
Z9 5
U1 1
U2 12
PU SCIENDO
PI WARSAW
PA BOGUMILA ZUGA 32A, WARSAW, MAZOVIA, POLAND
SN 1691-5208
EI 2255-8837
J9 ENVIRON CLIM TECHNOL
JI Environ. Clim. Technol.
PD JAN
PY 2021
VL 25
IS 1
BP 254
EP 264
DI 10.2478/rtuect-2021-0018
PG 11
WC Green & Sustainable Science & Technology
WE Emerging Sources Citation Index (ESCI)
SC Science & Technology - Other Topics
GA SW6PU
UT WOS:000664636800008
OA gold
DA 2025-01-10
ER

PT J
AU Thorne, JH
   Gogol-Prokurat, M
   Hill, S
   Walsh, D
   Boynton, RM
   Choe, H
AF Thorne, James H.
   Gogol-Prokurat, Melanie
   Hill, Sandra
   Walsh, Dana
   Boynton, Ryan M.
   Choe, Hyeyeong
TI Vegetation refugia can inform climate-adaptive land management under
   global warming
SO FRONTIERS IN ECOLOGY AND THE ENVIRONMENT
LA English
DT Article
ID FORESTS; EXPOSURE; WILDFIRE; DRY
AB Natural resource managers need information about the risks associated with climate change to provide guidance on where to implement various management practices on natural lands. The spatial variation of projected impacts within a vegetation type can be used to target climate-adaptive management actions because different locations will be exposed to different levels of climatic stress. Vegetation refugia are areas that retain non-stressful climate conditions under future climates. Consensus vegetation refugia - areas retaining suitable climates under both wetter and drier future projections - represent only 14.6% of California's natural vegetation. One state and one federal government agency have incorporated vegetation refugia maps into conservation planning for 522 vertebrate species and for post-wildfire reforestation. Monitoring how vegetation responds to management actions at sites within vegetation refugia can improve the conservation of plants subjected to a changing climate.
C1 [Thorne, James H.; Boynton, Ryan M.] Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA.
   [Gogol-Prokurat, Melanie; Hill, Sandra] Calif Dept Fish & Wildlife, Sacramento, CA USA.
   [Walsh, Dana] US Forest Serv, Eldorado Natl Forest, USDA, Georgetown, CA USA.
   [Choe, Hyeyeong] Kangwon Natl Univ, Chunchon, South Korea.
C3 University of California System; University of California Davis; United
   States Department of Agriculture (USDA); United States Forest Service;
   Kangwon National University
RP Thorne, JH (corresponding author), Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA.
EM jhthorne@ucdavis.edu
OI Boynton, Ryan/0000-0002-3952-2573; Choe, Hyeyeong/0000-0003-2130-1622
FU US Department of the Interior National, Northeast, and Northwest Climate
   Adaptation Science Centers
FX Publication of this Special Issue was funded by the US Department of the
   Interior National, Northeast, and Northwest Climate Adaptation Science
   Centers. Thanks to TL Morelli for comments.
CR Brody SD, 2007, J AM PLANN ASSOC, V73, P330, DOI 10.1080/01944360708977981
   Buck J.M., 1970, CALIFORNIA TREE SEED
   Burge Dylan O., 2016, Madrono, V63, P3, DOI 10.3120/madr-63-02-3-206.1
   California Department of Fish and Wildlife [CDFW], 2014, CWHR VERS 9 0 PERS C
   Cartwright J, 2019, FRONT ECOL ENVIRON, V17, P331, DOI 10.1002/fee.2058
   Choe H, 2019, CLIMATIC CHANGE, V156, P51, DOI 10.1007/s10584-019-02493-8
   Choe H, 2017, J APPL ECOL, V54, P1742, DOI 10.1111/1365-2664.12865
   Davis KT, 2019, P NATL ACAD SCI USA, V116, P6193, DOI 10.1073/pnas.1815107116
   Dobrowski SZ, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12349
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Enquist CAF, 2017, FRONT ECOL ENVIRON, V15, P541, DOI 10.1002/fee.1733
   FRAP (Fire and Resources Assessment Program), 2016, GIS DAT
   Goforth BR, 2008, FOREST ECOL MANAG, V256, P36, DOI 10.1016/j.foreco.2008.03.032
   Gogol-Prokurat M, 2019, ASSESSMENT CLIMATE I
   Hallett LM, 2017, FRONT ECOL ENVIRON, V15, P578, DOI 10.1002/fee.1734
   Keeley ATH, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aacb85
   Krawchuk MA, 2020, FRONT ECOL ENVIRON, V18, P235, DOI 10.1002/fee.2190
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   McIntyre PJ, 2015, P NATL ACAD SCI USA, V112, P1458, DOI 10.1073/pnas.1410186112
   Michalak JL, 2020, FRONT ECOL ENVIRON, V18, P254, DOI 10.1002/fee.2207
   Millar CI, 2015, SCIENCE, V349, P823, DOI 10.1126/science.aaa9933
   Morelli TL, 2020, FRONT ECOL ENVIRON, V18, P228, DOI 10.1002/fee.2189
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   North MP, 2019, FOREST ECOL MANAG, V432, P209, DOI 10.1016/j.foreco.2018.09.007
   Pérez-García N, 2017, DIVERS DISTRIB, V23, P771, DOI 10.1111/ddi.12574
   Schwartz MW, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00003.1
   Steel ZL, 2018, LANDSCAPE ECOL, V33, P1159, DOI 10.1007/s10980-018-0665-5
   Thorne JH, 2009, NAT AREA J, V29, P344, DOI 10.3375/043.029.0402
   Thorne JH, 2018, CLIMATIC CHANGE, V148, P387, DOI 10.1007/s10584-017-2010-4
   Thorne JH, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.2021
   Thorne JamesH., 2016, A climate change vulnerability assessment of Californias terrestrial vegetation
   Voldoire A, 2013, CLIM DYNAM, V40, P2091, DOI 10.1007/s00382-011-1259-y
   Watanabe S, 2011, GEOSCI MODEL DEV, V4, P845, DOI 10.5194/gmd-4-845-2011
   Westerling A.L., 2018, California's Fourth Climate Change Assessment, P57
   Williams JN, 2018, J BIOGEOGR, V45, P2361, DOI 10.1111/jbi.13413
   Yoon EJ, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/aaf0cf
NR 36
TC 19
Z9 21
U1 0
U2 16
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1540-9295
EI 1540-9309
J9 FRONT ECOL ENVIRON
JI Front. Ecol. Environ.
PD JUN
PY 2020
VL 18
IS 5
SI SI
BP 281
EP 287
DI 10.1002/fee.2208
PG 7
WC Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA LS9DR
UT WOS:000536679700010
OA hybrid
DA 2025-01-10
ER

PT J
AU Alekneviciene, V
   Bendoraityte, A
AF Alekneviciene, Vilija
   Bendoraityte, Asta
TI ROLE OF GREEN FINANCE IN GREENING THE ECONOMY: CONCEPTUAL APPROACH
SO CENTRAL EUROPEAN BUSINESS REVIEW
LA English
DT Article
DE Green finance; green economy; environmental protection; green financial
   sector; green public funds
ID WEATHER DERIVATIVES; CLIMATE FUND; BOND; MECHANISM; SUBSIDY
AB Currently, economic development of countries and regions is not possible without the implementation of the European Green Deal. A set of policy initiatives by the European Commission is closely related to concepts such as greening the economy, green finance, climate finance, climate change adaptation and mitigation, environmental protection and others. This research is dedicated to highlighting the role of green finance in environmental protection and development of the financial sector. Green finance connects the worlds of finance and business with environmentally friendly behaviour. In principle, all strategic decisions made by business organisations must take into account the potential impact on the environment, which means that value creation in the long term is integral to the well-being of current and future generations. The novelty of the research lies in the developed conceptual framework of the role of green finance in greening the economy. The conceptual framework covers three main elements of green economy: real green economy, green finance and providers of green finance - the green financial sector and public funds. It is developed by applying the methods of content analysis and synthesis, comparison and logical modelling, the model as a research design proposed by Jaakkola (2020), a system test proposed by Arnold and Wade (2015) and the main features of the conceptual framework presented by Jabareen (2009).
   Implications for Central European audience: The main "green" economic and financial concepts are described and their interconnectedness is revealed in this study. This is important in the phase of greening the economy when various actors - users of information and decision-makers - interpret the concepts differently. Different understanding and thinking slow down the development of green economy. The developed conceptual framework provides a clear understanding of how business and public organisations, as well as individuals, can change their behaviour to environmentally friendly by investing in real investment projects or financial assets. Finally, the main research challenges and directions related to green real and financial investments are revealed.
C1 [Alekneviciene, Vilija; Bendoraityte, Asta] Vytautas Magnus Univ, Fac Bioecon Dev, Dept Appl Econ Finance & Accounting, Univ 10, Kaunas, Lithuania.
C3 Vytautas Magnus University
RP Alekneviciene, V (corresponding author), Vytautas Magnus Univ, Fac Bioecon Dev, Dept Appl Econ Finance & Accounting, Univ 10, Kaunas, Lithuania.
EM vilija.alekneviciene@vdu.lt; asta.bendoraityte@vdu.lt
OI Alekneviciene, Vilija/0000-0002-6501-8792; Bendoraityte,
   Asta/0000-0002-5761-6450
CR Agliardi E, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100868
   Alessi L, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100869
   Amundsen ES, 2009, J POLICY MODEL, V31, P903, DOI 10.1016/j.jpolmod.2009.09.002
   [Anonymous], 2009, Technical Report
   [Anonymous], 2020, Regulation (EU) 2020/852 of the European Parliament and of the Council of 18 June 2020 on the establishment of a framework to facilitate sustainable investment and amending Regulation (EU) 2019/2088
   [Anonymous], 2010, Working Paper
   Antimiani A, 2017, ENVIRON SCI POLICY, V77, P49, DOI 10.1016/j.envsci.2017.07.015
   Arnold RD, 2015, PROCEDIA COMPUT SCI, V44, P669, DOI 10.1016/j.procs.2015.03.050
   Aune FR, 2012, ENERG ECON, V34, P992, DOI 10.1016/j.eneco.2011.07.006
   Baker M., 2018, Financing the response to climate change: The pricing and ownership of us green bonds, DOI [10.2139/ssrn.3275327, DOI 10.3386/W25194]
   Balmer Michael., 2009, ENVIRON CLAIM J, V21, P337, DOI DOI 10.1080/10406020903361787
   Benth JS, 2012, ENERG ECON, V34, P592, DOI 10.1016/j.eneco.2011.09.012
   Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Bódis K, 2019, RENEW SUST ENERG REV, V114, DOI 10.1016/j.rser.2019.109309
   Bongaerts D., 2019, SSRN Electronic Journal, DOI [10.2139/ssrn.3389762, DOI 10.2139/SSRN.3389762]
   Borghesi S., 2022, Energy Pol., V166, DOI DOI 10.1016/J.ENPOL.2022.113004
   Bouri E, 2022, FINANC RES LETT, V47, DOI 10.1016/j.frl.2022.102740
   Boutabba MA, 2022, INT REV FINANC ANAL, V81, DOI 10.1016/j.irfa.2022.102071
   Bressan GM, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100877
   Brockett P.L., 2005, RISK MANAG INSUR REV, V8, P127, DOI [10.1111/j.1540-6296.2005.00052.x, DOI 10.1111/J.1540-6296.2005.00052.X]
   Buchholz M, 2014, AGR WATER MANAGE, V146, P34, DOI 10.1016/j.agwat.2014.07.011
   Chakrabarti G, 2021, J CLEAN PROD, V303, DOI 10.1016/j.jclepro.2021.127028
   Charnovitz S., 2014, Working Paper No. RSCAS 2014/93
   Chen QP, 2022, ASIA PAC J MANAG, V39, P899, DOI 10.1007/s10490-020-09750-w
   Cheng WJ, 2018, J CLEAN PROD, V176, P770, DOI 10.1016/j.jclepro.2017.12.027
   Criscuolo C, 2015, ENERG POLICY, V83, P38, DOI 10.1016/j.enpol.2015.03.023
   Cui LB, 2018, WORLD DEV, V101, P173, DOI 10.1016/j.worlddev.2017.08.009
   Cumming D, 2016, INT REV FINANC ANAL, V44, P86, DOI 10.1016/j.irfa.2016.01.015
   Dziwok E, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132111902
   European Commission, 2018, The European Green Deal COM (2019) 640 final, DOI [10.2833/9937, DOI 10.2833/9937]
   Eyraud L., 2011, IMF Working Paper WP/11/296
   Fatica S, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100873
   Febi W, 2018, FINANC RES LETT, V27, P53, DOI 10.1016/j.frl.2018.02.025
   Feldman S.J., 1997, J INVEST, V6, P87
   Fischer C., 2016, Resources for the Future Discussion Paper, P16
   Flammer C., 2019, Academy of Management Proceedings, V2019, P15250, DOI 10.5465/AMBPP.2019.15250abstract
   Flammer C, 2021, J FINANC ECON, V142, P499, DOI 10.1016/j.jfineco.2021.01.010
   Ghosh S., 2010, 11020 HARV BUS SCH E, DOI [10.2139/ssrn.1669445, DOI 10.2139/SSRN.1669445, https://doi.org/10.2139/ssrn.1669445]
   Gianfrate G, 2019, J CLEAN PROD, V219, P127, DOI 10.1016/j.jclepro.2019.02.022
   Gilchrist D, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13020478
   Giraudet LG, 2021, ENERG POLICY, V149, DOI 10.1016/j.enpol.2020.111861
   Golub S. S., 2011, An Exploratory Review of Existing Work and Evidence, DOI [10.1787/5kg58j1cvcvk-en, DOI 10.1787/5KG58J1CVCVK-EN]
   Gu W, 2018, INT ENTREP MANAG J, V14, P35, DOI 10.1007/s11365-017-0463-6
   Hachenberg B, 2018, J ASSET MANAG, V19, P371, DOI 10.1057/s41260-018-0088-5
   Hafner S, 2020, ENVIRON INNOV SOC TR, V34, P26, DOI 10.1016/j.eist.2019.11.007
   Han YW, 2022, INT REV FINANC ANAL, V80, DOI 10.1016/j.irfa.2021.101998
   Heimvik A, 2021, ENERG ECON, V99, DOI 10.1016/j.eneco.2021.105316
   Heinkel R, 2001, J FINANC QUANT ANAL, V36, P431, DOI 10.2307/2676219
   Hohne B. N., 2012, Mapping of Green Finance Delivered by IDFC Members in 2011
   Hong H, 2019, J ECONOMETRICS, V208, P265, DOI 10.1016/j.jeconom.2018.09.015
   Huang ZH, 2019, TECHNOL FORECAST SOC, V144, P148, DOI 10.1016/j.techfore.2019.04.023
   Hyun S, 2021, FINANC RES LETT, V41, DOI 10.1016/j.frl.2020.101816
   Jaakkola E., 2020, AMS Review, V10, P18, DOI DOI 10.1007/S13162-020-00161-0
   Jabareen Y.R., 2009, INT J QUAL METH, V8, P49, DOI DOI 10.1177/160940690900800406
   Janda K, 2022, ENERG ECON, V108, DOI 10.1016/j.eneco.2022.105911
   Javadi S, 2021, J CORP FINANC, V69, DOI 10.1016/j.jcorpfin.2021.102019
   Kemp-Benedict E, 2018, ECOL ECON, V153, P218, DOI 10.1016/j.ecolecon.2018.07.012
   Larcker DF, 2020, J ACCOUNT ECON, V69, DOI 10.1016/j.jacceco.2020.101312
   Lin B, 2022, INT REV FINANC ANAL, V81, DOI 10.1016/j.irfa.2022.102063
   Lindenberg N., 2014, Definition of Green Finance
   Pham L, 2020, FINANC RES LETT, V35, DOI 10.1016/j.frl.2020.101533
   MacAskill S, 2021, J CLEAN PROD, V280, DOI 10.1016/j.jclepro.2020.124491
   Mathew P, 2021, ENERG POLICY, V150, DOI 10.1016/j.enpol.2021.112137
   Matsumoto T, 2021, ENERG ECON, V95, DOI 10.1016/j.eneco.2021.105101
   Meric I., 2012, International Research Journal of Finance and Economics, P15
   Monasterolo I, 2020, ECOL ECON, V170, DOI 10.1016/j.ecolecon.2019.106571
   Moon C., 2020, P EUR C INN ENTR, P412, DOI [10.34190/EIE.20.090, DOI 10.34190/EIE.20.090]
   Mumtaz M. Z., 2021, Environmental Challenges, V5, DOI [10.1016/j.envc.2021.100325, DOI 10.1016/J.ENVC.2021.100325]
   Naeem MA, 2022, J ENVIRON MANAGE, V305, DOI 10.1016/j.jenvman.2021.114358
   Nagy RLG, 2021, ENERG ECON, V98, DOI 10.1016/j.eneco.2021.105259
   Nanayakkara M, 2019, APPL ECON, V51, P4425, DOI 10.1080/00036846.2019.1591611
   Pástor L, 2021, J FINANC ECON, V142, P550, DOI 10.1016/j.jfineco.2020.12.011
   Pham L, 2021, ENERG ECON, V98, DOI 10.1016/j.eneco.2021.105257
   Pollard JS, 2008, GEOFORUM, V39, P616, DOI 10.1016/j.geoforum.2006.03.008
   Randjelovic J., 2003, Business Strategy and the Environment, V12, P240, DOI DOI 10.1002/BSE.361
   Reboredo JC, 2018, ENERG ECON, V74, P38, DOI 10.1016/j.eneco.2018.05.030
   Renström TI, 2021, ENERG ECON, V95, DOI 10.1016/j.eneco.2020.105084
   Sangiorgi I, 2021, INT REV FINANC ANAL, V75, DOI 10.1016/j.irfa.2021.101738
   Sarumathi S., 2014, Global Journal of Finance and Management, V6, P777
   Schulz K, 2021, EARTH SYST GOV-NETH, V7, DOI 10.1016/j.esg.2020.100084
   Stulec I, 2019, J RETAIL CONSUM SERV, V49, P1, DOI 10.1016/j.jretconser.2019.02.025
   Svec J, 2007, GLOB FINANC J, V18, P185, DOI 10.1016/j.gfj.2006.04.006
   Taghizadeh-Hesary F, 2019, FINANC RES LETT, V31, P98, DOI 10.1016/j.frl.2019.04.016
   Tang DY, 2020, J CORP FINANC, V61, DOI 10.1016/j.jcorpfin.2018.12.001
   Tolliver C, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab1118
   Tzouvanas P, 2021, INT REV FINANC ANAL, V77, DOI 10.1016/j.irfa.2021.101812
   UNFCCC, 2015, PAR AGR
   Venturini A, 2022, INT REV FINANC ANAL, V79, DOI 10.1016/j.irfa.2021.101934
   Vizzotto V. D., 2012, Revista SINTESE Direito Empresarial, V4
   Wang C, 2017, J CLEAN PROD, V148, P111, DOI 10.1016/j.jclepro.2017.01.145
   Wang Y, 2016, ENRGY PROCED, V104, P311, DOI 10.1016/j.egypro.2016.12.053
   Weber O., 2005, Corporate Social Responsibility and Environmental Management, V12, P73, DOI DOI 10.1002/CSR.77
   Xing C, 2021, INT REV FINANC ANAL, V77, DOI 10.1016/j.irfa.2021.101838
   Zadek S., 2013, South-Originating Green Finance: Exploring the Potential
   Zerbib OD, 2019, J BANK FINANC, V98, P39, DOI 10.1016/j.jbankfin.2018.10.012
   Zhang R, 2021, PAC-BASIN FINANC J, V69, DOI 10.1016/j.pacfin.2021.101626
NR 96
TC 1
Z9 1
U1 9
U2 39
PU UNIV ECONOMICS-PRAGUE
PI PRAGUE 3
PA OECONOMICA PUBL, NAM W CHIRCHILLA 4, PRAGUE 3, CZ-130 67, CZECH REPUBLIC
EI 1805-4862
J9 CENT EUR BUS REV
JI Cent. Eur. Bus. Rev.
PY 2023
VL 12
IS 2
BP 105
EP 130
DI 10.18267/j.cebr.317
PG 26
WC Business
WE Emerging Sources Citation Index (ESCI)
SC Business & Economics
GA U9PE1
UT WOS:001088045500006
OA gold
DA 2025-01-10
ER

PT J
AU Dhouib, M
   Zitouna-Chebbi, R
   Prévot, L
   Molénat, J
   Mekki, I
   Jacob, F
AF Dhouib, M.
   Zitouna-Chebbi, R.
   Prevot, L.
   Molenat, J.
   Mekki, I
   Jacob, F.
TI Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed
   Mediterranean agrosystem
SO AGRICULTURAL WATER MANAGEMENT
LA English
DT Article
DE AquaCrop model; Rainfed agrosystems; Hilly terrains; Multicriteria
   evaluation; Mediterranean soils and crops; Soil water balance
ID WATER-USE EFFICIENCY; EDDY COVARIANCE MEASUREMENTS; GLOBAL
   SENSITIVITY-ANALYSIS; SIMULATE YIELD RESPONSE; CLIMATE-CHANGE IMPACTS;
   SOIL-MOISTURE; DEFICIT IRRIGATION; ENERGY FLUXES; WINTER-WHEAT;
   GRAIN-YIELD
AB Exploring crop spatial organizations within landscapes is a promising solution for agroecological transitions and climate change adaptation in Mediterranean rainfed hilly agrosystems. A prerequisite is to ensure that crop models can simulate a range of agrohydrological processes in such agrosystems. The current study deepened the evaluation of the AquaCrop model by conducting a multicriteria evaluation (canopy cover CC, dry aboveground biomass AGB, actual evapotranspiration ETa, runoff R, soil water content SWC) for a range of crop and soil combinations, and for contrasted hydroclimatic years in northeastern Tunisia. The data were collected in the Kamech catchment (OMERE Observatory) during nine measurement campaigns on predominant soils and crops. AquaCrop simulations were based on field observations and parameters from the literature. AquaCrop could simulate plant dynamics and water fluxes for contrasted hydroclimatic years, with a slight dependence on soil class and a significant dependence on crop type. Model simulations were of moderate quality for CC (R-2 of 0.45, RMSE of 0.24 on average) and of acceptable quality for AGB (R-2 of 0.81, RMSE of 0.85 ton ha(-1) on average). AquaCrop acceptably simulated water transfer across the soil-plant continuum (R-2 of 0.62, RMSE of 0.77 mm day(-1) on average for ETa; R-2 of 0.68, RMSE of 0.75 mm day(-1) on average for R; R-2 of 0.86, RMSE of 27.4 mm on average for SWC). The model performances were satisfactory for most cases, with p values larger than 5 % for the Student's t test on linear regressions of validation. Our results were similar to those reported in previous studies over flat terrain, including delayed senescence by model simulations with subsequent overestimation of CC and AGB observations. Additionally, soil cracks likely altered the AquaCrop ability to simulate runoff. Despite these limitations, our results support the application of AquaCrop to evaluate water productivity in hilly agrosystems.
C1 [Dhouib, M.] Univ Montpellier, Inst Agro Montpellier UMR LISAH, Inst Agro Montpellier, AgroParisTech,IRD, Montpellier, France.
   [Zitouna-Chebbi, R.; Mekki, I] Univ Carthage, INRGREF, Tunis, Tunisia.
   [Prevot, L.; Molenat, J.] Univ Montpellier, Inst Agro Montpellier, AgroParisTech, INRAE,IRD,INRAE UMR LISAH, Montpellier, France.
   [Jacob, F.] Univ Montpellier, Agro Montpellier Inst, AgroParisTech, INRAE,IRD UMR LISAH,IRD, Montpellier, France.
C3 Institut de Recherche pour le Developpement (IRD); Universite de
   Montpellier; AgroParisTech; Institut Agro; Universite de Carthage;
   Institut de Recherche pour le Developpement (IRD); AgroParisTech; INRAE;
   Universite de Montpellier; Institut Agro; Universite de Montpellier;
   AgroParisTech; INRAE; Institut de Recherche pour le Developpement (IRD)
RP Dhouib, M (corresponding author), Univ Montpellier, Inst Agro Montpellier UMR LISAH, Inst Agro Montpellier, AgroParisTech,IRD, Montpellier, France.
EM mariemdhouib93@gmail.com
RI Mekki, Insaf/HMV-6192-2023; Prevot, Laurent/A-5929-2011; Molénat,
   Jérôme/ABB-5677-2020; Jacob, Frederic/A-5946-2011
OI Prevot, Laurent/0000-0002-4627-4379; Jacob,
   Frederic/0000-0002-2491-3096; Zitouna Chebbi, Rim/0000-0003-0795-5371;
   Molenat, Jerome/0000-0002-5957-0927
FU Tunisian Ministry of Higher Education and Scientific Research (MESRS);
   French National Research Institute for Sustainable Development (IRD)
FX The first author benefited from funding provided by the Tunisian
   Ministry of Higher Education and Scientific Research (MESRS) and the
   French National Research Institute for Sustainable Development (IRD) to
   carry out her Ph.D. research. The current study is part of the ALTOS
   project in the framework of the PRIMA program, with financial
   contributions from France and Tunisia. The authors would like to thank
   (1) the Environmental Research Observatory OMERE (http://
   www.obsomere.org), which policy drives the availability of the data used
   in the current study, and Damien Raclot, (2) Guillaume Coulouma
   (INRAE/UMR LISAH) for the help and expertise provided in soil science,
   and (3) Marie Weiss (INRAE/UMR EMMAH) for the exchanges about CAN-EYE
   software.
CR Ahmadi SH, 2015, WATER RESOUR MANAG, V29, P2837, DOI 10.1007/s11269-015-0973-3
   Alaya I, 2019, ARAB J GEOSCI, V12, DOI 10.1007/s12517-019-4588-5
   Allen R.G., 1998, FAO Irrigation and Drainage Paper
   Andarzian B, 2011, AGR WATER MANAGE, V100, P1, DOI 10.1016/j.agwat.2011.08.023
   [Anonymous], 2014, REV RE GIONS ARIDES
   Araya A, 2010, AGR WATER MANAGE, V97, P1838, DOI 10.1016/j.agwat.2010.06.021
   Bhattacharya A, 2019, CHANGING CLIMATE AND RESOURCE USE EFFICIENCY IN PLANTS, P111, DOI 10.1016/B978-0-12-816209-5.00003-9
   Bird DN, 2016, SCI TOTAL ENVIRON, V543, P1019, DOI 10.1016/j.scitotenv.2015.07.035
   Boudhina N, 2019, ARAB J GEOSCI, V12, DOI 10.1007/s12517-019-4434-9
   Boudhina N, 2018, ADV SCI TECHNOL INN, P909, DOI 10.1007/978-3-319-70548-4_266
   Boudhina N, 2018, GEOSCI INSTRUM METH, V7, P151, DOI 10.5194/gi-7-151-2018
   Brisson N, 2003, EUR J AGRON, V18, P309, DOI 10.1016/S1161-0301(02)00110-7
   Brun M., 2016, PERSPECTIVE GLOBALE
   Cassel D. K., 1986, Methods of soil analysis. Part 1. Physical and mineralogical methods, P901
   Constantin J, 2015, AGR FOREST METEOROL, V206, P55, DOI 10.1016/j.agrformet.2015.02.011
   Cusicanqui J, 2013, SPAN J AGRIC RES, V11, P894, DOI 10.5424/sjar/2013114-4097
   de Wit A, 2019, AGR SYST, V168, P154, DOI 10.1016/j.agsy.2018.06.018
   Deb P, 2015, THEOR APPL CLIMATOL, V121, P649, DOI 10.1007/s00704-014-1262-4
   El Mokh F., 2017, WATER LAND SECUR DRY
   Er-Raki S, 2021, AGR WATER MANAGE, V245, DOI 10.1016/j.agwat.2020.106585
   Evett D., 2017, WATER LAND SECURITY, P67, DOI [10.1007/978-3-319- 54021-4_7, DOI 10.1007/978-3-319-54021-4_7]
   García-López J, 2014, CLIMATIC CHANGE, V124, P147, DOI 10.1007/s10584-014-1067-6
   García-Vila M, 2012, EUR J AGRON, V36, P21, DOI 10.1016/j.eja.2011.08.003
   Geerts S, 2009, AGR WATER MANAGE, V96, P1652, DOI 10.1016/j.agwat.2009.06.020
   Han CY, 2019, AGR WATER MANAGE, V218, P165, DOI 10.1016/j.agwat.2019.03.035
   Inoubli N., 2016, THESIS I NATL AGRONO
   Inoubli N, 2017, VADOSE ZONE J, V16, DOI 10.2136/vzj2017.06.0124
   International Assessment of Agricultural Knowledge Science and Technology for Development (IAASTD), 2008, EX SUMM SYNTH REP
   Jacob F, 2002, REMOTE SENS ENVIRON, V80, P36, DOI 10.1016/S0034-4257(01)00265-6
   JAMIESON PD, 1991, FIELD CROP RES, V27, P337, DOI 10.1016/0378-4290(91)90040-3
   Jonckheere I, 2004, AGR FOREST METEOROL, V121, P19, DOI 10.1016/j.agrformet.2003.08.027
   Jones JW, 2017, AGR SYST, V155, P240, DOI 10.1016/j.agsy.2016.05.014
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Kanda EK, 2018, BULG J AGRIC SCI, V24, P380
   Katerji N, 2006, AGR FOREST METEOROL, V138, P142, DOI 10.1016/j.agrformet.2006.04.006
   Katerji N, 2013, AGR WATER MANAGE, V130, P14, DOI 10.1016/j.agwat.2013.08.005
   Keating BA, 2003, EUR J AGRON, V18, P267, DOI 10.1016/S1161-0301(02)00108-9
   Kustas WP, 1996, J APPL METEOROL, V35, P110, DOI 10.1175/1520-0450(1996)035<0110:SADSMO>2.0.CO;2
   Lekshmi SUS, 2014, MEASUREMENT, V54, P92, DOI 10.1016/j.measurement.2014.04.007
   Leuning R, 2012, AGR FOREST METEOROL, V156, P65, DOI 10.1016/j.agrformet.2011.12.002
   Lovelli S, 2007, AGR WATER MANAGE, V92, P73, DOI 10.1016/j.agwat.2007.05.005
   Lu Y, 2021, FIELD CROP RES, V269, DOI 10.1016/j.fcr.2021.108182
   Masasi B, 2019, J AM WATER RESOUR AS, V55, P976, DOI 10.1111/1752-1688.12757
   Mekki I, 2006, PHYS CHEM EARTH, V31, P1048, DOI 10.1016/j.pce.2006.07.003
   Mekki I., 2003, THESIS MONTPELLIER 2, P2
   Mekki I, 2018, LAND USE POLICY, V75, P772, DOI 10.1016/j.landusepol.2018.04.004
   Mkhabela MS, 2012, AGR WATER MANAGE, V110, P16, DOI 10.1016/j.agwat.2012.03.009
   Molénat J, 2018, VADOSE ZONE J, V17, DOI 10.2136/vzj2018.04.0086
   Montes C, 2014, AGR FOREST METEOROL, V191, P64, DOI 10.1016/j.agrformet.2014.02.004
   Moriasi DN, 2015, T ASABE, V58, P1763
   Mubvuma MT, 2021, COGENT FOOD AGR, V7, DOI 10.1080/23311932.2021.1898135
   Muluneh A, 2020, J ARID ENVIRON, V179, DOI 10.1016/j.jaridenv.2020.104195
   Norouzi M, 2010, ACTA AGR SCAND B-S P, V60, P341, DOI 10.1080/09064710903005682
   Nouri H, 2020, J HYDROL, V588, DOI 10.1016/j.jhydrol.2020.125086
   Nyakudya IW, 2014, AGR WATER MANAGE, V146, P280, DOI 10.1016/j.agwat.2014.08.024
   Nyathi MK, 2018, AGR WATER MANAGE, V208, P107, DOI 10.1016/j.agwat.2018.06.012
   Pereira LS, 2015, AGR WATER MANAGE, V159, P239, DOI 10.1016/j.agwat.2015.06.006
   Qin W, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0078828
   Raes D, 2009, AGRON J, V101, P438, DOI 10.2134/agronj2008.0140s
   Raoufi RS, 2020, INT J BIOMETEOROL, V64, P1657, DOI 10.1007/s00484-020-01946-5
   Rashid MA, 2019, AGR WATER MANAGE, V222, P193, DOI 10.1016/j.agwat.2019.06.004
   Reichstein M, 2005, GLOBAL CHANGE BIOL, V11, P1424, DOI [10.1111/j.1365-2486.2005.001002.x, 10.1111/j.1365-2486.2005.001010.x]
   Robinson DA, 2008, VADOSE ZONE J, V7, P358, DOI 10.2136/vzj2007.0143
   Ruben R, 2004, FOOD POLICY, V29, P303, DOI 10.1016/j.foodpol.2004.07.004
   Salman M., 2021, FOOD AGR ORGAN, V47
   Sandhu R, 2019, AGR WATER MANAGE, V223, DOI 10.1016/j.agwat.2019.105687
   Shrestha S, 2016, MITIG ADAPT STRAT GL, V21, P15, DOI 10.1007/s11027-014-9567-2
   Silvestro PC, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9050509
   Sreelash K, 2017, J HYDROL, V546, P166, DOI 10.1016/j.jhydrol.2016.12.049
   Steduto P, 2009, AGRON J, V101, P426, DOI 10.2134/agronj2008.0139s
   Stöckle CO, 2003, EUR J AGRON, V18, P289, DOI 10.1016/S1161-0301(02)00109-0
   Todorovic M, 2009, AGRON J, V101, P509, DOI 10.2134/agronj2008.0166s
   Toumi J, 2016, AGR WATER MANAGE, V163, P219, DOI 10.1016/j.agwat.2015.09.007
   Tribouillois H, 2018, AGR FOREST METEOROL, V262, P412, DOI 10.1016/j.agrformet.2018.07.026
   Van Loo M, 2021, WATER-SUI, V13, DOI 10.3390/w13152023
   Vanuytrecht E, 2014, ENVIRON MODELL SOFTW, V51, P323, DOI 10.1016/j.envsoft.2013.10.017
   Vastola A., 2015, SUSTAINABILITY AGRO
   Walker JP, 2004, J HYDROL, V293, P85, DOI 10.1016/j.jhydrol.2004.01.008
   Wani S. P., 2009, Rainfed agriculture: unlocking the potential, px, DOI 10.1079/9781845933890.0000
   Weiss M, 2020, REMOTE SENS ENVIRON, V236, DOI 10.1016/j.rse.2019.111402
   Williams J.R., 1984, T ASAE AM SOC AGR EN
   Wolka K, 2021, J ENVIRON MANAGE, V296, DOI 10.1016/j.jenvman.2021.113187
   Xing HM, 2017, J INTEGR AGR, V16, P2444, DOI 10.1016/S2095-3119(16)61626-X
   Yang JM, 2014, AGR SYST, V127, P81, DOI 10.1016/j.agsy.2014.01.008
   Yuan M, 2013, AGR WATER MANAGE, V122, P28, DOI 10.1016/j.agwat.2013.02.006
   Zeleke KT, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9060320
   Zitouna-Chebbi R., 2009, THESIS MONTPELLIER S
   Zitouna-Chebbi R, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9020068
   Zitouna-Chebbi R, 2015, J GEOPHYS RES-ATMOS, V120, P4920, DOI 10.1002/2014JD022999
   Zitouna-Chebbi R, 2012, AGR FOREST METEOROL, V164, P123, DOI 10.1016/j.agrformet.2012.05.010
NR 90
TC 6
Z9 6
U1 4
U2 28
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0378-3774
EI 1873-2283
J9 AGR WATER MANAGE
JI Agric. Water Manage.
PD NOV 1
PY 2022
VL 273
AR 107912
DI 10.1016/j.agwat.2022.107912
EA SEP 2022
PG 16
WC Agronomy; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Water Resources
GA 4V1XP
UT WOS:000859277600001
OA Green Submitted, Bronze
DA 2025-01-10
ER

PT J
AU Orchard, S
   Schiel, DR
AF Orchard, Shane
   Schiel, David R.
TI Enabling nature-based solutions for climate change on a peri-urban
   sandspit in Christchurch, New Zealand
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Natural hazards; Natural features; Social-ecological systems; Shoreline
   management; Climate change adaptation; SLR
ID SEA-LEVEL RISE; SANDY BEACH ECOSYSTEMS; 2010-2011 CANTERBURY; COASTAL
   SQUEEZE; BRUUN RULE; SHORELINE CHANGE; CHANGE IMPACTS; MANAGEMENT;
   CONSERVATION; ADAPTATION
AB Barrier sandspits are biodiverse natural features that regulate the development of lagoon systems and are popular areas for human settlement. Despite many studies on barrier island dynamics, few have investigated the impacts of sea-level rise (SLR) on sandspits. In peri-urban settings, we hypothesised that shoreline environment change would be strongly dependent on contemporary land use decisions, whilst modern engineering capabilities also present new opportunities for working with nature. Our study site in Christchurch, New Zealand, included a unique example of SLR caused by tectonic subsidence and an associated managed retreat initiative. We used a novel scenario modelling approach to evaluate both shorelines simultaneously for 0.25m SLR increments and incorporating open coast sediment supply in 25-year periods. Our key questions addressed the potential impacts of shoreline change on open coast dune and estuarine-coast saltmarsh ecosystems and implications for the role of 'nature-based' climate change solutions. The results identify challenges for dune conservation, with a third of the dune system eliminated in the '1-m SLR in 100-year' scenario. The associated exposure of urban areas to natural hazards such as extreme storms and tsunami will likely fuel demand for seawalls unless natural alternatives can be enabled. In contrast, the managed retreat initiative on the backshore presents an opportunity to restart saltmarsh accretion processes seaward of coastal defences with the potential to reverse decades of degradation. Considering both shorelines simultaneously highlights the existence of pinch-points from opposing forces that result in small land volumes above the tidal range. Societal adaptation is delicately poised between the paradigms of resisting or accommodating nature and challenged by the long perimeter and confined nature of the sandspit feature. The use of innovative policy measures in disaster recovery contexts, as highlighted here, may offer a beneficial framework for enabling nature-based solutions to climate change and natural hazards.YY
C1 [Orchard, Shane] Univ Canterbury, Waterways Ctr Freshwater Management, Christchurch, New Zealand.
   [Orchard, Shane] Lincoln Univ, Christchurch, New Zealand.
   [Orchard, Shane; Schiel, David R.] Univ Canterbury, Marine Ecol Res Grp, Christchurch, New Zealand.
C3 University of Canterbury; University of Canterbury
RP Orchard, S (corresponding author), Univ Canterbury, Waterways Ctr Freshwater Management, Christchurch, New Zealand.; Orchard, S (corresponding author), Lincoln Univ, Christchurch, New Zealand.; Orchard, S (corresponding author), Univ Canterbury, Marine Ecol Res Grp, Christchurch, New Zealand.
EM s.orchard@waterlink.nz
OI Orchard, Shane/0000-0002-9040-6404
FU Ngai Tahu Research Centre, University of Canterbury; Coastal Restoration
   Trust of New Zealand
FX This work was funded by the Ngai Tahu Research Centre, University of
   Canterbury. Dune conservation research was supported by the Coastal
   Restoration Trust of New Zealand.
CR Adams VM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0158350
   Anderson TR, 2015, NAT HAZARDS, V78, P75, DOI 10.1007/s11069-015-1698-6
   [Anonymous], 1979, DYNAMICS MANAGEMENT
   [Anonymous], 1998, Beach processes and sedimentation
   [Anonymous], 2018, NZ NAUTICAL ALMANAC, P271
   Bardsley DK, 2010, ENVIRON MANAGE, V45, P1127, DOI 10.1007/s00267-010-9487-1
   Beavan J, 2012, NEW ZEAL J GEOL GEOP, V55, P207, DOI 10.1080/00288306.2012.697472
   Begg JG., 2015, GEOLOGY GEOMORPHOLOG, P101
   Bell R., 2017, COASTAL HAZARDS CLIM, P279
   Bergin DO., 2008, ERL0803 DUN REST TRU
   Berry A, 2013, J COASTAL RES, V29, P899, DOI 10.2112/JCOASTRES-D-12-00150.1
   BLAKE GJ, 1968, NEW ZEAL J GEOL GEOP, V11, P225, DOI 10.1080/00288306.1968.10423687
   Brown AC, 2002, ENVIRON CONSERV, V29, P62, DOI 10.1017/S037689290200005X
   BRUUN P, 1988, J COASTAL RES, V4, P627
   BRUUN P, 1983, COAST ENG, V7, P77, DOI 10.1016/0378-3839(83)90028-5
   Bruun P., 1962, J WATERWAYS HARBORS, V88, P117, DOI DOI 10.1061/JWHEAU.0000252
   Canterbury Geotechnical Database, 2014, VER LIDAR ACQ CANT E, P52
   Christchurch R., 2019, OTAKARO AVON RIVER C, P85
   Church JA, 2011, SURV GEOPHYS, V32, P585, DOI 10.1007/s10712-011-9119-1
   Cohen-Shacham E, 2019, ENVIRON SCI POLICY, V98, P20, DOI 10.1016/j.envsci.2019.04.014
   Colls A., 2009, Ecosystem-based adaptation: a natural response to climate change
   Cooper J.A.G., 2012, Pitfalls of Shoreline Stabilization: Selected Case Studies
   Cooper JAG, 2004, GLOBAL PLANET CHANGE, V43, P157, DOI 10.1016/j.gloplacha.2004.07.001
   Cowell PJ, 2006, J COASTAL RES, V22, P232, DOI 10.2112/05A-0018.1
   Cubrinovski M, 2012, NEW ZEAL J GEOL GEOP, V55, P255, DOI 10.1080/00288306.2012.699895
   Davidson-Arnott RGD, 2005, J COASTAL RES, V21, P1166, DOI 10.2112/03-0051.1
   Dean RG, 2016, COAST ENG, V114, P1, DOI 10.1016/j.coastaleng.2016.03.009
   Defeo O, 2009, ESTUAR COAST SHELF S, V81, P1, DOI 10.1016/j.ecss.2008.09.022
   Di Marco M, 2016, CONSERV BIOL, V30, P189, DOI 10.1111/cobi.12559
   Doody J. Pat, 2004, Journal of Coastal Conservation, V10, P129, DOI 10.1652/1400-0350(2004)010[0129:CSAHP]2.0.CO;2
   Dugan JE, 2010, SCIENCE, V329, P1146, DOI 10.1126/science.329.5996.1146-a
   Fallon AR, 2017, COAST MANAGE, V45, P360, DOI 10.1080/08920753.2017.1345607
   Feagin RA, 2010, ECOL SOC, V15
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Gorman RM, 2003, NEW ZEAL J MAR FRESH, V37, P567, DOI 10.1080/00288330.2003.9517190
   Grove P., 2012, R1224 ENV CANT, P57
   HALLERMEIER RJ, 1981, COAST ENG, V4, P253
   Hannah J, 2012, J GEOPHYS RES-OCEANS, V117, DOI 10.1029/2011JC007591
   Harley CDG, 2006, ECOL LETT, V9, P228, DOI 10.1111/j.1461-0248.2005.00871.x
   Harris L, 2015, OCEAN COAST MANAGE, V110, P12, DOI 10.1016/j.ocecoaman.2015.03.003
   Hart DE, 2009, J COASTAL RES, V25, P131, DOI 10.2112/07-0960.1
   HEWARD AP, 1981, EARTH-SCI REV, V17, P223, DOI 10.1016/0012-8252(81)90022-2
   Hicks DM., 1993, MODELLING LONG TERM, P22
   Hinkel J, 2014, P NATL ACAD SCI USA, V111, P3292, DOI 10.1073/pnas.1222469111
   Hoekstra JM, 2005, ECOL LETT, V8, P23, DOI 10.1111/j.1461-0248.2004.00686.x
   Hughes M.W., 2015, GSA TODAY, V25, P4, DOI [10.1130/GSATG221A.1, DOI 10.1130/GSATG221A.1]
   Jackson CW Jr, 2012, COMPUT GEOSCI-UK, V41, P199, DOI 10.1016/j.cageo.2011.08.009
   Jackson NL, 2020, GEOMORPHOLOGY, V366, DOI 10.1016/j.geomorph.2019.04.009
   Jennings MD, 2017, LANDSCAPE ECOL, V32, P195, DOI 10.1007/s10980-016-0435-1
   Jones C, 2009, NAT GEOSCI, V2, P484, DOI 10.1038/ngeo555
   Jones MB., 2007, LIFE ESTUARY ILLUSTR
   Kabisch N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08373-210239
   Kaiser A, 2012, NEW ZEAL J GEOL GEOP, V55, P67, DOI 10.1080/00288306.2011.641182
   Kirwan ML, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL045489
   Klein Y. L., 2004, Journal of Coastal Research, V20, P1080, DOI 10.2112/003-0018.1
   KOMAR PD, 1991, J COASTAL RES, V7, P895
   Kopp RE, 2014, EARTHS FUTURE, V2, P383, DOI 10.1002/2014EF000239
   Kron W, 2013, NAT HAZARDS, V66, P1363, DOI 10.1007/s11069-012-0215-4
   LEATHERMAN SP, 1983, NATURE, V301, P415, DOI 10.1038/301415a0
   Lentz EE, 2016, NAT CLIM CHANGE, V6, P696, DOI [10.1038/NCLIMATE2957, 10.1038/nclimate2957]
   LINZ, 2018, LOC MEAN SEA LEV DAT
   LINZ, 2019, TID LEV INF SURV
   LINZ, 2016, CHRISTCH 0 075M URB
   LINZ, 2017, CANT CHRISTCH SELW L
   Liu ZZ, 2021, COMMUN EARTH ENVIRON, V2, DOI 10.1038/s43247-021-00117-7
   Lorenzo-Trueba J, 2014, J GEOPHYS RES-EARTH, V119, P779, DOI 10.1002/2013JF002941
   Martinez ML, 2017, J COASTAL RES, P1, DOI 10.2112/SI77-001.1
   Martinez ML, 2016, J COASTAL RES, P303, DOI 10.2112/SI75-061.1
   March H, 2012, ECOL ECON, V82, P126, DOI 10.1016/j.ecolecon.2012.07.006
   Martínez ML, 2014, GLOBAL ENVIRON CHANG, V29, P180, DOI 10.1016/j.gloenvcha.2014.09.009
   Masselink G, 2014, MAR GEOL, V352, P321, DOI 10.1016/j.margeo.2013.11.004
   McGranahan G, 2007, ENVIRON URBAN, V19, P17, DOI 10.1177/0956247807076960
   Mckee KL, 2007, GLOBAL ECOL BIOGEOGR, V16, P545, DOI 10.1111/j.1466-8238.2007.00317.x
   McLachlan A, 2013, OCEAN COAST MANAGE, V71, P256, DOI 10.1016/j.ocecoaman.2012.10.005
   Measures R, 2013, CHC2013116 NIWA, P29
   Moore LJ, 2010, J GEOPHYS RES-EARTH, V115, DOI 10.1029/2009JF001299
   Narayan S, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0154735
   Nel R, 2014, ESTUAR COAST SHELF S, V150, P1, DOI 10.1016/j.ecss.2014.07.016
   Neumann B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118571
   New Zealand Department of Conservation, 2010, NZ COAST POL STAT
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Nordstrom KF, 2014, ESTUAR COAST SHELF S, V150, P11, DOI 10.1016/j.ecss.2013.11.003
   Nordstrom KF, 2005, RESTOR ECOL, V13, P215, DOI 10.1111/j.1526-100X.2005.00026.x
   Nunn PD, 2021, OCEAN COAST MANAGE, V205, DOI 10.1016/j.ocecoaman.2021.105554
   Orchard S., 2016, DEV FINE SCALE SALIN
   Orchard S, 2011, IMPLICATIONS NZ COAS, P46
   Orchard S., IN PRESS
   Orchard S., 2014, SAFE HAVENS PROTECTE, P83
   Orchard S., 2017, Floodplain Restoration principles for the Avon-takaro Red Zone: Case Studies and Recommendations, P40
   Orchard S, 2020, SCI TOTAL ENVIRON, V746, DOI 10.1016/j.scitotenv.2020.141241
   Orchard S, 2020, NAT HAZARDS, V103, P3609, DOI 10.1007/s11069-020-04147-w
   Otvos EG, 2012, GEOMORPHOLOGY, V139, P39, DOI 10.1016/j.geomorph.2011.10.037
   Parsons GR, 2001, COAST MANAGE, V29, P91
   Passeri DL, 2015, EARTHS FUTURE, V3, P159, DOI 10.1002/2015EF000298
   Peterson CH, 2005, BIOSCIENCE, V55, P887, DOI 10.1641/0006-3568(2005)055[0887:ATEIOB]2.0.CO;2
   Peterson GD, 2003, CONSERV BIOL, V17, P358, DOI 10.1046/j.1523-1739.2003.01491.x
   Potter SH, 2015, INT J DISAST RISK RE, V14, P6, DOI 10.1016/j.ijdrr.2015.01.014
   QGIS, 2022, QGIS Geographic Information System
   Quigley MC, 2016, TECTONOPHYSICS, V672, P228, DOI 10.1016/j.tecto.2016.01.044
   Reynolds-Fleming JV, 2005, NEW ZEAL J MAR FRESH, V39, P217, DOI 10.1080/00288330.2005.9517301
   Roberts D, 2012, ENVIRON URBAN, V24, P167, DOI 10.1177/0956247811431412
   Rosati JD, 2013, MAR GEOL, V340, P71, DOI 10.1016/j.margeo.2013.04.018
   Schiel DR, 2016, MAR FRESHWATER RES, V67, P57, DOI 10.1071/MF14295
   Schlacher TA, 2006, ETHOL ECOL EVOL, V18, P349, DOI 10.1080/08927014.2006.9522701
   Schlacher TA, 2008, MAR ECOL-EVOL PERSP, V29, P70, DOI 10.1111/j.1439-0485.2007.00204.x
   Schlacher TA, 2007, DIVERS DISTRIB, V13, P556, DOI 10.1111/j.1472-4642.2007.00363.x
   Schleupner C, 2008, OCEAN COAST MANAGE, V51, P383, DOI 10.1016/j.ocecoaman.2008.01.008
   Schoeman DS, 2014, GLOBAL CHANGE BIOL, V20, P2383, DOI 10.1111/gcb.12505
   Short A.D., 1999, BEACH SHOREFACE MORP
   Spalding MD, 2014, OCEAN COAST MANAGE, V90, P50, DOI 10.1016/j.ocecoaman.2013.09.007
   Stive MJF, 2004, CLIMATIC CHANGE, V64, P27, DOI 10.1023/B:CLIM.0000024785.91858.1d
   Stocker, 2014, CLIMATE CHANGE 2013
   Strayer DL, 2010, AQUAT SCI, V72, P127, DOI 10.1007/s00027-010-0128-9
   Team R.C., 2020, R LANG ENV STAT COMP
   Temmerman S, 2013, NATURE, V504, P79, DOI 10.1038/nature12859
   Thoms MC, 2018, GEOMORPHOLOGY, V305, P1, DOI 10.1016/j.geomorph.2018.01.021
   Tonkin & Taylor, 2017, COASTAL HAZARD ASSES
   UNEP, 2010, ECOSYSTEM BASED ADAP
   Wamsler C, 2015, ECOL SOC, V20, DOI 10.5751/ES-07489-200230
   Yohe G, 1999, GLOBAL ENVIRON CHANG, V9, P233, DOI 10.1016/S0959-3780(99)00012-6
   Zeldis J, 2011, U1114 ENV CANT, P27
NR 121
TC 7
Z9 7
U1 3
U2 26
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD SEP
PY 2021
VL 21
IS 3
AR 66
DI 10.1007/s10113-021-01791-1
PG 18
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA SP2NZ
UT WOS:000659512700001
DA 2025-01-10
ER

PT J
AU Walsh, ES
   Hudiburg, TW
AF Walsh, Eric S.
   Hudiburg, Tara W.
TI Response of avian cavity nesters and carbon dynamics to forest
   management and climate change in the Northern Rockies
SO ECOSPHERE
LA English
DT Article
DE avifauna habitat suitability; climate change; forest landscape modeling;
   interdisciplinary modeling; USFS
ID CONTERMINOUS UNITED-STATES; SEVERITY FIRE REGIMES; LAND-USE CHANGE;
   PACIFIC-NORTHWEST; CHANGE ADAPTATION; ECOSYSTEM SERVICES;
   LANDSCAPE-SCALE; GROWTH-RESPONSE; PONDEROSA PINE; CHANGE IMPACTS
AB Forest ecosystem services (e.g., carbon and nutrient cycling, biodiversity, and wood products) in many moisture-limited systems in the western USA are being impacted by climate change. Maintaining these services, increasing resiliency, and conserving wildlife habitat will depend on climate change adaptive forest management strategies. Studying the impacts of U.S. Forest Service (USFS) land management plans on long-term carbon cycling and wildlife habitat is imperative for evaluating and implementing adaptive management under climate change. In this study, we present the results of an integrated framework of forest landscape and avifauna niche suitability modeling, applied in the northern Rockies of Idaho (NRI). We report on the interactive effects of climate change, fire, and harvest management on carbon cycling and the distribution of suitable habitat of two avian cavity nesters: Flammulated Owl (Psiloscops flammeolus) and American Three-toed Woodpecker (Picoides dorsalis). The net ecosystem carbon balance (NECB) of the NRI was predicted to be negative (carbon source) at the end of the century, primarily because of harvest removals on privately managed lands. This was despite increases in net ecosystem productivity stimulated by harvest. In contrast, NECB of USFS land was positive throughout the century. This was a direct result of the Idaho Panhandle National Forest Land Management Plan (Plan) objectives that were implemented via harvest prescriptions. Under climate warming, compositional shifts in Pinus ponderosa and Pseudotsuga menziesii along with increases in mature/old-growth forest stands were in agreement with the Plan's objectives. These and additional species composition shifts also maintained the realized niche of the Flammulated Owl and increased the potential niche of the American Three-toed Woodpecker on USFS land by the end of the century. These projections highlight the potential for the NRI to remain viable wildlife habitat in a warming climate and to sequester carbon. The research demonstrates the benefits of an integration modeling framework as a tool to evaluate multi-objective forest management directives.
C1 [Walsh, Eric S.; Hudiburg, Tara W.] Univ Idaho, Dept Forest Rangeland & Fire Sci, Moscow, ID 83843 USA.
C3 University of Idaho
RP Walsh, ES (corresponding author), Univ Idaho, Dept Forest Rangeland & Fire Sci, Moscow, ID 83843 USA.
EM wals0292@alumni.uidaho.edu
RI Hudiburg, Tara/AAG-3134-2019; Walsh, Eric/ABH-5950-2020
OI Walsh, Eric/0000-0003-0077-3639
FU NSF Idaho EPSCoR Program; National Science Foundation [IIA-1301792];
   USDA NIFA McIntire-Stennis project [1004594]; NIFA [690775, 1004594]
   Funding Source: Federal RePORTER
FX We thank Kristina Bartowitz and Jeffrey Stenzel for valuable input and
   comments. This work was supported by the NSF Idaho EPSCoR Program and by
   the National Science Foundation under award number IIA-1301792 and USDA
   NIFA McIntire-Stennis project 1004594.
CR Abatzoglou JT, 2016, P NATL ACAD SCI USA, V113, P11770, DOI 10.1073/pnas.1607171113
   Abatzoglou JT, 2013, INT J CLIMATOL, V33, P121, DOI 10.1002/joc.3413
   Adams HD, 2009, P NATL ACAD SCI USA, V106, P7063, DOI 10.1073/pnas.0901438106
   Anderegg WRL, 2015, SCIENCE, V349, P528, DOI 10.1126/science.aab1833
   Anderegg WRL, 2013, NAT CLIM CHANGE, V3, P30, DOI 10.1038/nclimate1635
   [Anonymous], 1993, CENTURY SOIL ORGANIC
   [Anonymous], 2015, Forest Inventory Analysis (FIA)
   [Anonymous], 1999, ATLAS RELATIONS CLIM
   [Anonymous], 2015, Web Soil Survey
   Arno S., 1976, INT187 USDA, P29
   Arno S. F., 1979, Research Paper, Intermountain Forest and Range Experiment Station, USDA Forest Service
   Arno SF, 2000, US FOR SERV RMRS-P, V5, P225
   Bartowitz K.J., 2019, FIRE, V2, P1
   Bennett JM, 2014, DIVERS DISTRIB, V20, P1321, DOI 10.1111/ddi.12230
   Birdsey R.A., 1992, Carbon storage and accumulation in United States forests ecosystem, P51, DOI [DOI 10.5962/BHL.TITLE.94267, 10.5962/bhl.title.94267]
   Blodgett D.L., 2011, US GEOLOGICAL SURVEY
   BROWNE J, 1986, Ireland Department of Fisheries and Forestry Trade and Information Section Fishery Leaflet, P1
   Buotte PC, 2020, ECOL APPL, V30, DOI 10.1002/eap.2039
   Buotte PC, 2019, GLOBAL CHANGE BIOL, V25, P290, DOI 10.1111/gcb.14490
   Bureau of Reclamation, 2013, DOWNSCALED CMIP3 CMI
   Cadieux P, 2019, GLOB ECOL CONSERV, V17, DOI 10.1016/j.gecco.2019.e00530
   Cassell BA, 2019, ECOSPHERE, V10, DOI 10.1002/ecs2.2934
   Charney ND, 2016, ECOL LETT, V19, P1119, DOI 10.1111/ele.12650
   Charnley S, 2017, ECOL SOC, V22, DOI 10.5751/ES-08753-220122
   Chen PY, 2010, GLOBAL CHANGE BIOL, V16, P3374, DOI 10.1111/j.1365-2486.2010.02166.x
   Ciais P, 2005, NATURE, V437, P529, DOI 10.1038/nature03972
   Coops NC, 2005, ECOL MODEL, V183, P107, DOI 10.1016/j.ecolmodel.2004.08.002
   Coops NC, 2011, ECOL MODEL, V222, P2119, DOI 10.1016/j.ecolmodel.2011.03.033
   Creutzburg MK, 2017, ECOL APPL, V27, P503, DOI 10.1002/eap.1460
   Creutzburg MK, 2016, GCB BIOENERGY, V8, P357, DOI 10.1111/gcbb.12255
   Crookston L., 2012, SCHWEIZERISCHE Z FOR, V163, P70
   del Campo AD, 2014, EUR J FOREST RES, V133, P879, DOI 10.1007/s10342-014-0805-7
   Di Febbraro M, 2015, DIVERS DISTRIB, V21, P1141, DOI 10.1111/ddi.12362
   Dijak William, 2013, Computational Ecology and Software, V3, P17
   Drever MC, 2008, BIOL CONSERV, V141, P624, DOI 10.1016/j.biocon.2007.12.004
   Dudley JG, 2012, CONDOR, V114, P348, DOI 10.1525/cond.2012.110020
   Endsley K.A, 2016, ANN WILDLAND FIRE EM
   Felton A, 2016, BIOL CONSERV, V194, P11, DOI 10.1016/j.biocon.2015.11.030
   Forestry Canada Fire Danger Group, 1992, DEV CAN FOR FIR BEH
   Fryer J.L., 2016, Fire Effects Information System
   Gibson C.E., 2005, Fire history polygons for the Northern Rockies - 1889-2003
   Groves C, 1997, GREAT BASIN NAT, V57, P116
   Gustafson EJ, 2013, ECOSYSTEMS, V16, P60, DOI 10.1007/s10021-012-9596-1
   Halofsky J.E., 2018, CLIMATE CHANGE VULNE, P275
   Halofsky JE, 2013, ECOL MODEL, V266, P131, DOI 10.1016/j.ecolmodel.2013.07.003
   Halupka L, 2008, J AVIAN BIOL, V39, P95, DOI 10.1111/j.0908-8857.2008.04047.x
   Harvey A.E., 1987, INT225 USDA FOR SERV, P1
   Harvey BJ, 2014, P NATL ACAD SCI USA, V111, P15120, DOI 10.1073/pnas.1411346111
   Hayward G.D., 1994, FLAMMULATED BOREAL
   Hessl A.E., 2004, Ecophysiological parameters for Pacific Northwest trees, P1
   Holmes TP, 2014, CLIMATE CHANGE ADAPTATION AND MITIGATION MANAGEMENT OPTIONS: A GUIDE FOR NATURAL RESOURCE MANAGERS IN SOUTHERN FOREST ECOSYSTEMS, P45
   Houghton RA, 2003, TELLUS B, V55, P378, DOI 10.1034/j.1600-0889.2003.01450.x
   Hudiburg TW, 2013, ENVIRON SCI TECHNOL, V47, P13132, DOI 10.1021/es402903u
   Janowiak M.K., 2008, ESTIMATING CARBON MA
   Janowiak MK, 2014, J FOREST, V112, P424, DOI 10.5849/jof.13-094
   Jenouvrier S, 2013, GLOBAL CHANGE BIOL, V19, P2036, DOI 10.1111/gcb.12195
   Jetz W, 2007, PLOS BIOL, V5, P1211, DOI 10.1371/journal.pbio.0050157
   Joyce LA, 2009, ENVIRON MANAGE, V44, P1022, DOI 10.1007/s00267-009-9324-6
   Kellndorfer J, 2013, ORNL DAAC
   Kemp KB, 2019, ECOSPHERE, V10, DOI 10.1002/ecs2.2568
   Kotliar N. B., 2008, Fire Ecology, V4, P26
   LANDFIRE, 2014, EXIST VEG TYP LAY
   Langdon JGR, 2015, ECOSPHERE, V6, DOI 10.1890/ES14-00400.1
   Langham GM, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0135350
   Larson MA, 2004, ECOL MODEL, V180, P103, DOI 10.1016/j.ecolmodel.2003.12.054
   Law BE, 2018, P NATL ACAD SCI USA, V115, P3663, DOI 10.1073/pnas.1720064115
   Law BE, 2013, PLANT ECOL DIVERS, V6, P73, DOI 10.1080/17550874.2012.679013
   Lawler JJ, 2014, P NATL ACAD SCI USA, V111, P7492, DOI 10.1073/pnas.1405557111
   Layton-Matthews K, 2018, OECOLOGIA, V186, P907, DOI 10.1007/s00442-018-4100-z
   LeBrun JJ, 2017, LANDSCAPE ECOL, V32, P1433, DOI 10.1007/s10980-016-0463-x
   Lenihan JM, 2008, GLOBAL PLANET CHANGE, V64, P16, DOI 10.1016/j.gloplacha.2008.01.006
   Liao W, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0168880
   Liu YQ, 2013, FOREST ECOL MANAG, V294, P120, DOI 10.1016/j.foreco.2012.06.049
   Loudermilk EL, 2013, GLOBAL CHANGE BIOL, V19, P3502, DOI 10.1111/gcb.12310
   Mahon CL, 2014, FOREST ECOL MANAG, V312, P28, DOI 10.1016/j.foreco.2013.10.025
   Martin KL, 2015, ECOSYSTEMS, V18, P76, DOI 10.1007/s10021-014-9813-1
   Martin TE, 2015, J APPL ECOL, V52, P475, DOI 10.1111/1365-2664.12375
   Maurer EP, 2002, J CLIMATE, V15, P3237, DOI 10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2
   McComb B.C., 2015, Wildlife Habitat Management: Concepts and Applications in Forestry, V2nd
   McElhinny C, 2005, FOREST ECOL MANAG, V218, P1, DOI 10.1016/j.foreco.2005.08.034
   McKelvey KS, 2018, ADV GLOB CHANGE RES, V63, P143, DOI 10.1007/978-3-319-56928-4_8
   McKinley DC, 2011, ECOL APPL, V21, P1902, DOI 10.1890/10-0697.1
   Milner K. S., 1992, Western Journal of Applied Forestry, V7, P9
   Murray B.C., 2005, Greenhouse gas mitigation: Potential in US forestry and agriculture, P1
   Naficy C, 2010, ECOL APPL, V20, P1851, DOI 10.1890/09-0217.1
   National Research Council (U.S.), 2011, Climate Stabilization Targets: Emissions, Concentrations and Impacts Over Decades to Millennia
   Noormets A, 2008, NEW PHYTOL, V179, P818, DOI 10.1111/j.1469-8137.2008.02501.x
   Northern Rockies Fire Science , 2018, NO ROCK EC TYP DES
   Odion DC, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0087852
   Oliver G.V., 2010, ECOLOGICAL INTEGRITY
   Omernik JM, 2014, ENVIRON MANAGE, V54, P1249, DOI 10.1007/s00267-014-0364-1
   Onaindia M, 2013, FOREST ECOL MANAG, V289, P1, DOI 10.1016/j.foreco.2012.10.010
   Page-Dumroese DS, 2006, CAN J FOREST RES, V36, P2270, DOI 10.1139/X06-125
   Pakkala T, 2002, SILVA FENN, V36, P279, DOI 10.14214/sf.563
   Parrish JD, 2003, BIOSCIENCE, V53, P851, DOI 10.1641/0006-3568(2003)053[0851:AWCWWS]2.0.CO;2
   Parton W.J., 1996, The CENTURY model, P283, DOI DOI 10.1007/978-3-642-61094-3_23
   Pennanen J, 2002, SILVA FENN, V36, P213, DOI 10.14214/sf.559
   R Core Team, 2019, R LANG ENV STAT COMP
   Rees J.D., 2018, Ecography, V22, P31
   Reyer CPO, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5ef1
   Riley KL, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1543
   Rocca ME, 2014, FOREST ECOL MANAG, V327, P290, DOI 10.1016/j.foreco.2014.04.005
   Rupp DE, 2017, CLIM DYNAM, V49, P1783, DOI 10.1007/s00382-016-3418-7
   Rupp DE, 2013, J GEOPHYS RES-ATMOS, V118, P10884, DOI 10.1002/jgrd.50843
   Saab VA, 2009, FOREST ECOL MANAG, V257, P151, DOI 10.1016/j.foreco.2008.08.028
   Scheller RM, 2007, ECOL MODEL, V201, P409, DOI 10.1016/j.ecolmodel.2006.10.009
   Scheller RM, 2012, ECOSPHERE, V3, DOI 10.1890/ES12-00241.1
   Scheller RM, 2011, LANDSCAPE ECOL, V26, P1491, DOI 10.1007/s10980-011-9663-6
   Scheller RM, 2011, ECOL MODEL, V222, P144, DOI 10.1016/j.ecolmodel.2010.09.009
   Schiegg K, 2002, P ROY SOC B-BIOL SCI, V269, P1153, DOI 10.1098/rspb.2002.1966
   Scholer MN, 2014, J RAPTOR RES, V48, P128, DOI 10.3356/JRR-13-00049.1
   Schultz C, 2010, BIOSCIENCE, V60, P545, DOI 10.1525/bio.2010.60.7.10
   Scott L.M., 2009, Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, P27, DOI [10.1007/978-3-642-03647-7, DOI 10.1007/978-3-642-03647-7]
   Sekercioglu CH, 2012, BIOL CONSERV, V148, P1, DOI 10.1016/j.biocon.2011.10.019
   Selwood KE, 2015, BIOL REV, V90, P837, DOI 10.1111/brv.12136
   Sergio F, 2006, J APPL ECOL, V43, P1049, DOI 10.1111/j.1365-2664.2006.01218.x
   Shang ZB, 2012, ECOL MODEL, V229, P50, DOI 10.1016/j.ecolmodel.2011.08.014
   Sheehan T, 2015, ECOL MODEL, V317, P16, DOI 10.1016/j.ecolmodel.2015.08.023
   Shifley SR, 2008, FOREST ECOL MANAG, V254, P474, DOI 10.1016/j.foreco.2007.08.030
   Shuman JK, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5eed
   Siikamäki J, 2012, AMBIO, V41, P78, DOI 10.1007/s13280-011-0243-4
   Sillero N, 2011, ECOL MODEL, V222, P1343, DOI 10.1016/j.ecolmodel.2011.01.018
   Simmons E.A., 2017, IDAHOS FOREST PRODUC, P1
   Smith J K., 1997, Fire ecology of the forest habitat types of northern Idaho, P148
   Spelter H., 2002, FPLGTR131 USDA AGR
   Spies TA, 2007, ECOL APPL, V17, P48, DOI 10.1890/1051-0761(2007)017[0048:PEOFPO]2.0.CO;2
   Spies TA, 2010, LANDSCAPE ECOL, V25, P1185, DOI 10.1007/s10980-010-9483-0
   Stenzel JE, 2019, GLOBAL CHANGE BIOL, V25, P3985, DOI 10.1111/gcb.14716
   Strassburg BBN, 2010, CONSERV LETT, V3, P98, DOI 10.1111/j.1755-263X.2009.00092.x
   Strom H, 2001, ORNIS FENNICA, V78, P145
   Sturtevant BR, 2009, ECOL MODEL, V220, P3380, DOI 10.1016/j.ecolmodel.2009.07.030
   Syphard AD, 2011, INT J WILDLAND FIRE, V20, P364, DOI 10.1071/WF09125
   Thomas CD, 2013, ECOL LETT, V16, P39, DOI 10.1111/ele.12054
   Thompson RS., 2015, Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America-Revisions for all taxa from the United States and Canada and new taxa from the western United States, DOI [DOI 10.3133/PP1650G, 10.3133/pp1650g]
   Tremblay JA, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0191645
   USDA, 2017, NO REG EX VEG MAPP P
   USDA, 2015, REV LAND MAN PLAN ID
   USDA, 2015, FIR HIST POLYG REG 1
   Veloz S., 2013, Projected effects of climate change on the distribution and abundance of North Pacific birds and their habitats: Final report to the North Pacific Landscape Conservation Cooperative
   Walsh ES, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0217299
   Walsh ES, 2019, ECOL EVOL, V9, P2305, DOI 10.1002/ece3.4876
   Warziniack T., 2018, CLIMATE CHANGE VULNE
   Weed AS, 2013, ECOL MONOGR, V83, P441, DOI 10.1890/13-0160.1
   West T.O., 2014, Soil Carbon Estimates in 20-cm Layers to 1-meter Depth, Conterminous US, 1970-1993
   Whitlock C, 2003, FOREST ECOL MANAG, V178, P5, DOI 10.1016/S0378-1127(03)00051-3
   Wiebe KL, 2010, AUK, V127, P917, DOI 10.1525/auk.2010.10025
   Wiens JA, 2009, P NATL ACAD SCI USA, V106, P19729, DOI 10.1073/pnas.0901639106
   Wiggins D.A., 2004, American three-toed woodpecker (Picoides dorsalis): a technical conservation assessment [Online]
   WRIGHT DH, 1983, OIKOS, V41, P496, DOI 10.2307/3544109
   Zhao MS, 2010, SCIENCE, V329, P940, DOI [10.1126/science.1192666, 10.1126/science.1189590]
NR 150
TC 2
Z9 3
U1 1
U2 10
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2150-8925
J9 ECOSPHERE
JI Ecosphere
PD JUL
PY 2021
VL 12
IS 7
AR e03636
DI 10.1002/ecs2.3636
PG 27
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA TR1KK
UT WOS:000678730500001
OA gold
DA 2025-01-10
ER

PT J
AU Ma, WZ
   Zhan, Y
   Chen, SC
   Ren, ZQ
   Chen, XJ
   Qin, FJ
   Lu, RH
   Lv, XN
   Deng, XF
AF Ma, Wanzhu
   Zhan, Yu
   Chen, Songchao
   Ren, Zhouqiao
   Chen, Xiaojia
   Qin, Fangjin
   Lu, Ruohui
   Lv, Xiaonan
   Deng, Xunfei
TI Organic carbon storage potential of cropland topsoils in East China:
   Indispensable roles of cropping systems and soil managements
SO SOIL & TILLAGE RESEARCH
LA English
DT Article
DE Mixture duster models; SOC storage potential; Carbon landscape systems;
   Soil management practices; Random forests
ID LAND-USE CHANGE; PADDY SOILS; BASE-LINE; SEQUESTRATION; CLIMATE;
   NITROGEN; STOCK; CHALLENGES; TEXTURE; MODEL
AB Soil organic carbon (SOC) is receiving increasing attention due to its large storage potential in global carbon cycles and its great importance to soil fertility, agricultural production, and ecosystem services. The increases of SOC storage and reliable estimation of its potential are essential for evaluating the soil sustainability and climate change adaptation under intensive cultivation. In this work, a data-driven approach combining mixture clustering and Random Forest models was proposed to estimate the SOC storage potential of cropland topsoil and its controlling factors in East China. The carbon landscapes systems (CLSs) were delineated using a mixture clustering model by combining the climatic condition, soil properties, cropping systems, and soil management practices. The SOC storage potentials with 95 % confidence intervals at 250 m spatial resolution were estimated as the difference between the current SOC stock and empirically maximum SOC stock at basic (75 %), intermediate (85 %), and ambitious (95 %) expectation objectives for each CLS. The SOC storage potential increased with the increasing of expectation objective settings, with the averaged levels of 13.1, 20.8, and 35.5 t C ha(-1) at 75 %, 85 %, and 95 % percentile objectives, respectively. The variable importance from Random Forest indicated that the cropping systems and soil management practices were the unignorable factors controlling the SOC storage potential beyond the climatic conditions and soil properties. Moreover, the shifts of human-induced controlling factors, e.g., cropping systems, also indicated their capability of SOC sequestration potential for partly achieving the "4p1000" initiative (annual growth rate of 0.4 % carbon stocks in the first 30 cm of topsoil). The currently optimal soil management practices for achieving the SOC sequestration potential was the combination of rice-based cropping systems, straw return, and organic fertilizer applied. The data-driven approach coupling with CLSs improved our understanding of the controlling factors on SOC storage potential at regional level with homogenous conditions, enabling evidence-based decision making in promoting carbon sequestration by adopting locally feasible soil management practices.
C1 [Ma, Wanzhu; Ren, Zhouqiao; Chen, Xiaojia; Lv, Xiaonan; Deng, Xunfei] Zhejiang Acad Agr Sci, Inst Digital Agr, Hangzhou 310021, Zhejiang, Peoples R China.
   [Ma, Wanzhu; Ren, Zhouqiao; Lv, Xiaonan; Deng, Xunfei] Minist Agr & Rural Affairs, Key Lab Informat Traceabil Agr Prod, Hangzhou 310021, Zhejiang, Peoples R China.
   [Zhan, Yu] Sichuan Univ, Dept Environm Sci & Engn, Chengdu 610065, Sichuan, Peoples R China.
   [Zhan, Yu] Sichuan Univ Yibin Pk, Yibin Inst Ind Technol, Yibin 644000, Sichuan, Peoples R China.
   [Chen, Songchao] Natl Res Inst Agr Food & Environm INRAE, Unite InfoSol, F-45075 Orleans, France.
   [Qin, Fangjin] Stn Agr Technol Extens Ningbo City, Ningbo 315012, Zhejiang, Peoples R China.
   [Lu, Ruohui] Adm Stn Cultivated Land Qual & Fertilizer Zhejian, Hangzhou 310029, Zhejiang, Peoples R China.
C3 Zhejiang Academy of Agricultural Sciences; Ministry of Agriculture &
   Rural Affairs; Sichuan University; INRAE
RP Deng, XF (corresponding author), Zhejiang Acad Agr Sci, Inst Digital Agr, Hangzhou 310021, Zhejiang, Peoples R China.
EM dengxf@zaas.ac.cn
RI Chen, Songchao/S-7982-2019; Chen, Xiaojia/JYV-2395-2024
OI Chen, Songchao/0000-0003-1245-0482; deng, xunfei/0000-0001-7306-6199
FU National Key Research and Development Program of China [2016YFD0200802,
   2018YFD0200502]; Key Research and Development Program of Zhejiang
   Province, China [2020C02023]
FX We are grateful to Junfang Ding, Jianxia Liang, Zhen Tong,Gengmiao
   Zhang, and other colleagues for their assistance in document collecting,
   field sampling, and laboratory analyses. This research was supported by
   the National Key Research and Development Program of China
   (2016YFD0200802, 2018YFD0200502) , and the Key Research and Development
   Program of Zhejiang Province, China (2020C02023) .
CR Adair EC, 2008, GLOBAL CHANGE BIOL, V14, P2636, DOI 10.1111/j.1365-2486.2008.01674.x
   Angers DA, 2011, SOIL USE MANAGE, V27, P448, DOI 10.1111/j.1475-2743.2011.00366.x
   [Anonymous], 1996, EVALUATION SOIL ORGA
   [Anonymous], 2001, Machine Learning
   Barre P., 2017, Biogeosci. Discuss, P1, DOI DOI 10.5194/BG-2017-395
   Batjes NH, 1996, EUR J SOIL SCI, V47, P151, DOI [10.1111/j.1365-2389.1996.tb01386.x, 10.1111/ejss.12114_2]
   Batjes NH, 2019, LAND DEGRAD DEV, V30, P25, DOI 10.1002/ldr.3209
   Batjes NH, 2017, EARTH SYST SCI DATA, V9, P1, DOI 10.5194/essd-9-1-2017
   Bolinder MA, 2007, AGR ECOSYST ENVIRON, V118, P29, DOI 10.1016/j.agee.2006.05.013
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Chen SC, 2019, SCI TOTAL ENVIRON, V666, P355, DOI 10.1016/j.scitotenv.2019.02.249
   Chen SC, 2018, SCI TOTAL ENVIRON, V630, P389, DOI 10.1016/j.scitotenv.2018.02.209
   Chenu C, 2019, SOIL TILL RES, V188, P41, DOI 10.1016/j.still.2018.04.011
   CMDC China Meteorological Data Center, 2020, MONTHL STAND DAT GRO
   Deng XF, 2018, AGR ECOSYST ENVIRON, V254, P213, DOI 10.1016/j.agee.2017.11.022
   Deng XF, 2016, SCI TOTAL ENVIRON, V565, P539, DOI 10.1016/j.scitotenv.2016.05.042
   Dignac MF, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-017-0421-2
   Elith J, 2008, J ANIM ECOL, V77, P802, DOI 10.1111/j.1365-2656.2008.01390.x
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Hassink J, 1997, PLANT SOIL, V191, P77, DOI 10.1023/A:1004213929699
   Hengl T, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0169748
   Iovleff S, 2016, MIXALL CLUSTERING MI
   Jandl R, 2007, GEODERMA, V137, P253, DOI 10.1016/j.geoderma.2006.09.003
   Jobbágy EG, 2000, ECOL APPL, V10, P423, DOI 10.2307/2641104
   Lal R, 2004, GEODERMA, V123, P1, DOI 10.1016/j.geoderma.2004.01.032
   Lal R, 2016, J SOIL WATER CONSERV, V71, p20A, DOI 10.2489/jswc.71.1.20A
   Li J, 2011, ENVIRON MODELL SOFTW, V26, P1647, DOI 10.1016/j.envsoft.2011.07.004
   Lilly A, 2013, SOIL USE MANAGE, V29, P39, DOI 10.1111/sum.12009
   Lugato E, 2014, GLOBAL CHANGE BIOL, V20, P313, DOI 10.1111/gcb.12292
   Mathew I, 2020, GEODERMA, V367, DOI 10.1016/j.geoderma.2020.114230
   McBratney AB, 2014, PROGR SOIL SCI, P3, DOI 10.1007/978-3-319-04084-4_1
   Miller AJ, 2004, BIOGEOCHEMISTRY, V67, P57, DOI 10.1023/B:BIOG.0000015302.16640.a5
   Minasny B, 2017, GEODERMA, V292, P59, DOI 10.1016/j.geoderma.2017.01.002
   Minasny B, 2013, ADV AGRON, V118, P1, DOI 10.1016/B978-0-12-405942-9.00001-3
   Minasny B, 2012, GLOBAL BIOGEOCHEM CY, V26, DOI 10.1029/2012GB004406
   Mulder VL, 2015, GLOBAL BIOGEOCHEM CY, V29, P1210, DOI 10.1002/2015GB005178
   Nielsen SF, 2000, BERNOULLI, V6, P457, DOI 10.2307/3318671
   Pan GX, 2010, AGR ECOSYST ENVIRON, V136, P133, DOI 10.1016/j.agee.2009.12.011
   Pan GX, 2004, GLOBAL CHANGE BIOL, V10, P79, DOI 10.1111/j.1365-2486.2003.00717.x
   Paradelo R, 2015, AGR ECOSYST ENVIRON, V202, P98, DOI 10.1016/j.agee.2015.01.005
   PARTON WJ, 1994, SSSA SPEC PUBL, P147
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   Post WM, 2000, GLOBAL CHANGE BIOL, V6, P317, DOI 10.1046/j.1365-2486.2000.00308.x
   R Core Team, 2019, R LANG ENV STAT COMP
   Rumpel C., 2019, AMBIO
   Running S., 2015, NASA EOSDIS Land Processes DAAC, P660, DOI DOI 10.5067/MODIS/MOD17A2H.006
   Sierra CA, 2015, J ADV MODEL EARTH SY, V7, P335, DOI 10.1002/2014MS000358
   Six J, 2000, SOIL BIOL BIOCHEM, V32, P2099, DOI 10.1016/S0038-0717(00)00179-6
   Smith J, 2005, GLOBAL CHANGE BIOL, V11, P2141, DOI 10.1111/j.1365-2486.2005.001075.x
   SOLARGIS, 2020, GLOB SOL ATL
   Soussana JF, 2019, SOIL TILL RES, V188, P3, DOI 10.1016/j.still.2017.12.002
   Stockmann U, 2013, AGR ECOSYST ENVIRON, V164, P80, DOI 10.1016/j.agee.2012.10.001
   Stolbovoy V., 2008, Threats to soil quality in Europe, P87
   Tao FL, 2019, SOIL TILL RES, V186, P70, DOI 10.1016/j.still.2018.10.009
   Wang F., 2011, EVALUATION SOIL FERT, Vfirst, P47
   Wang H, 2014, ECOL ENG, V70, P206, DOI 10.1016/j.ecoleng.2014.05.027
   Wang MY, 2013, PEDOSPHERE, V23, P799, DOI 10.1016/S1002-0160(13)60071-5
   Wang SL, 2004, ENVIRON MANAGE, V33, pS200, DOI 10.1007/s00267-003-9130-5
   Wang S, 2020, PEERJ, V8, DOI 10.7717/peerj.9126
   Wiesmeier M, 2014, GLOBAL CHANGE BIOL, V20, P653, DOI 10.1111/gcb.12384
   Wiesmeier M, 2011, PLANT SOIL, V340, P7, DOI 10.1007/s11104-010-0425-z
   Wissing L, 2014, GEODERMA, V228- 229, P90, DOI DOI 10.1016/j.geoderma.2013.12.012
   Wissing L, 2013, SOIL TILL RES, V126, P60, DOI 10.1016/j.still.2012.08.004
   Yan Y, 2012, AGR ECOSYST ENVIRON, V150, P102, DOI 10.1016/j.agee.2012.01.024
   Zhang HX, 2015, PADDY WATER ENVIRON, V13, P495, DOI 10.1007/s10333-014-0467-6
   Zhang H, 2017, SCI TOTAL ENVIRON, V592, P704, DOI 10.1016/j.scitotenv.2017.02.146
   Zhang LM, 2019, GEODERMA, V337, P1105, DOI 10.1016/j.geoderma.2018.11.026
   ZJSSO Zhejiang Soil Survey Office, 1994, ZHEJ SOIL, P391
   Zomer RJ, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-15794-8
NR 69
TC 8
Z9 8
U1 8
U2 70
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0167-1987
EI 1879-3444
J9 SOIL TILL RES
JI Soil Tillage Res.
PD JUL
PY 2021
VL 211
AR 105052
DI 10.1016/j.still.2021.105052
EA MAY 2021
PG 12
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA TE5LY
UT WOS:000670055800004
DA 2025-01-10
ER

PT J
AU Masuda, YJ
   Castro, B
   Aggraeni, I
   Wolff, NH
   Ebi, K
   Garg, T
   Game, ET
   Krenz, J
   Spector, J
AF Masuda, Yuta J.
   Castro, Brianna
   Aggraeni, Ike
   Wolff, Nicholas H.
   Ebi, Kristie
   Garg, Teevrat
   Game, Edward T.
   Krenz, Jennifer
   Spector, June
TI How are healthy, working populations affected by increasing temperatures
   in the tropics? Implications for climate change adaptation policies
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate change; Heat exposure; Deforestation; Human well-being;
   Adaptation; Livelihoods
ID HEAT-STRESS; LAND-COVER; OCCUPATIONAL-HEALTH; KIDNEY-FUNCTION; RISK;
   FORESTS; INJURY; PRODUCTIVITY; PERCEPTIONS; MORTALITY
AB Climate change and land use change are increasing average and extreme temperatures. Hotter temperatures can detrimentally affect workers' health and their economic productivity and livelihoods, especially in rural areas in industrializing countries that may be more vulnerable and less resilient. A growing literature has examined these factors at large spatial scales, yet few studies have done so at finer scales. Micro-level data from developing regions is needed to understand the extent of heat exposure, as well as current and future adaptation strategies of working, healthy, and rural populations. We fill this gap using objective environmental measurements from 3M (TM) Questemp (TM) 46 Heat Stress Monitors, as well as survey data from working, healthy, and rural communities in East Kalimantan, Indonesia. Our data contain two groups: those who work in only open areas, and those who work in both forests and open areas. We document workers' livelihood strategies, work schedules, perceptions of how temperatures impact their work, and future adaptation strategies for even hotter days. Ambient tempera. tures are 2.6-8.3 degrees C cooler in forests compared to open areas, indicating the temperature effects of deforestation can be immediate and significant. Those working only in open areas face up to 6.5 h of exposure to temperatures above the accepted Threshold Limit Value for worker well-being. Workers adapt to hotter temperatures by altering the timing of their work shifts and breaks, indicating our sample is already adapting to increasing temperatures from climate and land use change. We also find differential adaptation strategies between those working only in open areas compared to those working in both forests and open areas, suggesting current acclimatization may be a factor in how people adapt. Our results suggest the need for adaptation and mitigation policies tailored to the unique constraints of rural workers that specifically incorporate extant adaptation strategies.
C1 [Masuda, Yuta J.; Wolff, Nicholas H.; Game, Edward T.] Nature Conservancy, Global Sci, Arlington, VA USA.
   [Castro, Brianna] Harvard Univ, Dept Sociol, Cambridge, MA 02138 USA.
   [Aggraeni, Ike] Mulawarman Univ, Fac Publ Hlth, Samarinda, Indonesia.
   [Ebi, Kristie; Krenz, Jennifer; Spector, June] Univ Washington, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USA.
   [Ebi, Kristie] Univ Washington, Dept Global Hlth, Seattle, WA 98195 USA.
   [Garg, Teevrat] Univ Calif San Diego, Sch Global Policy & Strategy, San Diego, CA 92103 USA.
C3 Nature Conservancy; Harvard University; Universitas Mulawarman;
   University of Washington; University of Washington Seattle; University
   of Washington; University of Washington Seattle; University of
   California System; University of California San Diego
RP Masuda, YJ (corresponding author), Nature Conservancy, 4245 Fairfax Dr 100, Arlington, VA 22203 USA.
EM ymasuda@tnc.org
RI Game, Edward/AAD-2289-2020; Castro, Brianna/KMA-4001-2024; Ebi,
   Kristie/AFK-6769-2022
OI Wolff, Nicholas/0000-0003-1162-3556; Game, Edward/0000-0003-4707-9281;
   Ebi, Kristie/0000-0003-4746-8236
CR Anggraeni I., 2018, PEERJ PREPR, DOI [10.7287/peerj.preprints.27375v1, DOI 10.7287/PEERJ.PREPRINTS.27375V1]
   [Anonymous], 2015, THRESH LIM VAL CHEM
   Baez J, 2017, AM ECON REV, V107, P446, DOI 10.1257/aer.p20171053
   Bank A. D., 2017, REG RISK HUM DIM CLI, DOI [10.22617/TCS178839-2, DOI 10.22617/TCS178839-2]
   BAPPENAS, 2013, 35 BAPPENAS
   Barreca A., 2013, Adapting to climate change: The remarkable decline in the U.S. temperaturemortality relationship over the 20th century, DOI [10.3386/w18692, DOI 10.3386/W18692]
   Barrett CB, 2016, ANNU REV RESOUR ECON, V8, P303, DOI 10.1146/annurev-resource-100815-095235
   Bathiany S, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aar5809
   Berau B. P. S. K., 2017, KAB BER DAL ANGK BER
   Berry HL, 2010, INT J PUBLIC HEALTH, V55, P123, DOI 10.1007/s00038-009-0112-0
   Bonan GB, 2008, SCIENCE, V320, P1444, DOI 10.1126/science.1155121
   Bright RM, 2017, NAT CLIM CHANGE, V7, P296, DOI [10.1038/nclimate3250, 10.1038/NCLIMATE3250]
   Burke M, 2016, SCIENCE, V352, P292, DOI 10.1126/science.aad9634
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Cantley LF, 2016, OCCUP ENVIRON MED, V73, P229, DOI 10.1136/oemed-2015-102831
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   Chow WTL, 2016, URBAN FOR URBAN GREE, V16, P62, DOI 10.1016/j.ufug.2016.01.010
   Coffel ED, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa00e
   Crowe J, 2015, AM J IND MED, V58, P541, DOI 10.1002/ajim.22450
   de Sherbinin A, 2011, SCIENCE, V334, P456, DOI 10.1126/science.1208821
   Dunne JP, 2013, NAT CLIM CHANGE, V3, P563, DOI 10.1038/NCLIMATE1827
   Ellison D, 2017, GLOBAL ENVIRON CHANG, V43, P51, DOI 10.1016/j.gloenvcha.2017.01.002
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fogleman M, 2005, INT J IND ERGONOM, V35, P47, DOI 10.1016/j.ergon.2004.08.003
   Garg Teevrat., 2018, Temperature and human capital in India
   Gasparrini A, 2017, LANCET PLANET HEALTH, V1, pE360, DOI 10.1016/S2542-5196(17)30156-0
   Griscom BW, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0146357
   Hajat S, 2010, J EPIDEMIOL COMMUN H, V64, P753, DOI 10.1136/jech.2009.087999
   Hanson MA, 2012, SCIENCE, V335, P851, DOI [10.1126/science.1244693, 10.1126/science.1215904]
   Harrington LJ, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/5/055007
   Hondula DM, 2015, CURR CLIM CHANGE REP, V1, P144, DOI 10.1007/s40641-015-0016-4
   Houghton RA, 2017, GLOBAL BIOGEOCHEM CY, V31, P456, DOI 10.1002/2016GB005546
   Hsiang SM, 2016, SCI REP-UK, V6, DOI 10.1038/srep25697
   Hughes AC, 2018, BIOL CONSERV, V223, P129, DOI 10.1016/j.biocon.2018.04.029
   Iglesias A, 2011, EUR REV AGRIC ECON, V38, P427, DOI 10.1093/erae/jbr037
   Kakota T, 2011, CLIM DEV, V3, P298, DOI 10.1080/17565529.2011.627419
   Kjellstrom T., 2009, Climate change exposures, chronic diseases and mental health in urban populations-a threat to health security, particularly for the poor and disadvantaged
   Kjellstrom Tord, 2017, WHO South East Asia J Public Health, V6, P15, DOI 10.4103/2224-3151.213786
   Kjellstrom T, 2016, ANNU REV PUBL HEALTH, V37, P97, DOI 10.1146/annurev-publhealth-032315-021740
   Kjellstrom T, 2009, GLOBAL HEALTH ACTION, V2, DOI [10.3402/gha.v2i0.1958, 10.3402/gha.v2i0.2047]
   Kwasi F., 2014, Sustainable Agriculture Research, V3, P56
   Le Quéré C, 2015, EARTH SYST SCI DATA, V7, P349, DOI 10.5194/essd-7-349-2015
   Lee M., 2016, EFFECTS TEMPERATURE, DOI [10.2139/ssrn.2894767, DOI 10.2139/SSRN.2894767]
   Malik A., 2010, Institute for International Economic Policy Working Paper Series, P1
   Mani M., 2018, South Asia's Hotspots: The Impact of Temperature and Precipitation Changes on Living Standards, DOI DOI 10.1596/978-1-4648-1155-5
   Margono BA, 2014, NAT CLIM CHANGE, V4, P730, DOI [10.1038/nclimate2277, 10.1038/NCLIMATE2277]
   Marx SM, 2007, GLOBAL ENVIRON CHANG, V17, P47, DOI 10.1016/j.gloenvcha.2006.10.004
   McAlpine CA, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa4ff
   McKinnon M., 2016, Climate Change and Labour: Impacts of Heat in the Workplace
   Menne MJ, 2012, J ATMOS OCEAN TECH, V29, P897, DOI 10.1175/JTECH-D-11-00103.1
   Mersha AA, 2018, WORLD DEV, V107, P87, DOI 10.1016/j.worlddev.2018.03.001
   Moore F. C., 2019, P NATL ACAD SCI USA, DOI [10.1073/pnas.1816541116.201816541, DOI 10.1073/PNAS.1816541116.201816541]
   Mora C, 2017, CIRC-CARDIOVASC QUAL, V10, DOI 10.1161/CIRCOUTCOMES.117.004233
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Morabito M, 2006, IND HEALTH, V44, P458, DOI 10.2486/indhealth.44.458
   Moyce S, 2017, OCCUP ENVIRON MED, V74, P402, DOI 10.1136/oemed-2016-103848
   Mueller B, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/4/044011
   Mueller V, 2014, NAT CLIM CHANGE, V4, P182, DOI [10.1038/nclimate2103, 10.1038/NCLIMATE2103]
   Nikolopoulou M, 2003, ENERG BUILDINGS, V35, P95, DOI 10.1016/S0378-7788(02)00084-1
   Orlove B, 2010, CLIMATIC CHANGE, V100, P243, DOI 10.1007/s10584-009-9586-2
   Parsons K.C., 2002, HUMAN THERMAL ENV EF
   Parsons K, 2013, IND HEALTH, V51, P86, DOI 10.2486/indhealth.2012-0165
   Peckham TK, 2017, ANN WORK EXPOS HEAL, V61, P3, DOI 10.1093/annweh/wxw011
   Pellier AS, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103005
   Peraza S, 2012, AM J KIDNEY DIS, V59, P531, DOI 10.1053/j.ajkd.2011.11.039
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Quiller G, 2017, ARCH ENVIRON OCCUP H, V72, P313, DOI 10.1080/19338244.2017.1288077
   Raines N, 2014, MEDICC REV, V16, P16, DOI 10.37757/MR2014.V16.N2.4
   Ramdani F, 2014, CLIMATIC CHANGE, V123, P189, DOI 10.1007/s10584-013-1045-4
   Renton A., 2009, 130 OXF
   Rigaud KantaKumari., 2018, GROUNDSWELL PREPARIN
   Rogelj J, 2012, NAT CLIM CHANGE, V2, P248, DOI [10.1038/NCLIMATE1385, 10.1038/nclimate1385]
   Schlenker W, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014010
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Scott CE, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-017-02412-4
   Semenza JC, 1999, AM J PREV MED, V16, P269, DOI 10.1016/S0749-3797(99)00025-2
   Song XP, 2018, NATURE, V560, P639, DOI 10.1038/s41586-018-0411-9
   Spector JT, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0164498
   Spector JT, 2014, ANN OCCUP HYG, V58, P936, DOI 10.1093/annhyg/meu073
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   Stocker TF., 2013, The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P3
   Struebig MJ, 2015, CURR BIOL, V25, P372, DOI 10.1016/j.cub.2014.11.067
   Taraz V, 2017, ENVIRON DEV ECON, V22, P517, DOI [10.1017/S1355770X17000195, 10.1017/s1355770x17000195]
   Tawatsupa B, 2013, IND HEALTH, V51, P34, DOI 10.2486/indhealth.2012-0138
   Tawatsupa B, 2012, J EPIDEMIOL, V22, P251, DOI 10.2188/jea.JE20110082
   Thiede B., 2017, GLOBAL ENVIRON CHANG, V41, P228, DOI [10.1016/j.gloenveha.2016.10.005, DOI 10.1016/J.GLOENVEHA.2016.10.005]
   TVERSKY A, 1991, Q J ECON, V106, P1039, DOI 10.2307/2937956
   Verbesselt J, 2016, NAT CLIM CHANGE, V6, P1028, DOI [10.1038/nclimate3108, 10.1038/NCLIMATE3108]
   Watts N., 2017, LANCET COUNTDOWN HLT, DOI [10.1016/S0140-6736(17)32464-9, DOI 10.1016/S0140-6736(17)32464-9]
   Weber EU, 2006, CLIMATIC CHANGE, V77, P103, DOI 10.1007/s10584-006-9060-3
   Whitmee S, 2015, LANCET, V386, P1973, DOI 10.1016/S0140-6736(15)60901-1
   Wolff N. H., 2018, GLOB ENV CHANGE
   Zivin JG, 2014, J LABOR ECON, V32, P1, DOI 10.1086/671766
NR 93
TC 43
Z9 46
U1 1
U2 31
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0959-3780
EI 1872-9495
J9 GLOBAL ENVIRON CHANG
JI Glob. Environ. Change-Human Policy Dimens.
PD MAY
PY 2019
VL 56
BP 29
EP 40
DI 10.1016/j.gloenvcha.2019.03.005
PG 12
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA IB1VN
UT WOS:000470053200004
OA hybrid
DA 2025-01-10
ER

PT J
AU dos Santos, GMADA
   dos Santos, AR
   Teixeira, LJQ
   Saraiva, SH
   Freitas, DF
   Pereira, OD
   Ribeiro, CAAS
   Lorenzon, AS
   Eugenio, FC
   Neves, AA
   de Queiroz, MELR
   Scherer, R
AF Dino Alves dos Santos, Gleissy Mary Amaral
   dos Santos, Alexandre Rosa
   Quintao Teixeira, Luciano Jose
   Saraiva, Sergio Henriques
   Freitas, Deivid Franca
   Pereira, Olavo dos Santos, Jr.
   Alvares Soares Ribeiro, Carlos Antonio
   Lorenzon, Alexandre Simoes
   Eugenio, Fernando Coelho
   Neves, Antonio Augusto
   Lopes Ribeiro de Queiroz, Maria Eliana
   Scherer, Rodrigo
TI GIS applied to agriclimatological zoning and agrotoxin residue
   monitoring in tomatoes: A case study in Espirito Santo state, Brazil
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Geotechnology; Multiresidue analysis; Health; Global warming
ID PERMANENT PRESERVATION AREAS; CLIMATE-CHANGE ADAPTATION; LAND-USE
   CHANGES; HUMAN HEALTH; VALIDATION; PESTICIDES; EXPOSURE; LYCOPENE;
   IMPACTS; YIELD
AB Searches related to global warming have provided important insights into the response of terrestrial ecosystems, but few have examined the impacts on agricultural crops, particularly those associated with the monitoring of agrotoxin residues. In this context, the agriclimatological zoning is an important tool in the planning and consolidation of crops and should be considered in any initiative that involves such planning. This tool is particularly important in the analysis of agrotoxin residues and may be applied by the Program Analysis of Agrotoxin Residues in Food (PARA) created by the National Health Vigilance Agency of Brazil (ANVISA), which enables greater food security and contributes to the improvement of human health. The aim of this study was to elaborate the current and future agriclimatological zoning for the tomato crop, relating it with the monitoring of samples collected by PARA in Espirito Santo State, Brazil. The results indicate that a temperature increase of 5 degrees C creates a decrease in apt areas from 37.3% to 43%, for a total reduction of 33 percentage points (-88.5%). It is noted that of the 41 producing municipalities, only 26 have apt areas greater than 50%, highlighting the municipalities with apt areas greater than 90%, represented by Mantenopolis (100%), Guacui (98.5%), Sao Jose do Calcado (97.8%), Irupi (94.4%), Santa Teresa (92.3%), and Marechal Floriano (91.4%). The veracity of agriclimatological zoning is proved by a Kendall rank correlation coefficient of 0.876, indicating that the distribution of the variables of apt areas and productivity are similar at the significance level of 0.05 with a confidence interval 95%. After validation of the agriclimatological zoning for the tomato crop, it is recommended that the PARA should monitor 36 municipalities rather than the current 18, representing an increase of 100%. The methodology can be adjusted to agricultural crops of other countries. (c) 2015 Elsevier Ltd. All rights reserved.
C1 [Dino Alves dos Santos, Gleissy Mary Amaral; Neves, Antonio Augusto; Lopes Ribeiro de Queiroz, Maria Eliana] Fed Univ Vicosa UFV, PostGrad Programme Agrochem, BR-36570000 Vicosa, MG, Brazil.
   [dos Santos, Alexandre Rosa] Fed Univ Espirito Santo UFES, Dept Rural Engn, BR-29500000 Alegre, ES, Brazil.
   [Quintao Teixeira, Luciano Jose; Saraiva, Sergio Henriques] Fed Univ Espirito Santo UFES, Dept Food Engn, BR-29500000 Alegre, ES, Brazil.
   [Freitas, Deivid Franca] Fed Univ Norte Fluminense Darcy Ribeiro UENF, PostGrad Programme Biosci & Biotechnol, BR-29500000 Campos Dos Goytacazes, RJ, Brazil.
   [Pereira, Olavo dos Santos, Jr.] Fed Univ Juiz de Fora UFJF, Fac Pharm & Biochem, BR-36037000 Juiz De Fora, MG, Brazil.
   [Alvares Soares Ribeiro, Carlos Antonio; Lorenzon, Alexandre Simoes] Fed Univ Vicosa UFV, Dept Forest Engn, BR-36570000 Vicosa, MG, Brazil.
   [Eugenio, Fernando Coelho] Fed Univ Espirito Santo UFES, PostGrad Programme Forest Sci, BR-29500000 Alegre, ES, Brazil.
   [Scherer, Rodrigo] Univ Vila Velha UVV, Dept Nat Prod, BR-29102920 Vila Velha, ES, Brazil.
C3 Universidade Federal do Espirito Santo; Universidade Federal do Espirito
   Santo; Universidade Federal de Juiz de Fora; Universidade Federal do
   Espirito Santo; Centro Universitario Vila Velha
RP dos Santos, AR (corresponding author), Fed Univ Espirito Santo UFES, Dept Rural Engn, Alto Univ S-N, BR-29500000 Alegre, ES, Brazil.
EM gleissym@yahoo.com.br; alexandre.santos@pq.cnpq.br;
   luqteixeira@yahoo.com.br; sergiohsaraiva@gmail.com; dfnaweb@gmail.com;
   olavo.pereira@ufjf.edu.br; cribeiro@ufv.br; alelorenzon@yahoo.com.br;
   coelho.fernando@yahoo.com.br; aneves@ufv.br; meliana@ufv.br;
   rodrigo.scherer@uvv.br
RI Oliveira Ribeiro, Ciro/A-5199-2008; Eugenio, Fernando/AAW-9546-2021;
   Teixeira, Luciano/Z-3565-2019; dos Santos, Alexandre/JAO-0274-2023;
   Ribeiro, Carlos Antonio/E-7856-2015; Saraiva, Sergio
   Henriques/AAE-1419-2020; Rosa dos Santos, Alexandre/Q-5978-2016;
   Scherer, Rodrigo/J-8594-2012; Simoes Lorenzon, Alexandre/AAI-1474-2020
OI Ribeiro, Carlos Antonio/0000-0003-0514-6853; Saraiva, Sergio
   Henriques/0000-0003-0158-9155; Rosa dos Santos,
   Alexandre/0000-0003-2617-9451; Scherer, Rodrigo/0000-0001-7656-0248;
   Simoes Lorenzon, Alexandre/0000-0001-7733-2730; Coelho Eugenio,
   Fernando/0000-0002-1148-1167; Neves, Antonio/0000-0002-2152-6736;
   Quintao Teixeira, Luciano Jose/0000-0003-2546-615X
CR Adenle AA, 2015, J ENVIRON MANAGE, V161, P261, DOI 10.1016/j.jenvman.2015.05.040
   [Anonymous], 2008, REV ESC ENFERM USP, DOI DOI 10.1590/S0080
   ANVISA - Agencia Nacional de Vigilancia Sanitaria, 2014, BRASIL PROGR AN RES, P32
   ANVISA - Agenda Nacional de Vigilancia Sanitaria, 2011, PROGRAMS DE ANALISE, P26
   Archie KM, 2014, J ENVIRON MANAGE, V133, P397, DOI 10.1016/j.jenvman.2013.12.015
   Assad ED, 2004, PESQUI AGROPECU BRAS, V39, P1057, DOI 10.1590/S0100-204X2004001100001
   Caldiz DO, 2002, AGR ECOSYST ENVIRON, V88, P3, DOI 10.1016/S0167-8809(01)00160-8
   Campanharo WA, 2011, SCI FOR, V39, P105
   Cantarutti T.F.P., 2009, REV ECOTOXICOLOGIA M, V18, P9
   Carreño J, 2007, ENVIRON RES, V103, P55, DOI 10.1016/j.envres.2006.06.007
   Clinton SK, 1998, NUTR REV, V56, P35, DOI 10.1111/j.1753-4887.1998.tb01691.x
   Cockshull K.E, 1992, ACTA HORTIC, V312, P77
   Costanza JK, 2015, J ENVIRON MANAGE, V151, P186, DOI 10.1016/j.jenvman.2014.12.032
   Cressie N. A. C., 1991, STAT SPATIAL DATA, P920
   da Silva KG, 2015, CERNE, V21, P311, DOI 10.1590/01047760201521021562
   Peluzio TMD, 2013, CIENC FLOREST, V23, P537, DOI 10.5902/198050989298
   Sabatini MD, 2007, J ENVIRON MANAGE, V83, P198, DOI 10.1016/j.jenvman.2006.02.005
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   El-Khoury A, 2015, J ENVIRON MANAGE, V151, P76, DOI 10.1016/j.jenvman.2014.12.012
   Eugenio FC, 2011, CERNE, V17, P563, DOI 10.1590/S0104-77602011000400016
   Ferrari J. L., 2012, Revista Brasileira de Ciencias Agrarias (Agraria), V7, P133
   Ferrari JL, 2015, FLORESTA AMBIENTE, V22, P307, DOI 10.1590/2179-8087.042113
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fu BH, 2015, J ENVIRON MANAGE, V157, P127, DOI 10.1016/j.jenvman.2015.04.021
   Geng QL, 2014, ECOL INDIC, V40, P43, DOI 10.1016/j.ecolind.2014.01.003
   Gfrerer M, 2005, ANAL CHIM ACTA, V533, P203, DOI 10.1016/j.aca.2004.11.016
   Gibson G, 2008, REV PANAM SALUD PUBL, V24, P240, DOI 10.1590/S1020-49892008001000003
   Giordano L.B., 2000, TOMATE PROCESSAMENTO, P168
   Hayden KM, 2010, NEUROLOGY, V74, P1524, DOI 10.1212/WNL.0b013e3181dd4423
   IDAF - Institute de Defesa Agropecuaria e Florestal do ES, 2012, BRASIL RES AN REAL P
   Klippel AH, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0134877
   Lago I, 2008, PESQUI AGROPECU BRAS, V43, P1441, DOI 10.1590/S0100-204X2008001100001
   Luppi ASL, 2015, FLORESTA AMBIENTE, V22, P13, DOI 10.1590/2179-8087.0027
   Lindner M, 2014, J ENVIRON MANAGE, V146, P69, DOI 10.1016/j.jenvman.2014.07.030
   LIRA S. A., 2006, RECIE CIENCIA ENGENH, V15, P45
   Londres F, 2011, AGROTOXICOS BRASIL G, P190
   MANRIQUE LA, 1993, J PLANT NUTR, V16, P2411, DOI 10.1080/01904169309364697
   Marín AI, 2015, SCI TOTAL ENVIRON, V532, P435, DOI 10.1016/j.scitotenv.2015.05.029
   Marin FR, 2013, CLIMATIC CHANGE, V117, P227, DOI 10.1007/s10584-012-0561-y
   Mazzini P. L. F., 2009, Brazilian Journal of Aquatic Science & Technology, V13, P53
   MIRANDA E.E, 2005, BRASIL EM RELEVO
   Moreira TR, 2015, FLORESTA AMBIENTE, V22, P141, DOI 10.1590/2179-8087.019012
   Nguyen ML, 1998, P SOC EXP BIOL MED, V218, P101, DOI 10.3181/00379727-218-44274
   Ometto J.C., 1981, BIOCLIMATOLOGIA VEGE, P435
   Paroissien JB, 2015, J ENVIRON MANAGE, V150, P57, DOI [10.1016/j.jenvman.2014.10.034, 1]
   PEREIRA A.R., 2002, Agrometeorologia: fundamentos e aplicacoes praticas, P478
   Peres F, 2007, CAD SAUDE PUBLICA, V23, pS612, DOI 10.1590/S0102-311X2007001600021
   Pires Dario Xavier, 2005, Cad. Saúde Pública, V21, P598, DOI 10.1590/S0102-311X2005000200027
   Pirovani DB, 2015, CERNE, V21, P27, DOI 10.1590/01047760201521011182
   Pirovani DB, 2014, REV ARVORE, V38, P271, DOI 10.1590/S0100-67622014000200007
   de Carvalho JRP, 2013, ATMOS RES, V132, P12, DOI 10.1016/j.atmosres.2013.04.003
   Qu JW, 2015, J ENVIRON MANAGE, V151, P22, DOI 10.1016/j.jenvman.2014.11.033
   Ribeiro Jr J.I., 2011, ANALISES ESTATISTICA, P258
   Rosenzweig C, 2013, AGR FOREST METEOROL, V170, P166, DOI 10.1016/j.agrformet.2012.09.011
   Santos A.R., 2010, ARCGIS 9 3 TOTAL APL, P184
   Santos A.R., 2015, ESPACIALIZACAO DADOS, P64
   Schmidt Maria Luiza Gava, 2006, Rev. bras. saúde ocup., V31, P27
   Sediyama G.C., 2001, Revista Brasileira de Agrometeorologia, V9, P501
   Shih HC, 2015, J ENVIRON MANAGE, V151, P393, DOI 10.1016/j.jenvman.2014.12.020
   Strassburg BBN, 2014, GLOBAL ENVIRON CHANG, V28, P84, DOI 10.1016/j.gloenvcha.2014.06.001
   Thornthwaite C.W., 1955, PUBLICATIONS CLIMATO, V8, P1
   Thornton PK, 2009, GLOBAL ENVIRON CHANG, V19, P54, DOI 10.1016/j.gloenvcha.2008.08.005
   Vianello R.L., 2004, METEOROLOGIA BASICA, P450
   Yates KL, 2015, J ENVIRON MANAGE, V152, P201, DOI 10.1016/j.jenvman.2015.01.045
   Zirlewagen D, 2007, FOREST ECOL MANAG, V248, P43, DOI 10.1016/j.foreco.2007.02.038
NR 65
TC 13
Z9 14
U1 0
U2 25
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD JAN 15
PY 2016
VL 166
BP 429
EP 439
DI 10.1016/j.jenvman.2015.10.040
PG 11
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA DA4GD
UT WOS:000367757200044
PM 26555099
DA 2025-01-10
ER

PT J
AU Schroth, G
   Laderach, P
   Dempewolf, J
   Philpott, S
   Haggar, J
   Eakin, H
   Castillejos, T
   Moreno, JG
   Pinto, LS
   Hernandez, R
   Eitzinger, A
   Ramirez-Villegas, J
AF Schroth, Goetz
   Laderach, Peter
   Dempewolf, Jan
   Philpott, Stacy
   Haggar, Jeremy
   Eakin, Hallie
   Castillejos, Teresa
   Moreno, Jaime Garcia
   Pinto, Lorena Soto
   Hernandez, Ricardo
   Eitzinger, Anton
   Ramirez-Villegas, Julian
TI Towards a climate change adaptation strategy for coffee communities and
   ecosystems in the Sierra Madre de Chiapas, Mexico
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Adaptive resource management; Coffea arabica; Coffee quality; Crop
   suitability modeling; Ecosystem based adaptation; Livelihoods
   diversification; MAXENT; Natural disaster
ID SPECIES DISTRIBUTIONS; LAND-USE; LANDSCAPES; CRISIS; PLANTATIONS;
   MANAGEMENT; INTENSITY; GUATEMALA; DIVERSITY; PREDATION
AB The mountain chain of the Sierra Madre de Chiapas in southern Mexico is globally significant for its biodiversity and is one of the most important coffee production areas of Mexico. It provides water for several municipalities and its biosphere reserves are important tourist attractions. Much of the forest cover outside the core protected areas is in fact coffee grown under traditional forest shade. Unless this (agro)forest cover can be sustained, the biodiversity of the Sierra Madre and the environmental services it provides are at risk. We analyzed the threats to livelihoods and environment from climate change through crop suitability modeling based on downscaled climate scenarios for the period 2040 to 2069 (referred to as 2050s) and developed adaptation options through an expert workshop. Significant areas of forest and occasionally coffee are destroyed every year by wildfires, and this problem is bound to increase in a hotter and drier future climate. Widespread landslides and inundations, including on coffee farms, have recently been caused by hurricanes whose intensity is predicted to increase. A hotter climate with more irregular rainfall will be less favorable to the production of quality coffee and lower profitability may compel farmers to abandon shade coffee and expand other land uses of less biodiversity value, probably at the expense of forest. A comprehensive strategy to sustain the biodiversity, ecosystem services and livelihoods of the Sierra Madre in the face of climate change should include the promotion of biodiversity friendly coffee growing and processing practices including complex shade which can offer some hurricane protection and product diversification; payments for forest conservation and restoration from existing government programs complemented by private initiatives; diversification of income sources to mitigate risks associated with unstable environmental conditions and coffee markets; integrated fire management; development of markets that reward sustainable land use practices and forest conservation; crop insurance programs that are accessible to smallholders; and the strengthening of local capacity for adaptive resource management.
C1 [Schroth, Goetz; Dempewolf, Jan; Moreno, Jaime Garcia] Conservat Int, Arlington, VA 22202 USA.
   [Laderach, Peter] CIAT, Managua, Nicaragua.
   [Philpott, Stacy] Univ Toledo, Dept Environm Sci, Toledo, OH 43606 USA.
   [Haggar, Jeremy] CATIE, Managua, Nicaragua.
   [Eakin, Hallie] Arizona State Univ, Tempe, AZ 85287 USA.
   [Castillejos, Teresa; Hernandez, Ricardo] Conservac Int Mexico, Tuxtla Gutierrez 29030, Chiapas, Mexico.
   [Pinto, Lorena Soto] El Colegio Frontera ECOSUR, Chiapas 29200, Mexico.
   [Eitzinger, Anton; Ramirez-Villegas, Julian] CIAT, Cali, Colombia.
C3 Conservation International; Alliance; International Center for Tropical
   Agriculture - CIAT; University System of Ohio; University of Toledo;
   Arizona State University; Arizona State University-Tempe; El Colegio de
   la Frontera Sur (ECOSUR); Alliance; International Center for Tropical
   Agriculture - CIAT
RP Schroth, G (corresponding author), Conservat Int, 2011 Crystal Dr,Suite 500, Arlington, VA 22202 USA.
EM g.schroth@conservation.org
RI Philpott, Stacy/M-3486-2019; Ramirez-Villegas, Julian/AAY-8073-2020;
   Eakin, Hallie/J-3654-2012; Eitzinger, Anton/AAU-4960-2020; Philpott,
   Stacy/F-2330-2011
OI Soto-Pinto, Lorena/0000-0002-2254-8603; Eitzinger,
   Anton/0000-0001-7317-3381; Philpott, Stacy/0000-0002-8338-3806;
   Ramirez-Villegas, Julian/0000-0002-8044-583X; Laderach,
   Peter/0000-0001-8708-6318
CR AGRAWAL A, 2008, W08I3 INT FOR RES I
   Anderson ER., 2008, Potential Impacts of Climate Change on Biodiversity in Central America Mexico and the Dominican Republic, P105
   [Anonymous], 2008, Hole-filled seamless SRTM data V4
   [Anonymous], 1977, Exploratory Data Analysis
   Armbrecht I, 2007, ENTOMOL EXP APPL, V124, P261, DOI 10.1111/j.1570-7458.2007.00574.x
   BAKER PS, 2007, GLOBAL WARMING IMPAC, P14
   Bosselmann AS, 2009, AGR ECOSYST ENVIRON, V129, P253, DOI 10.1016/j.agee.2008.09.004
   *CAFENICA, 2008, MEJ CAL CAF PROC POS, P34
   CARABIAS J, 1999, PLAN MANEJO RESERVA
   CENAPRED, 2006, CAR IMP SOC PRINC DE
   *CONANP TNC FMCN, 2004, PROGR MAN INT FUEG R
   Dormann CF, 2007, BASIC APPL ECOL, V8, P387, DOI 10.1016/j.baae.2006.11.001
   Eakin H, 2005, MT RES DEV, V25, P304, DOI 10.1659/0276-4741(2005)025[0304:MSACVT]2.0.CO;2
   Eakin H, 2005, WORLD DEV, V33, P1923, DOI 10.1016/j.worlddev.2005.06.005
   Eakin H, 2000, CLIMATIC CHANGE, V45, P19, DOI 10.1023/A:1005628631627
   EAKIN H, 2008, COFFEE FARMERS RESPO, P19
   EAKIN H, 2009, LINKING LOCAL VULNER
   Eakin H, 2006, GEOGR J, V172, P156, DOI 10.1111/j.1475-4959.2006.00195.x
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Ellis EA, 2008, FOREST ECOL MANAG, V256, P1971, DOI 10.1016/j.foreco.2008.07.036
   Elsner JB, 2008, NATURE, V455, P92, DOI 10.1038/nature07234
   FOURNIER LA, 2001, AGRON COSTARRIC, V28, P101
   Gay C, 2006, CLIMATIC CHANGE, V79, P259, DOI 10.1007/s10584-006-9066-x
   Gergis JL, 2009, CLIMATIC CHANGE, V92, P343, DOI 10.1007/s10584-008-9476-z
   GUHL A, 2006, CAMBIOS AMBIENTALES, V2, P191
   HAGGAR J, 2008, IMPACT CLIMATE CHANG
   Hausermann H, 2008, J LAT AM GEOGR, V7, P109, DOI 10.1353/lag.2008.0001
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Instituto Nacional de Estadistica y Geografia-INEGI, 2000, CENS GEN POL VIV
   LAMOROUX N, 2005, J PHYTOPATHOL, V143, P403
   Lin BB, 2008, BIOSCIENCE, V58, P847, DOI 10.1641/B580911
   Lorenzoni I, 2000, GLOBAL ENVIRON CHANG, V10, P145, DOI 10.1016/S0959-3780(00)00016-9
   Macip-Ríos R, 2008, REV MEX BIODIVERS, V79, P185
   MENDOZA RB, 2002, MEXICO CAFETICULTURA, P311
   Moguel P, 1999, CONSERV BIOL, V13, P11, DOI 10.1046/j.1523-1739.1999.97153.x
   Muñoz-Piña C, 2008, ECOL ECON, V65, P725, DOI 10.1016/j.ecolecon.2007.07.031
   Perfecto I, 2004, ECOLOGY, V85, P2677, DOI 10.1890/03-3145
   Perfecto I, 1996, BIOSCIENCE, V46, P598, DOI 10.2307/1312989
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2008, ECOGRAPHY, V31, P161, DOI 10.1111/j.0906-7590.2008.5203.x
   Philpott SM, 2008, CONSERV BIOL, V22, P1093, DOI 10.1111/j.1523-1739.2008.01029.x
   Philpott SM, 2008, AGR ECOSYST ENVIRON, V128, P12, DOI 10.1016/j.agee.2008.04.016
   Pierce DW, 2009, P NATL ACAD SCI USA, V106, P8441, DOI 10.1073/pnas.0900094106
   Pyke CR, 2007, CLIMATIC CHANGE, V80, P239, DOI 10.1007/s10584-006-9110-x
   Richter M, 2000, MT RES DEV, V20, P332, DOI 10.1659/0276-4741(2000)020[0332:TECICA]2.0.CO;2
   Saldaña-Zorrilla SO, 2008, GLOBAL ENVIRON CHANG, V18, P583, DOI 10.1016/j.gloenvcha.2008.09.004
   Soto-Pinto L, 2000, AGR ECOSYST ENVIRON, V80, P61, DOI 10.1016/S0167-8809(00)00134-1
   Soto-Pinto L, 2001, REV BIOL TROP, V49, P977
   Vaast P, 2006, J SCI FOOD AGR, V86, P197, DOI 10.1002/jsfa.2338
   Webster PJ, 2005, SCIENCE, V309, P1844, DOI 10.1126/science.1116448
NR 52
TC 144
Z9 175
U1 0
U2 192
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1381-2386
EI 1573-1596
J9 MITIG ADAPT STRAT GL
JI Mitig. Adapt. Strateg. Glob. Chang.
PD OCT
PY 2009
VL 14
IS 7
BP 605
EP 625
DI 10.1007/s11027-009-9186-5
PG 21
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 659GD
UT WOS:000282554100002
DA 2025-01-10
ER

PT J
AU Voldseth, RA
   Johnson, WC
   Guntenspergen, GR
   Gilmanov, T
   Millett, BV
AF Voldseth, Richard A.
   Johnson, W. Carter
   Guntenspergen, Glenn R.
   Gilmanov, Tagir
   Millett, Bruce V.
TI ADAPTATION OF FARMING PRACTICES COULD BUFFER EFFECTS OF CLIMATE CHANGE
   ON NORTHERN PRAIRIE WETLANDS
SO WETLANDS
LA English
DT Article
DE grassland management; grazing; land use; mitigation; Prairie Pothole
   Region; wetland modeling
ID CHANGE IMPACTS; PRESENT TECHNOLOGY; WATER LEVELS; LAND-USE; SIMULATIONS;
   HYDROLOGY; VULNERABILITY; AGRICULTURE; ADJUSTMENTS; CATCHMENTS
AB Wetlands of the Prairie Pothole Region of North America are vulnerable to climate change. Adaptation of farming practices to mitigate adverse impacts of climate change on wetland water levels is a potential watershed management option. We chose a modeling approach (WETSIM 3.2) to examine the effects of changes in climate and watershed cover on the water levels of a semi-permanent wetland in eastern South Dakota. Land-use practices simulated were unmanaged grassland, grassland managed with moderately heavy grazing, and cultivated crops. Climate scenarios were developed by adjusting the historical climate in combinations of 2 degrees C and 4 degrees C air temperature and +/- 10% precipitation. For these climate change scenarios, simulations of land use that produced water levels equal to or greater than unmanaged grassland under historical climate were judged to have mitigative potential against a drier climate. Water levels in wetlands surrounded by managed grasslands were significantly greater than those surrounded by unmanaged grassland. Management reduced both the proportion of years the wetland went dry and the frequency of dry periods, producing the most dynamic vegetation cycle for this modeled wetland. Both cultivated crops and managed grassland achieved water levels that were equal or greater than unmanaged grassland under historical climate for the 2 degrees C rise in air temperature, and the 2 degrees C rise plus 10% increase in precipitation scenarios. Managed grassland also produced water levels that were equal or greater than unmanaged grassland under historical climate for the 4 degrees C rise plus 10% increase in precipitation scenario. Although these modeling results stand as hypotheses, they indicate that amelioration potential exists for a change in climate up to an increase of 2 degrees C or 4 degrees C with a concomitant 10% increase in precipitation. Few empirical data exist to verify the results of such land-use simulations; however, adaptation of farming practices is one possible mitigation avenue available for prairie wetlands.
C1 [Voldseth, Richard A.; Johnson, W. Carter] S Dakota State Univ, Dept Hort Forestry Landscape & Parks, Brookings, SD 57007 USA.
   [Guntenspergen, Glenn R.] US Geol Survey, Biol Resources Div, Patuxent Wildlife Res Ctr, Laurel, MD 20708 USA.
   [Gilmanov, Tagir] S Dakota State Univ, Biol & Microbiol Dept, Brookings, SD 57007 USA.
   [Millett, Bruce V.] S Dakota State Univ, Dept Geog, Brookings, SD 57007 USA.
C3 South Dakota State University; United States Department of the Interior;
   United States Geological Survey; South Dakota State University; South
   Dakota State University
RP Voldseth, RA (corresponding author), N Dakota State Univ, Sch Nat Resource Sci, Dept Soil Sci, 106 Walster Hall, Fargo, ND 58108 USA.
EM richard.voldseth@ndsu.edu
OI Gilmanov, Tagir/0000-0002-7993-2518
FU USGS - Biological Resources Division's Global Change Research Program;
   US-EPA STAR
FX This project was funded by the USGS - Biological Resources Division's
   Global Change Research Program. Additional funding was provided through
   the US-EPA STAR Grant Program. We would like to thank South Dakota State
   University and the USDA - Forest Service for providing additional
   support. We also thank the USFWS for access to the Orchid Meadows field
   site. Our appreciation is extended to Karen Poiani, Tom Winter, Jim
   Lynch, Brett Werner, Tor Johnson, and Susan Boettcher for their
   assistance. We also thank the anonymous reviewers and subject-matter
   editor for their insight and direction.
CR ADAMS RM, 1990, NATURE, V345, P219, DOI 10.1038/345219a0
   [Anonymous], 1972, NAT ENG HDB
   [Anonymous], 2001, CLIMATE CHANGE IMPAC
   Asner GP, 2004, ANNU REV ENV RESOUR, V29, P261, DOI 10.1146/annurev.energy.29.062403.102142
   Carroll R, 2005, J HYDROL ENG, V10, P70, DOI 10.1061/(ASCE)1084-0699(2005)10:1(70)
   Clair TA, 1998, WATER RESOUR RES, V34, P447, DOI 10.1029/97WR03472
   Covich AP, 1997, HYDROL PROCESS, V11, P993
   Dahl T.E., 2000, Status and trends of wetlands in the conterminous United States 1986 to 1997
   DUEBBERT HF, 1987, J SOIL WATER CONSERV, V42, P50
   EASTERLING WE, 1992, AGR FOREST METEOROL, V59, P75, DOI 10.1016/0168-1923(92)90087-K
   Easterling WE, 1996, AGR FOREST METEOROL, V80, P1, DOI 10.1016/0168-1923(95)02315-1
   EASTERLING WE, 1992, AGR FOREST METEOROL, V59, P53, DOI 10.1016/0168-1923(92)90086-J
   EISENLOHR WS, 1972, 585A US DEP INT GEOL
   Field CB, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P617
   HARGREAVES GH, 1994, J IRRIG DRAIN ENG, V120, P1132, DOI 10.1061/(ASCE)0733-9437(1994)120:6(1132)
   Hayashi M, 1998, J HYDROL, V207, P42, DOI 10.1016/S0022-1694(98)00098-5
   HAYASHI M, 1998, J HYDROL, V270, P214
   HUBBARD DE, 1988, P NATIONAL WETLAND S, P137
   INKLEY DB, 2004, 042 WILDL SOC
   *IUCN, 2001, 6 M SUBS BOD SCI TEC
   Johnson WC, 2005, BIOSCIENCE, V55, P863, DOI 10.1641/0006-3568(2005)055[0863:VONPWT]2.0.CO;2
   Johnson WC, 2004, WETLANDS, V24, P385, DOI 10.1672/0277-5212(2004)024[0385:IOWEOT]2.0.CO;2
   KANTRUD HA, 1990, USDA ROCKY, V194, P93
   Lane DR, 2000, J VEG SCI, V11, P359, DOI 10.2307/3236628
   Millett B, 2009, CLIMATIC CHANGE, V93, P243, DOI 10.1007/s10584-008-9543-5
   Mortsch LD, 1998, CLIMATIC CHANGE, V40, P391, DOI 10.1023/A:1005445709728
   Ojima D, 1999, J AM WATER RESOUR AS, V35, P1443, DOI 10.1111/j.1752-1688.1999.tb04228.x
   Ojima D.S, 2002, PREPARING CHANGING C
   POIANI KA, 1991, BIOSCIENCE, V41, P611, DOI 10.2307/1311698
   Poiani KA, 1996, LIMNOL OCEANOGR, V41, P871, DOI 10.4319/lo.1996.41.5.0871
   POIANI KA, 1993, ECOL APPL, V3, P279, DOI 10.2307/1941831
   POIANI KA, 1993, CLIMATIC CHANGE, V24, P213, DOI 10.1007/BF01091830
   POIANI KA, 1995, WATER RESOUR BULL, V31, P283
   Prtner H.O, 2022, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, P3056, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Pyke CR, 2007, CLIMATIC CHANGE, V80, P239, DOI 10.1007/s10584-006-9110-x
   Pyke CR, 2005, CONSERV BIOL, V19, P1619, DOI 10.1111/j.1523-1739.2005.00233.x
   Reilly J, 2003, CLIMATIC CHANGE, V57, P43, DOI 10.1023/A:1022103315424
   Rosenberg N.J., 1993, Climatic Change, V24
   ROSENBERG NJ, 2005, CLIMATIC CHANGE, V69
   Rosenzweig C., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P855, DOI 10.1007/s11027-007-9103-8
   Rosenzweig C., 2000, CTR HLTH GLOBAL ENV
   *SAS I INC, 1999, SAS WIND VERS 8
   SCHUT P, 2005, NATL ECOLOGICAL FRAM
   Scurlock J., 2001, ORNLTM2001268
   SHJEFLO JB, 1968, 585B US DEP INT GEOL
   Stewart RE, 1971, Resource Publication, V92
   Swanson G.A., 1989, P228
   Thomson AM, 2005, CLIMATIC CHANGE, V69, P43, DOI 10.1007/s10584-005-3612-9
   van der Kamp G, 2003, HYDROL PROCESS, V17, P559, DOI 10.1002/hyp.1157
   van der Kamp G, 1999, HYDROLOG SCI J, V44, P387, DOI 10.1080/02626669909492234
   van der Valk AG, 2005, HYDROBIOLOGIA, V539, P171, DOI 10.1007/s10750-004-4866-3
   VOLDSETH RA, 2004, THESIS S DAKOTA STAT
   Voldseth RA, 2007, ECOL APPL, V17, P527, DOI 10.1890/05-1195
   Williams J. R., 1995, Computer models of watershed hydrology., P909
   Winter TC, 2000, J AM WATER RESOUR AS, V36, P305, DOI 10.1111/j.1752-1688.2000.tb04269.x
   Winter ThomasC., 2003, HYDROLOGICAL CHEM BI, P1
   WOLFRAM S, 1999, MATHEMATICA BOOK
   WOO MK, 1993, J HYDROL, V146, P175, DOI 10.1016/0022-1694(93)90275-E
   ,, 2007, Climate change 2007: Synthesis Report. Contribution of Working Group I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers
NR 59
TC 27
Z9 33
U1 1
U2 47
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0277-5212
EI 1943-6246
J9 WETLANDS
JI Wetlands
PD JUN
PY 2009
VL 29
IS 2
BP 635
EP 647
DI 10.1672/07-241.1
PG 13
WC Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 483SD
UT WOS:000268987300022
DA 2025-01-10
ER

PT J
AU Chen, JQ
   Zhang, LW
   Zhao, RM
   Wu, HX
   Lin, LH
   Li, P
   Li, H
   Qu, YF
   Ji, X
AF Chen, Jun-Qiong
   Zhang, Lu-Wen
   Zhao, Ru-Meng
   Wu, Hai-Xia
   Lin, Long-Hui
   Li, Peng
   Li, Hong
   Qu, Yan-Fu
   Ji, Xiang
TI Gut microbiota differs between two cold- climate lizards distributed in
   thermally different regions
SO BMC ECOLOGY AND EVOLUTION
LA English
DT Article
DE 16S rRNA gene sequencing; Cold-climate adaptation; Gut microbiota;
   Phtynocephalus erythrurus; Phrynocephalus przewalskii; Toad-headed
   lizard
ID HATCHLING MORPHOLOGY; COMMUNITIES; ADAPTATION; DIVERSITY; AGAMIDAE;
   TEMPERATURE; POPULATION; METABOLISM; PLASTICITY; PREFERENCE
AB Background The metabolic cold-climate adaption hypothesis predicts that animals from cold environments have relatively high metabolic rates compared with their warm-climate counterparts. However, studies testing this hypothesis are sparse. Here, we compared gut microbes between two cold-climate lizard species of the genus Phrynocephalus to see if gut microbiota could help lizards adapt to cold environments by promoting metabolism. We conducted a 2 species (P. erythrurus and P. przewalskii) x 2 temperatures (24 and 30 degrees C) factorial design experiment, whereby we kept lizards of two Phrynocephalus species at 24 and 30 degrees C for 25 d and then collected their fecal samples to analyze and compare the microbiota based on 16S rRNA gene sequencing technology.
   Results The gut microbiota was mainly composed of bacteria of the phyla Proteobacteria, Firmicutes, Bacteroidetes, and Verrucomicrobia in both species (Proteobacteria > Firmicutes >Verrucomicrobiota in P. erythrurus, and Bacteroidetes> Proteobacteria > Firmicutes in P. przewalskii). Further analysis revealed that the gut microbiota promoted thermal adaptation in both lizard species, but with differences in the relative abundance of the contributory bacteria between the two species. An analysis based on the Kyoto Encyclopedia of Genes and Genomes revealed that the gut microbiota played important roles in metabolism, genetic information processing, cellular processes, and environmental information processing in both species. Furthermore, genes related to metabolism were more abundant in P. erythrurus at 24 degrees C than in other species temperature combinations.
   Conclusion Our study provides evidence that gut microbiota promotes thermal adaptation in both species but more evidently in P. erythrurus using colder habitats than P. przewalskii all year round, thus confirming the role of gut microbiota in cold-climate adaptation in lizards.
C1 [Chen, Jun-Qiong; Zhang, Lu-Wen; Zhao, Ru-Meng; Wu, Hai-Xia; Li, Peng; Li, Hong; Qu, Yan-Fu] Nanjing Normal Univ, Coll Life Sci, Jiangsu Key Lab Biodivers & Biotechnol, Nanjing 210023, Jiangsu, Peoples R China.
   [Ji, Xiang] Wenzhou Univ, Coll Life & Environm Sci, Zhejiang Prov Key Lab Water Environm & Marine Bio, Wenzhou 325035, Zhejiang, Peoples R China.
   [Lin, Long-Hui] Hangzhou Normal Univ, Coll Life & Environm Sci, Hangzhou Key Lab Ecosyst Protect & Restorat, Hangzhou 311121, Zhejiang, Peoples R China.
C3 Nanjing Normal University; Wenzhou University; Hangzhou Normal
   University
RP Qu, YF (corresponding author), Nanjing Normal Univ, Coll Life Sci, Jiangsu Key Lab Biodivers & Biotechnol, Nanjing 210023, Jiangsu, Peoples R China.; Ji, X (corresponding author), Wenzhou Univ, Coll Life & Environm Sci, Zhejiang Prov Key Lab Water Environm & Marine Bio, Wenzhou 325035, Zhejiang, Peoples R China.
EM quyanfu@njnu.edu.cn; xji@wzu.edu.cn
RI zhang, lm/JWP-8874-2024; Li, Hong/AAW-2866-2021; Li, Peng/GYD-6748-2022;
   Wu, Haixia/GSE-4837-2022
OI Li, Peng/0000-0001-9481-1282
FU National Natural Science Foundation of China [31670422, 31672277,
   31870390, 31971414]; Second Tibetan Plateau Scientific Expedition and
   Research Program (STEP) [2019QZKK05010216]; Jiangsu Provincial Natural
   Science Foundation [BK20161556]; Natural Science Foundation of the
   Jiangsu Higher Education Institutions [19KJA330001]; Postgraduate
   Research & Practice Innovation Program of Jiangsu Province [KYCX20_1241]
FX The study was supported by the grants from the National Natural Science
   Foundation of China to HL (31670422), XJ (31672277 and 31870390), and
   LHL (31971414), the Second Tibetan Plateau Scientific Expedition and
   Research Program (STEP) to XJ (2019QZKK05010216), Jiangsu Provincial
   Natural Science Foundation to YFQ (BK20161556), Natural Science
   Foundation of the Jiangsu Higher Education Institutions to PL
   (19KJA330001), and Postgraduate Research & Practice Innovation Program
   of Jiangsu Province to HXW (KYCX20_1241).
CR Anderson MJ, 2013, ECOL MONOGR, V83, P557, DOI 10.1890/12-2010.1
   Bai L, 2019, ISCIENCE, V11, P519, DOI 10.1016/j.isci.2018.11.034
   Bestion E, 2017, NAT ECOL EVOL, V1, DOI 10.1038/s41559-017-0161
   Bolyen E, 2019, NAT BIOTECHNOL, V37, P852, DOI 10.1038/s41587-019-0209-9
   Buglione M, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-16955-0
   Butt RL, 2019, FRONT ENDOCRINOL, V10, DOI 10.3389/fendo.2019.00009
   Callahan BJ, 2016, NAT METHODS, V13, P581, DOI [10.1038/NMETH.3869, 10.1038/nmeth.3869]
   Chevalier C, 2015, CELL, V163, P1360, DOI 10.1016/j.cell.2015.11.004
   Colston TJ, 2016, MOL ECOL, V25, P3776, DOI 10.1111/mec.13730
   Fernando SC, 2010, APPL ENVIRON MICROB, V76, P7482, DOI 10.1128/AEM.00388-10
   Fontaine SS, 2018, J EXP BIOL, V221, DOI 10.1242/jeb.187559
   Gao W, 2019, P NATL ACAD SCI USA, V116, P3646, DOI 10.1073/pnas.1816086116
   Guo K, 2021, ECOL EVOL, V11, P8573, DOI 10.1002/ece3.7671
   Hong PY, 2011, ISME J, V5, P1461, DOI 10.1038/ismej.2011.33
   Huo TR, 2020, ENVIRON INT, V143, DOI 10.1016/j.envint.2020.105915
   Ijssennagger N, 2016, TRENDS MOL MED, V22, P190, DOI 10.1016/j.molmed.2016.01.002
   Jiang HY, 2017, FRONT MICROBIOL, V8, DOI 10.3389/fmicb.2017.02073
   Jing TZ, 2020, MICROBIOME, V8, DOI 10.1186/s40168-020-00823-y
   Kaakoush NO, 2015, FRONT CELL INFECT MI, V5, DOI [10.3309/fcimb.2015.00004, 10.3389/fcimb.2015.00084]
   Kanehisa M, 2000, NUCLEIC ACIDS RES, V28, P27, DOI 10.1093/nar/28.1.27
   Kartzinel TR, 2019, P NATL ACAD SCI USA, V116, P23588, DOI 10.1073/pnas.1905666116
   Kohl KD, 2017, MOL ECOL, V26, P1175, DOI 10.1111/mec.13921
   Kohl KD, 2016, ENVIRON MICROBIOL, V18, P1561, DOI 10.1111/1462-2920.13255
   Kokou F, 2018, ELIFE, V7, DOI 10.7554/eLife.36398
   Langille MGI, 2013, NAT BIOTECHNOL, V31, P814, DOI 10.1038/nbt.2676
   Lardies MA, 2004, CAN J ZOOL, V82, P677, DOI 10.1139/Z04-033
   Li H, 2017, FEMS MICROBIOL ECOL, V93, DOI 10.1093/femsec/fix009
   Li XM, 2012, J MICROBIOL, V50, P29, DOI 10.1007/s12275-012-1340-1
   Martin MO, 2010, SYMBIOSIS, V51, P97, DOI 10.1007/s13199-010-0078-y
   Moeller AH, 2020, APPL ENVIRON MICROB, V86, DOI 10.1128/AEM.01181-20
   Qu YF, 2020, PEERJ, V8, DOI 10.7717/peerj.10271
   Qu YF, 2011, ACTA OECOL, V37, P375, DOI 10.1016/j.actao.2011.04.006
   Qu YF, 2011, ANIM BIOL, V61, P139, DOI 10.1163/157075511X566470
   Qu YF, 2011, CURR ZOOL, V57, P684, DOI 10.1093/czoolo/57.6.684
   Reed PT, 2014, BIORESOURCE TECHNOL, V155, P50, DOI 10.1016/j.biortech.2013.12.051
   Ren TT, 2016, MOL ECOL, V25, P4793, DOI 10.1111/mec.13796
   Rock C., 2014, Reference Module in Biomedical Sciences, VThird, DOI [DOI 10.1016/B978-0-12-801238-3.00136-7, 10.1016/b978-0-12-801238-3.00136-7]
   Rowland I, 2018, EUR J NUTR, V57, P1, DOI 10.1007/s00394-017-1445-8
   Schaefer J, 2010, FUNCT ECOL, V24, P1087, DOI 10.1111/j.1365-2435.2010.01726.x
   Segata N, 2011, GENOME BIOL, V12, DOI 10.1186/gb-2011-12-6-r60
   Sepulveda J, 2020, FRONT MICROBIOL, V11, DOI 10.3389/fmicb.2020.00384
   [舒霖 SHU Lin], 2010, [生态学报, Acta Ecologica Sinica], V30, P2036
   Siviter H, 2019, BEHAV PROCESS, V165, P9, DOI 10.1016/j.beproc.2019.06.003
   Storey KB, 2012, CABI CLIM CHANGE SER, V3, P98, DOI 10.1079/9781845938222.0098
   Tajima K, 2007, ANAEROBE, V13, P57, DOI 10.1016/j.anaerobe.2006.12.001
   Tang GS, 2020, FRONT MICROBIOL, V11, DOI 10.3389/fmicb.2020.00550
   Tang KY, 2019, FRONT MICROBIOL, V10, DOI 10.3389/fmicb.2019.02409
   Tomasova L, 2016, MOLECULES, V21, DOI 10.3390/molecules21111558
   Wang Z, 2017, OECOLOGIA, V185, P573, DOI 10.1007/s00442-017-3979-0
   Wang Z, 2014, OECOLOGIA, V174, P639, DOI 10.1007/s00442-013-2811-8
   Wang Z, 2013, ASIAN HERPETOL RES, V4, P225, DOI 10.3724/SP.J.1245.2013.00225
   Wang Z, 2013, ASIAN HERPETOL RES, V4, P214, DOI 10.3724/SP.J.1245.2013.00214
   Wei W, 2021, CLIN NUTR, V40, P4234, DOI 10.1016/j.clnu.2021.01.031
   White CR, 2012, P ROY SOC B-BIOL SCI, V279, P1740, DOI 10.1098/rspb.2011.2060
   Zhang WY, 2018, ECOL EVOL, V8, P4695, DOI 10.1002/ece3.4029
   Zhang ZG, 2016, CURR BIOL, V26, P1873, DOI 10.1016/j.cub.2016.05.012
   Zhao EM, 1999, FAUNA SINICA REPTILI
   Zhou J, 2020, MICROBIOLOGYOPEN, V9, DOI 10.1002/mbo3.1095
   Zhu BL, 2010, PROTEIN CELL, V1, P718, DOI 10.1007/s13238-010-0093-z
   Zhu LF, 2021, EVOL APPL, V14, P735, DOI 10.1111/eva.13152
   Zhu LH, 2019, APPL MICROBIOL BIOT, V103, P461, DOI 10.1007/s00253-018-9465-8
NR 61
TC 4
Z9 4
U1 7
U2 52
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
EI 2730-7182
J9 BMC ECOL EVOL
JI BMC Ecol. Evol.
PD OCT 21
PY 2022
VL 22
IS 1
AR 120
DI 10.1186/s12862-022-02077-8
PG 13
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 5M4AU
UT WOS:000871041000002
PM 36271355
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Ma, LJ
   Cao, LJ
   Chen, JC
   Tang, MQ
   Song, W
   Yang, FY
   Shen, XJ
   Ren, YJ
   Yang, Q
   Li, H
   Hoffmann, AA
   Wei, SJ
AF Ma, Li-Jun
   Cao, Li-Jun
   Chen, Jin-Cui
   Tang, Meng-Qing
   Song, Wei
   Yang, Fang-Yuan
   Shen, Xiu-Jing
   Ren, Ya-Jing
   Yang, Qiong
   Li, Hu
   Hoffmann, Ary Anthony
   Wei, Shu-Jun
TI Rapid and Repeated Climate Adaptation Involving Chromosome Inversions
   following Invasion of an Insect
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE climate change; population genomics; local adaption; phenotypic
   variation; structure variation
ID WHITE-TAILED DEER; EFFECTIVE POPULATION-SIZE; ODOCOILEUS-VIRGINIANUS;
   MULE DEER; GENETIC-STRUCTURE; GENOMES REVEAL; DEMOGRAPHIC INFERENCES;
   POSITIVE SELECTION; NORTH-AMERICA; MITOCHONDRIAL
AB Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.
C1 [Ma, Li-Jun; Cao, Li-Jun; Chen, Jin-Cui; Tang, Meng-Qing; Song, Wei; Yang, Fang-Yuan; Shen, Xiu-Jing; Ren, Ya-Jing; Wei, Shu-Jun] Beijing Acad Agr & Forestry Sci, Inst Plant Protect, Beijing 100097, Peoples R China.
   [Tang, Meng-Qing; Ren, Ya-Jing; Li, Hu] China Agr Univ, Coll Plant Protect, Dept Entomol, Beijing 100193, Peoples R China.
   [Tang, Meng-Qing; Ren, Ya-Jing; Li, Hu] China Agr Univ, Coll Plant Protect, MOA Key Lab Pest Monitoring & Green Management, Beijing 100193, Peoples R China.
   [Yang, Qiong; Hoffmann, Ary Anthony] Univ Melbourne, Bio21 Inst, Sch BioSci, Parkville, Vic 3010, Australia.
C3 Chinese Academy of Agricultural Sciences; Institute of Plant Protection,
   CAAS; Beijing Academy of Agriculture & Forestry Sciences (BAAFS); China
   Agricultural University; China Agricultural University; University of
   Melbourne
RP Wei, SJ (corresponding author), Beijing Acad Agr & Forestry Sci, Inst Plant Protect, Beijing 100097, Peoples R China.; Hoffmann, AA (corresponding author), Univ Melbourne, Bio21 Inst, Sch BioSci, Parkville, Vic 3010, Australia.
EM ary@unimelb.edu.au; shujun268@163.com
RI Hoffmann, Ary/C-2961-2011; Cao, Lijun/ABA-6079-2021; Wei,
   Shu-Jun/C-1109-2011
FU Beijing Natural Science Foundation [JQ21021]; Program of Beijing Academy
   of Agriculture and Forestry Sciences [JKZX202208]; Joint Laboratory of
   Pest Control Research Between China and Australia [Z201100008320013];
   Australian Research Council
FX This work is supported by the Beijing Natural Science Foundation
   (JQ21021), the Program of Beijing Academy of Agriculture and Forestry
   Sciences (JKZX202208), and the Joint Laboratory of Pest Control Research
   Between China and Australia (Z201100008320013). A.A.H. is supported by a
   grant from the Australian Research Council.
CR Adams KP, 2011, Biology and Management of White-Tailed Deer, P355
   Allen JRM, 2020, J BIOGEOGR, V47, P2073, DOI 10.1111/jbi.13930
   Allendorf FW, 2009, P NATL ACAD SCI USA, V106, P9987, DOI 10.1073/pnas.0901069106
   Andrews S., 2010, FASTQC QUALITY CONTR
   ANTHONY RG, 1977, ECOL MONOGR, V47, P255, DOI 10.2307/1942517
   Baca M, 2020, QUATERNARY SCI REV, V233, DOI 10.1016/j.quascirev.2020.106239
   BACCUS R, 1983, J MAMMAL, V64, P109, DOI 10.2307/1380756
   Batchelor CL, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-11601-2
   Bennett MR, 2021, SCIENCE, V373, P1528, DOI 10.1126/science.abg7586
   Bergman EJ, 2015, WILDLIFE BIOL, V21, P18, DOI 10.2981/wlb.00012
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Brain RA, 2022, ENVIRON SCI POLLUT R, V29, P66010, DOI 10.1007/s11356-022-22102-z
   Broad Institute GitHub Repository, 2019, Picard toolkit
   Brunjes KJ, 2006, J WILDLIFE MANAGE, V70, P1351, DOI 10.2193/0022-541X(2006)70[1351:HUBSMA]2.0.CO;2
   Budd K, 2018, J WILDLIFE MANAGE, V82, P1598, DOI 10.1002/jwmg.21546
   Cambronne A., 2013, Deerland: Americas Hunt for Ecological Balance and the Essence of Wildness, V1, P1
   Campbell TA, 2011, BIOLOGY AND MANAGEMENT OF WHITE-TAILED DEER, P219
   CARR SM, 1993, J MAMMAL, V74, P331, DOI 10.2307/1382388
   Cars BS, 2023, bioRxiv, DOI [10.1101/2023.08.01.551454, 10.1101/2023.08.01.551454, DOI 10.1101/2023.08.01.551454]
   Ceballos G, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1400253
   Chafin TK, 2021, EVOL APPL, V14, P1673, DOI 10.1111/eva.13233
   Chang CC, 2015, GIGASCIENCE, V4, DOI 10.1186/s13742-015-0047-8
   Charlesworth B, 2009, NAT REV GENET, V10, P195, DOI 10.1038/nrg2526
   Chen L, 2019, SCIENCE, V364, P1152, DOI 10.1126/science.aav6202
   Chigurapati S., 2018, bioRxiv, DOI [10.1101/397356, DOI 10.1101/397356]
   Clark PU, 2009, SCIENCE, V325, P710, DOI 10.1126/science.1172873
   Clements CD, 1997, J RANGE MANAGE, V50, P129, DOI 10.2307/4002369
   Colella JP, 2021, J BIOGEOGR, V48, P1153, DOI 10.1111/jbi.14068
   Combe FJ, 2022, EVOL APPL, V15, P111, DOI 10.1111/eva.13330
   Commerford JL, 2022, VEG HIST ARCHAEOBOT, V31, P467, DOI 10.1007/s00334-021-00864-9
   CRONIN MA, 1991, CAN J ZOOL, V69, P1270, DOI 10.1139/z91-179
   CROW J F, 1970, P591, DOI 10.1093/bioinformatics/btr330
   Dawe KL, 2016, ECOL EVOL, V6, P6435, DOI 10.1002/ece3.2316
   de Jong MJ, 2020, MOL ECOL, V29, P2777, DOI 10.1111/mec.15450
   Dedato MN, 2022, EVOL APPL, V15, P2043, DOI 10.1111/eva.13495
   Deer Friendly, Deer population. Deer Friendly
   DERR JN, 1991, J WILDLIFE MANAGE, V55, P228, DOI 10.2307/3809144
   DeVivo MT, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0186512
   DeYoung RW, 2003, MOL ECOL, V12, P3237, DOI 10.1046/j.1365-294X.2003.01996.x
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Douzery E, 1997, MOL BIOL EVOL, V14, P1154, DOI 10.1093/oxfordjournals.molbev.a025725
   Dussex N, 2020, BMC GENOMICS, V21, DOI 10.1186/s12864-020-07208-3
   Elias S., 2007, Encyclopedia of quaternary science, V2, P700
   ELLSWORTH DL, 1994, EVOLUTION, V48, P122, DOI 10.1111/j.1558-5646.1994.tb01299.x
   Ersmark E, 2019, ECOL EVOL, V9, P5891, DOI 10.1002/ece3.5172
   Evanno G, 2005, MOL ECOL, V14, P2611, DOI 10.1111/j.1365-294X.2005.02553.x
   Ewels P, 2016, BIOINFORMATICS, V32, P3047, DOI 10.1093/bioinformatics/btw354
   Ferchaud AL, 2016, HEREDITY, V117, P268, DOI 10.1038/hdy.2016.62
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Forrester TD, 2013, MAMMAL REV, V43, P292, DOI 10.1111/mam.12002
   Frankham R, 2005, BIOL CONSERV, V126, P131, DOI 10.1016/j.biocon.2005.05.002
   FRANKHAM R, 1995, GENET RES, V66, P95, DOI 10.1017/S0016672300034455
   Fréchette B, 2013, QUATERNARY RES, V79, P242, DOI 10.1016/j.yqres.2012.11.011
   Fulton AE, 2020, ANN AM ASSOC GEOGR, V111, P771, DOI 10.1080/24694452.2020.1846489
   Fusco NA., 2023, Mol Ecol, V17230, pe17230
   Gajewski K, 2019, VEG HIST ARCHAEOBOT, V28, P635, DOI 10.1007/s00334-019-00721-w
   Garrison E, 2022, PLOS COMPUT BIOL, V18, DOI 10.1371/journal.pcbi.1009123
   Gill R B., 1999, Declining mule deer populations in Colorado: reasons and responses. A report to the Colorado legislature
   Gowan EJ, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21469-w
   Greenslade AD., 1998, Interand intraspecific phylogeography of North American Odocoileus deer based on mitochondrial DNA sequences
   Grinberg S, 2019, findPeaks
   Grossen C, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-14803-1
   Gruell GE., 1986, Post-1900 mule deer irruptions in the Intermountain West: Principal cause and influences
   Gutenkunst RN, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000695
   Hahn MW, 2018, Molecular population genetics, V1st
   Hanberry BB, 2023, J QUATERNARY SCI, V38, P829, DOI 10.1002/jqs.3526
   Heffelfinger J.R., 2023, Ecology and management of black-tailed and mule deer of North America
   Hempel E, 2022, MOL BIOL EVOL, V39, DOI 10.1093/molbev/msac241
   Hewitt DG, 2011, Biology and Management of White-Tailed Deer, P1
   Hijmans Robert J, 2023, CRAN
   Ito T, 2021, J BIOGEOGR, V48, P1420, DOI 10.1111/jbi.14087
   Jensen W. F., 2023, Ecology and management of blacktailed and mule deer of North America, P25
   Kerr PJ, 2021, QUATERNARY SCI REV, V261, DOI 10.1016/j.quascirev.2021.106926
   Kessler C, 2023, MOL ECOL, V32, P1117, DOI 10.1111/mec.16824
   Klassmann A, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0262024
   Klicka LB., 2023, IN PRESS
   Kopelman NM, 2015, MOL ECOL RESOUR, V15, P1179, DOI 10.1111/1755-0998.12387
   Korneliussen TS, 2014, BMC BIOINFORMATICS, V15, DOI 10.1186/s12859-014-0356-4
   Kvalnes T, 2016, EVOLUTION, V70, P1486, DOI 10.1111/evo.12952
   Lamb Sydney, 2021, GigaByte, V2021, pgigabyte34, DOI 10.46471/gigabyte.34
   Lapierre M, 2017, GENETICS, V206, P439, DOI 10.1534/genetics.116.192708
   Latch EK, 2014, MOL ECOL, V23, P3171, DOI 10.1111/mec.12803
   Latch EK, 2009, MOL ECOL, V18, P1730, DOI 10.1111/j.1365-294X.2009.04153.x
   LEGENDRE L., 1983, NUMERICAL ECOLOGY
   Li H, 2011, NATURE, V475, P493, DOI 10.1038/nature10231
   Li H, 2009, BIOINFORMATICS, V25, P2078, DOI 10.1093/bioinformatics/btp352
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Lindo J, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms13175
   Liu XM, 2020, GENOME BIOL, V21, DOI 10.1186/s13059-020-02196-9
   Liu XM, 2015, NAT GENET, V47, P555, DOI 10.1038/ng.3254
   Loog L, 2020, MOL ECOL, V29, P1596, DOI 10.1111/mec.15329
   Lorenzen ED, 2011, NATURE, V479, P359, DOI 10.1038/nature10574
   Lynch VJ, 2015, CELL REP, V12, P217, DOI 10.1016/j.celrep.2015.06.027
   Malhi Y, 2022, CURR BIOL, V32, pR181, DOI 10.1016/j.cub.2022.01.041
   Malhi Y, 2016, P NATL ACAD SCI USA, V113, P838, DOI 10.1073/pnas.1502540113
   Manel S, 2016, MOL ECOL, V25, P170, DOI 10.1111/mec.13468
   Martchenko D, 2023, HEREDITY, V131, P273, DOI 10.1038/s41437-023-00643-4
   Martin M, 2016, bioRxiv, DOI [DOI 10.1101/085050, 10.1101/085050v2, DOI 10.1101/085050V2]
   Martin S., 2021, genomics_general
   Mautz W. W., 1985, Biology of deer production. Proceedings of an International Conference held at Dunedin, New Zealand, 13-18 February 1983, P453
   McDonald J. S., 2004, HIST WHITE TAILED DE
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Meiri M, 2020, J BIOGEOGR, V47, P2223, DOI 10.1111/jbi.13935
   Meisner J, 2018, GENETICS, V210, P719, DOI 10.1534/genetics.118.301336
   Meltzer DJ, 2020, P NATL ACAD SCI USA, V117, P28555, DOI 10.1073/pnas.2015032117
   Moscarella RA, 2003, J MAMMAL, V84, P1300, DOI 10.1644/BRB-028
   Mottl O, 2021, SCIENCE, V372, P860, DOI 10.1126/science.abg1685
   O'Connell J, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004234
   Oksanen Jari, 2022, CRAN
   Palkopoulou E, 2015, CURR BIOL, V25, P1395, DOI 10.1016/j.cub.2015.04.007
   Palstra FP, 2008, MOL ECOL, V17, P3428, DOI 10.1111/j.1365-294X.2008.03842.x
   Pamilo P, 1999, HEREDITAS, V130, P229, DOI 10.1111/j.1601-5223.1999.00229.x
   Paradis E, 2019, BIOINFORMATICS, V35, P526, DOI 10.1093/bioinformatics/bty633
   Patterson M, 2015, J COMPUT BIOL, V22, P498, DOI 10.1089/cmb.2014.0157
   Peart CR, 2020, NAT ECOL EVOL, V4, P1095, DOI 10.1038/s41559-020-1215-5
   Pedersen BS, 2018, BIOINFORMATICS, V34, P867, DOI 10.1093/bioinformatics/btx699
   Peres TM, 2018, J ARCHAEOL SCI-REP, V20, P888, DOI 10.1016/j.jasrep.2017.10.028
   Portik DM, 2017, MOL ECOL, V26, P5245, DOI 10.1111/mec.14266
   Pundir Sangya, 2016, Curr Protoc Bioinformatics, V53, DOI 10.1002/0471250953.bi0129s53
   Robin M, 2022, MOL ECOL, V31, P3548, DOI 10.1111/mec.16503
   Roycroft E, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2021390118
   Russell T, 2021, EVOL APPL, V14, P1914, DOI 10.1111/eva.13250
   Sabeti PC, 2002, NATURE, V419, P832, DOI 10.1038/nature01140
   Santiago E, 2020, MOL BIOL EVOL, V37, P3642, DOI 10.1093/molbev/msaa169
   Schiffels S, 2020, METHODS MOL BIOL, V2090, P147, DOI 10.1007/978-1-0716-0199-0_7
   Schiffels S, 2014, NAT GENET, V46, P919, DOI 10.1038/ng.3015
   Seabury CM, 2020, G3-GENES GENOM GENET, V10, P1433, DOI 10.1534/g3.119.401002
   Shafer ABA, 2015, MOL ECOL, V24, P328, DOI 10.1111/mec.13034
   Shafer ABA, 2010, MOL ECOL, V19, P4589, DOI 10.1111/j.1365-294X.2010.04828.x
   Skotte L, 2013, GENETICS, V195, P693, DOI 10.1534/genetics.113.154138
   Smith BT, 2021, P ROY SOC B-BIOL SCI, V288, DOI 10.1098/rspb.2020.1945
   Soltis DE, 2006, MOL ECOL, V15, P4261, DOI 10.1111/j.1365-294X.2006.03061.x
   Stevens N, 2022, ANNU REV ENV RESOUR, V47, P261, DOI 10.1146/annurev-environ-112420-015211
   Stewart M, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21201-8
   Stuart AJ, 2015, GEOL J, V50, P338, DOI 10.1002/gj.2633
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Szpiech ZA, 2023, bioRxiv, DOI [10.1101/2021.10.22.465497, 10.1101/2021.10.22.465497, DOI 10.1101/2021.10.22.465497]
   Tarasov A, 2015, BIOINFORMATICS, V31, P2032, DOI 10.1093/bioinformatics/btv098
   Tavares GM, 2019, AM J HUM BIOL, V31, DOI 10.1002/ajhb.23243
   Taylor RS, 2021, MOL ECOL, V30, P6121, DOI 10.1111/mec.16166
   Team RC, 2021, R LANGUAGE ENV STAT
   Udall S., 1967, Endangered species list
   Van de Walle J, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03506-3
   Villanova VL, 2017, CONSERV GENET, V18, P1061, DOI 10.1007/s10592-017-0958-2
   Voight BF, 2006, PLOS BIOL, V4, P446, DOI 10.1371/journal.pbio.0040072
   Wang K, 2020, PLOS GENET, V16, DOI 10.1371/journal.pgen.1008552
   Waples RS, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2013.1339
   Webb G.K., 2018, IIS, V19, P163, DOI [DOI 10.48009/2_IIS_2018_163-173, 10.48009/2 iis 2018 163-173, DOI 10.48009/2IIS2018163-173]
   Weitzel EM., 2021, SE ARCHAEOLOGY, V40, P1, DOI [10.1080/0734578X.2021.1873641, DOI 10.1080/0734578X.2021.1873641]
   Wilder AP, 2023, SCIENCE, V380, P372, DOI 10.1126/science.abn5856
   Willerslev E, 2021, NATURE, V594, P356, DOI 10.1038/s41586-021-03499-y
   Woinarski JCZ, 2015, P NATL ACAD SCI USA, V112, P4531, DOI 10.1073/pnas.1417301112
   Wolverton Steve., 2008, Before Farming, V2008, P1, DOI 10.3828/bfarm.2008.2.3
   Wootton E, 2023, MOL ECOL, V32, P1943, DOI 10.1111/mec.16863
   Wright EA, 2022, J MAMMAL, V103, P723, DOI 10.1093/jmammal/gyab156
   Zamorano LS, 2023, CURR BIOL, V33, P3272, DOI 10.1016/j.cub.2023.06.056
NR 156
TC 6
Z9 6
U1 16
U2 30
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0737-4038
EI 1537-1719
J9 MOL BIOL EVOL
JI Mol. Biol. Evol.
PD MAR 1
PY 2024
VL 41
IS 3
AR msae044
DI 10.1093/molbev/msae044
EA MAR 2024
PG 15
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA MC0N8
UT WOS:001191312300003
PM 38401527
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Landaverde, R
   Rodriguez, MT
   Niewoehner-Green, J
   Kitchel, T
   Chuquillanqui, J
AF Landaverde, Rafael
   Rodriguez, Mary T.
   Niewoehner-Green, Jera
   Kitchel, Tracy
   Chuquillanqui, Jaqueline
TI Climate Change Perceptions and Adaptation Strategies: A Mixed Methods
   Study with Subsistence Farmers in Rural Peru
SO SUSTAINABILITY
LA English
DT Article
DE adaptation; climate change; perceptions; subsistence farmers
ID SMALLHOLDER FARMERS; FOOD-SECURITY; COPING STRATEGIES; NATURAL
   DISASTERS; OPPORTUNITIES; AGRICULTURE; EXPERIENCES; INSECURITY;
   DIMENSIONS; FREQUENCY
AB In Peru, subsistence farmers experience firsthand the direct and indirect impacts of climate change (CC). To understand how farmers adapt their livelihoods to climatic variability, this mixed methods study explored their perceptions and climate adaptability strategies implemented in Huayhuay, Peru. Twenty farmers participated in semi-structured interviews, and 103 completed a survey questionnaire. The results indicated that most farmers perceive changes in temperature, precipitation, and drought that negatively affect agricultural production and local natural resources. To deal with CC, farmers are implementing twenty-six climate adaptation strategies. Diversifying agricultural products and practices, and exploring new economic activities were adaptability strategies identified in this study that the literature has previously documented as having positive implications for agricultural livelihoods. However, some farmers reported that adaptability strategies are failed attempts at local climate action. The results, along with the adaptability literature, revealed that farmers implement locally accessible adaptability strategies based on their climate variability perceptions. Therefore, this study recommends exploring CC perceptions and adaptability strategies with a site-based approach. It is also recommended that future research, local climate planning, and action must focus on the efficiency and inclusiveness of strategies rather than their frequency or levels of adoption. Finally, strengthening the technical capacities and knowledge of CC among subsistence farmers must be a priority for authorities and practitioners in Huayhuay, Peru.
C1 [Landaverde, Rafael] Texas A&M Univ, Dept Agr Leadership Educ & Commun, College Stn, TX 77843 USA.
   [Rodriguez, Mary T.; Niewoehner-Green, Jera; Kitchel, Tracy] Ohio State Univ, Dept Agr Commun Educ & Leadership, Columbus, OH 43210 USA.
   [Chuquillanqui, Jaqueline] Zamorano Univ, Postgrad Dept, Valle Del Yeguare 11101, Tegucigalpa, Honduras.
C3 Texas A&M University System; Texas A&M University College Station;
   University System of Ohio; Ohio State University
RP Landaverde, R (corresponding author), Texas A&M Univ, Dept Agr Leadership Educ & Commun, College Stn, TX 77843 USA.
EM rafael.q@ag.tamu.edu
RI ; Chuquillanqui, Jaqueline/KQV-1918-2024
OI Rodriguez, Mary/0000-0002-8716-2787; Chuquillanqui,
   Jaqueline/0000-0001-8535-0429; Kitchel, Tracy/0000-0002-7563-5874;
   Landaverde, Rafael/0000-0001-6489-0477
CR Acevedo M, 2020, NAT PLANTS, V6, P1231, DOI 10.1038/s41477-020-00783-z
   Alvi S, 2020, AGRICULTURE-BASEL, V10, DOI 10.3390/agriculture10060212
   [Anonymous], 2018, CLIMATE CHANGE HLTH
   [Anonymous], 2016, Climate Change Risk Profile: Ethiopia
   Ansell N, 2004, J S AFR STUD, V30, P673, DOI 10.1080/0305707042000254155
   Ariom TO, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su141811370
   Asare-Nuamah P, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e06928
   Asrat P, 2018, ECOL PROCESS, V7, DOI 10.1186/s13717-018-0118-8
   Assoumana B. T., 2016, Journal of Sustainable Development, V9, P118, DOI 10.5539/jsd.v9n3p118
   Awazi N.P., 2021, African Handbook of Climate Change Adaptation, P87
   Aylas E, 2020, THESIS NATL U PERU L
   Azadi Y, 2019, J ENVIRON MANAGE, V250, DOI 10.1016/j.jenvman.2019.109456
   BBVA Peru, PER CONS NOT ACT CLI
   Bee BA, 2014, AGR HUM VALUES, V31, P607, DOI 10.1007/s10460-014-9503-9
   Below TB, 2015, REG ENVIRON CHANGE, V15, P1169, DOI 10.1007/s10113-014-0620-1
   Below TB, 2012, GLOBAL ENVIRON CHANG, V22, P223, DOI 10.1016/j.gloenvcha.2011.11.012
   Benson Todd., 2021, Disentangling food security from subsistence agriculture in Malawi, DOI 10.2499/9780896294059
   Burnham M, 2017, REG ENVIRON CHANGE, V17, P171, DOI 10.1007/s10113-016-0975-6
   Carmen E, 2022, AMBIO, V51, P1371, DOI 10.1007/s13280-021-01678-9
   Carr ER, 2020, GLOBAL ENVIRON CHANG, V64, DOI 10.1016/j.gloenvcha.2020.102155
   Castells-Quintana D, 2018, WORLD DEV, V104, P183, DOI 10.1016/j.worlddev.2017.11.016
   Climate Diplomacy, GEND CLIM SEC LAT AM
   CORBETT J, 1988, WORLD DEV, V16, P1099, DOI 10.1016/0305-750X(88)90112-X
   Coronese M, 2019, P NATL ACAD SCI USA, V116, P21450, DOI 10.1073/pnas.1907826116
   Creswell JW., 2017, DESIGNING CONDUCTING
   Daramola AY, 2016, INT J DISAST RISK RE, V15, P132, DOI 10.1016/j.ijdrr.2016.01.007
   Davies S., 2016, Adaptable Livelihoods: Coping with Food Insecurity in the Malian Sahel
   Deressa TT, 2011, J AGR SCI-CAMBRIDGE, V149, P23, DOI 10.1017/S0021859610000687
   Dodd W, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17030706
   Dubey SK, 2017, ENVIRON DEV, V21, P38, DOI 10.1016/j.envdev.2016.12.002
   Eakin Hallie, 2014, Environment Development and Sustainability, V16, P123, DOI 10.1007/s10668-013-9466-9
   Ellis F, 1998, J DEV STUD, V35, P1, DOI 10.1080/00220389808422553
   Fadina AMR, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5010015
   Espinosa-Cristia JF, 2019, J PUBLIC AFF, V19, DOI 10.1002/pa.1999
   Fierros-González I, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.672399
   Furberg M, 2018, POPUL ENVIRON, V40, P47, DOI 10.1007/s11111-018-0302-x
   Gautam Y, 2016, J RURAL STUD, V44, P239, DOI 10.1016/j.jrurstud.2016.02.001
   Gebru G., 2018, J Agri Food Sec, V7, P1, DOI [DOI 10.1186/S40066-018-0214-0, 10.1186/s40066-018-0214-0]
   Guttormsen AG, 2014, J AGRIC EDUC EXT, V20, P133, DOI 10.1080/1389224X.2013.775953
   Hamuda H.E. B., 2010, Obuda University e-Bulletin, V1, P87
   Hayes K, 2018, INT J MENT HEALTH SY, V12, DOI 10.1186/s13033-018-0210-6
   IDB, CARB NEUTR COULD PRO
   Iglesias A, 2012, CLIMATIC CHANGE, V112, P143, DOI 10.1007/s10584-011-0344-x
   IPCC. Climate Change, 2022, Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Vvol 2022
   Islam Md. Saiful, 2019, Agricultural Sciences, V10, P386, DOI 10.4236/as.2019.103031
   Israr SM, 2000, TROP MED INT HEALTH, V5, P288, DOI 10.1046/j.1365-3156.2000.00547.x
   Jat ML, 2016, ADV AGRON, V137, P127, DOI 10.1016/bs.agron.2015.12.005
   Jellason NP, 2022, ENVIRON DEV, V43, DOI 10.1016/j.envdev.2022.100733
   Knapp L, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100315
   Lamichhane P, 2021, DATA BRIEF, V39, DOI 10.1016/j.dib.2021.107620
   Landaverde Rafael Quijada, 2021, Journal of International Agricultural and Extension Education, V28, P90, DOI 10.5191/jiaee.2021.28390
   Landini F, 2016, PERFILES LATINOAM, V24, P47, DOI 10.18504/pl2447-005-2016
   Leung CW, 2020, J ACAD NUTR DIET, V120, P395, DOI 10.1016/j.jand.2019.10.012
   Limantol AM, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2433-9
   Lund V, 2006, J AGR ENVIRON ETHIC, V19, P47, DOI 10.1007/s10806-005-4378-9
   Magnan AK, 2020, CURR CLIM CHANGE REP, V6, P166, DOI 10.1007/s40641-020-00166-8
   Maxwell D, 1999, FOOD POLICY, V24, P411, DOI 10.1016/S0306-9192(99)00051-2
   Maxwell Daniel., 2003, Nairobi: CARE Eastern and Central Africa Regional Management Unit and the World Food Programme Vulnerability Assessment and Mapping Unit
   Maxwell DG, 1996, FOOD POLICY, V21, P291, DOI 10.1016/0306-9192(96)00005-X
   McGrath C, 2019, MED TEACH, V41, P1002, DOI 10.1080/0142159X.2018.1497149
   Mitter H, 2019, ENVIRON MANAGE, V63, P804, DOI 10.1007/s00267-019-01158-7
   Morton JF, 2007, P NATL ACAD SCI USA, V104, P19680, DOI 10.1073/pnas.0701855104
   Moser SC, 2010, APPL GEOGR, V30, P464, DOI 10.1016/j.apgeog.2009.09.003
   Mphande E, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su141911901
   Mu L, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187494
   National Institute of Statistics and Information, MED MENURECURSIVO PU
   Navarro-Castañeda S, 2021, LAND USE POLICY, V109, DOI 10.1016/j.landusepol.2021.105651
   Nuhu MG, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su141610432
   Ortiz AM, 2016, RESEARCH IN THE COLLEGE CONTEXT: APPROACHES AND METHODS, 2ND EDITION, P47
   Paltasingh K.R., 2013, Agricultural Economics Research Review, V26, P67, DOI DOI 10.22004/AG.ECON.158492
   Peruvian Ministry of Agriculture and Irrigation, NAT STRAT FAM AGR 20
   Popescu L., 2020, P 3 INT ELECT C ATMO, P21
   Preibisch KL, 2002, HUM ORGAN, V61, P68, DOI 10.17730/humo.61.1.b0xbdqk1lw37yy1j
   Regional Government of Junin, JUN REG STRAT CLIM C
   Rojas-Downing MM, 2017, CLIM RISK MANAG, V16, P145, DOI 10.1016/j.crm.2017.02.001
   Roy S., 2012, INDIAN J EXT ED, V48, P78
   Scoones I., 1998, Working Paper - Institute of Development Studies, University of Sussex
   Scoones I., 2015, SUSTAINABLE LIVELIHO, DOI DOI 10.3362/9781780448749
   Shaffril HAM, 2018, SCI TOTAL ENVIRON, V644, P683, DOI 10.1016/j.scitotenv.2018.06.349
   Sidibé A, 2005, AGR WATER MANAGE, V71, P211, DOI 10.1016/j.agwat.2004.09.002
   Skoufias E, 2003, WORLD DEV, V31, P1087, DOI 10.1016/S0305-750X(03)00069-X
   Soubry B, 2020, J RURAL STUD, V74, P210, DOI 10.1016/j.jrurstud.2019.09.005
   Sultana N, 2012, NAT HAZARDS, V64, P1209, DOI 10.1007/s11069-012-0291-5
   Sutcliffe C, 2016, REG ENVIRON CHANGE, V16, P1215, DOI 10.1007/s10113-015-0842-x
   Swart R, 2014, FRONT ENV SCI-SWITZ, V2, DOI 10.3389/fenvs.2014.00029
   Thomas DR, 2006, AM J EVAL, V27, P237, DOI 10.1177/1098214005283748
   Thorlakson T., 2012, Agric. Food Secur, V1, P1, DOI DOI 10.1186/2048-7010-1-15
   Thornton PK, 2018, GLOBAL ENVIRON CHANG, V52, P37, DOI 10.1016/j.gloenvcha.2018.06.003
   Tonconi Quispe Juan, 2014, Idesia, V32, P29, DOI 10.4067/S0718-34292014000200005
   USDA, PARTN CLIM SMART COM
   Valdivia C, 2014, TOUR MANAG PERSPECT, V11, P18, DOI 10.1016/j.tmp.2014.02.004
   Vignola R, 2015, AGR ECOSYST ENVIRON, V211, P126, DOI 10.1016/j.agee.2015.05.013
   Wagena MB, 2018, SCI TOTAL ENVIRON, V635, P132, DOI 10.1016/j.scitotenv.2018.04.110
   Whitmarsh L., 2018, Psychology and climate change, P13, DOI [DOI 10.1016/B978-0-12-813130-5.00002-3, 10.1016/b978-0-12813130-5.00002-3, DOI 10.1016/B978-0-12813130-5.00002-3]
   Winarto Y. T., 2018, IOP Conference Series: Earth and Environmental Science, V166, DOI 10.1088/1755-1315/166/1/012049
   Wiréhn L, 2018, LAND USE POLICY, V77, P63, DOI 10.1016/j.landusepol.2018.04.059
   WMO, WMO ISS REP STAT CLI
   World Bank, PER AGR PROD GROWS S
   World Bank, PERU
   Zhang YQW, 2017, CLIMATE, V5, DOI 10.3390/cli5040095
   Zhou WF, 2021, NAT HAZARDS, V106, P255, DOI 10.1007/s11069-020-04460-4
NR 101
TC 6
Z9 6
U1 9
U2 20
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD DEC
PY 2022
VL 14
IS 23
AR 16015
DI 10.3390/su142316015
PG 21
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA 6X2IW
UT WOS:000896244200001
OA gold
DA 2025-01-10
ER

PT J
AU Zhuang, CQ
   Choudhary, R
   Mavrogianni, A
AF Zhuang, Chaoqun
   Choudhary, Ruchi
   Mavrogianni, Anna
TI Uncertainty-based optimal energy retrofit methodology for building heat
   electrification with enhanced energy flexibility and climate
   adaptability
SO APPLIED ENERGY
LA English
DT Article
DE Air -source heat pump; Building electrification; Uncertainty; Energy
   flexibility; Climate adaptability
ID DEMAND RESPONSE; PUMP; PERFORMANCE; PRICE
AB To reach net zero emissions by 2050, the UK government relies heavily on heat degasification in buildings by using heat pump technology. However, existing buildings may have terminal radiators that require a higher operating temperature than what heat pumps typically provide. Increasing the size of radiators and thermally insulating building envelopes could be a potential solution, but the feasibility of these practices is uncertain due to space constraints and high retrofit costs. This study investigates the feasibility and potential benefits of incorporating air-source heat pumps into existing gas boiler heating systems to meet heating demands. The proposed probabilistic optimal air-source heat pump design method enhances energy flexibility and climate adaptability, taking into account a wide range of uncertainty sources and multiple flexibility services (e.g., energy and ancillary services). Heating systems of three educational buildings at the University of Cambridge are used as a testbed to assess and validate the effectiveness of the proposed method, under future climate scenarios and projected decreases in heating demand due to climate change. Results indicate that the best retrofit alter-native of the hybrid heating system reduces carbon emissions by 88%, total costs by 54% over its lifespan, and has an average payback period of around 3 years. Air-source heat pumps can meet the majority of the heating demand (around 80%) with gas boilers used for "top-up" heating during high demand. Furthermore, air-source heat pumps' design capacity can fulfil future cooling demand even if retrofit optimization is initially focused on meeting heating needs.
C1 [Zhuang, Chaoqun; Choudhary, Ruchi] Alan Turing Inst, Data Centr Engn, London, England.
   [Zhuang, Chaoqun; Choudhary, Ruchi] Univ Cambridge, Dept Engn, Energy Efficient Cities Initiat, Cambridge, England.
   [Mavrogianni, Anna] UCL, Inst Environm Design & Engn, Bartlett Fac Built Environm, London, England.
C3 University of Cambridge; University of London; University College London
RP Zhuang, CQ (corresponding author), Alan Turing Inst, Data Centr Engn, London, England.; Zhuang, CQ (corresponding author), Univ Cambridge, Dept Engn, Energy Efficient Cities Initiat, Cambridge, England.
EM czhuang@turing.ac.uk
FU AI for Science and Government (ASG), UKRI's Strategic Priorities Fund
   [EP/T001569/1, EP/W006022/1]; Towards Turing 2.0 under the EPSRC
   [EP/W037211/1]; Alan Turing Institute; SPF [EP/T001569/1] Funding
   Source: UKRI
FX The research presented in this paper was financially supported by the AI
   for Science and Government (ASG), UKRI's Strategic Priorities Fund
   awarded to the Alan Turing Institute, UK (EP/T001569/1 and
   EP/W006022/1). This work was also supported by Towards Turing 2.0 under
   the EPSRC Grant EP/W037211/1 & The Alan Turing Institute: C. Zhuang
   acknowledges support through an Alan Turing Institute Post-Doctoral
   Enrichment Award.
CR Annesi-Maesano I, 2016, J ALLERGY CLIN IMMUN, V138, P57, DOI 10.1016/j.jaci.2016.02.043
   [Anonymous], 2012, Assessment of Demand Response and Advanced Metering
   [Anonymous], 2018, 145112 EN
   ASHRAE, 2014, ASHRAE Guideline 14: Measurement of Energy and Demand Savings
   ASHRAE, 1996, HVAC SYST EQ, P1
   Avci M, 2013, ENERG BUILDINGS, V60, P199, DOI 10.1016/j.enbuild.2013.01.008
   Baeten B, 2017, APPL ENERG, V195, P184, DOI 10.1016/j.apenergy.2017.03.055
   Bechtel S, 2020, ENERG BUILDINGS, V226, DOI 10.1016/j.enbuild.2020.110364
   Bee E, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5120132
   Beis, 2017, ENERGY IND STRATEG, V58, P1112
   BEIS, 2020, UK ENSHR NEW TARG LA
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   Bober W, 2018, MATLAB ESSENTIALS, P105, DOI [10.1201/b22223-4, DOI 10.1201/B22223-4]
   CEN, 4422A1 EN CEN
   Chakraborty D, 2021, APPL ENERG, V291, DOI 10.1016/j.apenergy.2021.116807
   Daikin: Internet - UK, 2022, DAIK UK PRIC BOOK HE
   Department of Energy & Climate Change, 2015, DIGEST UK ENERGY STA
   Eames M, 2011, FUT WEATH FILES
   ensims, ENSIMS WEB TOOLS
   Entso-e, ENTSO E BAL REP 2022
   Gang WJ, 2015, SCI TECHNOL BUILT EN, V21, P789, DOI 10.1080/23744731.2015.1056657
   Government UK, 2021, GREEN BOOK SUPPL GUI
   GreenMatch, 2022, AIR SOURC HEAT PUMP
   Griffith B., 2008, METHODOLOGY MODELING
   Haarsma RJ, 2016, GEOSCI MODEL DEV, V9, P4185, DOI 10.5194/gmd-9-4185-2016
   Hang Y, 2014, ENERG BUILDINGS, V82, P746, DOI 10.1016/j.enbuild.2014.07.078
   Hansen J, 2010, REV GEOPHYS, V48, DOI 10.1029/2010RG000345
   Heller AJ, 2002, APPL ENERG, V72, P371, DOI 10.1016/S0306-2619(02)00020-X
   Heo Y, 2012, ENERG BUILDINGS, V47, P550, DOI 10.1016/j.enbuild.2011.12.029
   Hirth L, 2018, APPL ENERG, V225, P1054, DOI 10.1016/j.apenergy.2018.04.048
   Jenkins D, 2008, ENERG BUILDINGS, V40, P1901, DOI 10.1016/j.enbuild.2008.04.015
   Jenkins D, 2008, ENERG BUILDINGS, V40, P874, DOI 10.1016/j.enbuild.2007.06.006
   Jin X, 2017, P AMER CONTR CONF, P4147, DOI 10.23919/ACC.2017.7963592
   Kelly JA, 2016, ENERG POLICY, V98, P431, DOI 10.1016/j.enpol.2016.09.016
   Kim Y., 2014, 8th ACM International Conference on Ubiquitous Information Management and Communication, Cambodia, P1, DOI [10.1109/tdc.2014.6863424, DOI 10.1109/TDC.2014.6863424]
   Klein S.A., 1976, ASHRAE T, V82, P623
   Lämmle M, 2022, ENERGY, V242, DOI 10.1016/j.energy.2021.122952
   Le KX, 2020, APPL ENERG, V257, DOI 10.1016/j.apenergy.2019.113976
   Le KX, 2019, APPL ENERG, V250, P633, DOI 10.1016/j.apenergy.2019.05.041
   Leibowicz BD, 2018, APPL ENERG, V230, P1311, DOI 10.1016/j.apenergy.2018.09.046
   Li DHW, 2013, ENERGY, V54, P1, DOI 10.1016/j.energy.2013.01.070
   Lingard J, 2021, BUILD SERV ENG RES T, V42, P279, DOI 10.1177/0143624420975707
   Mattinen MK, 2015, J IND ECOL, V19, P61, DOI 10.1111/jiec.12166
   Meesenburg W, 2020, SUSTAIN ENERGY GRIDS, V23, DOI 10.1016/j.segan.2020.100382
   Meesenburg W, 2020, APPL ENERG, V271, DOI 10.1016/j.apenergy.2020.115126
   Mei VC, 1987, LIFE CYCLE COST ANAL
   Meteotest, METEONORM 8
   Office for National Statistics, 2018, INFL PRIC IND OFF NA
   Owen AD, 2019, POWER INTERCONNECT S, P52, DOI [10.4324/9780429424526-5, DOI 10.4324/9780429424526-5]
   Petrou G, 2019, BUILD SERV ENG RES T, V40, P30, DOI 10.1177/0143624418792340
   Rahmani-andebili M, 2016, ELECTR POW SYST RES, V132, P115, DOI 10.1016/j.epsr.2015.11.006
   Rodríguez LR, 2019, APPL ENERG, V233, P943, DOI 10.1016/j.apenergy.2018.09.103
   Safa AA, 2015, ENERG BUILDINGS, V94, P80, DOI 10.1016/j.enbuild.2015.02.041
   Shi DC, 2022, BUILD ENVIRON, V223, DOI 10.1016/j.buildenv.2022.109505
   Tang H, 2021, ENERGY, V221, DOI 10.1016/j.energy.2021.119756
   U.S. Department of Energy, OP MAINT YOUR HEAT P
   U.S. EIA, 2022, ANN ENERGY OUTLOOK 2, P108
   UK Government, 2022, BOIL UPGR SCHEM
   UK Government. Department for Business Energy & Industrial Strategy (BEIS), GUID PART UK ETS 202
   Wang D, 2012, APPL ENERG, V96, P104, DOI 10.1016/j.apenergy.2011.12.005
   Ward R, 2021, DATA-CENTRIC ENG, V2, DOI 10.1017/dce.2021.12
   Yassaghi H, 2020, APPL ENERG, V278, DOI 10.1016/j.apenergy.2020.115655
   Yoon JH, 2014, ENERG BUILDINGS, V80, P531, DOI 10.1016/j.enbuild.2014.05.002
   Zhang ML, 2022, CSEE J POWER ENERGY, V8, P769, DOI 10.17775/CSEEJPES.2020.06070
   Zhuang CQ, 2020, INDOOR BUILT ENVIRON, V29, P1214, DOI 10.1177/1420326X19899442
NR 65
TC 5
Z9 6
U1 7
U2 44
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0306-2619
EI 1872-9118
J9 APPL ENERG
JI Appl. Energy
PD JUL 1
PY 2023
VL 341
AR 121111
DI 10.1016/j.apenergy.2023.121111
EA APR 2023
PG 18
WC Energy & Fuels; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels; Engineering
GA G0HB5
UT WOS:000986055800001
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Ward, FA
   Amer, SA
   Salman, DA
   Belcher, WR
   Khamees, AA
   Saleh, HS
   Saeed, AAA
   Jazaa, HS
AF Ward, Frank A.
   Amer, Saud A.
   Salman, Dina A.
   Belcher, Wayne R.
   Khamees, Ahmed Abdulhamza
   Saleh, Hatem Salloom
   Saeed, Aysar Abdul Azeez
   Jazaa, Hamdiea Skheel
TI Economic optimization to guide climate water stress adaptation
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Water resources; Economics; Optimization; Middle east
ID ENERGY-FOOD NEXUS; RESOURCES MANAGEMENT; ENVIRONMENTAL FLOWS;
   COST-EFFECTIVENESS; RIVER-BASIN; MULTICRITERIA EVALUATION; QUALITY
   MANAGEMENT; SUSTAINABLE WATER; GROUNDWATER-FLOW; DECISION-SUPPORT
AB Allocation of water over its six dimensions of quantity, quality, timing, location, price, and cost remains an ongoing challenge facing water resource planning worldwide. This challenge is magnified with growing evidence of climate change and related water supply stressors. This stress will challenge food, energy, and water systems as climate adaptation policy measures see continued debate. Despite numerous achievements made many by previous works, few attempts have scanned the literature on economic optimization analysis for water resources planning to discover affordable climate adaptation measures. This paper aims to fill that gap by reviewing the literature on water resource optimization analysis at the basin scale to guide discovery of affordable climate adaptation measures. It does so by posing the question "What principles, practices, and recent developments are available to guide discovery of policy measures to improve water resource system adaptions to growing evidence of climate water stress?" It describes past achievements and identifies improvements needed for optimization analysis to inform policy debates for crafting plans to improve climate resilience. It describes an economic conceptual framework as well as identifying data needs for conducting economic optimization exercises to support river basin planning faced by the challenge of managing the six water dimensions described above. It presents an example from an ongoing issue facing water planners in the Middle East. Conclusions find considerable utility in the use of economic optimization exercises to guide climate water stressadaptation. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
C1 [Ward, Frank A.] New Mexico State Univ, Dept Agr Econ & Agr Business, Las Cruces, NM 88011 USA.
   [Amer, Saud A.; Belcher, Wayne R.] US Geol Survey, Washington, DC 20242 USA.
   [Salman, Dina A.] New Mexico State Univ, Las Cruces, NM 88003 USA.
   [Khamees, Ahmed Abdulhamza] Iraqi Minist Agr, Baghdad, Iraq.
   [Saleh, Hatem Salloom] Iraqi Minist Water, Baghdad, Iraq.
   [Saeed, Aysar Abdul Azeez; Jazaa, Hamdiea Skheel] Iraqi Minist Water Resources, Baghdad, Iraq.
C3 New Mexico State University; United States Department of the Interior;
   United States Geological Survey; New Mexico State University
RP Ward, FA (corresponding author), New Mexico State Univ, Dept Agr Econ & Agr Business, Las Cruces, NM 88011 USA.
EM fward@nmsu.edu; samer@usgs.gov; dinasalm@nmsu.edu; wbelcher@usgs.gov;
   ahmedhamza813@yahoo.com; hatem_sallom@yahoo.com; aiseralnife@yahoo.com;
   hamdya_sa04@yahoo.com
FU U.S. Department of State; New Mexico State University Agricultural
   Experiment Station; U.S. Geological Survey, Office of International
   Program
FX Thanks are owed for support by the U.S. Department of State, the New
   Mexico State University Agricultural Experiment Station, and the U.S.
   Geological Survey, Office of International Program.
CR Acreman MC, 2010, FRESHWATER BIOL, V55, P32, DOI 10.1111/j.1365-2427.2009.02181.x
   Adham A, 2018, INT SOIL WATER CONSE, V6, P297, DOI 10.1016/j.iswcr.2018.07.003
   Adler MD, 1999, YALE LAW J, V109, P165, DOI 10.2307/797489
   Aeschbach-Hertig W, 2012, NAT GEOSCI, V5, P853, DOI [10.1038/ngeo1617, 10.1038/NGEO1617]
   Al-Azawi AAO, 2017, INT J WATER RESOUR D, V33, P628, DOI 10.1080/07900627.2016.1213705
   Al-Faraj FAM, 2015, WATER POLICY, V17, P865, DOI 10.2166/wp.2014.237
   Al-Handal A, 2015, WETLANDS, V35, P31, DOI 10.1007/s13157-014-0590-6
   Al-Jawad JY, 2019, J ENVIRON MANAGE, V239, P211, DOI 10.1016/j.jenvman.2019.03.045
   Al-Jawad JY, 2019, SCI TOTAL ENVIRON, V651, P1877, DOI 10.1016/j.scitotenv.2018.10.063
   Al-Quraishi AK, 2021, SCI TOTAL ENVIRON, V768, DOI 10.1016/j.scitotenv.2020.144445
   Al-Smairan M, 2012, RENEW SUST ENERG REV, V16, P4500, DOI 10.1016/j.rser.2012.04.033
   Albrecht TR, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa9c6
   Aldieri L, 2021, ENERGIES, V14, DOI 10.3390/en14144269
   Algaze G, 2001, CURR ANTHROPOL, V42, P199, DOI 10.1086/320005
   Allawi MF, 2018, ENVIRON SCI POLLUT R, V25, P13446, DOI 10.1007/s11356-018-1867-8
   Almaarofi S.S., 2017, INDEX STAT METHODS I, V43, P21
   Alvarez JFO, 2004, IRRIGATION SCI, V23, P61, DOI 10.1007/s00271-004-0094-x
   Alvarez S, 2016, WATER-SUI, V8, DOI 10.3390/w8040112
   Anagnostopoulos JS, 2007, ENERG CONVERS MANAGE, V48, P2663, DOI 10.1016/j.enconman.2007.04.016
   Arena C, 2010, WATER SCI TECHNOL, V61, P3050, DOI 10.2166/wst.2010.220
   Attard G, 2016, HYDROGEOL J, V24, P5, DOI 10.1007/s10040-015-1317-3
   Barbier EB, 2017, ENVIRON RESOUR ECON, V68, P663, DOI 10.1007/s10640-016-0040-4
   Bauer CJ, 2004, WATER RESOUR RES, V40, DOI 10.1029/2003WR002838
   Bazilian M, 2011, ENERG POLICY, V39, P7896, DOI 10.1016/j.enpol.2011.09.039
   Beh EHY, 2015, ENVIRON MODELL SOFTW, V68, P181, DOI 10.1016/j.envsoft.2015.02.006
   Biggs EM, 2015, ENVIRON SCI POLICY, V54, P389, DOI 10.1016/j.envsci.2015.08.002
   Bilitewski B, 2008, WASTE MANAGE, V28, P2760, DOI 10.1016/j.wasman.2008.03.032
   Birol E, 2006, SCI TOTAL ENVIRON, V365, P105, DOI 10.1016/j.scitotenv.2006.02.032
   Black PE, 2012, J AM WATER RESOUR AS, V48, P244, DOI 10.1111/j.1752-1688.2011.00609.x
   Blanco-Gutiérrez I, 2013, J ENVIRON MANAGE, V128, P144, DOI 10.1016/j.jenvman.2013.04.037
   BOGLE MGV, 1979, WATER RESOUR RES, V15, P1229, DOI 10.1029/WR015i005p01229
   Booker JF, 2012, NAT RESOUR MODEL, V25, P168, DOI 10.1111/j.1939-7445.2011.00105.x
   Bouraoui F, 2014, SCI TOTAL ENVIRON, V468, P1267, DOI 10.1016/j.scitotenv.2013.07.066
   Bozorg-Haddad O, 2020, J WATER SUPPLY RES T, V69, P85, DOI 10.2166/aqua.2019.049
   Brozovic N, 2010, RESOUR ENERGY ECON, V32, P154, DOI 10.1016/j.reseneeco.2009.11.010
   Bryan BA, 2008, J ENVIRON MANAGE, V88, P1175, DOI 10.1016/j.jenvman.2007.06.003
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Buysse J, 2007, AGR ECOSYST ENVIRON, V120, P70, DOI 10.1016/j.agee.2006.03.035
   Carey JM, 2002, AM J AGR ECON, V84, P171, DOI 10.1111/1467-8276.00251
   Charles MB, 2007, ENERG POLICY, V35, P5737, DOI 10.1016/j.enpol.2007.06.008
   Chen JC, 2003, ENG APPL ARTIF INTEL, V16, P149, DOI 10.1016/S0952-1976(03)00056-3
   Chen ZQR, 2011, J HYDROL ENG, V16, P1083, DOI 10.1061/(ASCE)HE.1943-5584.0000208
   Chenoweth J, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR010269
   Cho JH, 2004, J ENVIRON MANAGE, V73, P229, DOI 10.1016/j.jenvman.2004.07.004
   Chong H, 2006, ANNU REV ENV RESOUR, V31, P239, DOI 10.1146/annurev.energy.31.020105.100323
   Chowdhury F, 2013, APPL GEOGR, V45, P58, DOI 10.1016/j.apgeog.2013.07.020
   Cicero M.T, 1899, OFFICIIS
   Conway D, 2015, NAT CLIM CHANGE, V5, P837, DOI [10.1038/nclimate2735, 10.1038/NCLIMATE2735]
   Cools J, 2011, ENVIRON MODELL SOFTW, V26, P44, DOI 10.1016/j.envsoft.2010.04.017
   Cortignani R, 2009, AGR WATER MANAGE, V96, P1785, DOI 10.1016/j.agwat.2009.07.016
   Cox WE, 2007, J WATER RES PL-ASCE, V133, P456, DOI 10.1061/(ASCE)0733-9496(2007)133:5(456)
   Croser J, 2011, WORLD TRADE REV, V10, P297, DOI 10.1017/S1474745611000176
   Crossman ND, 2009, ECOL ECON, V68, P654, DOI 10.1016/j.ecolecon.2008.05.003
   Das R, 2014, DESALINATION, V336, P97, DOI 10.1016/j.desal.2013.12.026
   Delgado W.R., 2020, SOLAR DESALINATION C, V7
   Dell'Anna F, 2021, ENERG POLICY, V149, DOI 10.1016/j.enpol.2020.112031
   DeVincentis AJ, 2020, J ENVIRON MANAGE, V261, DOI 10.1016/j.jenvman.2020.110205
   Dillon P, 2010, WATER SCI TECHNOL, V62, P2338, DOI 10.2166/wst.2010.444
   Djukic M, 2016, RENEW SUST ENERG REV, V59, P1419, DOI 10.1016/j.rser.2016.01.050
   Döll P, 2002, CLIMATIC CHANGE, V54, P269, DOI 10.1023/A:1016124032231
   Duarte CM, 2009, BIOSCIENCE, V59, P967, DOI 10.1525/bio.2009.59.11.8
   Eckart K, 2017, SCI TOTAL ENVIRON, V607, P413, DOI 10.1016/j.scitotenv.2017.06.254
   ELLINGWOOD B, 1993, J WATER RES PL-ASCE, V119, P64, DOI 10.1061/(ASCE)0733-9496(1993)119:1(64)
   Endo A, 2017, J HYDROL-REG STUD, V11, P20, DOI 10.1016/j.ejrh.2015.11.010
   Fahad S., 2021, CLIMATE CHANGE PLANT, V1st
   Fahad S., 2021, PLANT GROWTH REGULAT
   Fahad S., 2021, Abiotic stress in plants
   Fahad S., 2019, PLANT TOLERANCE ENV, P103, DOI DOI 10.1201/9780203705315-7
   Ferrer J, 2012, SCI TOTAL ENVIRON, V440, P42, DOI 10.1016/j.scitotenv.2012.08.032
   Ferrer PAF, 2017, RENEW SUST ENERG REV, V76, P507, DOI 10.1016/j.rser.2017.03.074
   Feyen L, 2005, WATER RESOUR RES, V41, DOI 10.1029/2003WR002901
   Garcia S, 2004, RESOUR ENERGY ECON, V26, P1, DOI 10.1016/j.reseneeco.2003.05.001
   García-Vila M, 2012, EUR J AGRON, V36, P21, DOI 10.1016/j.eja.2011.08.003
   George B, 2011, AGR WATER MANAGE, V98, P733, DOI 10.1016/j.agwat.2010.12.004
   Ghaffour N, 2013, DESALINATION, V309, P197, DOI 10.1016/j.desal.2012.10.015
   Giordano R, 2007, J ENVIRON MANAGE, V84, P213, DOI 10.1016/j.jenvman.2006.05.006
   Grantham RW, 2015, FISHERIES MANAG ECOL, V22, P458, DOI 10.1111/fme.12144
   Gregory PJ, 2005, PHILOS T R SOC B, V360, P2139, DOI 10.1098/rstb.2005.1745
   Grey D, 2007, WATER POLICY, V9, P545, DOI 10.2166/wp.2007.021
   Gupta J, 2008, PHYS CHEM EARTH, V33, P28, DOI 10.1016/j.pce.2007.04.003
   Hajkowicz S, 2009, LAND USE POLICY, V26, P471, DOI 10.1016/j.landusepol.2008.06.004
   Hall CAS, 2009, ENERGIES, V2, P25, DOI 10.3390/en20100025
   Hameed M, 2019, WATER-SUI, V11, DOI 10.3390/w11040682
   Hamilton AJ, 2007, VADOSE ZONE J, V6, P823, DOI 10.2136/vzj2007.0026
   Hanjra MA, 2010, FOOD POLICY, V35, P365, DOI 10.1016/j.foodpol.2010.05.006
   Hathaway OA, 2002, YALE LAW J, V111, P1935, DOI 10.2307/797642
   Heckelei T, 2003, EUR REV AGRIC ECON, V30, P27, DOI 10.1093/erae/30.1.27
   Heidecke C, 2010, AGR ECON-BLACKWELL, V41, P135, DOI 10.1111/j.1574-0862.2009.00431.x
   Heinz I, 2007, WATER RESOUR MANAG, V21, P1103, DOI 10.1007/s11269-006-9101-8
   Helfer F, 2014, J MEMBRANE SCI, V453, P337, DOI 10.1016/j.memsci.2013.10.053
   Hepbasli A, 2008, RENEW SUST ENERG REV, V12, P593, DOI 10.1016/j.rser.2006.10.001
   HOWITT RE, 1995, AM J AGR ECON, V77, P329, DOI 10.2307/1243543
   Howitt RE, 2012, ENVIRON MODELL SOFTW, V38, P244, DOI 10.1016/j.envsoft.2012.06.013
   Hyde KM, 2005, J ENVIRON MANAGE, V77, P278, DOI 10.1016/j.jenvman.2005.06.011
   Iglesias E, 2008, WATER RESOUR RES, V44, DOI 10.1029/2006WR005708
   Isik M, 2004, ENVIRON RESOUR ECON, V27, P247, DOI 10.1023/B:EARE.0000017624.07757.3f
   Issa IE, 2017, INT J SEDIMENT RES, V32, P127, DOI 10.1016/j.ijsrc.2015.12.001
   Issa IE, 2013, HYDROLOG SCI J, V58, P1456, DOI 10.1080/02626667.2013.789138
   Jalilov SM, 2018, J HYDROL, V557, P407, DOI 10.1016/j.jhydrol.2017.12.040
   Jobstvogt N, 2014, ECOL ECON, V97, P10, DOI 10.1016/j.ecolecon.2013.10.019
   Jones C, 2008, J HYDROL, V353, P59, DOI 10.1016/j.jhydrol.2008.01.029
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Jones MC, 2015, FISH FISH, V16, P603, DOI 10.1111/faf.12081
   Jorgensen SL, 2013, ECOL ECON, V92, P58, DOI 10.1016/j.ecolecon.2012.07.015
   Kanellopoulos A, 2010, J AGR ECON, V61, P274, DOI 10.1111/j.1477-9552.2010.00241.x
   Kang YH, 2009, PROG NAT SCI-MATER, V19, P1665, DOI 10.1016/j.pnsc.2009.08.001
   Kasprzyk JR, 2013, ENVIRON MODELL SOFTW, V42, P55, DOI 10.1016/j.envsoft.2012.12.007
   Kelman J, 2002, INT J WATER RESOUR D, V18, P391, DOI 10.1080/0790062022000006899
   Khattab MFO, 2014, ARAB J GEOSCI, V7, P3557, DOI 10.1007/s12517-013-1026-y
   Kibaroglu A, 2015, WATER INT, V40, P824, DOI 10.1080/02508060.2015.1078577
   Kibaroglu A, 2015, WATER INT, V40, P153, DOI 10.1080/02508060.2014.978971
   Kibaroglu A, 2013, GLOBAL GOV, V19, P279, DOI 10.1163/19426720-01902008
   Kobya M, 2020, ENVIRON TECHNOL INNO, V17, DOI 10.1016/j.eti.2019.100519
   Kondolf GM, 1996, WATER RESOUR RES, V32, P2589, DOI 10.1029/96WR00898
   Konikow LF, 2015, GROUNDWATER, V53, P2, DOI 10.1111/gwat.12306
   Kroon J, 2012, COMMUNITY DENT ORAL, V40, P441, DOI 10.1111/j.1600-0528.2012.00681.x
   Krutilla JV, 1967, AM ECON REV, V57, P777
   Kucukmehmetoglu M, 2010, J WATER RES PLAN MAN, V136, P95, DOI 10.1061/(ASCE)0733-9496(2010)136:1(95)
   Lal R, 2004, SCIENCE, V304, P1623, DOI 10.1126/science.1097396
   Lee JG, 2012, ENVIRON MODELL SOFTW, V37, P6, DOI 10.1016/j.envsoft.2012.04.011
   Li YP, 2008, J ENVIRON MANAGE, V88, P93, DOI 10.1016/j.jenvman.2007.01.056
   Li YP, 2009, J ENVIRON MANAGE, V90, P2402, DOI 10.1016/j.jenvman.2008.11.007
   Li YP, 2009, CLIM RES, V39, P31, DOI 10.3354/cr00797
   Love HA, 1997, J POLICY MODEL, V19, P207
   Lu HM, 2001, DESALINATION, V136, P13, DOI 10.1016/S0011-9164(01)00160-6
   Mandique EJ, 2007, SPE RESERV EVAL ENG, V10, P667
   MARGLIN SA, 1963, Q J ECON, V77, P95, DOI 10.2307/1879374
   Markowitz H, 2014, EUR J OPER RES, V234, P346, DOI 10.1016/j.ejor.2012.08.023
   Markowitz HM, 2010, ANNU REV FINANC ECON, V2, P1, DOI 10.1146/annurev-financial-011110-134602
   MARTIN QW, 1987, J WATER RES PL-ASCE, V113, P677, DOI 10.1061/(ASCE)0733-9496(1987)113:5(677)
   McConnachie MM, 2012, BIOL CONSERV, V155, P128, DOI 10.1016/j.biocon.2012.06.006
   McCulloch J, 2007, HYDROL EARTH SYST SC, V11, P3, DOI 10.5194/hess-11-3-2007
   Medellín-Azuara J, 2012, AGR WATER MANAGE, V108, P73, DOI 10.1016/j.agwat.2011.12.017
   Medellín-Azuara J, 2010, SCI TOTAL ENVIRON, V408, P5639, DOI 10.1016/j.scitotenv.2009.08.013
   Michelsen A.M., 2002, EC VALUE WATER AGR C, P423
   Milillo P, 2016, SCI REP-UK, V6, DOI 10.1038/srep37408
   Mini C, 2014, WATER POLICY, V16, P1054, DOI 10.2166/wp.2014.029
   Ministry of Water Resources Republic of Iraq, 2014, STRAT WAT LAND IR
   Mishan E.J., 2015, ELEMENTS COST BENEF
   Missimer TM, 2018, DESALINATION, V434, P198, DOI 10.1016/j.desal.2017.07.012
   Molden D, 2010, AGR WATER MANAGE, V97, P528, DOI 10.1016/j.agwat.2009.03.023
   Molina JL, 2012, WATER RESOUR MANAG, V26, P2951, DOI 10.1007/s11269-012-0058-5
   Montesinos P, 1999, WATER RESOUR RES, V35, P3467, DOI 10.1029/1999WR900167
   Munda G, 2006, LAND USE POLICY, V23, P86, DOI 10.1016/j.landusepol.2004.08.012
   MUNDA G, 1994, ECOL ECON, V10, P97, DOI 10.1016/0921-8009(94)90002-7
   Ngwakwe CC, 2012, SUSTAIN DEV, V20, P28, DOI 10.1002/sd.462
   Ning RY, 2006, DESALINATION, V201, P315, DOI 10.1016/j.desal.2006.06.006
   Ning SK, 2007, J ENVIRON MANAGE, V84, P427, DOI 10.1016/j.jenvman.2006.06.014
   Olmstead SM, 2014, ENERG ECON, V46, P500, DOI 10.1016/j.eneco.2013.09.005
   Olmstead SM, 2010, REV ENV ECON POLICY, V4, P179, DOI 10.1093/reep/req004
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Othman AA, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11222632
   Oweis T, 2006, AGR WATER MANAGE, V80, P57, DOI 10.1016/j.agwat.2005.07.004
   Pahl-Wostl C, 2009, GLOBAL ENVIRON CHANG, V19, P354, DOI 10.1016/j.gloenvcha.2009.06.001
   Panagopoulos Y, 2011, J ENVIRON MANAGE, V92, P2823, DOI 10.1016/j.jenvman.2011.06.035
   Paris Q, 1998, AM J AGR ECON, V80, P124, DOI 10.2307/3180275
   Peng N, 2012, PROG POLYM SCI, V37, P1401, DOI 10.1016/j.progpolymsci.2012.01.001
   Perry C, 2001, IRRIG DRAIN, V50, P1, DOI 10.1002/ird.8
   Perry LG, 2012, GLOBAL CHANGE BIOL, V18, P821, DOI 10.1111/j.1365-2486.2011.02588.x
   Piscopo V, 2020, WATER-SUI, V12, DOI 10.3390/w12092576
   Plappally AK, 2013, DESALIN WATER TREAT, V51, P200, DOI 10.1080/19443994.2012.708996
   Polglase PJ, 2013, CLIMATIC CHANGE, V121, P161, DOI 10.1007/s10584-013-0882-5
   Pretty JN, 2000, AGR SYST, V65, P113, DOI 10.1016/S0308-521X(00)00031-7
   Procházka P, 2018, WATER-SUI, V10, DOI 10.3390/w10101482
   Propst DL, 2004, T AM FISH SOC, V133, P922, DOI 10.1577/T03-057.1
   Qureshi ME, 2013, ENVIRON MODELL SOFTW, V41, P98, DOI 10.1016/j.envsoft.2012.11.007
   Ramaswami A, 2012, J IND ECOL, V16, P801, DOI 10.1111/j.1530-9290.2012.00566.x
   Rasul G, 2016, CLIM POLICY, V16, P682, DOI 10.1080/14693062.2015.1029865
   Rasul G, 2014, ENVIRON SCI POLICY, V39, P35, DOI 10.1016/j.envsci.2014.01.010
   Read L, 2014, J ENVIRON MANAGE, V133, P343, DOI 10.1016/j.jenvman.2013.11.045
   Ren SG, 2018, J CLEAN PROD, V173, P245, DOI 10.1016/j.jclepro.2016.08.113
   RIDD MK, 1995, INT J REMOTE SENS, V16, P2165, DOI 10.1080/01431169508954549
   Ringler C, 2013, CURR OPIN ENV SUST, V5, P617, DOI 10.1016/j.cosust.2013.11.002
   Rivers N, 2013, ENVIRON RESOUR ECON, V55, P419, DOI 10.1007/s10640-013-9633-3
   Röhm O, 2003, AM J AGR ECON, V85, P254, DOI 10.1111/1467-8276.00117
   Ruijs A, 2008, ECOL ECON, V66, P506, DOI 10.1016/j.ecolecon.2007.10.015
   Sadoff CW, 2005, WATER INT, V30, P420, DOI 10.1080/02508060508691886
   Salman DA, 2014, J AM WATER RESOUR AS, V50, P1208, DOI 10.1111/jawr.12186
   Sample DJ, 2014, J CLEAN PROD, V75, P174, DOI 10.1016/j.jclepro.2014.03.075
   Schoups G, 2005, HYDROL EARTH SYST SC, V9, P549, DOI 10.5194/hess-9-549-2005
   Schoups G, 2005, J HYDROL, V311, P20, DOI 10.1016/j.jhydrol.2005.01.001
   Schoups G, 2006, WATER RESOUR RES, V42, DOI 10.1029/2006WR004922
   Shafroth PB, 2010, FRESHWATER BIOL, V55, P68, DOI 10.1111/j.1365-2427.2009.02271.x
   Shah T, 2009, WORLD DEV, V37, P422, DOI 10.1016/j.worlddev.2008.05.008
   Sharpley AN, 2001, COMMUN SOIL SCI PLAN, V32, P1071, DOI 10.1081/CSS-100104104
   Sherif M, 2012, WATER RESOUR MANAG, V26, P751, DOI 10.1007/s11269-011-9943-6
   Shmelev SE, 2011, ECOL ECON, V70, P2039, DOI 10.1016/j.ecolecon.2011.06.003
   Siddiqi A, 2011, ENERG POLICY, V39, P4529, DOI 10.1016/j.enpol.2011.04.023
   Siyal AA, 2018, J ENVIRON MANAGE, V224, P327, DOI 10.1016/j.jenvman.2018.07.046
   Song H, 2018, CRIT CRIMINOL-NETH, V26, P251, DOI 10.1007/s10612-018-9384-0
   Sowers J, 2011, CLIMATIC CHANGE, V104, P599, DOI 10.1007/s10584-010-9835-4
   Stec A, 2015, RESOUR CONSERV RECY, V105, P84, DOI 10.1016/j.resconrec.2015.10.006
   Stock JH, 2007, J MONEY CREDIT BANK, V39, P3, DOI 10.1111/j.1538-4616.2007.00014.x
   Stock JH, 1999, J MONETARY ECON, V44, P293, DOI 10.1016/S0304-3932(99)00027-6
   Svensson LEO, 1997, EUR ECON REV, V41, P1111, DOI 10.1016/S0014-2921(96)00055-4
   Swinton SM, 2007, ECOL ECON, V64, P245, DOI 10.1016/j.ecolecon.2007.09.020
   Tam VWY, 2010, RESOUR CONSERV RECY, V54, P178, DOI 10.1016/j.resconrec.2009.07.014
   Taylor RG, 2013, NAT CLIM CHANGE, V3, P322, DOI [10.1038/nclimate1744, 10.1038/NCLIMATE1744]
   Taylor SD, 2016, J ENVIRON MANAGE, V180, P147, DOI 10.1016/j.jenvman.2016.05.002
   Tol RSJ, 2002, ENVIRON RESOUR ECON, V21, P47, DOI 10.1023/A:1014500930521
   Tsur Y, 1997, WORLD BANK ECON REV, V11, P243, DOI 10.1093/wber/11.2.243
   Tu MY, 2003, J WATER RES PLAN MAN, V129, P86, DOI 10.1061/(ASCE)0733-9496(2003)129:2(86)
   Tulloch AIT, 2013, BIOL CONSERV, V165, P128, DOI 10.1016/j.biocon.2013.05.025
   TURNOVSKY SJ, 1993, INT ECON REV, V34, P953, DOI 10.2307/2526974
   van Dam J, 2009, RENEW SUST ENERG REV, V13, P1679, DOI 10.1016/j.rser.2009.03.012
   van Koppen B, 2019, WATER ALTERN, V12, P146
   van Rijswick M, 2014, WATER INT, V39, P725, DOI 10.1080/02508060.2014.951828
   van Stokkom HTC, 2005, WATER INT, V30, P76, DOI 10.1080/02508060508691839
   van Vuuren DP, 2011, GLOBAL ENVIRON CHANG, V21, P575, DOI 10.1016/j.gloenvcha.2010.11.003
   Varela-Ortega C, 2011, GLOBAL ENVIRON CHANG, V21, P604, DOI 10.1016/j.gloenvcha.2010.12.001
   Vasileiou K, 2014, NAT RESOUR MODEL, V27, P128, DOI 10.1111/nrm.12022
   Verones F, 2017, SCI REP-UK, V7, DOI 10.1038/srep40743
   Wakeel M, 2016, APPL ENERG, V178, P868, DOI 10.1016/j.apenergy.2016.06.114
   Wang S, 2011, J ENVIRON MANAGE, V92, P1986, DOI 10.1016/j.jenvman.2011.03.024
   Ward FA, 2008, ECOL ECON, V66, P23, DOI 10.1016/j.ecolecon.2007.08.018
   Ward FA, 2007, WATER POLICY, V9, P1, DOI 10.2166/wp.2006.053
   Ward FA, 2021, SCI TOTAL ENVIRON, V796, DOI 10.1016/j.scitotenv.2021.148945
   Ward FA, 2019, J HYDROL, V576, P667, DOI 10.1016/j.jhydrol.2019.06.081
   Ward FA, 2012, WATER POLICY, V14, P250, DOI 10.2166/wp.2011.021
   Ward FA, 2009, J ENVIRON MANAGE, V90, P293, DOI 10.1016/j.jenvman.2007.09.009
   Watts G, 2012, J HYDROL, V414, P255, DOI 10.1016/j.jhydrol.2011.10.038
   Whitmee S, 2015, LANCET, V386, P1973, DOI 10.1016/S0140-6736(15)60901-1
   Wilby RL, 2009, INT J CLIMATOL, V29, P1193, DOI 10.1002/joc.1839
   Willardson L., 1994, 13 TH TECH 19 C USCI
   Xevi E, 2005, J ENVIRON MANAGE, V77, P269, DOI 10.1016/j.jenvman.2005.06.013
   Yadav SN, 1998, WATER RESOUR RES, V34, P497, DOI 10.1029/97WR01981
   Yates D, 2005, WATER INT, V30, P487, DOI 10.1080/02508060508691893
   Yazdanpanah M, 2014, J ENVIRON MANAGE, V135, P63, DOI 10.1016/j.jenvman.2014.01.016
   YOUNG HP, 1982, WATER RESOUR RES, V18, P463, DOI 10.1029/WR018i003p00463
   Young RA, 2014, DETERMINING EC VALUE
   Yuan F, 2008, INT J REMOTE SENS, V29, P1169, DOI 10.1080/01431160701294703
   Yuan Y, 2002, J SOIL WATER CONSERV, V57, P259
   Zadeh SM, 2013, SUSTAINABILITY-BASEL, V5, P2887, DOI 10.3390/su5072887
   ZARNIKAU J, 1994, RESOUR ENERGY ECON, V16, P189, DOI 10.1016/0928-7655(94)90005-1
   ZILBERMAN D, 1991, SCIENCE, V253, P518, DOI 10.1126/science.253.5019.518
   Zohrabian A, 2020, ENERGIES, V13, DOI 10.3390/en13215589
NR 236
TC 9
Z9 10
U1 0
U2 35
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD JAN 1
PY 2022
VL 301
AR 113884
DI 10.1016/j.jenvman.2021.113884
EA OCT 2021
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA WD2NX
UT WOS:000704785200002
PM 34607140
DA 2025-01-10
ER

PT J
AU Kong, DY
   Liu, H
   Wu, YX
   Li, BZ
   Wei, S
   Yuan, MW
AF Kong, Deyu
   Liu, Hong
   Wu, Yuxin
   Li, Baizhan
   Wei, Shen
   Yuan, Mengwei
TI Effects of indoor humidity on building occupants' thermal comfort and
   evidence in terms of climate adaptation
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Air humidity; Climate adaptation; Humidity responses; Thermal
   sensitivity; Humidity limits
ID RESIDENTIAL BUILDINGS; RELATIVE-HUMIDITY; HUMAN RESPONSES; HOT-SUMMER;
   ENVIRONMENT; COLD; PEOPLE; TEMPERATURES; PERCEPTION; IMPACT
AB Similar as temperature, air humidity may affect people's thermal comfort and humidity adaptation may happen when people changing their living conditions. To provide evidence on both effect from humidity on people's thermal comfort and their humidity adaptation, a comparative study has been conducted in a controlled climate chamber. During the experiment, the air temperature was set as 25 degrees C and 28 degrees C respectively and the relative humidity was changing between 20% and 90%. There were twenty four participants involved in this experiment, with half living in High Humidity (HH) regions of China, such as Chongqing, for over 20 years, and another half recently moved to Chongqing from Low Humidity (LH) regions in northwestern China. During the experiment, mean skin temperature was measured as an objective important parameter and subjective questionnaires were used to subjectively collect people's sensations with respect to heat, humidity and sweating. The data collected demonstrated that people living in HH regions showed a better adaptive ability to humidity changes than those came from LH regions. Climate adaptation also reduced the sensitivity of HH subjects' thermal responses. When air humidity was over 70%, subjects started to show stronger thermal responses. Based on these results, an upper limit of humidity of 17 g/kg has been proposed for Chongqing, China. The results from this study will help to broaden the adaptive thermal comfort theory and can provide important references regarding to humidity control for buildings.
C1 [Kong, Deyu; Liu, Hong; Wu, Yuxin; Li, Baizhan; Yuan, Mengwei] Chongqing Univ, Minist Educ, Joint Int Res Lab Green Bldg & Built Environm, Chongqing 400045, Peoples R China.
   [Kong, Deyu; Liu, Hong; Wu, Yuxin; Li, Baizhan; Yuan, Mengwei] Chongqing Univ, Minist Sci & Technol, Natl Ctr Int Res Low Carbon & Green Bldg, Chongqing 400045, Peoples R China.
   [Wei, Shen] UCL, Bartlett Sch Construct & Project Management, London WC1E 7HB, England.
C3 Chongqing University; Chongqing University; University of London;
   University College London
RP Liu, H (corresponding author), Chongqing Univ, Minist Educ, Joint Int Res Lab Green Bldg & Built Environm, Chongqing 400045, Peoples R China.
EM liuhong1865@163.com
RI li, bz/GVR-7133-2022; Wu, Yuxin/LQJ-8459-2024
OI Wei, Shen/0000-0001-9644-5095; Wu, Yuxin/0000-0002-7293-0325
FU Fundamental Research Funds for the Central Universities [2018CDYJSY0055,
   2018CDJDCH0015]; National Key Research and Development Program of China
   [2017YFC0702700]; 111 Project [B13041]
FX This research is supported by the Fundamental Research Funds for the
   Central Universities (Grant No. 2018CDYJSY0055, 2018CDJDCH0015), the
   National Key Research and Development Program of China (2017YFC0702700),
   and the 111 Project (Grant No. B13041).
CR [Anonymous], THESIS
   [Anonymous], 2008, THESIS
   [Anonymous], 2007, EN15251
   [Anonymous], 1960, ASHRAE T
   [Anonymous], 2003, GBT18977
   [Anonymous], 2007, ASHRAE T
   ASHRAE, 2014, 552013 ASHRAEANSI
   Bauman F., 1996, IMPACT HUMIDITY STAN
   Brager GS, 1998, ENERG BUILDINGS, V27, P83, DOI 10.1016/S0378-7788(97)00053-4
   Cao B, 2011, ENERG BUILDINGS, V43, P1051, DOI 10.1016/j.enbuild.2010.09.025
   Chen Jin-hua, 2015, Journal of Hunan University (Natural Science), V42, P128
   CIBSE A., 2006, CIBSE GUD ENV DES
   De Dear R., 1998, ASHRAE T, V104, P73
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Djamila H., 2014, Journal of Building Construction and Planning Research, 02, P109, DOI [10.3390/buildings5031025, DOI 10.4236/JBCPR.2014.22010]
   Du CQ, 2018, BUILD ENVIRON, V139, P134, DOI 10.1016/j.buildenv.2018.05.025
   Fang Z., 2017, INDOOR BUILT ENVIRON
   Fanger PO., 1967, ASHRAE T, V73, p4.0
   Fountain M. E., 1999, INVESTIGATION THERMA, V105
   Han J, 2007, BUILD ENVIRON, V42, P4043, DOI 10.1016/j.buildenv.2006.06.028
   Hayakawa K, 1989, J ARCHITECTURE PLANN, V405, P47
   Hwang RL, 2009, BUILD ENVIRON, V44, P1128, DOI 10.1016/j.buildenv.2008.08.001
   Ji XL, 2006, BUILD RES INF, V34, P507, DOI 10.1080/09613210600722511
   Jin L, 2017, BUILD ENVIRON, V114, P257, DOI 10.1016/j.buildenv.2016.12.028
   Jing SL, 2013, INDOOR BUILT ENVIRON, V22, P598, DOI 10.1177/1420326X12447614
   Juan Y., 2012, THESIS
   Koch W., 1960, J OCCUP ENVIRON MED, V2, P416, DOI [10.1097/00043764-196008000-00058, DOI 10.1097/00043764-196008000-00058]
   Lee S., 2010, INDOOR AIR, V9, P180
   Li BZ, 2018, ENERG BUILDINGS, V158, P393, DOI 10.1016/j.enbuild.2017.09.062
   Li BZ, 2018, APPL THERM ENG, V129, P693, DOI 10.1016/j.applthermaleng.2017.10.072
   Li C., 2018, INDOOR BUILT ENVIRON
   Li C, 2017, BUILD ENVIRON, V123, P458, DOI 10.1016/j.buildenv.2017.07.024
   Liu H., 2015, HEATING VENTILATING, P50
   Liu HE, 2009, THESIS
   Liu H, 2017, ENERG BUILDINGS, V140, P9, DOI 10.1016/j.enbuild.2017.01.066
   Liu YF, 2017, BUILD ENVIRON, V124, P90, DOI 10.1016/j.buildenv.2017.07.022
   Luo M, 2017, INDOOR AIR, V27, P273, DOI 10.1111/ina.12323
   Luo MH, 2016, BUILD ENVIRON, V98, P30, DOI 10.1016/j.buildenv.2015.12.015
   Maiti R, 2013, BUILD ENVIRON, V70, P306, DOI 10.1016/j.buildenv.2013.08.029
   Nakano J, 2002, ENERG BUILDINGS, V34, P615, DOI 10.1016/S0378-7788(02)00012-9
   Nevins R.G., 1966, ASHRAE T, V72, P283
   Nevins R.G., 1975, ASHRAE 75, ASHRAE Transactions, V86, P169
   Nicol F, 2010, BUILD ENVIRON, V45, P11, DOI 10.1016/j.buildenv.2008.12.013
   Nicol JF, 2011, BUILD RES INF, V39, P105, DOI 10.1080/09613218.2011.558690
   Ning HR, 2016, BUILD ENVIRON, V99, P161, DOI 10.1016/j.buildenv.2016.01.003
   RAMANATHAN NL, 1964, J APPL PHYSIOL, V19, P531, DOI 10.1152/jappl.1964.19.3.531
   Ren Y., 2017, HEAT VENT AIR COND, P109
   Rijal HB, 2010, BUILD ENVIRON, V45, P2743, DOI 10.1016/j.buildenv.2010.06.002
   Tanabe S., 1994, ASHRAE T, V100, P953
   Tian Y., 2003, Journal of HVAC, V04, P27
   Vellei M, 2017, BUILD ENVIRON, V124, P171, DOI 10.1016/j.buildenv.2017.08.005
   Wang L, 2015, HV&AC, V45, P87
   Wang ZJ, 2011, BUILD ENVIRON, V46, P2170, DOI 10.1016/j.buildenv.2011.04.029
   Wang Z, 2018, BUILD ENVIRON, V138, P181, DOI 10.1016/j.buildenv.2018.04.040
   Wong NH, 2002, BUILD ENVIRON, V37, P1267, DOI 10.1016/S0360-1323(01)00103-2
   Yan HY, 2017, ENERG BUILDINGS, V141, P28, DOI 10.1016/j.enbuild.2017.02.016
   Yang DY, 2017, BUILD ENVIRON, V114, P357, DOI 10.1016/j.buildenv.2016.12.038
   Yang Y, 2015, APPL THERM ENG, V76, P283, DOI 10.1016/j.applthermaleng.2014.11.004
   Yao RM, 2010, APPL ENERG, V87, P1015, DOI 10.1016/j.apenergy.2009.09.028
   Yao RM, 2009, BUILD ENVIRON, V44, P2089, DOI 10.1016/j.buildenv.2009.02.014
   Yoshino H, 2006, ENERG BUILDINGS, V38, P1308, DOI 10.1016/j.enbuild.2006.04.006
   Yu J, 2013, INDOOR AIR, V23, P303, DOI 10.1111/ina.12025
   Zhang HB, 2010, BUILD ENVIRON, V45, P2132, DOI 10.1016/j.buildenv.2010.03.011
   Zhang Y, 2016, INDOOR AIR, V26, P820, DOI 10.1111/ina.12256
   Zhang Y., 2011, HEAT VENT AIR COND, V45, P2562
NR 65
TC 80
Z9 84
U1 6
U2 65
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0360-1323
EI 1873-684X
J9 BUILD ENVIRON
JI Build. Environ.
PD MAY 15
PY 2019
VL 155
BP 298
EP 307
DI 10.1016/j.buildenv.2019.02.039
PG 10
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA HU0EF
UT WOS:000464943500024
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Shi, LD
   Chu, E
   Debats, J
AF Shi, Linda
   Chu, Eric
   Debats, Jessica
TI Explaining Progress in Climate Adaptation Planning Across 156 US
   Municipalities
SO JOURNAL OF THE AMERICAN PLANNING ASSOCIATION
LA English
DT Article
DE climate change; adaptation; urban planning; adaptive capacity
ID CITIES; BARRIERS; PROTECTION; MANAGEMENT; OPTIONS; SCALES; POLICY;
   PLANS; STATE
AB Problem, research strategy, and findings: Cities are increasingly experiencing the effects of climate change and taking steps to adapt to current and future natural hazard risks. Research on these efforts has identified numerous barriers to climate adaptation planning, but has not yet systematically evaluated the relative importance of different constraints for a large number of diverse cities. We draw on responses from 156 U.S. cities that participated in a 2011 global survey on local adaptation planning, 60% of which are planning for climate change. We use logistic regression analysis to assess the significance of 13 indicators measuring political leadership, fiscal and administrative resources, ability to obtain and communicate climate information, and state policies in predicting the status of adaptation planning. In keeping with the literature, we find that greater local elected officials' commitment, higher municipal expenditures per capita, and an awareness that the climate is already changing are associated with cities engaging in adaptation planning. The presence of state policies on climate adaptation is surprisingly not a statistically significant predictor, suggesting that current policies are not yet strong enough to increase local adaptation planning. However, the model's sampling bias toward larger and more environmentally progressive cities may mask the predictive power of state policies and other indicators.Takeaway for practice: State governments have an opportunity to increase local political commitment by integrating requirements for climate-risk evaluations into existing funding streams and investment plans. Regional planning entities also can help overcome the lack of local fiscal capacity and political support by facilitating the exchange of information, pooling and channeling resources, and providing technical assistance to local planners.
C1 [Shi, Linda; Debats, Jessica] MIT, Dept Urban Studies & Planning, Cambridge, MA 02139 USA.
   [Chu, Eric] Univ Amsterdam, Ctr Urban Studies, NL-1012 WX Amsterdam, Netherlands.
   [Chu, Eric] Univ Amsterdam, Dept Geog Planning & Int Dev Studies, NL-1012 WX Amsterdam, Netherlands.
C3 Massachusetts Institute of Technology (MIT); University of Amsterdam;
   University of Amsterdam
RP Shi, LD (corresponding author), MIT, Dept Urban Studies & Planning, Cambridge, MA 02139 USA.
EM lindashi@mit.edu; E.K.Chu@uva.nl; jdebats@mit.edu
RI Chu, Eric/O-6464-2015
OI Chu, Eric/0000-0002-5648-6615; Shi, Linda/0000-0002-2444-367X
FU National Science Foundation [0926349]; Directorate For Engineering; Div
   Of Civil, Mechanical, & Manufact Inn [0926349] Funding Source: National
   Science Foundation
FX We dedicate this article to JoAnn Carmin (1957-2014), associate
   professor at MIT, who conducted the survey (supported by National
   Science Foundation Grant No. 0926349) used in this article. We thank
   Alex Aylett and three anonymous reviewers for their insightful comments.
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Amundsen H, 2010, ENVIRON PLANN C, V28, P276, DOI 10.1068/c0941
   Anguelovski I, 2011, CURR OPIN ENV SUST, V3, P169, DOI 10.1016/j.cosust.2010.12.017
   Anguelovski I, 2014, GLOBAL ENVIRON CHANG, V27, P156, DOI 10.1016/j.gloenvcha.2014.05.010
   [Anonymous], ANT CLIM DEN CAUC 11
   [Anonymous], CISC VIS NETW IND GL
   Aylett A., 2014, Progress and Challenges in the Urban Governance of Climate Change Results of a Global Survey
   Barbour E, 2012, J AM PLANN ASSOC, V78, P70, DOI 10.1080/01944363.2011.645272
   Bassett E, 2010, J AM PLANN ASSOC, V76, P435, DOI 10.1080/01944363.2010.509703
   Bedsworth LW, 2013, GLOBAL ENVIRON CHANG, V23, P664, DOI 10.1016/j.gloenvcha.2013.02.004
   Bedsworth LW, 2010, J AM PLANN ASSOC, V76, P477, DOI 10.1080/01944363.2010.502047
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Betsill MM, 2009, AM COMP ENVIRON POLI, P201
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Birkmann J, 2010, NAT HAZARDS, V55, P637, DOI 10.1007/s11069-008-9319-2
   Borden KA, 2007, J HOMEL SECUR EMERG, V4, DOI 10.2202/1547-7355.1279
   Brady M., 2013, COST EFFICIENT CLIMA
   Brulle RJ, 2012, CLIMATIC CHANGE, V114, P169, DOI 10.1007/s10584-012-0403-y
   Bryan TK, 2016, J ENVIRON PLANN MAN, V59, P573, DOI 10.1080/09640568.2015.1030499
   Bulkeley H, 2010, ANNU REV ENV RESOUR, V35, P229, DOI 10.1146/annurev-environ-072809-101747
   Carmin J., 2013, OECD REGIONAL DEV WO, V2013
   Carmin JoAnn., 2012, Progress and Challenges in Urban Climate Adaptation Planning: Results of a Global Survey
   Carmin JoAnn., 2015, Climate Change and Society: Sociological Perspectives, P164
   Cruce T.L., 2009, Adaptation planning - What U.S. states and localities are doing
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Cutter SusanL., 2014, Climate Change Impacts in the United States: The Third National Climate Assessment, P282
   DALTON LC, 1994, J AM PLANN ASSOC, V60, P444, DOI 10.1080/01944369408975604
   Ebi KL, 2008, ENVIRON SCI POLICY, V11, P359, DOI 10.1016/j.envsci.2008.02.001
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fünfgeld H, 2010, CURR OPIN ENV SUST, V2, P156, DOI 10.1016/j.cosust.2010.07.001
   Füssel HM, 2007, SUSTAIN SCI, V2, P265, DOI 10.1007/s11625-007-0032-y
   Georgetown Climate Center, State and Local Climate Adaptation Plans
   Gurran N, 2013, OCEAN COAST MANAGE, V86, P100, DOI 10.1016/j.ocecoaman.2012.10.014
   Halsnæs K, 2009, ENVIRON MANAGE, V43, P765, DOI 10.1007/s00267-009-9273-0
   Hamin EM, 2014, J AM PLANN ASSOC, V80, P110, DOI 10.1080/01944363.2014.949590
   Hamin EM, 2009, HABITAT INT, V33, P238, DOI 10.1016/j.habitatint.2008.10.005
   Hanak E., 2008, Climate policy at the local level: A survey of California's cities and counties
   Haughton G, 2004, GEOGR J, V170, P135, DOI 10.1111/j.0016-7398.2004.00115.x
   Homsy GC, 2015, URBAN AFF REV, V51, P46, DOI 10.1177/1078087414530545
   Howe PD, 2015, NAT CLIM CHANGE, V5, P596, DOI 10.1038/nclimate2583
   Hunt A, 2011, CLIMATIC CHANGE, V104, P13, DOI 10.1007/s10584-010-9975-6
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Klein R. J. T., 2011, CLIMATE GOVERNANCE D, P35
   Krause RM, 2012, URBAN STUD, V49, P2399, DOI 10.1177/0042098011427183
   Krause RM, 2011, J URBAN AFF, V33, P45, DOI 10.1111/j.1467-9906.2010.00510.x
   Leck H., 2015, Current Opinion in Environmental Sustainability, V13, P61, DOI [10.1016/j.cosust.2015.02.004, DOI 10.1016/J.COSUST.2015.02.004]
   Lemieux CJ, 2011, ENVIRON MANAGE, V48, P675, DOI 10.1007/s00267-011-9700-x
   Lowe A., 2009, ASK CLIMATE QUESTION
   Lubell M, 2009, J AM PLANN ASSOC, V75, P293, DOI 10.1080/01944360902952295
   McCright AM, 2011, SOCIOL QUART, V52, P155, DOI 10.1111/j.1533-8525.2011.01198.x
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Moser S. C., 2015, SCIDEV NET      0319
   Moser S.C., 2009, IHDP update, P31
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   National Research Council, 2010, Adapting to the impacts of climate change. Adapting to the impacts of climate change, DOI DOI 10.17226/12783
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Quay R, 2010, J AM PLANN ASSOC, V76, P496, DOI 10.1080/01944363.2010.508428
   Roberts D, 2010, ENVIRON URBAN, V22, P397, DOI 10.1177/0956247810379948
   Shi L., HANDBOOK ON URBANIZA
   Solecki W, 2011, CURR OPIN ENV SUST, V3, P135, DOI 10.1016/j.cosust.2011.03.001
   Tribbia J, 2008, ENVIRON SCI POLICY, V11, P315, DOI 10.1016/j.envsci.2008.01.003
   Westerhoff L, 2011, CLIM POLICY, V11, P1071, DOI 10.1080/14693062.2011.579258
   While A, 2013, URBAN STUD, V50, P1325, DOI 10.1177/0042098013480963
NR 63
TC 117
Z9 131
U1 3
U2 74
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0194-4363
EI 1939-0130
J9 J AM PLANN ASSOC
JI J. Am. Plan. Assoc.
PD JUL 3
PY 2015
VL 81
IS 3
BP 191
EP 202
DI 10.1080/01944363.2015.1074526
PG 12
WC Regional & Urban Planning; Urban Studies
WE Social Science Citation Index (SSCI)
SC Public Administration; Urban Studies
GA CS5PE
UT WOS:000362129400003
OA Green Published
DA 2025-01-10
ER

PT J
AU Tanner, T
AF Tanner, Thomas
TI Climate Risk Screening of Development Portfolios and Programmes
SO IDS BULLETIN-INSTITUTE OF DEVELOPMENT STUDIES
LA English
DT Article
AB Development actors are becoming increasingly aware of the impact of climate-related shocks and stresses on their activities. Accordingly, tools and methods are emerging to support decision-making to integrate climate adaptation concerns within poverty reduction plans, programmes and projects. These provide information and guidance to help assess risks and prioritise corresponding actions to enhance adaptation and disaster risk reduction. This article examines the use of climate adaptation decision tools for development, placing the range of tools and information platforms within the context of different adaptation approaches. It uses the case study of the ORCHID climate risk screening methodology to highlight the challenges and opportunities of integrating adaptation and disaster risk reduction into development cooperation. The article concludes that a focus on climate science rather than social vulnerability tends to support the conception of 'adaptation as output' rather than of 'adaptation as process', which the article argues is necessary for pro-poor outcomes.
OI Tanner, Thomas/0000-0001-7975-4267
CR ADB, 2005, CLIM PROOF RISK BAS
   *ADB AS DEV BANK D, 2003, POV CLIM CHANG RED V
   Adger W.N., 2001, LIVING ENV CHANGE SO
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   [Anonymous], 2007, CLIMATE SOC
   [Anonymous], BRIDGE OVER TROUBLED
   [Anonymous], EU STRAT CLIM CHANG
   [Anonymous], 2006, EC CLIMATE CHANGE ST, DOI DOI 10.1378/CHEST.128.5
   [Anonymous], DECADAL FORECASTING
   [Anonymous], 2004, WHATS WORD CONFLICTI, DOI DOI 10.1016/j.enconman.2005.11.002
   [Anonymous], 2007, HUMAN DEV REPORT 200
   [Anonymous], COMENVEPOCDCDDAC2007
   [Anonymous], 2007, ORCHID PILOTING CLIM
   [Anonymous], 2005, CLEAN AIR ACT PLAN B
   BURTON I, 2004, LOOK YOU LEOP RISK M
   CHAMBERS R, 1989, IDS BULL-I DEV STUD, V20, P1, DOI 10.1111/j.1759-5436.1989.mp20002001.x
   DFID, 2006, EL WORLD POV MAK GOV
   DFID, 2004, POL DIV INF SER
   *G8, 2008, G8 HOKK TOY SUMM LEA
   *IISD, 2008, EARTH NEGOTIATI 0310
   KLEIN RTJ, 2007, CLIMATIC CHANGE, P23
   McGray H., 2007, Weathering the Storm: Options for Framing Adaptation and Development
   OECD, 2006, INT CLIM CHANG AD DE
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Stephen L, 2001, DISASTERS, V25, P113, DOI 10.1111/1467-7717.00165
   Tanner T., 2008, SCREENING CLIMATE CH
   Tanner T.M., 2007, ORCHID: Climate Risk Screening in DFID India
   TANNER TM, 2007, GEN WORKSH 11 12 APR
   TANNER TM, 2008, ASIAN DISASTER M JAN
   Thomalla F, 2006, DISASTERS, V30, P39, DOI 10.1111/j.1467-9523.2006.00305.x
   Venton C., 2004, DISASTER PREPAREDNES
NR 31
TC 2
Z9 3
U1 0
U2 3
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0265-5012
EI 1759-5436
J9 IDS BULL-I DEV STUD
JI IDS Bull.-Inst. Dev. Stud.
PD SEP
PY 2008
VL 39
IS 4
BP 87
EP +
PG 10
WC Area Studies; Development Studies
WE Social Science Citation Index (SSCI)
SC Area Studies; Development Studies
GA 377UX
UT WOS:000261277600012
DA 2025-01-10
ER

PT J
AU Smith, IA
   Fabian, MP
   Hutyra, LR
AF Smith, Ian A.
   Fabian, M. Patricia
   Hutyra, Lucy R.
TI Urban green space and albedo impacts on surface temperature across seven
   United States cities
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Urban greening; White roofs; Albedo; Surface temperature; Urban heat
   island; Climate change; Climate adaptation; Heat exposure
ID HEAT; TREES; EVAPOTRANSPIRATION; GRADIENTS; SATELLITE; COMMUNITY;
   STRESS; METRO; WHITE; ROOFS
AB Extreme heat represents a growing threat to public health, especially across the densely populated, developed landscape of cities. Climate adaptation strategies that aim to manage urban microclimates through purposeful design can reduce the heat exposure of urban populations, however, it is unclear how the temperature impacts of urban green space and albedo vary across cities and background climate. This study quantifies the sensitivity of surface temperature to landcover characteristics tied to two widely used climate adaptation strategies, urban greening and albedo manipulation (e.g. white roofs), by combining long-term remote sensing observations of land surface temperature, albedo, and moisture with high-resolution landcover datasets in a spatial regression analysis at the census block scale across seven United States cities. We find tree cover to have an average cooling impact of -0.089 K per % cover, which is approximately four times stronger than the average grass cover cooling impact of -0.021 K per % cover. Variability in the magnitude of grass cover cooling impacts was primarily a function of vegetation moisture content, with the Land Surface Water Index (LSWI) explaining 89 % of the variability in grass cover cooling impacts across cities. Variability in tree cover cooling impacts was primarily a function of sunlight and vegetation moisture content, with solar irradiance and LSWI explaining 97 % of the cooling variability across cities. Albedo cooling impacts were consistent across cities with an average cooling impact of -0.187 K per increase of 0.01. While these interventions are broadly effective across cities, there are critical regional trade-offs between vegetation cooling efficiency, irrigation requirements, and the temporal duration and evolution of the cooling benefits. In warm, arid cities, high albedo surfaces offer multifaceted benefits such as cooling and water conservation, whereas temperate, mesic cities likely benefit from a combination of strategies, with greening efforts targeting highly paved neighborhoods.
C1 [Smith, Ian A.; Hutyra, Lucy R.] Boston Univ, Dept Earth & Environm, 685 Commonwealth Ave, Boston, MA 02215 USA.
   [Fabian, M. Patricia] Boston Univ, Dept Environm Hlth, 715 Albany St, Boston, MA 02118 USA.
C3 Boston University; Boston University
RP Smith, IA (corresponding author), Boston Univ, Dept Earth & Environm, 685 Commonwealth Ave, Boston, MA 02215 USA.
EM iasmith@bu.edu
RI Hutyra, Lucy/KWU-0684-2024
OI Hutyra, Lucy/0009-0009-7229-0063
FU National Science Foundation [DGE-1840990, ICER-1854706, DGE-1735087];
   Boston University Initiative on Cities
FX Financial support for this research was provided by National Science
   Foundation awards DGE-1840990, ICER-1854706, and DGE-1735087. We thank
   Professor Dan Li for helpful comments on the analysis and the Boston
   University Master of Science in Statistical Practice Consulting group
   for assistance in statistical methodology. We also thank Katharine Lusk
   and the Boston University Initiative on Cities for their ideas, support,
   and dis- cussion of applications of this science.
CR Almanza E, 2012, HEALTH PLACE, V18, P46, DOI 10.1016/j.healthplace.2011.09.003
   Anderson GB, 2013, ENVIRON HEALTH PERSP, V121, P1111, DOI 10.1289/ehp.1206273
   [Anonymous], URBAN FOR URBAN GREE, V74, DOI [10.1016/j.ufug.2022.127635, DOI 10.1016/J.UFUG.2022.127635]
   [Anonymous], 2019, A
   [Anonymous], 2021, Climate change indicators: heat waves
   [Anonymous], 2023, SCI TOTAL ENVIRON, V857
   Bekkar B, 2020, JAMA NETW OPEN, V3, DOI 10.1001/jamanetworkopen.2020.8243
   Bell J.E., 2016, IMPACTS CLIMATE CHAN, P99, DOI [10.7930/JOBZ63ZV, DOI 10.7930/J0BZ63ZV]
   Bretz SE, 1997, ENERG BUILDINGS, V25, P159, DOI 10.1016/S0378-7788(96)01005-5
   CARLSON TN, 1978, J APPL METEOROL, V17, P998, DOI 10.1175/1520-0450(1978)017<0998:AOURCU>2.0.CO;2
   City of Boston, 2022, HEAT RES SOL BOST
   Crevier LP, 2001, J APPL METEOROL, V40, P2026, DOI 10.1175/1520-0450(2001)040<2026:MANMFR>2.0.CO;2
   Devitt DA, 2008, J IRRIG DRAIN ENG, V134, P74, DOI 10.1061/(ASCE)0733-9437(2008)134:1(74)
   Easterling D., 2018, REPORT IN BRIEF, V2, DOI [10.7930/NCA4.2018.RiBGraff, DOI 10.7930/NCA4.2018.RIBGRAFF]
   Erell E, 2014, URBAN CLIM, V10, P367, DOI 10.1016/j.uclim.2013.10.005
   Escobedo FJ, 2011, ENVIRON POLLUT, V159, P2078, DOI 10.1016/j.envpol.2011.01.010
   Filho WL, 2017, INT J ENV RES PUB HE, V14, DOI 10.3390/ijerph14121600
   Giordano F., 2019, CERN IdeaSquare J. Exp. Innov., V3, P12, DOI [10.23726/cij.2019.874, DOI 10.23726/CIJ.2019.874]
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Gu YX, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035772
   Hartig T, 2014, ANNU REV PUBL HEALTH, V35, P207, DOI 10.1146/annurev-publhealth-032013-182443
   He C, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/aba4c9
   He C, 2020, ENVIRON SCI TECHNOL, V54, P10831, DOI 10.1021/acs.est.0c03536
   Heal G, 2016, REV ENV ECON POLICY, V10, P347, DOI 10.1093/reep/rew007
   Hsu A, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22799-5
   Ibsen PC, 2022, SCI TOTAL ENVIRON, V829, DOI 10.1016/j.scitotenv.2022.154589
   Jacobson MZ, 2012, J CLIMATE, V25, P1028, DOI 10.1175/JCLI-D-11-00032.1
   JARVIS PG, 1986, ADV ECOL RES, V15, P1, DOI 10.1016/S0065-2504(08)60119-1
   Ji L, 2011, INT J REMOTE SENS, V32, P6901, DOI 10.1080/01431161.2010.510811
   Kendall A, 2012, INT J LIFE CYCLE ASS, V17, P444, DOI 10.1007/s11367-011-0339-x
   Kennedy P., 2018, GUIDE ECONOMETRICS
   Kestens Y, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-7
   Laraby KG, 2018, REMOTE SENS ENVIRON, V216, P472, DOI 10.1016/j.rse.2018.06.026
   LeSage J, 2009, STAT TEXTB MONOGR, P1
   Li D, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aau4299
   Li D, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/5/055002
   Liang SL, 2003, REMOTE SENS ENVIRON, V84, P25, DOI 10.1016/S0034-4257(02)00068-8
   Liang SL, 2001, REMOTE SENS ENVIRON, V76, P213, DOI 10.1016/S0034-4257(00)00205-4
   Lichstein JW, 2002, ECOL MONOGR, V72, P445, DOI 10.1890/0012-9615(2002)072[0445:SAAAMI]2.0.CO;2
   Lynn BH, 2009, J APPL METEOROL CLIM, V48, P199, DOI [10.1175/2008JAMC1774.1, 10.1175/2008.1AMC1774.1]
   Macintyre HL, 2021, ENVIRON INT, V154, DOI 10.1016/j.envint.2021.106606
   Macintyre HL, 2021, ENVIRON INT, V154, DOI 10.1016/j.envint.2021.106530
   Maki M, 2004, REMOTE SENS ENVIRON, V90, P441, DOI 10.1016/j.rse.2004.02.002
   Markevych I, 2017, ENVIRON RES, V158, P301, DOI 10.1016/j.envres.2017.06.028
   Masek JG, 2006, IEEE GEOSCI REMOTE S, V3, P68, DOI 10.1109/LGRS.2005.857030
   Myint Soe, 2015, Ecosystem Health and Sustainability, V1, P15, DOI 10.1890/EHS14-0028.1
   National Centers for Environmental Information, 2022, NAT CTR ENV INF US C
   National Solar Radiation Database, 2022, Data-viewer
   NYC CoolRoofs, NYC COOLROOFS NYC BU
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   OKE TR, 1988, PROG PHYS GEOG, V12, P471, DOI 10.1177/030913338801200401
   Oke TR, 1987, BOUNDARY LAYER CLIMA, DOI [10.4324/9780203407219, DOI 10.4324/9780203407219]
   Oleson KW, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2009GL042194
   Park J., 2015, POLICY REWORKING P, DOI [10.1596/1813-9450-7479, DOI 10.1596/1813-9450-7479]
   Park RJ, 2020, AM ECON J-ECON POLIC, V12, P306, DOI 10.1257/pol.20180612
   Pataki DE, 2011, ECOL APPL, V21, P661, DOI 10.1890/09-1717.1
   Petri AaronC., 2016, J ENVIRON HORTIC, V34, P101
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Rahman MA, 2020, BUILD ENVIRON, V170, DOI 10.1016/j.buildenv.2019.106606
   Rahman MA, 2019, URBAN ECOSYST, V22, P683, DOI 10.1007/s11252-019-00853-x
   Rahman MA, 2018, SCI TOTAL ENVIRON, V633, P100, DOI 10.1016/j.scitotenv.2018.03.168
   Rahman MA, 2017, AGR FOREST METEOROL, V232, P443, DOI 10.1016/j.agrformet.2016.10.006
   Sarofim M.C., 2016, The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment, P43, DOI [DOI 10.7930/J0MG7MDX, 10.7930/J0MG7MDX]
   Shi L., 2018, J AM PLANN ASSOC, P340, DOI [10.4324/9781351201117-38, DOI 10.4324/9781351201117-38]
   Smargiassi A, 2009, J EPIDEMIOL COMMUN H, V63, P659, DOI 10.1136/jech.2008.078147
   Smith IA, 2021, FRONT ECOL EVOL, V9, DOI 10.3389/fevo.2021.695995
   Sproul J, 2014, ENERG BUILDINGS, V71, P20, DOI 10.1016/j.enbuild.2013.11.058
   Taha H, 1997, ENERG BUILDINGS, V25, P99, DOI 10.1016/S0378-7788(96)00999-1
   Taleghani M, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/2/024003
   THORNES JE, 1991, METEOROL MAG, V120, P117
   Tiangco M, 2008, INT J REMOTE SENS, V29, P2799, DOI 10.1080/01431160701408360
   Tiefelsdorf M, 1999, ENVIRON PLANN A, V31, P165, DOI 10.1068/a310165
   Tieskens KF, 2022, SCI TOTAL ENVIRON, V845, DOI 10.1016/j.scitotenv.2022.157283
   University of Vermont Spatial Analysis Laboratory, 2017, A
   University of Vermont Spatial Analysis Laboratory, 2016, A
   University of Vermont Spatial Analysis Laboratory, 2012, A
   University of Vermont Spatial Analysis Laboratory, 2020, A
   University of Vermont Spatial Analysis Laboratory, 2013, A
   Van Renterghem T, 2015, APPL ACOUST, V92, P86, DOI 10.1016/j.apacoust.2015.01.004
   Venter ZS, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abb9569
   Vogt Jess, 2015, Arboriculture & Urban Forestry, V41, P293
   Wang C., 2023, SCI TOTAL ENVIRON, V857
   Wang CH, 2019, REMOTE SENS ENVIRON, V227, P28, DOI 10.1016/j.rse.2019.03.024
   Wang JA, 2017, J APPL METEOROL CLIM, V56, P817, DOI 10.1175/JAMC-D-16-0325.1
   Wang J, 2020, ISPRS J PHOTOGRAMM, V159, P78, DOI 10.1016/j.isprsjprs.2019.11.001
   Weinstein N, 2015, BIOSCIENCE, V65, P1141, DOI 10.1093/biosci/biv151
   Weng QH, 2006, PHOTOGRAMM ENG REM S, V72, P1275, DOI 10.14358/PERS.72.11.1275
   Winbourne JB, 2020, BIOSCIENCE, V70, P576, DOI 10.1093/biosci/biaa055
   World Health Organization, 2018, A
   Wynne T, 2020, HORTSCIENCE, V55, P1558, DOI 10.21273/HORTSCI15027-20
   Yu QY, 2020, INT J APPL EARTH OBS, V92, DOI 10.1016/j.jag.2020.102161
   Zhai P., 2021, CLIMATE CHANGE 2021
   Zhang YJ, 2019, LANDSCAPE ECOL, V34, P681, DOI 10.1007/s10980-019-00794-y
   Zhou DC, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002401
   Zhou DC, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11010048
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
   Zhu Z, 2012, REMOTE SENS ENVIRON, V118, P83, DOI 10.1016/j.rse.2011.10.028
   Zipper SC, 2017, GEOPHYS RES LETT, V44, P873, DOI 10.1002/2016GL072190
   Ziter CD, 2019, P NATL ACAD SCI USA, V116, P7575, DOI 10.1073/pnas.1817561116
   Zivin JG, 2014, J LABOR ECON, V32, P1, DOI 10.1086/671766
NR 103
TC 32
Z9 33
U1 14
U2 91
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD JAN 20
PY 2023
VL 857
AR 159663
DI 10.1016/j.scitotenv.2022.159663
EA OCT 2022
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 8U2XU
UT WOS:000929818100004
PM 36302415
OA Bronze
DA 2025-01-10
ER

PT J
AU Chevallier, R
AF Chevallier, Romy
TI Strengthening Africa's climate-smart agriculture and food systems
   through enhanced policy coherence and coordinated action
SO SOUTH AFRICAN JOURNAL OF INTERNATIONAL AFFAIRS-SAJIA
LA English
DT Article
DE Climate-smart agriculture; Africa; climate resilience; food security;
   CAADP; Malabo Declaration
AB Africa's climate, food and agricultural policy agendas are often fragmented and yet their integration is a key requirement for enhancing the continent's resilience and development outcomes. This research article explores actions to strengthen and better align Africa's climate adaptation and mitigation responses in the agricultural sector. These include recommendations to promote the coherence of Africa's climate-smart agriculture policy frameworks at numerous levels; to strengthen broad-based stakeholder engagement and inclusion; to promote institutional coordination, monitoring, evaluation and learning; and importantly, to enhance policy implementation.
C1 [Chevallier, Romy] Consultat Grp Int Agr Res, Cape Town, South Africa.
   [Chevallier, Romy] South African Inst Int Affairs, Johannesburg, South Africa.
RP Chevallier, R (corresponding author), Consultat Grp Int Agr Res, Cape Town, South Africa.; Chevallier, R (corresponding author), South African Inst Int Affairs, Johannesburg, South Africa.
EM Romy.Chevallier@saiia.org.za
FU Accelerating the Impact of CGIAR Climate Research for Africa
FX No Statement Available
CR AfDB, 2021, FEED AFR STRAT AGR T
   African Capacity Building Foundation (ACBF), 2023, COORD CHALL OPP CLIM
   African Union, 2018, IN BIENN REV REP AFR
   African Union, 2014, CAADP RES FRAM 2015
   African Union, 2022, 3 CAADP BIENN REV RE
   African Union, 3 CAADP BIENN REV RE
   African Union, 2014, Implementation Strategy and Roadmap to Achieve the 2025 Vision on CAADP
   African Union, 2020, 2 BIENN REV REP AFR
   African Union Commission, 2022, AFR UN CLIM CHANG RE
   African Union Commission, 2014, 31 AFR UN SUMM
   African Union Commission, 2020, CAADP BIENN REV REP
   African Union Commission, 2020, AFR UN GREEN REC ACT
   African Union Commission, 2022, AFR CLIM CHANG RES D
   African Union Commission, MAL DECL ACC AGR GRO
   [Anonymous], 2019, AFR GROUP NEG EXP SU
   [Anonymous], FURTH INF
   [Anonymous], FURTHER INFORM PLEAS
   [Anonymous], MORE INFORM PLEASE V
   [Anonymous], 2023, FOREIGN POLICY ANAL
   AUDA-NEPAD, 2022, US
   Beattie S, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13052785
   Benton T G., 2021, Food system impacts on biodiversity loss: three levers of food system transformation in support of nature [Internet]
   Boko M, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P433
   Chevallier, 2021, POLICY INSIGHT, V103
   Chevallier, 2022, STRENGTHENING AFRICA
   Chiriac Daniela, 2020, EX CLIM FIN GAP SMAL
   Chiriac Daniela, 2020, CLIMATE POLICY INITI
   CIAT & World Bank, 2017, CSA Country Profiles for Africa Series
   Cobourn, 2023, OECD FOOD AGR FISHER, V202, DOI [10.1787/5fa2c770-en, DOI 10.1787/5FA2C770-EN]
   CSA Guide, WHAT IS CLIM SMART A
   Curran Patrick., 2018, Policy Coherence for Sustainable Development in Sub-Saharan Africa
   Dessalegn, 2023, FOOD SECURITY AFRICA
   ECOWAS Commission, ECOWAP WEB BAS MON E
   ECOWAS Department of Agriculture Environment and Water Resources (DAEWR), 2017, 2025 STRAT POL FRAM
   Effective Multi-Level Public Investment OECD Principles in Action, 2019, OECD MULT GOV STUD
   FAO, REG CSA ALL PLATF IN
   FAO, GLOB ALL CSA
   Food and Agriculture Organisation, 2009, FOOD SECURITY AGR MI
   Food and Agriculture Organization of the United Nations, CLIM SMART AGR
   Frankel Anita, MORE INFORM
   FSIN and Global Network against Food Crises, 2022, GRFC 2022 MIDYEAR UP
   GCIAR, WHAT IS CLIM SMART A
   Global Alliance for Resilience-AGIR Sahel and West Africa, 2013, REG ROADM DRAFT OR V
   Grist Natasha, 2015, EVIDENCE DEMAND
   Hawkes Corinna, 2017, GREAT INSIGHTS MAGAZ
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2021The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel On Climate Change, DOI [10.1017/9781009325844.001, DOI 10.1017/9781009157940, 10.1017/9781009157896]
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Kaiser C., 2019, Investing in Nature: Private Finance for Nature-Based Resilience
   Kil, 2018, PEW CHARITABLE TRUST
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Lipper Leslie, 2017, NATURAL RESOURCE MAN, V52, P13
   Lynam John, 2016, AGR RES AFRICA INVES, DOI [10.2499/9780896292123, DOI 10.2499/9780896292123]
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Okou Cedric, 2022, IMF BLOG        0927
   Picourt Loreley, 2021, SWIMMING TALK STRENG
   Qi J., 2021, INT I SUSTAINABLE DE
   Republic of Rwanda, UPD NAT DET CONTR
   Schulte, 2020, PAPER
   South African Government, 2011, NATL CLIMATE CHANGE
   South African Government Department of Agriculture forestry and Fisheries, 2018, DRAFT CLIM SMART AGR
   Sunga, 2021, STRENGTHENING NDCS S
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   The Coalition of Finance Ministers for Climate Action,Ministries of Finance and NDCs, 2020, REP HELS PRINC 6
   The World Bank, 2021, Climate-smart Agriculture
   Tores Carmen, 2017, GREAT INSIGHTS MAGAZ, V6
   United Nations Climate Change, LONG TERM STRAT PORT
   World Bank, 2020, CUTT FOOD LOSS WAST
   Yohannes-Kassahun B., 2023, AFRICA RENEWAL
NR 68
TC 2
Z9 2
U1 2
U2 3
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1022-0461
EI 1938-0275
J9 S AFR J INT AFF
JI S. Afr. J. Int. Aff.
PD OCT 2
PY 2023
VL 30
IS 4
BP 595
EP 618
DI 10.1080/10220461.2024.2318712
EA OCT 2023
PG 24
WC International Relations
WE Emerging Sources Citation Index (ESCI)
SC International Relations
GA MI3O4
UT WOS:001187238800001
OA hybrid
DA 2025-01-10
ER

PT J
AU Embke, HS
   Lynch, AJ
   Beard, TD Jr
AF Embke, Holly S.
   Lynch, Abigail J.
   Beard Jr, T. Douglas
TI Supporting climate adaptation for rural Mekong River Basin communities
   in Thailand
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Resilience; Livelihoods; Participatory action; Synthesis;
   Resist-accept-direct framework
ID ECOSYSTEM SERVICES; IMPACTS; STRATEGIES; MANAGEMENT; FISHERIES; SCIENCE;
   RISKS; DAMS
AB Climate change impacts on large river basins, such as the Mekong River Basin (MRB), are complex due to shared governance and interconnected socioeconomic areas, making them highly vulnerable to change. The MRB, spanning six countries including Thailand, is crucial for the food and economic security of > 60 million people. However, in 2021, Thailand was ranked as the 9th highest risk country affected by climate change. To integrate climate adaptation in Thailand's MRB, we examined the effects of climate change on rapidly developing farmer and fisher communities in northeastern Thailand and explored feasible adaptation options. Using an interdisciplinary approach that included literature review, participatory action methods, and the resist-accept-direct (RAD) framework, we found that climate change is projected to increase temperatures, precipitation, extreme events, erosion, and water clarity, while decreasing heavy sediment transport. These changes negatively impact agriculture, fisheries, human health, and tourism. We identified several adaptation strategies across environmental, ecological, and human health categories to accommodate local needs, such as preventing habitat degradation (e.g., from dams and deforestation), providing fish refuge and passage, and supporting technical capacity. Community-driven adaptation planning and implementation are essential for supporting global sustainable development in a changing climate.
C1 [Embke, Holly S.] US Geol Survey, Midwest Climate Adaptat Sci Ctr, 1954 Buford Ave,St Paul, Buford, MN 55108 USA.
   [Lynch, Abigail J.; Beard Jr, T. Douglas] US Geol Survey, Natl Climate Adaptat Sci Ctr, 12201 Sunrise Valley,Dr MS 516, Reston, VA 20192 USA.
C3 United States Department of the Interior; United States Geological
   Survey; United States Department of the Interior; United States
   Geological Survey
RP Embke, HS (corresponding author), US Geol Survey, Midwest Climate Adaptat Sci Ctr, 1954 Buford Ave,St Paul, Buford, MN 55108 USA.
EM hembke@usgs.gov; ajlynch@usgs.gov; dbeard@usgs.gov
RI Lynch, Abigail/H-5059-2019
OI Lynch, Abigail J./0000-0001-8449-8392; Embke, Holly/0000-0002-9897-7068
FU United States Embassy Science Fellows program; U.S. Regional
   Environment, Science, Technology, and Health Office for East and
   Southeast Asia Small Grants program; U.S. Geological Survey (USGS)
   Climate Adaptation Science Centers
FX Funding for this activity was supported by the United States Embassy
   Science Fellows program, the U.S. Regional Environment, Science,
   Technology, and Health Office for East and Southeast Asia Small Grants
   program, and the U.S. Geological Survey (USGS) Climate Adaptation
   Science Centers. We thank the U.S. Embassy Bangkok, and specifically
   Evan Fox and Vararat Khemangkorn. Further, we express the sincerest
   gratitude to the many Thai governmental officials, agencies, and
   community members who welcomed us and shared their perspectives, (sic).
   We thank Hai (Heidi) Nguyen (North Carolina State University) for
   conducting an internal review for USGS. Kate Malpeli and Louise
   Johansson provided communications and outreach support. Any use of
   trade, firm, or product names is for descriptive purposes only and does
   not imply endorsement by the U.S. Government.
CR Abidoye BO, 2017, CLIM CHANG ECON, V8, DOI 10.1142/S2010007817400061
   Abisha R, 2022, J WATER CLIM CHANGE, V13, P2671, DOI 10.2166/wcc.2022.045
   Amabel D, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187438
   Amano T, 2021, PLOS BIOL, V19, DOI 10.1371/journal.pbio.3001296
   Arantes CC, 2019, CURR OPIN ENV SUST, V37, P28, DOI 10.1016/j.cosust.2019.04.009
   Arias ME, 2019, CURR OPIN ENV SUST, V37, P1, DOI 10.1016/j.cosust.2019.01.002
   Arunrat N, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12051241
   Baird IG, 2021, ENVIRON MANAGE, V67, P682, DOI 10.1007/s00267-020-01418-x
   Baird IanG., 2010, J LAO STUDIES, V1, P1
   Baird IG, 2006, FISHERIES MANAG ECOL, V13, P1, DOI 10.1111/j.1365-2400.2006.00460.x
   Baird IG, 2007, Putting fishers' knowledge to work, P87
   Baran E., 2007, Trop River Fish Valuation: Background Pap Glob Synth, P227
   Bastakoti RC, 2014, REG ENVIRON CHANGE, V14, P207, DOI 10.1007/s10113-013-0485-8
   Baumgartner Lee J., 2021, Aquaculture and Fisheries, V6, P113, DOI 10.1016/j.aaf.2018.12.008
   Beringer AL, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10051452
   Blackman RC, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-89942-6
   Boonwichai S, 2018, J CLEAN PROD, V198, P1157, DOI 10.1016/j.jclepro.2018.07.146
   Burbano M, 2020, J HYDROL, V581, DOI 10.1016/j.jhydrol.2019.124454
   Campbell T, 2022, WATER-SUI, V14, DOI 10.3390/w14192995
   Chaiyes A, 2022, ECOHEALTH, V19, P175, DOI 10.1007/s10393-022-01588-6
   Chaowiwat W., 2016, Naresuan University Engineering Journal, V11, P35, DOI DOI 10.14456/NUEJ.2016.6
   Chaudhury M, 2016, Lessons from Implementing Community Adaptation Plans in the Lower Mekong Basin
   Chen QW, 2020, NATL SCI REV, V7, P1449, DOI 10.1093/nsr/nwaa026
   Chiarelli DD, 2020, LAND DEGRAD DEV, V31, P2060, DOI 10.1002/ldr.3591
   Chuenchum P, 2020, WATER-SUI, V12, DOI 10.3390/w12010135
   Cobb AN, 2012, ENVIRON MODELL SOFTW, V38, P296, DOI 10.1016/j.envsoft.2012.06.012
   Cornish F, 2023, NAT REV METHOD PRIME, V3, DOI 10.1038/s43586-023-00214-1
   Eastham J, 2008, Eff Clim Change, V154
   Eckstein D., 2021, Global Climate Risk Index 2021: Who Suffers Most from Extreme Weather Events? Weather-Related Loss Events in 2019 and 20002019
   Evers J, 2018, CLIMATIC CHANGE, V149, P1, DOI 10.1007/s10584-018-2242-y
   Gaja-Svasti S, 2022, SOUTH EAST ASIA RES, V30, P287, DOI 10.1080/0967828X.2022.2118621
   Gregory R, 2012, UTOPIAN SPACES OF MODERNISM: BRITISH LITERATURE AND CULTURE, 1885-1945, P1
   Gustafson S, 2018, CLIMATIC CHANGE, V149, P91, DOI 10.1007/s10584-016-1887-7
   Harzing AW, 2007, Publish or Perish Internet
   Hecht JS, 2019, J HYDROL, V568, P285, DOI 10.1016/j.jhydrol.2018.10.045
   Heis A., 2020, ADV SE ASIAN STUDIES, V13, P211, DOI DOI 10.14764/10.ASEAS-0040
   Hoang LP, 2016, HYDROL EARTH SYST SC, V20, P3027, DOI 10.5194/hess-20-3027-2016
   Intralawan A, 2018, ECOSYST SERV, V30, P27, DOI 10.1016/j.ecoser.2018.01.007
   Islam SN, 2017, United Nations DESA Working Paper No. 152
   Kiguchi M, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abce80
   Kindon SL, 2007, ROUTL STUD HUM GEOGR, V22, P1
   Kondolf GM, 2018, SCI TOTAL ENVIRON, V625, P114, DOI 10.1016/j.scitotenv.2017.11.361
   Koning AA, 2020, NATURE, V588, P631, DOI 10.1038/s41586-020-2944-y
   Laurance WF, 2007, NATURE, V449, P409, DOI 10.1038/449409a
   Lebel L, 2018, WATER INT, V43, P257, DOI 10.1080/02508060.2017.1416446
   Limsakul A, 2008, ATMOS RES, V87, P89, DOI 10.1016/j.atmosres.2007.07.007
   Lowe BS, 2019, FISH FISH, V20, P1024, DOI 10.1111/faf.12388
   Lynch AJ, 2022, FISHERIES MANAG ECOL, V29, P329, DOI 10.1111/fme.12545
   Lynch AJ, 2022, BIOSCIENCE, V72, P45, DOI 10.1093/biosci/biab091
   Lynch AJ, 2020, NAT SUSTAIN, V3, P579, DOI 10.1038/s41893-020-0517-6
   Malawal P, 2020, GMSARN Int J, V14, P125
   Mekong River Commission, 2018, Mekong Climate Change Adaptation Strategy and Action Plan
   Mekong River Commission, 2019, The MRC Hydropower Mitigation Guidelines, V1
   Molle F., 2012, Contested waterscapes mekong reg. hydropower
   Morton L. W., 2018, Journal of Environmental Protection, V9, P431, DOI 10.4236/jep.2018.94027
   Naylor RL, 2021, NATURE, V591, P551, DOI 10.1038/s41586-021-03308-6
   Nguyen TPL, 2021, CURR RES ENVIRON SUS, V3, DOI 10.1016/j.crsust.2021.100087
   Nichols G, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9100385
   Phungpracha E., 2016, Kasetsart Journal of Social Sciences, V37, P82
   Prabnakorn S, 2021, WATER POLICY, V23, P1153, DOI 10.2166/wp.2021.011
   Rahmani Ardhi Arsala, 2022, F1000Res, V11, P1555, DOI 10.12688/f1000research.125294.2
   Sabo JL, 2017, SCIENCE, V358, DOI 10.1126/science.aao1053
   Saijuntha W., 2021, Biodiversity of Southeast Asian Parasites and Vectors Causing Human Disease, P1
   Schuurman GW, 2022, BIOSCIENCE, V72, P16, DOI 10.1093/biosci/biab067
   Seddon N, 2022, SCIENCE, V376, P1410, DOI 10.1126/science.abn9668
   Shrestha M, 2020, INT J RIVER BASIN MA, V18, P23, DOI 10.1080/15715124.2019.1566239
   Shrestha RP, 2017, CLIMATE, V5, DOI 10.3390/cli5030057
   Soukhaphon A, 2021, WATER-SUI, V13, DOI 10.3390/w13030265
   Spruce J, 2020, FRONT ENV SCI-SWITZ, V8, DOI 10.3389/fenvs.2020.00021
   Srisawat A, 2020, J Environ Manage Tourism, V8, P2083, DOI [10.14505/jemt.v11.8(48).19, DOI 10.14505/JEMT.V11.8(48).19]
   Supakosol J, 2020, J WATER CLIM CHANGE, V11, P992, DOI 10.2166/wcc.2019.040
   Suwannatrai A, 2017, PARASITOL RES, V116, P243, DOI 10.1007/s00436-016-5285-x
   Tamura T, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-64630-z
   Tang XJ, 2021, REMOTE SENS ENVIRON, V256, DOI 10.1016/j.rse.2021.112336
   Thawillarp S., 2016, OSIR J, V8, P15, DOI [10.59096/osir.v8i3.263275, DOI 10.59096/OSIR.V8I3.263275]
   Thompson LM, 2021, FISHERIES, V46, P8, DOI 10.1002/fsh.10506
   Trisurat Y, 2018, ECOL RES, V33, P73, DOI 10.1007/s11284-017-1510-z
   Villamayor-Tomas S, 2016, ECOL SOC, V21, DOI 10.5751/ES-08105-210103
   Weiskopf Sarah R., 2021, Ecology and Society, V26, DOI 10.5751/ES-12816-260436
   World Wildlife Fund, 2021, NDCSA FORC NAT
NR 80
TC 1
Z9 1
U1 2
U2 2
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1381-2386
EI 1573-1596
J9 MITIG ADAPT STRAT GL
JI Mitig. Adapt. Strateg. Glob. Chang.
PD OCT
PY 2024
VL 29
IS 7
AR 67
DI 10.1007/s11027-024-10154-0
PG 29
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA E1M1P
UT WOS:001300709000001
DA 2025-01-10
ER

PT J
AU Muelchi, R
   Rössler, O
   Schwanbeck, J
   Weingartner, R
   Martius, O
AF Muelchi, Regula
   Roessler, Ole
   Schwanbeck, Jan
   Weingartner, Rolf
   Martius, Olivia
TI River runoff in Switzerland in a changing climate - runoff regime
   changes and their time of emergence
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID CHANGE IMPACTS; EURO-CORDEX; ANTHROPOGENIC CHANGES; DISCHARGE;
   PROJECTIONS; ADAPTATION; HYDROLOGY; CYCLE; SNOW; RAIN
AB Assessments of climate change impacts on runoff regimes are essential to climate change adaptation and mitigation planning. Changing runoff regimes and thus changing seasonal patterns of water availability strongly influence various economic sectors such as agriculture, energy production, and fishery and also affect river ecology. In this study, we use new transient hydrological scenarios driven by the most up-to-date local climate projections for Switzerland, the Swiss Climate Change Scenarios. These provide detailed information on changes in runoff regimes and their time of emergence for 93 rivers in Switzerland under three Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5. These transient scenarios also allow changes to be framed as a function of global mean temperature.
   The new projections for seasonal runoff changes largely confirm the sign of changes in runoff from previous hydrological scenarios with increasing winter runoff and decreasing summer and autumn runoff. Spring runoff is projected to increase in high-elevation catchments and to decrease in lower-lying catchments. Despite the increases in winter and some increases in spring, the annual mean runoff is projected to decrease in most catchments. Compared to lowerlying catchments, runoff changes in high-elevation catchments (above 1500ma.s.l.) are larger in winter, spring, and summer due to the large influence of reduced snow accumulation and earlier snowmelt and glacier melt. The changes in runoff and the agreement between climate models on the sign of change both increase with increasing global mean temperatures and higher-emission scenarios. This amplification highlights the importance of climate change mitigation.
   The time of emergence is the time when the climate signal emerges significantly from natural variability. Under RCP8.5, times of emergence were found early, before the period 2036-2065, in winter and summer for catchments with mean altitudes above 1500ma.s.l. Significant changes in catchments below 1500ma.s.l. emerge later in the century. Not all catchments show significant changes in the distribution of seasonal means; thus, no time of emergence could be determined in these catchments. Furthermore, the significant changes of seasonal mean runoff are not persistent over time in some catchments due to nonlinear changes in runoff.
C1 [Muelchi, Regula; Roessler, Ole; Schwanbeck, Jan; Weingartner, Rolf; Martius, Olivia] Univ Bern, Inst Geog, Bern, Switzerland.
   [Muelchi, Regula; Roessler, Ole; Schwanbeck, Jan; Weingartner, Rolf; Martius, Olivia] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
   [Weingartner, Rolf; Martius, Olivia] Univ Bern, Mobiliar Lab Nat Risks, Bern, Switzerland.
   [Roessler, Ole] German Fed Inst Hydrol BfG, Koblenz, Germany.
C3 University of Bern; University of Bern; University of Bern
RP Muelchi, R (corresponding author), Univ Bern, Inst Geog, Bern, Switzerland.; Muelchi, R (corresponding author), Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
EM regula.muelchi@giub.unibe.ch
RI ; Rossler, Ole/C-7488-2009
OI Martius, Olivia/0000-0002-8645-4702; Muelchi,
   Regula/0000-0002-7291-9775; Rossler, Ole/0000-0003-2308-0907
FU Bundesamt fur Umwelt
FX This research has been supported by the Bundesamt fur Umwelt.
CR Addor N, 2014, WATER RESOUR RES, V50, P7541, DOI 10.1002/2014WR015549
   [Anonymous], 2014, 401 KLIWAS
   [Anonymous], 2012, Adv. Geosci., DOI DOI 10.5194/ADGEO-32-63-2012
   [Anonymous], 2018, CH2018: CH2018-Climate Scenarios for Switzerland, Tech. rep.
   [Anonymous], CLIMATE CHANGE 2013
   Barros V, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, pIX
   Bloeschl G., 2011, Oesterreichische Wasser- und Abfallwirtschaft, V63, P1, DOI 10.1007/s00506-010-0274-2
   Bosshard T, 2011, HYDROL EARTH SYST SC, V15, P2777, DOI 10.5194/hess-15-2777-2011
   Brunner MI, 2019, HYDROL EARTH SYST SC, V23, P4471, DOI 10.5194/hess-23-4471-2019
   Brunner MI, 2019, SCI TOTAL ENVIRON, V666, P1033, DOI 10.1016/j.scitotenv.2019.02.169
   Etter S, 2017, J HYDROL-REG STUD, V13, P222, DOI 10.1016/j.ejrh.2017.08.005
   Farinotti D, 2012, HYDROL PROCESS, V26, P1909, DOI 10.1002/hyp.8276
   Fatichi S, 2015, J HYDROL, V525, P362, DOI 10.1016/j.jhydrol.2015.03.036
   Finger D, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010733
   Gaetani M, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-63782-2
   Giorgi F, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL037593
   Goler RA, 2016, METEOROL Z, V25, P621, DOI 10.1127/metz/2016/0562
   Groppelli B, 2011, NAT HAZARD EARTH SYS, V11, P1769, DOI 10.5194/nhess-11-1769-2011
   Gudmundsson L, 2012, HYDROL EARTH SYST SC, V16, P3383, DOI 10.5194/hess-16-3383-2012
   Gutiérrez JM, 2019, INT J CLIMATOL, V39, P3750, DOI 10.1002/joc.5462
   Hanzer F, 2018, HYDROL EARTH SYST SC, V22, P1593, DOI 10.5194/hess-22-1593-2018
   Hattermann FF, 2015, METEOROL Z, V24, P201, DOI 10.1127/metz/2014/0575
   Horton P, 2006, HYDROL PROCESS, V20, P2091, DOI 10.1002/hyp.6197
   Huss M, 2008, HYDROL PROCESS, V22, P3888, DOI 10.1002/hyp.7055
   Huss M, 2014, J HYDROL, V510, P35, DOI 10.1016/j.jhydrol.2013.12.017
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   James R, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.457
   Jenicek M, 2018, WATER RESOUR RES, V54, P538, DOI 10.1002/2017WR021648
   Keller L, 2018, HYDROL PROCESS, V32, P228, DOI 10.1002/hyp.11407
   Köplin N, 2014, CLIMATIC CHANGE, V122, P171, DOI 10.1007/s10584-013-1015-x
   Köplin N, 2012, HYDROL EARTH SYST SC, V16, P2267, DOI 10.5194/hess-16-2267-2012
   Kotlarski S, 2014, GEOSCI MODEL DEV, V7, P1297, DOI 10.5194/gmd-7-1297-2014
   Leng GY, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/11/114003
   Mahlstein I, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/3/034009
   Mastrandrea M.D., 2010, Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties
   Milano M, 2015, SCI TOTAL ENVIRON, V536, P12, DOI 10.1016/j.scitotenv.2015.07.049
   Morice CP, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD017187
   Muelchi R., 2020, ZENODO, DOI 10.5281/zenodo.3937485
   Muelchi R., 2021, THESIS U BERN BERN S
   Muelchi R, 2022, GEOSCI DATA J, V9, P46, DOI 10.1002/gdj3.117
   Prasch M., 2011, ADV SCI RES, V7, P61, DOI [10.5194/asr-7-61-2011, DOI 10.5194/asr-7-61-2011]
   Rössler O, 2019, CLIM SERV, V13, P1, DOI 10.1016/j.cliser.2019.01.001
   Ruiz-Villanueva V, 2015, REG ENVIRON CHANGE, V15, P505, DOI 10.1007/s10113-014-0707-8
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Teutschbein C, 2012, J HYDROL, V456, P12, DOI 10.1016/j.jhydrol.2012.05.052
   Vidal JP, 2016, HYDROL EARTH SYST SC, V20, P3651, DOI 10.5194/hess-20-3651-2016
   Viviroli D, 2009, ENVIRON MODELL SOFTW, V24, P1209, DOI 10.1016/j.envsoft.2009.04.001
   Weber M, 2010, GEOGR FIS DIN QUAT, V33, P221
   Wijngaard RR, 2016, HYDROL RES, V47, P979, DOI 10.2166/nh.2015.093
   Wilby RL, 2010, WEATHER, V65, P180, DOI 10.1002/wea.543
   Zekollari H, 2019, CRYOSPHERE, V13, P1125, DOI 10.5194/tc-13-1125-2019
NR 51
TC 33
Z9 33
U1 7
U2 48
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1027-5606
EI 1607-7938
J9 HYDROL EARTH SYST SC
JI Hydrol. Earth Syst. Sci.
PD JUN 8
PY 2021
VL 25
IS 6
BP 3071
EP 3086
DI 10.5194/hess-25-3071-2021
PG 16
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA SR9MD
UT WOS:000661367100002
OA Green Submitted, Green Published, gold
DA 2025-01-10
ER

PT J
AU Deng, J
   Che, T
   Jiang, T
   Dai, LY
AF Deng Jie
   Che Tao
   Jiang Tong
   Dai Li-Yun
TI Suitability projection for Chinese ski areas under future natural and
   socioeconomic scenarios
SO ADVANCES IN CLIMATE CHANGE RESEARCH
LA English
DT Article
DE Suitability; Ski tourism; Climate change; Socioeconomic development;
   China
ID WINTER TOURISM DESTINATIONS; AGENT-BASED MODEL; CLIMATE-CHANGE; SNOW
   RELIABILITY; BEHAVIORAL ADAPTATION; IMPACT; VARIABILITY; POPULATION;
   SNOWMAKING; DEMAND
AB Ski tourism is extremely sensitive to climate change and is also heavily affected by socioeconomic conditions. Although some ski areas are still profitable under current climate and socioeconomic conditions, they will become difficult to operate in the face of rising winter temperatures, which will result in further economic losses, resource waste and environmental damage. This study projects variability in the suitability of ski area development across China in the coming decades. Natural suitability under three representative concentration pathway emission scenarios (RCP2.6, RCP4.5 and RCP8.5), socioeconomic suitability under four shared socioeconomic pathways (SSP1, SSP2, SSP3, and SSP5) and integrated suitability under four climatic-socioeconomic scenarios (RCP2.6-SSP1, RCP4.5-SSP2, RCP8.5-SSP3, and RCP8.5-SSP5) are reported. Furthermore, the suitability of 731 existing ski areas in China is assessed. The results show a substantial decline in integrated suitability for most regions of China except for some very cold areas, where higher air temperatures will make visitors feel more comfortable and the relatively poor socioeconomic conditions will improve in the 2030s, 2050s and 2090s. The average higher integrated suitability area (integrated suitability values greater than 0.5) under four climatic-socioeconomic scenarios decreases from the current 29.9%-14.4%, 5.0% and 4.5% by the 2030s, 2050s and 2090s, respectively. Under RCP2.6-SSP1, the higher integrated suitability area is projected to decrease from the current 28.0%-5.2% by the 2050s and then increase to 5.3% by the 2090s. Under RCP4.5-SSP2, RCP8.5-SSP3, and RCP8.5-SSP5, the higher integrated suitability area is projected to continuously decrease from 30.3%, 30.6% and 30.6% in the 2010s to 4.1%, 4.4% and 4.4% in the 2090s, respectively. By the 2090s, 41, 138 and 277 existing ski areas are projected to be closed under RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP3/RCP8.5-SSP5, respectively. It is clear that emission pathways and climate change adaptation and mitigation strategies will greatly shape the development of China's regional ski tourism.
C1 [Deng Jie; Che Tao; Dai Li-Yun] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China.
   [Deng Jie; Che Tao] Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China.
   [Deng Jie] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
   [Jiang Tong] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Sch Geog Sci, Nanjing 210044, Peoples R China.
   [Dai Li-Yun] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210000, Peoples R China.
C3 Chinese Academy of Sciences; Chinese Academy of Sciences; Chinese
   Academy of Sciences; University of Chinese Academy of Sciences, CAS;
   Nanjing University of Information Science & Technology
RP Che, T (corresponding author), Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China.
EM chetao@lzb.ac.cn
RI Che, Tao/K-7136-2013; Tong, Jiang/KHD-8592-2024; DAI, LIYUN/A-1450-2015
FU National Natural Science Foundation of China [41690140, 41771389];
   National Foundational Scientific and Technological Work Programs of the
   Ministry of Science and Technology of China [2017FY100501]
FX This work was supported by the National Natural Science Foundation of
   China (41690140 and 41771389) and the National Foundational Scientific
   and Technological Work Programs of the Ministry of Science and
   Technology of China (2017FY100501).
CR Abegg B., 2007, CLIMATE CHANGE EUROP, P25
   An HM, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11113138
   Balbi S, 2013, ENVIRON MODELL SOFTW, V45, P29, DOI 10.1016/j.envsoft.2012.10.004
   Behringer J., 2000, INTEGRATED ASSESSMEN, V1, P331, DOI [DOI 10.1023/A:1018940901744, 10.1023/a:1018940901744]
   Cai M., 2017, B SPORT SCI TECHNOLO, V25, P125, DOI [10.19379/j.cnki.issn.1005-0256.2017.01.055, DOI 10.19379/J.CNKI.ISSN.1005-0256.2017.01.055]
   Cai WY, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16020186
   Damm Andrea, 2017, Climate Services, V7, P31, DOI 10.1016/j.cliser.2016.07.003
   Damm A, 2014, TOURISM MANAGE, V43, P8, DOI 10.1016/j.tourman.2014.01.009
   Dawson J., 2013, Leisure/Loisir, V37, P127, DOI 10.1080/14927713.2013.805037
   Dawson J, 2009, CLIM RES, V39, P1, DOI 10.3354/cr00793
   Dawson J, 2011, J TRAVEL TOUR MARK, V28, P388, DOI 10.1080/10548408.2011.571573
   Dellink R, 2017, GLOBAL ENVIRON CHANG, V42, P200, DOI 10.1016/j.gloenvcha.2015.06.004
   Demiroglu OC, 2015, TOUR REV, V70, P1, DOI 10.1108/TR-01-2014-0003
   Demiroglu OC, 2016, ATMOSPHERE-BASEL, V7, DOI 10.3390/atmos7040052
   Deng J, 2019, CRYOSPHERE, V13, P2149, DOI 10.5194/tc-13-2149-2019
   Dezsi S, 2015, CARPATH J EARTH ENV, V10, P223
   Evren S, 2018, J DESTIN MARK MANAGE, V9, P247, DOI 10.1016/j.jdmm.2018.01.009
   Fang Y, 2021, INT J BIOMETEOROL, V65, P677, DOI 10.1007/s00484-019-01822-x
   Fidelus-Orzechowska J, 2018, SCI TOTAL ENVIRON, V630, P1298, DOI 10.1016/j.scitotenv.2018.02.305
   Fukushima T., 2002, Mitigation and Adaptation Strategies for Global Change, V7, P173, DOI 10.1023/A:1022803405470
   Hempel S, 2013, EARTH SYST DYNAM, V4, P219, DOI 10.5194/esd-4-219-2013
   Hennessy KJ, 2008, CLIM RES, V35, P255, DOI 10.3354/cr00706
   Huang JL, 2019, EARTHS FUTURE, V7, P250, DOI 10.1029/2018EF000964
   Jiang T., 2020, J NANJING U INFORM S, V12, P56, DOI [10.13878/j.cnki.jnu-ist.2020.01.009, DOI 10.13878/J.CNKI.JNU-IST.2020.01.009]
   Jing C, 2020, J GEOGR SCI, V30, P68, DOI 10.1007/s11442-020-1715-x
   Kan J., 2012, J WUHAN I PHYS ED, V46, P39, DOI [10.15930/j.cnki.wtxb.2012.01.009, DOI 10.15930/J.CNKI.WTXB.2012.01.009]
   Konig U., 1998, TOURISM WARMER WORLD
   Kureha M., 2008, GLOB ENVIRON RES, V12, P137
   Li X, 2017, J BEIJING SPORT U, V40, P9, DOI [10.19582/j.cnki.11-3785/g8.2017.10.002, DOI 10.19582/J.CNKI.11-3785/G8.2017.10.002]
   Marty C, 2017, CRYOSPHERE, V11, P517, DOI 10.5194/tc-11-517-2017
   Moen J., 2007, Journal of Sustainable Tourism, V15, P418, DOI 10.2167/jost624.0
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Pickering C, 2011, J SUSTAIN TOUR, V19, P767, DOI 10.1080/09669582.2010.544741
   Pons M, 2014, INT J GEOGR INF SCI, V28, P2474, DOI 10.1080/13658816.2014.933481
   Pütz M, 2011, MT RES DEV, V31, P357, DOI 10.1659/MRD-JOURNAL-D-11-00039.1
   Ristic R, 2012, ENVIRON MANAGE, V49, P580, DOI 10.1007/s00267-012-9812-y
   Rutty M, 2017, TOURISM MANAGE, V58, P196, DOI 10.1016/j.tourman.2016.10.020
   Rutty M, 2015, J OUTDO RECREAT TOUR, V11, P13, DOI 10.1016/j.jort.2015.07.002
   Scott D., 2006, Journal of Sustainable Tourism, V14, P376, DOI 10.2167/jost550.0
   Scott D, 2003, CLIM RES, V23, P171, DOI 10.3354/cr023171
   Scott D, 2019, CURR ISSUES TOUR, V22, P1327, DOI 10.1080/13683500.2017.1401984
   Soboll A, 2012, J SUSTAIN TOUR, V20, P101, DOI 10.1080/09669582.2011.610895
   Spandre P, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-44068-8
   Steiger R, 2020, TOURISM MANAGE, V77, DOI 10.1016/j.tourman.2019.104032
   Steiger R, 2019, CURR ISSUES TOUR, V22, P1343, DOI 10.1080/13683500.2017.1410110
   Steiger R, 2013, TOURISM GEOGR, V15, P577, DOI 10.1080/14616688.2012.762539
   Steiger R, 2011, TOUR REV, V66, P4, DOI 10.1108/16605371111175285
   Steiger R, 2010, CLIM RES, V43, P251, DOI 10.3354/cr00941
   Su BD, 2018, P NATL ACAD SCI USA, V115, P10600, DOI 10.1073/pnas.1802129115
   Su BD, 2017, CLIMATIC CHANGE, V141, P533, DOI 10.1007/s10584-016-1852-5
   Suzuki-Parker A, 2018, ADV METEOROL, V2018, DOI 10.1155/2018/8529748
   Tervo K, 2008, SCAND J HOSP TOUR, V8, P317, DOI 10.1080/15022250802553696
   Unbehaun W, 2008, TOUR REV, V63, P36, DOI 10.1108/16605370810861035
   [王世金 Wang Shijin], 2017, [冰川冻土, Journal of Glaciology and Geocryology], V39, P902
   Wang Xiu-rong, 2020, Yingyong Shengtai Xuebao, V31, P1259, DOI 10.13287/j.1001-9332.202004.013
   Wen SS, 2019, ATMOS RES, V218, P296, DOI 10.1016/j.atmosres.2018.12.003
   Witting M, 2019, J OUTDOOR REC TOUR, V26, P50, DOI 10.1016/j.jort.2019.03.002
   Wu B., 2020, 2019 CHINA SKI IND W
   Xu Q., 2014, METEOROLOGICAL SCI T, V42, P938, DOI [10.3969/j.issn.1671-6345.2014.05.037, DOI 10.3969/J.ISSN.1671-6345.2014.05.037]
   [杨笑宇 Yang Xiaoyu], 2017, [气候与环境研究, Climatic and Environmental Research], V22, P253
   Zhou BT, 2018, J CLIMATE, V31, P5873, DOI 10.1175/JCLI-D-17-0428.1
NR 61
TC 12
Z9 15
U1 8
U2 50
PU KEAI PUBLISHING LTD
PI BEIJING
PA 16 DONGHUANGCHENGGEN NORTH ST, Building 5, Room 411, BEIJING, DONGCHENG
   DISTRICT 100009, PEOPLES R CHINA
SN 1674-9278
J9 ADV CLIM CHANG RES
JI Adv. Clim. Chang. Res.
PD APR
PY 2021
VL 12
IS 2
BP 224
EP 239
DI 10.1016/j.accre.2021.03.007
PG 16
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA SH7XB
UT WOS:000654345800007
OA gold
DA 2025-01-10
ER

PT J
AU Fellous, A
   Shama, LNS
AF Fellous, Alexandre
   Shama, Lisa N. S.
TI Genome Survey of Chromatin-Modifying Enzymes in Threespine Stickleback:
   A Crucial Epigenetic Toolkit for Adaptation?
SO FRONTIERS IN MARINE SCIENCE
LA English
DT Article
DE evolution; fish; stickleback; DNA methylation/hydroxymethylation;
   histone modifications; miRNA; global climate change; aquaculture
ID DNA METHYLATION; HISTONE-DEMETHYLASE; JUMONJI GENE; TRANSGENERATIONAL
   PLASTICITY; O-GLCNACYLATION; FAMILY PROTEINS; FRESH-WATER; TET FAMILY;
   ZEBRAFISH; MARINE
AB Ocean environments are changing rapidly and marine organisms need to cope with these changes in order to survive, develop, and reproduce. To do so, organisms can either migrate, adapt in situ or acclimate via phenotypic plasticity. In this context, the emerging field of environmental epigenetics investigates the contribution of genetic and epigenetic information to adaptive potential of wild populations. Epigenetic modifications are based on the highly dynamic combination of DNA methylation, histone modifications, and non-coding RNAs, which may facilitate phenotypic plasticity through genotype-epigenotype-environment interactions, and can drive rapid evolution in wild populations. However, while knowledge of epigenetic contributions to phenotypes across different developmental and generational timescales is increasing for medical research model species, the mechanistic and synergistic action of these modifications remain comparatively understudied in ecological models such as teleost fishes. Here, we characterized the evolution of the gene toolkit involved in key molecular epigenetic pathways including DNA methylation, histone modifications, macroH2A histone, and miRNA biogenesis/turnover in threespine stickleback, a model species in evolution and ecology. We then investigated these genes within a phylogenetic context by comparing them in stickleback to human, mouse, chicken, tropical clawed frog, zebrafish, medaka, green spotted puffer, channel catfish, and mangrove rivulus. We found that, in general, conserved domains, in conjunction with their phylogenetic positions, suggest evolutionary conservation of putative enzyme activity in stickleback. However, molecular epigenetic pathways also revealed that teleost gene evolution is diversified and complex. Specifically, the number of genes, gene loss/duplication events, identified conserved domains, and putative protein lengths vary greatly from one species to another, particularly within fishes, which exhibit a potentially new class of histone deacetylases. This suggests different biological functions specific to fish species, and that the action of genes regulating epigenetic modifications in model species are not necessarily applicable to other related species. We integrate our results into recent advances concerning epigenetic mechanisms in teleosts, and conclude by discussing the necessity to delve deeper into the fundamental mechanics of epigenetic modifications in a wide array of taxa, particularly those relevant for assisted evolution, conservation, aquaculture, fisheries, and climate change-adaptation studies.
C1 [Fellous, Alexandre; Shama, Lisa N. S.] Alfred Wegener Inst, Helmholtz Ctr Polar & Marine Res, Coastal Ecol Sect, Wadden Sea Stn Sylt, Bremerhaven, Germany.
C3 Helmholtz Association; Alfred Wegener Institute, Helmholtz Centre for
   Polar & Marine Research
RP Fellous, A (corresponding author), Alfred Wegener Inst, Helmholtz Ctr Polar & Marine Res, Coastal Ecol Sect, Wadden Sea Stn Sylt, Bremerhaven, Germany.
EM alexandre.fellous@awi.de
RI Shama, Lisa N S/K-7469-2017
OI Shama, Lisa N S/0000-0002-9017-9950
FU Strategy Funds Grant of the Alfred-Wegener-Institut, Helmholtz-Zentrum
   fur Polar-und Meeresforschung
FX This study was funded by a Strategy Funds Grant of the
   Alfred-Wegener-Institut, Helmholtz-Zentrum fur Polar-und Meeresforschung
   awarded to LS.
CR Akerberg AA, 2017, DEV BIOL, V426, P84, DOI 10.1016/j.ydbio.2017.03.030
   [Anonymous], 2017, ONCOTARGET
   Artemov AV, 2017, MOL BIOL EVOL, V34, P2203, DOI 10.1093/molbev/msx156
   Balasubramanian S, 2019, GENE, V718, DOI 10.1016/j.gene.2019.144049
   Ballestar E, 2001, EUR J BIOCHEM, V268, P1, DOI 10.1046/j.1432-1327.2001.01869.x
   Baulcombe DC, 2014, CSH PERSPECT BIOL, V6, DOI 10.1101/cshperspect.a019471
   BAUMGART M, 2017, MIRNA CATALOGUE NCRN, V0018
   Belle JI, 2014, INT J BIOCHEM CELL B, V50, P161, DOI 10.1016/j.biocel.2014.03.004
   Best C, 2018, COMP BIOCHEM PHYS B, V224, P210, DOI 10.1016/j.cbpb.2018.01.006
   Biterge B, 2014, CELL TISSUE RES, V356, P457, DOI 10.1007/s00441-014-1862-4
   Black JC, 2012, MOL CELL, V48, P491, DOI 10.1016/j.molcel.2012.11.006
   Campos C, 2012, GENE, V500, P93, DOI 10.1016/j.gene.2012.03.041
   Cao J, 2012, FRONT ONCOL, V2, DOI 10.3389/fonc.2012.00026
   Balasch JC, 2019, FRONT ENDOCRINOL, V10, DOI 10.3389/fendo.2019.00062
   Chazelle B, 2019, J MACH LEARN RES, V20
   Cosseau C, 2017, TRENDS PARASITOL, V33, P285, DOI 10.1016/j.pt.2016.12.002
   Cossins AR, 2005, NAT REV GENET, V6, P324, DOI 10.1038/nrg1590
   Costa-Pinheiro P, 2015, EPIGENOMICS-UK, V7, P1003, DOI 10.2217/epi.15.56
   Dehennaut V, 2014, FRONT ENDOCRINOL, V5, DOI 10.3389/fendo.2014.00155
   Desvignes T, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-40361-8
   Deyrieux AF, 2017, ADV EXP MED BIOL, V963, P197, DOI 10.1007/978-3-319-50044-7_12
   Dupret B, 2017, BBA-GENE REGUL MECH, V1860, P1079, DOI 10.1016/j.bbagrm.2017.08.011
   Eckersley-Maslin MA, 2018, NAT REV MOL CELL BIO, V19, P436, DOI 10.1038/s41580-018-0008-z
   Edgar RC, 2004, NUCLEIC ACIDS RES, V32, P1792, DOI 10.1093/nar/gkh340
   Eirin-Lopez JM, 2019, ANNU REV MAR SCI, V11, P335, DOI 10.1146/annurev-marine-010318-095114
   Ellison A, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.1900
   Fatemi M, 2006, J CELL SCI, V119, P3033, DOI 10.1242/jcs.03099
   Fellous A, 2019, GENES-BASEL, V10, DOI 10.3390/genes10090695
   Fellous A, 2019, GENE, V691, P56, DOI 10.1016/j.gene.2018.12.057
   Fellous A, 2019, GENE, V687, P173, DOI 10.1016/j.gene.2018.11.046
   Fellous A, 2018, ECOL EVOL, V8, P6016, DOI 10.1002/ece3.4141
   Fellous A, 2015, MAR GENOM, V19, P23, DOI 10.1016/j.margen.2014.09.002
   Fellous A, 2014, GENE, V538, P164, DOI 10.1016/j.gene.2013.12.016
   Feng SH, 2010, P NATL ACAD SCI USA, V107, P8689, DOI 10.1073/pnas.1002720107
   Fincham JRS., 1997, GENET RES, V69, P159
   Firmino J, 2017, BMC DEV BIOL, V17, DOI 10.1186/s12861-017-0154-0
   Gao H, 2015, J CELL SCI, V128, P2340, DOI 10.1242/jcs.167874
   Gavery MR, 2019, GENES-BASEL, V10, DOI 10.3390/genes10050356
   Gavery MR, 2017, PEERJ, V5, DOI 10.7717/peerj.4147
   Gay S, 2018, PLOS GENET, V14, DOI 10.1371/journal.pgen.1007593
   Greiss S, 2013, EUROPE PMC FUNDERS G, V28, P407, DOI DOI 10.1007/S10059-009-0169-X.SIRTUIN/SIR2
   He Y, 2014, CELL PROLIFERAT, V47, P91, DOI 10.1111/cpr.12081
   Heckwolf M.J., 2019, BIORXIV, DOI [10.1101/649574, DOI 10.1101/649574]
   Heckwolf MJ, 2018, EVOL APPL, V11, P1873, DOI 10.1111/eva.12688
   Horsfield JA, 2019, BIOCHEM SOC T, V47, P713, DOI 10.1042/BST20180617
   Jiang Feng, 2017, GigaScience, V6, P1, DOI 10.1093/gigascience/gix031
   Kamstra JH, 2015, ENVIRON SCI POLLUT R, V22, P16262, DOI 10.1007/s11356-014-3466-7
   Karmodiya K, 2014, SCI REP-UK, V4, DOI 10.1038/srep06076
   Kim JH, 2009, BBA-MOL BASIS DIS, V1792, P155, DOI 10.1016/j.bbadis.2008.12.008
   Kitano J, 2019, DEV GROWTH DIFFER, V61, P104, DOI 10.1111/dgd.12576
   Kozlowski M, 2018, EMBO REP, V19, DOI 10.15252/embr.201744445
   Kumar A, 2019, GENE, V694, P1, DOI 10.1016/j.gene.2018.12.078
   Kumar S, 2016, MOL BIOL EVOL, V33, P1870, DOI [10.1093/molbev/msw054, 10.1093/molbev/msv279]
   Labbé C, 2017, AQUACULTURE, V472, P93, DOI 10.1016/j.aquaculture.2016.07.026
   Laporte M, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaw1644
   Le Luyer J, 2017, P NATL ACAD SCI USA, V114, P12964, DOI 10.1073/pnas.1711229114
   Lei L, 2012, BMC EVOL BIOL, V12, DOI 10.1186/1471-2148-12-51
   LI E, 1992, CELL, V69, P915, DOI 10.1016/0092-8674(92)90611-F
   Lim L. P., 2005, NATURE, V292, P288
   Lindeman LC, 2010, INT J DEV BIOL, V54, P803, DOI 10.1387/ijdb.103081ll
   Loponte S, 2016, SCI REP-UK, V6, DOI 10.1038/srep30213
   Lyko F, 2018, NAT REV GENET, V19, P81, DOI 10.1038/nrg.2017.80
   Martin C, 2005, NAT REV MOL CELL BIO, V6, P838, DOI 10.1038/nrm1761
   Mcghee K. E., 2014, P R SOC B, V281, P2
   Metzger DCH, 2018, GENOME BIOL EVOL, V10, P775, DOI 10.1093/gbe/evy034
   Metzger DCH, 2017, P ROY SOC B-BIOL SCI, V284, DOI 10.1098/rspb.2017.1667
   Metzger DCH, 2016, MAR GENOM, V30, P43, DOI 10.1016/j.margen.2016.01.004
   Nijman SMB, 2005, CELL, V123, P773, DOI 10.1016/j.cell.2005.11.007
   Nozawa K, 2017, DEV NEUROBIOL, V77, P1101, DOI 10.1002/dneu.22498
   Okano M, 1999, CELL, V99, P247, DOI 10.1016/S0092-8674(00)81656-6
   Panserat S, 2017, AQUACULTURE, V468, P515, DOI 10.1016/j.aquaculture.2016.11.021
   Perina D, 2014, DNA REPAIR, V23, P4, DOI 10.1016/j.dnarep.2014.05.003
   Petrie K, 2003, J BIOL CHEM, V278, P16059, DOI 10.1074/jbc.M212935200
   Petrossian TC, 2011, MOL CELL PROTEOMICS, V10, DOI 10.1074/mcp.M110.000976
   Pinto R, 2005, FEBS LETT, V579, P5553, DOI 10.1016/j.febslet.2005.09.019
   Potok ME, 2013, CELL, V153, P759, DOI 10.1016/j.cell.2013.04.030
   Putnam HM, 2016, EVOL APPL, V9, P1165, DOI 10.1111/eva.12408
   Putnam HM, 2015, J EXP BIOL, V218, P2365, DOI 10.1242/jeb.123018
   Qian SZ, 2015, PLANT PHYSIOL, V168, P1321, DOI 10.1104/pp.15.00520
   Rack JGM, 2018, CELL CHEM BIOL, V25, P1533, DOI 10.1016/j.chembiol.2018.11.001
   Radermacher PT, 2014, P NATL ACAD SCI USA, V111, P5592, DOI 10.1073/pnas.1322396111
   Rastorguev SM, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-18128-w
   Rastorguev SM, 2016, MOL ECOL RESOUR, V16, P1491, DOI 10.1111/1755-0998.12545
   Riviere G, 2013, MAR BIOTECHNOL, V15, P739, DOI 10.1007/s10126-013-9523-2
   Román AC, 2018, GENOME BIOL, V19, DOI 10.1186/s13059-018-1428-y
   Rossetto D, 2012, EPIGENETICS-US, V7, P1098, DOI 10.4161/epi.21975
   Santiago M, 2014, GENOMICS, V104, P334, DOI 10.1016/j.ygeno.2014.08.018
   Sasai N, 2007, FEBS J, V274, P6139, DOI 10.1111/j.1742-4658.2007.06135.x
   Seebacher F, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-44726-x
   Seto E, 2014, CSH PERSPECT BIOL, V6, DOI 10.1101/cshperspect.a018713
   Shama LNS, 2014, J EVOLUTION BIOL, V27, P2297, DOI 10.1111/jeb.12490
   Shama LNS, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-07140-9
   Shama LNS, 2016, EVOL APPL, V9, P1096, DOI 10.1111/eva.12370
   Shechter D, 2009, P NATL ACAD SCI USA, V106, P749, DOI 10.1073/pnas.0812207106
   Sheikh BN, 2019, NAT REV GENET, V20, P7, DOI 10.1038/s41576-018-0072-4
   Sheng K, 2014, BIOMED RES INT, V2014, DOI 10.1155/2014/870695
   Shi L, 2011, P NATL ACAD SCI USA, V108, P7541, DOI 10.1073/pnas.1017374108
   Shilo Y, 2003, P NATL ACAD SCI USA, V100, P13225, DOI 10.1073/pnas.1735528100
   Shin J, 2018, BMB REP, V51, P500, DOI 10.5483/BMBRep.2018.51.10.172
   Smith G, 2015, MOL BIOL EVOL, V32, P888, DOI 10.1093/molbev/msu344
   Sohn KC, 2005, BIOCHEM BIOPH RES CO, V337, P256, DOI 10.1016/j.bbrc.2005.09.049
   Stewart S, 2009, P NATL ACAD SCI USA, V106, P19889, DOI 10.1073/pnas.0904132106
   Takeuchi T, 1999, MECH DEVELOP, V86, P29, DOI 10.1016/S0925-4773(99)00100-8
   Teigen LE, 2015, COMP BIOCHEM PHYS A, V188, P139, DOI 10.1016/j.cbpa.2015.06.028
   Todd EV, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaw7006
   Toni LS, 2016, J EXP BIOL, V219, P544, DOI 10.1242/jeb.131862
   Tse ACK, 2016, AQUAT TOXICOL, V180, P266, DOI 10.1016/j.aquatox.2016.10.007
   Tse WKF, 2009, BMC GENOMICS, V10, DOI 10.1186/1471-2164-10-637
   Tse WKF, 2017, BIOCHEM BIOPH RES CO, V487, P813, DOI 10.1016/j.bbrc.2017.04.132
   van Leeuwen F, 2002, CELL, V109, P745, DOI 10.1016/S0092-8674(02)00759-6
   van Otterdijk SD, 2016, FASEB J, V30, P2457, DOI 10.1096/fj.201500083
   Vastenhouw NL, 2019, DEVELOPMENT, V146, DOI 10.1242/dev.161471
   Verdone L, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0144287
   Wang GF, 2017, J EXP BOT, V68, P797, DOI 10.1093/jxb/erw486
   Wang XG, 2019, EPIGENETICS-US, V14, P611, DOI 10.1080/15592294.2019.1605816
   Wang YC, 2012, FEBS J, V279, P932, DOI 10.1111/j.1742-4658.2012.08490.x
   Wu N, 2009, BIOL REPROD, V81, P275, DOI 10.1095/biolreprod.108.074955
   Yang XJ, 2015, BBA-MOL CELL RES, V1853, P1818, DOI 10.1016/j.bbamcr.2015.04.014
   Yeh HY, 2012, FISH PHYSIOL BIOCHEM, V38, P1083, DOI 10.1007/s10695-011-9593-x
   Yuan H, 2010, CELL RES, V20, P185, DOI 10.1038/cr.2009.101
   Zhang J, 2019, MOL MED REP, V19, P3963, DOI 10.3892/mmr.2019.10111
   Zhao HB, 2013, J HUM GENET, V58, P421, DOI 10.1038/jhg.2013.63
   Zheng N, 2017, ANNU REV BIOCHEM, V86, P129, DOI 10.1146/annurev-biochem-060815-014922
NR 123
TC 8
Z9 8
U1 1
U2 41
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-7745
J9 FRONT MAR SCI
JI Front. Mar. Sci.
PD NOV 20
PY 2019
VL 6
AR 721
DI 10.3389/fmars.2019.00721
PG 16
WC Environmental Sciences; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology
GA JO6ZV
UT WOS:000497726600001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Lalani, B
   Dorward, P
   Holloway, G
   Wauters, E
AF Lalani, Baqir
   Dorward, Peter
   Holloway, Garth
   Wauters, Erwin
TI Smallholder farmers' motivations for using Conservation Agriculture and
   the roles of yield, labour and soil fertility in decision making
SO AGRICULTURAL SYSTEMS
LA English
DT Article
DE Conservation Agriculture; Adoption; Theory of Planned Behaviour
ID CLIMATE-CHANGE ADAPTATION; FARMING SYSTEMS; ADOPTION; AFRICA;
   INTENSIFICATION; SUSTAINABILITY; PERCEPTIONS; MANAGEMENT; INTENTION;
   COUNTRIES
AB Conservation Agriculture (CA) has been widely promoted as an agro-ecological approach to sustainable production intensification. Despite numerous initiatives promoting CA across Sub-Saharan Africa there have been low rates of adoption. Furthermore, there has been strong debate concerning the ability of CA to provide benefits to smallholder farmers regarding yield, labour, soil quality and weeding, particularly where farmers are unable to access external inputs such as herbicides. This research finds evidence that CA, using no external inputs, is most attractive among the very poor and that farmers are driven primarily by strong motivational factors in the key areas of current contention, namely yield, labour, soil quality and weeding time benefits. This study is the first to incorporate a quantitative socio-psychological model to understand factors driving adoption of CA. Using the Theory of Planned Behaviour (TPB), it explores farmers' intention to use CA (within the next 12 months) in Cabo Delgado, Mozambique where CA has been promoted for almost a decade. The study site provides a rich population from which to examine farmers' decision making in using CA. Regression estimates show that the TPB provides a valid model of explaining farmers' intention to use CA accounting for 80% of the variation in intention. Farmers' attitude is found to be the strongest predictor of intention. This is mediated through key cognitive drivers present that influence farmers' attitude such as increased yields, reduction in labour, improvement in soil quality and, reduction in weeds. Subjective norm (i.e. social pressure from referents) and perceived behavioural control also significantly influenced farmers' intention. Furthermore, path analysis identifies farmers that are members of a Farmer Field School or participants of other organisations (e.g. savings group, seed multiplication group or a specific crop/livestock association) have a significantly stronger positive attitude towards CA with the poorest the most likely users and the cohort that find it the easiest to use. This study provides improved understanding relevant to many developing countries, of smallholder farmers' adoption dynamics related-to CA, and of how farmers may approach this and other 'new' management systems. (C) 2016 Elsevier Ltd. All rights reserved.
C1 [Lalani, Baqir; Dorward, Peter; Holloway, Garth] Univ Reading, Sch Agr Policy & Dev, POB 237, Reading RG6 6AR, Berks, England.
   [Wauters, Erwin] Inst Agr & Fisheries Res ILVO, Social Sci Unit, Burg van Gansberghelaan 115 Bus 2, B-9820 Merelbeke, Belgium.
   [Wauters, Erwin] Univ Antwerp, Dept Vet Sci, Antwerp, Belgium.
C3 University of Reading; Institute For Agricultural & Fisheries Research;
   University of Antwerp
RP Lalani, B (corresponding author), Univ Reading, Sch Agr Policy & Dev, POB 237, Reading RG6 6AR, Berks, England.
EM b.lalani@pgr.reading.ac.uk; p.t.dorward@reading.ac.uk;
   garth.holloway@reading.ac.uk; Erwin.Wauters@ilvo.vlaanderen.be
RI Wauters, Erwin/J-5536-2019
OI Wauters, Erwin/0000-0002-1054-0487; Dorward, Peter/0000-0003-2831-3693;
   Lalani, Baqir/0000-0001-8287-3283
FU Aga Khan Foundation (Mozambique); BBSRC [BB/S01490X/1] Funding Source:
   UKRI
FX The authors wish to thank the Aga Khan Foundation (Mozambique) for
   funding the household survey component of this study and for the many
   staff that supported the data collection activities. We are especially
   grateful to Jose Dambiro, Alastair Stewart, Graham Sherbut, Fredito
   Xavier and Gabriel Sebastiao. We would also like to thank two anonymous
   reviewers and the Editor of this Journal for very useful comments on the
   manuscript.
CR Adekunle A., 2008, WORKSH INV SUST CROP
   AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T
   Ajzen I., 2005, EBOOK: Attitudes, Personality and Behaviour
   Ajzen I, 2011, PSYCHOL HEALTH, V26, P1113, DOI 10.1080/08870446.2011.613995
   [Anonymous], 2015, RENEW AGR FOOD SYST
   [Anonymous], PERF DES HUM MOC 199
   [Anonymous], 2013, CONSERVATION AGR GLO
   [Anonymous], CONSERVATION AGR IN
   [Anonymous], ZON AGR EC MOC
   [Anonymous], NUTR CYCL AGROECOSYS
   [Anonymous], 2012, ASSESSING IMPACTS CO
   [Anonymous], 2002, Qualitative Research and Evaluation Methods
   Arriagada R. A., 2009, Journal of Sustainable Forestry, V28, P343, DOI 10.1080/10549810802701192
   Bandiera O, 2006, ECON J, V116, P869, DOI 10.1111/j.1468-0297.2006.01115.x
   Baudron F, 2012, J DEV STUD, V48, P393, DOI 10.1080/00220388.2011.587509
   Beedell J, 2000, J RURAL STUD, V16, P117, DOI 10.1016/S0743-0167(99)00043-1
   Benson T., 2012, SUPPLY INORAGANIC FE
   Borges JAR, 2014, LIVEST SCI, V169, P163, DOI 10.1016/j.livsci.2014.09.014
   Caswell K.F., 2001, ADOPTION AGR PRODUCT
   Cavane E., 2011, Journal of International Agricultural Extension and Education, V18, P5, DOI DOI 10.5191/JIAEE.2011.18101
   Chauhan BS, 2012, CROP PROT, V38, P57, DOI 10.1016/j.cropro.2012.03.010
   Cunguara B, 2011, FOOD POLICY, V36, P378, DOI 10.1016/j.foodpol.2011.03.002
   Davis LE, 2002, J EDUC PSYCHOL, V94, P810, DOI 10.1037//0022-0663.94.4.810
   Edirisinghe JC, 2015, ECON ANAL POLICY, V45, P33, DOI 10.1016/j.eap.2015.01.001
   FAO, 2009, The State of Food Insecurity in the World 2009
   Fishbein M., 1975, Belief, attitudes, intention, DOI DOI 10.1080/00336297.1994.10484118.FAO/RAP/FIPL
   Friedrich T., 2012, The journal of field actions, Field Actions Science Reports Special Issue (6): Reconciling Poverty Eradication and Protection of the Environment
   Garforth C.J., 2004, J FARM MANAG, P17
   Garforth C, 2006, LIVEST SCI, V103, P158, DOI 10.1016/j.livsci.2006.02.006
   Giller KE, 2012, NATURE, V485, P41, DOI 10.1038/485041c
   Giller KE, 2009, FIELD CROP RES, V114, P23, DOI 10.1016/j.fcr.2009.06.017
   Grabowski P. P., 2013, INT J AGR SUSTAIN, P1
   Greiner R, 2015, AGR SYST, V137, P154, DOI 10.1016/j.agsy.2015.04.005
   INE, 2013, PROJ AN POP TOT PROV, P2007
   Kassam A, 2009, INT J AGR SUSTAIN, V7, P292, DOI 10.3763/ijas.2009.0477
   Knowler D, 2007, FOOD POLICY, V32, P25, DOI 10.1016/j.foodpol.2006.01.003
   Läpple D, 2013, ECOL ECON, V88, P11, DOI 10.1016/j.ecolecon.2012.12.025
   Lalani B., 2016, EC ADOPTION IN PRESS
   Leonardo WJ, 2015, FOOD SECUR, V7, P857, DOI 10.1007/s12571-015-0480-7
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Maria R.M., 2006, Soil Science, V171
   Martinez -Garcia C.G., 2013, FACTORS INFLUENCING
   Nkala P, 2011, J SUSTAIN AGR, V35, P757, DOI 10.1080/10440046.2011.606492
   Okoye CU, 1998, SOIL TILL RES, V45, P251, DOI 10.1016/S0933-3630(96)00137-7
   Osbahr H, 2011, EXP AGR, V47, P293, DOI 10.1017/S0014479710000785
   Pretty J, 2008, PHILOS T R SOC B, V363, P447, DOI 10.1098/rstb.2007.2163
   Rockström J, 2009, SOIL TILL RES, V103, P23, DOI 10.1016/j.still.2008.09.013
   Roxburgh CW, 2016, AGR SYST, V142, P9, DOI 10.1016/j.agsy.2015.10.010
   Rusinamhodzi L, 2011, AGRON SUSTAIN DEV, V31, P657, DOI 10.1007/s13593-011-0040-2
   SALTIEL J, 1994, RURAL SOCIOL, V59, P333, DOI 10.1111/j.1549-0831.1994.tb00536.x
   Sewell AM, 2014, AGR SYST, V125, P63, DOI 10.1016/j.agsy.2013.12.002
   Silici L., 2015, Sustainable Agriculture For Small-Scale Farmers
   Somda J, 2002, ECOL ECON, V43, P175, DOI 10.1016/S0921-8009(02)00208-2
   Staff S.S., 2010, KEYS SOIL TAXONOMY, V11th
   Stevenson JR, 2014, AGR ECOSYST ENVIRON, V187, P1, DOI 10.1016/j.agee.2014.01.018
   Sumberg J, 2013, AGR HUM VALUES, V30, P71, DOI 10.1007/s10460-012-9376-8
   Sutcliffe C, 2016, REG ENVIRON CHANGE, V16, P1215, DOI 10.1007/s10113-015-0842-x
   Nguyen TPL, 2016, AGR SYST, V143, P205, DOI 10.1016/j.agsy.2016.01.001
   Thierfelder C, 2010, J CROP IMPROV, V24, P113, DOI 10.1080/15427520903558484
   Thierfelder C, 2016, AGR ECOSYST ENVIRON, V222, P112, DOI 10.1016/j.agee.2016.02.009
   Thierfelder C, 2013, INT J AGR SUSTAIN, V11, P108, DOI 10.1080/14735903.2012.703894
   Thierfelder C, 2013, FIELD CROP RES, V142, P47, DOI 10.1016/j.fcr.2012.11.010
   Tilman D, 1999, P NATL ACAD SCI USA, V96, P5995, DOI 10.1073/pnas.96.11.5995
   Uaiene R., 2009, DETERMINANT AGR TECH
   Van den Broeck Katleen, 2005, POVERTY MOZAMBIQUE U
   Waddington H., 2014, 3IE REV SUMMARY
   Wauters Erwin, 2014, International Journal of Agricultural Resources Governance and Ecology, V10, P78, DOI 10.1504/IJARGE.2014.061058
   Wauters E, 2010, LAND USE POLICY, V27, P86, DOI 10.1016/j.landusepol.2009.02.009
   Yazdanpanah M, 2014, J ENVIRON MANAGE, V135, P63, DOI 10.1016/j.jenvman.2014.01.016
NR 69
TC 146
Z9 162
U1 5
U2 128
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0308-521X
EI 1873-2267
J9 AGR SYST
JI Agric. Syst.
PD JUL
PY 2016
VL 146
BP 80
EP 90
DI 10.1016/j.agsy.2016.04.002
PG 11
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture
GA DQ7FC
UT WOS:000379371300008
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Geffert, K
   Voss, S
   Rehfuess, E
   Rechel, B
AF Geffert, Karin
   Voss, Stephan
   Rehfuess, Eva
   Rechel, Bernd
TI The role of the public health service in the implementation of heat
   health action plans for climate change adaptation in Germany: A
   qualitative study
SO HEALTH RESEARCH POLICY AND SYSTEMS
LA English
DT Article
DE Heat health action plan; Public health service; Climate change; Hot
   temperature
AB BackgroundIn response to climate change-induced increases in heat periods, the WHO recommends the implementation of heat health action plans (HHAPs). In Germany, HHAPs are implemented neither comprehensively nor nationwide. Several recommendations have identified the public health service (PHS) at municipal and federal state levels as a key actor regarding to heat and health. Therefore, this study aimed at assessing the role of the PHS in implementing HHAPs at municipal and federal state levels in Germany.MethodsWe conducted a policy document analysis to assess the legal basis for the work of the PHS in the 16 federal states in Germany. Furthermore, we conducted semi-structured interviews with 16 experts from within and outside the PHS to explore their perceptions of the PHS in the implementation of HHAPs. The interviews were analysed using reflective thematic analysis.ResultsThe policy document analysis revealed that heat is not mentioned in any of the federal states' regulatory frameworks for the PHS, while tasks related to environment and health are addressed, but tend to remain vague. The interviews confirmed that there is currently no clearly defined role for the PHS in implementing HHAPs in Germany and that the actual role primarily depends on the local setting. Main barriers and facilitators could be assigned to three levels (individual, organizational and political), and two overarching contextual factors (awareness of the need for adaptation and existence of other public health emergencies) influenced the implementation of HHAPs across all levels. At the individual level, motivation, knowledge and competencies, and previous experience were possible barriers or enablers. At the organizational level, administrative structures, financial and human resources, leadership and networks were barriers or facilitators, while at the political level they included legislation and political decisions.ConclusionsThe PHS could and should be a relevant actor for implementing measures addressing health and climate change locally, in particular because of its focus on vulnerable populations. However, our findings suggest that the legal basis in the federal states of Germany is insufficient. Tailored approaches are needed to overcome barriers such as rigid, non-agile administrative structures and competing priorities, while taking advantage of facilitators such as awareness of relevant actors.
C1 [Geffert, Karin; Voss, Stephan; Rehfuess, Eva] Ludwig Maximilians Univ Munchen, Inst Med Informat Proc Biometry & Epidemiol IBE, Fac Med, Chair Publ Hlth & Hlth Serv Res, Munich, Germany.
   [Geffert, Karin; Voss, Stephan; Rehfuess, Eva] Pettenkofer Sch Publ Hlth, Munich, Germany.
   [Rechel, Bernd] London Sch Hyg & Trop Med, European Observ Hlth Syst & Pol, London, England.
C3 University of Munich; University of London; London School of Hygiene &
   Tropical Medicine
RP Geffert, K (corresponding author), Ludwig Maximilians Univ Munchen, Inst Med Informat Proc Biometry & Epidemiol IBE, Fac Med, Chair Publ Hlth & Hlth Serv Res, Munich, Germany.; Geffert, K (corresponding author), Pettenkofer Sch Publ Hlth, Munich, Germany.
EM kgeffert@ibe.med.uni-muenchen.de
FU Ludwig-Maximilians-Universitt Mnchen (1024)
FX The authors acknowledge the support from Nicole Holliday for
   proofreading an earlier version of the manuscript and from Laura Arnold
   for providing friendly review.
CR Arnold Laura, 2021, Public Health Forum, V29, P47, DOI 10.1515/pubhef-2020-0130
   Austin SE, 2017, Public health adaptation to climate change in the federalist states of Canada
   Austin SE, 2019, SOC SCI MED, V220, P236, DOI 10.1016/j.socscimed.2018.11.002
   Blättner B, 2020, BUNDESGESUNDHEITSBLA, V63, P1013, DOI 10.1007/s00103-020-03189-6
   Blättner B, 2020, PRAVENT GESUNDHEIT, V15, P296, DOI 10.1007/s11553-020-00772-2
   Blumel M, 2020, Germany: health system review, pi
   Bohme C, 2005, 21 KOMM UMW GES GEST
   Bolitho A, 2017, LOCAL ENVIRON, V22, P682, DOI 10.1080/13549839.2016.1254169
   Braun V, 2021, QUAL RES PSYCHOL, V18, P328, DOI 10.1080/14780887.2020.1769238
   Bundesministerium fur Gesundheit, Difference between formal laws and statutory instruments Unterschied zwischen formlichen Gesetzen und Rechtsverordnungen 2016
   Bundesministerium fur Gesundheit, 2021, Pact for the Public Health Service Pakt fur den offentlichen Gesundheitsdienst
   Busetto L, 2020, NEUROL RES PRACT, V2, DOI 10.1186/s42466-020-00059-z
   Casanueva A, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16152657
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   Federal/Lander Ad hoc Working Group on adaptation to the impacts of climate change in health sector, 2017, Recommendations for Action: Heat Action Plans to protect human health Version: 1.0
   Hartwell C, 2023, BMC PUBLIC HEALTH, V23, DOI 10.1186/s12889-023-14996-2
   Herzog C., 2019, The palgrave handbook of methods for media policy research, P385, DOI DOI 10.1007/978-3-030-16065-4_22
   Hsieh HF, 2005, QUAL HEALTH RES, V15, P1277, DOI 10.1177/1049732305276687
   Jones R, Foundations for Decision Making. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Working Group II contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P195
   Kaiser TKC., 2021, Umwelt und Mensch, V1, P27
   Kuhn J., 2018, Public Health Forum, V26, P20
   Matthies F., 2008, Heathealth action plans: guidance, P2008
   Matthies-Wiesler F, 2021, The lancet countdown for health and climate change-2021 Policy Brief for Germany
   Microsoft 365 MSO, Microsoft Word Version, V2202
   Mücke HG, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17217862
   Nowell LS, 2017, INT J QUAL METH, V16, DOI 10.1177/1609406917733847
   O'Brien BC, 2014, ACAD MED, V89, P1245, DOI 10.1097/ACM.0000000000000388
   Poppe F., 2016, Blickpunkt ffentliche Gesundheit, V3, P8
   Rechel B., 2018, Organizing and financing of public health services in Europe
   Reisig V KJ, 2020, Public health service and health promotion Offentlicher Gesundheitsdienst (OGD) und Gesundheitsforderung: Bundeszentrale fur gesundheitliche Aufklarung
   Senatsverwaltung fur Gesundheit Pflege und Gleichstellung, 2016, RES 93 HLTH MIN C BE
   Sheehan M. C., 2022, PLOS CLIM, V1, DOI DOI 10.1371/JOURNAL.PCLM.0000012
   Taupitz J., 2001, MedR-Medizinrecht, V19, P277, DOI [10.1007/s003500100485, DOI 10.1007/S003500100485]
   Teichert U., 2015, Medizinkonomie 1: Das System der Medizinischen Versorgung, P351, DOI [10.1007/978-3-658-01966-210, DOI 10.1007/978-3-658-01966-210]
   Teichert U, 2020, The Public Health Service-Textbook for the Public Health Service Der Offentliche Gesundheitsdienst-Lehrbuch fur den Offentlichen Gesundheitsdienst
   The International Association of National Public Health Institutes (IANPHI), 2021, IANPHI Roadmap for Action on Health and Climate Change. Engaging and Supporting National Public Health Institutes as Key Climate Actors
   Transkripto, 2022, About us
   Vanderplanken K, 2021, HEALTH RES POLICY SY, V19, DOI 10.1186/s12961-020-00645-2
   Vasileiou K, 2018, BMC MED RES METHODOL, V18, DOI 10.1186/s12874-018-0594-7
   VERBI Software, Maxqda 2020
   Watts N, 2018, LANCET, V392, P2479, DOI 10.1016/S0140-6736(18)32594-7
   Winklmayr Claudia, 2023, J Health Monit, V8, P3, DOI 10.25646/11651
   Woodhall SC, 2021, J PUBLIC HEALTH-UK, V43, P425, DOI 10.1093/pubmed/fdz098
   World Health Organization. Regional Office for E, 2021, Heat and health in the WHO European Region: updated evidence for effective prevention
NR 44
TC 0
Z9 0
U1 1
U2 1
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1478-4505
J9 HEALTH RES POLICY SY
JI Health Res. Policy Syst.
PD DEC 5
PY 2024
VL 22
IS 1
AR 161
DI 10.1186/s12961-024-01231-6
PG 14
WC Health Policy & Services
WE Social Science Citation Index (SSCI)
SC Health Care Sciences & Services
GA O4E0D
UT WOS:001370667700002
PM 39639289
OA gold
DA 2025-01-10
ER

PT J
AU Marzouk, M
   Azab, S
AF Marzouk, Mohamed
   Azab, Shimaa
TI Modeling climate change adaptation for sustainable coastal zones using
   GIS and AHP
SO ENVIRONMENTAL MONITORING AND ASSESSMENT
LA English
DT Article
DE Climate change; Coastal vulnerability; Adaptation systems; Geographic
   information system; Decision support systems
ID MULTICRITERIA DECISION-MAKING; RISK REDUCTION; VULNERABILITY; IMPACTS
AB The world is currently confronting one of its biggest environmental challenges: combating climate change. Coastal zones are one of the areas thought to be most sensitive to current and future climate change threats. The paper integrates Remote Sensing (RS), Geographic Information System (GIS) techniques, and Multi-Criteria Decision Analysis (MCDA) to detect vulnerable areas from climate change impacts in coastal zones in order to recommend adaptation systems in new coastal zones that can withstand various climatic changes. The proposed decision-making framework was developed in three phases: 1) climate data collection and processing; 2) Coastal Climate Impact Assessment (CCIA) model development; and 3) implementation and adaptation system selection. The climate data collection and processing phase involves determining the most significant climate change parameters and their indicators that affect coastal zone stability, extracting climatic data indicators from different climate database sources, and prioritizing the selected indicators. The indicators' weights were estimated using the Analytical Hierarchy Process (AHP) through a questionnaire survey shared with experts in climate change impacts. A CCIA model development phase involves the formulation of the proposed model using GIS technique to discover the vulnerable areas according to the most dominant impact. The implementation and adaptation system selection phase involves the application of the framework to Al-Alamein New City in Egypt. A sensitivity analysis was conducted to measure the behavior of several climate change parameters to identify the most critical parameter for climate change in Al-Alamein New City. The results showed that the geology of the region is the most crucial component influenced by climate change. It is capable of producing a very sensitive area in the coastal zone while also taking other factors into account. When creating new urban neighborhoods, the erosion of the shoreline is the least important factor to consider. This is because coastal deterioration is caused by both the influence of metrological data on the region and the impact of human activity. Shoreline deterioration will be reduced if climate conditions are maintained while limiting the impact of human activities. To adapt to the long-term effects of climate change on coastal zones, a combination of soft and hard protection systems should be considered.
C1 [Marzouk, Mohamed] Cairo Univ, Fac Engn, Struct Engn Dept, Giza, Egypt.
   [Azab, Shimaa] Inst Natl Planning INP, Environm Planning & Dev Ctr, Cairo, Egypt.
C3 Egyptian Knowledge Bank (EKB); Cairo University; Institute of National
   Planning
RP Marzouk, M (corresponding author), Cairo Univ, Fac Engn, Struct Engn Dept, Giza, Egypt.
EM mmarzouk@cu.edu.eg; shaymaa.azab@inp.edu.eg
RI Marzouk, Mohamed/AAA-2717-2021
FU Cairo University
FX No Statement Available
CR [Allard C. International Monetary Fund International Monetary Fund], 2017, Regional Economic Outlook: Sub-Saharan Africa Restarting the Growth Engine
   [Anonymous], 2019, NASA's open data portal: Prediction Of Worldwide Energy Resources (POWER NASA)
   [Anonymous], 1992, GLOBAL CLIMATE CHANG
   [Anonymous], 2019, Climate Data Online
   [Anonymous], 2017, WMO Guidelines on the Calculation of Climate Normals
   Arun PV, 2013, EGYPT J REMOTE SENS, V16, P133, DOI 10.1016/j.ejrs.2013.09.001
   Azab S., 2022, Assessment of climate changes impact on coastal vulnerability for feasibility of developing new communities
   Bagheri M, 2021, URBAN SCI, V5, DOI 10.3390/urbansci5040084
   Bagheri M, 2013, J COAST CONSERV, V17, P1, DOI 10.1007/s11852-012-0213-4
   Barton M., 2019, Encyclopedia of Earth Sciences Series, DOI [10.1007/978-3-319-93806-6_394, DOI 10.1007/978-3-319-93806-6_394]
   Baucic M, 2019, INT ARCH PHOTOGRAMM, V42-3, P59, DOI 10.5194/isprs-archives-XLII-3-W8-59-2019
   Beavers R.L., 2016, Coastal Adaptation Strategies Handbook
   Birgani RA, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14148494
   Lebbe TB, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.740602
   Boulomytis VTG, 2015, WORLD ENVIRONMENTAL AND WATER RESOURCES CONGRESS 2015: FLOODS, DROUGHTS, AND ECOSYSTEMS, P1248
   Cabana D, 2023, EARTHS FUTURE, V11, DOI 10.1029/2023EF003713
   Chabot W., 2014, Seawalls Kill Beach'
   Chauhan D, 2022, ENVIRON SCI POLLUT R, V29, P85904, DOI 10.1007/s11356-021-15713-5
   Childs C., 2004, ArcUser, P32
   CoastAdapt, 2017, Overview of the impacts on our coast
   Consultants A., 2015, Al-Alamein New City (ANC), conceptual design
   Cowen D. J., 1990, Introductory Readings in Geographic Information Systems, V1st, P70, DOI 10.1201/b12579-11/gis-versus-cad-versus-dbms-differences-david-cowen
   Cross C., 2016, The difference between soft and hard engineering'
   Culshaw MG, 2011, B ENG GEOL ENVIRON, V70, P333, DOI 10.1007/s10064-011-0377-4
   El-Masry EA, 2022, ENVIRON DEV SUSTAIN, V24, P1145, DOI 10.1007/s10668-021-01488-9
   El-Said M., 2020, Egypt to lose 1000 km of sandy coasts due to erosion
   El-Shahat S, 2021, ENVIRON DEV SUSTAIN, V23, P2827, DOI 10.1007/s10668-020-00639-8
   Figlus J., 2015, Int. Conf. Coastal. Eng, V1, P20, DOI DOI 10.9753/ICCE.V34.SEDIMENT.20
   French PW, 2004, GEOGR J, V170, P116, DOI 10.1111/j.0016-7398.2004.00113.x
   Gargiulo C, 2020, LAND USE POLICY, V91, DOI 10.1016/j.landusepol.2019.104413
   Goodman E., 2021, Benefits of Mangroves-Flood Protection'
   Haugen A, 2018, GEOSCIENCES, V8, DOI 10.3390/geosciences8100370
   Huang F, 2011, COMPUT GEOSCI-UK, V37, P426, DOI 10.1016/j.cageo.2010.05.024
   Hutchinson M. F., 1988, Proceedings of the Third International Symposium on Spatial Data Handling, P117
   Jiang HQ, 2021, ENVIRON SCI POLLUT R, V28, P39757, DOI 10.1007/s11356-021-13513-5
   Kaliraj S, 2015, ARAB J GEOSCI, V8, P239, DOI 10.1007/s12517-013-1216-7
   Kim Y, 2013, CLIMATIC CHANGE, V121, P301, DOI 10.1007/s10584-013-0879-0
   Li Jin, 2008, A Review of Spatial Interpolation Methods for Environmental Scientists'
   Li XG, 2009, PHOTOGRAMM ENG REM S, V75, P807, DOI 10.14358/PERS.75.7.807
   Luo SL, 2015, OCEAN COAST MANAGE, V103, P134, DOI 10.1016/j.ocecoaman.2014.08.008
   Maanan M, 2018, HUM ECOL RISK ASSESS, V24, P1642, DOI 10.1080/10807039.2017.1421452
   Marzouk M, 2021, J CLEAN PROD, V290, DOI 10.1016/j.jclepro.2020.125723
   Mcfadden L, 2007, COAST MANAGE, V35, P429, DOI 10.1080/08920750701525768
   McInnes R., 2006, Responding to the risks from climate change in coastal zones. A good practice guide. LIFE Environment project 'Response'-'Responding to the risks from climate change
   Murali RM, 2013, NAT HAZARD EARTH SYS, V13, P3291, DOI 10.5194/nhess-13-3291-2013
   National Authority for Remote Sensing & Space Sciences (NARSS), 1987, The Geological Map of Egypt, Scale 1:500,000
   Nelson S. A., 2018, Coastal Zones
   Pachauri R. K., 2014, Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P118
   Palacios-Abrantes J, 2022, SUSTAIN SCI, DOI 10.1007/s11625-022-01200-4
   Papari G, 2009, LECT NOTES COMPUT SC, V5702, P509, DOI 10.1007/978-3-642-03767-2_62
   Rahman B., 2018, Daily sun
   Rahmawan GA, 2022, GEOGR TECH, V17, P84, DOI 10.21163/GT_2022.172.08
   Rangel-Buitrago N, 2020, OCEAN COAST MANAGE, V189, DOI 10.1016/j.ocecoaman.2020.105134
   Reguero BG, 2018, J ENVIRON MANAGE, V210, P146, DOI 10.1016/j.jenvman.2018.01.024
   Roy P, 2023, J ENVIRON MANAGE, V330, DOI 10.1016/j.jenvman.2022.117187
   Saaty T.L., 1985, IEEE Transactions on, Systems, Man and Cybernetics, P450, DOI DOI 10.1109/TSMC.1985.6313384
   SAATY TL, 1977, J MATH PSYCHOL, V15, P234, DOI 10.1016/0022-2496(77)90033-5
   Sahoo B, 2018, J ENVIRON MANAGE, V206, P1166, DOI 10.1016/j.jenvman.2017.10.075
   Sanuy M, 2018, NAT HAZARD EARTH SYS, V18, P1825, DOI 10.5194/nhess-18-1825-2018
   Satta A., 2014, An Index-based method to assess vulnerabilities and risks of Mediterranean coastal zones to multiple hazards
   Sibson R., 1981, A Brief Description of Nearest Neighbor Interpolation. Interpolating Multivariate Data, V2, P21
   Stocker, 2014, CLIMATE CHANGE 2013
   Sutton-Grier AE, 2015, ENVIRON SCI POLICY, V51, P137, DOI 10.1016/j.envsci.2015.04.006
   Thirumurthy S, 2022, J ENVIRON MANAGE, V313, DOI 10.1016/j.jenvman.2022.114941
   Torresan S, 2008, SUSTAIN SCI, V3, P45, DOI 10.1007/s11625-008-0045-1
   VanZomeren C., 2019, A review of coastal vulnerability assessments: Definitions, components, and variables, DOI [10.21079/11681/33289, DOI 10.21079/11681/33289]
   Vieira LR, 2021, ISPRS INT J GEO-INF, V10, DOI 10.3390/ijgi10090598
   Watson R, 2001, CLIMATE CHANGE 2001: THE SCIENTIFIC BASIS, pIX
   Wei PB, 2021, DISCRETE DYN NAT SOC, V2021, DOI 10.1155/2021/5540452
   Woodruff S, 2018, COMPREHENSIVE GEOGRAPHIC INFORMATION SYSTEMS, VOL 2: GIS APPLICATIONS FOR ENVIRONMENT AND RESOURCES, P236
   Wunsch C, 1997, REV GEOPHYS, V35, P79, DOI 10.1029/96RG03037
   Yannis G, 2020, J TRAFFIC TRANSP ENG, V7, P413, DOI 10.1016/j.jtte.2020.05.005
NR 72
TC 0
Z9 0
U1 12
U2 25
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0167-6369
EI 1573-2959
J9 ENVIRON MONIT ASSESS
JI Environ. Monit. Assess.
PD FEB
PY 2024
VL 196
IS 2
AR 147
DI 10.1007/s10661-023-12287-2
PG 24
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EX4B6
UT WOS:001142207300002
PM 38221585
OA hybrid
DA 2025-01-10
ER

PT J
AU Li, ZW
   Liu, F
   Peng, XY
   Hu, BG
   Song, XD
AF Li, Zhenwang
   Liu, Feng
   Peng, Xiuyuan
   Hu, Bangguo
   Song, Xiaodong
TI Synergetic use of DEM derivatives, Sentinel-1 and Sentinel-2 data for
   mapping soil properties of a sloped cropland based on a two-step
   ensemble learning method
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Digital soil mapping; Optical Sentinel-2; Sentinel-1 SAR; Machine
   learning model; Two-step ensemble learning
ID ORGANIC-CARBON STOCKS; MATTER; UNCERTAINTY; PREDICTION; MOISTURE;
   TEXTURE; EXAMPLE; SCALE; INDEX
AB Understanding the spatial variability of soil organic matter (SOM), soil total nitrogen (STN), soil total phosphorus (STP), and soil total potassium (STK) is important to support site-specific agronomic management, food production, and climate change adaptation. High-resolution remote sensing imageries have emerged as an innovative solution to investigate the spatial variation in agricultural soils with machine learning (ML) algorithms. However, the predic-tive power of the individual and combined effects of Sentinel-1 (S1) synthetic aperture radar (SAR) and Sentinel-2 (S2) multispectral images for mapping soil properties, especially STN, STP, and STK, have rarely been investigated. Moreover, single ML model may achieve unstable performance for predicting multiple soil properties due to strong spatial heterogeneity. This study explored the combine use of S1, S2, and DEM derivatives to map SOM, STN, STP, and STK content of a sloped cropland of northeastern China. A two-step method with a weighted sum of four ML models was proposed to improve the accuracy and robustness in predicting multiple soil properties. Our results showed that single ML model has various performance in predicting the four soil properties. The optimal ML models could explain approximately 56 %, 53 %, 56 % and 37 % of the variability of SOM, STN, STP, and STK, respectively. Using the weights estimated through a 10-fold cross-validation procedure, the two-step ensemble learning model was retrained and showed more robust performance than the four ML models, in which the prediction accuracy was im-proved by 2.38 %, 1.40 %, 3.52 %, and 3.29 % for SOM, STN, STP, and STK, respectively. Our results also showed that the optical S2 derived features, especially the two S2 short-wave infrared bands, enhanced vegetation index, and soil adjusted vegetation index, were more important for soil property prediction than S1 data and DEM derivatives. Compared with individual sensor, a combination of S1 and S2 data yielded more accurate predictions of STN and STP but not for SOM and STK. The results of this study highlight the potential of high-resolution S1 and S2 data and the two-step method for soil property prediction at farmland scale.
C1 [Li, Zhenwang] Yangzhou Univ, Agr Coll, Jiangsu Key Lab Crop Genet & Physiol, Jiangsu Key Lab Crop Cultivat & Physiol, Yangzhou 225009, Peoples R China.
   [Liu, Feng; Song, Xiaodong] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.
   [Peng, Xiuyuan] Informat Res Inst, Liaoning Acad Agr Sci, Shenyang 110161, Peoples R China.
   [Hu, Bangguo] Beijing Deep Blue Space Remote Sensing Technol Co, Beijing 100101, Peoples R China.
C3 Yangzhou University; Chinese Academy of Sciences; Nanjing Institute of
   Soil Science, CAS; Liaoning Academy of Agricultural Sciences
RP Song, XD (corresponding author), Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.
EM xdsong@issas.ac.cn
FU Natural Science Foundation of Jiangsu Province [BK20220093]; National
   Natural Science Founda- tion of China [42271058]; International
   Partnership Program of Chinese Academy of Sciences [131323KYSB20210004];
   Liaoning Pro- vincial People's Livelihood Science and Technology Program
   Joint Project [2021030337-JH2/102]
FX Acknowledgements This study was jointly supported by the Natural Science
   Foundation of Jiangsu Province (No. BK20220093) , the National Natural
   Science Founda- tion of China (No. 42271058) , the International
   Partnership Program of Chinese Academy of Sciences (131323KYSB20210004)
   , and Liaoning Pro- vincial People's Livelihood Science and Technology
   Program Joint Project (2021030337-JH2/102) .
CR Arshad M, 2020, SOIL SCI SOC AM J, V84, P314, DOI 10.1002/saj2.20008
   Bakka H, 2018, WIRES COMPUT STAT, V10, DOI 10.1002/wics.1443
   Bargaoui YE, 2019, GEODERMA, V356, DOI 10.1016/j.geoderma.2019.113907
   BenDor E, 1997, REMOTE SENS ENVIRON, V61, P1, DOI 10.1016/S0034-4257(96)00120-4
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Brungard CW, 2010, PROGR SOIL SCI, V2, P67, DOI 10.1007/978-90-481-8863-5_6
   Castaldi F, 2019, ISPRS J PHOTOGRAMM, V147, P267, DOI 10.1016/j.isprsjprs.2018.11.026
   Castaldi F, 2016, REMOTE SENS ENVIRON, V179, P54, DOI 10.1016/j.rse.2016.03.025
   Chen SC, 2022, GEODERMA, V409, DOI 10.1016/j.geoderma.2021.115567
   Chen SC, 2019, SCI TOTAL ENVIRON, V655, P273, DOI 10.1016/j.scitotenv.2018.11.230
   dos Santos UJ, 2020, GEODERMA REG, V23, DOI 10.1016/j.geodrs.2020.e00333
   Elser JJ, 2000, NATURE, V408, P578, DOI 10.1038/35046058
   Escadafal R., 1989, Remote sensing of the earth's surface., P159, DOI 10.1016/0273-1177(89)90481-X
   Fang YQ, 2021, SCI TOTAL ENVIRON, V756, DOI 10.1016/j.scitotenv.2020.143841
   Fathololoumi S, 2020, SCI TOTAL ENVIRON, V721, DOI 10.1016/j.scitotenv.2020.137703
   Filipponi F., 2019, P 3 INT EL C REM SEN, P11, DOI [10.3390/ECRS-3-06201, DOI 10.3390/ECRS-3-06201]
   Ganaie MA, 2022, ENG APPL ARTIF INTEL, V115, DOI 10.1016/j.engappai.2022.105151
   Gelfand AE, 2012, SPAT STAT-NETH, V1, P30, DOI 10.1016/j.spasta.2012.02.005
   Grimm R, 2008, GEODERMA, V146, P102, DOI 10.1016/j.geoderma.2008.05.008
   Guo L, 2021, GEODERMA, V398, DOI 10.1016/j.geoderma.2021.115118
   Guo L, 2020, SOIL TILL RES, V196, DOI 10.1016/j.still.2019.104477
   Guo PT, 2015, GEODERMA, V237, P49, DOI 10.1016/j.geoderma.2014.08.009
   Heung B, 2016, GEODERMA, V265, P62, DOI 10.1016/j.geoderma.2015.11.014
   Hosseini M, 2017, INT J APPL EARTH OBS, V58, P50, DOI 10.1016/j.jag.2017.01.006
   Hu BF, 2022, CATENA, V217, DOI 10.1016/j.catena.2022.106468
   Huang JY, 2017, SCI TOTAL ENVIRON, V609, P621, DOI 10.1016/j.scitotenv.2017.07.201
   HUETE A R, 1988, Remote Sensing of Environment, V25, P295, DOI 10.1016/0034-4257(88)90106-X
   Huete AR, 1997, REMOTE SENS ENVIRON, V59, P440, DOI 10.1016/S0034-4257(96)00112-5
   Ju C, 2018, J APPL STAT, V45, P2800, DOI 10.1080/02664763.2018.1441383
   Kasischke ES, 1997, REMOTE SENS ENVIRON, V59, P141, DOI 10.1016/S0034-4257(96)00148-4
   Keaney A, 2013, SPAT STAT-NETH, V5, P3, DOI 10.1016/j.spasta.2013.05.003
   Keskin H, 2018, GEODERMA, V326, P22, DOI 10.1016/j.geoderma.2018.04.004
   Keskin H, 2019, GEODERMA, V339, P40, DOI 10.1016/j.geoderma.2018.12.037
   Kursa MB, 2010, J STAT SOFTW, V36, P1, DOI 10.18637/jss.v036.i11
   Li ZW, 2017, J INTEGR AGR, V16, P286, DOI [10.1016/s2095-3119(15)61303-x, 10.1016/S2095-3119(15)61303-X]
   Li ZW, 2022, SCI TOTAL ENVIRON, V815, DOI 10.1016/j.scitotenv.2021.152880
   Lindgren F, 2015, J STAT SOFTW, V63, P1, DOI 10.18637/jss.v063.i19
   Lindgren F, 2011, J ROY STAT SOC B, V73, P423, DOI 10.1111/j.1467-9868.2011.00777.x
   Liu F, 2012, GEODERMA, V171, P44, DOI 10.1016/j.geoderma.2011.05.007
   Lu MY, 2022, COMPUT ELECTRON AGR, V200, DOI 10.1016/j.compag.2022.107246
   Ma GL, 2021, REG SUSTAIN, V2, P177, DOI 10.1016/j.regsus.2021.06.001
   Mahmoudabadi E, 2017, ENVIRON MONIT ASSESS, V189, DOI 10.1007/s10661-017-6197-7
   Maleki MR, 2006, BIOSYST ENG, V95, P425, DOI 10.1016/j.biosystemseng.2006.07.015
   Mammadov E, 2021, GEODERMA REG, V26, DOI 10.1016/j.geodrs.2021.e00411
   Marchant BP, 2021, GEODERMA, V403, DOI 10.1016/j.geoderma.2021.115232
   Markham K, 2023, LANDSCAPE ECOL, V38, P619, DOI 10.1007/s10980-022-01449-1
   Martin MP, 2014, GEODERMA, V223, P97, DOI 10.1016/j.geoderma.2014.01.005
   Mathieu R, 1998, REMOTE SENS ENVIRON, V66, P17, DOI 10.1016/S0034-4257(98)00030-3
   McBratney AB, 2003, GEODERMA, V117, P3, DOI 10.1016/S0016-7061(03)00223-4
   Meersmans J, 2009, SOIL USE MANAGE, V25, P346, DOI 10.1111/j.1475-2743.2009.00242.x
   Minasny B, 2016, GEODERMA, V264, P301, DOI 10.1016/j.geoderma.2015.07.017
   Moraga P, 2021, SPAT SPATIO-TEMPORAL, V39, DOI 10.1016/j.sste.2021.100440
   Mponela P, 2020, APPL GEOGR, V124, DOI 10.1016/j.apgeog.2020.102299
   Mukherjee S, 2019, J OPT-INDIA, V48, P87, DOI 10.1007/s12596-019-00517-1
   Mulder VL, 2011, GEODERMA, V162, P1, DOI 10.1016/j.geoderma.2010.12.018
   Piikki K, 2021, SOIL USE MANAGE, V37, P7, DOI 10.1111/sum.12694
   Poggio L, 2016, GEODERMA, V277, P69, DOI 10.1016/j.geoderma.2016.04.026
   Poggio L, 2014, GEODERMA, V232, P284, DOI 10.1016/j.geoderma.2014.05.004
   Potdar RP, 2021, J PLANT NUTR, V44, P1826, DOI 10.1080/01904167.2021.1884702
   Quinlan J.R., 1993, MACHINE LEARNING P 1, DOI [DOI 10.1016/B978-1-55860-307-3.50037-X, 10.1016/b978-1-55860-307-3.50037-x]
   Roberts DR, 2017, ECOGRAPHY, V40, P913, DOI 10.1111/ecog.02881
   Rocha AD, 2019, REMOTE SENS ENVIRON, V231, DOI 10.1016/j.rse.2019.05.019
   Rue H, 2009, J ROY STAT SOC B, V71, P319, DOI 10.1111/j.1467-9868.2008.00700.x
   Shafizadeh-Moghadam H, 2022, CATENA, V212, DOI 10.1016/j.catena.2022.106077
   Song XD, 2016, J ARID LAND, V8, P734, DOI 10.1007/s40333-016-0049-0
   Stenberg B, 2010, ADV AGRON, V107, P163, DOI 10.1016/S0065-2113(10)07005-7
   Sun XL, 2021, GEODERMA, V384, DOI 10.1016/j.geoderma.2020.114808
   Thaler EA, 2019, SOIL SCI SOC AM J, V83, P1443, DOI 10.2136/sssaj2018.09.0318
   Nguyen TT, 2022, SCI TOTAL ENVIRON, V804, DOI 10.1016/j.scitotenv.2021.150187
   Tyralis H, 2021, NEURAL COMPUT APPL, V33, P3053, DOI 10.1007/s00521-020-05172-3
   van der Laan MJ, 2007, STAT APPL GENET MOL, V6, DOI 10.2202/1544-6115.1309
   van Donkelaar A, 2016, ENVIRON SCI TECHNOL, V50, P3762, DOI 10.1021/acs.est.5b05833
   Vaudour E, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14122917
   Wadoux AMJC, 2020, EARTH-SCI REV, V210, DOI 10.1016/j.earscirev.2020.103359
   Wang S, 2017, GEODERMA, V305, P250, DOI 10.1016/j.geoderma.2017.05.048
   Yang RM, 2019, ENVIRON MONIT ASSESS, V191, DOI 10.1007/s10661-019-7580-3
   Zhang SH, 2022, LAND DEGRAD DEV, V33, P2220, DOI 10.1002/ldr.4255
   Zhang YK, 2022, PEDOSPHERE, V32, P588, DOI 10.1016/S1002-0160(21)60055-3
   Zhang YK, 2021, EUR J SOIL SCI, V72, P1690, DOI 10.1111/ejss.13086
   Zhou T, 2020, SCI TOTAL ENVIRON, V729, DOI 10.1016/j.scitotenv.2020.138244
   Zízala D, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11242947
NR 81
TC 9
Z9 9
U1 24
U2 109
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0048-9697
EI 1879-1026
J9 SCI TOTAL ENVIRON
JI Sci. Total Environ.
PD MAR 25
PY 2023
VL 866
AR 161421
DI 10.1016/j.scitotenv.2023.161421
EA JAN 2023
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 8E6SU
UT WOS:000919101300001
PM 36621491
DA 2025-01-10
ER

PT J
AU Eriksen, SH
   Cramera, LK
   Vetrhus, I
   Thornton, P
AF Eriksen, Siri Hallstrom
   Cramera, Laura Katherine
   Vetrhus, Ingvild
   Thornton, Philip
TI Can Climate Interventions Open Up Space for Transformation? Examining
   the Case of Climate-Smart Agriculture (CSA) in Uganda
SO FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
LA English
DT Article
DE climate change adaptation; subjectivity; power relations; gender;
   Africa; climate-smart agriculture; worldviews
ID REDD PLUS; ADAPTATION; FRAMEWORK; DISCOURSES; AUTHORITY; POLICIES;
   SYSTEMS; POWER
AB In this paper, we investigate the ways in which climate change-related interventions such as climate-smart agriculture (CSA) may open up-or close down-spaces for transformation. We explore the interface between worldviews, power relations and policy interventions, focusing in particular on the way that asymmetric gender and expert-farmer relations may be reinforced or contested through climate-smart agricultural interventions. It has been argued that fundamental changes required in the face of climate change can only take place through transformation across the personal, practical and political spheres. In particular, it is in the interaction between these spheres where spaces for transformation lie; for example, in the contesting of subjectivities casting farmers as passive recipients of expert advice, in the assumptions regarding what constitutes "good development", and in how worldviews frame the way we see human-nature relations. Nevertheless, interventions like CSA are often focused mainly on changes to practices or technologies, rather than on how power relations or worldviews shape practices, food security and inequity. Through a case study of Hoima, Uganda, we examine the ways in which the implementation of climate-smart agriculture reinforces existing subjectivities and authority relations or opens up for new (and potentially more emancipatory) subjectivities. First, we describe food security and social inequality drawing on survey data from Hoima. Next, we examine how social actors such as farmers, project workers, local leaders, and government officials position particular farmers or practices as good/progressive or problematic/traditional. We then analyze how these subjectivities reflect authority relations, and the ways in which CSA reinforces or creates space for contesting these. We argue that a focus on commercial agriculture as "good" by many social actors also persists within CSA activities, and is intertwined with asymmetric gender and expert-farmer relations. Commercialization takes place within the need to increase agricultural production to feed growing urban populations. However, commercialization for the case of Uganda has also entailed state attempts to govern farmers through farmer associations, the institutional set-up through which CSA often works. A closer attention to these dynamics could potentially help create deeper transformational change through climate-smart agriculture and related climate change interventions.
C1 [Eriksen, Siri Hallstrom] Norwegian Univ Life Sci, Dept Publ Hlth Sci, As, Norway.
   [Eriksen, Siri Hallstrom; Vetrhus, Ingvild] Norwegian Univ Life Sci, Dept Int Environm & Dev Studies, As, Norway.
   [Cramera, Laura Katherine; Thornton, Philip] CGIAR Res Program Climate Change Agr & Food Secur, Nairobi, Kenya.
   [Cramera, Laura Katherine; Thornton, Philip] Int Livestock Res Inst, Sustainable Livestock Syst, Nairobi, Kenya.
C3 Norwegian University of Life Sciences; Norwegian University of Life
   Sciences; CGIAR; CGIAR; International Livestock Research Institute
   (ILRI)
RP Eriksen, SH (corresponding author), Norwegian Univ Life Sci, Dept Publ Hlth Sci, As, Norway.; Eriksen, SH (corresponding author), Norwegian Univ Life Sci, Dept Int Environm & Dev Studies, As, Norway.
EM ski.eriksen@nmbu.no
RI Thornton, Philip/AAB-8806-2020; Cramer, Laura/R-6499-2019
OI Thornton, Philip/0000-0002-1854-0182; Cramer, Laura/0000-0003-1559-3497
FU Department of International Environment and Development Studies; CGIAR
   Trust Fund
FX This work was supported by the Department of International Environment
   and Development Studies through an MSc thesis travel grant. The
   contributions of LC and PT were made through the CGIAR Research Program
   on Climate Change, Agriculture and Food Security (CCAFS), which is
   carried out with support from the CGIAR Trust Fund and through bilateral
   funding agreements. For details please visit
   https://ccafs.cgiar.org/donors.
CR Aboda C, 2021, J REFUG STUD, V34, P851, DOI 10.1093/jrs/fez066
   Acosta M., 2016, GENDER RESPONSIVE PO
   Acosta M, 2019, WOMEN STUD INT FORUM, V74, P9, DOI 10.1016/j.wsif.2019.02.010
   Adger WN, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P1, DOI 10.1017/CBO9780511596667.002
   [Anonymous], 2014, POLITICAL ECOLOGY CL
   [Anonymous], 2017, NAT POP HOUS CENS 20
   [Anonymous], 2010, CLIM SMART AGR POL P
   [Anonymous], 2018, The State of Food Security and Nutrition in the World: Building Climate Resilience for Food Security and Nutrition
   [Anonymous], 2013, AGR FOOD SECUR, DOI DOI 10.1186/2048-7010-2-12
   Arora-Jonsson S, 2011, GLOBAL ENVIRON CHANG, V21, P744, DOI 10.1016/j.gloenvcha.2011.01.005
   Arslan A, 2015, J AGR ECON, V66, P753, DOI 10.1111/1477-9552.12107
   Atteridge A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.500
   Benjaminsen G, 2018, GEOFORUM, V93, P48, DOI 10.1016/j.geoforum.2018.04.021
   Benjaminsen G, 2017, J EAST AFR STUD, V11, P506, DOI 10.1080/17531055.2017.1357103
   Benjaminsen G, 2014, FORUM DEV STUD, V41, P377, DOI 10.1080/08039410.2014.961953
   Blackburn S, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.549
   Bonilla-Findji O, 2017, East Africa climate-smart villages AR4D sites: 2016 inventory. 2017
   CIAT BFS/USAID, 2017, CSA COUNTR PROF AFR, P22
   Denton F., 2014, WORKING GROUP 2 CONT
   Eriksen S., 2015, CLIMATE CHANGE ADAPT, P1
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Forch W., 2014, Agric Food Secur, V31, P1, DOI DOI 10.1186/2048-7010-3-13
   Herrero M, 2010, SCIENCE, V327, P822, DOI 10.1126/science.1183725
   Hoima District Local Government, 2015, DISTR DEV PLAN 2015
   IPCC, 2019, Food Security. In: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security
   Karlsson L, 2018, J PEASANT STUD, V45, P150, DOI 10.1080/03066150.2017.1351433
   Lamanna Christine, 2017, CLIMATE SMART AGR, P385, DOI [10.1007/978-3-319-61194-5, DOI 10.1007/978-3-319-61194-5]
   Leichenko R., 2019, CLIMATE SOC TRANSFOR
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   MAAIF, 2016, AGR SECT STRAT PLAN
   Margiotta S., 2018, IMPROVING SMALLHOLDE
   Meadows D., 1999, LEVERAGE POINTS PLAC
   Merilä J, 2014, EVOL APPL, V7, P1, DOI 10.1111/eva.12137
   Mubiru DN., 2012, Summary of baseline household survey results: Hoima District, West Central Uganda
   Nagoda S, 2015, GLOBAL ENVIRON CHANG, V35, P570, DOI 10.1016/j.gloenvcha.2015.08.014
   Nightingale AJ, 2017, GEOFORUM, V84, P11, DOI 10.1016/j.geoforum.2017.05.011
   Nightingale AJ, 2013, DEV CHANGE, V44, P29, DOI 10.1111/dech.12004
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   O'Brien K., 2013, P TRANSFORMATION CHA, P16
   O'Brien K, 2018, CURR OPIN ENV SUST, V31, P153, DOI 10.1016/j.cosust.2018.04.010
   O'Brien K, 2012, PROG HUM GEOG, V36, P667, DOI 10.1177/0309132511425767
   O'Brien K, 2015, CONSTRUC KNOWLEDGE, V9, P27
   Ogwang T, 2019, LAND-BASEL, V8, DOI 10.3390/land8070109
   Olsson L, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P793
   Onyango L., 2012, VILLAGE BASELINE STU
   Osiru D. S. O., 2014, CLIMATE SMART AGR FI
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Patterson J, 2017, ENVIRON INNOV SOC TR, V24, P1, DOI 10.1016/j.eist.2016.09.001
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Pelling M., 2014, J EXTREME EVENTS, V01
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Quinney M., 2016, COMPANION DOCUMENT C
   Recha J., 2016, PROGR ACHIEVING HOUS
   Recha J. W., 2017, Tech. Rep.
   Ritzema RS, 2017, FOOD SECUR, V9, P115, DOI 10.1007/s12571-016-0638-y
   Sharma M., 2017, Radical Transformational Leadership: Strategic Action For Change agents
   Tanner T, 2011, IDS BULL-I DEV STUD, V42, P1, DOI 10.1111/j.1759-5436.2011.00217.x
   Thornton PK, 2018, GLOBAL ENVIRON CHANG, V52, P37, DOI 10.1016/j.gloenvcha.2018.06.003
   Thornton PK, 2018, AGR SYST, V167, P161, DOI 10.1016/j.agsy.2018.09.009
   Thornton PK, 2010, AGR SYST, V103, P73, DOI 10.1016/j.agsy.2009.09.003
   van Bers C, 2019, CURR OPIN ENV SUST, V39, P94, DOI 10.1016/j.cosust.2019.08.003
   Vermeulen SJ, 2018, FRONT SUSTAIN FOOD S, V2, DOI 10.3389/fsufs.2018.00065
   World Bank, 2016, FARMS CIT GOOD FORT
NR 63
TC 15
Z9 16
U1 1
U2 21
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2571-581X
J9 FRONT SUSTAIN FOOD S
JI Front. Sustain. Food Syst.
PD DEC 6
PY 2019
VL 3
AR 111
DI 10.3389/fsufs.2019.00111
PG 17
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA JU8AM
UT WOS:000501893000001
OA gold
DA 2025-01-10
ER

PT J
AU Zhang, SY
   Li, XY
   Ma, YJ
   Zhao, GQ
   Li, L
   Chen, J
   Jiang, ZY
   Huang, YM
AF Zhang, Si-Yi
   Li, Xiao-Yan
   Ma, Yu-Jun
   Zhao, Guo-Qin
   Li, Liu
   Chen, Ji
   Jiang, Zhi-Yun
   Huang, Yong-Mei
TI Interannual and seasonal variability in evapotranspiration and energy
   partitioning over the alpine riparian shrub <i>Myricaria</i>
   <i>squamosa</i> Desv. on Qinghai-Tibet Plateau
SO COLD REGIONS SCIENCE AND TECHNOLOGY
LA English
DT Article
DE Bowen ratio; Energy balance; Latent heat flux; Sensible heat flux;
   Freeze-thaw cycle; Qinghai Lake watershed
ID BOWEN-RATIO; SURFACE-ENERGY; WATER-BALANCE; PHRAGMITES-AUSTRALIS; MEADOW
   ECOSYSTEM; LAKE QINGHAI; BUDGET; HEAT; FLUX; EXCHANGE
AB The Qinghai-Tibet Plateau is a sensitive area of global climate changes, and riparian ecosystems are thought as "hotspots" for climate change adaptation, but little work has been conducted regarding the alpine riparian ecosystems on the Qinghai-Tibet Plateau. We measured evapotranspiration (ET) and surface energy fluxes over the riparian shrub Myricaria squamosa Desv., which is widely distributed on the Qinghai-Tibet Plateau but has not been studied until now. The results indicated that annual ET was 390 mm and 503 mm for the period of 2010 to 2011 and 2011 to 2012, respectively, which was higher than the amount of precipitation during the same period. Cumulative ET was lower than the cumulative reference evapotranspiration during the entire experimental period, whereas ET in August was higher than reference evapotranspiration. ET in the growing season occupied over 80% of annual ET with a maximum daily ET of 7.2 mm d(-1), and the ET in the non-growing season was quite low because of the frozen soil. In general, temperature and net radiation were the key variables controlling daily ET rates for M. squamosa. Annual sensible heat flux (H) consumed 60% of net radiation (R-n) and latent heat flux (LE) 40% during the three years of the study. LE occupied the main part of R-n from July to September. H was the highest in May and June, then sunk in the mid-growing season, and rebounded the other peak at late September and early October. Daily ground heat flux was positive from April to mid-September, and it was an important heat source of land surface in the winter and spring. This study highlighted that as an alpine riparian ecosystem in a semiarid region, ET and surface energy partitioning of the M. squamosa community are strongly affected by the freeze-thaw cycle, groundwater fluctuation, precipitation pulses and soil water content. We speculate that climate warming has a significant impact on ET process and surface energy partitioning of the M. squamosa community by influencing the freeze-thaw cycle and soil water content. (C) 2014 Elsevier B.V. All rights reserved.
C1 [Zhang, Si-Yi; Li, Xiao-Yan; Ma, Yu-Jun] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.
   [Zhang, Si-Yi; Li, Xiao-Yan; Ma, Yu-Jun; Zhao, Guo-Qin; Li, Liu; Jiang, Zhi-Yun; Huang, Yong-Mei] Beijing Normal Univ, Coll Resources Sci & Technol, Beijing 100875, Peoples R China.
   [Chen, Ji] Chinese Acad Sci, Inst Earth Environm, SKLLQG, Key Lab Aerosol Sci & Technol, Xian 710075, Peoples R China.
C3 Beijing Normal University; Beijing Normal University; Chinese Academy of
   Sciences; Institute of Earth Environment, CAS
RP Li, XY (corresponding author), Beijing Normal Univ, Coll Resources Sci & Technol, 19 Xinjiekouwai St, Beijing 100875, Peoples R China.
EM zdxzqyzsy@163.com; xyli@bnu.edu.cn; myj3648@163.com;
   zhaoguoqin2008@126.com; lhataki@163.com; chenji@ieecas.cn;
   fhzmjzy@mail.bnu.edu.cn; ymhuang@bnu.edu.cn
RI Li, Xiaoyan/K-8544-2012; Zhiyun, Jiang/ABF-3554-2021; Si-Yi,
   Zhang/ISS-2652-2023; Chen, Ji/A-6299-2018
OI Chen, Ji/0000-0001-7026-6312; Li, XiaoYan/0000-0002-7454-7821; zhang, si
   yi/0000-0003-1928-5766
FU National Science Foundation of China [NSFC 41130640, 41025001, 41390462,
   41321001]; Fundamental Research Funds for the Central Universities;
   PCSIRT [IRT1108]; State Key Laboratory of Earth Surface Processes and
   Resource Ecology
FX We would like to thank the editors and two anonymous reviewers for
   valuable and constructive comments. The study was financially supported
   by the National Science Foundation of China (NSFC 41130640, 41025001,
   41390462 and 41321001), the Fundamental Research Funds for the Central
   Universities, the PCSIRT (No. IRT1108), and projects from the State Key
   Laboratory of Earth Surface Processes and Resource Ecology.
CR Alfieri JG, 2007, J HYDROMETEOROL, V8, P207, DOI 10.1175/JHM569.1
   Alfieri JG, 2009, J APPL METEOROL CLIM, V48, P982, DOI 10.1175/2008JAMC1873.1
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   ANGUS DE, 1984, AGR WATER MANAGE, V8, P133, DOI 10.1016/0378-3774(84)90050-7
   Betts AK, 1999, J GEOPHYS RES-ATMOS, V104, P19293, DOI 10.1029/1999JD900056
   Bowen IS, 1926, PHYS REV, V27, P779, DOI 10.1103/PhysRev.27.779
   Burba GG, 1999, AGR FOREST METEOROL, V94, P31, DOI 10.1016/S0168-1923(99)00007-6
   Capon SJ, 2013, ECOSYSTEMS, V16, P359, DOI 10.1007/s10021-013-9656-1
   Catford JA, 2013, ECOSYSTEMS, V16, P382, DOI 10.1007/s10021-012-9566-7
   Cavanaugh ML, 2011, ECOHYDROLOGY, V4, P671, DOI 10.1002/eco.157
   Chen G.S., 2008, PROTECTION RESTORATI
   Cleverly JR, 2006, HYDROL PROCESS, V20, P3207, DOI 10.1002/hyp.6328
   Daamen CC, 1999, AGR FOREST METEOROL, V93, P171, DOI 10.1016/S0168-1923(98)00114-2
   Dahm CN, 2002, FRESHWATER BIOL, V47, P831, DOI 10.1046/j.1365-2427.2002.00917.x
   Dawson TE, 1996, TREE PHYSIOL, V16, P263
   de Vries D.A., 1963, PHYS PLANT ENV, P210
   Domingo F, 1999, AGR FOREST METEOROL, V95, P67, DOI 10.1016/S0168-1923(99)00031-3
   Drexler JZ, 2004, HYDROL PROCESS, V18, P2071, DOI 10.1002/hyp.1462
   Eugster W, 2000, GLOBAL CHANGE BIOL, V6, P84, DOI 10.1046/j.1365-2486.2000.06015.x
   FELDHAKE CM, 1986, AGR FOREST METEOROL, V37, P309, DOI 10.1016/0168-1923(86)90068-7
   Frank AB, 2003, AGRON J, V95, P1504, DOI 10.2134/agronj2003.1504
   Goodrich DC, 2000, AGR FOREST METEOROL, V105, P281, DOI 10.1016/S0168-1923(00)00197-0
   GREGORY SV, 1991, BIOSCIENCE, V41, P540, DOI 10.2307/1311607
   Gu S, 2005, AGR FOREST METEOROL, V129, P175, DOI 10.1016/j.agrformet.2004.12.002
   Gu S, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009173
   HEILMAN JL, 1989, AGR FOREST METEOROL, V44, P261, DOI 10.1016/0168-1923(89)90021-X
   Hu ZM, 2009, AGR FOREST METEOROL, V149, P1410, DOI 10.1016/j.agrformet.2009.03.014
   Johnson RK, 2006, HYDROBIOLOGIA, V566, P139, DOI 10.1007/s10750-006-0100-9
   Kang SC, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/015101
   Kar G, 2007, AGR FOREST METEOROL, V146, P94, DOI 10.1016/j.agrformet.2007.05.008
   Klein JA, 2004, ECOL LETT, V7, P1170, DOI 10.1111/j.1461-0248.2004.00677.x
   Lenters JD, 2011, J HYDROL, V408, P19, DOI 10.1016/j.jhydrol.2011.07.010
   Li J, 2013, J INTEGR AGR, V12, P1396, DOI 10.1016/S2095-3119(13)60546-8
   Li SG, 2007, J HYDROL, V333, P133, DOI 10.1016/j.jhydrol.2006.07.021
   Li SS, 2009, ENVIRON GEOL, V57, P389, DOI 10.1007/s00254-008-1308-y
   Li XY, 2009, LAND DEGRAD DEV, V20, P69, DOI 10.1002/ldr.885
   Li XY, 2007, WATER RESOUR MANAG, V21, P1505, DOI 10.1007/s11269-006-9096-1
   [刘帅 LIU Shuai], 2010, [生态学报, Acta Ecologica Sinica], V30, P557
   Ma WQ, 2006, ENVIRON GEOL, V50, P645, DOI 10.1007/s00254-006-0238-9
   Ma YM, 2003, PHYS CHEM EARTH, V28, P63, DOI 10.1016/S1474-7065(03)00008-1
   MALEK E, 1993, J HYDROL, V146, P209, DOI 10.1016/0022-1694(93)90276-F
   Mander U, 1997, ECOL ENG, V8, P299, DOI 10.1016/S0925-8574(97)00025-6
   Meehan W.R., 1977, Proceedings: Importance, preservation and management of riparian habitat: a symposium, P137
   Nilsson C, 2013, ECOSYSTEMS, V16, P401, DOI 10.1007/s10021-012-9622-3
   OHMURA A, 1982, J APPL METEOROL, V21, P595, DOI 10.1175/1520-0450(1982)021<0595:OCFRDF>2.0.CO;2
   Peacock CE, 2004, HYDROL PROCESS, V18, P247, DOI 10.1002/hyp.1373
   Perez PJ, 1999, AGR FOREST METEOROL, V97, P141, DOI 10.1016/S0168-1923(99)00080-5
   Pielke RA, 1998, GLOBAL CHANGE BIOL, V4, P461, DOI 10.1046/j.1365-2486.1998.t01-1-00176.x
   Prueger JH, 1997, AGRON J, V89, P730, DOI 10.2134/agronj1997.00021962008900050004x
   Qiu GY, 2011, J HYDROL, V411, P120, DOI 10.1016/j.jhydrol.2011.09.040
   Rohli RV, 2004, J GREAT LAKES RES, V30, P241, DOI 10.1016/S0380-1330(04)70342-1
   Savage MJ, 2009, J HYDROL, V376, P249, DOI 10.1016/j.jhydrol.2009.07.038
   Savage MJ, 2010, SENSORS-BASEL, V10, P7748, DOI 10.3390/s100807748
   Scott RL, 2008, J ARID ENVIRON, V72, P1232, DOI 10.1016/j.jaridenv.2008.01.001
   Serrat-Capdevila A, 2011, J HYDROL, V399, P1, DOI 10.1016/j.jhydrol.2010.12.021
   Si JH, 2005, ENVIRON GEOL, V48, P861, DOI 10.1007/s00254-005-0025-z
   Stannard DI, 2004, WETLANDS, V24, P498, DOI 10.1672/0277-5212(2004)024[0498:EOFEIB]2.0.CO;2
   Stannard DI, 1997, BOUND-LAY METEOROL, V83, P375, DOI 10.1023/A:1000286829849
   STAUDINGER M, 1981, NORD HYDROL, V12, P207
   Swanson F.J., 1982, ANAL CONIFEROUS FORE, P267
   Tanaka K, 2003, J HYDROL, V283, P169, DOI 10.1016/S0022-1694(03)00243-9
   Tanaka K, 2001, J METEOROL SOC JPN, V79, P505, DOI 10.2151/jmsj.79.505
   Tian FX, 2011, J ARID ENVIRON, V75, P648, DOI 10.1016/j.jaridenv.2011.02.001
   Todd RW, 2000, AGR FOREST METEOROL, V103, P335, DOI 10.1016/S0168-1923(00)00139-8
   Wang SS, 1996, SCI CHINA SER D, V39, P418
   Wang Z.Q., 2003, ESTIMATION HYDRAULIC
   Williams DG, 2006, HYDROL PROCESS, V20, P3191, DOI 10.1002/hyp.6327
   Wu TH, 2013, INT J CLIMATOL, V33, P920, DOI 10.1002/joc.3479
   Xing ZS, 2008, SENSORS-BASEL, V8, P412, DOI 10.3390/s8010412
   [杨梅学 Yang Meixue], 2002, [山地学报, Journal of Mountain Science], V20, P553
   [阳勇 Yang Yong], 2011, [地球科学进展, Advance in Earth Sciences], V26, P711
   Yao JM, 2008, COLD REG SCI TECHNOL, V52, P326, DOI 10.1016/j.coldregions.2007.04.001
   Yi W., 2011, EVALUATION CARRYING
   Yoshida M, 2010, J HYDROL, V395, P180, DOI 10.1016/j.jhydrol.2010.10.023
   You QL, 2010, GLOBAL PLANET CHANGE, V72, P11, DOI 10.1016/j.gloplacha.2010.04.003
   Zhang BZ, 2008, AGR FOREST METEOROL, V148, P1629, DOI 10.1016/j.agrformet.2008.05.016
   Zhang GQ, 2011, J APPL REMOTE SENS, V5, DOI 10.1117/1.3601363
   Zhang K, 2011, HYDROL PROCESS, V25, P4142, DOI 10.1002/hyp.8350
   Zhang X., 2005, FRESHW FISH, V35, P57
   [张镱锂 Zhang Yili], 2002, [地理研究, Geographical Research], V21, P1
   Zhang YS, 2003, J HYDROL, V283, P41, DOI 10.1016/S0022-1694(03)00240-3
   Zhao Guo-Qin, 2013, Chinese Journal of Plant Ecology, V37, P1091, DOI 10.3724/SP.J.1258.2013.00112
   Zhao SQ, 2009, BIOGEOSCIENCES, V6, P1647, DOI 10.5194/bg-6-1647-2009
   [周剑 ZHOU Jian], 2008, [冰川冻土, Journal of Glaciology and Geocryology], V30, P398
NR 84
TC 29
Z9 35
U1 3
U2 115
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0165-232X
EI 1872-7441
J9 COLD REG SCI TECHNOL
JI Cold Reg. Sci. Tech.
PD JUN
PY 2014
VL 102
BP 8
EP 20
DI 10.1016/j.coldregions.2014.02.001
PG 13
WC Engineering, Environmental; Engineering, Civil; Geosciences,
   Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology
GA AG2VF
UT WOS:000335274500002
DA 2025-01-10
ER

PT J
AU Kuster, EL
   Hesed, CDM
AF Kuster, Emma L.
   Hesed, Christine D. Miller
TI Designing and delivering climate training for natural resource managers:
   Increasing climate literacy and action through education and engagement
SO CONSERVATION SCIENCE AND PRACTICE
LA English
DT Article
DE actionable science; climate literacy; grassland conservation; natural
   resource management
AB Responding to climate impacts and expanding adaptation efforts necessitates getting the right knowledge and tools in the hands of land managers and decision-makers. In 2022-2023, several regional US Geological Survey Climate Adaptation Science Centers partnered with the US Fish and Wildlife Service (FWS) Science Applications Program on the first targeted climate training series designed for the FWS Grassland Ecosystem Team. This training spanned multiple months and formats with self-paced virtual lessons, webinars, and an in-person workshop. As the FWS Grassland Ecosystem Team is tasked with conservation planning for grassland birds and other species, the focus of the workshop was an interactive collaborative activity incorporating species adaptive capacity assessments, future climate projections, and adaptation menus into the decision-making process. Herein, we describe the methods used to design and deliver the training series, as well as lessons learned for future climate literacy programs aimed at natural resource managers.
   Responding to climate impacts and expanding adaptation efforts necessitates getting the right knowledge and tools in the hands of land managers and decision makers. In 2022-2023, several regional US Geological Survey Climate Adaptation Science Centers partnered with the US Fish and Wildlife Service Science Applications Program on the first targeted climate training series designed for the FWS Grassland Ecosystem Team. Herein, we describe the methods used to design and deliver the training series, as well as lessons learned for future climate literacy programs aimed at natural resource managers. image
C1 [Kuster, Emma L.] Univ Oklahoma, South Cent Climate Adaptat Sci Ctr, 201 Stephenson Pkwy,Suite 2100, Norman, OK 73019 USA.
   [Hesed, Christine D. Miller] Univ Colorado Boulder, Cooperat Inst Res Environm Sci, North Cent Climate Adaptat Sci Ctr, Boulder, CO USA.
   201 Stephenson Pkwy,Suite 2100, Norman, OK 73019 USA.
C3 University of Oklahoma System; University of Oklahoma - Norman;
   University of Colorado System; University of Colorado Boulder
RP Kuster, EL (corresponding author), Univ Oklahoma, South Cent Climate Adaptat Sci Ctr, 201 Stephenson Pkwy,Suite 2100, Norman, OK 73019 USA.
EM emmakuster@ou.edu
RI Miller Hesed, Christine/HCH-2956-2022
OI Kuster, Emma/0009-0002-1070-4290
FU North Central Climate Adaptation Science Center
FX The authors gratefully acknowledge Sean Finn, Elise Elliot-Smith, John
   Carlson, Steve Kettler, Michael Disney, Jessica Dowler, and Kathryn
   Nuessly for their role in designing and implementing the training
   series; and Imtiaz Rangwala, David Wood, Toni Klemm, Jennifer Koch, Amy
   Symstad, Shelley Crausbay, Benjamin Zuckerberg, Christine Ribic, Jacy
   Bernath-Plaisted, Katherine Hegewisch, Lindsey Thurman, Courtney
   Peterson, and Gregor Schuurman for providing content for the training
   series.
CR Anderson A., 2012, Journal of Education for Sustainable Development, V6, P191, DOI [10.1177/0973408212475199, DOI 10.1177/0973408212475199]
   Arndt DS, 2008, PHYS GEOGR, V29, P487, DOI 10.2747/0272-3646.29.6.487
   Bamzai-Dodson A, 2021, WEATHER CLIM SOC, V13, P1027, DOI 10.1175/WCAS-D-21-0046.1
   Creutzig F, 2020, ENERGY RES SOC SCI, V70, DOI 10.1016/j.erss.2020.101779
   Crimmins A.R., 2023, 5 NATL CLIMATE ASSES, DOI [10.7930/NCA5.2023, DOI 10.7930/NCA5.2023]
   DeCrappeo NM, 2018, ENVIRON MANAGE, V61, P181, DOI 10.1007/s00267-017-0960-y
   Gerlak AK, 2023, WORLD DEV, V170, DOI 10.1016/j.worlddev.2023.106336
   Halofsky JE, 2011, J FOREST, V109, P219
   Hesed CDM, 2023, CONSERV SCI PRACT, V5, DOI 10.1111/csp2.12998
   Hess DJ, 2018, J CLEAN PROD, V170, P1451, DOI 10.1016/j.jclepro.2017.09.215
   IPCC, 2023, Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [DOI 10.59327/IPCC/AR6-9789291691647, 10.59327/IPCC/AR6-9789291691647.001]
   Kemp KB, 2015, ECOL SOC, V20, DOI 10.5751/ES-07522-200217
   Kuster EL, 2017, CLIMATIC CHANGE, V141, P613, DOI 10.1007/s10584-017-1918-z
   LeDee OE, 2011, WILDLIFE SOC B, V35, P508, DOI 10.1002/wsb.62
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Miller Hesed C. D., 2023, GRASSLAND MANAGEMENT
   Miller Hesed C. D., 2023, SYNTHESIS CLIMATE EC
   Moser SusanneC., 2017, Rising to the Challenge, Together
   Nelson SM, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14031804
   Schuurman G., 2020, RESISTACCEPTDIRECT R, DOI [10.36967/nrr-2283597, DOI 10.36967/NRR-2283597]
   Sheehan K.B., 2001, J COMPUT-MEDIAT COMM, V6
   Smidt A, 2009, J INTELLECT DEV DIS, V34, P266, DOI 10.1080/13668250903093125
   Thurman L., 2019, EVALUATING SPECIESAD
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
NR 24
TC 0
Z9 0
U1 3
U2 3
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
EI 2578-4854
J9 CONSERV SCI PRACT
JI Conserv. Sci. Pract.
PD OCT
PY 2024
VL 6
IS 10
DI 10.1111/csp2.13226
EA SEP 2024
PG 10
WC Biodiversity Conservation
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation
GA I5A3Y
UT WOS:001308235200001
OA gold
DA 2025-01-10
ER

PT J
AU Broadbent, AM
   Krayenhoff, ES
   Georgescu, M
AF Broadbent, Ashley Mark
   Krayenhoff, Eric Scott
   Georgescu, Matei
TI The motley drivers of heat and cold exposure in 21st century US cities
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE heat exposure; cold exposure; climate change; climate adaptation; urban
   climate
ID POPULATION EXPOSURE; EXCESS MORTALITY; URBAN EXPANSION; CLIMATE-CHANGE;
   IMPACTS; ADAPTATION; PROJECTIONS; HEALTH; MODEL; WAVES
AB We use a suite of decadal-length regional climate simulations to quantify potential changes in population-weighted heat and cold exposure in 47 US metropolitan regions during the 21st century. Our results show that population-weighted exposure to locally defined extreme heat (i.e., "population heat exposure") would increase by a factor of 12.7-29.5 under a high-intensity greenhouse gas (GHG) emissions and urban development pathway. Additionally, end-of-century population cold exposure is projected to rise by a factor of 1.3-2.2, relative to start-of-century population cold exposure. We identify specific metropolitan regions in which population heat exposure would increase most markedly and characterize the relative significance of various drivers responsible for this increase. The largest absolute changes in population heat exposure during the 21st century are projected to occur in major US metropolitan regions like New York City (NY), Los Angeles (CA), Atlanta (GA), and Washington DC. The largest relative changes in population heat exposure (i.e., changes relative to start-of-century) are projected to occur in rapidly growing cities across the US Sunbelt, for example Orlando (FL), Austin (TX), Miami (FL), and Atlanta. The surge in population heat exposure across the Sunbelt is driven by concurrent GHG-induced warming and population growth which, in tandem, could strongly compound population heat exposure. Our simulations provide initial guidance to inform the prioritization of urban climate adaptation measures and policy.
C1 [Broadbent, Ashley Mark; Georgescu, Matei] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85281 USA.
   [Broadbent, Ashley Mark; Krayenhoff, Eric Scott; Georgescu, Matei] Arizona State Univ, Urban Climate Res Ctr, Tempe, AZ 85281 USA.
   [Krayenhoff, Eric Scott] Univ Guelph, Sch Environm Sci, Guelph, ON N1G 2W1, Canada.
   [Georgescu, Matei] Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85281 USA.
C3 Arizona State University; Arizona State University-Tempe; Arizona State
   University; Arizona State University-Tempe; University of Guelph;
   Arizona State University; Arizona State University-Tempe
RP Broadbent, AM; Georgescu, M (corresponding author), Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85281 USA.; Broadbent, AM; Georgescu, M (corresponding author), Arizona State Univ, Urban Climate Res Ctr, Tempe, AZ 85281 USA.; Georgescu, M (corresponding author), Arizona State Univ, Global Inst Sustainabil, Tempe, AZ 85281 USA.
EM ashley.broadbent@asu.edu; Matei.Georgescu@asu.edu
RI Georgescu, Matei/G-5442-2011
OI Krayenhoff, Eric Scott/0000-0002-4776-4353; Broadbent,
   Ashley/0000-0003-1906-8112
FU NSF Sustainability Research Network [1444758]; Urban Water Innovation
   Network; NSF [SES-1520803]
FX This work was supported by NSF Sustainability Research Network
   Cooperative Agreement 1444758, the Urban Water Innovation Network, and
   NSF Grant SES-1520803. We acknowledge support from Research Computing at
   Arizona State University for the provision of high-performance
   supercomputing services. Additionally, we thank the three anonymous
   referees for helpful and constructive comments.
CR Anderson BG, 2009, EPIDEMIOLOGY, V20, P205, DOI 10.1097/EDE.0b013e318190ee08
   Arbuthnott K., 2016, ENV HEAL, V15, P74
   Bierwagen BG, 2010, P NATL ACAD SCI USA, V107, P20887, DOI 10.1073/pnas.1002096107
   Broadbent AM, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab6a23
   Dunne JP, 2012, J CLIMATE, V25, P6646, DOI 10.1175/JCLI-D-11-00560.1
   Ebi KL, 2008, AM J PREV MED, V35, P501, DOI 10.1016/j.amepre.2008.08.018
   European Centre for Medium-Range Weather Forecasts ERA-Interim Project, 2009, LABORATORY RESEARCH
   Fouillet A, 2006, INT ARCH OCC ENV HEA, V80, P16, DOI 10.1007/s00420-006-0089-4
   Gasparrini A, 2017, LANCET PLANET HEALTH, V1, pE360, DOI 10.1016/S2542-5196(17)30156-0
   Georgescu M, 2013, NAT CLIM CHANGE, V3, P37, DOI 10.1038/nclimate1656
   Georgescu M, 2014, P NATL ACAD SCI USA, V111, P2909, DOI 10.1073/pnas.1322280111
   Huang KN, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4b71
   Jones B, 2018, CLIMATIC CHANGE, V146, P423, DOI 10.1007/s10584-017-2133-7
   Jones B, 2015, NAT CLIM CHANGE, V5, P652, DOI [10.1038/nclimate2631, 10.1038/NCLIMATE2631]
   Karner A, 2015, J TRANSP HEALTH, V2, P451, DOI 10.1016/j.jth.2015.10.001
   Krayenhoff E. S., ASU WRF CLIMATE DATA
   Krayenhoff ES, 2018, NAT CLIM CHANGE, V8, P1097, DOI 10.1038/s41558-018-0320-9
   Kusaka H, 2001, BOUND-LAY METEOROL, V101, P329, DOI 10.1023/A:1019207923078
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Middel A, 2019, SCI TOTAL ENVIRON, V687, P137, DOI 10.1016/j.scitotenv.2019.06.085
   Myers SS, 2017, LANCET, V390, P2860, DOI 10.1016/S0140-6736(17)32846-5
   Nagendra H, 2018, NAT SUSTAIN, V1, P341, DOI 10.1038/s41893-018-0101-5
   Oleson KW, 2018, CLIMATIC CHANGE, V146, P377, DOI 10.1007/s10584-015-1504-1
   Palecki MA, 2001, B AM METEOROL SOC, V82, P1353, DOI 10.1175/1520-0477(2001)082<1353:TNAIOT>2.3.CO;2
   Scott AA, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabd6c
   Seto KC, 2012, P NATL ACAD SCI USA, V109, P16083, DOI 10.1073/pnas.1211658109
   Skamarock WC, 2008, J COMPUT PHYS, V227, P3465, DOI 10.1016/j.jcp.2007.01.037
   STEIN U, 1993, J ATMOS SCI, V50, P2107, DOI 10.1175/1520-0469(1993)050<2107:FSINS>2.0.CO;2
   *US ENV PROT AG, 2010, ICLUS TOOLS AND DATA
   Whitman S, 1997, AM J PUBLIC HEALTH, V87, P1515, DOI 10.2105/AJPH.87.9.1515
   Wobus C, 2018, EARTHS FUTURE, V6, P1323, DOI 10.1029/2018EF000943
   Wu JG, 2014, LANDSCAPE URBAN PLAN, V125, P209, DOI 10.1016/j.landurbplan.2014.01.018
   Wuebbles D. J., 2017, Climate science special report: Fourth national climate assessment, VI
   Ye XF, 2012, ENVIRON HEALTH PERSP, V120, P19, DOI [10.1289/ehp.1003198, 10.1289/ehp.120-a19]
   Zobel Z, 2017, EARTHS FUTURE, V5, P1234, DOI 10.1002/2017EF000642
NR 35
TC 52
Z9 54
U1 14
U2 42
PU NATL ACAD SCIENCES
PI WASHINGTON
PA 2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA
SN 0027-8424
J9 P NATL ACAD SCI USA
JI Proc. Natl. Acad. Sci. U. S. A.
PD SEP 1
PY 2020
VL 117
IS 35
BP 21108
EP 21117
DI 10.1073/pnas.2005492117
PG 10
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA NS6CI
UT WOS:000572346700026
PM 32817528
OA Green Published, Bronze
DA 2025-01-10
ER

PT C
AU Stocker, L
   Kennedy, D
   Metcalf, S
   Dambacher, JM
   Middle, G
   Wood, D
AF Stocker, Laura
   Kennedy, Deborah
   Metcalf, Sarah
   Dambacher, Jeffrey M.
   Middle, Garry
   Wood, David
BE Chan, F
   Marinova, D
   Anderssen, RS
TI Modelling coastal planning in southwest Western Australia: complexity,
   collaboration and climate adaptation
SO 19TH INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2011)
LA English
DT Proceedings Paper
CT 19th International Congress on Modelling and Simulation (MODSIM)
CY DEC 12-16, 2011
CL Perth, AUSTRALIA
SP CSIRO, Australian Govt, Bur Meteorol, Per Convent & Exhibit Ctr, Perth Convent Bur, Curtin Univ, Australian Math Soc (Aust MS), Australian & New Zealand Ind & Appl Math (ANZIAM), Australian Math Sci Inst (AMSI), Maralte Publishers, Econ Soc Australian (ESA), HEMA Consulting, Simulat Australia, Stat Soc Australia Inc (SSAI), Modelling & Simulat Soc Australia & New Zealand Inc (MSSANZ), Int Assoc Math & Comp Simulat (IMACS)
DE coastal governance; climate adaptation; qualitative modelling; social
   ecological systems; action research
ID SYSTEMS; GOVERNANCE; ECOSYSTEMS
AB This action-research project investigates the extent to which current coastal planning arrangements can respond to climate change impacts such as coastal erosion and recession in the southwest of Western Australia. The complex social ecological system that comprises coastal planning in the region was modelled in a collaborative process. This took the form of a major action research workshop followed by further small workshops and interviews with key actors. The modelling process has implications for coastal planning as it shows that despite recent changes to coastal planning policy there are still significant areas of liability resulting from climate change that are not yet accounted for by governance. More generally, private and public coastal developments in WA are in a phase of rapid growth, with observable degradation of the coastal environment. Within the context of the model system, this implies that the positive feedback subsystems are strongly driving the system, and current levels of response to public liability and environmental advocacy are relatively weak and inadequate to achieve sustainable coastal management. For this system to be stable requires that negative system feedback be stronger than positive feedback. Future modelling efforts will investigate potential interventions and restructuring of governance system to achieve goals of sustainable development. Thus far, the main use of the model has been as a heuristic device to discuss the coastal planning system with key informants, and to identify constraints and opportunities to coastal adaptation through the planning system.
C1 [Stocker, Laura; Kennedy, Deborah; Wood, David] Curtin Univ Technol, Sustainabil Policy Inst, Perth, WA 6845, Australia.
C3 Curtin University
RP Stocker, L (corresponding author), Curtin Univ Technol, Sustainabil Policy Inst, Perth, WA 6845, Australia.
EM L.Stocker@curtin.edu.au
CR Anderies J.M., 2008, Complexity Theory for a Sustainable Future, P155
   [Anonymous], RISING SEA
   [Anonymous], 1998, Linking social and ecological systems: Management practices and social mechanisms for building resilience
   Bicknell C., 2010, SEA LEVEL CHANGE W A
   Church JA, 2006, AUST METEOROL MAG, V55, P253
   COSTANZA R, 1993, BIOSCIENCE, V43, P545, DOI 10.2307/1311949
   Dambacher JM, 2007, ENVIRON SCI TECHNOL, V41, P555, DOI 10.1021/es0610333
   Dambacher JM, 2003, AM NAT, V161, P876, DOI 10.1086/367590
   Dambacher JM, 2003, ECOL MODEL, V161, P79, DOI 10.1016/S0304-3800(02)00295-8
   Duit A, 2008, GOVERNANCE, V21, P311, DOI 10.1111/j.1468-0491.2008.00402.x
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   LEVINS R, 1974, ANN NY ACAD SCI, V231, P123, DOI 10.1111/j.1749-6632.1974.tb20562.x
   Miller JH, 2007, PRINC STUD COMPLEX, P1, DOI 10.1007/1-4020-5602-8_1
   Norberg J., 2008, Complexity theory for a sustainable future
   Pattiaratchi C., 2009, CHANGING CLIMATE W A, P22
   Stocker L, 2010, CLIM CHANG MANAG, P31, DOI 10.1007/978-3-642-10751-1_3
   Wood D., 2009, The International Journal of Science in Society, V1, P137
NR 17
TC 1
Z9 1
U1 0
U2 6
PU MODELLING & SIMULATION SOC AUSTRALIA & NEW ZEALAND INC
PI CHRISTCHURCH
PA MSSANZ, CHRISTCHURCH, 00000, NEW ZEALAND
BN 978-0-9872143-1-7
PY 2011
BP 2996
EP 3002
PG 7
WC Computer Science, Interdisciplinary Applications; Operations Research &
   Management Science; Mathematics, Applied
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science; Operations Research & Management Science; Mathematics
GA BDU79
UT WOS:000314989302139
DA 2025-01-10
ER

PT J
AU Ziro, JS
   Kichamu-Wachira, E
   Ross, H
   Palaniappan, G
AF Ziro, John Safari
   Kichamu-Wachira, Edith
   Ross, Helen
   Palaniappan, Gomathy
TI Adoption of climate resilient agricultural practices among the Giriama
   community in South East Kenya: implications for conceptual frameworks
SO FRONTIERS IN CLIMATE
LA English
DT Article
DE climate change; adaptation; gender; culture; vulnerability; qualitative;
   conceptual framework
ID SMALLHOLDER FARMERS; CHANGE ADAPTATION; STRATEGIES; PERCEPTIONS;
   SYSTEMS; PRIORITIZATION; DETERMINANTS; VARIABILITY; TECHNOLOGY;
   EXTENSION
AB While quantitative studies are robust at assessing the extent of climate change adaptation, and statistical relationships among variables involved, qualitative studies are also essential to understand the social rationales underlying relationships among variables, and to identify the roles of variables that have been overlooked or are hard to measure. This study investigates factors that influence the adoption of climate resilient agricultural practices by resource-poor Giriama farmers in southeast Kenya, with a view to understanding why some smallholders from this cultural group adopt climate resilient practices, while others do not. Data was collected through in-depth interviews with 30 farmers, 15 of whom had adopted climate resilient farming practices recommended by agricultural experts, and 15 of whom had not adopted any of those practices. The adopters were market-oriented, and tended to have individual land tenure, higher levels of experience in farming, slightly larger farm sizes, middle to high school education levels, and be younger. They had access to agricultural extension, access to farm inputs, and their off-farm activities tended to be related to agricultural supply chains. Non-adopters farmed entirely for subsistence, on communal or leased land, had less formal education, and adhered strongly to cultural beliefs and practices. Their off-farm income was unrelated to agriculture. More of the adopters were males, while many of the non-adopters were female. Particular cultural practices and taboos inhibited the adoption of several of the climate resilient practices, such as planting hybrid maize, keeping dairy goats, using improved goats such as the Kenyan Alpine for breeding purposes and the use of water conservation structures for crop production. Further, the qualitative information explains how and why factors such as land ownership, gender, culture, and access to information are interrelated, in ways that are not necessarily obvious in statistical analysis. The study thus highlights issues that need to be considered in conceptual frameworks underpinning both quantitative and qualitative studies, and particularly how they interact, in order to provide the knowledge essential to policy and programs intended to enhance smallholder farmers' adaptive capacity.
C1 [Ziro, John Safari; Kichamu-Wachira, Edith; Ross, Helen; Palaniappan, Gomathy] Univ Queensland, Sch Agr & Food Sci, Brisbane, Qld, Australia.
   [Ziro, John Safari] Minist Agr Livestock Fisheries & Cooperat, Dept Crop Dev & Agr Res, Nairobi, Kenya.
   [Kichamu-Wachira, Edith] Griffith Univ, Ctr Planetary Hlth & Food Secur, Brisbane, Qld, Australia.
C3 University of Queensland; Griffith University
RP Ross, H (corresponding author), Univ Queensland, Sch Agr & Food Sci, Brisbane, Qld, Australia.
EM Helen.Ross@uq.edu.au
RI Ross, Helen/B-9585-2014
OI Palaniappan, Gomathy/0000-0002-3213-4666
FU Australia Awards [ST000EE07, ST000ED81]; The University of Queensland
FX This study was funded by the JZ and EK-W's scholarship from Australia
   Awards (Grant Nos. ST000EE07 and ST000ED81 respectively) and The
   University of Queensland.
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Amadu FO, 2020, WORLD DEV, V126, DOI 10.1016/j.worlddev.2019.104692
   Anita W., 2010, Climate change and agriculture impacts, adaptation and Mitigation: Impacts, adaptation and Mitigation
   [Anonymous], 2010, International Journal of Environmental, Cultural, Economic and Social Sustainability, DOI [DOI 10.18848/1832-2077/CGP/V06I05/54835, 10.18848/1832-2077/CGP/v06i05/54835]
   Antwi-Agyei P, 2021, REG SUSTAIN, V2, P375, DOI 10.1016/j.regsus.2022.01.005
   Asfaw A, 2004, AGR ECON-BLACKWELL, V30, P215, DOI [10.1016/j.agecon.2002.12.002, 10.1111/j.1574-0862.2004.tb00190.x]
   Asfaw A, 2019, ENVIRON DEV SUSTAIN, V21, P2535, DOI 10.1007/s10668-018-0150-y
   Awiti AO, 2022, FRONT CLIM, V4, DOI 10.3389/fclim.2022.895950
   Ayugi B, 2022, NAT HAZARDS, V113, P1151, DOI 10.1007/s11069-022-05341-8
   Brown B, 2018, GLOB FOOD SECUR-AGR, V17, P213, DOI 10.1016/j.gfs.2017.10.002
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Bryant CR, 2000, CLIMATIC CHANGE, V45, P181, DOI 10.1023/A:1005653320241
   Chiang F, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22314-w
   Cobon DH, 2009, RANGELAND J, V31, P31, DOI 10.1071/RJ08069
   Cooper PJM, 2008, AGR ECOSYST ENVIRON, V126, P24, DOI 10.1016/j.agee.2008.01.007
   Creswell J. W., 2018, Research design: qualitative, quantitative, and mixed methods approaches
   Debonne N, 2021, AGR SYST, V186, DOI 10.1016/j.agsy.2020.102943
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Etim N.-A., 2020, J LIFESCI, V1, P20, DOI [10.37899/journallalifesci.v1i4.203, DOI 10.37899/JOURNALLALIFESCI.V1I4.203]
   Gebrehiwot T, 2013, ENVIRON MANAGE, V52, P29, DOI 10.1007/s00267-013-0039-3
   Gikunda R., 2022, Advancements in Agricultural Development, V3, DOI DOI 10.37433/AAD.V3I2.203
   Hair J.F., 2009, Research Methods for Business
   Intergovernmental Panel on Climate Change, 2014, WORK GROUP 2 CONTR I
   Kamau JW, 2013, INT J CLIM CHANG STR, V5, P152, DOI 10.1108/17568691311327569
   Khatri-Chhetri A, 2017, AGR SYST, V151, P184, DOI 10.1016/j.agsy.2016.10.005
   Kichamu E. A., 2018, Environment, Development and Sustainability, V20, P2663, DOI 10.1007/s10668-017-0010-1
   Kim SA, 2008, AUST J AGR RESOUR EC, V52, P235, DOI 10.1111/j.1467-8489.2007.00434.x
   Kiptot E, 2019, INT J AGR SUSTAIN, V17, P401, DOI 10.1080/14735903.2019.1679576
   Kuehne G, 2017, AGR SYST, V156, P115, DOI 10.1016/j.agsy.2017.06.007
   Kumasi TC, 2019, ENVIRON DEV SUSTAIN, V21, P745, DOI 10.1007/s10668-017-0062-2
   Kurgat BK, 2020, FRONT SUSTAIN FOOD S, V4, DOI 10.3389/fsufs.2020.00055
   Makate C, 2019, J ENVIRON MANAGE, V231, P858, DOI 10.1016/j.jenvman.2018.10.069
   Makate C, 2018, AFR J SCI TECHNOL IN, V10, P421, DOI 10.1080/20421338.2018.1471027
   Matarira CH, 2013, INT J CLIM CHANG STR, V5, P404, DOI 10.1108/IJCCSM-06-2012-0034
   Meijer SS, 2015, INT J AGR SUSTAIN, V13, P40, DOI 10.1080/14735903.2014.912493
   Morse J.M., 2004, The SAGE encyclopedia of social science research methods, P1122
   Murage AW, 2015, CROP PROT, V76, P83, DOI 10.1016/j.cropro.2015.06.014
   Musa FB, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5110122
   Muyanga M, 2008, J AGRIC EDUC EXT, V14, P111, DOI 10.1080/13892240802019063
   Mwalukasa N, 2013, LIBR REV, V62, P266, DOI 10.1108/LR-12-2011-0096
   Mwongera C, 2017, AGR SYST, V151, P192, DOI 10.1016/j.agsy.2016.05.009
   Neef A, 2018, WORLD DEV, V107, P125, DOI 10.1016/j.worlddev.2018.02.029
   Nelson GC, 2009, Climate change: Impact on Agriculture and costs of Adaptation, V21, DOI DOI 10.2499/0896295354
   Nkomoki W, 2018, LAND USE POLICY, V78, P532, DOI 10.1016/j.landusepol.2018.07.021
   Nyang'au JO, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e06789
   OECD, 2013, GLOB FOOD SECUR-AGR, DOI DOI 10.1787/9789264195363-EN
   Olaosebikan O, 2019, PHYSIOL MOL PLANT P, V105, P17, DOI 10.1016/j.pmpp.2018.11.007
   Osumba J. L., 2011, ADAPTATION STRATEGIE
   PARKIN D, 1970, AFRICA, V40, P217, DOI 10.2307/1158883
   Posas PJ, 2011, PROG PLANN, V75, P109, DOI 10.1016/j.progress.2011.05.001
   Ramirez O.A., 2000, Journal of Agricultural and Applied Economics, V32, P21, DOI DOI 10.1017/S1074070800027796
   Republic of Kenya, 2019, 2019 KEN POP HOUS CE
   Ross H, 2015, CLIMATIC CHANGE, V129, P27, DOI 10.1007/s10584-014-1318-6
   Sanneh ES, 2014, MITIG ADAPT STRAT GL, V19, P1163, DOI 10.1007/s11027-013-9465-z
   Serdeczny O, 2017, REG ENVIRON CHANGE, V17, P1585, DOI 10.1007/s10113-015-0910-2
   Serote B, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11121222
   Sissinto-Gbenou EVS, 2022, FOOD SECUR, V14, P1459, DOI 10.1007/s12571-022-01297-6
   Shaw R, 2013, CLIMATE CHANGE ADAPT, P3
   Shrestha AB, 2011, REG ENVIRON CHANGE, V11, pS65, DOI 10.1007/s10113-010-0174-9
   Silvestri S, 2012, REG ENVIRON CHANGE, V12, P791, DOI 10.1007/s10113-012-0293-6
   State Department of Crop Development and Agricultural Research, 2020, ANN REPORT
   Stokes D, 2006, QUAL MARK RES, V9, P26, DOI 10.1108/13522750610640530
   Tariq A, 2018, AGR SYST, V167, P72, DOI 10.1016/j.agsy.2018.08.012
   Teklewold H, 2019, CLIM DEV, V11, P180, DOI 10.1080/17565529.2018.1442801
   Wassie A, 2018, SINGAPORE J TROP GEO, V39, P300, DOI 10.1111/sjtg.12240
   Yila JO, 2013, MANAG ENVIRON QUAL, V24, P341, DOI 10.1108/14777831311322659
   Zakaria A, 2020, EARTH SYST ENVIRON, V4, P257, DOI 10.1007/s41748-020-00146-w
NR 67
TC 5
Z9 5
U1 2
U2 6
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-9553
J9 FRONT CLIM
JI Front. Clim.
PD JUN 15
PY 2023
VL 5
AR 1032780
DI 10.3389/fclim.2023.1032780
PG 14
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA L2OE4
UT WOS:001021695700001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Curry, T
   Lopez, EDS
AF Curry, Tracie
   Lopez, Ellen D. S.
TI Images as Information: Context-Rich Images and the Communication of
   Place-Based Information Through Increased Representation in
   Environmental Governance
SO FRONTIERS IN COMMUNICATION
LA English
DT Article
DE boundary objects; communication; context-rich images; decision-making;
   governance; information; local knowledge; social-ecological systems
ID BOUNDARY-WORK; KNOWLEDGE; ADAPTATION; SCIENCE; IMPACT
AB Practitioners widely acknowledge the importance of including local and Indigenous knowledge in environmental research and decision-making. Nevertheless, it remains a challenge to achieve this integration in a meaningful way. The pilot study reported here was a necessary step toward developing improved methods for communicating local and Indigenous knowledge to decision-makers, with a focus on public sector practitioners as audience and visual content as medium. The proposed methodology extends previous research on climate change adaptation in the Alaskan Arctic, and it examines the effect of a reporting approach that introduces two components outside of general conventions in public sector information dissemination; (1) the application of context-rich images to help convey the social and cultural nuances of place-based information, and (2) multiple evidence base (MEB) reporting which engages information from both Western science and local/Indigenous knowledge systems. Context-rich images-defined here as detailed visuals that address the particularities of specific environments and cultures-are explored given their potential merits in expressing place-based concepts, such as social life and lived experience quickly and concisely when presented in tandem with text. With a focus on practical application, public sector conventions for reporting place-based information to decision-makers are investigated, including the benefits, and limitations associated with these conventions. Insights from both theory and practice informed the research methodology, and the design of a sample report and online questionnaire tested with upper-level public sector practitioners who have influence on environmental decision-making. Pilot study results indicated significant benefits of using context-rich images in addition to quotes about lived experience for reporting information about the local context and experience of Northern environmental changes. When presented alongside research from Western science, neither local observations in the form of quotes, nor context-rich images posed negative impacts on the perceived credibility of the report. The pilot study revealed the proposed methodology to be particularly beneficial for a target audience of practitioners who may lack expertise in the local context or field of research being reported. Additionally, several potential improvements to the content and design of research materials were identified for the benefit of future studies.
C1 [Curry, Tracie] Univ Alaska Fairbanks, Dept Nat Resources & Environm, Fairbanks, AK 99775 USA.
   [Lopez, Ellen D. S.] Univ Alaska Fairbanks, Dept Psychol, Fairbanks, AK USA.
C3 University of Alaska System; University of Alaska Fairbanks; University
   of Alaska System; University of Alaska Fairbanks
RP Curry, T (corresponding author), Univ Alaska Fairbanks, Dept Nat Resources & Environm, Fairbanks, AK 99775 USA.
EM tracie.curry@alaska.edu
OI Curry, Tracie/0000-0002-4191-2714
FU National Science Foundation [1342979, OIA-1208927]; State of Alaska;
   Cooperative Institute for Alaska Research; National Oceanic and
   Atmospheric Administration [NA13OAR4320056]; University of Alaska;
   University of Alaska Fairbanks Resilience and Adaptation Program;
   Department of Natural Resources and Environment; Sitka Sound Science
   Center; ICER; Directorate For Geosciences [1342979] Funding Source:
   National Science Foundation
FX This research was based on work supported by the National Science
   Foundation under Grant No. 1342979, by the National Science Foundation
   under award #OIA-1208927 and by the State of Alaska, and also by the
   Cooperative Institute for Alaska Research with funds from the National
   Oceanic and Atmospheric Administration under cooperative agreement
   NA13OAR4320056 with the University of Alaska. Additional financial
   support was provided by the University of Alaska Fairbanks Resilience
   and Adaptation Program, the Department of Natural Resources and
   Environment, and the Sitka Sound Science Center.
CR Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   [Anonymous], 2007, MIXED METHODS SOCIAL
   [Anonymous], 2013, DOING RES REAL WORLD
   Barthes Roland., 1978, IMAGE MUSIC TEXT, P69
   Berkes Fikret., 2012, Sacred Ecology, V3rd, DOI DOI 10.4324/9780203123843
   Brubaker Michael., 2014, Climate Change in Wainwright, Alaska: Strategies for Community Health
   Carmack E, 2015, PROG OCEANOGR, V139, P13, DOI 10.1016/j.pocean.2015.07.014
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Chaffin BC, 2014, ECOL SOC, V19, DOI 10.5751/ES-06824-190356
   Clark WC, 2016, P NATL ACAD SCI USA, V113, P4615, DOI 10.1073/pnas.0900231108
   Curry T., 2019, THESIS U AALASKA FAI
   Denzin N., 2011, The SAGE handbook of qualitative research
   Department of Labor, 2018, AL POP EST BOR CENS
   Dietz T, 2003, SCIENCE, V302, P1907, DOI 10.1126/science.1091015
   Eden S, 2006, ENVIRON PLANN A, V38, P1061, DOI 10.1068/a37287
   Eira IMG, 2013, COLD REG SCI TECHNOL, V85, P117, DOI 10.1016/j.coldregions.2012.09.004
   FELDER RM, 1988, ENG EDUC, V78, P674
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Harper D., 2002, Visual Studies, V17, P13, DOI [DOI 10.1080/14725860220137345, 10.1080/14725860220137345]
   Healy RG., 2010, KNOWLEDGE ENV POLICY, DOI [10.7551/mitpress/8398.001.0001, DOI 10.7551/MITPRESS/8398.001.0001]
   Kress Gunther, 2020, READING IMAGES GRAMM
   Latour B., 1999, Pandora's Hope: Essays on the Reality of Science Studies
   Latour Bruno, 1986, Knowledge and Society: Studies in the Sociology of Culture Past and Present, P1
   Lemos M.C., 2008, Water, Place, and Equity, P249
   Lemos MC, 2015, CURR OPIN ENV SUST, V12, P48, DOI 10.1016/j.cosust.2014.09.005
   Livingstone S., 1998, MEDIA RITUAL IDENTIT
   Lurie NH, 2007, J MARKETING, V71, P160, DOI 10.1509/jmkg.71.1.160
   Martin T, 2007, ENVIRON COMMUN, V1, P171, DOI 10.1080/17524030701642595
   McGreavy B, 2013, SUSTAINABILITY-BASEL, V5, P4195, DOI 10.3390/su5104195
   Meadows DH, 2008, THINKING SYSTEMS PRI
   Meyer J, 1999, HUM FACTORS, V41, P570, DOI 10.1518/001872099779656707
   Meyer RE, 2013, ACAD MANAG ANN, V7, P489, DOI 10.1080/19416520.2013.781867
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Pahl-Wostl C, 2009, GLOBAL ENVIRON CHANG, V19, P354, DOI 10.1016/j.gloenvcha.2009.06.001
   Radner R, 1972, Decision and Organization, P161
   Raymond-Yakoubian J, 2017, MAR POLICY, V78, P132, DOI 10.1016/j.marpol.2016.12.024
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Salinas C., 2002, TECH COMMUN Q, V11, P165, DOI DOI 10.1207/S15427625TCQ11024
   Shenton A. K., 2004, Education for Information, V22, P63, DOI DOI 10.3233/EFI-2004-22201
   STAR SL, 1989, SOC STUD SCI, V19, P387, DOI 10.1177/030631289019003001
   Star SL, 2010, SCI TECHNOL HUM VAL, V35, P601, DOI 10.1177/0162243910377624
   Swedberg R, 2018, J CLASS SOCIOL, V18, P181, DOI 10.1177/1468795X17743643
   Tengö M, 2014, AMBIO, V43, P579, DOI 10.1007/s13280-014-0501-3
   Trainor S., 2017, ADAPTATION ACTIONS C, P177
   Ulin PR., 2005, Qualitative methods in public health, P11
   Van Leeuwen T., 2011, Multimodal studies: Exploring issues and domains, P115
   van Wyk E, 2008, ENVIRON MANAGE, V41, P779, DOI 10.1007/s00267-008-9084-8
   Vargas-Moreno J.C., 2016, Prioritizing Science Needs Through Participatory Scenarios for Energy and Resource Development on the North Slope and Adjacent Seas
   Village of Wainwright, 2016, WAINWR COMM GUID
   Webber M, 1904, ARCH SOZIALWISS SOZI, V19, P22
NR 50
TC 1
Z9 1
U1 1
U2 6
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2297-900X
J9 FRONT COMMUN
JI Front. Commun.
PD JUL 9
PY 2020
VL 5
AR 43
DI 10.3389/fcomm.2020.00043
PG 15
WC Communication
WE Emerging Sources Citation Index (ESCI)
SC Communication
GA TP5NP
UT WOS:000677646500001
OA gold
DA 2025-01-10
ER

PT J
AU Borchert, SM
   Osland, MJ
   Enwright, NM
   Griffith, KT
AF Borchert, Sinead M.
   Osland, Michael J.
   Enwright, Nicholas M.
   Griffith, Kereen T.
TI Coastal wetland adaptation to sea level rise: Quantifying potential for
   landward migration and coastal squeeze
SO JOURNAL OF APPLIED ECOLOGY
LA English
DT Article
DE climate change adaptation; coastal squeeze; coastal wetlands; mangroves;
   marsh; sea level rise; urbanization; wetland migration
ID CLIMATE-CHANGE; MANAGED RETREAT; MARSH; MANGROVE; VULNERABILITY;
   IMPACTS; FLORIDA; FACE; INFRASTRUCTURE; OPPORTUNITIES
AB 1. Coastal wetland ecosystems are expected to migrate landwards in response to rising seas. However, due to differences in topography and coastal urbanization, estuaries vary in their ability to accommodate migration. Low-lying urban areas can constrain migration and lead to wetland loss (i.e. coastal squeeze), especially where existing wetlands cannot keep pace with rising seas via vertical adjustments. In many estuaries, there is a pressing need to identify landward migration corridors and better quantify the potential for landward migration and coastal squeeze.
   2. We quantified and compared the area available for landward migration of tidal saline wetlands and the area where urban development is expected to prevent migration for 39 estuaries along the wetland-rich USA Gulf of Mexico coast. We did so under three sea level rise scenarios (0.5, 1.0, and 1.5 m by 2100).
   3. Within the region, the potential for wetland migration is highest within certain estuaries in Louisiana and southern Florida (e.g. Atchafalaya/Vermilion Bays, Mermentau River, Barataria Bay, and the North and South Ten Thousand Islands estuaries).
   4. The potential for coastal squeeze is highest in estuaries containing major metropolitan areas that extend into low-lying lands. The Charlotte Harbor, Tampa Bay, and Crystal-Pithlachascotee estuaries (Florida) have the highest amounts of urban land expected to constrain wetland migration. Urban barriers to migration are also high in the Galveston Bay (Texas) and Atchafalaya/Vermilion Bays (Louisiana) estuaries.
   5. Synthesis and applications. Coastal wetlands provide many ecosystem services that benefit human health and well-being, including shoreline protection and fish and wildlife habitat. As the rate of sea level rise accelerates in response to climate change, coastal wetland resources could be lost in areas that lack space for landward migration. Migration corridors are particularly important in highly urbanized estuaries where, due to low-lying coastal development, there is not space for wetlands to move and adapt to sea level rise. Future-focused landscape conservation plans that incorporate the protection of wetland migration corridors can increase the adaptive capacity of these valuable ecosystems and simultaneously decrease the vulnerability of coastal human communities to the harmful effects of rising seas.
C1 [Borchert, Sinead M.] US Geol Survey, Wetland & Aquat Res Ctr, Borchert Consulting, Lafayette, LA 70506 USA.
   [Osland, Michael J.; Enwright, Nicholas M.] US Geol Survey, Wetland & Aquat Res Ctr, Lafayette, LA USA.
   [Griffith, Kereen T.] US Geol Survey, Wetland & Aquat Res Ctr, Griffith Consulting, Lafayette, LA USA.
C3 United States Department of the Interior; United States Geological
   Survey; United States Department of the Interior; United States
   Geological Survey; United States Department of the Interior; United
   States Geological Survey
RP Borchert, SM (corresponding author), US Geol Survey, Wetland & Aquat Res Ctr, Borchert Consulting, Lafayette, LA 70506 USA.
EM sborchert@usgs.gov
RI Enwright, Nicholas/R-3640-2019; Osland, Michael/D-1814-2014; Enwright,
   Nicholas/G-9657-2014
OI Osland, Michael/0000-0001-9902-8692; Enwright,
   Nicholas/0000-0002-7887-3261; Borchert, Sinead/0000-0002-6665-7115
FU U.S. Geological Survey Ecosystems and Land Change Science Mission Areas;
   U.S. Fish and Wildlife Service; Department of Interior South Central
   Climate Science Center; Department of Interior Southeast Climate Science
   Center
FX We thank the U.S. Geological Survey Ecosystems and Land Change Science
   Mission Areas, the U.S. Fish and Wildlife Service, the Department of
   Interior South Central Climate Science Center, and the Department of
   Interior Southeast Climate Science Center for their support of this
   project. We also thank William Vervaeke for comments on a previous
   version of this manuscript. Any use of trade, firm or product names is
   for descriptive purposes only and does not imply endorsement by the U.S.
   Government.
CR Alizad K, 2016, EARTHS FUTURE, V4, P483, DOI 10.1002/2016EF000385
   Alizad K, 2016, ECOL MODEL, V327, P29, DOI 10.1016/j.ecolmodel.2016.01.013
   [Anonymous], GULF MEXICO ORIGIN W
   [Anonymous], 1999, SEA LEVEL RISE COAST, DOI DOI 10.3133/OFR99441
   [Anonymous], 2015, U.S. Geol. Surv. Data Ser., DOI DOI 10.3133/DS969
   [Anonymous], 2016, CONSERV LETT, DOI DOI 10.1111/conl.12213
   [Anonymous], 1982, FWSOBS8124
   [Anonymous], 1815 US GEOL SURV
   [Anonymous], 2017, 083 NOAA NOS COOPS
   Arkema KK, 2013, NAT CLIM CHANGE, V3, P913, DOI 10.1038/NCLIMATE1944
   Barbier EB, 2011, ECOL MONOGR, V81, P169, DOI 10.1890/10-1510.1
   Buffington KJ, 2016, REMOTE SENS ENVIRON, V186, P616, DOI 10.1016/j.rse.2016.09.020
   Church JA, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1137
   Costanza R, 2014, GLOBAL ENVIRON CHANG, V26, P152, DOI 10.1016/j.gloenvcha.2014.04.002
   Couvillion B.R., 2017, Land area change in coastal Louisiana (1932 to 2016), Scientific Investigations Map, P3381
   Craft C, 2009, FRONT ECOL ENVIRON, V7, P73, DOI 10.1890/070219
   Di Nitto D, 2014, BIOGEOSCIENCES, V11, P857, DOI 10.5194/bg-11-857-2014
   Doody JP, 2013, OCEAN COAST MANAGE, V79, P34, DOI 10.1016/j.ocecoaman.2012.05.008
   Doyle TW, 2010, FOREST ECOL MANAG, V259, P770, DOI 10.1016/j.foreco.2009.10.023
   Duarte CM, 2013, NAT CLIM CHANGE, V3, P961, DOI [10.1038/NCLIMATE1970, 10.1038/nclimate1970]
   Ellison JC, 2015, WETL ECOL MANAG, V23, P115, DOI 10.1007/s11273-014-9397-8
   Engle VD, 2011, WETLANDS, V31, P179, DOI 10.1007/s13157-010-0132-9
   Enwright NM, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10010005
   Enwright NM, 2016, FRONT ECOL ENVIRON, V14, P307, DOI 10.1002/fee.1282
   Feagin RA, 2010, ECOL SOC, V15
   Feher LC, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.1956
   Field D.W., 1991, Coastal wetlands of the United States- An accounting of a valuable national resource
   Flower H, 2017, ENVIRON MANAGE, V60, P989, DOI 10.1007/s00267-017-0916-2
   Gabler CA, 2017, NAT CLIM CHANGE, V7, P142, DOI [10.1038/nclimate3203, 10.1038/NCLIMATE3203]
   Geselbracht L, 2011, CLIMATIC CHANGE, V107, P35, DOI [10.1007/s10584-011-0084-y, 10.1007/s10584-011-0084-v]
   Geselbracht LL, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0132079
   Gittman RK, 2015, FRONT ECOL ENVIRON, V13, P301, DOI 10.1890/150065
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hill K, 2015, FRONT ECOL ENVIRON, V13, P468, DOI 10.1890/150088
   Hinkel J, 2014, P NATL ACAD SCI USA, V111, P3292, DOI 10.1073/pnas.1222469111
   Howard RJ, 2017, RESTOR ECOL, V25, P471, DOI 10.1111/rec.12452
   Hulme PE, 2005, J APPL ECOL, V42, P784, DOI 10.1111/j.1365-2664.2005.01082.x
   Jankowski KL, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14792
   Kirwan ML, 2013, NATURE, V504, P53, DOI 10.1038/nature12856
   Kirwan ML, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL045489
   Kirwan ML, 2010, J GEOPHYS RES-EARTH, V115, DOI 10.1029/2009JF001400
   Krauss KW, 2014, NEW PHYTOL, V202, P19, DOI 10.1111/nph.12605
   Krauss KW, 2011, J COAST CONSERV, V15, P629, DOI 10.1007/s11852-011-0153-4
   Krolik-Root C, 2015, OCEAN COAST MANAGE, V114, P164, DOI 10.1016/j.ocecoaman.2015.06.013
   Langston AK, 2017, GLOBAL CHANGE BIOL, V23, P5383, DOI 10.1111/gcb.13805
   Lawler JJ, 2009, ANN NY ACAD SCI, V1162, P79, DOI 10.1111/j.1749-6632.2009.04147.x
   Lester Charles, 2016, STANFORD ENV LAW J, V36, P31
   Linhoss AC, 2015, J COASTAL RES, V31, P36, DOI 10.2112/JCOASTRES-D-13-00215.1
   Mawdsley JR, 2009, CONSERV BIOL, V23, P1080, DOI 10.1111/j.1523-1739.2009.01264.x
   McKee KL, 2011, ESTUAR COAST SHELF S, V91, P475, DOI 10.1016/j.ecss.2010.05.001
   Medeiros S, 2015, REMOTE SENS-BASEL, V7, P3507, DOI 10.3390/rs70403507
   Morgan PA, 2009, ESTUAR COAST, V32, P483, DOI 10.1007/s12237-009-9145-0
   Morris JT, 2002, ECOLOGY, V83, P2869, DOI 10.1890/0012-9658(2002)083[2869:ROCWTR]2.0.CO;2
   Nicholls RJ, 1999, GLOBAL ENVIRON CHANG, V9, pS69, DOI 10.1016/S0959-3780(99)00019-9
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Nyman JA, 2006, ESTUAR COAST SHELF S, V69, P370, DOI 10.1016/j.ecss.2006.05.041
   Osland MJ, 2016, GLOBAL CHANGE BIOL, V22, P1, DOI 10.1111/gcb.13084
   Parker BB, 2003, J COASTAL RES, P44
   Passeri DL, 2015, EARTHS FUTURE, V3, P159, DOI 10.1002/2015EF000298
   Pontee N, 2013, OCEAN COAST MANAGE, V84, P204, DOI 10.1016/j.ocecoaman.2013.07.010
   R Core Team, 2017, R LANG ENV STAT COMP
   Rogers K, 2016, MAR POLICY, V72, P139, DOI 10.1016/j.marpol.2016.06.025
   Rogers K, 2014, ESTUAR COAST, V37, P67, DOI 10.1007/s12237-013-9664-6
   Runting RK, 2017, CONSERV LETT, V10, P49, DOI 10.1111/conl.12239
   Scavia D, 2002, ESTUARIES, V25, P149, DOI 10.1007/BF02691304
   Schile LM, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0088760
   Schleupner C, 2008, OCEAN COAST MANAGE, V51, P383, DOI 10.1016/j.ocecoaman.2008.01.008
   Schmid K, 2014, J COASTAL RES, V30, P548, DOI 10.2112/JCOASTRES-D-13-00118.1
   Schmidt KA, 2011, J COASTAL RES, V27, P116, DOI 10.2112/JCOASTRES-D-10-00188.1
   Spalding MD, 2014, OCEAN COAST MANAGE, V90, P50, DOI 10.1016/j.ocecoaman.2013.09.007
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Sterr H, 2008, J COASTAL RES, V24, P380, DOI 10.2112/07A-0011.1
   Stralberg D, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0027388
   Sutton-Grier AE, 2015, ENVIRON SCI POLICY, V51, P137, DOI 10.1016/j.envsci.2015.04.006
   Terando AJ, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0102261
   Thorne K, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao3270
   Titus J., 1998, Maryland Land Review, V27, P1279
   Titus JG, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/4/044008
   TITUS JG, 1986, COAST MANAGE, V14, P147, DOI 10.1080/08920758609362000
   Torio DD, 2015, ESTUAR COAST, V38, P1288, DOI 10.1007/s12237-013-9740-y
   Torio DD, 2013, J COASTAL RES, V29, P1049, DOI 10.2112/JCOASTRES-D-12-00162.1
   Traill LW, 2011, DIVERS DISTRIB, V17, P1225, DOI 10.1111/j.1472-4642.2011.00807.x
   West R. C., 1977, Wet coastal ecosystems., P193
   Wigand Cathleen, 2017, Estuaries Coast, V40, P682
   Williams K, 1999, ECOLOGY, V80, P2045, DOI 10.1890/0012-9658(1999)080[2045:SLRACF]2.0.CO;2
   Withers Kim, 2002, P114
   Woodroffe CD, 2016, ANNU REV MAR SCI, V8, P243, DOI 10.1146/annurev-marine-122414-034025
   Yoskowitz D, 2017, INTEGR ENVIRON ASSES, V13, P431, DOI 10.1002/ieam.1798
NR 88
TC 122
Z9 143
U1 16
U2 204
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0021-8901
EI 1365-2664
J9 J APPL ECOL
JI J. Appl. Ecol.
PD NOV
PY 2018
VL 55
IS 6
BP 2876
EP 2887
DI 10.1111/1365-2664.13169
PG 12
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA GW9HW
UT WOS:000447296300033
OA Bronze
DA 2025-01-10
ER

PT J
AU Lasco, RD
   Espaldon, MLO
   Habito, CMD
AF Lasco, Rodel D.
   Espaldon, Marya Laya O.
   Habito, Christine Marie D.
TI Smallholder farmers' perceptions of climate change and the roles of
   trees and agroforestry in climate risk adaptation: evidence from Bohol,
   Philippines
SO AGROFORESTRY SYSTEMS
LA English
DT Article
DE Roles of trees; Agroforestry; Ecosystem services; Climate change;
   Adaptation; Philippines
ID ECOSYSTEM SERVICES; STRATEGIES; VULNERABILITY; AGRICULTURE; COMMUNITIES;
   DECISIONS; ADOPTION; IMPACTS; MODEL
AB Recent studies have highlighted the importance of trees and agroforestry in climate change adaptation and mitigation. This paper analyzes how farmers, members of their households, and community leaders in the Wahig-Inabanga watershed, Bohol province in the Philippines perceive of climate change, and define and value the roles of trees in coping with climate risks. Focus group discussions revealed that farmers and community leaders had observed changes in rainfall and temperature over the years. They also had positive perceptions of tree roles in coping with climate change, with most timber tree species valued for regulating functions, while non-timber trees were valued as sources of food and income. Statistical analysis of the household survey results was done through linear probability models for both determinants of farmers' perceived changes in climate, and perceived importance of tree roles in coping with climate risks. Perceiving of changes in rainfall was more likely among farmers who had access to electricity, had access to water for irrigation, and derived climate information from government agencies and mass media, and less likely among farmers who were members of farmers' organizations. On the other hand, perceiving of an increase in temperature was more likely among famers who were members of women's organizations and had more off/non-farm sources of income, and less likely among those who derived climate information from government agencies. Meanwhile, marginal effects of the regression on perceived importance of trees in coping with climate change revealed positively significant relationships with the following predictor variables: access to electricity, number of off/non-farm sources of income, having trees planted by household members, observed increase in temperature and decline in yield, and sourcing climate information from government agencies. In contrast, a negatively significant relationship was observed between recognition of the importance of tree roles, and level of education, and deriving income from tree products. In promoting tree-based adaptation, we recommend improving access to necessary inputs and resources, exploring the potentials of farmer-to-farmer extension, using participatory approaches to generate farmer-led solutions based on their experiences of climate change, and initiating government-led extension to farmers backed by non-government partners.
C1 [Lasco, Rodel D.; Espaldon, Marya Laya O.; Habito, Christine Marie D.] World Agroforestry Ctr ICRAF Philippines, Int Rice Res Inst IRRI Headquarters, 2-F Khush Hall, Los Banos, Laguna, Philippines.
   [Lasco, Rodel D.] OML Ctr Climate Change Adaptat & Disaster Risk Ma, Pasig, Philippines.
C3 CGIAR; World Agroforestry (ICRAF)
RP Lasco, RD (corresponding author), World Agroforestry Ctr ICRAF Philippines, Int Rice Res Inst IRRI Headquarters, 2-F Khush Hall, Los Banos, Laguna, Philippines.; Lasco, RD (corresponding author), OML Ctr Climate Change Adaptat & Disaster Risk Ma, Pasig, Philippines.
EM rlasco@cgiar.org
RI Rodel, Lasco/AAA-6206-2022
OI Lasco, Rodel/0000-0003-3675-4237
FU CGIAR Research Programme on Forest Trees and Agroforestry [CRP 6.4];
   CGIAR Research Programme on Climate Change, Agriculture and Food
   Security (CCAFS)
FX This research was funded by the CGIAR Research Programme on Forest Trees
   and Agroforestry (CRP 6.4) and the CGIAR Research Programme on Climate
   Change, Agriculture and Food Security (CCAFS), and implemented in
   partnership with the Institute of Agroforestry (IAF) at the University
   of the Philippines Los Banos (UPLB). The authors would like to thank the
   farmers and stakeholders of the Municipalities of Pilar and Danao in the
   Province of Bohol, Philippines, for their participation and support in
   the conduct of this study. The authors also wish to thank Mr. Justin
   McKinley, and the two anonymous reviewers who helped improve this study.
CR Acosta-Michlik L, 2008, GLOBAL ENVIRON CHANG, V18, P554, DOI 10.1016/j.gloenvcha.2008.08.006
   ADB (Asian Development Bank), 2014, KEY IND AS PAC 2014
   Alauddin M, 2014, ECOL ECON, V106, P204, DOI 10.1016/j.ecolecon.2014.07.025
   [Anonymous], CLIM PROJ
   [Anonymous], BIG FACTS CLIM CHANG
   [Anonymous], 2007, WORLD BANK POLICY RE
   [Anonymous], 2007, THESIS U PRETORIA
   [Anonymous], POV STAT
   [Anonymous], SELF RAT POV HUNG
   [Anonymous], PHILIPPINE STAR
   [Anonymous], DROUGHT CONDITIONS M
   [Anonymous], 2014, CHANGING PHILIPPINE
   [Anonymous], 0809PAD ADAPTNET POL
   [Anonymous], COUNTRYSTAT PHIL
   [Anonymous], 2009, GLOBAL ENVIRON CHANG, DOI DOI 10.1016/j.gloenvcha.2009.01.002
   [Anonymous], IMP EV BOH IRR PROJ
   [Anonymous], MANILA B
   [Anonymous], ENVIRON MANAGE
   [Anonymous], BOH AGR MAST PLAN
   [Anonymous], 2009, UNDERSTANDING FARMER
   [Anonymous], PHILIPPINE STAR
   [Anonymous], CURR CLIM OBS TRENDS
   [Anonymous], 1999, NAGA ICLARM Q
   [Anonymous], MANILA B
   [Anonymous], ENC SOILS ENV
   [Anonymous], J AGR SCI 1
   [Anonymous], BOHOL STAND
   [Anonymous], 2003, Ecosystems and human well-being: A framework for assessment (Millenium Ecosystem Assessment), DOI DOI 10.1023/A:1009652531101
   Apata T G., 2009, INT ASS AGR ECONOMIS
   Bryan E, 2013, J ENVIRON MANAGE, V114, P26, DOI 10.1016/j.jenvman.2012.10.036
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Cerdán CR, 2012, AGR SYST, V110, P119, DOI 10.1016/j.agsy.2012.03.014
   Chambers R, 2006, IDS BULL-I DEV STUD, V37, P33, DOI 10.1111/j.1759-5436.2006.tb00284.x
   Croppenstedt A., 2003, Review of Development Economics, V7, P58, DOI [DOI 10.1111/1467-9361.00175, 10.1111/1467-9361.00175]
   Cruz RV, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P469
   de Groot RS, 2002, ECOL ECON, V41, P393, DOI 10.1016/S0921-8009(02)00089-7
   Di Falco S, 2011, AM J AGR ECON, V93, P825, DOI 10.1093/ajae/aar006
   Food and Agriculture Organization of the United Nations ( FAO), 2010, CLIMATESMARTAGRICULT
   Frank E, 2011, GLOBAL ENVIRON CHANG, V21, P66, DOI 10.1016/j.gloenvcha.2010.11.001
   Gandure S, 2013, ENVIRON DEV, V5, P39, DOI 10.1016/j.envdev.2012.11.004
   Giddens A., 1984, CONSTITUTION SOC ELE
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Halcoussis D., 2005, Understanding econometrics
   Hassan R, 2008, AFR J AGRIC RESOUR E, V2, P83
   Hijioka Y, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1327
   Dang HL, 2014, ENVIRON SCI POLICY, V41, P11, DOI 10.1016/j.envsci.2014.04.002
   Jerneck A, 2013, J RURAL STUD, V32, P114, DOI 10.1016/j.jrurstud.2013.04.004
   Knowler D, 2007, FOOD POLICY, V32, P25, DOI 10.1016/j.foodpol.2006.01.003
   Lasco R.D., 2010, ASSESSING CLIMATE CH
   Lasco RD, 2014, WIRES CLIM CHANGE, V5, P825, DOI 10.1002/wcc.301
   Lasco RD, 2014, CURR OPIN ENV SUST, V6, P83, DOI 10.1016/j.cosust.2013.11.013
   Lyle G, 2015, J RURAL STUD, V37, P38, DOI 10.1016/j.jrurstud.2014.10.004
   Martín-López B, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0038970
   Matocha J., 2012, Agroforestry-the Future of Global Land use, P105
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P61, DOI 10.1016/j.cosust.2013.10.014
   Muhamad D, 2014, ECOSYST SERV, V8, P197, DOI 10.1016/j.ecoser.2014.04.003
   Nair P.K.R., 1993, An Introduction to Agroforestry: Four Decades of Scientific Developments, DOI [10.1007/978-3-030-75358-0, DOI 10.1007/978-3-030-75358-0]
   Perez RT, 1999, CLIMATE RES, V12, P97, DOI 10.3354/cr012097
   Nguyen Q, 2013, CLIMATIC CHANGE, V117, P241, DOI 10.1007/s10584-012-0550-1
   Roco L, 2014, ENVIRON SCI POLICY, V44, P86, DOI 10.1016/j.envsci.2014.07.008
   Saldajeno PB, 2012, J ENVIRON SCI MANAG, V15, P1
   StataCorp LLC, 2019, STATA STAT SOFTWARE
   Thornton P.K, 2008, ILRI Discussion Paper
   Truelove HB, 2015, GLOBAL ENVIRON CHANG, V31, P85, DOI 10.1016/j.gloenvcha.2014.12.010
   Verbeek Marno, 2008, A Guide to Modern Econometrics
   Verchot L. V., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P901, DOI 10.1007/s11027-007-9105-6
   Weber EU, 2006, CLIMATIC CHANGE, V77, P103, DOI 10.1007/s10584-006-9060-3
   Weber EU, 2010, WIRES CLIM CHANGE, V1, P332, DOI 10.1002/wcc.41
   Zomer RobertJ., 2009, ICRAF Working Paper-World Agroforestry Centre, V89
   Zubair M, 2006, AGROFOREST SYST, V66, P217, DOI 10.1007/s10457-005-8846-z
NR 70
TC 50
Z9 55
U1 8
U2 106
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0167-4366
EI 1572-9680
J9 AGROFOREST SYST
JI Agrofor. Syst.
PD JUN
PY 2016
VL 90
IS 3
BP 521
EP 540
DI 10.1007/s10457-015-9874-y
PG 20
WC Agronomy; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture; Forestry
GA DT1DT
UT WOS:000381222600013
DA 2025-01-10
ER

PT J
AU Burnside-Lawry, J
   Carvalho, L
AF Burnside-Lawry, Judy
   Carvalho, Luis
TI Building local level engagement in disaster risk reduction: a Portugese
   case study
SO DISASTER PREVENTION AND MANAGEMENT
LA English
DT Article
DE Portugal; Leadership; Resilience; Dialogue; Disaster risk reduction;
   Participatory communication
ID CLIMATE-CHANGE ADAPTATION; RESILIENCE; COMMUNICATION; PARTICIPATION;
   CAPACITY; PERSPECTIVES; HABERMAS; DIALOGUE
AB Purpose - Contributing to the global dialogue on disaster risk reduction (DRR), the purpose of this paper is to address a key priority for the Post-2015 Framework for DRR (HFA2) by analysing initiatives used by one local government to increase local-level engagement in DRR.
   Design/methodology/approach - A review of literature from the multidisciplinary areas of communication, social and political theory examines the role that communication theory and practice can play in facilitating public participation to build community resilience. Building on these insights, the authors introduce a research methodology to examine modes of communication, the quality of dialogue and opportunities for "voice" and "listening" between decision makers and local-level stakeholders during DRR planning A qualitative, case study is undertaken with data sourced from observation, document analysis and interviews to provide insights into public engagement events, policies and procedures that enhance or impede local engagement in DRR.
   Findings - Communication between the DRR campaign team and publics are analysed according to the range of communication practices used and opportunities provided for dialogue between parties. Findings differentiate between public information, consultation and participation events. Factors that enable and conversely, constrain local-level engagement to build community resilience, and conditions associated with each factor, are identified.
   Research limitations/implications - A unique analytical framework adapted from the duel lenses of participatory communication and information flow models, is used to differentiate events using one-way information from those offering opportunities for dialogue and participation. The framework provides a method for DRR practitioners to plan and evaluate local-level engagement events to meet the communication needs of particular situations.
   Practical implications - The framework provides a method for DRR practitioners to plan and evaluate local-level engagement events to meet the communication needs of particular situations.
   Originality/value - Co-authored by an Australian academic and a member of Amadora's campaign team, the paper is a combination of one city's experience in developing strategies to build community resilience, analysed using communication, social and political theory. Findings have implications for standard command-and-control management systems and styles of leadership and crisis management. Results will assist practitioners' advance their understanding of different ways that publics may be engaged to build community resilience.
C1 [Burnside-Lawry, Judy] RMIT Univ, Sch Media & Commun, Melbourne, Vic, Australia.
   [Carvalho, Luis] Municipal Amadora, Civil Protect Serv, Amadora, Portugal.
C3 Royal Melbourne Institute of Technology (RMIT)
RP Burnside-Lawry, J (corresponding author), RMIT Univ, Sch Media & Commun, Melbourne, Vic, Australia.
EM judy.burnside-lawry@rmit.edu.au
RI Carvalho, Luís/JTS-8886-2023
CR Adger WN, 2000, PROG HUM GEOG, V24, P347, DOI 10.1191/030913200701540465
   Alexander DE, 2013, NAT HAZARD EARTH SYS, V13, P2707, DOI 10.5194/nhess-13-2707-2013
   Amadora Campaign, 2013, AM RES
   Amadora Campaign, 2013, WORLD DIS RED CAMP 2
   Amundsen H, 2012, ECOL SOC, V17, DOI 10.5751/ES-05142-170446
   [Anonymous], 2004, DEMOCRATIE DEBAT CIT
   [Anonymous], 2013, DEF COMM RES AN, P1
   ARNSTEIN SR, 1969, J AM I PLANNERS, V35, P216, DOI 10.1080/01944366908977225
   Becker P, 2012, DISASTER PREV MANAG, V21, P226, DOI 10.1108/09653561211220016
   Bene C., 2012, 405 IDS U SUSS CTR S
   Burnside-Lawry J., 2011, Australian Journal of Communication, V38, P147
   Burnside-Lawry J., 2014, J PUBLIC AFFAIRS
   Burnside-Lawry J, 2013, COMMUN POLITICS CULT, V46, P155
   Burnside-Lawry J, 2013, AUST J EMERG MANAG, V28, P29
   Cheney G., 1995, Journal of Applied Communication Research, V23, P167, DOI DOI 10.1080/00909889509365424
   Collins K., 2006, Dare we jump off Arnstein's ladder? Social learning as a new policy paradigm
   Council of Australian Governments, 2011, NAT STRAT DIS RES BU
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Deetz Stanley., 2001, NEW HDB ORG COMMUNIC, P3
   Deetz Stanley A., 1992, Democracy in an Age of Corporate Colonization: Developments in Communication and the Politics of Everyday Life
   Dempsey SE, 2010, MANAGE COMMUN Q, V24, P359, DOI 10.1177/0893318909352247
   Fishkin JS, 2009, PEOPLE SPEAK DELIBER, P65
   Freeman R. E., 1984, STRATEG MANAG
   Gaillard JC, 2010, J INT DEV, V22, P218, DOI 10.1002/jid.1675
   Gao S.S., 2001, Perspectives of Corporate Citizenship, DOI [10.9774/GLEAF.978-1-909493-19-3_16, DOI 10.9774/GLEAF.978-1-909493-19-3_16]
   Garnham N, 2007, GLOB MEDIA COMMUN, V3, P201, DOI 10.1177/1742766507078417
   Groven K, 2012, LOCAL ENVIRON, V17, P679, DOI 10.1080/13549839.2012.665859
   Habermas J., 1984, The theory of communicative action: Reason and the rationalization of society
   Habermas J., 2001, On the pragmatics of social interaction: Preliminary studies in the theory of communicative action
   Hofstede G., 1993, Executive, V7, P81, DOI [DOI 10.5465/AME.1993.9409142061, 10.5465/ame.1993.9409142061]
   Jacobson T. L., 2007, WORKSH MEAS PRESS FR
   Jacobson TL, 2004, COMMUN THEOR, V14, P99, DOI 10.1111/j.1468-2885.2004.tb00307.x
   Klein R.J.T., 2003, ENVIRON HAZARDS-UK, V5, P35, DOI DOI 10.1016/J.HAZARDS.2004.02.001
   Kusumasari B, 2010, DISASTER PREV MANAG, V19, P438, DOI 10.1108/09653561011070367
   Lagadec E., 2009, Leadership in Unconventional Crises: A Transatlantic and Cross-Sector Assessment
   Lagadec Erwan., 2007, Unconventional Crises, Unconventional Responses: Reforming Leadership in the Age of Catastrophic Crises and Hypercomplexity
   Lal P. N., 2011, CLIMATE CHANGE ADAPT
   Lopes C., 2003, Ownership, Leadership and Transformation: Can We Do Better for Capacity Development?
   Lunenburg FC, 2011, International journal of management, business, and administration, V14, P1, DOI DOI 10.12691/EDUCATION-6-1-3
   Manyena SB, 2006, DISASTERS, V30, P433
   Manyena SB, 2011, LOCAL ENVIRON, V16, P417, DOI 10.1080/13549839.2011.583049
   Meisenbach RJ, 2009, COMMUN SER, P253
   Miles M. B., 1994, QUALITATIVE DATA ANA
   Nye JosephS., 2008, POWERS LEAD
   Pfeifer J., 2012, WNYF NEW YORK FIREFI, V1, P20
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Renschler C., 2010, 9 US NAT 10 CAN C EA, P1152
   Rowe G, 2005, SCI TECHNOL HUM VAL, V30, P251, DOI 10.1177/0162243904271724
   Servaes J., 2005, Media and Global Change, P91
   Servaes J., 1996, Africa Media Review, V10, P73
   't Hart P, 2008, ANZSOG MONOGR, P1
   Twigg J., 2007, Characteristics of a disaster-resilient community: A guidance note
   United Nations Economic Commission for Europe, 1998, CONV ACC INF PUBL PA
   United Nations International Strategy for Disaster Risk Reduction, 2013, IMPL HYOG FRAM ACT E
   United Nations International Strategy for Disaster Risk Reduction, 2012, MAK CIT RES REP 2012
   United Nations International Strategy for Disaster Risk Reduction, 2014, 6 MIN C AS PAC BANGK
   van den Berg M, 2012, LOCAL ENVIRON, V17, P441, DOI 10.1080/13549839.2012.678313
   Varghese J, 2006, RURAL SOCIOL, V71, P505, DOI 10.1526/003601106778070653
   Weaver CK, 2007, MANAGE COMMUN Q, V21, P92, DOI 10.1177/0893318907302640
   Webler T, 2001, ENVIRON MANAGE, V27, P435
NR 60
TC 22
Z9 28
U1 3
U2 36
PU EMERALD GROUP PUBLISHING LTD
PI BINGLEY
PA HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND
SN 0965-3562
EI 1758-6100
J9 DISASTER PREV MANAG
JI Disaster Prev. Manag.
PY 2015
VL 24
IS 1
BP 80
EP 99
DI 10.1108/DPM-07-2014-0129
PG 20
WC Environmental Studies; Public, Environmental & Occupational Health;
   Management
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health; Business & Economics
GA CB5BK
UT WOS:000349642300007
DA 2025-01-10
ER

PT J
AU Brousse, O
   Simpson, CH
   Poorthuis, A
   Heaviside, C
AF Brousse, Oscar
   Simpson, Charles H.
   Poorthuis, Ate
   Heaviside, Clare
TI Unequal distributions of crowdsourced weather data in England and Wales
SO NATURE COMMUNICATIONS
LA English
DT Article
ID URBAN HEAT-ISLAND; HOT WEATHER; VULNERABILITY; MORTALITY; LONDON;
   HEALTH; TEMPERATURE; POPULATION; STATIONS; SCIENCE
AB Personal weather stations (PWS) can provide useful data on urban climates by densifying the number of weather measurements across major cities. They do so at a lower cost than official weather stations by national meteorological services. Despite the increasing use of PWS data, little attention has yet been paid to the underlying socio-economic and environmental inequalities in PWS coverage. Using social deprivation, demographic, and environmental indicators in England and Wales, we characterize existing inequalities in the current coverage of PWS. We find that there are fewer PWS in more deprived areas which also observe higher proportions of ethnic minorities, lower vegetation coverage, higher building height and building surface fraction, and lower proportions of inhabitants under 65 years old. This implies that data on urban climate may be less reliable or more uncertain in particular areas, which may limit the potential for climate adaptation and empowerment in those communities.
   Crowdsourced personal weather data are sought to cope with weather data scarcity. But, in England and Wales, more deprived areas are less covered. This limits the potential for climate adaptation of communities living in these environments.
C1 [Brousse, Oscar; Simpson, Charles H.; Heaviside, Clare] UCL, Inst Environm Design & Engn, London, England.
   [Poorthuis, Ate] Katholieke Univ Leuven, Dept Earth & Environm Sci, Leuven, Belgium.
C3 University of London; University College London; KU Leuven
RP Brousse, O (corresponding author), UCL, Inst Environm Design & Engn, London, England.
EM o.brousse@ucl.ac.uk
RI Brousse, Oscar/AAU-1836-2021; Simpson, Charles/ADR-1004-2022; Poorthuis,
   Ate/S-2675-2018
OI Heaviside, Clare/0000-0002-0263-4985; Poorthuis,
   Ate/0000-0002-3808-7493; Simpson, Charles/0000-0001-9356-5833
FU Wellcome Trust (Wellcome); European Commission [NE/R01440X/1]; NERC
   fellowship [216035/Z/19/Z]; HEROIC project; Wellcome Trust
FX We would like to thank the providers of the openly accessible data sets
   used in this study, namely: the WUDAPT project for the LCZ maps,
   Google's Earth Engine for the MODIS data, courtesy of the NASA and USGS,
   the European Commission for the GHSL data, and the Office of National
   Statistics for the census and the IMD data. Additionally, the authors
   would like to thank Prof. Nicole van Lipzig who organised a seminar that
   led to this collaboration and Dr. Daniel Fenner and Dr. Fred Meier for
   their support in gathering and filtering of Netatmo crowd-sourced data.
   C.H. is supported by a NERC fellowship (NE/R01440X/1) and acknowledges
   funding for the HEROIC project (216035/Z/19/Z) from the Wellcome Trust,
   which funds O.B. and C.H.S.
CR Arbuthnott KG, 2017, ENVIRON HEALTH-GLOB, V16, P1, DOI 10.1186/s12940-017-0322-5
   Bell S, 2015, WEATHER, V70, P75, DOI 10.1002/wea.2316
   Benmarhnia T, 2015, EPIDEMIOLOGY, V26, P781, DOI 10.1097/EDE.0000000000000375
   Brousse O, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac5c0f
   Brousse O, 2023, J APPL METEOROL CLIM, V62, P1539, DOI 10.1175/JAMC-D-22-0142.1
   Burkart K, 2016, ENVIRON HEALTH PERSP, V124, P927, DOI 10.1289/ehp.1409529
   Chapman L, 2017, INT J CLIMATOL, V37, P3597, DOI 10.1002/joc.4940
   Chen JY, 2021, Q J ROY METEOR SOC, V147, P3647, DOI 10.1002/qj.4146
   Cheng WW, 2021, SCI TOTAL ENVIRON, V799, DOI 10.1016/j.scitotenv.2021.149417
   Ching J, 2018, B AM METEOROL SOC, V99, P1907, DOI 10.1175/BAMS-D-16-0236.1
   Christen A., 2017, Urban Climates, pi, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Coney J, 2022, METEOROL APPL, V29, DOI 10.1002/met.2075
   Crichton D., 1999, Nat Disaster Manag, P102
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   de Vos LW, 2020, B AM METEOROL SOC, V101, pE167, DOI 10.1175/BAMS-D-19-0091.1
   de Vos LW, 2019, GEOPHYS RES LETT, V46, P8820, DOI 10.1029/2019GL083731
   Demuzere M, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0214474
   Dessai S, 2022, CLIM RISK MANAG, V37, DOI 10.1016/j.crm.2022.100440
   Dinku T., 2019, Extrem Hydrol. Clim. Var. Monit. Model Adapt Mitig, P71, DOI [10.1016/B978-0-12-8159989.00007-5, DOI 10.1016/B978-0-12-8159989.00007-5, DOI 10.1016/B978-0-12-815998-9.00007-5]
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   Estellés-Arolas E, 2012, J INF SCI, V38, P189, DOI 10.1177/0165551512437638
   Fenner D, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.720747
   Fenner D, 2017, METEOROL Z, V26, P525, DOI 10.1127/metz/2017/0861
   Fouillet A, 2006, INT ARCH OCC ENV HEA, V80, P16, DOI 10.1007/s00420-006-0089-4
   Garcia-Marti I, 2023, INT J CLIMATOL, V43, P275, DOI 10.1002/joc.7757
   Grellier J, 2017, BMJ OPEN, V7, DOI 10.1136/bmjopen-2017-016188
   Grimmond S., 2013, Tech. Rep.
   Hajat S, 2007, OCCUP ENVIRON MED, V64, P93, DOI 10.1136/oem.2006.029017
   Hammerberg K, 2018, INT J CLIMATOL, V38, pE1241, DOI 10.1002/joc.5447
   Heaviside Clare, 2017, Curr Environ Health Rep, V4, P296, DOI 10.1007/s40572-017-0150-3
   Heaviside C, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0100-9
   Hinkel KM, 2003, INT J CLIMATOL, V23, P1889, DOI 10.1002/joc.971
   Hintz KS, 2019, ATMOS SCI LETT, V20, DOI 10.1002/asl.921
   Hondula DM, 2012, ENVIRON HEALTH-GLOB, V11, DOI 10.1186/1476-069X-11-16
   Huete A, 2002, REMOTE SENS ENVIRON, V83, P195, DOI 10.1016/S0034-4257(02)00096-2
   Iungman T, 2023, LANCET, V401, P577, DOI 10.1016/S0140-6736(22)02585-5
   Kaiser A, 2016, ECOL EVOL, V6, P4129, DOI 10.1002/ece3.2166
   Kendon M., 2022, UNPRECEDENTED EXTREM
   Kidd C, 2017, B AM METEOROL SOC, V98, P69, DOI 10.1175/BAMS-D-14-00283.1
   Kovats RS, 2004, OCCUP ENVIRON MED, V61, P893, DOI 10.1136/oem.2003.012047
   Li SC, 2015, INFORM SYST FRONT, V17, P243, DOI 10.1007/s10796-014-9492-7
   Liao ZM, 2015, J APPL REMOTE SENS, V9, DOI 10.1117/1.JRS.9.096068
   Macintyre HL, 2018, SCI TOTAL ENVIRON, V610, P678, DOI 10.1016/j.scitotenv.2017.08.062
   McLennan D, 2019, Technical report
   Meier F, 2017, URBAN CLIM, V19, P170, DOI 10.1016/j.uclim.2017.01.006
   Mitchell TD, 2024, INT J CLIMATOL, V44, P1409, DOI 10.1002/joc.8390
   Murage P, 2024, ENVIRON INT, V183, DOI 10.1016/j.envint.2023.108391
   Napoly A, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00118
   O'Hara T, 2023, HYDROL RES, V54, P547, DOI 10.2166/nh.2023.136
   Office for National Statistics, 2011, Office for National Statistics: 2011 Census geography products for England and Wales
   Paavola J, 2017, ENVIRON HEALTH-GLOB, V16, P61, DOI 10.1186/s12940-017-0328-z
   Perkins SE, 2007, J CLIMATE, V20, P4356, DOI 10.1175/JCLI4253.1
   Pesaresi M, 2013, IEEE J-STARS, V6, P2102, DOI 10.1109/JSTARS.2013.2271445
   Potgieter J, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.720323
   Robinson C, 2022, ANN AM ASSOC GEOGR, V112, P2152, DOI 10.1080/24694452.2022.2077169
   Robinson C, 2021, T I BRIT GEOGR, V46, P238, DOI 10.1111/tran.12415
   Saverino KC, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031511
   Schaaf C., 2015, NASA EOSDIS LAND PRO, DOI [10.5067/MODIS/MCD43A3.006, DOI 10.5067/MODIS/MCD43A3.006]
   Son NT, 2014, AGR FOREST METEOROL, V197, P52, DOI 10.1016/j.agrformet.2014.06.007
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Tomlinson CJ, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-42
   van de Giesen N, 2014, WIRES WATER, V1, P341, DOI 10.1002/wat2.1034
   Varentsov M, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.716968
   Venter ZS, 2020, LANDSCAPE URBAN PLAN, V203, DOI 10.1016/j.landurbplan.2020.103889
   Wolf T, 2013, WEATHER CLIM EXTREME, V1, P59, DOI 10.1016/j.wace.2013.07.004
   Xu ZW, 2014, INT J BIOMETEOROL, V58, P239, DOI 10.1007/s00484-013-0655-x
NR 66
TC 2
Z9 2
U1 3
U2 3
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
EI 2041-1723
J9 NAT COMMUN
JI Nat. Commun.
PD JUN 20
PY 2024
VL 15
IS 1
AR 4828
DI 10.1038/s41467-024-49276-z
PG 11
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA WA1N2
UT WOS:001252057400015
PM 38902290
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Miao, Q
   Feeney, MK
   Zhang, FX
   Welch, EW
   Sriraj, PS
AF Miao, Qing
   Feeney, Mary K.
   Zhang, Fengxiu
   Welch, Eric W.
   Sriraj, P. S.
TI Through the storm: Transit agency management in response to climate
   change
SO TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
LA English
DT Article
DE Public transit; Extreme weather; Risk perceptions; Climate adaptation;
   Climate change
ID IMPACT; WEATHER; ADAPTATION; TRANSPORT; RESILIENCE; RIDERSHIP;
   PERFORMANCE
AB The increase in extreme weather events due to climate change poses serious challenges to public transit systems. These events disrupt transit operations, impair service quality, increase threats to public safety, and damage infrastructure. Despite the growing risk of extreme weather and climate change, little is known about how public managers recognize, experience and address these risks. Using data from a national study of public transit agencies we investigate the types of extreme weather events transit agencies are experiencing, the associated risks, and how agencies are preparing for them. We find that while extreme events are commonly experienced by transit agencies across states and transit managers perceive increased risks from these events, most agencies rely on the traditional emergency management approach to address extreme weather ex post rather than taking a proactive approach to mitigating the adverse weather impact on transit assets and infrastructure ex ante. Managers report that a lack of access to financial resources is the greatest challenge for undertaking adaptation and preparation. We conclude with a discussion of what these findings mean for understanding organizational adaptation behavior as well as climate adaptation policy making.
C1 [Miao, Qing] Rochester Inst Technol, Dept Publ Policy, 3242 Eastman Hall,92 Lomb Mem Dr, Rochester, NY 14623 USA.
   [Feeney, Mary K.; Zhang, Fengxiu; Welch, Eric W.] Arizona State Univ, Ctr Sci Technol & Environm Policy Studies, Tempe, AZ 85287 USA.
   [Sriraj, P. S.] Univ Illinois, Urban Transportat Ctr, Metropolitan Transportat Support Initiat METSI, Chicago, IL 60680 USA.
C3 Rochester Institute of Technology; Arizona State University; Arizona
   State University-Tempe; University of Illinois System; University of
   Illinois Chicago; University of Illinois Chicago Hospital
RP Miao, Q (corresponding author), Rochester Inst Technol, Dept Publ Policy, 3242 Eastman Hall,92 Lomb Mem Dr, Rochester, NY 14623 USA.
EM qxmgla@rit.edu
RI Feeney, Mary/I-4689-2019; Welch, Eric/D-5097-2015
OI Sriraj, P S/0000-0002-0013-205X; Zhang, Fengxiu/0000-0001-5784-9708
FU Federal Transit Administration, US Department of Transportation through
   the Metropolitan Transportation Support Initiative at UIC for 2015-2016
FX This study was funded by the Federal Transit Administration, US
   Department of Transportation through the Metropolitan Transportation
   Support Initiative at UIC for 2015-2016.
CR Adger WN, 2011, WIRES CLIM CHANGE, V2, P757, DOI 10.1002/wcc.133
   [Anonymous], 2003, 21 SESS IPCC VIENN A, DOI DOI 10.4324/9781315270326-109
   [Anonymous], NEW YORK DAILY NEWS
   [Anonymous], 2013, NY TIMES
   [Anonymous], 2017, BILL DOLL WEATH CLIM
   Arana P, 2014, TRANSPORT RES A-POL, V59, P1, DOI 10.1016/j.tra.2013.10.019
   Bedsworth L.W., 2008, Climate change and California's local public health agencies
   Berkhout F, 2012, WIRES CLIM CHANGE, V3, P91, DOI 10.1002/wcc.154
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Changnon SA, 1996, CLIMATIC CHANGE, V32, P481, DOI 10.1007/BF00140357
   Chapman L, 2007, J TRANSP GEOGR, V15, P354, DOI 10.1016/j.jtrangeo.2006.11.008
   Chung J, 2013, SEVERE WEATHER ADVIS
   Cravo V.S., 2009, P 88 ANN M TRANSPORT
   DOT, 2014, ENS TRANSP INFR SYST
   Eiser JR, 2012, INT J DISAST RISK RE, V1, P5, DOI 10.1016/j.ijdrr.2012.05.002
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Guo Z, 2007, TRANSPORT RES REC, P3, DOI 10.3141/2034-01
   Hegerl GC, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P663
   Hodges T., 2011, 0001 FED TRANS ADM
   Jochem P, 2016, TRANSPORT RES D-TR E, V45, P1, DOI 10.1016/j.trd.2016.03.001
   Kalkstein AJ, 2009, J TRANSP GEOGR, V17, P198, DOI 10.1016/j.jtrangeo.2008.07.003
   Koch J., 2013, TRANSP RES BOARD 92
   Koetse MJ, 2009, TRANSPORT RES D-TR E, V14, P205, DOI 10.1016/j.trd.2008.12.004
   Linnenluecke MK, 2012, BUS STRATEG ENVIRON, V21, P17, DOI 10.1002/bse.708
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Pregnolato M, 2017, TRANSPORT RES D-TR E, V55, P67, DOI 10.1016/j.trd.2017.06.020
   Quinn F. H., 2003, POTENTIAL IMPACTS CL
   Singhal A, 2014, TRANSPORT RES A-POL, V69, P379, DOI 10.1016/j.tra.2014.09.008
   Smithers J, 1997, GLOBAL ENVIRON CHANG, V7, P129, DOI 10.1016/S0959-3780(97)00003-4
   Stamos I, 2015, TRANSPORT RES D-TR E, V34, P168, DOI 10.1016/j.trd.2014.11.002
   Stover VW, 2012, J PUBLIC TRANSPORT, V15, P95, DOI 10.5038/2375-0901.15.1.6
   Suarez P, 2005, TRANSPORT RES D-TR E, V10, P231, DOI 10.1016/j.trd.2005.04.007
   Thomson Barbara, 2017, MANAGING EXTREME WEA
   Tribbia J, 2008, ENVIRON SCI POLICY, V11, P315, DOI 10.1016/j.envsci.2008.01.003
   Winn MI, 2011, BUS STRATEG ENVIRON, V20, P157, DOI 10.1002/bse.679
   Xia YN, 2013, TRANSPORT RES D-TR E, V18, P97, DOI 10.1016/j.trd.2012.09.008
   Zhang FX, 2018, J PUBL ADM RES THEOR, V28, P371, DOI 10.1093/jopart/muy004
NR 38
TC 24
Z9 28
U1 9
U2 36
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 1361-9209
J9 TRANSPORT RES D-TR E
JI Transport. Res. Part D-Transport. Environ.
PD AUG
PY 2018
VL 63
BP 421
EP 432
DI 10.1016/j.trd.2018.06.005
PG 12
WC Environmental Studies; Transportation; Transportation Science &
   Technology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Transportation
GA GR8MM
UT WOS:000442978000027
DA 2025-01-10
ER

PT J
AU Prosser, IP
   Chiew, FHS
   Smith, MS
AF Prosser, Ian P.
   Chiew, Francis H. S.
   Stafford Smith, Mark
TI Adapting Water Management to Climate Change in the Murray-Darling Basin,
   Australia
SO WATER
LA English
DT Article
DE climate change; water policy; climate adaptation; Murray-Darling Basin
ID RAINFALL; IMPACT; ADAPTATION; RUNOFF; STREAMFLOW; STATIONARITY;
   UNCERTAINTY; VARIABILITY; ECOSYSTEMS; GOVERNANCE
AB Climate change is threatening water security in water-scarce regions across the world, challenging water management policy in terms of how best to adapt. Transformative new approaches have been proposed, but management policies remain largely the same in many instances, and there are claims that good current management practice is well adapted. This paper takes the case of the Murray-Darling Basin, Australia, where management policies are highly sophisticated and have been through a recent transformation in order to critically review how well adapted the basin's management is to climate change. This paper synthesizes published data, recent literature, and water plans in order to evaluate the outcomes of water management policy. It identifies several limitations and inequities that could emerge in the context of climate change and, through synthesis of the broader climate adaptation literature, proposes solutions that can be implemented when basin management is formally reviewed in 2026.
C1 [Prosser, Ian P.] Univ Canberra, Ctr Appl Water Sci, Bruce, ACT 2617, Australia.
   [Chiew, Francis H. S.; Stafford Smith, Mark] CSIRO Land & Water, Black Mt, ACT 2601, Australia.
C3 University of Canberra; Commonwealth Scientific & Industrial Research
   Organisation (CSIRO)
RP Prosser, IP (corresponding author), Univ Canberra, Ctr Appl Water Sci, Bruce, ACT 2617, Australia.
EM ian.prosser@canberra.edu.au; mark.staffordsmith@csiro.au;
   mark.staffordsmith@csiro.au
RI Smith, Mark/G-1680-2010; Chiew, Francis/A-9743-2011; Prosser,
   Ian/F-5760-2013
OI Prosser, Ian/0000-0001-7252-1540; Stafford Smith,
   Mark/0000-0002-1333-3651; Chiew, Francis/0000-0001-8020-8773
CR Abram NJ, 2020, NATURE, V579, P385, DOI 10.1038/s41586-020-2084-4
   Alexandra J, 2020, ENVIRON SCI POLICY, V112, P17, DOI 10.1016/j.envsci.2020.05.022
   Allan C, 2013, CURR OPIN ENV SUST, V5, P625, DOI 10.1016/j.cosust.2013.09.004
   [Anonymous], 2019, FINAL REPORT INDEPEN
   [Anonymous], 2008, REPORT AUSTR GOVT CS
   Bates BC, 2008, CLIMATIC CHANGE, V89, P339, DOI 10.1007/s10584-007-9390-9
   Bino G, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0132682
   BOM CSIRO, 2020, STAT CLIM
   Brookhouse MT, 2013, WATER RESOUR RES, V49, P4493, DOI 10.1002/wrcr.20351
   Carmody E., 2019, ANAL ARE OUR WATER L
   Charles SP, 2020, HYDROL EARTH SYST SC, V24, P2981, DOI 10.5194/hess-24-2981-2020
   Cheng L, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-00114-5
   Chiew F., 2017, MODSIM, P1745
   Chiew FHS, 2014, STOCH ENV RES RISK A, V28, P3, DOI 10.1007/s00477-013-0755-5
   Chiew FHS, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR007338
   Chiew F. H. S., 2011, WATER RESOURCES PLAN, P439
   Chiew FHS, 2002, HYDROLOG SCI J, V47, P505, DOI 10.1080/02626660209492950
   Chiew FHS, 2006, HYDROLOG SCI J, V51, P613, DOI 10.1623/hysj.51.4.613
   COAG, 2019, COUNC AUSTR GOV M CO
   Cobb KM, 2003, NATURE, V424, P271, DOI 10.1038/nature01779
   Commonwealth Environmental Water Office, COMM ENV WAT HOLD CA
   Cradock-Henry NA, 2021, ELEMENTA-SCI ANTHROP, V9, DOI 10.1525/elementa.2020.00175
   CSIRO Climate Compass, 2018, CLIMATE RISK MANAGEM
   CSIRO Water, 2008, REP CSIRO AUSTR GOV
   Davies A., 2020, GEOGRAPHIES ANTICOLO
   Doolan J., 2016, The Australian water reform journey: An overview of three decades of policy, management and institutional transformation
   Dovers SR, 2010, WIRES CLIM CHANGE, V1, P212, DOI 10.1002/wcc.29
   Dyson M., 2021, MURRAY DARLING BASIN, P163
   Ekstrom Marie, 2016, Climate Services, V4, P13, DOI 10.1016/j.cliser.2016.09.003
   Flack AL, 2020, HYDROL EARTH SYST SC, V24, P5699, DOI 10.5194/hess-24-5699-2020
   Fowler K, 2015, AUSTRALAS J WAT RESO, V19, P96, DOI 10.1080/13241583.2015.1116182
   Gallant AJE, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009832
   Gibbs MT, 2020, OCEAN COAST MANAGE, V190, DOI 10.1016/j.ocecoaman.2020.105150
   Gibbs MT, 2013, OCEAN COAST MANAGE, V85, P119, DOI 10.1016/j.ocecoaman.2013.09.001
   Grafton RQ, 2014, AMBIO, V43, P1082, DOI 10.1007/s13280-014-0495-x
   Grose MR, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001469
   Grose MR, 2019, CLIM DYNAM, V53, P3675, DOI 10.1007/s00382-019-04736-x
   Gupta M., 2020, Future scenarios for the southern MurrayDarling Basin report to the independent assessment of social and economic conditions in the basin (Issue February), DOI [10.25814/5e5c8daaa823a, DOI 10.25814/5E5C8DAAA823A]
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Hart B.T., 2021, Murray-Darling Basin, Australia, P389
   Hart BT, 2016, ECOHYDROL HYDROBIOL, V16, P229, DOI 10.1016/j.ecohyd.2016.09.002
   Horne AC, 2019, BIOSCIENCE, V69, P789, DOI 10.1093/biosci/biz087
   Horne J, 2017, WATER INT, V42, P1000, DOI 10.1080/02508060.2017.1412201
   Horne J, 2014, INT J WATER RESOUR D, V30, P152, DOI 10.1080/07900627.2013.787833
   Hughes JD, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050797
   Huntjens P, 2012, GLOBAL ENVIRON CHANG, V22, P67, DOI 10.1016/j.gloenvcha.2011.09.015
   Cisneros BEJ, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P229
   Keelty M.J.A.O., 2020, IMPACT LOWER INFLOWS
   Kirby M, 2014, AGR WATER MANAGE, V145, P154, DOI 10.1016/j.agwat.2014.02.013
   Kirono DGC, 2020, WEATHER CLIM EXTREME, V30, DOI 10.1016/j.wace.2020.100280
   Kirsch E, 2022, MAR FRESHWATER RES, V73, P1225, DOI 10.1071/MF21036
   Linke S, 2019, AQUAT CONSERV, V29, P1149, DOI 10.1002/aqc.3162
   Malekpour S, 2020, ENVIRON SCI POLICY, V107, P158, DOI 10.1016/j.envsci.2020.03.002
   Marshall GR, 2010, RANGELAND J, V32, P267, DOI 10.1071/RJ10020
   Matthews Ken., 2017, INDEPENDENT INVESTIG
   MDBA, 2019, CLIM CHANG MURR DARL
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Murray-Darling Basin Authority (MDBA), 2020, 2020 BAS PLAN EV
   Neave I., 2015, Water J. Aust. Water Assoc, V42, P102
   NSW, 2021, DPIE DRAFT REG WAT S
   Pahl-Wostl C, 2011, WATER RESOUR MANAG, V25, P837, DOI 10.1007/s11269-010-9729-2
   Peel MC, 2004, J HYDROL, V295, P185, DOI 10.1016/j.jhydrol.2004.03.004
   Peterson TJ, 2021, SCIENCE, V372, P745, DOI 10.1126/science.abd5085
   Pittock J., 2015, WATER-SUI, V42, P28, DOI [DOI 10.3316/INFORMIT.603377005698763, 10.3316/informit.603377005698763]
   Post DA, 2014, EARTHS FUTURE, V2, P231, DOI 10.1002/2013EF000194
   Potter NJ, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR010333
   Potter NJ, 2010, J HYDROL, V381, P52, DOI 10.1016/j.jhydrol.2009.11.025
   Potter NJ, 2020, HYDROL EARTH SYST SC, V24, P2963, DOI 10.5194/hess-24-2963-2020
   Productivity Commission, 2018, MURR DARL BAS PLAN 5
   Qureshi ME, 2018, WATER ECON POLICY, V4, DOI 10.1142/S2382624X15500204
   Rauniyar SP, 2020, J CLIMATE, V33, P8087, DOI 10.1175/JCLI-D-19-0759.1
   Reeder T., 2011, YOU ADAPT UNCERTAIN
   Saft M, 2016, WATER RESOUR RES, V52, P9290, DOI 10.1002/2016WR019525
   Sefton R, 2020, Independent assessment of social and economic conditions in the Murray-Darling Basin
   Siebentritt M., 2014, Regional climate change adaptation plan for the Eyre Peninsula
   Siebentritt M., 2016, A User's Guide To Applied Adaptation Pathways Version 1
   Slatyer Anthony, 2021, Murray-Darling Basin, Australia: Its Future Management, P275
   Smith MS, 2011, PHILOS T R SOC A, V369, P196, DOI 10.1098/rsta.2010.0277
   Stewardson MJ., 2021, Murray-Darling basin, P47, DOI [10.1016/B978-0-12-818152-2.00003-6, DOI 10.1016/B978-0-12-818152-2.00003-6]
   Swirepik JL, 2016, RIVER RES APPL, V32, P1153, DOI 10.1002/rra.2975
   Timbal B, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009834
   Tomkins KM, 2014, HYDROL PROCESS, V28, P464, DOI 10.1002/hyp.9567
   Tonkin JD, 2019, NATURE, V570, P301, DOI 10.1038/d41586-019-01877-1
   Ukkola AM, 2016, NAT CLIM CHANGE, V6, P75, DOI [10.1038/nclimate2831, 10.1038/NCLIMATE2831]
   UNESCO, 2020, UNW UN WORLD WAT DEV
   Uni. Melbourne, 2020, VICT WAT CHANG CLIM
   van Dijk AIJM, 2013, WATER RESOUR RES, V49, P1040, DOI 10.1002/wrcr.20123
   Vörösmarty CJ, 2010, NATURE, V467, P555, DOI 10.1038/nature09440
   Walker Bret., 2019, Murray-Darling Basin royal commission report
   Walker G, WATER-SUI
   Walker GR, 2021, WATER-SUI, V13, DOI 10.3390/w13101366
   Walker WE, 2013, SUSTAINABILITY-BASEL, V5, P955, DOI 10.3390/su5030955
   Wentworth Group of Concerned Scientists, 2020, ASS RIV FLOWS MURR D
   Whetton P., 2021, Murray-Darling Basin, Australia, P253, DOI DOI 10.1016/B978-0-12-818152-2.00012-7
   WSAA, 2016, CLIMATE CHANGE ADAPT
   Zheng H., 2019, MODSIM 2019 INT C MO, P1000, DOI DOI 10.36334/MODSIM.2019.K7.ZHENGH
NR 96
TC 45
Z9 47
U1 7
U2 30
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD SEP
PY 2021
VL 13
IS 18
AR 2504
DI 10.3390/w13182504
PG 19
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA UY4YM
UT WOS:000701531200001
OA gold
DA 2025-01-10
ER

PT J
AU van der Plank, S
   Addo, KA
   Anderson, R
   Boruff, B
   Bruce, E
   Chambers, K
   Duncan, J
   Davies, K
   Escoffery, D
   Fidai, Y
   Fletcher, D
   Hickey, S
   Jayson-Quashigah, PN
   Maxam, A
   Pauli, N
   Schlenker, M
   Sowah, WNA
   Dash, J
AF van der Plank, Sien
   Addo, Kwasi Appeaning
   Anderson, Romario
   Boruff, Bryan
   Bruce, Eleanor
   Chambers, Kishna
   Duncan, John
   Davies, Kevin
   Escoffery, Damoi
   Fidai, Yanna
   Fletcher, Darren
   Hickey, Sharyn
   Jayson-Quashigah, Philip-Neri
   Maxam, Ava
   Pauli, Natasha
   Schlenker, Marie
   Sowah, Winnie Naa Adjorkor
   Dash, Jadu
TI The 'More Than Maps' framework for building research capacity among
   young people in coastal climate change adaptation
SO AREA
LA English
DT Article
DE adaptation; capacity building; climate change; coastal hazards;
   education; young people
AB When young people engage with climate change education, they are often left feeling disempowered and daunted. But past research has shown that there are ways to design and deliver climate change education that can be empowering and enabling. The delivery of climate change education was further challenged in 2020 by the shift to online learning driven by the COVID-19 pandemic restrictions. However, the challenges of the pandemic context also offered an opportunity to engage new audiences and establish new collaborations in climate change education. In this paper, we explore how the shift to online research, collaboration and education can also be harnessed to develop interdisciplinary coastal adaptation training for young people interested in better understanding the complexities of our coastal environments. The resulting 'More than Maps' framework draws on qualitative and quantitative data collected over a two-year programme focused on the design and delivery of an international climate change research capacity building workshop series, across the United Kingdom, Ghana, Jamaica and Australia. Carried out by an interdisciplinary team of early career researchers and established academics, 15 workshops were developed on coastal adaptation research methods, targeting a range of 'young' audiences who are and will continue to be impacted by climate change. Building on reflections from the workshops' design and delivery, we developed a scalable framework to aid researchers in sharing open-access, replicable methods for studying climate change mitigation and adaptation. This work demonstrates that our workshop participants had increased confidence, sought to apply learned methods to other contexts, and wanted to share this knowledge with others. We conclude that the COVID-19 online workspace facilitated rather than hindered the international collaboration and delivery of these coastal adaptation research methods workshops, and we provide best practice tips to researchers delivering climate change education.
   When young people engage with climate change education, they are often left feeling disempowered and daunted. The delivery of climate change education was further challenged in 2020 by the shift to online learning driven by the COVID-19 pandemic restrictions. We conclude that the COVID-19 online workspace facilitated rather than hindered the international collaboration and delivery of coastal adaptation research methods workshops, and we provide a best practice framework for developing science skills-based capacity building resources.image
C1 [van der Plank, Sien; Fidai, Yanna; Dash, Jadu] Univ Southampton, Sch Geog & Environm Sci, Southampton, England.
   [Addo, Kwasi Appeaning; Jayson-Quashigah, Philip-Neri] Univ Ghana, Inst Environm & Sanitat Studies, Accra, Ghana.
   [Anderson, Romario; Chambers, Kishna; Escoffery, Damoi; Fletcher, Darren; Maxam, Ava] Univ West Indies, Mona Geoinformat Inst, Kingston, Jamaica.
   [Boruff, Bryan; Duncan, John; Hickey, Sharyn; Pauli, Natasha] Univ Western Australia, Perth, WA, Australia.
   [Bruce, Eleanor; Davies, Kevin] Univ Sydney, Camperdown, NSW, Australia.
   [Schlenker, Marie] Univ Southampton, Fac Engn & Phys Sci, Southampton, England.
   [Sowah, Winnie Naa Adjorkor] Univ Ghana, Accra, Ghana.
   [van der Plank, Sien] Univ Southampton, Sch Geog & Environm Sci, Univ Rd, Southampton SO17 1BJ, England.
   [Maxam, Ava] Inst Marine Affairs Trinidad & Tobago, Chaguaramas, Trinidad Tobago.
C3 University of Southampton; University of Ghana; University West Indies
   Mona Jamaica; University of Western Australia; University of Sydney;
   University of Southampton; University of Ghana; University of
   Southampton
RP van der Plank, S (corresponding author), Univ Southampton, Sch Geog & Environm Sci, Univ Rd, Southampton SO17 1BJ, England.
EM sien.vanderplank@soton.ac.uk
RI Hickey, Sharyn/AGZ-1731-2022; Bruce, Eleanor/AAP-4305-2020; Addo,
   Kwasi/AAP-9556-2020; Pauli, Natasha/H-5605-2014
OI Pauli, Natasha/0000-0002-1145-7458; Van Der Plank,
   Sien/0000-0001-6650-4111; Dash, Jadunandan/0000-0002-5444-2109;
   Schlenker, Marie/0000-0002-3254-6353; Hickey,
   Sharyn/0000-0001-8914-4155; Fidai, Yanna Alexia/0000-0003-3561-4718;
   Duncan, John/0000-0001-9752-1002; Boruff, Bryan/0000-0001-6693-0671;
   Davies, Kevin/0000-0003-2170-7008; Sowah, Winnie Naa
   Adjorkor/0000-0003-0093-0091
FU Economic and Social Research Council [UKRI ESRC ES/W006189/1,
   ES/T002964/1]; British Council; Australian Government [2020-2021];
   University of Southampton Public Engaging with Research unit seed
   funding; Festival of Social Sciences [2022]; ESRC [ES/W006189/1] Funding
   Source: UKRI; GCRF [ES/T002964/1] Funding Source: UKRI; NERC
   [NE/X018490/1] Funding Source: UKRI
FX The author team wish to thank Professor Jack Corbett, Professor Emma
   Tompkins, Dr Heather Brown and Camilla Rous for their contributions to
   this project, as well as university staff from outreach, education and
   public engagement units who have contributed their time and expertise.
   The authors thank the anonymous reviewers whose useful comments helped
   improve the manusript. This work was funded through UKRI ESRC
   ES/W006189/1 and ES/T002964/1, and supported by the British Council and
   the Australian Government as part of the UK/Australia Season. The work
   also received financial support from the University of Southampton
   Public Engaging with Research unit seed funding (2020-2021), and the
   Festival of Social Sciences (2020, 2022).
CR Bryson JR, 2020, J GEOGR HIGHER EDUC, V44, P608, DOI 10.1080/03098265.2020.1807478
   Busch IM, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192013357
   Darlington E, 2015, AREA, V47, P481, DOI 10.1111/area.12227
   Dawson V, 2020, RES SCI EDUC, V50, P863, DOI 10.1007/s11165-018-9715-x
   Dever M., 2006, RES WORKS WOMEN
   Hendriks F, 2022, SCI COMMUN, V44, P693, DOI 10.1177/10755470221137052
   Jones CA, 2023, WIRES CLIM CHANGE, V14, DOI 10.1002/wcc.853
   Jones CA, 2021, GEOFORUM, V118, P190, DOI 10.1016/j.geoforum.2020.11.006
   Kelly R, 2022, ONE EARTH, V5, P861, DOI 10.1016/j.oneear.2022.07.007
   McBean G, 2010, WIRES CLIM CHANGE, V1, P871, DOI 10.1002/wcc.77
   McKenzie L., 2021, Researchers at risk: precarity, jeopardy and uncertainty in academia, P115, DOI [10.1007/978-3-030-53857-68, DOI 10.1007/978-3-030-53857-68, DOI 10.1007/978-3-030-53857-6_8]
   Nicholls RJ, 2021, NAT CLIM CHANGE, V11, P338, DOI 10.1038/s41558-021-00993-z
   Pontee N, 2013, OCEAN COAST MANAGE, V84, P204, DOI 10.1016/j.ocecoaman.2013.07.010
   Puvirajah A, 2015, INT J SCI EDUC PART, V5, P250, DOI 10.1080/21548455.2014.930210
   Reeves J., 2020, INSPIRING COLLABORAT
   Roche J, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.662947
   Rousell D, 2020, CHILD GEOGR, V18, P191, DOI 10.1080/14733285.2019.1614532
   Schrot OG, 2021, CLIM RISK MANAG, V33, DOI 10.1016/j.crm.2021.100327
   Talia M, 2021, INT J PUBLIC THEOL, V15, P595, DOI 10.1163/15697320-01
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Wallis H, 2021, J ENVIRON PSYCHOL, V74, DOI 10.1016/j.jenvp.2021.101581
NR 21
TC 0
Z9 0
U1 2
U2 3
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0004-0894
EI 1475-4762
J9 AREA
JI Area
PD JUN
PY 2024
VL 56
IS 2
DI 10.1111/area.12919
EA JAN 2024
PG 13
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA OR4Y9
UT WOS:001152158100001
OA hybrid
DA 2025-01-10
ER

PT J
AU Kirina, T
   Groot, A
   Shilomboleni, H
   Ludwig, F
   Demissie, T
AF Kirina, Thomas
   Groot, Annemarie
   Shilomboleni, Helena
   Ludwig, Fulco
   Demissie, Teferi
TI Scaling Climate Smart Agriculture in East Africa: Experiences and
   Lessons
SO AGRONOMY-BASEL
LA English
DT Article
DE climate-smart agriculture; scaling; partnerships; East Africa
ID CROP-LIVESTOCK SYSTEMS; CONSERVATION AGRICULTURE; SMALLHOLDER FARMERS;
   CHANGE ADAPTATION; BUSINESS MODELS; FOOD SECURITY; TECHNOLOGIES;
   INNOVATIONS; INTERVENTIONS; DETERMINANTS
AB Climate-smart agriculture (CSA) responds in order to sustain agriculture under a changing environment, and is a major priority in the development sphere. However, to achieve impact at scale, CSA innovations must address agricultural systems' context-specific and multi-dimensional nature and be purveyed through feasible scaling processes. Unfortunately, knowledge on the scaling of CSA innovations under smallholder farming systems and in the context of developing countries remains scant. Understanding scaling processes is essential to the design of a sustainable scaling strategy. This study aimed to draw lessons on scaling from 25 cases of scaling CSA, and related projects in Ethiopia, Kenya, Uganda, and Tanzania implemented by public institutions, local and international research organisations, Non-Govermental Orginsations(NGOs), and community-based organisations. Generally, scaling follows a linear pathway comprising technology testing and scaling. Most cases promoted technologies and models geared towards climate change adaptation in crop-based value chains, and only a few cases incorporated mitigation measures. Efforts to engage the private sector involved building business models as a potential scaling pathway. The cases were very strong on capacity building and institutionalisation from local, national, and even regional levels. However, four critical areas of concern about the sustainability of scaling emerged from the study: (i) There is little understanding and capture of the dynamics of smallholder farming systems in scaling strategies; (ii) climate data, projections, and impact models are rarely applied to support the decision of scaling; (iii) considerations for the biophysical and spatial-temporal impacts and trade-offs analysis in scaling is minimal and just starting to emerge; and (iv) there are still challenges effecting systemic change to enable sustainable scaling. In response to these concerns, we propose investment in understanding and considering the dynamics of the smallholder farming system and how it affects adoption, and subsequently scaling. Programme design should incorporate climate change scenarios. Scaling programmes can maximise synergies and leverage resources by adopting a robust partnerships model. Furthermore, understanding the spatio-temporal impact of scaling CSA on ecological functioning deserves more attention. Lastly, scaling takes time, which needs to be factored into the design of programmes.
C1 [Kirina, Thomas; Ludwig, Fulco] Wageningen Univ & Res, Water Syst & Global Change WSG Grp, Wageningen Inst Environm & Climate Res WIMEK, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Groot, Annemarie] Wageningen Univ & Res, Environm Syst Anal Grp, Wageningen Inst Environm & Climate Res WIMEK, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Shilomboleni, Helena; Demissie, Teferi] Int Livestock Res Inst ILRI, Climate Change Agr & Food Secur Programme CCAFS, POB 30709, Nairobi 00100, Kenya.
C3 Wageningen University & Research; Wageningen University & Research;
   CGIAR; International Livestock Research Institute (ILRI)
RP Kirina, T (corresponding author), Wageningen Univ & Res, Water Syst & Global Change WSG Grp, Wageningen Inst Environm & Climate Res WIMEK, POB 47, NL-6700 AA Wageningen, Netherlands.
EM thomas.kirina@wur.nl; annemarie.groot@wur.nl; h.shilomboleni@cgiar.org;
   fulco.ludwig@wur.nl; teferidem@gmail.com
RI Ludwig, Fulco/N-7732-2013
OI groot, annemarie/0000-0002-7111-1088; Demissie,
   Teferi/0000-0002-0228-1972
FU Dutch Ministry of Foreign Affairs [4000000819]
FX This research was funded by Dutch Ministry of Foreign Affairs, Activity
   number 4000000819.
CR Abegunde VO, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12010195
   Abegunde VO, 2019, CLIMATE, V7, DOI 10.3390/cli7110132
   Abrams R.W., 2017, ENCY ANTHROPOCENE, P177
   Adenle AA, 2019, TECHNOL SOC, V58, DOI 10.1016/j.techsoc.2019.05.007
   Adenle AA, 2017, ECOL ECON, V141, P190, DOI 10.1016/j.ecolecon.2017.06.004
   African Union, 2014, MAL DECL ACC AGR GRO
   Aggarwal PK, 2018, ECOL SOC, V23, DOI 10.5751/ES-09844-230114
   Anandajayasekeram P., 2019, SCALING SCALABILITY
   Anderson J., 2016, NATL SURVEY SEGMENTA, P101
   Andrieu N, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00037
   [Anonymous], 2015, IFADS OP FRAM SCAL R
   [Anonymous], 2015, CLIM SMART AGR KEN
   [Anonymous], AFR AGR STAT REP 201
   [Anonymous], 2017, BUILDING RESILIENCE
   [Anonymous], 2016, Planning, implementing and evaluating Climate-Smart Agriculture in Smallholder Farming Systems The experience of the MICCA pilot projects in Kenya No
   Ara I., 2016, Agriculture and Food Security, P1, DOI [DOI 10.1186/S40066-016-0061-9, 10.1186/s40066-016-0061-9]
   Barker PM, 2016, IMPLEMENT SCI, V11, DOI 10.1186/s13012-016-0374-x
   Baudron F, 2015, FOOD SECUR, V7, P889, DOI 10.1007/s12571-015-0476-3
   Baudron F, 2014, AGR ECOSYST ENVIRON, V187, P171, DOI 10.1016/j.agee.2013.08.020
   Belotti F., 2014, SMALLHOLDER PRODUCTI, V16
   Biesbroek R, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.548
   Boons F, 2013, J CLEAN PROD, V45, P9, DOI 10.1016/j.jclepro.2012.07.007
   Burbridge M., 2017, BUSINESS MODELS SUST
   Call M, 2019, WORLD DEV, V115, P132, DOI 10.1016/j.worlddev.2018.11.009
   Chinse E, 2019, LAND DEGRAD DEV, V30, P533, DOI 10.1002/ldr.3190
   Cooley L., 2014, Taking Innovations to Scale: Methods, Applications, and Lessons
   Cooley L., 2016, WATER-SUI, P1
   Cooley L., 2018, SCALE SOURCEBOOK, P44
   Corbeels M, 2014, AGR ECOSYST ENVIRON, V187, P155, DOI 10.1016/j.agee.2013.10.011
   de Roo N, 2019, AGR SYST, V174, P52, DOI 10.1016/j.agsy.2019.04.004
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Descheemaeker K, 2019, EXP AGR, V55, P169, DOI 10.1017/S001447971600048X
   Descheemaeker K, 2016, REG ENVIRON CHANGE, V16, P2331, DOI 10.1007/s10113-016-0957-8
   Douthwaite B., 2007, The Canadian Journal of Program Evaluation, V22, P127, DOI [DOI 10.3138/CJPE.22.007, 10.3138/cjpe.22.007]
   EAC, 2011, E AFR COMM CLIM CHAN
   Enríquez-de-Salamanca A, 2017, ENVIRON IMPACT ASSES, V64, P87, DOI 10.1016/j.eiar.2017.03.005
   Etana D, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12114526
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   Farris J, 2017, AGR ECON-BLACKWELL, V48, P671, DOI 10.1111/agec.12365
   Garb Y, 2014, AGR SYST, V128, P13, DOI 10.1016/j.agsy.2014.04.003
   George R., 2015, EC LIVES SMALLHOLDER
   Giller KE, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00870
   Grassini P, 2017, GLOB FOOD SECUR-AGR, V14, P18, DOI 10.1016/j.gfs.2017.01.002
   Groot AE, 2019, J CLEAN PROD, V210, P1109, DOI 10.1016/j.jclepro.2018.11.054
   Hammond J, 2020, AGR SYST, V183, DOI 10.1016/j.agsy.2020.102857
   Hartmann A., 2008, 5 WOLF CTR DEV
   hartmann a., 2007, About IFPRI and the 2020 Vision Initiative, P549
   Hosman L, 2011, INFORM TECHNOL DEV, V17, P232, DOI 10.1080/02681102.2011.568225
   Jacobs F., 2018, SCALING SCAN PRACTIC, P35
   Jena PR, 2019, J CLEAN PROD, V218, P465, DOI 10.1016/j.jclepro.2019.01.278
   Kaweesa S, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103375
   Keddie J., 2016, IMPACT SCALE CHALLEN
   Keya S., 2013, P INT S AGR EAC PART, V5
   Kilelu C, 2017, EUR J DEV RES, V29, P1102, DOI 10.1057/s41287-016-0074-z
   Kimaro J, 2019, ADV METEOROL, V2019, DOI 10.1155/2019/9178136
   Kristjanson P, 2012, FOOD SECUR, V4, P381, DOI 10.1007/s12571-012-0194-z
   Lan L, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0207700
   Lee J, 2017, LAND USE POLICY, V68, P72, DOI 10.1016/j.landusepol.2017.07.020
   Liu TT, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10020432
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Lobell DB, 2014, GLOB FOOD SECUR-AGR, V3, P72, DOI 10.1016/j.gfs.2014.05.002
   Long TB, 2017, INT FOOD AGRIBUS MAN, V20, P5, DOI [10.22434/IFAMR2016.0081, 10.22434/ifamr2016.0081]
   Low JW, 2020, AGR SYST, V179, DOI 10.1016/j.agsy.2019.102770
   Lyon B, 2017, GEOPHYS MONOGR SER, V226, P265
   Makate C, 2019, ENVIRON SCI POLICY, V96, P37, DOI 10.1016/j.envsci.2019.01.014
   Martinez-Baron D, 2018, CURR OPIN ENV SUST, V31, P112, DOI 10.1016/j.cosust.2018.02.013
   Masud MM, 2017, J CLEAN PROD, V156, P698, DOI 10.1016/j.jclepro.2017.04.060
   Mdee A., 2014, POLITICS SMALL SCALE, P23
   Moher D, 2009, INT J SURG, V339, pb2535, DOI [DOI 10.1016/j.ijsu.2010.02.007, DOI 10.1016/J.IJSU.2010.02.007, 10.1136/bmj.b2535]
   Moore KM, 2014, J AGRIC EDUC EXT, V20, P291, DOI 10.1080/1389224X.2014.887758
   Murray R., 2017, FOLIA JPN OPHTHALMOL, V10, P1000
   Muthoni FK, 2017, LAND USE POLICY, V66, P34, DOI 10.1016/j.landusepol.2017.04.028
   Mwongera C, 2017, AGR SYST, V151, P192, DOI 10.1016/j.agsy.2016.05.009
   Ndoli A, 2018, FIELD CROP RES, V221, P238, DOI 10.1016/j.fcr.2018.03.003
   Neufeldt H., 2015, SCALING CLIMATE SMAR, P1
   Notenbaert A, 2017, AGR SYST, V151, P153, DOI 10.1016/j.agsy.2016.05.017
   Nyasimi M, 2017, CLIMATE, V5, DOI 10.3390/cli5030063
   Ochieng J, 2016, NJAS-WAGEN J LIFE SC, V77, P71, DOI 10.1016/j.njas.2016.03.005
   Ogot C., 2020, THESIS U NAIROBI NAI
   Orr A, 2018, J AGRIBUS DEV EMERG, V8, P14, DOI 10.1108/JADEE-03-2017-0031
   Owenya MZ, 2011, INT J AGR SUSTAIN, V9, P145, DOI 10.3763/ijas.2010.0557
   Paul BK, 2018, AGR SYST, V163, P16, DOI 10.1016/j.agsy.2017.02.007
   Picciotto R., 2013, SCALING DEV STRATEGY
   Prain G, 2020, AGR SYST, V182, DOI 10.1016/j.agsy.2020.102834
   Prestele R, 2020, GLOBAL CHANGE BIOL, V26, P1045, DOI 10.1111/gcb.14940
   Quail S., 2016, Climate Change and Multi-Dimensional Sustainability in African Agriculture, P525
   Ramirez-Villegas J., 2015, 119 CCAFS CGIAR
   Rosenstock T.S., 2018, CLIMATE SMART AGR PA
   Rosenstock T.S., 2014, SCI SUPPORT CLIMATE
   Rosenstock TS, 2014, AGR ECOSYST ENVIRON, V187, P47, DOI 10.1016/j.agee.2013.11.011
   Salami A., 2010, 105 AFR DEV BANK
   Sartas M, 2020, AGR SYST, V183, DOI 10.1016/j.agsy.2020.102874
   Sartas M, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0197993
   Schaller M., 2017, SCALING OUT CLIMATE
   Scherr S.J., 2012, Agriculture Food Security, V1, P1
   Schut M, 2020, AGR SYST, V184, DOI 10.1016/j.agsy.2020.102908
   Seifu M, 2020, AGR SYST, V182, DOI 10.1016/j.agsy.2020.102810
   Shikuku KM, 2017, CLIM RISK MANAG, V16, P234, DOI 10.1016/j.crm.2017.03.001
   Shikuku KM, 2019, WORLD DEV, V115, P94, DOI 10.1016/j.worlddev.2018.11.012
   Shilomboleni H, 2019, AGR SYST, V175, P58, DOI 10.1016/j.agsy.2019.05.012
   Shirsath PB, 2017, AGR SYST, V151, P174, DOI 10.1016/j.agsy.2016.09.018
   Snelder D., 2017, RAINWATER SMART AGR, P95
   Sova C.A., 2019, BRINGING CONCEPT CLI
   Teixeira S, 2018, QUAL SOC WORK, V17, P9, DOI 10.1177/1473325016655203
   TerrAfrica FAO, 2016, INF FUT INT SCAL UP, P38
   Thoai TQ, 2018, LAND USE POLICY, V70, P224, DOI 10.1016/j.landusepol.2017.10.023
   Totin E, 2020, AGR SYST, V179, DOI 10.1016/j.agsy.2019.102764
   Turkana County Government, 2016, TURK COUNT INV PLAN
   Twongyirwe R, 2019, WEATHER CLIM EXTREME, V24, DOI 10.1016/j.wace.2019.100201
   UNDP, 2013, GUID NOT SCAL DEV PR, P1
   Van Loon J, 2020, AGR SYST, V180, DOI 10.1016/j.agsy.2020.102792
   Wambugu C., 2014, OPTIONS CLIMATE SMAR, V185
   Westermann O, 2018, AGR SYST, V165, P283, DOI 10.1016/j.agsy.2018.07.007
   Wigboldus S., 2013, RESPONSIBLE SCALING, P65
   Wigboldus S, 2016, AGRON SUSTAIN DEV, V36, DOI 10.1007/s13593-016-0380-z
   Wohlin C., 2014, P EASE 14 18 INT C E
   Woltering L, 2019, AGR SYST, V176, DOI 10.1016/j.agsy.2019.102652
NR 117
TC 9
Z9 9
U1 4
U2 30
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4395
J9 AGRONOMY-BASEL
JI Agronomy-Basel
PD APR
PY 2022
VL 12
IS 4
AR 820
DI 10.3390/agronomy12040820
PG 30
WC Agronomy; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture; Plant Sciences
GA 0Q6KA
UT WOS:000785023900001
OA gold
DA 2025-01-10
ER

PT J
AU Thissen, P
AF Thissen, Paul
TI ESTATE LANDSCAPES IN GELDERLAND. GOVERNMENT INTERVENTIONS, PAST AND
   PRESENT
SO BULLETIN KNOB
LA Dutch
DT Article
AB The Province of Gelderland has long boasted a large number of country houses and landed estates, which over time coalesced into estate landscapes around the historical capitals of the Duchy of Guelders quarters of Nijmegen, Arnhem and Zutphen.
   Rapidly increasing urbanization from the end of the nineteenth century onwards threatened the coherence and accessibility of these landscapes. Gelderland's largest cities, Arnhem and Nijmegen, watched in dismay as many country houses and landed estates fell victim to subdivision and development. In response they started to buy up portions of that estate landscape to ensure that they would remain available to city dwellers. In addition, the `safety net' provided by newly established nature and landscape organizations, in particular Natuurmonumenten and Geldersch Landschap & Kas-teelen, also contributed to preservation and permanent accessibility by offering landed families the opportunity to keep their estate intact, albeit no longer under their ownership.
   Similar motives - the need to preserve attractive, accessible walking areas for the increasingly urbanized society - underpinned the government's introduction of the Nature Conservation Act in 1928. The Act was invoked more frequently in Gelderland than in any other province. It promoted the opening up of private properties as well as the preservation of the cultural value of the kind of 'natural beauty' to be found on landed estates.
   After the Second World War, in addition to resorting to the Nature Conservation Act, the owners of country houses and landed estates could avail themselves of an increasing variety of grants aimed at preserving (publicly accessible) nature, landscape and heritage, although the emphasis was firmly on nature. Estate landscapes like the Veluwezoom and the County of Zutphen were eventually safeguarded by a patchwork of different government regulations.
   In the twenty-first century, government policy shifted towards providing financial support for both public and private contributions to nature, landscape and heritage by country houses and landed estates. This in turn has stimulated interest in estate landscapes. Instead of individual heritage-listed estates, the focus is now on areas with multiple country house and landed estates where there are spatial tasks waiting to be fulfilled: not just the preservation of natural beauty for outdoor recreation, but also spatial articulation, climate change adaptation, increased biodiversity and sustainable agriculture. Interest in design, both past and present, has burgeoned thanks to this development.
CR [Anonymous], 1996, STREEKPLAN GELDERLAN
   Bouwer K, 2020, BIJ BOOM MARIA GESCH, P175
   Bouwer K, 2018, BRAKKENSTEIN NIJMEEG, P132
   Briene M., 2014, BELEIDSEVALUATIE NAT, P10
   Derks G., 2011, STORMS SMEETS, P104
   Driessen A.M.A.J., 2000, GIJ BEKEN EEUWIGVLOE, P233
   Gorter H.P., 1986, RUIMTE NATUUR 80 JAA, P21
   Holtman E., 2014, THESIS ERFGOED STUDI
   Kroonjuwelen van Bronckhorst, 2013, GEZAMENLIJKE VERANTW
   Oomen H.C.J, 1975, NUMAGA TIJDSCHRIFT T, VXXii, P219
   Oosten Slingeland J.F., 1979, 8 ZWERFSTENEN UIT GE, P189
   Peltzer E., 1994, BIOGRAFISCH WOORDENB, V4
   Purmer M., 2020, VIRTUS, V27, P9
   Purmer M., 2018, LANDSCHAP BEWAARD NA, P406
   Roelofs B., 2014, POTTENKIJKER BOEGBEE, P11
   Ruijgrok E, 2012, STAND HOUDEN LOONT E
   Saris F., 2019, OPKOMST NATUURBESCHE, P21
   Sluyterman K, 1998, BUITENPLAATSEN JB MO, P13
   Snijders R, 1989, GELDERSCH LANDSCHAP, P42
   Steurea G.G, 1979, 8 ZWERFSTENEN UIT GE, P71
   Storms-Smeets E., 2016, VIRTUS, V23, P147
   Storms-Smeets E., 2019, CULTUURHISTORISCHE A
   Storms-Smeets Zie ook E, 2021, BULL KNOB, V4, P33
   Thissen P., 1995, ANDERHALVE EEUW GELD, P354
   van Cruyningen P.J, 2005, LANDGOEDEREN LANDSCH, P121
   van der Goes van Naters M, 1980, MET TEGEN TIJD, P62
   van der Windt H.J., 1995, DAN WAT IS NATUUR NO, P57
   van der Wyck H. W. M, 1988, ATLAS GELDERSE BUITE, P25
   vanDuuren L., 2007, NATUUR ALS BONDGENOO, P230
   Verrips-Roukens K., 1982, HEREN BOEREN SALLAND, P196
   Verrips-Roukens K., 1982, HEREN BOEREN SALLAND, P145
   Verstegen W., 2017, VRIJE WANDELING, V47, P32
   Verstegen W., 2011, GELDERS ARCADIE ATLA, P128
NR 33
TC 0
Z9 0
U1 0
U2 2
PU KONINKLIJKE NEDERLANDSE OUDHEIDKUNDIGE BOND-KNOB
PI DEFT
PA POSTBUS 5043, DEFT, 2600 GA, NETHERLANDS
SN 0166-0470
EI 2589-3343
J9 BULL KNOB
JI Bull. KNOB
PY 2021
VL 120
IS 4
BP 47
EP 61
PG 15
WC Architecture
WE Emerging Sources Citation Index (ESCI)
SC Architecture
GA XP1DY
UT WOS:000730614800005
DA 2025-01-10
ER

PT J
AU Deva, CR
   Urban, MO
   Challinor, AJ
   Falloon, P
   Svitakova, L
AF Deva, Chetan R.
   Urban, Milan O.
   Challinor, Andrew J.
   Falloon, Pete
   Svitakova, Lenka
TI Enhanced Leaf Cooling Is a Pathway to Heat Tolerance in Common Bean
SO FRONTIERS IN PLANT SCIENCE
LA English
DT Article
DE heat tolerance; common bean; leaf temperature depression; VPD; plant
   breeding; modeling; climate change adaptation
ID CANOPY TEMPERATURE DEPRESSION; STOMATAL CONDUCTANCE; INDUCED STERILITY;
   STRESS; RICE; SIMULATION; METHODOLOGY; GENOTYPES; HUMIDITY; RUBISCO
AB Common bean is the most consumed legume in the world and an important source of protein in Latin America, Eastern, and Southern Africa. It is grown in a variety of environments with mean air temperatures of between 14 degrees C and 35 degrees C and is more sensitive to high temperatures than other legumes. As global heating continues, breeding for heat tolerance in common bean is an urgent priority. Transpirational cooling has been shown to be an important mechanism for heat avoidance in many crops, and leaf cooling traits have been used to breed for both drought and heat tolerance. As yet, little is known about the magnitude of leaf cooling in common bean, nor whether this trait is functionally linked to heat tolerance. Accordingly, we explore the extent and genotypic variation of transpirational cooling in common bean. Our results show that leaf cooling is an important heat avoidance mechanism in common bean. On average, leaf temperatures are 5 degrees C cooler than air temperatures, and can range from between 13 degrees C cooler and 2 degrees C warmer. We show that the magnitude of leaf cooling keeps leaf temperatures within a photosynthetically functional range. Heat tolerant genotypes cool more than heat sensitive genotypes and the magnitude of this difference increases at elevated temperatures. Furthermore, we find that differences in leaf cooling are largest at the top of the canopy where determinate bush beans are most sensitive to the impact of high temperatures during the flowering period. Our results suggest that heat tolerant genotypes cool more than heat sensitive genotypes as a result of higher stomatal conductance and enhanced transpirational cooling. We demonstrate that it is possible to accurately simulate the temperature of the leaf by genotype using only air temperature and relative humidity. Our work suggests that greater leaf cooling is a pathway to heat tolerance. Bean breeders can use the difference between air and leaf temperature to screen for genotypes with enhanced capacity for heat avoidance. Once evaluated for a particular target population of environments, breeders can use our model for modeling leaf temperatures by genotype to assess the value of selecting for cooler beans.
C1 [Deva, Chetan R.; Challinor, Andrew J.] Univ Leeds, Sch Earth & Environm, Inst Climate & Atmospher Sci, Climate Impacts Grp, Leeds, W Yorkshire, England.
   [Urban, Milan O.] Int Ctr Trop Agr CIAT, Cali, Colombia.
   [Falloon, Pete] Hadley Ctr, Met Off, Exeter, Devon, England.
   [Svitakova, Lenka] Charles Univ Prague, Fac Sci, Dept Expt Plant Biol, Prague, Czech Republic.
C3 University of Leeds; Alliance; International Center for Tropical
   Agriculture - CIAT; Met Office - UK; Hadley Centre; Charles University
   Prague
RP Deva, CR (corresponding author), Univ Leeds, Sch Earth & Environm, Inst Climate & Atmospher Sci, Climate Impacts Grp, Leeds, W Yorkshire, England.
EM C.R.Deva@leeds.ac.uk
RI Challinor, Andrew/C-4992-2008
OI Urban, Milan/0000-0002-3684-856X
FU UK National Environmental Research Council Industrial Case Award; UK Met
   Office [NE/M009793/1]; CGIAR Research Program on Climate Change,
   Agriculture and Food Security (CCAFS); Met Office Hadley Centre Climate
   Programme - BEIS; Defra; Biotechnology and Biological Sciences Research
   Council (BBSRC) [BB/S018964/1]; BBSRC [BB/S018964/1] Funding Source:
   UKRI; NERC [1652933] Funding Source: UKRI; UKRI [BB/R022801/1] Funding
   Source: UKRI
FX CD was supported by a UK National Environmental Research Council
   Industrial Case Award in collaboration with the UK Met Office
   NE/M009793/1. AC is supported by the CGIAR Research Program on Climate
   Change, Agriculture and Food Security (CCAFS), which is carried out with
   support from CGIAR Fund Donors and through bilateral funding agreements.
   For details please visit https://ccafs.cgiar.org/donors.PF was supported
   by the Met Office Hadley Centre Climate Programme funded by BEIS and
   Defra. MU was supported by a Biotechnology and Biological Sciences
   Research Council (BBSRC) funded project named Bean Breeding for
   Adaptation to a Changing Climate and Post-Conflict Colombia (BBACO).
   Grant number BB/S018964/1. The views expressed in this document cannot
   be taken to reflect the official opinions of these organizations.
CR Andersson-Sköld Y, 2008, INT J CLIMATOL, V28, P961, DOI 10.1002/joc.1586
   [Anonymous], 2012, J BOT, DOI [DOI 10.1155/2012/803413, 10.1155/2012/803413]
   Araújo SS, 2015, CRIT REV PLANT SCI, V34, P237, DOI 10.1080/07352689.2014.898450
   Beebe S, 2011, CROP ADAPTATION TO CLIMATE CHANGE, P356
   Beebe SE, 2008, CROP SCI, V48, P582, DOI 10.2135/cropsci2007.07.0404
   Bertin N, 2010, J EXP BOT, V61, P955, DOI 10.1093/jxb/erp377
   Blonder B, 2018, AGR FOREST METEOROL, V262, P354, DOI 10.1016/j.agrformet.2018.07.012
   CIAT, 2015, TECH REP
   CLEVELAND WS, 1988, J AM STAT ASSOC, V83, P596, DOI 10.2307/2289282
   del mar Angel L., 2017, CIAT BEAN HIGH DAY N, V18-12, P5578
   Dong N, 2017, GLOBAL ECOL BIOGEOGR, V26, P998, DOI 10.1111/geb.12614
   FARQUHAR GD, 1982, ANNU REV PLANT PHYS, V33, P317, DOI 10.1146/annurev.pp.33.060182.001533
   Fukuda A, 2018, BREEDING SCI, V68, P305, DOI 10.1270/jsbbs.17129
   Ibrahim HM, 2011, EUPHYTICA, V180, P99, DOI 10.1007/s10681-011-0443-9
   Julia C, 2013, EUR J AGRON, V49, P50, DOI 10.1016/j.eja.2013.03.006
   Kuhlgert S, 2016, ROY SOC OPEN SCI, V3, DOI 10.1098/rsos.160592
   Kumar M, 2017, S AFR J BOT, V113, P230, DOI 10.1016/j.sajb.2017.08.016
   Kumar Pramod, 2017, Indian Journal of Plant Physiology, V22, P164, DOI 10.1007/s40502-017-0301-4
   Leigh A, 2012, NEW PHYTOL, V194, P477, DOI 10.1111/j.1469-8137.2012.04058.x
   LICOR, 2019, SPEC
   Ludbrook J, 1998, AM STAT, V52, P127, DOI 10.2307/2685470
   McClean PE, 2011, FUNCT PLANT BIOL, V38, P927, DOI 10.1071/FP11102
   Metergroup, 2019, SC 1 LEAF POR
   Mhlaba ZB, 2018, SCI HORTIC-AMSTERDAM, V237, P112, DOI 10.1016/j.scienta.2018.04.012
   Michaletz ST, 2016, NAT PLANTS, V2, DOI [10.1038/NPLANTS.2016.129, 10.1038/nplants.2016.129]
   Neukam D, 2016, AGRONOMY-BASEL, V6, DOI 10.3390/agronomy6010007
   PhotosynQ, 2019, MULT V2 0
   Pinto RS, 2015, THEOR APPL GENET, V128, P575, DOI 10.1007/s00122-015-2453-9
   Polania J, 2016, EUPHYTICA, V210, P17, DOI 10.1007/s10681-016-1691-5
   Porch TG., 2013, Genomics and breeding for climateresilient crops, V2, P167, DOI DOI 10.1007/978-3-642-37048-94
   Porch TG, 2010, HORTSCIENCE, V45, P1278, DOI 10.21273/HORTSCI.45.8.1278
   Prasad PVV, 2017, FIELD CROP RES, V200, P114, DOI 10.1016/j.fcr.2016.09.024
   Purushothaman R, 2015, FIELD CROP RES, V174, P1, DOI 10.1016/j.fcr.2015.01.007
   Rao IM, 2017, J AGR SCI-CAMBRIDGE, V155, P857, DOI 10.1017/S0021859616000915
   Ryan T.P., 1997, Modern Regression Methods
   Sage RF, 2008, J EXP BOT, V59, P1581, DOI 10.1093/jxb/ern053
   Salvucci ME, 2004, PHYSIOL PLANTARUM, V120, P179, DOI 10.1111/j.0031-9317.2004.0173.x
   Sen A., 1990, Regression Analysis, V102, DOI [DOI 10.1007/978-3-662-25092-1, 10.1007/978-3-662-25092-1, DOI 10.1007/978-3-662-25092-1_2]
   Siebert S, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/4/044012
   Sinclair TR, 2017, PLANT SCI, V260, P109, DOI 10.1016/j.plantsci.2017.04.007
   Tardieu F, 2012, J EXP BOT, V63, P25, DOI 10.1093/jxb/err269
   Traub J, 2018, CROP SCI, V58, P2459, DOI 10.2135/cropsci2018.04.0275
   Tsukaguchi T, 2003, PLANT PROD SCI, V6, P24, DOI 10.1626/pps.6.24
   Urban M., 2018, CIAT BEAN SOIL VS CY, V18-18, P3768
   Urban M., 2018, CIAT BEAN RICE BEAN, V18-03, P4169
   Urban M., 2018, CIAT BEAN LEAF PROLO, V18-08, P4747
   Urban M., 2018, CIAT BEAN HIGH NIGHT, V18-01, P4089
   van Oort PAJ, 2014, FIELD CROP RES, V156, P303, DOI 10.1016/j.fcr.2013.11.007
   Wahid A, 2007, ENVIRON EXP BOT, V61, P199, DOI 10.1016/j.envexpbot.2007.05.011
   Webber H, 2016, ENVIRON MODELL SOFTW, V77, P143, DOI 10.1016/j.envsoft.2015.12.003
   Webber H, 2018, FIELD CROP RES, V216, P75, DOI 10.1016/j.fcr.2017.11.005
   Weerakoon WMW, 2008, J AGRON CROP SCI, V194, P135, DOI 10.1111/j.1439-037X.2008.00293.x
   Zwillinger D., 1990, CRC STANDARD PROBABI
NR 53
TC 53
Z9 59
U1 3
U2 32
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 1664-462X
J9 FRONT PLANT SCI
JI Front. Plant Sci.
PD FEB 28
PY 2020
VL 11
AR 19
DI 10.3389/fpls.2020.00019
PG 17
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA LB5HM
UT WOS:000524666200001
PM 32180776
OA Green Published, gold
DA 2025-01-10
ER

PT C
AU Gouldby, B
   Krzhizhanovskaya, V
   Simm, J
AF Gouldby, Ben
   Krzhizhanovskaya, Valeria
   Simm, Jonathan
GP ICCS
BE Sloot, PMA
   Albada, GDV
   Dongarra, J
TI Multiscale modelling in real-time flood forecasting systems: From sand
   grain to dike failure and inundation
SO ICCS 2010 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE,
   PROCEEDINGS
SE Procedia Computer Science
LA English
DT Proceedings Paper
CT International Conference on Computational Science (ICCS)
CY MAY 31-JUN 02, 2010
CL Univ Amsterdam, Amsterdam, NETHERLANDS
SP NWO, Netherlands Org Sci Res, KNAW, Royal Netherlands Acad Arts & Sci, Elsevier, Univ Amsterdam
HO Univ Amsterdam
DE Flood; forecast; modeling; multiscale; dike failure; inundation;
   UrbanFlood
AB Severe events around the globe have highlighted the threat to life, infrastructure and the environment posed by flooding. Flood forecasting systems are a vital component of broader flood risk management activities. These systems are becoming increasingly more sophisticated as their importance in reducing life loss and economic damages is realized. Part of this increase in complexity is focused on the ability to predict and warn of failures in dykes, levees and embankments. A new European ICT project, UrbanFlood for Environmental Services and Climate Change Adaptation, has recently been commissioned and is introduced in this presentation. The primary objective of the Urban Flood project is to develop early warning systems that will monitor flood protection systems in real-time, identify vulnerable locations, model the failure and predict dike collapse and subsequent inundation. In combination with the damage assessment, Urban Flood will serve as an advanced decision support system, mitigating the impact of seasonal and catastrophic floods.
   Modeling is one of the key tasks in the project. The models will be required to simulate the behavior of the material properties of the layered dikes (sand, clay, peat, grass or concrete cover, metal frame, dam gates, etc.), during extreme hydraulic loading events. In earthen dikes, extra challenge is posed by the non-linear elastic plastic properties of the deformable clay. A realistic simulation of the dike will model the free-surface water dynamics; convective and diffusive transfer of water inside the porous materials; dynamic response of clay to the water pressure; structural mechanics, deformation and actual dike breakdown and flood.
   The models shall cover a wide range of scales from a sand grain to a flooded city. The time scales will range from seconds (for water penetrating the soil) to hours (for dike collapse dynamics and ocean tides). Eventually, the models will predict the influence of seasonal and global changes on the stability of flood defense systems. Full 3D transient simulation of dike failure with subsequent inundation will require significant computing resources. The project started three months ago, and we will present the plan for developing the modeling cascade for the system. This work is supported by the UrbanFlood European Union project N 248767, theme ICT-2009.6.4 (C) 2010 Published by Elsevier Ltd.
C1 [Krzhizhanovskaya, Valeria] Univ Amsterdam, NL-1012 WX Amsterdam, Netherlands.
   [Gouldby, Ben; Simm, Jonathan] HR Wallingford, Wallingford, Oxon, England.
   [Krzhizhanovskaya, Valeria] St Petersburg State Polytech Univ, St Petersburg, Russia.
C3 University of Amsterdam; HR Wallingford Limited; Peter the Great St.
   Petersburg Polytechnic University
RP Krzhizhanovskaya, V (corresponding author), Univ Amsterdam, NL-1012 WX Amsterdam, Netherlands.
EM V.Krzhizhanovskaya@uva.nl
RI ; Krzhizhanovskaya, Valeria/E-8204-2012
OI Gouldby, Ben/0000-0003-0415-5897; Krzhizhanovskaya,
   Valeria/0000-0002-8247-129X
NR 0
TC 10
Z9 11
U1 0
U2 14
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 1877-0509
J9 PROCEDIA COMPUT SCI
PY 2010
VL 1
IS 1
BP 809
EP 809
DI 10.1016/j.procs.2010.04.087
PG 1
WC Computer Science, Theory & Methods
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science
GA BQV31
UT WOS:000281951600086
OA gold
DA 2025-01-10
ER

PT J
AU Nizar, S
   Thomas, J
   Jainet, PJ
   Sebastian, DE
   Surendran, U
   Narasimhan, B
   Sudheer, KP
AF Nizar, Sinan
   Thomas, Jobin
   Jainet, P. J.
   Sebastian, Dawn Emil
   Surendran, U.
   Narasimhan, Balaji
   Sudheer, K. P.
TI Shifts in bioclimatic zones mirror climate change signals in a tropical
   agriculture-dominated Bharathapuzha River basin of southern Western
   Ghats (India)
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE bioclimatic variables; climate change assessment; ETCCDI; tropical
   climate
ID SPATIAL SCALE; DATA SET; TEMPERATURE; PRECIPITATION; ENSEMBLE; IMPACTS;
   PROJECTIONS; SCENARIOS; SELECTION; RAINFALL
AB Assessing anthropogenic climate change in a regional context is challenging due to the spatial heterogeneity of climatic variables and is more complicated than at the global scale. Especially in the Tropics, such spatial variations are expected to increase, warranting the identification of homogeneous climatic zones for assessing regional climate change. The present study explores the ability of bioclimatic variables in defining regional climatic zones, and the detection of climate change therein. We hypothesize that the identification of homogeneous climatic zones based on bioclimatic variables could be an effective approach rather than the conventional extreme climate-based indices to identify climate change signals. To demonstrate the hypothesis, bioclimatic variables representing the generalized climatic characteristics of a tropical river basin were derived from observed gridded datasets of rainfall and temperature. Clusters of homogeneous climatic zones were identified, and their temporal variations were analysed to examine the existence of climate change. The results indicate that despite the spatial heterogeneity in extreme climate-based indices, the bioclimatic variables-based approach renders a meaningful representation of the regional climatic pattern. Investigation of bioclimatic zones of the study area helped to identify a shift in its climatic zones with a slant towards drier conditions. Further, future changes in climatic zones were identified from 13 different GCMs that participated in the CMIP6, projecting drier conditions over the basin, with varying spatial extend based on future emission scenarios. The study significantly contributes towards the identification of climatologically fragile regions in changing climate, which is an essential component in developing any regional climate change adaptation and mitigation strategy.
   The present study explores the ability of bioclimatic variables in defining regional climatic zones, and the detection of climate change therein. The results indicate that despite the spatial heterogeneity in extreme climate-based indices, the bioclimatic variables-based approach renders a meaningful representation of the regional climatic pattern. image
C1 [Nizar, Sinan] KSCSTE Inst Climate Change Studies, Kottayam, India.
   [Thomas, Jobin] Univ Mississippi, Dept Geol & Geol Engn, Oxford, MS USA.
   [Jainet, P. J.; Surendran, U.] KSCSTE Ctr Water Resources Dev & Management, Calicut, India.
   [Jainet, P. J.] Indian Inst Technol Palakkad, Dept Civil Engn, Palakkad, India.
   [Sebastian, Dawn Emil] Indian Inst Human Settlements, Sch Environm & Sustainabil, Bengaluru, India.
   [Surendran, U.] ICAR Natl Bur Soil Survey & Land Use Planning, Nagpur, India.
   [Narasimhan, Balaji; Sudheer, K. P.] Indian Inst Technol Madras, Dept Civil Engn, Chennai 600036, India.
   [Sudheer, K. P.] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN USA.
   [Sudheer, K. P.] Kerala State Council Sci Technol & Environm, Thiruvananthapuram, India.
C3 University of Mississippi; Indian Institute of Technology System (IIT
   System); Indian Institute of Technology (IIT) - Palakkad; Indian
   Institute for Human Settlements (IIHS); Indian Council of Agricultural
   Research (ICAR); ICAR - National Bureau of Soil Survey & Land Use
   Planning; Indian Institute of Technology System (IIT System); Indian
   Institute of Technology (IIT) - Madras; Purdue University System; Purdue
   University
RP Sudheer, KP (corresponding author), Indian Inst Technol Madras, Dept Civil Engn, Chennai 600036, India.
EM sudheer@iitm.ac.in
RI NIZAR, SINAN/V-7039-2019; Narasimhan, Balaji/V-9018-2018; U,
   Surendran/F-6930-2010; KP, Sudheer/C-7123-2013; Narasimhan,
   Balaji/H-6050-2011
OI KP, Sudheer/0000-0002-0947-1197; Sebastian, Dawn/0000-0001-8837-8515;
   Narasimhan, Balaji/0000-0003-2609-9320; NIZAR, SINAN/0000-0001-9378-9247
FU Department of Science and Technology (DST)-SERB; Integrating Hydrology
   and Agriculture; Indian Institute of Technology, Madras; Government of
   India;  [CRG/2020/002752]
FX This work was conducted under the DST-SERB project "Integrating
   Hydrology and Agriculture with livelihood issues: Development of Climate
   Change Adaptation Approaches for sustainable water management in humid
   tropical Kerala" by the collaboration of the KSCSTE-Institute for
   Climate Change Studies, Kottayam, KSCSTE-Centre for Water Resources
   Development and Management, and the Indian Institute of Technology,
   Madras. The authors acknowledge funding from the Department of Science
   and Technology (DST)-SERB (No. CRG/2020/002752), the Government of
   India.
CR Adams RM, 2003, CLIMATIC CHANGE, V60, P131, DOI 10.1023/A:1026014311149
   Ahmed N., 2020, Environmental Systems Research, V9, P32, DOI [10.1186/s40068-020-00195-0, DOI 10.1186/S40068-020-00195-0]
   Al Ruheili AM, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10030460
   Alexander LV, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab51b6
   Alves LM, 2021, INT J CLIMATOL, V41, pE1875, DOI 10.1002/joc.6818
   Amiri M, 2020, ECOL INFORM, V57, DOI 10.1016/j.ecoinf.2020.101060
   Beaumont LJ, 2011, P NATL ACAD SCI USA, V108, P2306, DOI 10.1073/pnas.1007217108
   CGWB, 2022, Dynamic Ground Water Resources of India, 2022
   Chervenkov H., 2021, Advances in High Performance Computing, V902, P398, DOI [10.1007/978-3- 030-55347-0_34, DOI 10.1007/978-3-030-55347-0_34]
   Chi CF, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063450
   Christidis N, 2013, J CLIMATE, V26, P2756, DOI 10.1175/JCLI-D-12-00169.1
   Corlett R.T., 2014, STATE OF THE TROPICS
   Donat MG, 2013, J GEOPHYS RES-ATMOS, V118, P2098, DOI 10.1002/jgrd.50150
   Donat MG, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052459
   Dosio A, 2019, CLIM DYNAM, V53, P5833, DOI 10.1007/s00382-019-04900-3
   Dosio A, 2016, J GEOPHYS RES-ATMOS, V121, P5488, DOI 10.1002/2015JD024411
   ETCCDI, 2023, PACIFIC CLIMATE IMPA
   Gopar-Merino LF, 2015, ECOSPHERE, V6, DOI 10.1890/ES14-00138.1
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Frey BJ, 2007, SCIENCE, V315, P972, DOI 10.1126/science.1136800
   Geiger R., 1961, Uberarbeitete Neuausgabe von Geiger
   George J, 2020, THEOR APPL CLIMATOL, V142, P269, DOI 10.1007/s00704-020-03255-8
   Ghosh S, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0158670
   Ghosh S, 2012, NAT CLIM CHANGE, V2, P86, DOI 10.1038/NCLIMATE1327
   Herold N, 2016, GEOPHYS RES LETT, V43, P341, DOI 10.1002/2015GL066615
   Holdridge L. R., 1967, Life zone ecology.
   Hossell J. E., 2003, Journal for Nature Conservation (Jena), V11, P5, DOI 10.1078/1617-1381-00033
   Hurtado P, 2020, MICROORGANISMS, V8, DOI 10.3390/microorganisms8121913
   Intergovernmental Panel on Climate Change (IPCC), 2023, Climate Change 2021The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel On Climate Change, DOI [10.1017/9781009325844.001, DOI 10.1017/9781009157940, 10.1017/9781009157896]
   Kendall M. G., 1948, Rank correlation methods.
   Koppen W, 1884, Meteorol Z, V1, P215
   KSCSTE, 2019, REPORT COMMITTEE EXA
   Lobell DB, 2007, AGR FOREST METEOROL, V145, P229, DOI 10.1016/j.agrformet.2007.05.002
   Malhi GS, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13031318
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Mishra V, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-00681-1
   Molloy SW, 2014, ENVIRON CONSERV, V41, P176, DOI 10.1017/S0376892913000337
   Morrison BD, 2019, ECOL EVOL, V9, P12026, DOI 10.1002/ece3.5511
   Mrdero S., 2014, INT PERSPECTIVES CLI, P189, DOI [10.1007/978-3-319-04489-713, DOI 10.1007/978-3-319-04489-713]
   Narulita I, 2021, THEOR APPL CLIMATOL, V144, P625, DOI 10.1007/s00704-021-03527-x
   NIX HA, 1986, ATLAS ELAPID SNAKES, P4
   Nneji LM, 2023, DIVERS DISTRIB, V29, P1035, DOI 10.1111/ddi.13717
   Noor Muhammad, 2019, Theoretical and Applied Climatology, V138, P999, DOI 10.1007/s00704-019-02874-0
   O'Donnell M.S., 2012, Bioclimatic predictors for supporting ecological applications in the conterminous United States
   Pai DS, 2014, MAUSAM, V65, P1
   Park C, 2022, ASIA-PAC J ATMOS SCI, V58, P715, DOI 10.1007/s13143-022-00292-3
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Pettitt A. N., 1979, Applied Statistics, V28, P126, DOI 10.2307/2346729
   Pramanik M, 2018, CLIM RISK MANAG, V19, P94, DOI 10.1016/j.crm.2017.11.002
   Rahman MR, 2017, THEOR APPL CLIMATOL, V128, P27, DOI 10.1007/s00704-015-1688-3
   Rao CAR., 2019, Risk and Vulnerability Assessment of Indian Agriculture to Climate Change
   Soteriades AD, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7689
   Srivastava AK, 2009, ATMOS SCI LETT, V10, P249, DOI 10.1002/asl.232
   Surendran U, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11185132
   Surendran U, 2014, J WATER CLIM CHANGE, V5, P472, DOI 10.2166/wcc.2014.108
   Tariku TB, 2018, CLIM DYNAM, V51, P3487, DOI 10.1007/s00382-018-4092-8
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   Trewartha G.T., 1968, INTRO CLIMATE, VFourth
   Tsvetsinskaya EA, 2003, CLIMATIC CHANGE, V60, P37, DOI 10.1023/A:1026056215847
   Turner AG, 2012, NAT CLIM CHANGE, V2, P587, DOI 10.1038/NCLIMATE1495
   Varadan K.M., 1996, WATER MODULE UPLAND
   WCRP, 2023, World Climate Research Programme
   Yaghmaei L, 2009, INT J CLIMATOL, V29, P1850, DOI 10.1002/joc.1835
   Yoon S, 2021, COMPUT ELECTRON AGR, V190, DOI 10.1016/j.compag.2021.106430
NR 64
TC 0
Z9 0
U1 2
U2 2
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0899-8418
EI 1097-0088
J9 INT J CLIMATOL
JI Int. J. Climatol.
PD AUG
PY 2024
VL 44
IS 10
BP 3499
EP 3513
DI 10.1002/joc.8535
EA JUN 2024
PG 15
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA A8Y7B
UT WOS:001248163900001
DA 2025-01-10
ER

PT J
AU Zagre, I
   Akinseye, FM
   Worou, ON
   Kone, M
   Faye, A
AF Zagre, Inoussa
   Akinseye, Folorunso Mathew
   Worou, Omonlola Nadine
   Kone, Mama
   Faye, Aliou
TI Climate change adaptation strategies among smallholder farmers in
   Senegal's semi-arid zone: role of socio-economic factors and
   institutional supports
SO FRONTIERS IN CLIMATE
LA English
DT Article
DE climate-smart technology; policies; farmers perception; logit-model;
   climate variability
ID SUB-SAHARAN AFRICA; SMART AGRICULTURE; PLANTING DATES; BURKINA-FASO;
   MAIZE; VARIABILITY; SERVICES; PRODUCTIVITY; IMPACTS; DROUGHT
AB In dryland agricultural systems, developing appropriate climate-smart technology (CST) options is important to adapt agriculture to climate change and transition toward sustainability, as well as increasing productivity and incomes. This study examines the impact of socio-economic and institutional support on community responses to climate change and the impact of changes in three selected regions of Senegal (Meouane, Thiel, and Daga Birame), which fall within different rainfall gradients. It captures community perceptions of climate change, compares them to long-term meteorological data, and identifies site-specific response strategies. Communities are randomly selected from a list of communities within the target sites. We used a two-stage stratified sampling method to select sample households. First, purposive sampling was conducted to select at least six (6) villages as a cluster within each rainfall gradient. Likewise, the selection of households in each cluster was based on the main value chains of crops grown in the study area, namely groundnut, millet, black pea, and livestock. A total of 145 households participated in this study. Data from surveys conducted during the 2022 post-harvest season were analyzed using descriptive statistics and logit models. The analysis found that smallholders have a comprehensive understanding of climate indicators, including annual rainfall, shortened crop seasons, and rising temperatures, compared to historical data trends. Additionally, the results highlight how farmers view the negative impacts of seasonal rainfall deficiencies (72%), delayed start of the growing season (88%), frequent dry spells (68%), and longer dry spells (76%), which ultimately lead to decreased grain and fodder yields. The logit model also highlights the importance of socio-economic and institutional factors such as access to credit, extension services, agricultural experience, frequency of interaction with extension workers, and access to government subsidies. These factors play a crucial role in farmers' decision to adopt CST. Given the specificity of community contexts, these insights have important implications for guiding policymakers and making it easier to reduce climate risk among smallholder farmers.
C1 [Zagre, Inoussa] Univ Sci Tech & Technol Bamako USTTB, WASCAL Grad Res Program Climate Change & Agr, Bamako, Mali.
   [Zagre, Inoussa] Rural Polytech Inst Training & Appl Res IPR IFRA K, Koulikoro, Mali.
   [Akinseye, Folorunso Mathew] Int Crop Res Inst Semiarid Trop ICRISAT, Dakar, Senegal.
   [Akinseye, Folorunso Mathew; Faye, Aliou] Reg Ctr Excellence Improvement Plant Adaptat Droug, Thies, Senegal.
   [Worou, Omonlola Nadine] Int Livestock Res Inst ILRI, Dakar, Senegal.
   [Kone, Mama] Inst Econ Rurale IER, Bamako, Mali.
C3 University of Science & Technology of Bamako; CGIAR; International
   Livestock Research Institute (ILRI)
RP Zagre, I (corresponding author), Univ Sci Tech & Technol Bamako USTTB, WASCAL Grad Res Program Climate Change & Agr, Bamako, Mali.; Zagre, I (corresponding author), Rural Polytech Inst Training & Appl Res IPR IFRA K, Koulikoro, Mali.
EM zagre.i@edu.wascal.org
FU West Africa Sciences Service Center on Climate Change and Adapted Land
   Use (WASCAL); German Federal Ministry of Education and Research (BMBF);
   Prince Albert II of Monaco Foundation for Young Researchers scholarship
   under IPCC Program; World Bank - CGIAR Research Program on the AICCRA
FX The author(s) declare that financial support was received for the
   research, authorship, and/or publication of this article. IZ gratefully
   acknowledges the support of this work by the West Africa Sciences
   Service Center on Climate Change and Adapted Land Use (WASCAL) through
   the support of the German Federal Ministry of Education and Research
   (BMBF) and Prince Albert II of Monaco Foundation for Young Researchers
   scholarship under IPCC Program. Also, acknowledged is the field survey
   support provided by the World Bank-funded project through the CGIAR
   Research Program on the AICCRA project (Accelerating Impacts of CGIAR
   Climate Research for Africa) Project ID 173398 and Climate Resilience
   otherwise known as ClimBeR, which funded the involvement of FA in this
   study.
CR Adiku S. G. K., 2015, Climate Change Impacts on West African Agriculture: An Integrated Regional Assessment (CIWARA)
   Akinseye FM, 2016, THEOR APPL CLIMATOL, V124, P973, DOI 10.1007/s00704-015-1460-8
   Akinseye F. M., 2012, International Journal of Academic Research, V4, P107
   Akinseye F. M., 2013, Assessing the impacts of climate variability on crop yield over Sudano-Sahelian zone in Nigeria change detection and trend analysis of future temperature and rainfall over West Africa view project WASCAL view project
   Akinseye FM, 2023, AGRONOMY-BASEL, V13, DOI 10.3390/agronomy13030727
   Akponikpe I., 2010, Farmers' perception of climate change and adaptation strategies in sub-Saharan West-Africa synergizing fertilizer micro-dosing and indigenous vegetable production to enhance food and economic security of West African farmers (IDRC/CIFSRF phase 2) view project scaling-up fertilizers microdosing and indigenous vegetables production and utilization in West-Africa (MICRO-VEG) view project
   Akponikpè PBI, 2010, EUR J AGRON, V32, P144, DOI 10.1016/j.eja.2009.09.005
   Alexander LV, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006290
   Alvar-Beltrán J, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11080827
   Amadou L. M., 2015, Comparing farmers' perception of climate change and varia-bility with historical climate data in the Upper East Region of Ghana Pojet AMMA View project Tropical Forests in the Context of Climate Change: From Drivers, Policies to REDD+ Actions and Intensity Analysis-A Review View project
   Araya A, 2022, CLIM RISK MANAG, V36, DOI 10.1016/j.crm.2022.100436
   Assoumana B. T., 2016, Journal of Sustainable Development, V9, P118, DOI 10.5539/jsd.v9n3p118
   Badiane A, 2001, BIOL AGRIC HORTIC, V19, P219, DOI 10.1080/01448765.2001.9754926
   Beaman L, 2012, J DEV ECON, V98, P124, DOI 10.1016/j.jdeveco.2011.06.005
   Bedeke S, 2019, NJAS-WAGEN J LIFE SC, V88, P96, DOI 10.1016/j.njas.2018.09.001
   Bosello F, 2018, ENVIRON RESOUR ECON, V69, P787, DOI 10.1007/s10640-016-0105-4
   Clements R., 2011, Agriculture sector
   Danso I, 2018, EUR J AGRON, V101, P1, DOI 10.1016/j.eja.2018.08.001
   Diallo A, 2020, CLIMATIC CHANGE, V159, P309, DOI 10.1007/s10584-020-02684-8
   Diarra FB, 2021, ENVIRON DEV SUSTAIN, V23, P13854, DOI 10.1007/s10668-021-01242-1
   Diouf NS, 2019, GEND TECHNOL DEV, V23, P93, DOI 10.1080/09718524.2019.1649790
   Emma T., 2014, CARAF/WECORD
   Fatondji D., 2012, IMPROVING SOIL FERTI, P77
   Faye A., 2022, AICCRA Report
   Faye A, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15054093
   Faye N. F., 2018, J. AGRICUL. ENVIRON. SCI, V7, P91, DOI [10.15640/jaes.v7n2a10, DOI 10.15640/JAES.V7N2A10]
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fisher M, 2015, CLIMATIC CHANGE, V133, P283, DOI 10.1007/s10584-015-1459-2
   Fonta W M., 2018, Agric Econ, V6, P1, DOI [10.1186/s40100-018-0104-6, DOI 10.1186/S40100-018-0104-6]
   Gadedjisso-Tossou A., 2015, Agricultural Sciences, V6, P1441, DOI 10.4236/as.2015.612140
   Gebru GW, 2020, HELIYON, V6, DOI 10.1016/j.heliyon.2020.e04356
   Greene H. W., 2003, Econometric Analysis, p1058p
   Greene W. H., 2012, Econometric analysis, p1241p
   Haile M, 2005, PHILOS T R SOC B, V360, P2169, DOI 10.1098/rstb.2005.1746
   Hansen JW, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00021
   Harr RN, 2014, ECOL SOC, V19, DOI 10.5751/ES-06404-190241
   Ibitoye S. J., 2011, International Journal of Agricultural Science, Research and Technology (IJASRT), V1, P185
   Ibrahim B, 2012, CLIM DYNAM, V39, P1287, DOI 10.1007/s00382-011-1276-x
   IFAD, 2021, IFAD Annual Report 2021
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Jamala G., 2021, Nigeria Article in IOSR J. Environ. Sci. Toxicol. Food Technol, V6, P2319
   Joseph JE, 2023, AGR FOREST METEOROL, V333, DOI 10.1016/j.agrformet.2023.109431
   Kassa Y., 2013, Int. J. Environ. Monit. Anal, V1, P111, DOI [10.11648/j.ijema.20130104.11, DOI 10.11648/J.IJEMA.20130104.11]
   Kumar U, 2021, CLIM RISK MANAG, V33, DOI 10.1016/j.crm.2021.100346
   Laminou R. H. M., 2020, Am. J. Agric. Fores, V8, P69, DOI [DOI 10.11648/J.AJAF.20200803.13, 10.11648/j.ajaf.20200803.13]
   Liu ZJ, 2016, SCI TOTAL ENVIRON, V541, P756, DOI 10.1016/j.scitotenv.2015.08.145
   Lodoun T, 2013, ENVIRON DEV, V5, P96, DOI 10.1016/j.envdev.2012.11.010
   McClintock N. C., 2005, International Journal of Agricultural Sustainability, V3, P79, DOI 10.1080/14735903.2005.9684746
   Mohamed AML, 2023, J CROP IMPROV, V37, P41, DOI 10.1080/15427528.2022.2048764
   Moron V, 2013, J CLIMATE, V26, P2580, DOI 10.1175/JCLI-D-12-00357.1
   Moutouama FT, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12061348
   Muzari W., 2012, Journal of Sustainable Development, V5, P69, DOI 10.5539/jsd.v5n8p69
   Mwase W., 2015, Environment and Natural Resources Research, V5, P148
   Naab FZ, 2019, CLIM SERV, V13, P24, DOI 10.1016/j.cliser.2019.01.007
   Namatsheve T, 2020, AGRON SUSTAIN DEV, V40, DOI 10.1007/s13593-020-00629-0
   Ngigi MW, 2017, ECOL ECON, V138, P99, DOI 10.1016/j.ecolecon.2017.03.019
   Nordey T, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-017-0460-8
   Ntim-Amo G, 2022, INT J DISAST RISK RE, V80, DOI 10.1016/j.ijdrr.2022.103223
   Ouedraogo Harouna, 2023, International Journal of Biological and Chemical Sciences, V16, P2841, DOI 10.4314/ijbcs.v16i6.29
   Ouedraogo I, 2018, CLIMATE, V6, DOI 10.3390/cli6010013
   Ouedraogo Mathieu, 2010, Secheresse (Montrouge), V21, P87, DOI 10.1684/sec.2010.0244
   Owusu V, 2021, WEATHER CLIM EXTREME, V33, DOI 10.1016/j.wace.2021.100353
   Panthou G, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac334
   Partey ST, 2020, CLIMATIC CHANGE, V158, P61, DOI 10.1007/s10584-018-2239-6
   Partey ST, 2018, J CLEAN PROD, V187, P285, DOI 10.1016/j.jclepro.2018.03.199
   Patnaik H, 2021, WORLD DEV, V142, DOI 10.1016/j.worlddev.2021.105448
   Perez C, 2015, GLOBAL ENVIRON CHANG, V34, P95, DOI 10.1016/j.gloenvcha.2015.06.003
   Ramaraj AP, 2023, CLIM SERV, V31, DOI 10.1016/j.cliser.2023.100403
   Rienecker MM, 2011, J CLIMATE, V24, P3624, DOI 10.1175/JCLI-D-11-00015.1
   Salack S, 2011, THEOR APPL CLIMATOL, V106, P1, DOI 10.1007/s00704-011-0414-z
   Sanfo S, 2022, CLIM SERV, V25, DOI 10.1016/j.cliser.2021.100280
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Sivakumar M. V. K., 1992, Clim. Res, V2, P13
   SIVAKUMAR MVK, 1988, AGR FOREST METEOROL, V42, P295, DOI 10.1016/0168-1923(88)90039-1
   Soler CMT, 2008, J AGR SCI-CAMBRIDGE, V146, P445, DOI 10.1017/S0021859607007617
   Sraku-Lartey M, 2020, INFORM DEV, V36, P16, DOI 10.1177/0266666918811391
   StataCorp, 2021, Stata Statistical Software: Release 17
   Stewart ZP, 2020, J EXP BOT, V71, P632, DOI 10.1093/jxb/erz446
   Sultan B, 2005, AGR FOREST METEOROL, V128, P93, DOI 10.1016/j.agrformet.2004.08.005
   Sylla MB, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-32736-0
   Tesfaye A, 2019, ECOL ECON, V162, P157, DOI 10.1016/j.ecolecon.2019.04.019
   Theriault V, 2017, WORLD DEV, V92, P177, DOI 10.1016/j.worlddev.2016.12.003
   Thornton PK, 2018, AGR SYST, V167, P161, DOI 10.1016/j.agsy.2018.09.009
   Totin E, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061990
   Traore B, 2014, FIELD CROP RES, V156, P63, DOI 10.1016/j.fcr.2013.10.014
   Traore B, 2013, EUR J AGRON, V49, P115, DOI 10.1016/j.eja.2013.04.004
   Traore S, 2013, INT J GLOBAL WARM, V5, P498, DOI 10.1504/IJGW.2013.057288
   van Ittersum MK, 2016, P NATL ACAD SCI USA, V113, P14964, DOI 10.1073/pnas.1610359113
   Vieira N Jr, 2023, AGR WATER MANAGE, V278, DOI 10.1016/j.agwat.2023.108173
   Waha K, 2016, SCI DATA, V3, DOI 10.1038/sdata.2016.20
   Waongo M, 2015, AGR FOREST METEOROL, V205, P23, DOI 10.1016/j.agrformet.2015.02.006
   West CT, 2008, LAND DEGRAD DEV, V19, P289, DOI 10.1002/ldr.842
   Yameogo J. T., 2011, Int. J. Biol. Chem. Sci, V5, P56, DOI [10.4314/ijbcs.v5i1.68085, DOI 10.4314/IJBCS.V5I1.68085]
   Yegbemey RN, 2014, CAH AGRIC, V23, P177, DOI 10.1684/agr.2014.0697
   Zougmore R., 2014, Climate-smart soil water and nutrient management options in semiarid West Africa: a review of evidence and analysis of stone bunds and zai techniques
NR 95
TC 5
Z9 5
U1 4
U2 4
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-9553
J9 FRONT CLIM
JI Front. Clim.
PD MAY 2
PY 2024
VL 6
AR 1332196
DI 10.3389/fclim.2024.1332196
PG 17
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA QW6W5
UT WOS:001223956100001
OA gold
DA 2025-01-10
ER

PT J
AU Szabó, Z
   Szijártó, M
   Tóth, A
   Mádl-Szonyi, J
AF Szabo, Zsoka
   Szijarto, Mark
   Toth, Adam
   Madl-Szonyi, Judit
TI The Significance of Groundwater Table Inclination for Nature-Based
   Replenishment of Groundwater-Dependent Ecosystems by Managed Aquifer
   Recharge
SO WATER
LA English
DT Article
DE managed aquifer recharge; modelling; water replenishment; climate change
   adaptation; groundwater flow systems
ID THEORETICAL-ANALYSIS; CLIMATE-CHANGE; ARTIFICIAL RECHARGE; EVOLUTION;
   DYNAMICS; IMPACT; FLOW; INVENTORY; SYSTEM; GROWTH
AB Managed aquifer recharge (MAR) is an increasingly popular technique; however, the significance of groundwater flow dynamics is rarely examined in detail regarding MAR systems. In general, a high hydraulic gradient is not favoured for MAR implementation, as it causes higher water loss and mixing of recharge water with native groundwater. However, during groundwater-dependent ecosystem (GDE) rehabilitation, these hydraulic gradient-driven flow processes can be taken advantage of. The aim of this research is to test this hypothesis by evaluating the effect of groundwater table inclination, topography, and other local characteristics on MAR efficiency from the perspective of GDE restoration. MAR efficiency was examined from recharge to discharge area in a simple half-basin based on theoretical flow simulations, using GeoStudio SEEP/W software. Different scenarios were compared to analyse the groundwater level increase and the infiltrated water volumes and to assess the efficiency of MAR based on these parameters in each scenario. The theoretical results were applied to a close-to-real situation of Lake Kondor, a GDE of the Danube-Tisza Interfluve (Hungary), which dried up in the past decades due to groundwater decline in the area. Based on the results, initial hydraulic head difference, model length, and hydraulic conductivity are the most critical parameters regarding water level increase at the discharge area. The water amount needed for increasing the water table is mainly influenced by the thickness of the unsaturated zone and the material properties of the aquifer. The findings can help better understand MAR efficiency in light of local groundwater flow processes and contribute to optimising MAR systems. The results of the study suggest that, if water is infiltrated at the local recharge area, the water table will also increase at the corresponding discharge area, which positively effects the connected GDEs. This approach can serve as a nature-based solution (NBS) to sustain sensitive ecosystems in changing climatic conditions.
C1 [Szabo, Zsoka; Szijarto, Mark; Toth, Adam; Madl-Szonyi, Judit] Eotvos Lorand Univ, Inst Geog & Earth Sci, Jozsef & Erzsebet Toth Endowed Hydrogeol Chair, Dept Geol, Pazmany Peter Setany 1-C, H-1117 Budapest, Hungary.
   [Szijarto, Mark] Eotvos Lorand Univ, Inst Geog & Earth Sci, Dept Geophys & Space Sci, Pazmany Peter Setany 1-C, H-1117 Budapest, Hungary.
C3 Eotvos Lorand University; Eotvos Lorand University
RP Szabó, Z (corresponding author), Eotvos Lorand Univ, Inst Geog & Earth Sci, Jozsef & Erzsebet Toth Endowed Hydrogeol Chair, Dept Geol, Pazmany Peter Setany 1-C, H-1117 Budapest, Hungary.
EM szazsoka@staff.elte.hu
RI Mádl-Szőnyi, Judit/H-5042-2017; Toth, Adam/H-1506-2017
OI Toth, Adam/0000-0002-7300-6687; Madl-Szonyi, Judit/0000-0002-5628-4386;
   Szabo, Zsoka/0000-0001-8912-4218; Szijarto, Mark/0000-0001-5408-4092
FU Doctoral Student Scholarship Program of the Co-operative Doctoral
   Program of the Ministry of Innovation and Technology financed from the
   National Research, Development and Innovation Fund; National
   Multidisciplinary Laboratory for Climate Change
   [RRF-2.3.1-21-2022-00014]
FX The doctoral research of Zsoka Szabo was supported by the Doctoral
   Student Scholarship Program of the Co-operative Doctoral Program of the
   Ministry of Innovation and Technology financed from the National
   Research, Development and Innovation Fund. This research was funded by
   the National Multidisciplinary Laboratory for Climate Change,
   RRF-2.3.1-21-2022-00014 project.
CR Abbo H, 2008, DESALINATION, V226, P47, DOI 10.1016/j.desal.2007.01.233
   Al Atawneh D, 2021, J HYDROL, V601, DOI 10.1016/j.jhydrol.2021.126602
   Alam M.F., 2020, UNDERGROUND TRANSFER
   Alam S, 2021, SCI TOTAL ENVIRON, V768, DOI 10.1016/j.scitotenv.2021.144992
   Aldous AR, 2021, ECOHYDROLOGY, V14, DOI 10.1002/eco.2342
   Alfoldi L., 2011, HIDROL KOZLONY, V91, P1
   Alkhatib J, 2021, ENVIRON EARTH SCI, V80, DOI 10.1007/s12665-021-09797-y
   Amanambu AC, 2020, J HYDROL, V589, DOI 10.1016/j.jhydrol.2020.125163
   An R, 2015, HYDROGEOL J, V23, P397, DOI 10.1007/s10040-014-1197-y
   [Anonymous], 2013, FEFLOW: a finite-element ground water flow and transport modeling tool
   Arnell NW, 2016, CLIMATIC CHANGE, V134, P457, DOI 10.1007/s10584-014-1281-2
   Bahar T, 2021, J CONTAM HYDROL, V237, DOI 10.1016/j.jconhyd.2020.103758
   Bouwer H, 2002, HYDROGEOL J, V10, P121, DOI 10.1007/s10040-001-0182-4
   Caligaris E, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9010014
   Cannavo P, 2018, INT J SEDIMENT RES, V33, P371, DOI 10.1016/j.ijsrc.2018.04.005
   Casanova J., 2016, INTEGRATED GROUNDWAT, P413, DOI [DOI 10.1007/978-3-319-23576-916, 10.1007/978-3-319-23576-9_16, DOI 10.1007/978-3-319-23576-9_16]
   Clark R, 2015, ENVIRON MODELL SOFTW, V72, P117, DOI 10.1016/j.envsoft.2015.07.009
   Dahlke HE, 2018, ADV CHEM POLL ENV MG, V3, P215, DOI 10.1016/bs.apmp.2018.07.003
   da Costa LRD, 2020, ENVIRON EARTH SCI, V79, DOI 10.1007/s12665-020-09003-5
   Dillon P, 2019, HYDROGEOL J, V27, P1, DOI 10.1007/s10040-018-1841-z
   Dillon P, 2005, HYDROGEOL J, V13, P313, DOI 10.1007/s10040-004-0413-6
   Dillon P, 2010, WATER SCI TECHNOL, V62, P2338, DOI 10.2166/wst.2010.444
   Dillon P., 2009, INTRO WATERLINES REP
   Dillon PJ, 2012, WATER RECLAMATION TECHNOLOGIES FOR SAFE MANAGED AQUIFER RECHARGE, P299
   DOMENICO PA, 1973, GEOL SOC AM BULL, V84, P3803, DOI 10.1130/0016-7606(1973)84<3803:TAOFCH>2.0.CO;2
   Engelen G.B., 1996, Hydrological systems analysis: Methods and applications
   Escalante EF, 2022, WATER-SUI, V14, DOI 10.3390/w14213405
   Escalante EF, 2020, ACQUE SOTTER, V9, P7, DOI 10.7343/as-2020-462
   Escalante EF, 2019, WATER-SUI, V11, DOI 10.3390/w11091943
   Freeze A.R., 1979, GROUNDWATER
   FREEZE RA, 1966, WATER RESOUR RES, V2, P641, DOI 10.1029/WR002i004p00641
   GABRIS G, 1994, TERRA NOVA, V6, P495, DOI 10.1111/j.1365-3121.1994.tb00893.x
   Gábris G, 2012, NETH J GEOSCI, V91, P111
   Gale I., 2005, Strategies for managed aquifer recharge (MAR) in semi-arid areas
   Gale I., 2002, The effectiveness of Artificial Recharge of groundwater: a review
   Gale I., 2006, Managed Aquifer Recharge: An Assessment of Its Role and Effectiveness in Watershed Management: Final Report for DFID KAR Project R8169
   Ganot Y, 2017, HYDROL EARTH SYST SC, V21, P4479, DOI 10.5194/hess-21-4479-2017
   GEO-SLOPE, 2015, SEEPAGE MODELING SEE
   Ghasemi A, 2017, J WATER SUPPLY RES T, V66, P141, DOI 10.2166/aqua.2017.049
   Gyiran I., 2009, P MAG HIDR TARS 27 O
   HANTUSH MS, 1967, WATER RESOUR RES, V3, P227, DOI 10.1029/WR003i001p00227
   Harrison PA, 2015, CLIMATIC CHANGE, V128, P279, DOI 10.1007/s10584-014-1239-4
   Havril T, 2018, J HYDROL, V563, P1169, DOI 10.1016/j.jhydrol.2017.09.020
   Casas JDH, 2022, WATER-SUI, V14, DOI 10.3390/w14223703
   IGRAC, 2007, ARTIFICIAL RECHARGE
   Imig A, 2022, INTEGR ENVIRON ASSES, V18, P1513, DOI 10.1002/ieam.4584
   Jiang XW, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL041251
   Kacimov AR, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-015-5137-5
   Kiss T, 2015, QUATERN INT, V388, P142, DOI 10.1016/j.quaint.2014.05.050
   Kourakos G, 2019, WATER RESOUR RES, V55, P7464, DOI 10.1029/2018WR024019
   Kovács AD, 2017, EUR COUNTRYS, V9, P29, DOI 10.1515/euco-2017-0003
   Kuti L., 1989, ALFOLD FOLDTANI ATLA
   Mádl-Szonyi J, 2009, HYDROGEOL J, V17, P961, DOI 10.1007/s10040-008-0421-z
   Major P., 1988, Vizugyi Kozlemenyek, V70, P605
   Marino M. A., 1974, Journal of Hydrology, V22, P295, DOI 10.1016/0022-1694(74)90082-1
   MARINO MA, 1974, J HYDROL, V23, P289, DOI 10.1016/0022-1694(74)90009-2
   MARINO MA, 1967, J GEOPHYS RES, V72, P1195, DOI 10.1029/JZ072i004p01195
   Masetti M, 2016, WATER RESOUR MANAG, V30, P149, DOI 10.1007/s11269-015-1151-3
   Massuel S, 2014, J HYDROL, V512, P157, DOI 10.1016/j.jhydrol.2014.02.062
   Missimer TM, 2017, WATER-SUI, V9, DOI 10.3390/w9100774
   Modflow H. A., 2005, The U.S. Geological Survey Modular Groundwater Model, the Groundwater Flow Process
   Nagy I., 2016, HIDROL K ZL NY, V96, P42
   Nemere P., 1994, V Z GYI K ZLEM NYEK, V76, P339
   NRMMC EPHC NHMRC, 2009, AUSTR GUID WAT REC C, V2C
   OHogain S., 2018, TECHNOLOGY PORTFOLIO
   Olah S, 2022, THESIS EOTVOS LORAND
   Orloci I., 2003, HIDROL KOZLONY, V83, P243
   Palfai I., 2010, HIDROL GIAI K ZL NY, V90, P40
   Palfai I, 1993, V Z GYI K ZLEM NYEK, V75, P431
   Pavelic P., 2020, MANAGED AQUIFER RECH
   Pyne RDG., 2005, Aquifer storage recovery: a guide to groundwater recharge through wells
   Qi TS, 2021, WATER-SUI, V13, DOI 10.3390/w13081052
   Racz AJ, 2012, GROUND WATER, V50, P562, DOI 10.1111/j.1745-6584.2011.00875.x
   Rahman MA, 2013, J ENVIRON MANAGE, V124, P25, DOI 10.1016/j.jenvman.2013.03.023
   Ringleb J, 2016, WATER-SUI, V8, DOI 10.3390/w8120579
   Scanlon BR, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/035013
   Scherberg J, 2014, WATER RESOUR MANAG, V28, P4971, DOI 10.1007/s11269-014-0780-2
   Simon S, 2011, HYDROGEOL J, V19, P701, DOI 10.1007/s10040-011-0711-8
   SINGH R, 1976, WATER RESOUR RES, V12, P775, DOI 10.1029/WR012i004p00775
   Smith AJ, 2012, GROUND WATER, V50, P133, DOI 10.1111/j.1745-6584.2011.00808.x
   Sprenger C, 2017, HYDROGEOL J, V25, P1909, DOI 10.1007/s10040-017-1554-8
   Stefan C, 2018, SUST WAT RESOUR MAN, V4, P153, DOI 10.1007/s40899-017-0212-6
   Szabó Z, 2023, GROUNDWATER SUST DEV, V20, DOI 10.1016/j.gsd.2022.100884
   Szijartó M, 2019, J HYDROL, V572, P364, DOI 10.1016/j.jhydrol.2019.03.003
   Szilagyi J., 1997, J. Hydrol. Hydromech., V45, P328
   Tóth J, 1999, HYDROGEOL J, V7, P1, DOI 10.1007/s100400050176
   TOTH J, 1970, Journal of Hydrology (Amsterdam), V10, P164, DOI 10.1016/0022-1694(70)90186-1
   TOTH J, 1962, J GEOPHYS RES, V67, P4375, DOI 10.1029/JZ067i011p04375
   Toth J., 1995, HYDROGEOL J, V3, P4, DOI [10.1007/s100400050250, DOI 10.1007/S100400050250]
   Trásy-Havril T, 2022, WATER-SUI, V14, DOI 10.3390/w14193026
   Tzoraki O, 2018, SCI TOTAL ENVIRON, V626, P875, DOI 10.1016/j.scitotenv.2018.01.160
   Ujhazy N., 2013, T J KOL GIAI LAPOK, V11, P291, DOI [10.56617/tl.3755, DOI 10.56617/TL.3755]
   UN WATER, 2018, UN WORLD WAT DEV REP
   van Engelenburg J, 2018, WATER RESOUR MANAG, V32, P259, DOI 10.1007/s11269-017-1808-1
   Van Houtte E, 2021, INT J WATER RESOUR D, V37, P1027, DOI 10.1080/07900627.2020.1858035
   VANGENUCHTEN MT, 1980, SOIL SCI SOC AM J, V44, P892, DOI 10.2136/sssaj1980.03615995004400050002x
   Ward JD, 2009, J HYDROL, V370, P83, DOI 10.1016/j.jhydrol.2009.02.055
   Ward J, 2012, HYDROGEOL J, V20, P943, DOI 10.1007/s10040-012-0865-z
   Woessner WilliamW., 2020, Hydrogeologic Properties of Earth Materials and Principles of Groundwater Flow
   Wu PP, 2021, HYDROGEOL J, V29, P2107, DOI 10.1007/s10040-021-02375-3
   Yaraghi N, 2019, SCI TOTAL ENVIRON, V675, P429, DOI 10.1016/j.scitotenv.2019.04.253
   Yousif N., 2022, THESIS EOTVOS LORAND
   Zimmerman W.B., 2006, MULTIPHYSICS MODELIN, V18
   Zlotnik VA, 2017, GROUNDWATER, V55, P797, DOI 10.1111/gwat.12530
   Zou ZK, 2019, WATER-SUI, V11, DOI 10.3390/w11051083
NR 105
TC 5
Z9 5
U1 4
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD MAR
PY 2023
VL 15
IS 6
AR 1077
DI 10.3390/w15061077
PG 27
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA C2IQ7
UT WOS:000960220000001
OA gold
DA 2025-01-10
ER

PT J
AU Furlan, E
   Derepasko, D
   Torresan, S
   Pham, H
   Fogarin, S
   Critto, A
AF Furlan, Elisa
   Derepasko, Diana
   Torresan, Silvia
   Pham, Hung, V
   Fogarin, Stefano
   Critto, Andrea
TI Ecosystem services at risk in Italy from coastal inundation under
   extreme sea level scenarios up to 2050: A spatially resolved approach
   supporting climate change adaptation
SO INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT
LA English
DT Article
DE Climate change; Coastal flooding; Ecosystem services; Risk assessment;
   Sea level rise
ID CHANGE IMPACTS; BIODIVERSITY
AB According to the latest projections of the Intergovernmental Panel on Climate Change, at the end of the century, coastal zones and low-lying ecosystems will be increasingly threatened by rising global mean sea levels. In order to support integrated coastal zone management and advance the basic source-pathway-receptor-consequence" approach focused on traditional receptors (e.g., population, infrastructure, and economy), a novel risk framework is proposed able to evaluate potential risks of loss or degradation of ecosystem services (ESs) due to projected extreme sea level scenarios in the Italian coast. Three risk scenarios for the reference period (1969-2010) and future time frame up to 2050 under RCP4.5 and RCP8.5 are developed by integrating extreme water-level projections related to changing climate conditions, with vulnerability information about the topography, distance from coastlines, and presence of artificial protections. A risk assessment is then performed considering the potential effects of the spatial-temporal variability of inundations and land use on the supply level and spatial distribution of ESs. The results of the analysis are summarized into a spatially explicit risk index, useful to rank coastal areas more prone to ESs losses or degradation due to coastal inundation at the national scale. Overall, the Northern Adriatic coast is scored at high risk of ESs loss or degradation in the future scenario. Other small coastal strips with medium risk scores are the Eastern Puglia coast, Western Sardinia, and Tuscany's coast. The ESs Coastal Risk Index provides an easy-to-understand screening assessment that could support the prioritization of areas for coastal adaptation at the national scale. Moreover, this index allows the direct evaluation of the public value of ecosystems and supports more effective territorial planning and environmental management decisions. In particular, it could support the mainstreaming of ecosystem-based approaches (e.g., ecological engineering and green infrastructures) to mitigate the risks of climate change and extreme events while protecting ecosystems and biodiversity. (C) 2021 SETAC
C1 [Furlan, Elisa; Derepasko, Diana; Torresan, Silvia; Pham, Hung, V; Fogarin, Stefano; Critto, Andrea] Fdn Ctr Euro Mediterraneo Cambiamenti Climat, Lecce, Italy.
   [Furlan, Elisa; Torresan, Silvia; Pham, Hung, V; Fogarin, Stefano; Critto, Andrea] Univ Ca Foscari Venice, Dept Environm Sci Informat & Stat, I-30170 Venice, Italy.
C3 Universita Ca Foscari Venezia
RP Critto, A (corresponding author), Univ Ca Foscari Venice, Dept Environm Sci Informat & Stat, I-30170 Venice, Italy.
EM critto@unive.it
RI Furlan, Elisa/AAA-4247-2021
OI Derepasko, Diana/0000-0002-2030-9297; TORRESAN,
   Silvia/0000-0002-9758-7084
FU European Union Humanitarian Aid and Civil Protection
   [ECHO/SUB/2016/742473/PREV16]
FX The authors gratefully acknowledge Dr. Marco Anzidei for his relevant
   advice within the hazard assessment phase, as well as the ISOTECH Team
   (Dr. Xenia Loizidou, Dr. Demetra Orthodoxou, and Dr. Demetra Petsa) for
   the analysis of the risk perceptions of Italian stakeholders. The
   research leading to these results has been funded by the SaveMedCoast
   project (Sea level rise scenarios along the Mediterranean coasts, )
   funded by the European Union Humanitarian Aid and Civil Protection
   (Reference number: ECHO/SUB/2016/742473/PREV16).
CR Abadie LM, 2018, J CLEAN PROD, V175, P582, DOI 10.1016/j.jclepro.2017.11.069
   Allen JL, 2016, BIOL CONSERV, V202, P119, DOI 10.1016/j.biocon.2016.08.031
   [Anonymous], 2004, Gli habitat secondo la nomenclatura EUNIS: manuale di classificazione per la realta italiana
   Antonioli F, 2017, QUATERNARY SCI REV, V158, P29, DOI 10.1016/j.quascirev.2016.12.021
   Antonioli F, 2020, WATER-SUI, V12, DOI 10.3390/w12082173
   Bai Y, 2019, ECOL INDIC, V102, P51, DOI 10.1016/j.ecolind.2019.01.079
   Baranzelli C., 2015, 27019 EUR, DOI [10.2788/85104, DOI 10.2788/85104]
   Chiu MC, 2017, TERR ATMOS OCEAN SCI, V28, P57, DOI 10.3319/TAO.2016.06.30.01(CCA)
   Courchamp F, 2014, TRENDS ECOL EVOL, V29, P127, DOI 10.1016/j.tree.2014.01.001
   Falcucci A, 2007, LANDSCAPE ECOL, V22, P617, DOI 10.1007/s10980-006-9056-4
   Finney StanleyC., 2016, GSA TODAY, V26, P4, DOI [10.1130/GSATG270A.1, DOI 10.1130/GSATG270A.1]
   Furlan E, 2021, SCI TOTAL ENVIRON, V772, DOI 10.1016/j.scitotenv.2020.144650
   Furlan E, 2018, SCI TOTAL ENVIRON, V618, P1008, DOI 10.1016/j.scitotenv.2017.09.076
   Gallina V, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093697
   Gallina V, 2019, WATER-SUI, V11, DOI 10.3390/w11061300
   Haines-Young R., 2018, One Ecosystem, V3, pe27108, DOI 10.3897/oneeco.3.e27108
   Horton BP, 2020, NPJ CLIM ATMOS SCI, V3, DOI 10.1038/s41612-020-0121-5
   Intergovernmental Panel on Climate Change (IPCC), 2019, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI 10.1017/CBO9781107415324.024
   Lambeck K, 2011, QUATERN INT, V232, P250, DOI 10.1016/j.quaint.2010.04.026
   Lionello P, 2017, GLOBAL PLANET CHANGE, V151, P80, DOI 10.1016/j.gloplacha.2016.06.012
   Maes J., 2015, Mapping and Assessment of Ecosystems and their Services: Trends in ecosystems and ecosystem services in the European Union between 2000 and 2010
   Marsico A, 2017, J MAPS, V13, P961, DOI 10.1080/17445647.2017.1415989
   Meier HEM, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00046
   Mentaschi L., 2016, Hydrol. Earth Syst. Sci. Discuss., P1, DOI [10.5194/hess-2016-65, DOI 10.5194/HESS-2016-65]
   Munns WR, 2017, INTEGR ENVIRON ASSES, V13, P62, DOI 10.1002/ieam.1835
   Peltier WR, 2004, ANNU REV EARTH PL SC, V32, P111, DOI 10.1146/annurev.earth.32.082503.144359
   Prakash S., 2021, International Journal of Biological Innovations, V1, P60, DOI [DOI 10.46505/IJBI.2019.1205, 10.46505/IJBI.2019.1205]
   Ramasubramanian L, 2009, J PLAN LIT, V23, P263, DOI 10.1177/0885412208327016
   Rizzi J, 2017, J COAST CONSERV, V21, P453, DOI 10.1007/s11852-017-0517-5
   Runting RK, 2018, J APPL ECOL, V55, P2193, DOI 10.1111/1365-2664.13190
   Santini M, 2011, REG ENVIRON CHANGE, V11, P483, DOI 10.1007/s10113-010-0157-x
   Satta A, 2017, INT J DISAST RISK RE, V24, P284, DOI 10.1016/j.ijdrr.2017.06.018
   Stocker, 2014, CLIMATE CHANGE 2013
   Torresan S, 2020, INTEGR ENVIRON ASSES, V16, P761, DOI 10.1002/ieam.4280
   Torresan S, 2016, OCEAN COAST MANAGE, V120, P49, DOI 10.1016/j.ocecoaman.2015.11.003
   Trégarot E, 2021, SCI TOTAL ENVIRON, V763, DOI 10.1016/j.scitotenv.2020.143004
   Tsendbazar N, 2021, REMOTE SENS ENVIRON, V266, DOI 10.1016/j.rse.2021.112686
   Vojinovic Z, 2017, ENVIRONMENTS, V4, DOI 10.3390/environments4010003
   Vousdoukas MI, 2017, EARTHS FUTURE, V5, P304, DOI 10.1002/2016EF000505
   Wahl T, 2016, J GEOPHYS RES-OCEANS, V121, P1274, DOI 10.1002/2015JC011057
   Weissenberger S, 2015, SPRINGERBR ENV SCI, P1, DOI 10.1007/978-94-017-9888-4
   Xia M, 2021, ECOL INDIC, V123, DOI 10.1016/j.ecolind.2020.107274
   Zambon I, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041159
NR 43
TC 4
Z9 4
U1 5
U2 30
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1551-3777
EI 1551-3793
J9 INTEGR ENVIRON ASSES
JI Integr. Environ. Assess. Manag.
PD NOV
PY 2022
VL 18
IS 6
BP 1564
EP 1577
DI 10.1002/ieam.4620
EA MAY 2022
PG 14
WC Environmental Sciences; Toxicology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Toxicology
GA 5V5QV
UT WOS:000796550900001
PM 35429140
DA 2025-01-10
ER

PT J
AU Antongiovanni, M
   Venticinque, EM
   Tambosi, LR
   Matsumoto, M
   Metzger, JP
   Fonseca, CR
AF Antongiovanni, Marina
   Venticinque, Eduardo M.
   Tambosi, Leandro R.
   Matsumoto, Marcelo
   Metzger, Jean Paul
   Fonseca, Carlos Roberto
TI Restoration priorities for Caatinga dry forests: Landscape resilience,
   connectivity and biodiversity value
SO JOURNAL OF APPLIED ECOLOGY
LA English
DT Article
DE biodiversity; Brazil; conservation; endemism; graph theory; planning;
   protected area; threatened species
ID ECOSYSTEM SERVICES; HABITAT PATCHES; CONSERVATION; CLIMATE
AB Restoration actions can halt biodiversity loss and rescue its services. However, in order to be effective, priority areas for restoration should be chosen based on objective large-scale restoration planning. Here, a multicriteria graph theory framework was used to propose restoration priority areas for the Brazilian Caatinga, the largest seasonally dry tropical forest of the New World, based on landscape resilience, landscape connectivity and biodiversity conservation value, focusing on threatened endemic plant species. We applied this graph theory framework to 10,406 Caatinga catchment basins. Vegetation cover and within-catchment connectivity were used to select catchments of intermediate landscape resilience, which in principle offer more effective opportunities for restoration. Then, such catchments were independently classified into (a) three classes according their contribution for between-catchment connectivity and (b) three classes according their value for biodiversity conservation, estimated by the richness of threatened, endemic plant species. By the integration of landscape resilience, landscape connectivity and biodiversity conservation values, three priority classes for restoration were generated. The multicriteria framework generated several restoration priority cut-offs. Prioritization based on landscape resilience selected 36% of the Caatinga catchments as high priority for restoration. By independently adding landscape connectivity and biodiversity conservation value, only 12% and 3% of the catchments, respectively, were considered as high priority. By combining all three criteria, 9% of the catchments were selected as high priority and Synthesis and applications. Restoration of drylands can contribute immensely to the conservation of its threatened biodiversity but large-scale planning is quintessential. Here, a multicriteria graph theory framework was applied to indicate priority areas for restoration, which maximizes the effectiveness of restoration actions, landscape connectivity for climate change adaptation and conservation of threatened species. The framework was applied to the Caatinga, the largest seasonally dry tropical forest of the new world, but it can be applied world-wide under different budged limitations and spatial scales, being useful for private, state and federal initiatives.
C1 [Antongiovanni, Marina; Venticinque, Eduardo M.; Fonseca, Carlos Roberto] Univ Fed Rio Grande do Norte, Dept Ecol, Natal, RN, Brazil.
   [Tambosi, Leandro R.] Univ Fed ABC, Ctr Engn Modelagem & Ciencias Socials Aplicadas, Santo Andre, SP, Brazil.
   [Matsumoto, Marcelo] World Resources Inst Brazil, Sao Paulo, Brazil.
   [Metzger, Jean Paul] Univ Sao Paulo, Dept Ecol, Sao Paulo, Brazil.
C3 Universidade Federal do Rio Grande do Norte; Universidade Federal do ABC
   (UFABC); Universidade de Sao Paulo
RP Fonseca, CR (corresponding author), Univ Fed Rio Grande do Norte, Dept Ecol, Natal, RN, Brazil.
EM fonseca.crsd@gmail.com
RI Antongiovanni, Marina/KRP-8017-2024; Metzger, Jean Paul/C-2514-2012;
   Reverberi Tambosi, Leandro/B-2359-2013; Fonseca, Carlos
   Roberto/V-5869-2017; Venticinque, Eduardo/G-8961-2015
OI Antongiovanni, Marina/0000-0002-6171-9620; Metzger, Jean
   Paul/0000-0002-0087-5240; Reverberi Tambosi,
   Leandro/0000-0001-5486-7310; Fonseca, Carlos
   Roberto/0000-0003-0292-0399; Venticinque, Eduardo/0000-0002-3455-9107
FU Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
   [308040/2017--1, 305304/2013--5]
FX Conselho Nacional de Desenvolvimento Cientifico e Tecnologico,
   Grant/Award Number: 308040/2017--1 and 305304/2013--5
CR ANDRADE EM, 2017, CAATINGA LARGEST TRO, P281
   Antongiovanni M, 2020, J APPL ECOL, V57, P2064, DOI 10.1111/1365-2664.13686
   Antongiovanni M, 2018, LANDSCAPE ECOL, V33, P1353, DOI 10.1007/s10980-018-0672-6
   Baudry J, 2003, LANDSCAPE ECOL, V18, P303, DOI 10.1023/A:1024465200284
   Beyer HL, 2016, ECOL MODEL, V328, P14, DOI 10.1016/j.ecolmodel.2016.02.005
   Bezerra FGS, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106579
   Bodin Ö, 2010, ECOL MODEL, V221, P2393, DOI 10.1016/j.ecolmodel.2010.06.017
   Bottrill MC, 2008, TRENDS ECOL EVOL, V23, P649, DOI 10.1016/j.tree.2008.07.007
   Bunn AG, 2000, J ENVIRON MANAGE, V59, P265, DOI 10.1006/jema.2000.0373
   Chazdon RL, 2017, CONSERV LETT, V10, P125, DOI 10.1111/conl.12220
   da SilvaJ.M. C., 2018, Caatinga. s.l., DOI 10.1007/978-3-319-68339-3_13
   de Queiroz L., 2017, CAATINGA LARGEST TRO, P23, DOI [DOI 10.1007/978-3-319-68339-3_2, 10.1007/978-3-319-68339-32, DOI 10.1007/978-3-319-68339-32]
   Doerr VAJ, 2011, J APPL ECOL, V48, P143, DOI 10.1111/j.1365-2664.2010.01899.x
   Donald PF, 2006, J APPL ECOL, V43, P209, DOI 10.1111/j.1365-2664.2006.01146.x
   Fonseca CR., 2017, Caatinga: the largest tropical dry forest region in South America, P429, DOI [10.1007/978-3-319-68339-317, DOI 10.1007/978-3-319-68339-3_17]
   Gourevitch JD, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/11/114027
   Holl KD, 2011, FOREST ECOL MANAG, V261, P1558, DOI 10.1016/j.foreco.2010.07.004
   Huxel GR, 1999, RESTOR ECOL, V7, P309, DOI 10.1046/j.1526-100X.1999.72024.x
   Leite MD, 2013, NAT CONSERVACAO, V11, P108
   Manhaes AP, 2016, DIVERS DISTRIB, V22, P932, DOI 10.1111/ddi.12459
   MapBiomas, 2020, REL RIO AN DESM NO B
   Margules CR, 2000, NATURE, V405, P243, DOI 10.1038/35012251
   Martinelli G., 2013, Livro Vermelho da Flora do Brasil
   Metzger, 2019, NAT CONSERVACAO, V8, P1
   Overbeck GE, 2015, DIVERS DISTRIB, V21, P1455, DOI 10.1111/ddi.12380
   Rappaport DI, 2015, J APPL ECOL, V52, P590, DOI 10.1111/1365-2664.12405
   Benayas JMR, 2009, SCIENCE, V325, P1121, DOI 10.1126/science.1172460
   Rudnick D. A., 2012, Issues in Ecology, V16, P1, DOI [10.1095/biolreprod46.1.155, DOI 10.1095/BIOLREPROD46.1.155]
   Saura S, 2009, ENVIRON MODELL SOFTW, V24, P135, DOI 10.1016/j.envsoft.2008.05.005
   Saura S, 2007, LANDSCAPE URBAN PLAN, V83, P91, DOI 10.1016/j.landurbplan.2007.03.005
   Seddon AWR, 2016, NATURE, V531, P229, DOI 10.1038/nature16986
   Silva JMC, 2017, Caatinga: The Largest Tropical Dry Forest Region in South America, P3, DOI [10.1007/978-3-319-68339-3, DOI 10.1007/978-3-319-68339-31]
   Stefanes M, 2016, ECOL SOC, V21, DOI 10.5751/ES-08922-210454
   Strassburg BBN, 2020, NATURE, V586, P724, DOI 10.1038/s41586-020-2784-9
   Strassburg BBN, 2019, NAT ECOL EVOL, V3, P62, DOI 10.1038/s41559-018-0743-8
   Suding KN, 2004, TRENDS ECOL EVOL, V19, P46, DOI 10.1016/j.tree.2003.10.005
   Tambosi LR, 2014, RESTOR ECOL, V22, P169, DOI 10.1111/rec.12049
   Urban D, 2001, ECOLOGY, V82, P1205, DOI 10.1890/0012-9658(2001)082[1205:LCAGTP]2.0.CO;2
   Zwiener VP, 2017, DIVERS DISTRIB, V23, P955, DOI 10.1111/ddi.12588
NR 39
TC 15
Z9 16
U1 5
U2 58
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0021-8901
EI 1365-2664
J9 J APPL ECOL
JI J. Appl. Ecol.
PD SEP
PY 2022
VL 59
IS 9
BP 2287
EP 2298
DI 10.1111/1365-2664.14131
EA MAR 2022
PG 12
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 4G6VQ
UT WOS:000763120200001
DA 2025-01-10
ER

PT J
AU Nishina, K
   Ito, A
   Zhou, F
   Yan, X
   Hayashi, S
   Winiwarter, W
AF Nishina, K.
   Ito, A.
   Zhou, F.
   Yan, X.
   Hayashi, S.
   Winiwarter, W.
TI Historical trends of riverine nitrogen loading from land to the East
   China Sea: a model-based evaluation
SO ENVIRONMENTAL RESEARCH COMMUNICATIONS
LA English
DT Article
DE N loading; point source; non-point source; East China sea
ID TERRESTRIAL BIOSPHERE; USE EFFICIENCY; EUTROPHICATION; POLLUTION;
   NITRATE; SYSTEM; DENITRIFICATION; FERTILIZER; OCEAN; N2O
AB East Asia is the one of the hotspot regions with too much reactive nitrogen (N) inputs from anthropogenic sources. Here, we evaluated historical total inorganic N (TIN) load from land to sea through the rivers surrounding the East China sea using biogeochemical model 'VISIT' combined with a newly developed VISIT Off-line River Nitrogen scheme (VISIToRN). VISIT calculated N cycling in both natural and agricultural ecosystems and VISIToRN calculated inorganic N transport and riverine denitrification through the river channels at half degree spatial resolution. Between 1961 and 2010, the estimated TIN load from land to the sea surrounding the East China Sea increased from 2.7 Tg-N Year(-1) to 5.5 Tg-N Year(-1), a twofold increase, while the anthropogenic N input to the East China Sea basin (N deposition, N fertilizer, manure, and human sewage) increased from 12.9 Tg-N Year(-1) to 36.9 Tg-N Year(-1), an increase of about 3 times. This difference in the rate of increase is due in large part to the terrestrial nitrogen budget, and the results of the model balance indicate that TIN load to rivers has been suppressed by improvements in fertilizer application rates, harvesting on agricultural land, and nitrogen accumulation in forests. The results of the model balance showed that the increase rate of nitrogen runoff from Chinese rivers has been declining since 2000. In our estimation by VISIToRN, the amount of nitrogen removed by river denitrification in the river channel before the mouth is not negligible, ranging from 1.6 Tg-N Year(-1) to 2.16 Tg-N Year(-1). The N load from agricultural sources is still significant and needs to be further reduced. TIN load tended to increase in years with high precipitation. In order to effectively reduce TIN load, it is necessary to consider climate change-adaptive agricultural N management.
C1 [Nishina, K.; Ito, A.; Hayashi, S.] Natl Inst Environm Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
   [Zhou, F.] Peking Univ, Coll Urban & Environm Sci, Sino France Inst Earth Syst Sci, Lab Earth Surface Proc, Beijing 100871, Peoples R China.
   [Yan, X.] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.
   [Winiwarter, W.] Int Inst Appl Syst Anal IIASA, A-2361 Laxenburg, Austria.
   [Winiwarter, W.] Univ Zielona Gora, Inst Environm Engn, PL-65417 Zielona Gora, Poland.
C3 National Institute for Environmental Studies - Japan; Peking University;
   Chinese Academy of Sciences; Nanjing Institute of Soil Science, CAS;
   International Institute for Applied Systems Analysis (IIASA); University
   of Zielona Gora
RP Nishina, K (corresponding author), Natl Inst Environm Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
EM nishina.kazuya@nies.go.jp
RI Nishina, Kazuya/KIB-4227-2024; Zhou, Feng/C-9377-2011; Winiwarter,
   Wilfried/F-5073-2017; Ito, Akihiko/P-2624-2017
OI Zhou, Feng/0000-0001-6122-0611; Nishina, Kazuya/0000-0002-8820-1282;
   Winiwarter, Wilfried/0000-0001-7131-1496; Ito,
   Akihiko/0000-0001-5265-0791
FU Environment Research and Technology Development Fund of the
   Environmental Restoration and Conservation Agency of Japan
   [JPMEERF20182R02]; JSPS KAKENHI [17H01867]; Grants-in-Aid for Scientific
   Research [17H01867] Funding Source: KAKEN
FX The authors would like to thank the members of INMS East-Asian
   demonstration. Wegreatly appreciate Pro. Xiaotang Ju of China
   Agricultural University, Pro. Baojing Gu of Zhejiang University and Dr.
   Kentaro Hayashi for valuable comments on this study and warm
   encouragements. K.N was supported by the Environment Research and
   Technology Development Fund JPMEERF20182R02 of the Environmental
   Restoration and Conservation Agency of Japan and JSPS KAKENHI Grant
   Number 17H01867.
CR Ballard TC, 2019, ENVIRON SCI TECHNOL, V53, P5080, DOI 10.1021/acs.est.8b06898
   Beusen AHW, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/3/034035
   Bouwman AF, 2013, PHILOS T R SOC B, V368, DOI 10.1098/rstb.2013.0112
   Bouwman AF, 2005, GLOBAL BIOGEOCHEM CY, V19, DOI 10.1029/2004GB002314
   Bowles TM, 2018, NAT SUSTAIN, V1, P399, DOI 10.1038/s41893-018-0106-0
   Breitburg D, 2018, SCIENCE, V359, P46, DOI 10.1126/science.aam7240
   Chen CTA, 2008, J OCEANOGR, V64, P737, DOI 10.1007/s10872-008-0062-9
   Chen NW, 2014, AGR ECOSYST ENVIRON, V189, P1, DOI 10.1016/j.agee.2014.03.004
   Chen XJ, 2019, SCI TOTAL ENVIRON, V671, P1282, DOI 10.1016/j.scitotenv.2019.03.323
   Dentener F, 2006, GLOBAL BIOGEOCHEM CY, V20, DOI 10.1029/2005GB002672
   Dumont E, 2005, GLOBAL BIOGEOCHEM CY, V19, DOI 10.1029/2005GB002488
   Galloway JN, 2003, BIOSCIENCE, V53, P341, DOI 10.1641/0006-3568(2003)053[0341:TNC]2.0.CO;2
   Gao J, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15788-7
   Goldewijk KK, 2017, EARTH SYST SCI DATA, V9, P927, DOI 10.5194/essd-9-927-2017
   Greaver TL, 2016, NAT CLIM CHANGE, V6, P836, DOI [10.1038/NCLIMATE3088, 10.1038/nclimate3088]
   Gruber N, 2008, NATURE, V451, P293, DOI 10.1038/nature06592
   Gu BJ, 2015, P NATL ACAD SCI USA, V112, P8792, DOI 10.1073/pnas.1510211112
   Gu BJ, 2013, GLOBAL ENVIRON CHANG, V23, P1112, DOI 10.1016/j.gloenvcha.2013.05.004
   Gu BJ, 2012, ENVIRON POLLUT, V171, P30, DOI 10.1016/j.envpol.2012.07.015
   Guo JH, 2017, EARTHS FUTURE, V5, P285, DOI 10.1002/2016EF000433
   Hanasaki N, 2006, J HYDROL, V327, P22, DOI 10.1016/j.jhydrol.2005.11.011
   Harris I, 2014, INT J CLIMATOL, V34, P623, DOI 10.1002/joc.3711
   He B, 2011, WATER RES, V45, P2573, DOI 10.1016/j.watres.2011.02.011
   Hong J, 2008, ECOL MODEL, V212, P492, DOI 10.1016/j.ecolmodel.2007.10.048
   Howarth RW, 2008, HARMFUL ALGAE, V8, P14, DOI 10.1016/j.hal.2008.08.015
   Hurtt GC, 2011, CLIMATIC CHANGE, V109, P117, DOI 10.1007/s10584-011-0153-2
   Inatomi M, 2010, ECOSYSTEMS, V13, P472, DOI 10.1007/s10021-010-9332-7
   Ito A, 2018, PROG EARTH PLANET SC, V5, DOI 10.1186/s40645-018-0215-4
   Ito A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7a19
   Ito A, 2012, J HYDROMETEOROL, V13, P681, DOI 10.1175/JHM-D-10-05034.1
   Jin ShuQin Jin ShuQin, 2018, Journal of Resources and Ecology, V9, P50
   Ju XT, 2016, GLOBAL ENVIRON CHANG, V41, P26, DOI 10.1016/j.gloenvcha.2016.08.005
   Li DJ, 2004, AMBIO, V33, P107
   Li HM, 2014, HARMFUL ALGAE, V39, P92, DOI 10.1016/j.hal.2014.07.002
   Liu XC, 2018, WATER RES, V142, P246, DOI 10.1016/j.watres.2018.06.006
   Liu XJ, 2016, ENVIRON SCI TECHNOL, V50, P505, DOI 10.1021/acs.est.5b05972
   Liu XJ, 2013, NATURE, V494, P459, DOI 10.1038/nature11917
   Mayorga E, 2010, ENVIRON MODELL SOFTW, V25, P837, DOI 10.1016/j.envsoft.2010.01.007
   Monfreda C, 2008, GLOBAL BIOGEOCHEM CY, V22, DOI 10.1029/2007GB002947
   Müller B, 2012, GLOBAL BIOGEOCHEM CY, V26, DOI 10.1029/2011GB004273
   Mulholland PJ, 2009, LIMNOL OCEANOGR, V54, P666, DOI 10.4319/lo.2009.54.3.0666
   Nash J.E., 1957, INT ASS SCI HYDROL P, V45, P114
   Nishina K, 2017, EARTH SYST SCI DATA, V9, P149, DOI 10.5194/essd-9-149-2017
   Oki T., 1998, EARTH INTERACT, V2, P1, DOI [DOI 10.1175/1087-3562(1998)002<0001:DOTRIP>2.3.CO;2, DOI 10.1175/1087-3562(1998)0022.3.CO;2]
   Parton WJ, 1996, GLOBAL BIOGEOCHEM CY, V10, P401, DOI 10.1029/96GB01455
   Purcell JE, 2001, HYDROBIOLOGIA, V451, P27, DOI 10.1023/A:1011883905394
   Seitzinger S, 2006, ECOL APPL, V16, P2064, DOI 10.1890/1051-0761(2006)016[2064:DALAWA]2.0.CO;2
   Seitzinger SP, 2005, GLOBAL BIOGEOCHEM CY, V19, DOI 10.1029/2005GB002606
   Shang ZY, 2019, GLOBAL CHANGE BIOL, V25, P3706, DOI 10.1111/gcb.14741
   Shindo J, 2003, ECOL MODEL, V169, P197, DOI 10.1016/S0304-3800(03)00270-9
   Sinha E, 2017, SCIENCE, V357, P405, DOI 10.1126/science.aan2409
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Strokal M, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/2/024014
   Strokal M, 2014, MAR POLLUT BULL, V85, P123, DOI 10.1016/j.marpolbul.2014.06.011
   Sudo K, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD001113
   Ti CP, 2012, BIOGEOCHEMISTRY, V108, P381, DOI 10.1007/s10533-011-9606-y
   Tian HQ, 2020, NATURE, V586, P248, DOI 10.1038/s41586-020-2780-0
   Tian HQ, 2016, NATURE, V531, P225, DOI 10.1038/nature16946
   Wang BD, 2018, MAR POLLUT BULL, V136, P394, DOI 10.1016/j.marpolbul.2018.09.044
   Wang JJ, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001516
   Wang L, 2013, ENVIRON GEOCHEM HLTH, V35, P667, DOI 10.1007/s10653-013-9550-y
   Wang QH, 2020, NATL SCI REV, V7, P441, DOI 10.1093/nsr/nwz087
   Wang QX, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/11/115005
   Winiwarter W, 2013, CLIMATIC CHANGE, V120, P889, DOI 10.1007/s10584-013-0834-0
   Yamazaki D, 2019, WATER RESOUR RES, V55, P5053, DOI [10.1029/2019WR024873, 10.1029/2019wr024873]
   Yan WJ, 2004, ENVIRON CHEM, V1, P95, DOI 10.1071/EN04031
   Yan WJ, 2010, GLOBAL BIOGEOCHEM CY, V24, DOI 10.1029/2009GB003575
   Zhang BW, 2017, EARTH SYST SCI DATA, V9, P667, DOI 10.5194/essd-9-667-2017
   Zhang X, 2017, SCI TOTAL ENVIRON, V596, P61, DOI 10.1016/j.scitotenv.2017.04.064
NR 69
TC 2
Z9 2
U1 5
U2 31
PU IOP PUBLISHING LTD
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 2515-7620
J9 ENVIRON RES COMMUN
JI Environ. Res. Commun.
PD AUG 1
PY 2021
VL 3
IS 8
AR 085005
DI 10.1088/2515-7620/ac1ce8
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA UJ1KV
UT WOS:000691054000001
OA gold
DA 2025-01-10
ER

PT J
AU Diouf, NS
   Ouedraogo, I
   Zougmoré, RB
   Niang, M
AF Diouf, Ndeye Seynabou
   Ouedraogo, Issa
   Zougmore, Robert B.
   Niang, Madicke
TI Fishers' Perceptions and Attitudes toward Weather and Climate
   Information Services for Climate Change Adaptation in Senegal
SO SUSTAINABILITY
LA English
DT Article
DE climate; weather and climate information services; fisher folks;
   perceptions
ID IMPACTS
AB Climate variability has become a major issue for vital sectors in the context of climate change. In fisheries, in particular, the effects of climate change are reflected in the decline of fishing yield and loss of lives during extreme weather events in the sea. This study analyzed the perception of climate variability and change by fisher-folks, the attitude of fisher-folks toward the weather forecast and the adoption rate of the use of the weather forecast as well as the factors determining its use in Senegal. To this end, 576 fisher-folks belonging to 41 local fishing committees along the coastal areas were surveyed and focus group discussions were organized with key informants. The adoption rate was identified using the method of the average treatment effect (ATE) and the test of independency (chi-square) was used to analyze the perceptions of and beliefs on climate change. The results showed that 96% of fisher-folks perceive the change in the climate, though the effects are differently appreciated across the coastline. The most frequently observed effects are: coastal erosion, change in wind direction, increase in extreme swells and sea level rise. Nearly half of fisher-folks confirm that they noticed these changes over the past five years. In the Southern Coast in particular, 40% of fisher-folks stated that these changes happened 10 years ago. This statement is confirmed by the qualitative data. More than 90% of the respondents ascertain the weather forecast before going to fish, 63% regularly receive the weather forecast and 53% avoid going to sea during extreme events. In addition, the results showed that if the weather forecast was made accessible to the majority of fisher-folks, more than 83% would avoid going to sea during periods of extreme weather extreme events, thus reducing significantly the number of fatalities. The best way to protect the fisher-folks from the harmful effects of climate change is to ensure large-scale access to and use of accurate weather forecasts.
C1 [Diouf, Ndeye Seynabou; Ouedraogo, Issa; Zougmore, Robert B.] CGIAR Res Program Climate Change Agr & Food Secur, ICRISAT West & Cent Africa Reg Off, BP 320, Bamako, Mali.
   [Niang, Madicke] Initiat Prospect Agr & Rurale IPAR, BP 16788, Ouest Foire Dakar, Senegal.
C3 CGIAR
RP Diouf, NS (corresponding author), CGIAR Res Program Climate Change Agr & Food Secur, ICRISAT West & Cent Africa Reg Off, BP 320, Bamako, Mali.
EM S.Diouf@cgiar.org; i.ouedraogo@cgiar.org; r.zougmore@cgiar.org;
   madickee@yahoo.fr
OI Ouedraogo, Issa/0000-0002-5675-6769; Zougmore,
   Robert/0000-0002-6215-4852
FU USAID; CGIAR
FX The authors acknowledge the USAID funding support to the CINSERE project
   in Senegal and we are thankful to the IPAR for data collection and the
   community (fisher-folks and key informants) for their collaboration.
   USAID/CINSERE project is implemented through ICRISAT by the CGIAR
   Research Program on Climate Change, Agriculture and Food Security
   (CCAFS), a strategic partnership of CGIAR and Future Earth, led by the
   International Center for Tropical Agriculture (CIAT) and carried out
   with support from CGIAR Fund Donors and through bilateral funding
   agreements (For details please visit https://ccafs.cgiar.org/donors).We
   would like to express our deepest gratitude to the technicians of ANACIM
   who carried out the trainings on the ground.
CR Adger W. N., 2003, Progress in Development Studies, V3, P179, DOI 10.1191/1464993403ps060oa
   Aggarwal PK, 2018, ECOL SOC, V23, DOI 10.5751/ES-09844-230114
   [Anonymous], 2013, LIFE SCI J
   [Anonymous], 2006, AFRICA ENV OUTLOOK O
   [Anonymous], 2016, Agriculture Food Security, DOI [10.1186/s40066-016-0075-3, DOI 10.1186/S40066-016-0075-3]
   ANSD, 2018, SIT EC SOC SEN 2015, P11
   Brander KM, 2007, P NATL ACAD SCI USA, V104, P19709, DOI 10.1073/pnas.0702059104
   Broutin C., 2000, APERCU FILIERE HALIE
   Dennis K.C., 1995, J COASTAL RES, V14, P243
   Diagne A., 2012, WORKING PAPERS, DOI [10.22004/ag.econ.266589, DOI 10.22004/AG.ECON.266589]
   Diagne A, 2007, AGR ECON-BLACKWELL, V37, P201, DOI 10.1111/j.1574-0862.2007.00266.x
   Diakhate M., 2012, REV GEOGRAPHIE LABOR
   Dibba L., 2010, THESIS
   Diop S, 2011, TREATISE ON ESTUARINE AND COASTAL SCIENCE, VOL 11: MANAGEMENT OF ESTUARIES AND COASTS, P315
   Durand P, 2010, CYBERGEO, DOI 10.4000/cybergeo.23017
   FAO, 2007, INF COMM TTECHN BEN
   FAO, 2009, BNP REP
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Hasan Z, 2018, J ENVIRON PLANN MAN, V61, P1204, DOI 10.1080/09640568.2017.1339026
   HAUSMAN JA, 1978, ECONOMETRICA, V46, P403, DOI 10.2307/1913909
   Howell P, 2003, Indigenous Early Warning Indicators of Cyclones: Potential Application in Coastal Bangladesh
   Kenny C., 2008, P RUR FUT C PLYM UK
   Kularatne, 1997, INFORMATION DEV, V13, P117, DOI [10.1177/0266666974238708, DOI 10.1177/0266666974238708]
   Lam VWY, 2012, AFR J MAR SCI, V34, P103, DOI 10.2989/1814232X.2012.673294
   Mbaye A., 2020, SSRN ELECT J, DOI [10.2139/ssrn.3553622, DOI 10.2139/SSRN.3553622]
   Menon M, 2016, INDIAN J FISH, V63, P110, DOI 10.21077/ijf.2016.63.3.51566-16
   Mulyasari G, 2018, IOP C SER EARTH ENV, V200, DOI 10.1088/1755-1315/200/1/012037
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Niang I, 2010, GLOBAL PLANET CHANGE, V72, P294, DOI 10.1016/j.gloplacha.2010.01.005
   Niang Ndeye Astou., 2009, Dynamique socio-environnementale et developpement local des regions cotieres du Senegal: lexemple de la peche artisanale
   Niasse M., 2004, REDUCING W AFRICAS V, V17, P66
   Ninawe AS, 2018, BIOTECHNOLOGY FOR SUSTAINABLE AGRICULTURE: EMERGING APPROACHES AND STRATEGIES, P257, DOI 10.1016/B978-0-12-812160-3.00009-X
   Omar SZ., 2012, J BASIC APPL SCI RES, V2, P9905
   Ouedraogo I, 2018, CLIMATE, V6, DOI 10.3390/cli6010013
   Peden AE, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0196421
   Rana R., 2015, J Pract Cardiovasc Sci, V1, P69, DOI DOI 10.4103/2395-5414.157577
   Rao C.R., 2002, GOODNESS FIT TESTS M, DOI [10.1007/978-1-4612-0103-8_2, DOI 10.1007/978-1-4612-0103-8_2]
   Sagna P., 2016, Poll Atmos, DOI DOI 10.4267/POLLUTION-ATMOSPHERIQUE.5320
   Sall M., 2011, CHANGEMENTS CLIMATIQ, P49
   Sambou D., 2020, PAPIERS FOND, V23
   Shaffril HAM, 2013, INT J CLIM CHANG STR, V5, P38, DOI 10.1108/17568691311299354
   Wooldridge, 2002, ECONOMETRIC ANAL CRO
NR 42
TC 6
Z9 7
U1 0
U2 12
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD NOV
PY 2020
VL 12
IS 22
AR 9465
DI 10.3390/su12229465
PG 16
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA OY9FB
UT WOS:000594543500001
OA Green Accepted, gold
DA 2025-01-10
ER

PT J
AU Rhiney, K
   Eitzinger, A
   Farrell, AD
   Prager, SD
AF Rhiney, Kevon
   Eitzinger, Anton
   Farrell, Aidan D.
   Prager, Steven D.
TI Assessing the implications of a 1.5°C temperature limit for the Jamaican
   agriculture sector
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Small island developing states; Climate change; Agriculture; Adaptation;
   Jamaica; Caribbean
ID CLIMATE-CHANGE ADAPTATION; LOCAL KNOWLEDGE; DROUGHT; IMPACTS; FUTURE;
   MODEL; TRENDS; VULNERABILITY; HEAT; SEA
AB Despite recent calls to limit future increases in the global average temperature to well below 2 degrees C, little is known about how different climatic thresholds will impact human society. Future warming trends have significant global food security implications, particularly for small island developing states (SIDS) that are recognized as being among the most vulnerable to global climate change. In the case of the Caribbean, any significant change in the region's climate is likely to have significant adverse effects on the agriculture sector. This paper explores the potential biophysical impacts of a +1.5 degrees C warming scenario on several economically important crops grown in the Caribbean island of Jamaica. Also, it explores differences to a >2.0 degrees C warming scenario, which is more likely, if the current policy agreements cannot be complied with by the international community. We use the ECOCROP niche model to estimate how predicted changes in future climate could affect the growing conditions of several commonly cultivated crops from both future scenarios. We then discuss some key policy considerations for Jamaica's agriculture sector, specifically related to the challenges posed to future adaptation pathways amidst growing climate uncertainty and complexity. Our model results show that even an increase less than +1.5 degrees C is expected to have an overall negative impact on crop suitability and a general reduction in the range of crops available to Jamaican farmers. This observation is instructive as increases above the +1.5 degrees C threshold would likely lead to even more irreversible and potentially catastrophic changes to the sustainability of Jamaica's agriculture sector. The paper concludes by outlining some key considerations for future action, paying keen attention to the policy relevance of a +1.5 degrees C temperature limit. Given little room for optimism with respect to the imminent changes that SIDS will need to confront in the near future, broad-based policy engagement by stakeholders in these geographies is paramount, irrespective of the climate warming scenario.
C1 [Rhiney, Kevon] Rutgers State Univ, Dept Geog, 54 Joyce Kilmer Ave, Piscataway, NJ 08854 USA.
   [Eitzinger, Anton; Prager, Steven D.] Int Ctr Trop Agr, Valle Del Cauca, Colombia.
   [Farrell, Aidan D.] Univ West Indies, Dept Life Sci, Trinidad, Jamaica.
C3 Rutgers University System; Rutgers University New Brunswick; Alliance;
   International Center for Tropical Agriculture - CIAT; University West
   Indies Mona Jamaica
RP Rhiney, K (corresponding author), Rutgers State Univ, Dept Geog, 54 Joyce Kilmer Ave, Piscataway, NJ 08854 USA.
EM kevon.rhiney@rutgers.edu; A.Eitzinger@CGIAR.ORG;
   Aidan.Farrell@sta.uwi.edu; S.Prager@CGIAR.ORG
RI Eitzinger, Anton/AAU-4960-2020; Prager, Steven/ABD-2092-2020
OI Eitzinger, Anton/0000-0001-7317-3381
CR Adger WN, 2003, ECON GEOGR, V79, P387
   [Anonymous], AGR DIS RISK MAN PLA
   [Anonymous], 2009, Trans. Am. Geophys. Union, DOI DOI 10.1029/2009EO130003
   [Anonymous], 2016, Globalization, Agriculture and Food in the Caribbean: Climate Change, Gender and Geography, DOI [10.1057/978-1-137-53837-6_6, DOI 10.1057/978-1-137-53837-6_6]
   [Anonymous], GLOBAL CHANGE CARIBB
   [Anonymous], FEASABILITY LIMITING
   [Anonymous], 2016, Globalization, Agriculture and Food in the Caribbean, DOI [DOI 10.1057/978-1-137-53837-6, 10.1057/978-1-137-53837-6]
   [Anonymous], JAMAICA GLEANER 0801
   [Anonymous], 2013, CARIBB GEOGR
   [Anonymous], GLOBAL CHANGE CARIBB
   [Anonymous], JAMAICA GLEANER 1117
   [Anonymous], JAM I ENV PROF JIEP
   [Anonymous], 1985, PLANTATIONS PEASANTR
   [Anonymous], GLOBALIZATION AGR FO
   [Anonymous], 2014, PLANTS IN ACTION
   [Anonymous], CARIBBEAN GEOGRAPHY
   [Anonymous], CLIMATE CHANGE 2013
   [Anonymous], GLOBAL CHANGE CARIBB
   [Anonymous], 2016, STRUCTURAL ADJUSTMEN
   [Anonymous], GLOBAL CHANGE CARIBB
   [Anonymous], APPL PHYSL BREEDING
   [Anonymous], 2015, Caribbean Geography
   [Anonymous], 2007, CLIMATE CHANGE 2007
   [Anonymous], 2010, CURR OPIN PLANT BIOL, DOI DOI 10.1016/j.pbi.2010.04.008
   Barker D., 1993, Tijdschrift voor Economische en Sociale Geografie, V84, P332, DOI 10.1111/j.1467-9663.1993.tb00662.x
   Barker D., 2012, Caribbean Studies, V40, P41, DOI [DOI 10.1353/CRB.2012.0027, DOI 10.1353/crb.2012.0027]
   Barker D, 2006, TIJDSCHR ECON SOC GE, V97, P535, DOI 10.1111/j.1467-9663.2006.00362.x
   Barnston AG, 2010, J APPL METEOROL CLIM, V49, P493, DOI 10.1175/2009JAMC2325.1
   Beckford C., 2013, Domestic food production and food security in the Caribbean: Building capacity and strengthening local food production systems
   Beckford C, 2007, SINGAPORE J TROP GEO, V28, P273, DOI 10.1111/j.1467-9493.2007.00301.x
   Beckford C, 2007, GEOGR J, V173, P118, DOI 10.1111/j.1475-4959.2007.00238.x
   Beebe S, 2011, CROP ADAPTATION TO CLIMATE CHANGE, P356
   Campbell Donovan, 2009, Sustainability, V1, P1366, DOI 10.3390/su1041366
   Campbell D, 2011, APPL GEOGR, V31, P146, DOI 10.1016/j.apgeog.2010.03.007
   Campbell JD, 2011, INT J CLIMATOL, V31, P1866, DOI 10.1002/joc.2200
   Challinor AJ, 2009, J EXP BOT, V60, P2775, DOI 10.1093/jxb/erp062
   Chen AA, 2002, INT J CLIMATOL, V22, P87, DOI 10.1002/joc.711
   Church JA, 2004, J CLIMATE, V17, P2609, DOI 10.1175/1520-0442(2004)017<2609:EOTRDO>2.0.CO;2
   Curtis S, 2014, EARTH INTERACT, V18, DOI 10.1175/EI-D-14-0001.1
   Delerce S, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0161620
   Dessai S, 2004, CLIM POLICY, V4, P107
   Farrell AD, 2018, AGROECOL SUST FOOD, V42, P812, DOI 10.1080/21683565.2018.1448924
   Feller U, 2016, J PLANT PHYSIOL, V203, P69, DOI 10.1016/j.jplph.2016.04.002
   Feller U, 2014, FRONT ENV SCI-SWITZ, V2, DOI 10.3389/fenvs.2014.00039
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Friedl MA, 2010, REMOTE SENS ENVIRON, V114, P168, DOI 10.1016/j.rse.2009.08.016
   Gamble DW, 2008, PROG PHYS GEOG, V32, P265, DOI 10.1177/0309133308096027
   Gamble DW, 2010, ANN ASSOC AM GEOGR, V100, P880, DOI 10.1080/00045608.2010.497122
   Glenn E, 2015, GEOPHYS RES LETT, V42, P6785, DOI 10.1002/2015GL065002
   Gregory PJ, 2005, PHILOS T R SOC B, V360, P2139, DOI 10.1098/rstb.2005.1745
   Guido Z, 2018, CLIMATIC CHANGE, V147, P253, DOI 10.1007/s10584-017-2125-7
   Hall TC, 2013, THEOR APPL CLIMATOL, V113, P271, DOI 10.1007/s00704-012-0779-7
   Harrison S., 2009, EOS, V90, P111, DOI DOI 10.1029/2009E0130004
   Harvey CA, 2014, CONSERV LETT, V7, P77, DOI 10.1111/conl.12066
   Hijmans R. J., 2001, Plant Genetic Resources Newsletter, P15
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Holdschlag A, 2016, ANTHROPOCENE, V13, P80, DOI 10.1016/j.ancene.2016.03.002
   Janssen MA, 2006, GLOBAL ENVIRON CHANG, V16, P240, DOI 10.1016/j.gloenvcha.2006.04.001
   Jarvis A, 2012, TROP PLANT BIOL, V5, P9, DOI 10.1007/s12042-012-9096-7
   Jones PG, 2003, GLOBAL ENVIRON CHANG, V13, P51, DOI 10.1016/S0959-3780(02)00090-0
   Karmalkar AV, 2013, ATMOSFERA, V26, P283, DOI 10.1016/S0187-6236(13)71076-2
   Karmalkar AV, 2011, CLIM DYNAM, V37, P605, DOI 10.1007/s00382-011-1099-9
   Kelman I, 2014, GEOGR J, V180, P120, DOI 10.1111/geoj.12019
   Khoury CK, 2015, BIOL CONSERV, V184, P259, DOI 10.1016/j.biocon.2015.01.032
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Mace MJ, 2016, REV EUR COMP INT ENV, V25, P197, DOI [10.1111/reel.12164, 10.1111/reel.12172]
   McGregor D., 2009, Global change and Caribbean vulnerability: Environment, economy and society at risk, P273
   Mimura N, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P687
   Moulton AA, 2017, ENVIRON PLANN D, V35, P714, DOI 10.1177/0263775816679669
   Müller C, 2013, ANNU REV NUTR, V33, P395, DOI 10.1146/annurev-nutr-071812-161121
   Nankishore A, 2016, J PLANT PHYSIOL, V202, P75, DOI 10.1016/j.jplph.2016.07.006
   Nelson M, 2016, GEOGR COMPASS, V10, P414, DOI 10.1111/gec3.12281
   NKEMDIRIM LC, 1979, GEOGR REV, V69, P288, DOI 10.2307/214886
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Ovalle-Rivera O, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0124155
   Palanisamy H, 2012, J GEOD SCI, V2, P125, DOI 10.2478/v10156-011-0029-4
   Popke J, 2016, GEOFORUM, V73, P70, DOI 10.1016/j.geoforum.2014.11.003
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Powlson DS, 2011, FOOD POLICY, V36, pS72, DOI 10.1016/j.foodpol.2010.11.025
   Pulwarty RS, 2010, ENVIRONMENT, V52, P16, DOI 10.1080/00139157.2010.522460
   Ramirez-Villegas J, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/024018
   Ramirez-Villegas J, 2013, AGR FOREST METEOROL, V170, P67, DOI 10.1016/j.agrformet.2011.09.005
   Rankine DR, 2015, AGRON J, V107, P375, DOI 10.2134/agronj14.0287
   Rauscher SA, 2008, CLIM DYNAM, V31, P551, DOI 10.1007/s00382-007-0359-1
   Rhiney K, 2015, GEOGR COMPASS, V9, P97, DOI 10.1111/gec3.12199
   Rhiney Kevon., 2017, Climate Change and Food Security: Africa and the Caribbean, P59
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Richards J, 2013, J IRRIG DRAIN ENG, V139, P922, DOI 10.1061/(ASCE)IR.1943-4774.0000629
   Rippke U, 2016, NAT CLIM CHANGE, V6, P605, DOI [10.1038/nclimate2947, 10.1038/NCLIMATE2947]
   Robinson SA, 2017, MITIG ADAPT STRAT GL, V22, P669, DOI 10.1007/s11027-015-9693-5
   Rosenzweig C, 2014, P NATL ACAD SCI USA, V111, P3268, DOI 10.1073/pnas.1222463110
   Schafleitner R, 2011, CROP ADAPTATION TO CLIMATE CHANGE, P287
   Schleussner CF, 2016, EARTH SYST DYNAM, V7, P327, DOI 10.5194/esd-7-327-2016
   Siebers MH, 2017, AGR ECOSYST ENVIRON, V240, P162, DOI 10.1016/j.agee.2016.11.008
   Smith RAJ, 2016, GEOFORUM, V73, P22, DOI 10.1016/j.geoforum.2015.11.008
   Stephenson TS, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009127
   Stephenson TS, 2014, INT J CLIMATOL, V34, P2957, DOI 10.1002/joc.3889
   Taylor M., 2007, GLIMPSES FUTURE BRIE
   Taylor M.A., 2012, Caribbean Studies, V40, P169, DOI DOI 10.1353/CRB.2012.0020
   Taylor MA, 2018, J CLIMATE, V31, P2907, DOI [10.1175/JCLI-D-17-0074.1, 10.1175/jcli-d-17-0074.1]
   Taylor MA, 2013, INT J CLIMATOL, V33, P784, DOI 10.1002/joc.3461
   Timms B.F., 2008, Caribbean Geography, V15, P101
   Tomlinson J, 2018, J ENVIRON STUD SCI, V8, P86, DOI 10.1007/s13412-017-0461-6
   Trotz U., 2013, Small Island Digest, V2, P25
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P1, DOI 10.1007/s10584-011-0157-y
   Weis T., 2004, Journal of Agrarian Change, V4, P461, DOI 10.1111/j.1471-0366.2004.00088.x
   Wells J., 2013, Complexity and sustainability
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Wolkovich EM, 2014, AOB PLANTS, V6, DOI 10.1093/aobpla/plu013
   Zandalinas SI, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00953
   Zhou R, 2017, BMC PLANT BIOL, V17, DOI 10.1186/s12870-017-0974-x
NR 113
TC 18
Z9 20
U1 0
U2 28
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1436-3798
EI 1436-378X
J9 REG ENVIRON CHANGE
JI Reg. Envir. Chang.
PD DEC
PY 2018
VL 18
IS 8
SI SI
BP 2313
EP 2327
DI 10.1007/s10113-018-1409-4
PG 15
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA HA8VS
UT WOS:000450572900012
DA 2025-01-10
ER

PT J
AU Powers, RP
   Coops, NC
   Tulloch, VJ
   Gergel, SE
   Nelson, TA
   Wulder, MA
AF Powers, Ryan P.
   Coops, Nicholas C.
   Tulloch, Vivitskaia J.
   Gergel, Sarah E.
   Nelson, Trisalyn A.
   Wulder, Michael A.
TI A conservation assessment of Canada's boreal forest incorporating
   alternate climate change scenarios
SO REMOTE SENSING IN ECOLOGY AND CONSERVATION
LA English
DT Article
DE Boreal; climate change; MarProb; Marxan; prioritization; systematic
   conservation planning
ID PROTECTED AREAS; RESERVE DESIGN; BIODIVERSITY ASSESSMENT; AVHRR DATA;
   SYSTEM; UNCERTAINTY; CONSEQUENCES; COMMUNITIES; DISTURBANCE; LANDSCAPES
AB Ecologically based strategies for climate change adaptation can be constructively integrated into a terrestrial conservation assessment for Canada's boreal forest, one of Earth's largest remaining wilderness areas. Identifying solutions that minimize variability in projected vegetation productivity may represent a less risky conservation investment by reducing the amount of anticipated environmental change. In this study, we assessed hypothetical protected area networks designed for future vegetation variability under a range of different climate conditions to provide relevant recommendations of conservation requirements that support ongoing boreal conservation and land-use planning. We constructed a boreal conservation assessment using both a conventional (Marxan) and a new probabilistic site-selection approach (Marxan with probability) with projected 2080 vegetation variability probability (VVP) for least change (B1), business as usual (A1B) and most extreme change (A2) climate scenarios. We then assessed (1) reserve network performance (cost and area), (2) high conservation priority areas and (3) the influence and implications of VVP on reserve networks. We found that including VVP dramatically increased the relative cost and total area of reserve networks. Many low-cost sites with high VVP values were given higher conservation priority over fewer sites with low VVP values. Reserve networks designed for A1B and A2 climate scenarios contained more sites with very high VVP values. The ratio of sites with high and very high VVP values changes dramatically for reserve networks designed for current and least change (B1) climate scenarios when under more severe A1B and A2 conditions. We conclude that introducing additional complexity and realism into national or boreal-wide conservation assessments, that include, for example, elements of climate change, will increase the total area and cost of a reserve network. Moreover, reserve networks designed for current or least change (B1) climate scenarios will likely not achieve conservation targets when faced with more severe conditions, and will require additional sites. The adaptive strategies presented are well suited for a boreal conservation assessment and may improve long-term effectiveness of biodiversity conservation objectives.
C1 [Powers, Ryan P.] Yale Univ, Dept Ecol & Evolutionary Biol, 165 Prospect St, New Haven, CT 06520 USA.
   [Coops, Nicholas C.] Univ British Columbia, Dept Forest Resources Management, IRSS, Vancouver, BC, Canada.
   [Tulloch, Vivitskaia J.] Univ Queensland, Austrailian Res Council, Ctr Excellence Environm Decis, Sch Biol Sci, Brisbane, Qld, Australia.
   [Gergel, Sarah E.] Univ British Columbia, Dept Forest & Conservat Sci, Landscape Ecol Lab, Vancouver, BC, Canada.
   [Nelson, Trisalyn A.] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ USA.
   [Wulder, Michael A.] Nat Resources Canada, Pacific Forestry Ctr, Canadian Forest Serv, Victoria, BC, Canada.
C3 Yale University; University of British Columbia; University of
   Queensland; University of British Columbia; Arizona State University;
   Arizona State University-Tempe; Natural Resources Canada; Canadian
   Forest Service
RP Powers, RP (corresponding author), Yale Univ, Dept Ecol & Evolutionary Biol, 165 Prospect St, New Haven, CT 06520 USA.
EM ryan.powers@yale.edu
RI Tulloch, Vivitskaia/G-1336-2013; Wulder, Michael/J-5597-2016; Coops,
   Nicholas/J-1543-2012
OI Tulloch, Vivitskaia/0000-0002-7673-3716; Wulder,
   Michael/0000-0002-6942-1896; Coops, Nicholas/0000-0002-0151-9037;
   Nelson, Trisalyn/0000-0003-2537-6971
FU Natural Sciences and Engineering Research Council of Canada (NSERC);
   Ivey Foundation; Nature Conservancy of Canada, Canadian Space Agency
   (CSA); Government Related Initiatives Program (GRIP); Canadian Forest
   Service (CFS); Pacific Forestry Centre (PFC); University of British
   Columbia (UBC)
FX This research was undertaken as part of the 'BioSpace: Biodiversity
   monitoring with Earth Observation data' project jointly funded by the
   Natural Sciences and Engineering Research Council of Canada (NSERC),
   Ivey Foundation, the Nature Conservancy of Canada, Canadian Space Agency
   (CSA), Government Related Initiatives Program (GRIP), Canadian Forest
   Service (CFS), Pacific Forestry Centre (PFC) and the University of
   British Columbia (UBC).
CR Andrew ME, 2014, ENVIRON REV, V22, P135, DOI 10.1139/er-2013-0056
   Andrew ME, 2012, BIOL CONSERV, V146, P97, DOI 10.1016/j.biocon.2011.11.029
   [Anonymous], 2005, 16 CCEA
   Ball I., 2000, MARINE RESERVE DESIG
   Beazley K, 2005, ECOL APPL, V15, P2192, DOI 10.1890/03-5270
   Bradshaw CJA, 2009, TRENDS ECOL EVOL, V24, P541, DOI 10.1016/j.tree.2009.03.019
   Brandt JP, 2013, ENVIRON REV, V21, P207, DOI 10.1139/er-2013-0040
   Brandt JP, 2009, ENVIRON REV, V17, P101, DOI 10.1139/A09-004
   BURKEY TV, 1995, CONSERV BIOL, V9, P527, DOI 10.1046/j.1523-1739.1995.09030527.x
   Carvalho SB, 2011, BIOL CONSERV, V144, P2020, DOI 10.1016/j.biocon.2011.04.024
   Coops NC, 2008, ECOL INDIC, V8, P754, DOI 10.1016/j.ecolind.2008.01.007
   Coops NC, 2009, ECOL INFORM, V4, P8, DOI 10.1016/j.ecoinf.2008.09.005
   Drechsler M, 2009, ECOL MODEL, V220, P438, DOI 10.1016/j.ecolmodel.2008.11.013
   Ferraz G, 2003, P NATL ACAD SCI USA, V100, P14069, DOI 10.1073/pnas.2336195100
   Fleming RA, 1998, ENVIRON MONIT ASSESS, V49, P235, DOI 10.1023/A:1005818108382
   Fontana FMA, 2012, REMOTE SENS ENVIRON, V121, P171, DOI 10.1016/j.rse.2012.01.007
   Game ET, 2008, ECOL APPL, V18, P670, DOI 10.1890/07-1027.1
   Game ET, 2011, GLOBAL CHANGE BIOL, V17, P3150, DOI 10.1111/j.1365-2486.2011.02457.x
   Game ET, 2009, ECOL LETT, V12, P1336, DOI 10.1111/j.1461-0248.2009.01384.x
   Game ET, 2010, INCORPORATING CLIMAT
   Groves CR, 2012, BIODIVERS CONSERV, V21, P1651, DOI 10.1007/s10531-012-0269-3
   Hagen-Zanker A, 2006, COMP CONTINUOUS VALU
   Hannah L, 2007, FRONT ECOL ENVIRON, V5, P131, DOI 10.1890/1540-9295(2007)5[131:PANIAC]2.0.CO;2
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Klein C, 2009, ECOL APPL, V19, P206, DOI 10.1890/07-1684.1
   Kurz W.A., 1992, NOR10326 FOR CAN NW
   Lehman CL, 2000, AM NAT, V156, P534, DOI 10.1086/303402
   Lemieux CJ, 2011, LAND USE POLICY, V28, P928, DOI 10.1016/j.landusepol.2011.03.008
   Leroux SJ, 2007, ECOL APPL, V17, P1954, DOI 10.1890/06-1115.1
   Leroux SJ, 2007, BIOL CONSERV, V138, P464, DOI 10.1016/j.biocon.2007.05.012
   Leroux SJ, 2014, DIVERS DISTRIB, V20, P258, DOI 10.1111/ddi.12155
   Lourival R, 2011, DIVERS DISTRIB, V17, P297, DOI 10.1111/j.1472-4642.2010.00722.x
   Margules CR, 2000, NATURE, V405, P243, DOI 10.1038/35012251
   Moilanen A, 2006, ECOL MODEL, V199, P115, DOI 10.1016/j.ecolmodel.2006.07.004
   Naidoo R, 2006, TRENDS ECOL EVOL, V21, P681, DOI 10.1016/j.tree.2006.10.003
   Nelson T. A., 2014, Diversity, V6, P133, DOI 10.3390/d6010133
   Plummer DA, 2006, J CLIMATE, V19, P3112, DOI 10.1175/JCLI3769.1
   Powers RP, 2016, CAN J REMOTE SENS, V42, P171, DOI 10.1080/07038992.2016.1171065
   Powers RP, 2013, BIOL CONSERV, V167, P371, DOI 10.1016/j.biocon.2013.08.032
   Powers RP, 2013, PROG PHYS GEOG, V37, P36, DOI 10.1177/0309133312457405
   Pressey RL, 2007, TRENDS ECOL EVOL, V22, P583, DOI 10.1016/j.tree.2007.10.001
   Price DT, 2013, ENVIRON REV, V21, P322, DOI 10.1139/er-2013-0042
   Rayfield B, 2008, BIOL CONSERV, V141, P438, DOI 10.1016/j.biocon.2007.10.013
   Ross H, 2009, AUSTRALAS J ENVIRON, V16, P242
   Saxon E, 2005, ECOL LETT, V8, P53, DOI 10.1111/j.1461-0248.2004.00694.x
   Scott D, 2005, FOREST CHRON, V81, P696, DOI 10.5558/tfc81696-5
   Serreze MC, 2000, CLIMATIC CHANGE, V46, P159, DOI 10.1023/A:1005504031923
   Stewart RR, 2005, ENVIRON MODEL ASSESS, V10, P203, DOI 10.1007/s10666-005-9001-y
   Tilman D, 1999, ECOLOGY, V80, P1455, DOI 10.1890/0012-9658(1999)080[1455:TECOCI]2.0.CO;2
   Tulloch VJ, 2013, BIOL CONSERV, V162, P41, DOI 10.1016/j.biocon.2013.03.003
   Venier LA, 2014, ENVIRON REV, V22, P457, DOI 10.1139/er-2013-0075
   Wulder MA, 2011, CAN GEOGR-GEOGR CAN, V55, P288, DOI 10.1111/j.1541-0064.2010.00335.x
   Wulder MA, 2008, CAN J REMOTE SENS, V34, P549, DOI 10.5589/m08-066
NR 57
TC 7
Z9 7
U1 0
U2 22
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN, NJ 07030 USA
EI 2056-3485
J9 REMOTE SENS ECOL CON
JI Remote Sens. Ecol. Conserv.
PD DEC
PY 2017
VL 3
IS 4
BP 202
EP 216
DI 10.1002/rse2.34
PG 15
WC Ecology; Remote Sensing
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Remote Sensing
GA FO9XS
UT WOS:000417252400003
OA gold
DA 2025-01-10
ER

PT J
AU Martin, E
   McPherson, R
   Kuster, E
   Bamzai-Dodson, A
AF Martin, Elinor
   McPherson, Renee
   Kuster, Emma
   Bamzai-Dodson, Aparna
TI Managing for a Changing Climate A Blended Interdisciplinary Climate
   Course
SO BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
LA English
DT Article
AB We developed a blended (or hybrid) interactive course-Managing for a Changing Climate-that provides a holistic view of climate change. The course results from communication with university students and natural and cultural resource managers as well as the need for educational efforts aimed at the public, legislators, and decision-makers. Content includes the components of the physical climate system, natural climate variability, anthropogenic drivers of climate change, climate models and projections, climate assessments, energy economics, environmental policy, vulnerabilities to climate hazards, impacts of climate change, and decision-making related to climate adaptation and mitigation efforts. To convey most of the content, the course-development team created over 50 short videos (3-10 min each) in partnership with experts from a variety of academic, government, and industry institutions. The blended course has been offered as an upper-division, undergraduate course in the Department of Geography and Environmental Sustainability and School of Meteorology (four times) and College of International Studies (in Italy, once) at the University of Oklahoma with over 100 total students. The course has also been presented online-only at no cost to the participants in four fall semesters with over 1,000 total registrations. Videos created for this course are freely available on the YouTube page of the South Central Climate Adaptation Science Center. This course and its associated materials comprise high-quality, formal climate training and education that can be adapted to other formal and informal education settings beyond the walls of the university.
C1 [Martin, Elinor; McPherson, Renee] Univ Oklahoma, South Cent Climate Adaptat Sci Ctr, Norman, OK 73019 USA.
   [Martin, Elinor] Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA.
   [McPherson, Renee; Bamzai-Dodson, Aparna] Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA.
   [Kuster, Emma] South Cent Climate Adaptat Sci Ctr, Norman, OK USA.
   [Bamzai-Dodson, Aparna] US Geol Survey, North Cent Climate Adaptat Sci Ctr, Ft Collins, CO USA.
C3 University of Oklahoma System; University of Oklahoma - Norman;
   University of Oklahoma System; University of Oklahoma - Norman;
   University of Oklahoma System; University of Oklahoma - Norman; United
   States Department of the Interior; United States Geological Survey
RP Martin, E (corresponding author), Univ Oklahoma, South Cent Climate Adaptat Sci Ctr, Norman, OK 73019 USA.; Martin, E (corresponding author), Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA.
EM elinor.martin@ou.edu
RI Martin, Elinor/AAU-6834-2021; Bamzai-Dodson, Aparna/LKL-3984-2024;
   McPherson, Renee/H-6256-2016
OI Bamzai-Dodson, Aparna/0000-0002-2444-9051; McPherson,
   Renee/0000-0002-1497-9681; Martin, Elinor/0000-0003-1480-3843
FU U.S. Geological Survey [G15AP00136]; National Aeronautics and Space
   Administration [NNX11AB54H]; University of Oklahoma College of
   Atmospheric and Geographic Sciences
FX We thank three anonymous reviewers for their thoughtful comments and
   suggestions that improved the manuscript. The project described in this
   publication was supported by Grant G15AP00136 from the U.S. Geological
   Survey, Grant NNX11AB54H from the National Aeronautics and Space
   Administration, and the University of Oklahoma College of Atmospheric
   and Geographic Sciences. Its contents are solely the responsibility of
   the authors and do not necessarily represent the views of the South
   Central Climate Adaptation Science Center, the USGS, the Oklahoma Space
   Grant Consortium, or NASA. This manuscript is submitted for publication
   with the understanding that the U.S. Government is authorized to
   reproduce and distribute reprints for governmental purposes. Neither the
   authors nor their institutions endorse the use of any particular
   classroom management software system. Any use of trade, firm, or product
   names is for descriptive purposes only and does not imply endorsement by
   the U.S. Government.
CR American Geophysical Union, 2002, EOS T AM GEOPHYS UNI, V83, P595, DOI [10.1029/2002EO000409, DOI 10.1029/2002EO000409]
   BLOOM B. S., 1956, Taxonomy of Educational Objectives: The Classification of Educational Goals
   Carter L., 2010, BLENDING PERSPECTIVE
   Climate and Development Knowledge Network, 2014, DEC DEC
   Cordero EC, 2008, B AM METEOROL SOC, V89, P865, DOI 10.1175/2007BAMS2432.1
   Ferreira RN, 2012, B AM METEOROL SOC, V93, P1539, DOI 10.1175/BAMS-D-11-00048.1
   Gautier C., 2005, J GEOSCIENCE ED, V53, P5, DOI DOI 10.5408/1089-9995-53.5.508
   Hanrahan J, 2019, B AM METEOROL SOC, V100, P1209, DOI 10.1175/BAMS-D-17-0332.1
   Hotinski R, 2015, STABILIZATION WEDGES
   Huguet C., 2020, Journal of Geoscience Education, V68, P20, DOI DOI 10.1080/10899995.2019.1588489
   Jordan K, 2015, INT REV RES OPEN DIS, V16, DOI 10.19173/irrodl.v16i3.2112
   Kramarski B, 2006, J COMPUT ASSIST LEAR, V22, P24, DOI 10.1111/j.1365-2729.2006.00157.x
   Leiserowitz A., 2018, CLIMATE CHANGE AM MI
   McGee P., 2012, Journal of Asynchronous Learning Networks, V16, P7, DOI [10.24059/olj.v16i4.239, DOI 10.24059/OLJ.V16I4.239]
   Prince M, 2004, J ENG EDUC, V93, P223, DOI 10.1002/j.2168-9830.2004.tb00809.x
   Rebich S., 2005, Journal of Geoscience Education, V53, P355, DOI [DOI 10.5408/1089-9995-53.4.355, 10.5408/1089-9995-53.4.355]
   Reed D, 2014, B AM METEOROL SOC, V95, P1209, DOI 10.1175/BAMS-D-13-00003.1
   Riley R., 2012, An Assessment of the Climate-Related Needs of Oklahoma Decision Makersq
   Rosendahl D., 2019, EOS T AM GEOPHYS UN, V100, DOI [10.1029/2019EO136493, DOI 10.1029/2019EO136493]
   Stocker, 2015, CEUR WORKSHOP PROC, V1542, P33, DOI [10.1017/CBO9781107415324, DOI 10.1017/CBO9781107415324]
   Tallent-Runnels MK, 2006, REV EDUC RES, V76, P93, DOI 10.3102/00346543076001093
   Wanner T, 2015, COMPUT EDUC, V88, P354, DOI 10.1016/j.compedu.2015.07.008
   Yuretich R.F., 2001, J GEOSCIENCE ED, V49, P111, DOI DOI 10.5408/1089-9995-49.2.111
NR 23
TC 1
Z9 1
U1 2
U2 13
PU AMER METEOROLOGICAL SOC
PI BOSTON
PA 45 BEACON ST, BOSTON, MA 02108-3693 USA
SN 0003-0007
EI 1520-0477
J9 B AM METEOROL SOC
JI Bull. Amer. Meteorol. Soc.
PD DEC
PY 2020
VL 101
IS 12
BP E2138
EP E2148
DI 10.1175/BAMS-D-19-0242.1
PG 11
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA QU9FK
UT WOS:000627585400008
OA Bronze
DA 2025-01-10
ER

PT J
AU Yu, ZW
   Fryd, O
   Sun, RH
   Jorgensen, G
   Yang, GY
   Ozdil, NC
   Vejre, H
AF Yu, Zhaowu
   Fryd, Ole
   Sun, Ranhao
   Jorgensen, Gertrud
   Yang, Gaoyuan
   Ozdil, Nevruz Cinar
   Vejre, Henrik
TI Where and how to cool? An idealized urban thermal security pattern model
SO LANDSCAPE ECOLOGY
LA English
DT Article
DE Urban heat island; Urban green infrastructure; Urban thermal security
   pattern; Hierarchical hexagonal structure; Climate adaption planning
ID LAND-SURFACE TEMPERATURE; LOCAL BACKGROUND CLIMATE; HEAT-ISLAND; GREEN
   SPACE; MITIGATION TECHNOLOGIES; RAPID URBANIZATION; SPATIAL-PATTERN;
   INFRASTRUCTURE; IMPACT; CITIES
AB Contexts Urban green infrastructure (UGI) has been recognized as a promising approach to mitigating urban heat island (UHI); however, most of the previous studies are case-based and explore the effects of the existent landscape and its spatial configuration on UHI mitigation rather than modeling an optimized spatial pattern. Objectives We aimed to transcend the existing research logic (from case studies to obtain the patterns of the cooling effect of UGI, then propose implications for UHI mitigation) and established a hypothetical idealized urban thermal security pattern model (TSPurban). Methods Based on two basic concepts deduced from the physical property of UGI-(threshold) size and cooling distance, as well as the simplifying assumptions we defined. Then, three proposed conceptual UGI types (ecological, efficient, and elementary-3E) and subtypes were used to frame the model. Results We deduced that the idealized TSPurban model conforms to a hierarchical hexagonal structure in theory and it can be calculated and applied, although it generally cannot be seen in the real world. Conclusions The idealized TSPurban model can help us better-understanding UGI cooling effects when considering climate adaption planning and decision-making; it also serves as a novel pathway to study the cooling effects of UGI and mitigate the UHI effect.
C1 [Yu, Zhaowu; Fryd, Ole; Jorgensen, Gertrud; Yang, Gaoyuan; Ozdil, Nevruz Cinar; Vejre, Henrik] Univ Copenhagen, Fac Sci, Dept Geosci & Nat Resource Management, DK-1958 Copenhagen, Denmark.
   [Yu, Zhaowu; Sun, Ranhao] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China.
   [Yu, Zhaowu] Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Shanghai, Peoples R China.
C3 University of Copenhagen; Chinese Academy of Sciences; Research Center
   for Eco-Environmental Sciences (RCEES)
RP Yu, ZW (corresponding author), Univ Copenhagen, Fac Sci, Dept Geosci & Nat Resource Management, DK-1958 Copenhagen, Denmark.
EM zhyu@ign.ku.dk
RI Fryd, Ole/A-4648-2013; Gaoyuan, Yang/HKO-4087-2023; sun,
   ranhao/AAM-6837-2021; Yu, Zhaowu/E-8032-2016; Jorgensen,
   Gertrud/B-1396-2015; Vejre, Henrik/P-7142-2014; Cinar Ozdil,
   Nevruz/D-9037-2015
OI Yu, Zhaowu/0000-0003-4576-4541; Sun, Ranhao/0000-0003-2396-5131;
   Jorgensen, Gertrud/0000-0003-3987-3098; Yang,
   Gaoyuan/0000-0001-9735-6529; Vejre, Henrik/0000-0002-6820-0389; Cinar
   Ozdil, Nevruz/0000-0001-7128-7625
FU Open Foundation of the State Key Laboratory of Urban and Regional
   Ecology of China [SKLURE2019-2-6]; National Natural Science Foundation
   of China [41922007]; Shanghai Key Lab for Urban Ecological Processes and
   Eco-Restoration [SHUES2019A01]; China Scholarship Council [201504910797]
FX This work was financially supported by Open Foundation of the State Key
   Laboratory of Urban and Regional Ecology of China (Grant No.
   SKLURE2019-2-6); National Natural Science Foundation of China (Grant No.
   41922007); Shanghai Key Lab for Urban Ecological Processes and
   Eco-Restoration (Grant No. SHUES2019A01); WEL Visiting Fellowship
   Program; China Scholarship Council (Grant No. 201504910797). We also
   thank anonymous reviewers for their constructive comments and
   suggestions.
CR Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   [Anonymous], 2018, COOLING EFFECT URBAN
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Chen AL, 2014, ECOL INDIC, V45, P424, DOI 10.1016/j.ecolind.2014.05.002
   Coumou D, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/3/034018
   Debbage N, 2015, COMPUT ENVIRON URBAN, V54, P181, DOI 10.1016/j.compenvurbsys.2015.08.002
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   Derkzen ML, 2017, LANDSCAPE URBAN PLAN, V157, P106, DOI 10.1016/j.landurbplan.2016.05.027
   European Environment Agency, 2016, TRANSFORMING CITIES, DOI DOI 10.2800/41895
   Fan HY, 2019, AGR FOREST METEOROL, V265, P338, DOI 10.1016/j.agrformet.2018.11.027
   Forman RTT, 2014, URBAN ECOLOGY: SCIENCE OF CITIES, P1
   Forman RTT, 2016, LANDSCAPE ECOL, V31, P1653, DOI 10.1007/s10980-016-0424-4
   Gao J, 2019, ECOL INDIC, V107, DOI 10.1016/j.ecolind.2019.105579
   Gillner S, 2015, LANDSCAPE URBAN PLAN, V143, P33, DOI 10.1016/j.landurbplan.2015.06.005
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Gustafson EJ, 1998, ECOSYSTEMS, V1, P143, DOI 10.1007/s100219900011
   Hamada S, 2010, URBAN FOR URBAN GREE, V9, P15, DOI 10.1016/j.ufug.2009.10.002
   Jaganmohan M, 2016, J ENVIRON QUAL, V45, P134, DOI 10.2134/jeq2015.01.0062
   Jiao M, 2017, AGR FOREST METEOROL, V247, P293, DOI 10.1016/j.agrformet.2017.08.013
   Kong FH, 2014, LANDSCAPE URBAN PLAN, V128, P35, DOI 10.1016/j.landurbplan.2014.04.018
   Li XX, 2017, LANDSCAPE URBAN PLAN, V163, P107, DOI 10.1016/j.landurbplan.2017.02.009
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   Liu Y, 2018, RISK ANAL, V38, P2208, DOI 10.1111/risa.12998
   Luan XL, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030391
   Martins TAL, 2016, SUSTAIN CITIES SOC, V26, P9, DOI 10.1016/j.scs.2016.05.003
   Mikami T, 2009, 7 INT C URB CLIM YOK
   Le MT, 2019, E3S WEB CONF, V97, DOI 10.1051/e3sconf/20199701013
   Monteiro MV, 2016, URBAN FOR URBAN GREE, V16, P160, DOI 10.1016/j.ufug.2016.02.008
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   O'Malley C, 2015, SUSTAIN CITIES SOC, V19, P222, DOI 10.1016/j.scs.2015.05.009
   Oke T. R., 1987, Boundary layer climates, V2nd
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Pickett Steward T. A., 2016, Ecosystem Health and Sustainability, V2, pe01229, DOI 10.1002/ehs2.1229
   Santamouris M, 2014, SOL ENERGY, V103, P682, DOI 10.1016/j.solener.2012.07.003
   Santamouris M, 2018, J CIV ENG MANAG, V24, P638, DOI 10.3846/jcem.2018.6604
   Shih WY, 2017, HABITAT INT, V60, P69, DOI 10.1016/j.habitatint.2016.12.006
   Sobstyl JM, 2018, PHYS REV LETT, V120, DOI 10.1103/PhysRevLett.120.108701
   Solcerova A, 2017, BUILD ENVIRON, V111, P249, DOI 10.1016/j.buildenv.2016.10.021
   Sun RH, 2018, LANDSCAPE URBAN PLAN, V178, P43, DOI 10.1016/j.landurbplan.2018.05.015
   Sun RH, 2018, J CLEAN PROD, V170, P601, DOI 10.1016/j.jclepro.2017.09.153
   Sun RH, 2017, ECOSYST SERV, V23, P38, DOI 10.1016/j.ecoser.2016.11.011
   Sun RH, 2012, LANDSCAPE URBAN PLAN, V105, P27, DOI 10.1016/j.landurbplan.2011.11.018
   Ward K, 2016, SCI TOTAL ENVIRON, V569, P527, DOI 10.1016/j.scitotenv.2016.06.119
   Wu JG, 2014, LANDSCAPE URBAN PLAN, V125, P209, DOI 10.1016/j.landurbplan.2014.01.018
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yu Z, 2019, AGU FALL M 2019 SAN
   Yu Zhao-wu, 2015, Yingyong Shengtai Xuebao, V26, P636
   Yu ZW, 2019, FOREST ECOL MANAG, V446, P214, DOI 10.1016/j.foreco.2019.05.046
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Yu ZW, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-25296-w
   Yu ZW, 2018, URBAN FOR URBAN GREE, V29, P113, DOI 10.1016/j.ufug.2017.11.008
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Zhang YJ, 2017, LANDSCAPE URBAN PLAN, V165, P162, DOI 10.1016/j.landurbplan.2017.04.009
   Zhao L, 2014, NATURE, V511, P216, DOI 10.1038/nature13462
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
   Zhou W, 2019, J URBAN PLAN DEV, V145, DOI 10.1061/(ASCE)UP.1943-5444.0000520
   Zuvela-Aloise M, 2016, CLIMATIC CHANGE, V135, P425, DOI 10.1007/s10584-016-1596-2
NR 59
TC 31
Z9 33
U1 18
U2 163
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0921-2973
EI 1572-9761
J9 LANDSCAPE ECOL
JI Landsc. Ecol.
PD JUL
PY 2021
VL 36
IS 7
SI SI
BP 2165
EP 2174
DI 10.1007/s10980-020-00982-1
EA FEB 2020
PG 10
WC Ecology; Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Physical Geography; Geology
GA ST3AA
UT WOS:000516278600002
DA 2025-01-10
ER

PT J
AU Tantoh, HB
   Mokotjomela, TM
   Ebhuoma, EE
   Donkor, FK
AF Tantoh, Henry Bikwibili
   Mokotjomela, Thabiso Michael
   Ebhuoma, Eromose E.
   Donkor, Felix K.
TI Factors preventing smallholder farmers from adapting to climate
   variability in South Africa: lessons from Capricorn and uMshwati
   municipalities
SO CLIMATE RESEARCH
LA English
DT Article
DE Adaptation; Climate change; Food production; Poverty; South Africa
ID VULNERABILITY; PERSPECTIVE; LIVELIHOODS; ADAPTATION; STRESSORS
AB Climate variability has adversely compromised food production in South Africa, with severe consequences for the livelihood of smallholder farmers. However, the extent to which adaptation has enabled rural farmers to continue earning their livelihoods has received limited attention. This paper addresses this knowledge gap by examining the constraints faced in food production and the coping strategies adopted by these farmers in responding to climate variability and change. A mixed research approach (primary and secondary) was used to obtain data from the municipalities of Capricorn and uMshwati in Limpopo and KwaZulu-Natal provinces, South Africa. Structured questionnaires, focus group discussions and semi-structured interviews were used to obtain primary data, while internet, libraries and organizational reports were consulted to obtain secondary data. Results showed that rain-fed agriculture was the most common type of farming (60%), compared to irrigation farming (40%). Furthermore, 25% (8/30 respondents) of smallholder farmers practising mixed cropping had been involved in agriculture for more than a decade. Smallholder farmers have adopted mitigating strategies ranging from social adjustments at the household level and combining food production with off-farm activities to sustain their livelihoods and overall wellbeing. This study argues that an enabling environment will facilitate the ability of rural farmers to adapt to climate variability in the local context and present beneficial socio-economic dynamics within the small-scale agricultural food production sector.
C1 [Tantoh, Henry Bikwibili] Univ Bamenda, Fac Arts, Dept Geog & Planning, POB 39, Bambili, Nw Region, Cameroon.
   [Mokotjomela, Thabiso Michael] Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Private Bag 3, ZA-2050 Johannesburg, South Africa.
   [Mokotjomela, Thabiso Michael] South Africa Natl Biodivers Inst, Free State Natl Bot Garden, POB 29036, ZA-9310 Bloemfontein, Free State, South Africa.
   [Ebhuoma, Eromose E.; Donkor, Felix K.] Univ South Africa UNISA, Coll Agr & Environm Sci, Dept Environm Sci, ZA-1709 Florida, South Africa.
C3 University of Witwatersrand; South African National Biodiversity
   Institute; University of South Africa
RP Tantoh, HB (corresponding author), Univ Bamenda, Fac Arts, Dept Geog & Planning, POB 39, Bambili, Nw Region, Cameroon.
EM bikwibilith@gmail.com
RI Mokotjomela, Thabiso/D-7097-2013; Ebhuoma, Eromose/IWM-7295-2023;
   Tantoh, Henry/K-3444-2019
OI Donkor, Felix Kwabena/0000-0001-6043-7659
FU Global Change and Sustainability Research Institute, University of the
   Witwatersrand
FX Data collections were funded by the Global Change and Sustainability
   Research Institute, University of the Witwatersrand. The South African
   Department of Environment, Forestry, and Fisheries (DEFF) are thanked
   for funding; however, it is noted that this publication does not
   necessarily represent the views or opinions of DEFF or its employees.
   Rirhandu Jill Chauke and Nelisiwe Mofutsanyana are acknowledged for data
   collection. We thank Tsedzuluso Mundalamo for drawing the maps for the
   study sites.
CR Adeola A, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16245156
   Agri SA, 2016, RAINDR DROUGHT REP M
   [Anonymous], AM J MED SCI, DOI [DOI 10.1007/s11270-007-9372-6, DOI 10.1016/J.AMJMS.2021.03.001,00089-6]
   Anyadike R. N. C., 2009, IMPLICATIONS CLIMATE, P13
   Ariatti C., 2015, Journal of Economic and Financial Sciences, V8, P432
   Baudoin MA, 2017, INT J DISAST RISK RE, V23, P128, DOI 10.1016/j.ijdrr.2017.05.005
   Benhin J.K., 2006, Climate change and South African agriculture: Impacts and adaptation options, V21
   Boko M, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P433
   Borquez R, 2017, SUSTAIN SCI, V12, P163, DOI 10.1007/s11625-016-0400-6
   Calzadilla A, 2014, WATER RESOUR ECON, V5, P24, DOI 10.1016/j.wre.2014.03.001
   Capricorn District Municipality, 2014, AGR
   Clarke V, 2013, PSYCHOLOGIST, V26, P120
   Department of Environment Forestry and Fisheries, 2017, National Climate Change Adaptation Strategy-Republic of South Africa
   Ebhuoma EE, 2020, COGENT SOC SCI, V6, DOI 10.1080/23311886.2020.1792155
   Ebhuoma EE, 2019, JAMBA-J DISASTER RIS, V11
   Elum ZA, 2017, CLIM RISK MANAG, V16, P246, DOI 10.1016/j.crm.2016.11.001
   Engelbrecht F, 2019, GREEN BOOKDETAILED P
   Faber Jorge, 2014, Dental Press J. Orthod., V19, P27
   Fenyes T, 2013, AGR NATL EC, P21
   Ferguson J, 2013, J AGRAR CHANGE, V13, P166, DOI 10.1111/j.1471-0366.2012.00363.x
   Filho WL, 2021, ENVIRON SCI EUR, V33, DOI 10.1186/s12302-021-00552-5
   Gandure S, 2013, ENVIRON DEV, V5, P39, DOI 10.1016/j.envdev.2012.11.004
   Gbetibouo G.A., 2009, IFPRI DISCUSSION PAP, DOI DOI 10.1068/A312017
   Guha-Sapir D., 2015, EM-DAT: International disaster database, V27, P57
   Harrison L, 2011, CLIM RES, V46, P211, DOI 10.3354/cr00979
   Hosu S, 2013, AGROECOL SUST FOOD, V37, P985, DOI 10.1080/21683565.2013.802755
   Kwabena Donkor F., 2020, Food Security and Land Use Change under Conditions of Climatic Variability, P165, DOI [10.1007/978-3-030-36762-6_9, DOI 10.1007/978-3-030-36762-6_9, 10.1007]
   Madiba S, 2017, GLOBAL HEALTH ACTION, V10, DOI 10.1080/16549716.2017.1341597
   Maguire M., 2017, AISHE-J, V9, P3351
   Mokotjomela TM, 2020, S AFR GEOGR J, V102, P190, DOI 10.1080/03736245.2019.1670233
   Nhemachena C, 2014, JAMBA-J DISASTER RIS, V6, DOI 10.4102/jamba.v6i1.123
   Orimoloye IR, 2021, J ENVIRON MANAGE, V285, DOI 10.1016/j.jenvman.2021.112112
   Orimoloye IR, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13084132
   Pereira T, 2017, POLICY BRIEF 16 2017
   Pittock A.B., 2005, CLIMATE CHANGE TURNI
   Rankoana SA, 2020, J WATER CLIM CHANGE, V11, P677, DOI 10.2166/wcc.2019.109
   Rao MV, 2016, INTEGRATED LAND USE
   Sarrasanti Nediana, 2020, IEEE Engineering Management Review, V48, P37, DOI 10.1109/EMR.2020.3031313
   Scoones I, 2009, J PEASANT STUD, V36, P171, DOI 10.1080/03066150902820503
   Shackleton S, 2014, AGENDA-EMPOWER WOMEN, V28, P73, DOI 10.1080/10130950.2014.932560
   Simatele D, 2015, S AFR GEOGR J, V97, P243, DOI 10.1080/03736245.2014.924873
   South African Weather Services, 2015, ANN RAINF MIN MAX TE
   Tantoh HB, 2021, DEV PRACT, V31, P781, DOI 10.1080/09614524.2021.1937546
   Tantoh HB, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.707835
   Ubisi N.R., 2017, Change Adapt. Socio-Ecol. Syst, V3, P27, DOI [10.1515/cass-2017-0003, DOI 10.1515/CASS-2017-0003]
   Wichelns D, 2015, WATER INT, V40, P1059, DOI 10.1080/02508060.2015.1086255
   Wilk J, 2013, REG ENVIRON CHANGE, V13, P273, DOI 10.1007/s10113-012-0323-4
NR 47
TC 3
Z9 3
U1 0
U2 5
PU INTER-RESEARCH
PI OLDENDORF LUHE
PA NORDBUNTE 23, D-21385 OLDENDORF LUHE, GERMANY
SN 0936-577X
EI 1616-1572
J9 CLIM RES
JI Clim. Res.
PY 2022
VL 88
BP 1
EP 11
DI 10.3354/cr01693
PG 11
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 1H3YB
UT WOS:000796480200001
DA 2025-01-10
ER

PT J
AU Morris, D
   Cherian, D
   Castruccio, F
   Kleypas, J
   Krumhardt, K
   Moulton, M
   Williamson, RD
   Zohdy, S
   Dunning, K
AF Morris, Daniel
   Cherian, Deepak
   Castruccio, Frederic
   Kleypas, Joanie
   Krumhardt, Kristen
   Moulton, Melissa
   Williamson, Ryan D.
   Zohdy, Sarah
   Dunning, Kelly
TI How changes projected by climate models can inform climate adaptation
   and marine sanctuary management: A collaborative prototype methodology
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Climate change; Interdisciplinary methods; Coral reefs; Climate
   adaptation
ID ECOSYSTEM SERVICES; FUTURE; RESILIENCE; REEF; IMPACTS
AB Coral reefs are highly important ecosystems providing habitat for biodiverse marine life and numerous benefits for humans. However they face immense risks from climate change. To date, Representative Concentration Pathway (RCP) climate models have aided global discussions on possible policy responses to adapt to change, but tailored climate projections at a useful scale for environmental managers are often prohibitively expensive to produce. Our research addresses this problem by presenting a novel type of collaborative, participatory research that integrates 1) site specific climate metrics from the Community Earth System Model version 2 large ensemble (CESM2-LE), 2) ecosystem response models to determine Degree Heating Months and coral bleaching impacts, and 3) collaborative social science data from environmental manager engagement to see how managers in one of the most visited marine sanctuaries in the world are enacting adaptive governance, stewarding reefs through climate impacts of the future. Our research is valuable to decision-makers seeking opportunities for innovative policy responses to climate impacts focused on experimentation and dialogue.
C1 [Morris, Daniel; Zohdy, Sarah; Dunning, Kelly] Auburn Univ, Coll Forestry Wildlife & Environm, 602 Duncan Dr, Auburn, AL 36849 USA.
   [Cherian, Deepak; Castruccio, Frederic; Kleypas, Joanie; Krumhardt, Kristen; Moulton, Melissa] Natl Ctr Atmospher Res NCAR, 1850 Table Mesa Dr, Boulder, CO 80305 USA.
   [Moulton, Melissa] Univ Washington, Appl Phys Lab, 1013 NE 40th St, Seattle, WA 98105 USA.
   [Williamson, Ryan D.] Auburn Univ, Dept Polit Sci, Tichenor Hall 321, Auburn, AL 36849 USA.
   [Dunning, Kelly] Univ Wyoming, Haub Sch Nat Resources & Environm, 804 E Fremont St, Laramie, WY 82072 USA.
C3 Auburn University System; Auburn University; National Center Atmospheric
   Research (NCAR) - USA; University of Washington; University of
   Washington Seattle; Auburn University System; Auburn University;
   University of Wyoming
RP Dunning, K (corresponding author), Univ Wyoming, Haub Sch Nat Resources & Environm, 804 E Fremont St, Laramie, WY 82072 USA.
EM kelly.dunning@uwyo.edu
RI Williamson, Ryan/AAW-5974-2020
OI Cherian, Deepak/0000-0002-6861-8734
FU Early Career Faculty Innovator Program at the National Science
   Foundation (NSF) National Center for Atmospheric Research (NCAR); U.S.
   National Science Foundation (NSF) [1852977]; NOAA Climate Programs
   [202281-145001-2000]
FX The data that has been used is confidential. The CESM project is
   supported primarily by the US National Science Foundation (NSF). This
   material is based upon work supported by the Early Career Faculty
   Innovator Program at the National Science Foundation (NSF) National
   Center for Atmospheric Research (NCAR). NSF NCAR is a major facility
   sponsored by the U.S. National Science Foundation (NSF) under
   Cooperative Agreement No. 1852977. Any opinions, findings and
   conclusions or recommendations expressed in this material do not
   necessarily reflect the views of the National Science Foundation. This
   research was also funded by a NOAA Climate Programs Grant number
   202281-145001-2000.
CR [Anonymous], 2005, Adaptive Governance: Integrating Science, Policy, and Decision Making
   [Anonymous], Molasses Reef Sanctuary Preservation Area
   [Anonymous], About your National Marine Sanctuaries | Office of National Marine Sanctuaries
   [Anonymous], 2005, Millennium Ecosystem Assessment
   [Anonymous], Sanctuary Preservation Areas | Restoration Blueprint | Florida Keys National Marine Sanctuaries
   [Anonymous], 2000, Emissions Scenarios: Summary for Policymakers;a Special Report of IPCC Working Group III$Intergovernmental Panel on Climate Change
   [Anonymous], CLIMATE FORCING
   Anthony KRN, 2015, GLOBAL CHANGE BIOL, V21, P48, DOI 10.1111/gcb.12700
   Bohensky EL, 2006, CONSERV BIOL, V20, P1051, DOI 10.1111/j.1523-1739.2006.00475.x
   Chaffin BC, 2014, ECOL SOC, V19, DOI 10.5751/ES-06824-190356
   Craig RK, 2020, P NATL ACAD SCI USA, V117, P8245, DOI 10.1073/pnas.1922201117
   Creswell JW., 2017, DESIGNING CONDUCTING
   Datta AW, 2022, ECOL SOC, V27, DOI 10.5751/ES-13251-270230
   Day JC, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.972228
   Delevaux JMS, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-29951-0
   Dietz T, 2003, SCIENCE, V302, P1907, DOI 10.1126/science.1091015
   Dunning KH, 2021, MAR POLICY, V124, DOI 10.1016/j.marpol.2020.104248
   Evans LS, 2013, HUM ECOL, V41, P841, DOI 10.1007/s10745-013-9601-0
   Fascell Rep., 1990, B D F 19 HR5909 101
   Feely RA, 2004, SCIENCE, V305, P362, DOI 10.1126/science.1097329
   Frieler K, 2013, NAT CLIM CHANGE, V3, P165, DOI 10.1038/NCLIMATE1674
   Garmestani A, 2019, P NATL ACAD SCI USA, V116, P19899, DOI 10.1073/pnas.1906247116
   Groves C.R., 2016, Conservation planning: Informed decisions for a healthier planet
   Hafezi M, 2021, J ENVIRON MANAGE, V285, DOI 10.1016/j.jenvman.2021.112082
   Hoegh-Guldberg O, 1999, MAR FRESHWATER RES, V50, P839, DOI 10.1071/MF99078
   Hughes TP, 2017, NATURE, V546, P82, DOI 10.1038/nature22901
   Hughes TP, 2017, NATURE, V543, P373, DOI 10.1038/nature21707
   Hughes TP, 2003, SCIENCE, V301, P929, DOI 10.1126/science.1085046
   Lemos MC, 2006, ANNU REV ENV RESOUR, V31, P297, DOI 10.1146/annurev.energy.31.042605.135621
   Lemos MC, 2010, WIRES CLIM CHANGE, V1, P670, DOI 10.1002/wcc.71
   Magel JMT, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-018-37713-1
   Magnan AK, 2021, NAT CLIM CHANGE, V11, P879, DOI 10.1038/s41558-021-01156-w
   Malinga R, 2013, ECOL SOC, V18, DOI 10.5751/ES-05494-180410
   Mcleod E, 2019, J ENVIRON MANAGE, V233, P291, DOI 10.1016/j.jenvman.2018.11.034
   Melbourne-Thomas J, 2011, ECOL APPL, V21, P1380, DOI 10.1890/09-1564.1
   National Marine Sanctuary Foundation, Announces Grants to Scale Up Coral Restoration Through Mission: Iconic Reefs
   NOAA Coral Reef Conservation Program, 2020, Coral Reef Condition: A Status Report for Florida's Coral Reef
   Oreskes N, 2010, PHILOS SCI, V77, P1012, DOI 10.1086/657428
   Palacios-Agundez I, 2013, ECOL SOC, V18, DOI 10.5751/ES-05619-180307
   Palinkas LA, 2015, ADM POLICY MENT HLTH, V42, P533, DOI 10.1007/s10488-013-0528-y
   Palomo I, 2011, ECOL SOC, V16
   Rijke J, 2012, ENVIRON SCI POLICY, V22, P73, DOI 10.1016/j.envsci.2012.06.010
   Rodgers KB, 2021, EARTH SYST DYNAM, V12, P1393, DOI 10.5194/esd-12-1393-2021
   Rounsevell MDA, 2010, WIRES CLIM CHANGE, V1, P606, DOI 10.1002/wcc.63
   Saldana J., 2016, The coding manual for qualitative researchers, V3rd
   Sandhu H, 2018, ECOSYST SERV, V31, P194, DOI 10.1016/j.ecoser.2018.04.006
   Strauss A., 1997, Grounded theory in practice
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Teneva L, 2012, CORAL REEFS, V31, P1, DOI 10.1007/s00338-011-0812-9
   Tuda AO, 2021, OCEAN COAST MANAGE, V200, DOI 10.1016/j.ocecoaman.2020.105412
   van Hooidonk R, 2015, GLOBAL CHANGE BIOL, V21, P3389, DOI 10.1111/gcb.12901
   WALTERS CJ, 1990, ECOLOGY, V71, P2060, DOI 10.2307/1938620
   Walton CJ, 2018, FRONT MAR SCI, V5, DOI 10.3389/fmars.2018.00323
   Wynveen CJ, 2013, J PARK RECREAT ADM, V31, P28
   MANAGING RISKS EXTRE
NR 55
TC 0
Z9 0
U1 4
U2 4
PU ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
PI LONDON
PA 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
SN 0301-4797
EI 1095-8630
J9 J ENVIRON MANAGE
JI J. Environ. Manage.
PD SEP
PY 2024
VL 368
AR 121953
DI 10.1016/j.jenvman.2024.121953
EA AUG 2024
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA D9R5U
UT WOS:001299482000001
PM 39168002
DA 2025-01-10
ER

PT S
AU Pant, R
AF Pant, Raghav
BE Kondrup, C
   Mercogliano, P
   Bosello, F
   Mysiak, J
   Scoccimarro, E
   Rizzo, A
   Ebrey, R
   DeRuiter, M
   Jeuken, A
   Watkiss, P
TI Advances in Climate Adaptation Modeling of Infrastructure Networks
SO CLIMATE ADAPTATION MODELLING
SE Springer Climate
LA English
DT Article; Book Chapter
DE Infrastructure networks; Climate change; Vulnerability; Risks;
   Adaptation
AB As the adverse effects of climate change are increasingly becoming unavoidable, calls for improving climate adaptation assessments have gathered interest at the global scale. Infrastructure policymakers and practitioners are now interested in understanding climate vulnerabilities and risks that capture the systemic nature of failure propagation seen across interconnected networks. This would help inform adaptation planning objectives meant to improve systemic resilience. This paper presents recent technical methodological and tool-based advances made in climate vulnerability, risk, and adaptation modeling of large-scale infrastructure networks. These methodologies adopt a bottom-up approach that focuses on creating data-rich representations of infrastructure network attributes, resource flows, and socio-economic indicators that are all used for quantifying direct and indirect risks to network assets exposed to extreme climate hazards at multiple scales. Insights from different case studies are presented to show how such methodologies have been used in practice for informing different policy needs. The paper concludes by identifying the existing gaps and future opportunities for such bottom-up infrastructure network vulnerability, risk, and adaptation assessment methodologies.
C1 [Pant, Raghav] Univ Oxford, Environm Change Inst, Oxford, England.
C3 University of Oxford
RP Pant, R (corresponding author), Univ Oxford, Environm Change Inst, Oxford, England.
EM raghav.pant@ouce.ox.ac.uk
FU UK Engineering and Physical Sciences Research Council (EPSRC)
   [EP/I01344X/1, EP/N017064/1]; EPSRC [EP/I01344X/1, EP/N017064/1] Funding
   Source: UKRI
FX The author acknowledges the contribution to the Infrastructure
   Transitions Research Consortium (ITRC), which is funded by the UK
   Engineering and Physical Sciences Research Council (EPSRC) under two
   program grants EP/I01344X/1 and EP/N017064/1.
CR Christoff P, 2016, ENVIRON POLIT, V25, P765, DOI 10.1080/09644016.2016.1191818
   Conway D, 2019, NAT CLIM CHANGE, V9, P503, DOI 10.1038/s41558-019-0502-0
   European Commission, 2014, ADAPTATION CLIMATE C
   Global Commission on Adaptation, 2019, AD NOW GLOB CALL LEA
   Hall J.W., 2019, Adaptation of infrastructure systems: background paper for the global commission on adaptation
   Hallegatte S., 2019, Lifelines: The Resilient Infrastructure Opportunity, DOI [10.1596/978-1-4648-1430-3, DOI 10.1596/978-1-4648-1430-3]
   ITRC, 2020, UK INFR TRANS CONS
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Oh JE., 2019, ADDRESSING CLIMATE C, DOI [10.1596/32412, DOI 10.1596/32412]
   Pant R., 2018, Transport risk analysis for the United Republic of Tanzania-Systemic vulnerability assessment of multi-modal transport networks
   Pant R., 2020, RESILIENCE STUDY RES
   Pant R, 2019, ARGENTINA TRANSPORT
   Wang GL, 2017, NAT CLIM CHANGE, V7, P268, DOI [10.1038/nclimate3239, 10.1038/NCLIMATE3239]
   Zorn C, 2020, ASCE-ASME J RISK U B, V6, DOI 10.1115/1.4046327
NR 14
TC 0
Z9 0
U1 0
U2 4
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2352-0698
EI 2352-0701
BN 978-3-030-86211-4; 978-3-030-86210-7
J9 SPRINGER CLIMATE
PY 2022
BP 159
EP 167
DI 10.1007/978-3-030-86211-4_19
D2 10.1007/978-3-030-86211-4
PG 9
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Mathematical & Computational Biology
WE Book Citation Index – Science (BKCI-S)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Mathematical & Computational Biology
GA BS9RI
UT WOS:000783726600025
OA hybrid
DA 2025-01-10
ER

PT J
AU Schmitt, KM
   Ontl, TA
   Handler, SD
   Janowiak, MK
   Brandt, LA
   Butler-Leopold, PR
   Shannon, PD
   Peterson, CL
   Swanston, CW
AF Schmitt, Kristen M.
   Ontl, Todd A.
   Handler, Stephen D.
   Janowiak, Maria K.
   Brandt, Leslie A.
   Butler-Leopold, Patricia R.
   Shannon, P. Danielle
   Peterson, Courtney L.
   Swanston, Christopher W.
TI Beyond Planning Tools: Experiential Learning in Climate Adaptation
   Planning and Practices
SO CLIMATE
LA English
DT Article
DE climate change; adaptation planning; natural resources; training;
   climate framework; climate-informed management
ID MANAGEMENT; SCIENCE; VULNERABILITY; STRATEGIES; FRAMEWORK; MIDWEST
AB In the past decade, several dedicated tools have been developed to help natural resources professionals integrate climate science into their planning and implementation; however, it is unclear how often these tools lead to on-the-ground climate adaptation. Here, we describe a training approach that we developed to help managers effectively plan to execute intentional, climate-informed actions. This training approach was developed through the Climate Change Response Framework (CCRF) and uses active and focused work time and peer-to-peer interaction to overcome observed barriers to using adaptation planning tools. We evaluate the effectiveness of this approach by examining participant evaluations and outlining the progress of natural resources projects that have participated in our trainings. We outline a case study that describes how this training approach can lead to place and context-based climate-informed action. Finally, we describe best practices based on our experience for engaging natural resources professionals and helping them increase their comfort with climate-informed planning.
C1 [Schmitt, Kristen M.; Ontl, Todd A.; Butler-Leopold, Patricia R.; Shannon, P. Danielle] Michigan Technol Univ, Coll Forest Resources & Environm Sci, Houghton, MI 49931 USA.
   [Schmitt, Kristen M.; Ontl, Todd A.; Handler, Stephen D.; Janowiak, Maria K.; Brandt, Leslie A.; Butler-Leopold, Patricia R.; Shannon, P. Danielle; Peterson, Courtney L.; Swanston, Christopher W.] Northern Inst Appl Climate Sci, Houghton, MI 49931 USA.
   [Schmitt, Kristen M.; Ontl, Todd A.; Handler, Stephen D.; Janowiak, Maria K.; Brandt, Leslie A.; Butler-Leopold, Patricia R.; Shannon, P. Danielle; Peterson, Courtney L.; Swanston, Christopher W.] USDA, Northern Forests Climate Hub, Houghton, MI 49931 USA.
   [Handler, Stephen D.; Janowiak, Maria K.; Brandt, Leslie A.; Swanston, Christopher W.] US Forest Serv, Northern Res Stn, USDA, Houghton, MI 49931 USA.
   [Peterson, Courtney L.] Colorado State Univ, Forest & Rangeland Stewardship Dept, Ft Collins, CO 80523 USA.
C3 Michigan Technological University; United States Department of
   Agriculture (USDA); United States Department of Agriculture (USDA);
   United States Forest Service; Colorado State University
RP Schmitt, KM (corresponding author), Michigan Technol Univ, Coll Forest Resources & Environm Sci, Houghton, MI 49931 USA.; Schmitt, KM (corresponding author), Northern Inst Appl Climate Sci, Houghton, MI 49931 USA.; Schmitt, KM (corresponding author), USDA, Northern Forests Climate Hub, Houghton, MI 49931 USA.
EM kmschmit@mtu.edu; taontl@mtu.edu; stephen.handler@usda.gov;
   maria.janowiak@usda.gov; leslie.brandt@usda.gov; pleopold@mtu.edu;
   dshannon@mtu.edu; courtney.peterson@colostate.edu;
   christopher.swanston@usda.gov
RI Ontl, Todd/ISA-3527-2023
OI Ontl, Todd/0000-0003-4036-4848; Schmitt, Kristen/0000-0003-2500-9282;
   Swanston, Chris/0000-0003-2167-0970; Peterson,
   Courtney/0000-0003-3335-6604; Leopold, Patricia R./0000-0002-1907-3467
FU American Forests; USDA Forest Service Northern Research Station; USDA
   Climate Hubs
FX We are grateful to American Forests, the USDA Forest Service Northern
   Research Station, and the USDA Climate Hubs for their support of this
   work.
CR Anhalt-Depies CM, 2016, ENVIRON MANAGE, V57, P987, DOI 10.1007/s00267-016-0673-7
   [Anonymous], Climate change response strategy
   [Anonymous], 2016, FOREST ADAPTATION RE, DOI [DOI 10.2737/NRS-GTR-87-2, 10.2737/NRS-GTR-87-2]
   [Anonymous], ADAPTATION WORKBOOK
   [Anonymous], 2018, IMPACTS RISKS ADAPTA, DOI [DOI 10.7930/NCA4.2018, 10.7930/ NCA4.2018, 10.7930/NCA4.2018]
   Beavers R.L., 2016, Coastal Adaptation Strategies Handbook
   Beier P, 2017, CONSERV LETT, V10, P288, DOI 10.1111/conl.12300
   Brandt LA, 2017, J FOREST, V115, P212, DOI 10.5849/jof.15-147
   Climate Change Response Framework, BAY MILLS IND COMM S
   Climate Change Response Framework, POK BAND POT DOW TRE
   Climate Change Response Framework, LITTL TRAV CONS JACK
   Climate Change Response Framework, LEEL CONS PALM WOODS
   Climate Change Response Framework Little Traverse Bay Bands of Odawa Indians, ZIIB FARM
   Cross MS, 2012, ENVIRON MANAGE, V50, P341, DOI 10.1007/s00267-012-9893-7
   Hall JA, 2010, CONSERV BIOL, V24, P120, DOI 10.1111/j.1523-1739.2009.01297.x
   HALOFSKY JE, 2014, US FOR SERV ROCKY MT, V71, P229
   Halofsky JE, 2016, ATMOSPHERE-BASEL, V7, DOI 10.3390/atmos7030046
   Janowiak M., 2020, Moving the needle: A review of needs to increase climate adaptation in the forests of New England, P1
   Janowiak M., 2016, ADAPTATION RESOURCES, V1, P70
   Janowiak M.K., 2011, SILVICULTURAL DECISI, P1, DOI [10.2737/NRS-GTR-81, DOI 10.2737/NRS-GTR-81]
   Janowiak MK, 2014, J FOREST, V112, P424, DOI 10.5849/jof.13-094
   Kershner J., 2020, Integrating climate change considerations into natural resource planning-An implementation guide: U.S. Geological Survey Techniques and Methods, P1, DOI DOI 10.3133/TM6C2
   Kirchhoff CJ, 2015, CLIM RISK MANAG, V9, P20, DOI 10.1016/j.crm.2015.04.001
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   National Fish Wildlife and Plants Climate Adaptation Partnership., 2012, NAT FISH WILDL PLANT, DOI [10.3996/082012-FWSReport-1, DOI 10.3996/082012-FWSREPORT-1]
   O'Toole D, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11247030
   Ontl TA, 2020, J FOREST, V118, P86, DOI 10.1093/jofore/fvz062
   Ontl TA, 2018, CLIMATIC CHANGE, V146, P75, DOI 10.1007/s10584-017-1983-3
   Rowland E., 2016, RESOURCE REPORT NPSN, V1, P44
   Rumore D, 2016, NAT CLIM CHANGE, V6, P745, DOI 10.1038/NCLIMATE3084
   Schuurman G.W., 2020, Resist-accept-direct (RAD)-A framework for the 21st-century natural resource manager, P1
   Shannon PD, 2019, CLIM SERV, V13, P51, DOI 10.1016/j.cliser.2019.01.005
   St-Laurent GP, 2021, COMMUN BIOL, V4, DOI 10.1038/s42003-020-01556-2
   Staffen A., 2019, CLIMATE ADAPTATION S, P1
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Stein B A., 2019, Climate Adaptation for DoD Natural Resource Managers
   Stern Marc J. J., 2020, CLIM AD WORKSH DELPH
   Swanston C., 2012, FOREST ADAPTATION RE, P1, DOI [10.2737/NRS-GTR-87, DOI 10.2737/NRS-GTR-87]
   Swanston C.W., 2020, CACH20201 USDA CAL C
   Swanston C, 2018, CLIMATIC CHANGE, V146, P103, DOI 10.1007/s10584-017-2065-2
   Tingley RW, 2019, LAKE RESERV MANAGE, V35, P435, DOI 10.1080/10402381.2019.1678535
   Tribal Adaptation Menu Team, 2019, DIB AN EZH TRIB CLIM, P2
   Wisconsin Initiative on Climate Change Impacts Plants and Natural Communities Working Group, CLIMATE CHANGE VULNE
   Woodru SC, 2016, NAT CLIM CHANGE, V6, P796, DOI 10.1038/NCLIMATE3012
NR 44
TC 8
Z9 8
U1 1
U2 8
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2225-1154
J9 CLIMATE
JI Climate
PD MAY
PY 2021
VL 9
IS 5
AR 76
DI 10.3390/cli9050076
PG 16
WC Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Meteorology & Atmospheric Sciences
GA SH1LT
UT WOS:000653898000001
OA gold
DA 2025-01-10
ER

PT J
AU Arheimer, B
   Donnelly, C
   Lindström, G
AF Arheimer, B.
   Donnelly, C.
   Lindstrom, G.
TI Regulation of snow-fed rivers affects flow regimes more than climate
   change
SO NATURE COMMUNICATIONS
LA English
DT Article
ID GLOBAL CLIMATE; CHANGE IMPACT; WATER; HYDROLOGY; MODEL; FRAGMENTATION;
   PRECIPITATION; BIODIVERSITY; VARIABILITY; PREDICTIONS
AB River flow is mainly controlled by climate, physiography and regulations, but their relative importance over large landmasses is poorly understood. Here we show from computational modelling that hydropower regulation is a key driver of flow regime change in snow-dominated regions and is more important than future climate changes. This implies that climate adaptation needs to include regulation schemes. The natural river regime in snowy regions has low flow when snow is stored and a pronounced peak flow when snow is melting. Global warming and hydropower regulation change this temporal pattern similarly, causing less difference in river flow between seasons. We conclude that in snow-fed rivers globally, the future climate change impact on flow regime is minor compared to regulation downstream of large reservoirs, and of similar magnitude over large landmasses. Our study not only highlights the impact of hydropower production but also that river regulation could be turned into a measure for climate adaptation to maintain biodiversity on floodplains under climate change.
C1 [Arheimer, B.; Donnelly, C.; Lindstrom, G.] SMHI, S-60176 Norrkoping, Sweden.
C3 Swedish Meteorological & Hydrological Institute
RP Arheimer, B (corresponding author), SMHI, S-60176 Norrkoping, Sweden.
EM berit.arheimer@smhi.se
OI Arheimer, Berit/0000-0001-8314-0735; Donnelly,
   Chantal/0000-0002-0086-4453
FU EU FP7 [603587]; Knowledge Center for Climate Change Adaptation at SMHI;
   Swedish Agency for Marine and Water Management (HaV)
FX The study was performed within the EU FP7-funded project SWITCH-ON
   (grant agreement 603587), which explores the untapped potential of Open
   Data to tackle changes in the Hydrosphere. Modelling of climate-change
   impact in Sweden was funded by the Knowledge Center for Climate Change
   Adaptation at SMHI and we would like to acknowledge contributions from
   Elin Sjoqvist and Jenny Axen-Martensson at SMHI for this part. Modelling
   of the hydropower influence was funded by the Swedish Agency for Marine
   and Water Management (HaV) and we would like to acknowledge valuable
   data of Dalalven River from Niclas Hjerdt, SMHI. The investigation was
   performed at the SMHI Hydrological Research unit, where much work
   benefits from joint efforts in developing models and concepts by the
   whole team. The scientific findings will contribute to the decadal
   research initiative "Panta Rhei-changes in hydrology and society" by the
   International Association of Hydrological Sciences (IAHS).
CR Adam JC, 2009, HYDROL PROCESS, V23, P962, DOI 10.1002/hyp.7201
   Andersson E, 2000, REGUL RIVER, V16, P83, DOI 10.1002/(SICI)1099-1646(200001/02)16:1<83::AID-RRR567>3.0.CO;2-T
   Andréasson J, 2004, AMBIO, V33, P228, DOI 10.1579/0044-7447-33.4.228
   Arheimer B, 2015, HYDROL EARTH SYST SC, V19, P771, DOI 10.5194/hess-19-771-2015
   Arheimer B., 2017, HYDROPOWER IMPACT RI
   Arheimer B., 2017, CLIMATE IMPACT RIVER
   Arheimer B, 2014, IAHS-AISH P, V364, P313
   Arthington AH, 2010, FRESHWATER BIOL, V55, P1, DOI 10.1111/j.1365-2427.2009.02340.x
   Barnett TP, 2008, SCIENCE, V319, P1080, DOI 10.1126/science.1152538
   Barnett TP, 2005, NATURE, V438, P303, DOI 10.1038/nature04141
   Berg P, 2013, NAT GEOSCI, V6, P181, DOI 10.1038/ngeo1731
   Berghuijs WR, 2014, NAT CLIM CHANGE, V4, P583, DOI [10.1038/nclimate2246, 10.1038/NCLIMATE2246]
   Bergström S, 2001, CLIM RES, V16, P101, DOI 10.3354/cr016101
   Bergstrom S., 2012, 24 ICOLD C KYOT JAP, pQ94
   Bin Ashraf F, 2016, J HYDROL, V542, P410, DOI 10.1016/j.jhydrol.2016.09.016
   Blöschl G, 2007, HYDROL PROCESS, V21, P1241, DOI 10.1002/hyp.6669
   Bunn SE, 2002, ENVIRON MANAGE, V30, P492, DOI 10.1007/s00267-002-2737-0
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   Donnelly C, 2016, HYDROLOG SCI J, V61, P255, DOI 10.1080/02626667.2015.1027710
   Donnelly C, 2014, CLIMATIC CHANGE, V122, P157, DOI 10.1007/s10584-013-0941-y
   DYSENIUS M, 1994, SCIENCE, V266, P753
   Eisner S, 2017, CLIMATIC CHANGE, V141, P401, DOI 10.1007/s10584-016-1844-5
   Falkenmark M, 2008, INT J WATER RESOUR D, V24, P201, DOI 10.1080/07900620701723570
   Fekete BM, 2010, GLOBAL BIOGEOCHEM CY, V24, DOI 10.1029/2009GB003593
   FitzHugh TW, 2011, RIVER RES APPL, V27, P1192, DOI 10.1002/rra.1417
   Godsey SE, 2014, HYDROL PROCESS, V28, P5048, DOI 10.1002/hyp.9943
   Grafton RQ, 2013, NAT CLIM CHANGE, V3, P315, DOI [10.1038/NCLIMATE1746, 10.1038/nclimate1746]
   Grizzetti B, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-00324-3
   Haddeland I, 2014, P NATL ACAD SCI USA, V111, P3251, DOI 10.1073/pnas.1222475110
   Hagemann S, 2013, EARTH SYST DYNAM, V4, P129, DOI 10.5194/esd-4-129-2013
   Hall J, 2014, HYDROL EARTH SYST SC, V18, P2735, DOI 10.5194/hess-18-2735-2014
   Heino J, 2009, BIOL REV, V84, P39, DOI 10.1111/j.1469-185X.2008.00060.x
   Huntington TG, 2006, J HYDROL, V319, P83, DOI 10.1016/j.jhydrol.2005.07.003
   Jager HI, 2008, RIVER RES APPL, V24, P340, DOI 10.1002/rra.1069
   Johansson B., 2002, Estimation of areal precipitation for hydrological modelling in Sweden
   Krasting JP, 2013, J CLIMATE, V26, P7813, DOI 10.1175/JCLI-D-12-00832.1
   Kuentz A, 2017, HYDROL EARTH SYST SC, V21, P2863, DOI 10.5194/hess-21-2863-2017
   Lehner B, 2011, FRONT ECOL ENVIRON, V9, P494, DOI 10.1890/100125
   Leira M, 2008, HYDROBIOLOGIA, V613, P171, DOI 10.1007/s10750-008-9465-2
   Lindström G, 2016, HYDROL RES, V47, P672, DOI 10.2166/nh.2016.019
   Lindström G, 2010, HYDROL RES, V41, P295, DOI 10.2166/nh.2010.007
   Lytle DA, 2004, TRENDS ECOL EVOL, V19, P94, DOI 10.1016/j.tree.2003.10.002
   Merz B, 2012, HYDROL EARTH SYST SC, V16, P1379, DOI 10.5194/hess-16-1379-2012
   Molini A, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL046477
   Montanari A, 2013, HYDROLOG SCI J, V58, P1256, DOI 10.1080/02626667.2013.809088
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   Nilsson C, 2005, SCIENCE, V308, P405, DOI 10.1126/science.1107887
   O'Gorman PA, 2014, NATURE, V512, P416, DOI 10.1038/nature13625
   Palmer MA, 2008, FRONT ECOL ENVIRON, V6, P81, DOI 10.1890/060148
   Palmer MA, 2009, ENVIRON MANAGE, V44, P1053, DOI 10.1007/s00267-009-9329-1
   Pittock J., 2010, Water Alternatives, V3, P444
   Poff NL, 1997, BIOSCIENCE, V47, P769, DOI 10.2307/1313099
   Rheinheimer DE, 2015, RIVER RES APPL, V31, P269, DOI 10.1002/rra.2749
   Rheinheimer DE, 2014, J WATER RES PLAN MAN, V140, P714, DOI 10.1061/(ASCE)WR.1943-5452.0000373
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Samuelsson P, 2011, TELLUS A, V63, P4, DOI 10.1111/j.1600-0870.2010.00478.x
   Sivapalan M, 2012, HYDROL PROCESS, V26, P1270, DOI 10.1002/hyp.8426
   Steffen W, 2007, AMBIO, V36, P614, DOI 10.1579/0044-7447(2007)36[614:TAAHNO]2.0.CO;2
   Stewart IT, 2005, J CLIMATE, V18, P1136, DOI 10.1175/JCLI3321.1
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Strömqvist J, 2012, HYDROLOG SCI J, V57, P229, DOI 10.1080/02626667.2011.637497
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   Vorosmarty CJ, 1997, AMBIO, V26, P210
   Wagener T, 2010, WATER RESOUR RES, V46, DOI 10.1029/2009WR008906
   Weedon GP, 2014, WATER RESOUR RES, V50, P7505, DOI 10.1002/2014WR015638
   Wenger SJ, 2011, P NATL ACAD SCI USA, V108, P14175, DOI 10.1073/pnas.1103097108
   Yang W, 2010, HYDROL RES, V41, P211, DOI 10.2166/nh.2010.004
   Zhang Y, 2012, RIVER RES APPL, V28, P989, DOI 10.1002/rra.1483
NR 68
TC 86
Z9 90
U1 17
U2 76
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
EI 2041-1723
J9 NAT COMMUN
JI Nat. Commun.
PD JUL 5
PY 2017
VL 8
AR 62
DI 10.1038/s41467-017-00092-8
PG 9
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA EZ5SP
UT WOS:000404778800006
PM 28680129
OA Green Published, gold
DA 2025-01-10
ER

EF